da Vinci Surgical System (IS5000)

K251739 · Intuitive Surgical, Inc. · NAY · Jan 16, 2026 · Gastroenterology, Urology

Device Facts

• Record ID: K251739
• Device Name: da Vinci Surgical System (IS5000)
• Applicant: Intuitive Surgical, Inc.
• Product Code: NAY · Gastroenterology, Urology
• Decision Date: Jan 16, 2026
• Decision: SESE
• Submission Type: Traditional
• Regulation: 21 CFR 876.1500
• Device Class: Class 2
• Attributes: Therapeutic, Real-World Evidence

Real-World Evidence

Submission	Device	Sponsor	RWD Sources	RWE Use Summary	Key Tags
K251739 · Jan 16, 2026	da Vinci Surgical System (IS5000)	Intuitive Surgical, Inc.	Premier Healthcare Database	A retrospective propensity score matched analysis of robotic vs. non-robotic mitral valve repair and CABG procedures performed in the U.S. between 2016 and 2023 to support substantial equivalence.	Retrospective cohort study; Propensity score matching; Mitral valve repair; CABG; Clinical outcomes

Clinical Evidence

Study Design	Population	Comparator	Key Endpoints
Retrospective cohort study using the Premier Healthcare Database; Retrospective cohort study with propensity score matched analysis; Follow-up/Duration: 2016-2023; Study Period: 2016-2023	Patients undergoing robotic or non-robotic mitral valve repair and CABG procedures in the United States; Sample Size: 1,507 robotic and 1,507 non-robotic mitral valve repair procedures; 3,893 robotic and 3,893 non-robotic CABG procedures	Non-robotic mitral valve repair and non-robotic CABG procedures	Operating time, length of hospital stay, ICU length of stay, blood transfusion, mortality, readmission, reoperation, and various postoperative complications

Indications for Use

The Intuitive Surgical Endoscopic Instrument Control System (da Vinci Surgical System, Model IS5000) shall assist in the accurate control of Intuitive Surgical Endoscopic Instruments including rigid endoscopes, blunt and sharp endoscopic dissectors, scissors, scalpels, forceps/pick-ups, needle holders, endoscopic retractors, electrocautery and accessories for endoscopic manipulation of tissue, including grasping, cutting, blunt and sharp dissection, approximation, ligation, electrocautery, suturing, and delivery and placement of microwave and cryogenic ablation probes and accessories, during urologic surgical procedures, general laparoscopic surgical procedures, gynecologic laparoscopic surgical procedures, and general thoracoscopic surgical procedures. The system is also indicated for selected thoracoscopically-assisted cardiac surgical procedures using the non-force feedback instruments. The system is indicated for adult use. It is intended to be used by trained physicians in an operating room environment in accordance with the representative specific procedures set forth in the Professional Instructions for Use.

Device Story

The da Vinci Surgical System (IS5000) is a computer-controlled, electromechanical system for minimally invasive surgery. It comprises a Surgeon Side Console, Patient Side Cart (Robot), and Vision System Cart. Surgeons operate the system in an OR environment, using the console to control endoscopic instruments (e.g., dissectors, scissors, needle holders) attached to the robot. The system translates surgeon hand movements into precise instrument actions, facilitating tissue manipulation, suturing, and ablation. This 510(k) update enables compatibility with specific cardiac instruments (Atrial Retractor Short Right, Cardiac Probe Grasper) and expands indications to include selected thoracoscopically-assisted cardiac procedures (e.g., mitral valve repair, IMA mobilization, ASD repair). The system provides surgeons with enhanced visualization and control, potentially reducing surgical trauma and improving patient outcomes compared to traditional approaches. Clinical evidence, including systematic literature reviews and real-world data, supports the safety and efficacy of the system for these cardiac interventions.

Clinical Evidence

Evidence includes systematic literature reviews and a retrospective cohort study using the Premier Healthcare Database (2016-2023). The database study compared 1,507 robotic vs. 1,507 non-robotic mitral valve repairs and 3,893 robotic vs. 3,893 non-robotic CABG procedures. Results indicate robotic-assisted procedures are substantially equivalent to non-robotic approaches in primary and secondary surgical outcomes. Literature reviews across various cardiac procedures (mitral valve repair, CABG, ASD repair, etc.) support safety and efficacy.

Technological Characteristics

Electromechanical, software-controlled system. Components: Surgeon Console, Patient Side Cart, Vision Cart. Connectivity: Networked system. Sterilization: Compatible with standard endoscopic instrument sterilization. Software: Updated to support specific cardiac instruments. No changes to core operational principles.

Indications for Use

Indicated for adult patients undergoing urologic, general laparoscopic, gynecologic laparoscopic, general thoracoscopic, and selected thoracoscopically-assisted cardiac surgical procedures. Contraindicated for use of force feedback needle driver in hysterectomy and myomectomy due to risk of vaginal bleeding.

Regulatory Classification

Identification

An endoscope and accessories is a device used to provide access, illumination, and allow observation or manipulation of body cavities, hollow organs, and canals. The device consists of various rigid or flexible instruments that are inserted into body spaces and may include an optical system for conveying an image to the user's eye and their accessories may assist in gaining access or increase the versatility and augment the capabilities of the devices. Examples of devices that are within this generic type of device include cleaning accessories for endoscopes, photographic accessories for endoscopes, nonpowered anoscopes, binolcular attachments for endoscopes, pocket battery boxes, flexible or rigid choledochoscopes, colonoscopes, diagnostic cystoscopes, cystourethroscopes, enteroscopes, esophagogastroduodenoscopes, rigid esophagoscopes, fiberoptic illuminators for endoscopes, incandescent endoscope lamps, biliary pancreatoscopes, proctoscopes, resectoscopes, nephroscopes, sigmoidoscopes, ureteroscopes, urethroscopes, endomagnetic retrievers, cytology brushes for endoscopes, and lubricating jelly for transurethral surgical instruments. This section does not apply to endoscopes that have specialized uses in other medical specialty areas and that are covered by classification regulations in other parts of the device classification regulations.

Special Controls

*Classification* —(1)*Class II (special controls).* The device, when it is an endoscope disinfectant basin, which consists solely of a container that holds disinfectant and endoscopes and accessories; an endoscopic magnetic retriever intended for single use; sterile scissors for cystoscope intended for single use; a disposable, non-powered endoscopic grasping/cutting instrument intended for single use; a diagnostic incandescent light source; a fiberoptic photographic light source; a routine fiberoptic light source; an endoscopic sponge carrier; a xenon arc endoscope light source; an endoscope transformer; an LED light source; or a gastroenterology-urology endoscopic guidewire, is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 876.9.(2) Class I for the photographic accessories for endoscope, miscellaneous bulb adapter for endoscope, binocular attachment for endoscope, eyepiece attachment for prescription lens, teaching attachment, inflation bulb, measuring device for panendoscope, photographic equipment for physiologic function monitor, special lens instrument for endoscope, smoke removal tube, rechargeable battery box, pocket battery box, bite block for endoscope, and cleaning brush for endoscope. The devices subject to this paragraph (b)(2) are exempt from the premarket notification procedures in subpart E of part 807of this chapter, subject to the limitations in § 876.9.

In combination with the general controls of the FD&C Act, the integrated operating table-electromechanical surgical system is subject to the following special controls: 1. (1) Premarket clinical performance testing, or a combination of premarket clinical performance testing and postmarket surveillance (in accordance with special control (2)), must include the following: 1. (i) Objective performance measures (e.g., rate and number of conversions to other surgical modalities, rate of device related adverse events (including tissue injury, hematoma, and increased blood loss), and their severity, cause, and outcomes) must be reported with relevant descriptive comparator performance measures. 2. (ii) The data must demonstrate the performance of the device for providing accurate and precise control of attached surgical instruments in range of clinical conditions relevant to the device's intended use. 3. (iii) The test dataset must include data collected from a patient population representative of the intended patient population under anticipated conditions of use. 2. (2) Data obtained from postmarket surveillance must demonstrate, in consideration of the premarket data obtained in accordance with special control (1), that the device performs in accordance with special control (1), unless FDA determines, based on the totality of the premarket data, that data from postmarket surveillance is not required to demonstrate that the device performs as intended. Such postmarket surveillance must be conducted per a protocol determined appropriate by FDA to demonstrate that the device performs as intended (in consideration of the premarket data obtained in accordance with special control (1)), and must include initiation, enrollment, and reporting requirements to ensure timely periodic updates to FDA on post-market surveillance progress and outcomes. 3. (3) Animal performance testing must evaluate the extent of port site trauma due to repositioning of table during surgical procedures when utilizing robotic minimally invasive and laparoscopic approaches 4. (4) The device manufacturer must develop, and update as necessary, a device-specific use training program that ensures proper device setup/use/shutdown, accurate control of instruments to perform the intended surgical procedures, troubleshooting and handling during unexpected events or emergencies, and safe practices to mitigate use error. 5. (5) The device manufacturer may only distribute the device to facilities that implement and maintain the device-specific use training program and ensure that users of the device have completed the device-specific use training program. (6) Human factors assessment must demonstrate that the user can correctly use the device system across all intended use environments with the provided instructions and training materials, including patient access during normal operating conditions and emergency situations, and effects arising from the integrated nature of the operating table and robotic surgical arms. (7) Labeling must include: (i) A detailed summary of clinical performance testing conducted with the device, including study population, results, adverse events, and comparisons to any comparator groups identified; (ii) A statement in the labeling that the safety and effectiveness for the representative specific procedures was based on evaluation of the device as a surgical tool and did not include evaluation of outcomes related to the treatment of the patient's underlying disease or condition, unless FDA determines that it can be removed or modified based on clinical performance data submitted to FDA; (iii) Identification of compatible devices; (iv) The list of surgical procedures for which the device has been determined to be safe with clinical justification; (v) Reprocessing instructions for reusable components; (vi) A shelf life for any sterile components; (vii) A description of the device-specific use training program; (viii) A statement that the device is only for distribution to facilities that implement and maintain the device-specific use training program and ensure that users of the device have completed the device-specific use training program; and (ix) A summary of any completed postmarket surveillance data collected as required by special control (2), including updated labeling to accurately reflect outcomes observed in postmarket surveillance. (8) Non-clinical performance testing must demonstrate that the device performs as intended under anticipated conditions of use and must include: (i) Device motion accuracy and repeatability; (ii) System testing; (iii) Instrument reliability; (iv) Crosstalk; (v) Table motion control; (vi) Thermal effects on tissue; (vii) User-device interface performance; (viii) Workspace access testing; and (ix) Performance testing with compatible devices. (9) Software verification, validation, and hazard analysis must be performed. (10) Electromagnetic compatibility and electrical, thermal, and mechanical safety testing must be performed. (11) Performance data must demonstrate the sterility of all patient-contacting device components. (12) Performance data must support the shelf life of the device components provided sterile by demonstrating continued sterility and package integrity over the labeled shelf life. (13) Performance data must validate the reprocessing instructions for the reusable components of the device. (14) Performance data must demonstrate that all patient-contacting components of the device are biocompatible. (15) Performance data must demonstrate that all patient-contacting components of the device are non-pyrogenic. (16) The device manufacturer must submit a report to the FDA annually on the anniversary of initial marketing authorization for the device, until such time as FDA may terminate such reporting, which comprises the following information: (i) Cumulative summary, by year, of complaints and adverse events since date of initial marketing authorization; and (ii) Identification and rationale for changes made to the device, labeling, or device specific use training program, which did not require submission of a premarket notification during the reporting period.

Predicate Devices

• da Vinci Surgical System (IS5000) (K232610)

Reference Devices

• da Vinci Xi Surgical System (IS4000) (K131861)

Submission Summary (Full Text)

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FDA U.S. FOOD & DRUG ADMINISTRATION

January 16, 2026

Intuitive Surgical, Inc.
Emily Hovick
Sr. Regulatory Affairs Specialist
1266 Kifer Road
Sunnyvale, California 94086

Re: K251739
Trade/Device Name: da Vinci Surgical System (IS5000)
Regulation Number: 21 CFR 876.1500
Regulation Name: Endoscope And Accessories
Regulatory Class: Class II
Product Code: NAY
Dated: December 18, 2025
Received: December 19, 2025

Dear Emily Hovick:

We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (the Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.

If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.

U.S. Food & Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993
www.fda.gov

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K251739 - Emily Hovick
Page 2

Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).

Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).

Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting (reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reporting-combination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.

All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/unique-device-identification-system-udi-system.

Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-devices/medical-device-safety/medical-device-reporting-mdr-how-report-medical-device-problems.

For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-

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K251739 - Emily Hovick
Page 3

assistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email ([e-mail]) or phone [phone] or 301-796-7100).

Sincerely,

Mark
Trumbore-S
Digitally signed by
Mark Trumbore-S
Date: 2026.01.16
11:21:00 -05'00'

Mark Trumbore Ph.D.
Assistant Director
DHT4A: Division of General Surgery Devices
OHT4: Office of Surgical and
Infection Control Devices
Office of Product Evaluation and Quality
Center for Devices and Radiological Health

Enclosure

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FORM FDA 3881 (6/20)
Page 1 of 1
PSC Publishing Services [phone]
EF

| DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration Indications for Use | Form Approved: OMB No. 0910-0120 Expiration Date: 06/30/2023 See PRA Statement below. |
| --- | --- |
| 510(k) Number (if known) K251739 | |
| Device Name da Vinci Surgical System (IS5000) | |
| Indications for Use (Describe) The Intuitive Surgical Endoscopic Instrument Control System (da Vinci Surgical System, Model IS5000) shall assist in the accurate control of Intuitive Surgical Endoscopic Instruments including rigid endoscopes, blunt and sharp endoscopic dissectors, scissors, scalpels, forceps/pick-ups, needle holders, endoscopic retractors, electrocautery and accessories for endoscopic manipulation of tissue, including grasping, cutting, blunt and sharp dissection, approximation, ligation, electrocautery, suturing, and delivery and placement of microwave and cryogenic ablation probes and accessories, during urologic surgical procedures, general laparoscopic surgical procedures, gynecologic laparoscopic surgical procedures, and general thoracoscopic surgical procedures. The system is also indicated for selected thoracoscopically-assisted cardiac surgical procedures using the non-force feedback instruments. The system is indicated for adult use. It is intended to be used by trained physicians in an operating room environment in accordance with the representative specific procedures set forth in the Professional Instructions for Use. Contraindication: Use of the force feedback needle driver is contraindicated in hysterectomy and myomectomy due to the risk of vaginal bleeding requiring hospital readmission and/or the need for additional procedures. The use of non-force feedback needle drivers is recommended for suturing in these procedures. | |
| Type of Use (Select one or both, as applicable) ☑ Prescription Use (Part 21 CFR 801 Subpart D) ☐ Over-The-Counter Use (21 CFR 801 Subpart C) | |
| CONTINUE ON A SEPARATE PAGE IF NEEDED. | |
| This section applies only to requirements of the Paperwork Reduction Act of 1995. *DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.* | |
| The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to: Department of Health and Human Services Food and Drug Administration Office of Chief Information Officer Paperwork Reduction Act (PRA) Staff [e-mail] "An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number." | |

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da Vinci Surgical System (IS5000)
510(k) Summary
Page 1 of 28

# 510(k) Summary (21 CFR § 807.92(c))

## I. Submitter Information

510(k) Owner:
Intuitive Surgical
1266 Kifer Road
Sunnyvale, CA 94085

Contact Person:
Emily Hovick
Senior Regulatory Affairs Specialist
Phone: [phone]
Email: [e-mail]

Date Summary Prepared:
January 16, 2026

## II. Subject Device Information

Trade Name:
da Vinci Surgical System (IS5000)

Common Name:
System, surgical, computer-controlled instrument

Classification:
Class II

Regulation:
21 CFR § 876.1500, Endoscope and Accessories

Product Code:
NAY

## III. Predicate Device Information

Predicate Device:
da Vinci Surgical System (IS5000), K232610

Reference Device:
da Vinci Xi Surgical System (IS4000), K131861

## IV. Device Description

The da Vinci Surgical System (IS5000) is a software-controlled, electromechanical system designed for surgeons to perform minimally invasive surgery. It consists of a Surgeon Side Console (Console), a Patient Side Cart (Robot), and a Vision System Cart (Tower) and is used with an Endoscope, EndoWrist Instruments, and Accessories.

## V. Indications for Use

The Intuitive Surgical Endoscopic Instrument Control System (da Vinci Surgical System, Model IS5000) shall assist in the accurate control of Intuitive Surgical Endoscopic Instruments including rigid endoscopes, blunt and sharp endoscopic dissectors, scissors, scalpels, forceps/pick-ups, needle holders, endoscopic retractors, electrocautery and accessories for endoscopic manipulation of tissue, including grasping, cutting, blunt and sharp dissection, approximation, ligation, electrocautery, suturing, and delivery and placement of microwave and cryogenic ablation probes and accessories, during urologic surgical procedures, general laparoscopic surgical procedures, gynecologic laparoscopic surgical procedures, and general thoracoscopic surgical procedures. The system is also indicated for selected thoracoscopically-assisted cardiac surgical procedures using the non-force feedback instruments. The system is indicated for adult use.

It is intended to be used by trained physicians in an operating room environment in accordance with the representative specific procedures set forth in the Professional Instructions for Use.

INTUITIVE

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da Vinci Surgical System (IS5000)
510(k) Summary
Page 2 of 28

Contraindication: Use of the force feedback needle driver is contraindicated in hysterectomy and myomectomy due to the risk of vaginal bleeding requiring hospital readmission and/or the need for additional procedures. The use of non-force feedback needle drivers is recommended for suturing in these procedures.

## VI. Technological Characteristics

The da Vinci Surgical System (IS5000) is technologically equivalent to the predicate device, with no changes to its operational principles. This 510(k) pertains exclusively to software and labeling modifications which include the following:

- Instrument compatibility:
- Atrial Retractor Short Right (PN 470246)
- Cardiac Probe Grasper (PN 470215)

- Revised indications for use to include:
"The system is also indicated for selected thoracoscopically-assisted cardiac surgical procedures using the non-force feedback instruments."

- Addition of specific, representative uses:
- Mitral valve repair
- IMA mobilization for cardiac revascularization
- Patent foramen ovale closure
- Atrial septal defect repair
- Left atrial appendage closure/occlusion
- Atrial myxoma excision
- Mitral valve replacement
- Tricuspid valve repair
- Epicardial pacing lead placement

## VII. Performance Data

### Software Testing

Software verification and validation have been conducted at the unit, integration, and system level to confirm that the subject device continues to meet design requirements and user needs. Software documentation has been provided in accordance with FDA Guidance, "Content of Premarket Submissions for Device Software Functions," issued on June 14, 2023.

### Cadaver and Animal Non-Clinical Testing

Equivalence studies were conducted to compare the surgical performance and safety of the da Vinci Surgical System (IS5000) to the reference da Vinci Xi Surgical System (IS4000) during mitral valve repair and IMA mobilization for cardiac revascularization procedures. The studies involved testing in both cadaveric and live canine models.

### Systematic Literature Reviews

Systematic literature reviews were conducted to evaluate clinical outcomes of robotic-assisted procedures performed with a da Vinci Surgical System, including mitral valve repair, coronary artery bypass grafting (CABG), atrial septal defect repair, left atrial appendage closure/occlusion, patent foramen ovale closure, atrial myxoma excision, mitral valve replacement, and tricuspid valve repair.

## INTUITIVE

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da Vinci Surgical System (IS5000)
510(k) Summary
Page 3 of 28

Findings from these systematic literature reviews demonstrate that the clinical outcomes of robotic-assisted procedures performed with the da Vinci Surgical System are comparable to those of traditional non-robotic approaches, supporting their efficacy and safety across a range of cardiac interventions. Summary data are presented in Table 1 through Table 10.

## Real World Data from the Premier Health Database

A retrospective cohort study using the Premier Healthcare Database compared clinical outcomes of robotic and non-robotic mitral valve repair and CABG performed in the United States between 2016 and 2023. The propensity score matched analysis included 1,507 robotic mitral valve repair procedures and 1,507 non-robotic mitral valve repair procedures and 3,893 robotic CABG procedures and 3,893 non-robotic CABG procedures. Results indicate that robotic mitral valve repair and CABG are substantially equivalent to non-robotic procedures. Primary and secondary surgical outcomes are presented in Table 11 through Table 16.

## VIII. Conclusion

The subject da Vinci Surgical System (IS5000) has the same intended use as the predicate device, with the addition of more specific indications for use, which includes selected thoracoscopically-assisted cardiac surgical procedures, with new specific, representative uses defined in the Professional Instructions for Use. Additionally, the IS5000 system has the same technological characteristics other than a minor software update to enable compatibility with two existing 510(k)-cleared cardiac instruments.

Performance data confirmed that these software and labeling modifications do not raise new or different questions of safety or effectiveness. Therefore, the subject da Vinci Surgical System (IS5000) is substantially equivalent to the cleared predicate device.

INTUITIVE

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da Vinci Surgical System (IS5000)

Traditional 510(k)

Table 1: da Vinci vs. Mini-thoracotomy or Sternotomy MVr Procedure Main Clinical Outcomes

| Author / Year | Study Arms | Study Size (N) | Operating time (minutes) | Conversion to sternotomy (%) | Blood transfusion (%) | Number of transfused units (N) | ICU LOS (hours) | Readmission to ICU (%) | LOS (days) | Postop. complications 30-d (%) | Mortality 30-day (%) | Readmission 30-d (%) | Reoperation for bleeding 30-d (%) | Reoperation for any reason 30-d (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1. Albano (2024) | Robotic | 98 | Median: 259 | NR | 21 | NR | Median: 41 | NR | Median: 10 | ISI calc. 49 | In-hospital: 0 | NR | 3 | NR |
| | Mini-Thoracotomy | 98 | Median: 235 | | 15 | | Median: 45 | | Median: 11 | ISI calc. 47 | In-hospital: 0 | | 2 | |
| 2. Baccanelli (2024) | Robotic | 111 | NR | In-hospital: 0 | NR | | | | | | | | | |
| | Mini-Thoracotomy | 205 | | | | | | | | | In-hospital: 0 | | | |
| 3. Barac (2021) | Robotic | 128 | NR | 1.6 | NR | 5 | NR | 0 | NR | 3 | NR | | | |
| | Mini-Thoracotomy | 249 | | 1.2 | | | | | | 5 | | 0.4 | 1 | |
| 4. Chemtob (2022) | Robotic | 605 | NR | 0 | 10 | NR | Median: 25 | NR | 5.2 ± 2.9 | NR | In-hospital: 0 | NR | 1.3 | Val. Dysf.: 0.66 |
| | Sternotomy | 395 | | NA | 17 | | Median: 27 | | 5.9 ± 2.3 | | In-hospital: 0 | | 0.51 | Val. Dysf.: 0.25 |
| 5. Coyan (2018) | Robotic | 91 | NR | Median: 27.5 | 3.3 | Median: 5 | 49.5 | Operative: 0 | 8.8 | 3.3 | Val. Dysf.: 0 | | | |
| | Sternotomy | 91 | | | | | Median: 34.0 | 5.5 | Median: 7 | 53.8 | Operative: 2.2 | 15.4 | 1.1 | Val. Dysf.: 1.1 |
| 6. Fujita (2021) | Robotic | 169 | *MVR (N=118): 201 ± 66 | 1.2 | NR | 1.8d ± 0.9 | NR | 8.1 ± 3.2 | NR | 0 | NR | 1.2 | | |
| | Mini-Thoracotomy | 166 | *MVR (N=142): 228 ± 49 | 0.6 | | | | 1.6d ± 0.8 | | 7.5 ± 1.7 | | | 0 | 0.6 |
| 7. Giroletti (2024) | Robotic | 80 | Median: 255 | NR | 21 | NR | Median: 32 | NR | Median: 10 | NR | In-hospital: 0 | NR | 4 | NR |
| | Mini-Thoracotomy | 80 | Median: 235 | | 15 | | Median: 45 | | Median: 11 | | In-hospital: 0 | | 1 | |
| 8. Hawkins (2018) | Robotic | 295 | Median: 222 | 0 | 15.3 | NR | Median: 26 | NR | Median: 4 | Major: 7.8 | Operative: 0.7 | 10.3 | 2.7 | 5 |
| | Mini-Thoracotomy | 295 | Median: 180 | 0 | 4.8 | | Median: 24 | | Median: 4 | Major: 5.8 | Operative: 0.7 | 6.5 | 1.4 | 2 |
| | Robotic | 314 | Median: 224 | 0 | 15.3 | | Median: 26 | | Median: 4 | Major: 8.6 | Operative: 0.6 | 10.9 | 2.6 | 5 |
| | Sternotomy | 314 | Median: 168 | NA | 17.8 | | Median: 31 | | Median: 5 | Major: 8.9 | Operative: 2.2 | 8.9 | 1.9 | 4 |
| 9. Iyigun (2017) | Robotic | 33 | NR | 5.7 | NR | 1.41 ± 1.93 | 1.15d ± 0.62 | NR | 7.03 ± 2.09 | NR | | | | |
| | Sternotomy | 29 | | NA | | 2.24 ± 1.75 | 1.31d ± 0.6 | | 9.03 ± 2.91 | | | | | |
| 10. Kam (2010) | Robotic | 107 | 238.63 | NR | | | 36.66 | NR | 6.47 | Bleeding: 1.8 | Operative: 0 | NR | | 2 |

#

INTUITIVE

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da Vinci Surgical System (IS5000)

Traditional 510(k)

Page 5 of 28

| Author / Year | Study Arms | Study Size (N) | Operating time (minutes) | Conversion to sternotomy (%) | Blood transfusion (%) | Number of transfused units (N) | ICU LOS (hours) | Readmission to ICU (%) | LOS (days) | Postop. complications 30-d (%) | Mortality 30-day (%) | Readmission 30-d (%) | Reoperation for bleeding 30-d (%) | Reoperation for any reason 30-d (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | Sternotomy | 40 | 201.76 | | | | 45.46 | | 8.76 | Bleeding: 0 | Operative: 0 | | | 0 |
| 11. Kesavuori (2018) | Robotic w/ learning curve | 142 | Median: 254 | 9.2 | NR | ≥2 units: 28.9 | Median: 1d | NR | Median: 7 | NR | 0.7 | NR | 7.7 | ISI calc.: 12.7 |
| Sternotomy | 142 | Median: 217 | NA | ≥2 units: 26.8 | Median: 1d | Median: 7 | 0 | 5.6 | ISI calc.: 7 |
| Robotic w/o learning curve | 112 | Median: 250 | NR | NR | Median: 1d | Median: 7 | NR | NR | NR |
| 12. Mihaljevic (2011) | Robotic | 106 | Median: 387 | NR | 0: 92
1: 2.8
2: 1.9
>3: 2.8 | NR | ISI calc. Median: 4.2 | 8.5 | 0 | NR | 3.8 | NR | | |
| Sternotomy | 106 | ISI calc. Median: 278 | 0: 85
1: 8.5
2: 5.7
>3: 0.94 | ISI calc. Median: 5.2 | 9.4 | 0 | 3.8 | | |
| Robotic | 223 | Median: 387 | 0: 89
1: 4.5
2: 3.1
>3: 3.1 | ISI calc. Median: 4.2 | 11 | 0 | 4.5 | | |
| Partial Sternotomy | 223 | ISI calc. Median: 277 | 0: 91
1: 4.9
2: 4.0
>3: 0.45 | ISI calc. Median: 5.8 | 9.9 | 0 | 4.9 | | |
| Robotic | 113 | Median: 387 | 0: 89
1: 4.4
2: 1.8
>3: 4.4 | ISI calc. Median: 4.2 | 12 | 0 | 6.2 | | |
| Mini-Thoracotomy | 113 | ISI calc. Median: 327 | 0: 95
1: 2.7
2: 0.88
>3: 1.8 | ISI calc. Median: 5.1 | 2.7 | 0 | 18 | | |
| 13. Mori (2024) | Robotic | 5540 | 375 ± 101 | NR | Intraop: 13
Postop: 15 | NR | 48 ± 62 | 1.6 | 5.00 ± 3.59 | In-hospital: 31 | Operative: 0.8 | 6.6 | NR | 3.1 |
| Mini-Thoracotomy | 5540 | 332 ± 88 | Intraop: 12
Postop: 13 | 51 ± 87 | 1.5 | 5.57 ± 3.54 | In-hospital: 34 | Operative: 0.8 | 7.1 | 2.6 |
| Robotic | 6962 | 374 ± 96 | Intraop: 13
Postop: 15 | 46 ± 59 | 1.6 | 4.95 ± 3.47 | NR | Operative: 0.7 | 6.1 | 2.9 |
| Sternotomy | 6962 | 305 ± 81 | Intraop: 17
Postop: 17 | 53 ± 65 | 2 | 6.21 ± 4.07 | Operative: 0.6 | 6.8 | 2.7 |
| 14. Orde (2020) | Robotic | 115 | 3.4 ± 1 | NR | 4.1 ± 2 | NR |
| Sternotomy | 43 | 3.2 ± 1 | 4.4 ± 2 |
| 15. Paul (2015) | Robotic | 631 | NR | Median: 4 | 37.4 | In-hospital: <10 | NR |

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| Author / Year | Study Arms | Study Size (N) | Operating time (minutes) | Conversion to sternotomy (%) | Blood transfusion (%) | Number of transfused units (N) | ICU LOS (hours) | Readmission to ICU (%) | LOS (days) | Postop. complications 30-d (%) | Mortality 30-day (%) | Readmission 30-d (%) | Reoperation for bleeding 30-d (%) | Reoperation for any reason 30-d (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | Sternotomy + Mini-thoracotomy | 631 | | | | | | | Median: 6 | 34.4 | In-hospital: <10 | | | |
| 16. Rao (2022) | Robotic | 62 | NR | 0 | NR | 6.3 ± 0.5 | NR | 0 | ISI calc.: 3.2 | | | | | |
| | Mini-Thoracotomy | 62 | | 0 | | | | | | 6.0 ± 0.3 | 0 | ISI calc.: 4.8 | | |
| 17. Rufa (2023) | Robotic | 52 | NR | 1.9 | NR | Median: 20.5 | NR | Median: 8 | NR | 0 | NR | 1.9 | 3-yr: 0 | |
| | Mini-Thoracotomy | 52 | | 1.9 | | | | Median: 22 | | Median: 9 | | 0 | 5.8 | 3-yr: 1 |
| 18. Seo (2019) | Robotic | 175 | 349 ± 13 | 2.20 | Intraop: 35
Postop: 15 | NR | 84 ± 63 | NR | 6.5 ± 3.2 | 30 | 0.6 | 5 | 2 | Other than for bleeding: 0.6 |
| | Sternotomy | 259 | 312 ± 121 | NA | Intraop: 50
Postop: 27 | | 144 ± 126 | | 9.9 ± 7.2 | 46 | 3 | 14 | 1 | Other than for bleeding: 2 |
| 19. Stevens (2012) | Robotic | 447 | NR | Postop: 18 | NR | MVR*
Median: 4 | NR | 1.1 | 12 | 3 | NR | | | |
| | Mini-Thoracotomy | 481 | | | | | | Postop: 43 | MVR*
Median: 5 | 2.1 | | 11 | 4 | |
| | Sternotomy | 377 | | | | | | Postop: 63 | MVR*
Median: 5 | 3.8 | | 11 | 5 | |
| 20. Suri (2011) | Robotic | 95 | NR | 0 | ISI calc.
Postop: 12.6 | ≥2: 10.53 | 31.29 ± 107.61 | NR | 4.46 ± 6.38 | Any: 6.31
Major: 4.21 | 0 | NR | 1.05 | Failed repair: 0 |
| | Sternotomy | 95 | | NA | ISI calc.
Postop: 18.9 | ≥2: 18.95 | 25.92 ± 20.20 | | 5.34 ± 1.67 | Any: 6.31
Major: 5.26 | 0 | | 2.1 | Failed repair: 1.05 |
| 21. Suri (2013) All | Robotic | 185 | NR | ≥2 RBC: 7 | NR | STS: 3.8 | NR | 0 | Val. Dysf.: 0.5 | | | | | |
| | Sternotomy | 185 | | | | | | | ≥2 RBC: 16.2 | STS: 3.2 | 1.6 | Val. Dysf.: 0.5 | | |
| Pre-July 2009
Post-July 2009 | Robotic | 66 | NR | 24.7 | NR | 4 | NR | Early: 0 | NR | | | | | |
| | Sternotomy | 111 | | | | | | 26.7 | | | | 5.6 | Early: 0 | |
| | Robotic | 119 | | | | | | 13.7 | | | | 3.7 | Early: 0 | |
| | Sternotomy | 74 | | | | | | 27.8 | | | | 5.7 | Early: 0 | |
| 22. Wang (2018) | Robotic | 503 | NR | Intraop: 20.48 | Intraop: 1.84 ± 2.09
Postop: 2.23 ± 2.69 | 41.96 ± 46.91 | NR | 5.26 ± 2.88 | NR | Operative: 0.6
In-hospital: 0.2
30-d: 0.6 | NR | 2.98 | Val. Dysf.: 0 | |
| | Sternotomy | 503 | | | Intraop: 35.19 | Intraop: 1.49 ± 1.43
Postop: 1.86 ± 1.56 | | 61.81 ± 61.40 | | 6.92 ± 3.54 | | Operative: 1.19
In-hospital: 1.19
30-d: 1.4 | 1.99 | Val. Dysf.: 0.4 |

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| Author / Year | Study Arms | Study Size (N) | Operating time (minutes) | Conversion to sternotomy (%) | Blood transfusion (%) | Number of transfused units (N) | ICU LOS (hours) | Readmission to ICU (%) | LOS (days) | Postop. complications 30-d (%) | Mortality 30-day (%) | Readmission 30-d (%) | Reoperation for bleeding 30-d (%) | Reoperation for any reason 30-d (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 23. Watanabe (2024) | Robotic | 577 | Median: 192 | 0.2 | 32.1 | NR | Median: 2d | NR | Median: 8 | NR | 0.2 | NR | 1.2 | NR |
| | Mini-Thoracotomy | 577 | Median: 232 | NR | 44.2 | | Median: 2d | | Median: 9 | | 0 | | 0.9 | |
| 24. Wei (2020) | Robotic | 121 | NR | 0.8 | 64.5 | NR | 3.6d ± 2.7 | NR | 0.8 | NR | 0 | Early failure: 2.5 | | |
| | Mini-Thoracotomy | 113 | | 0 | 52.2 | | 2.8d ± 2.3 | | | | 0.9 | 0.9 | Early failure: 0.9 | |
| 25. Zheng (2022) | Robotic | 69 | NR | 1.4 | 1.4 | NR | Median: 4 | NR | Operative: 0 | 13 | 0 | Val. Dysf.: 0 | | |
| | Mini-Thoracotomy | 69 | | 1.4 | 2.9 | | | | Median: 4 | Operative: 0 | 11.6 | 1.4 | Val. Dysf.: 2.9 | |

* Study reports data for overall cohort and mitral valve repair separately.

Table 2: da Vinci vs. Mini-thoracotomy or Sternotomy MVr Procedure Secondary Clinical Outcomes

| Author | Study Arms | Study Size (N) | CPB time (minutes) | XC time (minutes) | Ventilation time (hours) | Prolonged mechanical ventilation (%) | Pulmonary complications (%) | Atrial fibrillation (%) | MI 30-day (%) | Cardiac arrest 30-day (%) | Stroke 30-day (%) | Renal failure 30-day (%) | Discharge to nursing facility / rehab (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1. Albano (2024) | Robotic | 98 | Median: 165 | Median: 91 | Median: 3 | 9 | NR | 22 | NR | Dialysis: 0 | 10 | | |
| | Mini-Thoracotomy | 98 | Median: 137 | Median: 99 | Median: 6 | 21 | | 12 | | | | Dialysis: 0 | 41 |
| 2. Baccanelli (2024) | Robotic | 111 | NR | | | | | | | | | | |
| | Mini-Thoracotomy | 205 | | | | | | | | | | | |
| 3. Barac (2021) | Robotic | 128 | 275 ± 56 | 152 ± 38 | NR | 21 | NR | 0 | NR | | | | |
| | Mini-Thoracotomy | 249 | 195 ± 56 | 119 ± 36 | | | | | | | 24 | 0 | |
| 4. Chemtob (2022) | Robotic | 605 | 123 ± 33 | 73 ± 20 | NR | New-onset: 25 | NR | 0.5 | 0 | NR | | | |
| | Sternotomy | 395 | 74 ± 25 | 55 ± 19 | | | | | New-onset: 34 | | 1 | 0 | |
| 5. Coyan (2018) | Robotic | 91 | Median: 162 | Median: 108 | Initial Median: 3.9
Total postop Median: 0 | NR | Pulmonary thromboembolism: 0
Pneumonia: 1 | 36.3 | NR | 0 | Permanent: 0 | 0 | NR |
| | Sternotomy | 91 | Median: 124 | Median: 98 | Initial Median: 3.4
Total postopMedian: 3 | | Pulmonary thromboembolism: 0
Pneumonia: 0 | 38.5 | | 2.2 | Permanent: 0 | 1 | |
| 6. Fujita (2021) | Robotic | 169 | MVR* (N=118): 119 ± 51 | MVR* (N=118): 81 ± 35 | NR | 0.6 | NR | 0 | 0.6 | NR | | | |
| | Mini-Thoracotomy | 166 | MVR* (N=142): 121 ± 34 | MVR* (N=142): 84 ± 22 | | | | | 0 | | 0 | 1.2 | |
| | Robotic | 80 | Median: 163 | Median: 89 | Median: 2 | NR | | | | | | | Home: 90 |

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| Author | Study Arms | Study Size (N) | CPB time (minutes) | XC time (minutes) | Ventilation time (hours) | Prolonged mechanical ventilation (%) | Pulmonary complications (%) | Atrial fibrillation (%) | MI 30-day (%) | Cardiac arrest 30-day (%) | Stroke 30-day (%) | Renal failure 30-day (%) | Discharge to nursing facility / rehab (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 7. Giroletti (2024) | Mini-Thoracotomy | 80 | Median: 140 | Median: 100 | Median: 6 | | | | | | | | Home: 63 |
| 8. Hawkins (2018) | Robotic | 295 | Median: 139 | Median: 97 | NR | 3.1 | Pneumonia: 1 | 26.4 | NR | Cardiac arrest: 0.3 | Permanent: 1.4 | 0.3 | Facility: 5.4 |
| | Mini-Thoracotomy | 295 | Median: 130 | Median: 86 | | 3.1 | Pneumonia: 0.3 | 17.6 | | Cardiac arrest: 0 | Permanent: 1 | 0 | Facility: 5.8 |
| | Robotic | 314 | Median: 140 | Median: 97 | | 4.1 | Pneumonia: 1.6 | 24.8 | | Cardiac arrest: 0.3 | Permanent: 1.3 | 0.6 | Facility: 7.0 |
| | Sternotomy | 314 | Median: 112 | Median: 81 | | 5.7 | Pneumonia: 1.6 | 27.7 | | Cardiac arrest: 1 | Permanent: 1 | 0.3 | Facility: 14.8 |
| 9. Iyigun (2017) | Robotic | 33 | 157.92 ± 60.31 | 94.36 ± 45.63 | | | | | | | | | |
| | Sternotomy | 29 | 123.85 ± 50.19 | 83.81 ± 40.82 | | | | | | | | | |
| 10. Kam (2010) | Robotic | 107 | 126.39 | 94.93 | 6.17 (N=87) | | | | | | | | Inpatient rehab: 4.7 |
| | Sternotomy | 40 | 93.72 | 73.14 | 6.61 (N=32) | | | | | | | | Inpatient rehab: 10 |
| 11. Kesavuori (2018) | Robotic with learning curve | 142 | Median: 157 | Median: 104 | Median: 15 | NR | Pneumonia: 3.5 | NR | 0.7 | NR | 0 | Dialysis: 2.1 | NR |
| | Sternotomy | 142 | Median: 112 | Median: 86 | Median: 13 | | Pneumonia: 0 | | 2.1 | | 0.7 | Dialysis: 2.1 | |
| | Robotic w/o learning curve | 112 | Median: 151 | Median: 101 | Median: 14 | | NR | | NR | | NR | NR | |
| 12. Mihaljevic (2011) | Robotic | 106 | Median: 116 | Median: 85 | NR | >24h: 1.9 | Pleural effusion: 0 | 26 | NR | 1.9 | NR | | |
| | Sternotomy | 106 | ISI calc. Median: 74 | ISI calc. Median: 57 | | >24h: 2.8 | Pleural effusion: 8.5 | 30 | | 0.94 | | | |
| | Robotic | 223 | Median: 116 | Median: 85 | | >24h: 4.9 | Pleural effusion: 1.8 | 22 | | 2.7 | | | |
| | Partial Sternotomy | 223 | ISI calc. Median: 76 | ISI calc. Median: 59 | | >24h: 2.2 | Pleural effusion: 8.5 | 35 | | 3.1 | | | |
| | Robotic | 113 | Median: 116 | Median: 85 | | >24h: 3.5 | Pleural effusion: 1.8 | 19 | | 1.8 | | | |
| | Mini-Thoracotomy | 113 | ISI calc. Median: 106 | ISI calc. Median: 66 | | >24h: 0.88 | Pleural effusion: 1.8 | 26 | | 0 | | | |
| 13. Mori (2024) | Robotic | 5540 | 145 ± 57 | 95 ± 37 | 7.7 ± 33.9 | 3.1 | Pneumonia: 0.7 | 22 | NR | Permanent: 1.2 | 0.8 | NR | |
| | Mini-Thoracotomy | 5540 | 136 ± 54 | 94 ± 36 | 8.8 ± 38.8 | 3.1 | Pneumonia: 0.8 | 25 | | Permanent: 1 | 0.6 | | |
| | Robotic | 6962 | 143 ± 55 | 93 ± 36 | 7.4 ± 34.6 | 2.9 | Pneumonia: 0.6 | 22 | | Permanent: 1.1 | 0.7 | | |
| | Sternotomy | 6962 | 104 ± 45 | 79 ± 35 | 9.3 ± 42.6 | 3.2 | Pneumonia: 0.8 | 30 | | Permanent: 1 | 0.7 | | |
| 14. Orde (2020) | Robotic | 115 | 80 ± 22 | 51 ± 17 | 5.5 ± 3 | | | | | | | | |
| | Sternotomy | 43 | 49 ± 20 | 49 ± 19 | 8.5 ± 11 | | | | | | | | |
| 15. Paul (2015) | Robotic | 631 | | | | | 30.6 | | | | 3.5 | NR | Non-routine: 65.1 |

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| Author | Study Arms | Study Size (N) | CPB time (minutes) | XC time (minutes) | Ventilation time (hours) | Prolonged mechanical ventilation (%) | Pulmonary complications (%) | Atrial fibrillation (%) | MI 30-day (%) | Cardiac arrest 30-day (%) | Stroke 30-day (%) | Renal failure 30-day (%) | Discharge to nursing facility / rehab (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | Sternotomy + Mini-thoracotomy | 631 | | | | | 27.1 | | | | 2.4 | | Non-routine: 60.2 |
| 16. Rao (2022) | Robotic | 62 | 148 | 148 ± 37 | NR | 1.6 | NR | 3.2 | 0 | NR | | | |
| | Mini-Thoracotomy | 62 | 133 | 133 ± 42 | | 4.8 | | | | | 4.8 | 0 | |
| 17. Rufa (2023) | Robotic | 52 | Median: 181 | Median: 99 | Median: 6 | NR | Pneumonia: 5.8
Pleural effusion: puncture 9.6, drainage 7.7 | 44.2 | Postop + treated with PCI: 1.9
3-yr: 0 | NR | Postop CVA: 0
3-yr stroke: 0 | 1.9 | NR |
| | Mini-Thoracotomy | 52 | Median: 166 | Median: 101 | Median: 6 | | Pneumonia: 0
Pleural effusion: puncture 7.7, drainage 3.8 | 50 | Postop + treated with PCI: 1.9
3-yr: 0 | | Postop CVA: 1.9
3-yr stroke: 0 | 0 | |
| 18. Seo (2019) | Robotic | 175 | NR | 133 ± 47 | NR | Pneumonia: 1 | 13 | NR | Cardiac arrest: 1 (0.6%) | 1 (0.6%) | 1 (0.6%) | NR | |
| | Sternotomy | 259 | | 115 ± 52 | | | Pneumonia: 1 | | 18 | Cardiac arrest: 8 (3%) | 3 (1%) | | 6 (2%) |
| 19. Stevens (2012) | Robotic | 447 | 164 ± 40 | 125 ± 31 | NR | 28 | NR | 0.7 | NR | | | | |
| | Mini-Thoracotomy | 481 | 141 ± 51 | 87 ± 42 | | | | | | | 20 | 1.2 | |
| | Sternotomy | 377 | 122 ± 51 | 86 ± 34 | | | | | | | 26 | 3.4 | |
| 20. Suri (2011) | Robotic | 95 | 113.32 ± 40.39 | 81.40 ± 28.33 | 14.07 ± 88.92 | >48h: 1.05 | NR | Permanent: 0 | 3.16 | NR | Permanent: 1.05 | 0 | NR |
| | Sternotomy | 95 | 48.22 ± 24.55 | 35.94 ± 19.66 | 8.13 ± 6.25 | >48h: 1.05 | | Permanent: 0 | 0 | | Permanent: 0 | 1.05 | |
| 21. Suri (2013) All Pre-July 2009 Post-July 2009 | Robotic | 185 | NR | >48h: 0.5 | NR | In hospital: 18.4 | 1.1 | NR | 0.50 | 0.50 | NR | | |
| | Sternotomy | 185 | | | | >48h: 0 | In hospital: 30.3 | | 0 | 0 | | 0.50 | |
| | Robotic | 66 | NR | | | | | | | | | | |
| | Sternotomy | 111 | | | | | | | | | | | |
| | Robotic | 119 | | | | | | | | | | | |
| | Sternotomy | 74 | | | | | | | | | | | |
| 22. Wang (2018) | Robotic | 503 | 135.62 ± 52.89 | 90.52 ± 34.53 | NR | 2.58 | Pneumonia: 0.99
Pulm. thromboembolism: 66.67 - corrected to 0.3 | 27.83 | NR | Cardiac arrest: 0.8 | Permanent: 0.99 | 0.8 | NR |
| | Sternotomy | 503 | 109.97 ± 45.94 | 83.85 ± 38.24 | | 4.77 | Pneumonia: 7 (1.39%)
Pulm. thromboembolism: 0 (0%) | 39.76 | | Cardiac arrest: 1.39 | Permanent: 1.79 | 1.79 | |

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| Author | Study Arms | Study Size (N) | CPB.time (minutes) | XC time (minutes) | Ventilation time (hours) | Prolonged mechanical ventilation (%) | Pulmonary complications (%) | Atrial fibrillation (%) | MI 30-day (%) | Cardiac arrest 30-day (%) | Stroke 30-day (%) | Renal failure 30-day (%) | Discharge to nursing facility / rehab (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 23. Watanabe (2024) | Robotic | 577 | Median: 130 | Median: 80 | NR | 0.7 | NR | 5.9 | 0 | NR | 1.2 | 0.2 | NR |
| | Mini-Thoracotomy | 577 | Median: 150 | Median: 103 | | 0.3 | | 5.2 | 0.2 | | 0.7 | 0 | |
| 24. Wei (2020) | Robotic | 121 | 123.8 ± 34.9 | 84.9 ± 24.3 | 14.6 ± 4.4 | NR | Pleural effusion w/ pleurocentesis: 1.7 | NR | | | | | |
| | Mini-Thoracotomy | 113 | 153.2 ± 25.6 | 111.8 ± 23.0 | 10.5 ± 6.6 | | Pleural effusion w/ pleurocentesis: 0.9 | | | | | | |
| 25. Zheng (2022) | Robotic | 69 | Median: 85 | Median: 57 | NR | 1.4 | Pleural effusion requiring drainage: 0 Pneumothorax: 0 Pneumonia: 0 | 24.6 | NR | | | | |
| | Mini-Thoracotomy | 69 | Median: 88 | Median: 47 | | 0 | Pleural effusion requiring drainage: 4.3 Pneumothorax: 2.9 Pneumonia: 1.4 | 34.8 | | | | | |

* Study reports data for overall cohort and mitral valve repair separately

Table 3: da Vinci vs. Non Robotic-Assisted CABG Main Clinical Outcomes

| Author | Study Arms | Study Size (N) | Operating Time (minutes) | Conversion to Sternotomy (%) | Blood Transfusion (%) | Number of Transfused Units (n) | ICU Stay (days) | LOS (days) | Postoperative Complications 30-d (%) | Mortality 30-d (%) | Readmission 30-d (%) | Reoperation for bleeding 30-d (%) | Reoperation for any reason 30-d (%) | Reoperation for revascularization 30-d (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1. Algoet (2024) | Robotic | 54 | 364.0 ± 71.0 | NR | In-hospital: 16.7 | NR | 0.78 ± 1.70 | 6.78 ± 2.4 | NR | 0 | 0 | NR | 3.7 | TVR: 1.9 |
| | Open | 54 | 286.1 ± 45.8 | | In-hospital: 38.9 | | 1.91 ± 1.01 | 8.01 ± 2.5 | | 0 | 0 | | 9.3 | TVR: 1.9 |
| 2. Bachinsky (2012) | Robotic | 25 | 386 ± 49.4 | NR | 12 | 0.24 ± 0.72 | 28.50h ± 13.9h | 5.10 ± 2.8 | NR | 0 | NR | 0 | | |
| | Open | 27 | 261 ± 36.8 | | 67 | 1.78 ± 2 | 57.89h ± 84.7h | 8.19 ± 5.4 | | 4 | | | | 0 |
| 3. Basman (2020) | Robotic | 100 | NR | 0 | NR | 5.7 ± 7.5 | NR | 0 | NR | | | | | |
| | Open | 100 | | NA | | | | 7.5 ± 3.4 | | | | | 0 | |
| 4. Cavallaro (2014) | Robotic | 2582 | NR | 16.4 | NR | 6.3 ± 5.6 | Cardiac: 11.6 | 0.6 | NR | | | | | |
| | Open | 481546 | | | | | 31.3 | 9.0 ± 6.7 | | | | | Cardiac: 10.8 | 1.8 |
| 5. Dokollari (2023) | Robotic | 267 | 5.5h ± 1.1h | NR | Intraop: 3.4 Postop: 15.4 | NR | Median: 31.2h | Median: 5 | NR | 0.4 | 9.0 | 0.8 | NR | PCI: 1.5 |
| | Open | 267 | 6.2h ± 1.4h | | Intraop: 36.7 Postop: 50.2 | | Median: 65.0h | Median: 7 | | 0 | 3.4 | 0.4 | | PCI: 0.8 |
| 6. Ezelsoy (2015) | Robotic | 35 | 186.93 | 0 | NR | 0.23 ± 0.55 | 1.09 ± 0.28 | 6.63 ± 1.03 | NR | 0 | NR | | | |

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| Author | Study Arms | Study Size (N) | Operating Time (minutes) | Conversion to Sternotomy (%) | Blood Transfusion (%) | Number of Transfused Units (n) | ICU Stay (days) | LOS (days) | Postoperative Complications > 30-d (%) | Mortality 30-d (%) | Readmission 30-d (%) | Reoperation for bleeding 30-d (%) | Reoperation for any reason 30-d (%) | Reoperation for revascularization 30-d (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | Open | 35 | NR | NA | | 0.60 ± 0.91 | 1.66 ± 0.97 | 7.80 ± 2.29 | | 0 | | | | |
| 7. Ezelsoy (2016) | Robotic | 50 | NR | 1.3 | 5.62 | NR | 0 | NR | | | | | | |
| | Open | 50 | | | | | 2.1 | | | | | 7.96 | 0 | |
| 8. Giambruno (2018) | Robotic | 144 | NR | 5 | In-hospital: 14 | NR | 1.0 ± 0.8 | 4.5 ± 2.1 | NR | 0 | NR | 2.8 | NR | PCI or CABG: 3.5 |
| | Open | 546 | | NA | In-hospital: 25 | | 1.7 ± 2.3 | 6.7 ± 4.7 | | 1.3 | | 1.7 | | PCI or CABG: 0.6 |
| 9. Gianoli (2024) | Robotic | 79 | NR | 2.5 | RBC: 3.8 | NR | 0.6 ± 0.7 | 4.0 ± 2.0 | NR | 0 | To ICU: 0 | NR | Rethoracotomy: 3.8 | NR |
| | Open (ON) | 158 | | NA | RBC: 4.4 | | 1.0 ± 0.4 | 4.8 ± 2.7 | | 0 | To ICU: 2.5 | | Rethoracotomy: 3.2 | |
| | Robotic | 80 | | 2.5 | RBC: 3.7 | | 0.6 ± 0.7 | 4.0 ± 2.0 | | 0 | To ICU: 0 | | Rethoracotomy: 3.7 | |
| | Open (OFF) | 149 | | NA | RBC: 4.0 | | 1.1 ± 0.7 | 5.3 ± 3.6 | | 0 | To ICU: 2.0 | | Rethoracotomy: 2.0 | |
| 10. Gong (2016) | Robotic | 71 | 220.8 ± 23.1 | 4.2 | 15.5 | NR | 30.6h ± 8.7h | 7.8 ± 3.0 | NR | 0 | NR | 1.4 | NR | |
| | MCAB | 61 | 185.5 ± 49.3 | 3.3 | 18.0 | | 35.2h ± 9.4h | 9.2 ± 3.8 | | 1.6 | | 1.6 | | |
| 11. Hage (2019) | Robotic | 143 | NR | 5 | In-hospital: 15 | NR | 1.0 ± 0.8 | 4.5 ± 2.1 | NR | In-hospital: 0 | NR | 3.5 | NR | PCI or CABG: 3.4 |
| | Open | 201 | | NA | In-hospital: 28 | | 1.8 ± 1.3 | 8.1 ± 5.8 | | In-hospital: 1 | | 1.5 | | PCI or CABG: 0 |
| 12. Halkos (2014) | Robotic | 26 | 210 ± 54 | NR | 30.8 | 0.3 ± 0.8 | 30.4h ± 19.8h | 4.2 ± 1.3 | NR | 0 | NR | 0 | NR | |
| | Open | 28 | 274 ± 79 | | 71.4 | 1.5 ± 1.4 | 35.8h ± 25.7h | 5.6 ± 1.8 | | 0 | | | | 0 |
| 13. Jegaden (2011) | Robotic | 59 | 3.4h ± 0.7h | 0 | NR | 0.96 ± 0.8 | 5.5 ± 1.6 | NR | 1.7 | NR | 8.5 | 6.8 | NR | |
| | Open | 48 | 3.2h ± 0.6h | NA | | | 1.7 ± 2.7 | | 7.0 ± 3.0 | | 0 | 2.0 | | 0 |
| 14. Kiai (2019) | Robotic | 147 | NR | 14 | NR | 1.0 ± 0.8 | 4.5 ± 2.1 | NR | 0 | NR | 2.8 | NR | | |
| | Open | 682 | | | | 25 | 1.7 ± 2.3 | | 6.7 ± 4.7 | | 1.3 | | | 1.7 |
| 15. Kofler (2017) | Robotic | 134 | NR | Median RBC: 0 | 39.0h ± 77.0h | 8.4 ± 4.8 | NR | 0 | NR | 5.2 | NR | | | |
| | Open | 134 | | | | Median RBC: 0 | | 40.8h ± 58.6h | | 7.8 ± 4.3 | | | 1.5 | 2.2 |
| 16. Leyvi (2014) | Robotic | 150 | 3.7h ± 1.1h | 0.67 | Intraop: 6.00 Postop: 10.67 | NR | Median: 6 | 2.67 | 0 | NR | 1.33 | 0 | NR | |
| | Open | 1619 | 4.8h ± 1.2h | NA | Intraop: 20.30 Postop: 21.28 | | | Median: 9 | 11.54 | | 2.04 | 2.72 | | 1.48 |
| 17. Leyvi (2016) | Robotic | 141 | 3.51h ± 0.11h | 1.33 | 12.77% | NR | Median: 31h | Median: 6 | 4.26 | 0 | 8.51 | 1.42 | 0 | NR |
| | Open | 141 | 4.66h ± 0.13h | NA | 34.75% | | Median: 52h | Median: 7 | 13.48 | 1.42 | 4.26 | 3.55 | 0.71 | |

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| Author | Study Arms | Study Size (N) | Operating Time (minutes) | Conversion to Sternotomy (%) | Blood Transfusion (%) | Number of Transfused Units (n) | ICU Stay (days) | LOS (days) | Postoperative Complications > 30-d (%) | Mortality 30-d (%) | Readmission 30-d (%) | Reoperation for bleeding 30-d (%) | Reoperation for any reason 30-d (%) | Reoperation for revascularization 30-d (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 18. Lin (2021) | Robotic | 281 | NR | 5.4 ± 10.8 | 11.2 ± 12.7 | NR | In-hospital: 2.5 | NR | | | | | | |
| | Open | 235 | | | | | 11.4 ± 14.5 | | | | | 17.4 ± 11.9 | In-hospital: 7.3 | |
| 19. Patel (2018) | Robotic | 207 | NR | 0.7 | RBC: 14.0 | NR | 7.1 ± 8.0 | NR | 0.5 | NR | 4.3 | NR | 0.5 | |
| | Open | 207 | | NA | RBC: 28.5 | | | | 8.4 ± 5.7 | | 0.5 | | 3.4 | 1.0 |
| 20. Raad (2016) | Robotic | 142 | NR | 6.0 | NR | 5.0 ± 3.8 | NR | 16 | 0.7 | NR | | | | |
| | Open | 142 | | | | | | | 23 | | | 6.7 ± 3.8 | 15 | 2.1 |
| 21. Spanjersberg (2022) | Robotic | 102 | NR | 8.8 | NR | Median: 5 | NR | 0 | NR | Resternotomy 48h: 2 | | | | |
| | Open | 102 | | | | | | 6.9 | | | | Median: 7 | 0 | Resternotomy 48h: 2 |
| 22. Su (2018) | Robotic | 139 | NR | 0 | NR | Median: 3 | Median: 9 | NR | 1.4 | NR | | | | |
| | Open | 147 | | NA | | | Median: 7 | | Median: 15 | | | | | 10.2 |
| 23. Torregrossa (2022a) Robotic-asst | Robotic | 273 | Median: 6.00h | NR | Intraop: 13.2 Postop: 33.0 | NR | Median: 46.1h | Median: 5 | NR | Operative: 1.47 | 10.3 | 0.73 | NR | 0 |
| | Open | 273 | Median: 5.38h | | Intraop: 32.2 Postop: 54.9 | | Median: 49.8h | Median: 6 | | Operative: 1.47 | 11.4 | 0.37 | | 0.37 |
| 24. Torregrossa (2022b) Robotic hybr | Robotic | 31 | Median: 5.97h | NR | Intraop: 6.5 Postop: 25.8 | NR | Median: 28.1h | Median: 4 | NR | Operative: 3.23 | 12.90 | 0 | NR | 0 |
| | Open | 31 | Median: 5.40h | | Intraop: 19.4 Postop: 54.8 | | Median: 48.9h | Median: 6 | | Operative: 0 | 6.45 | 0 | | 0 |
| 25. Torregrossa (2022c) Hybrid rob | Robotic | 181 | Median: 5.80h | NR | Intraop: 10.5 Postop: 33.7 | NR | Median: 45.3h | Median: 5 | NR | Operative: 1.66 | 11.6 | 1.10 | NR | 0 |
| | Open (ON) | 138 | Median: 6.73h | | Intraop: 82.6 Postop: 63.0 | | Median: 72.6h | Median: 7 | | Operative: 2.17 | 15.2 | 1.45 | | 0 |
| | Open (OFF) | 412 | Median: 5.43h | | Intraop: 35.4 Postop: 60.0 | | Median: 52.2h | Median: 6 | | Operative: 0.73 | 10.4 | 0.49 | | 0.24 |
| 26. Whellan (2016) | Robotic | 9862 | NR | Median: 4 | Major: 10.2 | Operative: 1.2 Discharge: 1.0 | NR | 2.3 | NR | | | | | |
| | Non-Robotic | 95634 9 | | | | | | Median: 5 | | | Major: 13.5 | Operative: 1.5 Discharge: 1.2 | 2.0 | |
| 27. Wu (2019) | Robotic | 22 | 12.7h ± 1.7h | NR | In-hospital PRBC: 2.1 ± 2.0 | 4.8 ± 3.5 | 21.0 ± 8.8 | In-hospital: 18.2 | 0 | NR | | | | |
| | Open | 22 | 8.5h ± 1.5h | | | In-hospital PRBC: 1.4 ± 2.2 | 5.0 ± 3.3 | 24.4 ± 14.0 | In-hospital: 27.8 | | | | | 0 |
| 28. Yasar (2023) | Robotic | 158 | NR | 9.5 | NR | 0 | NR | | | | | | | |
| | MCAB | 116 | | 9.5 | | | | | | | 0.86 | | | |

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| Author | Study Arms | Study Size (N) | Operating Time (minutes) | Conversion to Sternotomy (%) | Blood Transfusion (%) | Number of Transfused Units (n) | ICU Stay (days) | LOS (days) | Postoperative Complications > 30-d (%) | Mortality 30-d (%) | Readmission 30-d (%) | Reoperation for bleeding 30-d (%) | Reoperation for any reason 30-d (%) | Reoperation for revascularization 30-d (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 29. Yokoyama (2021) | Robotic | 7330 | NR | 11.0 | NR | 7.3 ± 6.2 | NR | In-hospital: 1.1 | NR | | | | | |
| | Non-Robotic | 7330 | | | | | | 24.3 | | | | | 9.3 ± 6.6 | In-hospital: 2.1 |
| 30. Yusuf (2024) | Robotic | 104 | NR | 1.92 | NR | 0.69 ± 1.29 | 2.82 ± 0.76 | 4.69 ± 0.93 | NR | Operative: 1.92 | NR | | | |
| | Open | 104 | | NA | | 0.79 ± 1.13 | 3.41 ± 1.27 | 8.01 ± 1.98 | | Operative: 2.88 | | | | |
| 31. Zaouter (2015) | Robotic | 38 | NR | 2.6 | 26 | Median RBC: 2 | Median: 21h | Median: 8 | NR | In-hospital: 0 | NR | 0 | NR | Graft failure: 5 |
| | Open | 33 | | NA | 58 | Median RBC: 2 | Median: 45h | Median: 12 | | In-hospital: 0 | | 0 | | Graft failure: 0 |

Table 4: da Vinci vs. Non Robotic-Assisted CABG Secondary Clinical Outcomes

| Author | Study Arms | Study Size (N) | CPB Time (if on-pump) (min) | XC Time (min) | Ventilation Time (h) | Prolonged Ventilation Time (%) | Atrial Fibrillation (%) | MI 30-d (%) | Angina 30-d (%) | Stroke 30-d (%) | Renal Failure 30-d (%) | Ejection Fraction (%) | MACE (%) | Discharge Location (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1. Algoet (2024) | Robotic | 54 | NR | 31.5 | STEMI: 0 NSTEMI: 0 | NR | 0 | NR | 1.9 | NR | | | | |
| | Open | 54 | | | | | 20.4 | | | | STEMI: 1.9 NSTEMI: 1.9 | 1.9 | 0 | |
| 2. Bachinsky (2012) | Robotic | 25 | NR | 16 | Q-wave: 0 Non-Q-wave: 60 | NR | 0 | NR | | | | | | |
| | Open | 27 | | | | | 30 | | | | | Q-wave: 0 Non-Q-wave: 92 | 0 | |
| 3. Basman (2020) | Robotic | 100 | NR | 0 | NR | 0 | 0 | NR | | | | | | |
| | Open | 100 | | | | | | | | | 0 | 0 | 0 | |
| 4. Cavallaro (2014) | Robotic | 2582 | NR | 0.4 | 6.1 | NR | | | | | | | | |
| | Open | 481546 | | | | | | | | 0.9 | 11.5 | | | |
| 5. Dokollari (2023) | Robotic | 267 | NR | >24h: 1.5 | 17.6 | NR | 0.8 | Renal failure: 0.4 Dialysis: 0 | NR | | | | | |
| | Open | 267 | | | | | | >24h: 5.6 | | | | 30.3 | 0.8 | Renal failure: 1.9 Dialysis: 1.1 |
| 6. Ezelsoy (2015) | Robotic | 35 | NA | NA | 4.69 ± 1.20 | NR | Arrhythmia: 14 | NR | 0 | 62.657 | NR | | | |
| | Open | 35 | 31.49 ± 6.32 | 15.74 ± 4.83 | 5.23 ± 0.97 | | Arrhythmia: 17 | | | | | | 6 | NR |
| 7. Ezelsoy (2016) | Robotic | 50 | NR | 60.78 | NR | | | | | | | | | |
| | Open | 50 | | | | | | | | | | | NR | |

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| Author | Study Arms | Study Size (N) | CPB Time (if on-pump) (min) | XC Time (min) | Ventilation Time (h) | Prolonged Ventilation Time (%) | Atrial Fibrillation (%) | MI 30-d (%) | Angina 30-d (%) | Stroke 30-d (%) | Renal Failure 30-d (%) | Ejection Fraction (%) | MACE (%) | Discharge Location (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 8. Giambruno (2018) | Robotic | 144 | NR | >24h: 0.7 | 12 | 1.4 | NR | 2.1 | Dialysis: 0 | NR | | | | |
| | Open | 546 | | | | >24h: 2.0 | | 15 | 1.1 | | | | 2.4 | Dialysis: 0.4 |
| 9. Gianoli (2024) | Robotic | 79 | 104.0 ± 11.6 | NA | NR | 0 | 11.4 | 0 | NR | Renal failure: 0
Dialysis: 0 | NR | 1.3 | NR | |
| | Open (ON) | 158 | 74.4 ± 26.9 | 47.2 ± 18.3 | | 0.6 | 13.3 | 0.6 | | | | Renal failure: 0.6
Dialysis: 0 | | 1.3 |
| | Robotic | 80 | 104.0 ± 11.6 | NA | | 0 | 11.2 | 0 | | | | Renal failure: 0
Dialysis: 0 | | 1.2 |
| | Open (OFF) | 149 | NA | NA | | 3.3 | 12.1 | 1.3 | | | | Renal failure: 1.3
Dialysis: 0 | | 2.6 |
| 10. Gong (2016) | Robotic | 71 | NR | >12h: 1.4 | Arrhythmia: 2.8 | 1.4 | NR | 1.4 | NR | | | | | |
| | MCAB | 61 | | | | >12h: 4.9 | | | | | | Arrhythmia: 14.7 | 3.3 | 3.3 |
| 11. Hage (2019) | Robotic | 143 | NR | >24h: 0.7 | In-hospital: 12 | In-hospital: 1.4 | NR | In-hospital: 2.1 | Dialysis: 0 | NR | | | | |
| | Open | 201 | | | | >24h: 4.0 | | In-hospital: 19 | In-hospital: 0.5 | | | | In-hospital: 1.0 | Dialysis: 0.5 |
| 12. Halkos (2014) | Robotic | 26 | NR | 4.4 ± 4.5 | >24h: 0 | NR | 0 | NR | 0 | NR | | | | |
| | Open | 28 | | | 15.8 ± 17.6 | | >24h: 10.7 | | 0 | | | | | 0 |
| 13. Jegaden (2011) | Robotic | 59 | NA | NA | 4.6 ± 2.4 | NR | 3.4 | NR | 0 | NR | | | | |
| | Open | 48 | 52 ± 15 | 34 ± 15 | 8.0 ± 4.0 | | | | 2.0 | | | | | 2 |
| 14. Kiai (2019) | Robotic | 147 | NR | 0.7 | NR | 1.4 | NR | 2.13 | Dialysis: 0 | NR | | | | |
| | Open | 682 | | | | 2.0 | | 1.1 | 2.40 | | | | Dialysis: 0.4 | |
| 15. Kofler (2017) | Robotic | 134 | 111.9 ± 99.6 | 68.3 ± 54.1 | 15.5 ± 58.4 | NR | 14.2 | 0 | NR | 0.7 | Dialysis: 2.2 | NR | | |
| | Open | 134 | 66.8 ± 48.5 | 37.9 ± 27.3 | 16.3 ± 37.6 | | 18.5 | 2.2 | | 0 | Dialysis: 1.5 | | | |
| 16. Leyvi (2014) | Robotic | 150 | NR | 0.67 | 12.67 | NR | <24h: 0.67
>24h: 0.67 | Dialysis: 0 | NR | Facility: 16.00 | | | | |
| | Open | 1619 | | | | | | 4.79 | | | 17.84 | <24h: 1.17
>24h: 0.99 | Dialysis: 1.24 | Facility: 25.83 |
| 17. Leyvi (2016) | Robotic | 141 | NR | Q-wave: 0 | NR | Permanent: 0 | Dialysis: 0.71 | NR | Facility: 16.31 | | | | | |
| | Open | 141 | | | | | | | | Q-wave: 0 | Permanent: 1.42 | Dialysis: 0.71 | Facility: 19.15 | |
| 18. Lin (2021) | Robotic | 281 | NR | | | | | | | | | | | |
| | Open | 235 | | | | | | | | | | | | |
| 19. Patel (2018) | Robotic | 207 | NA | NA | NR | >24h: 3.9 | NR | 0 | NR | 0.5 | 0.5 | NR | | |

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| Author | Study Arms | Study Size (N) | CPB Time (if on-pump) (min) | XC Time (min) | Ventilation Time (h) | Prolonged Ventilation Time (%) | Atrial Fibrillation (%) | MI 30-d (%) | Angina 30-d (%) | Stroke 30-d (%) | Renal Failure 30-d (%) | Ejection Fraction (%) | MACE (%) | Discharge Location (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | Open | 207 | 88.7 ±24.6 | 63.1 ±25.0 | | >24h: 3.4 | | 0.5 | | 1.0 | 1.9 | | | |
| 20. Raad (2016) | Robotic | 142 | NR | 7.3 ± 20 | >24h: 3.5 | NR | 0 | Dialysis: 0 | NR | | | | | |
| | Open | 142 | | | 10.5 ± 10 | | | | | | | >24h: 6.3 | 2.8 | Dialysis: 0.4 |
| 21. Spanjersberg (2022) | Robotic | 102 | NR | 19.6 | NR | Home within 5-d: 51 | | | | | | | | |
| | Open | 102 | | | | | | | | | 27.5 | Home within 5-d: 20 | | |
| 22. Su (2018) | Robotic | 139 | NR | | | | | | | | | | | |
| | Open | 147 | | | | | | | | | | | | |
| 23. Torregrossa (2022a) Robotic-asst | Robotic | 273 | NR | >24h: 4.03 | 16.8 | NR | 1.47 | AKI: 1.83
Dialysis: 0.37 | NR | Home: 69.2
Rehab: 30.8 | | | | |
| | Open | 273 | | | | | | >24h: 5.86 | | | 25.6 | 0.37 | AKI: 4.40
Dialysis: 1.83 | Home: 65.6
Rehab: 34.4 |
| 24. Torregrossa (2022b) Robotic hybr | Robotic | 31 | NR | >24h: 0 | 9.68 | NR | 3.23 | AKI: 0
Dialysis: 0 | NR | Home: 77.4
Rehab: 22.6 | | | | |
| | Open | 31 | | | | | | >24h: 3.23 | | | 22.6 | 0 | AKI: 0
Dialysis: 0 | Home: 74.2
Rehab: 25.8 |
| 25. Torregrossa (2022c) Hybrid rob | Robotic | 181 | NR | >24h: 2.21 | 15.5 | NR | 1.10 | AKI: 0.55
Dialysis: 0 | NR | | | | | |
| | Open (ON) | 138 | | | | | | >24h: 16.70 | | | | 29.0 | 1.45 | AKI: 2.17
Dialysis: 0 |
| | Open (OFF) | 412 | | | | | | >24h: 5.58 | | | | 24.5 | 0.24 | AKI: 3.64
Dialysis: 1.46 |
| 26. Whellan (2016) | Robotic | 9862 | Median: 88 | Median: 63 | NR | >24h: 5.6 | NR | 1.1 | NR | Permanent (>24h): 0.5 | 2.2% | NR | | |
| | Non-Robotic | 956349 | Median: 90 | Median: 63 | | >24h: 8.6 | | 0.9 | | Permanent (>24h): 1.1 | 2.9% | | | |
| 27. Wu (2019) | Robotic | 22 | 123.9 ± 96.2 | NR | 2.2d ± 1.8d | NR | In-hospital: 0 | NR | In-hospital: 0 | NR | | | | |
| | Open | 22 | 131.4 ± 59.8 | | 2.3d ± 2.3d | | | | In-hospital: 0 | | | | | In-hospital: 0 |
| 28. Yasar (2023) | Robotic | 158 | 72.1 ± 25.8 | 39.6 ± 19.7 | NR | | | | | | | | | |
| | MCAB | 116 | 135.4 ± 45.2 | 64.2 ± 24.9 | | | | | | | | | | |
| 29. Yokoyama (2021) | Robotic | 7330 | NR | | | | | | | 1.0 | AKI: 12.3
Dialysis: 0.8 | NR | | Routine: 45.0
Nursing |

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| Author | Study Arms | Study Size (N) | CPB Time (if on-pump) (min) | XC Time (min) | Ventilation Time (h) | Prolonged Ventilation Time (%) | Atrial Fibrillation (%) | MI 30-d (%) | Angina 30-d (%) | Stroke 30-d (%) | Renal Failure 30-d (%) | Ejection Fraction (%) | MACE (%) | Discharge Location (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | | | | | | | facility: 13.4 Home: 40.0 | | | | | | | |
| | Non-Robotic | 7330 | | | | | | | | 1.3 | AKI: 15.8 Dialysis: 0.8 | Routine: 39.7 Nursing facility: 22.4 Home: 34.5 | | |
| 30. Yusuf (2024) | Robotic | 104 | NR | 9.42 ± 3.99 | NR | | | | | | | | | |
| | Open | 104 | | | | | | | | | | | | 15.46 ± 10.22 |
| 31. Zaouter (2015) | Robotic | 38 | NR | 18 | 0 | NR | 0 | Renal replacement therapy: 0 | NR | | | | | |
| | Open | 33 | | | | | 9 | 0 | | | | 3 | Renal replacement therapy: 0 | |

Table 5: da Vinci Robotic-Assisted Defect Closure Main Clinical Outcomes

| Cardiac procedure | Author | Study Arms | Study Size (N) | Operating time (minutes) | Conversion to open surgery (%) | Blood transfusion (%) | Number of transfused units, n | ICU LOS (days) | LOS (days) | Postop. complications 30-d (%) | Mortality 30-d (%) | Readmission 30-d (%) | Reoperation for bleeding 30-d (%) | Reoperation for any reason 30-d (%) | Postop. ejection fraction (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| ASD | 1. Liu (2023) Comparative retro. | Robotic | 101 | 190.4 ± 12.68 | NR | 3/101 | NR | 18.2h ± 4.6h | 8 ± 1.9 | NR | 1/101 | NR | 1/100 | NR | |
| | | Sternotomy | 162 | 181.4 ± 12.3 | | 10/162 | | 23.5h ± 5.6h | 10 ± 1.5 | | 0/162 | | 2/162 | | |
| | | p-value R/S | | <0.05 | | <0.05 | | <0.05 | <0.05 | | NS | | NS | | |
| MVr + LAA | 2. Chickwe (2023) Comparative retro. Excluding concomitant cyromaze | MVr + LAA | 431 | NR | Median 5 (IQR 4-6) | NR | 0 | 5.6 | 0.5 | Valve dysfunction: 0 | NR | | | | |
| | | MVr | 333 | | | | | | Median 5 (IQR 4-6.5) | 0.9 | | 3.9 | 3 | Valve dysfunction: 1.2 | |
| | | p-value MVr/MVr+LAA | | | | | | | 0.6 | 0.1 | | 0.29 | 0.008 | 0.04 | |
| Isolated MVr | 13. Chemtob (2022) Comparative pro. | Robotic | 605 | NR | 0 | Postop RBC: 10 | NR | 25 (IQR 21-51) | 5.2 ± 2.9 | NR | In-hospital: 0 | NR | 1.3 | 0.66 | NR |
| | | Sternotomy | 395 | | NA | Postop RBC: 17 | | 27 (IQR: 21-66) | 5.9 ± 2.3 | | In-hospital: 0 | | 0.51 | 0.25 | |
| | | p-value R/S | | | NA | 0.0008 | | 0.001 | <0.0001 | | NA | | 0.2 | 0.4 | |

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| Cardiac procedure | Author | Study Arms | Study Size (N) | Operating time (minutes) | Conversion to open surgery (%) | Blood transfusion (%) | Number of transfused units, n | ICU LOS (days) | LOS (days) | Postop. complications 30-d (%) | Mortality 30-d (%) | Readmission 30-d (%) | Reoperation for bleeding 30-d (%) | Reoperation for any reason 30-d (%) | Postop. ejection fraction (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Isolated MVr | 14. Seo (2019) Comparative retro. | Robotic | 175 | 349 ± 13 | 2.2 | Intraop: 35
Postop: 15 | NR | 84 ± 63 | 6.5 ± 3.2 | 30 | 0.6 | 5 | 2 | Other than bleeding: 0.6 | 54 ± 8 |
| | | Sternotomy | 259 | 312 ± 121 | NA | Intraop: 50
Postop: 27 | | 144 ± 126 | 9.9 ± 7.2 | 46 | 3 | 14 | 1 | Other than bleeding: 2 | 52 ± 12 |
| | | p-value R/S | | 0.001 | NA | 0.003
0.004 | | <0.001 | <0.001 | 0.001 | 0.105 | 0.001 | 0.89 | 0.157 | 0.176 |
| Isolated MVr | 15. Stevens (2012) Comparative retro. | Robotic | 447 | NR | 18 | NR | 4 (IQR 4-6) | NR | 1.1 | 12 | 3 | NR | | | |
| | | Mini-Thoracotomy | 481 | | | | | | 43 | 5 (IQR 4-7) | 2.1 | | | 11 | 4 |
| | | Sternotomy | 377 | | | | | | 63 | 5 (IQR 4-7) | 3.8 | | | 11 | 5 |
| | | p-value R/MT/S | | | | | | | <0.001 | <0.001
0.016 | 0.042 | | | 0.711 | 0.674 |
| MVR concomitant with PFO | 16. Mihaljevic (2011) Comparative retro. Matched | Robotic | 106 | Median: 387 | NR | 0: 98 (92%)
1: 3 (2.8%)
2: 2 (1.9%)
>3: 3 (2.8%) | NR | ISI calc. Median 4.2 | 8.5 | 0 | NR | 3.8 | NR | | |
| | | Sternotomy | 106 | ISI calc. Median: 278 | | | | 0: 90 (85%)
1: 9 (8.5%)
2: 6 (5.7%)
>3: 1 (0.94%) | ISI calc. Median 5.2 | 9.4 | | 0 | | | 3.8 |
| | | p-value R/S | | <0.0001 | | | | 0.1 | <0.001 | 0.8 | | NA | | | 1 |
| | | Robotic | 223 | Median: 387 | | | | 0: 199 (89%)
1: 10 (4.5%)
2: 7 (3.1%)
>3: 7 (3.1%) | ISI calc. Median 4.2 | 11 | | 0 | | | 4.5 |
| | | Partial Sternotomy | 223 | ISI calc. Median: 277 | | | | 0: 202 (91%)
1: 11 (4.9%)
2: 9 (4.0%)
>3: 1 (0.45%) | ISI calc. Median 5.8 | 9.9 | | 0 | | | 4.9 |

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| Cardiac procedure | Author | Study Arms | Study Size (N) | Operating time (minutes) | Conversion to open surgery (%) | Blood transfusion (%) | Number of transfused units, n | ICU LOS (days) | LOS (days) | Postop. complications 30-d (%) | Mortality 30-d (%) | Readmission 30-d (%) | Reoperation for bleeding 30-d (%) | Reoperation for any reason 30-d (%) | Postop. ejection fraction (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | | p-value R/PS | | <0.0001 | | | 0.2 | | <0.001 | 0.8 | NA | | 0.8 | | |
| | | Robotic | 113 | Median: 387 | | | 0: 101 (89%)
1: 5 (4.4%)
2: 2 (1.8%)
>3: 5 (4.4%) | | ISI calc. Median 4.2 | 12 | 0 | | 6.2 | | |
| | | Mini-Thoracotomy | 113 | ISI calc. Median: 327 | | | 0: 107 (95%)
1: 3 (2.7%)
2: 1 (0.88%)
>3: 2 (1.8%) | | ISI calc. Median 5.1 | 2.7 | 0 | | 1.8 | | |
| | | p-value R/MT | | <0.0001 | | | 0.5 | | <0.001 | 0.006 | NA | | 0.09 | | |
| MVR concomitant with PFO | 17. Mori (2024) Database Matched | Robotic | 5540 | 375 ± 101 | NR | Intraop: 13
Postop: 15 | NR | 48 ± 62 | 5 ± 3.59 | In-hospital: 31 | Operative: 0.8 | 6.6 | NR | 3.1 | NR |
| | | Mini-Thoracotomy | 5540 | 332 ± 88 | | Intraop: 12
Postop: 13 | | 51 ± 87 | 5.57 ± 3.54 | In-hospital: 34 | Operative: 0.8 | 7.1 | | 2.6 | |
| | | p-value R/MT | | <0.001 | | 0.3
<0.001 | | 0.0366 | <0.001 | 0.011 | >0.9 | <0.001 | | 0.076 | |
| | | Robotic | 6962 | 374 ± 96 | | Intraop: 13
Postop: 15 | | 46 ± 59 | 4.95 ± 3.47 | NR | Operative: 0.7 | 6.1 | | 2.9 | |
| | | Sternotomy | 6962 | 305 ± 81 | | Intraop: 17
Postop: 17 | | 53 ± 65 | 6.21 ± 4.07 | | Operative: 0.6 | 6.8 | | 2.7 | |
| | | p-value R/S | | <0.001 | | <0.001
<0.001 | | <0.001 | <0.001 | | 0.2 | <0.001 | | 0.5 | |
| MVR concomitant with PFO | 18. Suri (2011) Comparative retro. Matched | Robotic | 95 | NR | 0 | ISI calc. Postop: 12 | ≥2: 10.53 | 31.29 ± 107.61 | 4.46 ± 6.38 | Any: 6.31
Major: 4.21 | 0 | NR | 1.05 | 0 | NR |
| | | Sternotomy | 95 | | NA | ISI calc. Postop: 18 | ≥2: 18.95 | 25.92 ± 20.20 | 5.34 ± 1.67 | Any: 6.31
Major: 5.26 | 0 | | 2.1 | 1.05 | |
| | | p-value R/S | | | NA | ISI calc. 0.308 | 0.1 | <0.001 | <0.001 | 1.00
1.00 | NA | | 1 | 1 | |
| MVR concomitant with PFO | 19. Suri (2013) Comparative retro. All Pre-July | Robotic | 185 | NR | ≥2 RBC: 7 | NR | STS: 3.8 | NR | 0 | Valve dysfunction: 0.5 | NR | | | | |
| | | Sternotomy | 185 | | | | | | | ≥2 RBC: 16.2 | | STS: 3.2 | 1.6 | Valve dysfunction: 0.5 | |
| | | p-value R/S | | | | | | | | 0.009 | | >0.99 | 0.25 | >0.99 | |

#

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| Cardiac procedure | Author | Study Arms | Study Size (N) | Operating time (minutes) | Conversion to open surgery (%) | Blood transfusion (%) | Number of transfused units, n | ICU LOS (days) | LOS (days) | Postop. complications 30-d (%) | Mortality 30-d (%) | Readmission 30-d (%) | Reoperation for bleeding 30-d (%) | Reoperation for any reason 30-d (%) | Postop. ejection fraction (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | 2009
Post-July 2009 | Robotic | 66 | NR | 24.7 | 4 | NR | Early: 0 | NR | | | | | | |
| | | Sternotomy | 111 | | | | | 26.7 | | | | | 5.6 | Early: 0 | |
| | | p-value R/S | | | | | | 0.006 | | | | | <0.001 | NA | |
| | | Robotic | 119 | | | | | 13.7 | | | | | 3.7 | Early: 0 | |
| | | Sternotomy | 74 | | | | | 27.8 | | | | | 5.7 | Early: 0 | |
| | | p-value R/S | | | | | | <0.001 | | | | | <0.001 | NA | |
| MVR concomitant with PFO | 20. Wang (2018)
Database Matched | Robotic | 503 | NR | Intraop: 20.48 | Intraop: 1.84 ± 2.09
Postop: 2.23 ± 2.69 | 41.96 ± 46.91 | 5.26 ± 2.88 | NR | Operative: 0.6
In-hospital: 0.2
30-d: 0.6 | NR | 2.98 | Valve dysfunction: 0 | NR | |
| | | Sternotomy | 503 | | | Intraop: 35.19 | Intraop: 1.49 ± 1.43
Postop: 1.86 ± 1.56 | 61.81 ± 61.40 | | 6.92 ± 3.54 | | Operative: 1.19
In-hospital: 1.19
30-d: 1.4 | 1.99 | | Valve dysfunction: 0.4 |
| | | p-value R/S | | | | <0.0001 | 0.20
0.72 | <0.0001 | | <0.0001 | | 0.32
0.06
NR | 0.31 | | 0.16 |
| MVR concomitant with PFO | 21. Zheng (2022)
Comparative retro. Matched | Robotic | 69 | NR | 1.4 | 1.4 | NR | 4 (IQR 3-4) | NR | Operative: 0 | 13 | 0 | Valve dysfunction: 0 | NR | |
| | | Mini-Thoracotomy | 69 | | 1.4 | 2.9 | | | | 4 (IQR 4-6) | Operative: 0 | 11.6 | 1.4 | | Valve dysfunction: 2.9 |
| | | p-value R/MT | | | >0.99 | >0.99 | | | | 0.003 | NR | 0.8 | >0.99 | | >0.99 |

Table 6: da Vinci Robotic-Assisted Defect Closure Secondary Clinical Outcomes

| Cardiac procedure name | Author | Study Arms | Study Size (N) | CPB time (minutes) | XC time (minutes) | Ventilation time (hours) | Prolonged mechanical ventilation (%) | Pulmonary complications (%) | Cardiac arrest (%) | Myocardial infarction (%) | New-onset atrial fibrillation (%) | Renal failure (%) | Stroke (%) | Discharge location (%) | Atrial septal leakage (%) or Postoperative residual flow (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| ASD | | Robotic | 101 | 69.3 ± 7.8 | 0 | NR | | | | | | | | | 0 |

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| Cardiac procedure name | Author | Study Arms | Study Size (N) | CPB time (minutes) | XC time (minutes) | Ventilation time (hours) | Prolonged mechanical ventilation (%) | Pulmonary complications (%) | Cardiac arrest (%) | Myocardial infarction (%) | New-onset atrial fibrillation (%) | Renal failure (%) | Stroke (%) | Discharge location (%) | Atrial septal leakage (%) or Postoperative residual flow (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | 1. Liu (2023) Comparative retro. | Sternotomy | 162 | 60.3 ± 7.8 | 0 | | 0 | | | | | | | | |
| | | p-value R/S | | <0.05 | NS | | | | | | | | | | NR |
| MVr + LAA | 2. Chickwe (2023) Comparative retro. Excluding concomitant cyromaze | MVr + LAA | 431 | 113 (IQR 101-126) | 72 (IQR 63-83) | NR | 0.5 | NR | 31.8 | Req. dialysis: 0.2 | 0.5 | NR | 1.4 | | |
| | | MVr | 333 | 131 (IQR 113-154) | 87 (IQR 72-108) | | | | 0.6 | 25.2 | Req. dialysis: 1.2 | | 2.1 | 4.2 | |
| | | p-value MVr/MVr+LAA | | <0.0001 | <0.0001 | | | | 1 | 0.047 | 0.34 | | 0.046 | 0.02 | |
| Isolated MVr | 13. Chemtob (2022) Comparative pro. | Robotic | 605 | 123 ± 33 | 73 ± 20 | NR | 25 | 0 | 0.5 | NR | | | | | |
| | | Sternotomy | 395 | 74 ± 25 | 55 ± 19 | | | | | | | 34 | 0 | 1 | |
| | | p-value R/S | | NR | NR | | | | | | | 0.003 | NA | 0.3 | |
| Isolated MVr | 14. Seo (2019) Comparative retro. | Robotic | 175 | NR | 133 ± 47 | NR | 1 | 0.6 | NR | 13 | 0.6 | 0.6 | NR | | |
| | | Sternotomy | 259 | | 115 ± 52 | | | 1 | | 3 | 18 | 2 | | | 1 |
| | | p-value R/S | | | <0.001 | | | 0.725 | | 0.071 | 0.164 | 0.157 | | | 0.53 |
| Isolated MVr | 15. Stevens (2012) Comparative retro. | Robotic | 447 | 164 ± 40 | 125 ± 31 | NR | 28 | NR | 0.7 | NR | | | | | |
| | | Mini-Thoracotomy | 481 | 141 ± 51 | 87 ± 42 | | | | | | | 20 | 1.2 | | |
| | | Sternotomy | 377 | 122 ± 51 | 86 ± 34 | | | | | | | 26 | 3.4 | | |
| | | p-value R/MT/S | | <0.001 | <0.001 | | | | | | | 0.008 | 0.008 | | |
| MVR concomitant with PFO | 16. Mihaljevic (2011) Comparative retro. Matched | Robotic | 106 | Median: 116 | Median: 85 | NR | >24h: 1.9 | Pleural effusion: 0 | NR | 26 | NR | 1.9 | NR | | |
| | | Sternotomy | 106 | ISI calc. Median: 74 | ISI calc. Median: 57 | | >24h: 2.8 | Pleural effusion: 8.5 | | | | 30 | | | 0.94 |
| | | p-value R/S | | 0.007 | <0.0001 | | 0.6 | 0.002 | | | | 0.5 | | | 0.6 |
| | | Robotic | 223 | Median: 116 | Median: 85 | | >24h: 4.9 | Pleural effusion: 1.8 | | | | 22 | | | 2.7 |
| | | Partial Sternotomy | 223 | ISI calc. Median: 76 | ISI calc. Median: 59 | | >24h: 2.2 | Pleural effusion: 8.5 | | | | 35 | | | 3.1 |
| | | p-value R/PS | | 0.007 | <0.0001 | | 0.1 | 0.001 | | | | 0.002 | | | 0.8 |

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| Cardiac procedure name | Author | Study Arms | Study Size (N) | CPB time (minutes) | XC time (minutes) | Ventilation time (hours) | Prolonged mechanical ventilation (%) | Pulmonary complications (%) | Cardiac arrest (%) | Myocardial infarction (%) | New-onset atrial fibrillation (%) | Renal failure (%) | Stroke (%) | Discharge location (%) | Atrial septal leakage (%) or Postoperative residual flow (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | | Robotic | 113 | Median: 116 | Median: 85 | | >24h: 3.5 | Pleural effusion: 1.8 | | | 19 | | 1.8 | | |
| | | Mini-Thoracotomy | 113 | ISI calc. Median: 106 | ISI calc. Median: 66 | | >24h: 0.88% | Pleural effusion: 1.8 | | | 26 | | 0 | | |
| | | p-value R/MT | | 0.007 | <0.0001 | | 0.2 | 1 | | | 0.3 | | 0.2 | | |
| MVR concomitant with PFO | 17. Mori (2024) Database Matched | Robotic | 5540 | 145 ± 57 | 95 ± 37 | 7.7 ± 33.9 | 3.1 | Pneumonia: 0.7 | | | 22 | 0.8 | Permanent: 1.2 | | |
| | | Mini-Thoracotomy | 5540 | 136 ± 54 | 94 ± 36 | 8.8 ± 38.8 | 3.1 | Pneumonia: 0.8 | | | 25 | 0.6 | Permanent: 1 | | |
| | | p-value R/MT | | <0.001 | 0.3 | NR | >0.9 | 0.8 | | | 0.002 | 0.2 | 0.4 | | |
| | | Robotic | 6962 | 143 ± 55 | 93 ± 36 | 7.4 ± 34.6 | 2.9 | Pneumonia: 0.6 | | | 22 | 0.7 | Permanent: 1.1 | | |
| | | Sternotomy | 6962 | 104 ± 45 | 79 ± 35 | 9.3 ± 42.6 | 3.2 | Pneumonia: 0.8 | | | 30 | 0.7 | Permanent: 1 | | |
| | | p-value R/S | | <0.001 | <0.001 | NR | 0.2 | 0.4 | | | <0.001 | >0.9 | 0.8 | | |
| MVR concomitant with PFO | 18. Suri (2011) Comparative retro. Matched | Robotic | 95 | 113.32 ± 40.39 | 81.40 ± 28.33 | 14.07 ± 88.92 | >48h: 1.05 | | | 3.16 | Permanent: 0 | 0 | 1.05 | | |
| | | Sternotomy | 95 | 48.22 ± 24.55 | 35.94 ± 19.66 | 8.13 ± 6.25 | >48h: 1.05 | | | 0 | Permanent: 0 | 1.05 | 0 | | |
| | | p-value R/S | | <0.001 | <0.001 | <0.001 | 1 | | | 0.25 | NA | 1 | 1 | | |
| MVR concomitant with PFO | 19. Suri (2013) Comparative retro. All Pre-July 2009 Post-July 2009 | Robotic | 185 | | | | >48h: 0.5 | | | 1.1 | In hospital: 18.4 | 0.5 | 0.5 | | |
| | | Sternotomy | 185 | | | | >48h: 0 | | | 0 | In hospital: 30.3 | 0.5 | 0 | | |
| | | p-value R/S | | | | | >0.99 | | | 0.5 | 0.01 | >0.99 | >0.99 | | |
| | | Robotic | 66 | | | | | | | | | | | | |
| | | Sternotomy | 111 | | | | | | | | | | | | |
| | | p-value R/S | | | | | | | | | | | | | |
| | | Robotic | 119 | | | | | | | | | | | | |
| | | Sternotomy | 74 | | | | | | | | | | | | |
| | | p-value R/S | | | | | | | | | | | | | |
| MVR concomitant with PFO | 20. Wang (2018) Database Matched | Robotic | 503 | 135.62 ± 52.89 | 90.52 ± 34.53 | NR | 2.58 | Pneumonia: 0.99 Pulm. Thromboembolism: 0.3 | 0.8 | | 27.83 | 0.8 | Permanent: 0.99 | | |
| | | Sternotomy | 503 | 109.97 ± 45.94 | 83.85 ± 38.24 | | 4.77 | Pneumonia: 1.39 Pulm. | 1.39 | | 39.76 | 1.79 | Permanent: 1.79 | | |

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| Cardiac procedure name | Author | Study Arms | Study Size (N) | CPB time (minutes) | XC time (minutes) | Ventilation time (hours) | | Prolonged mechanical ventilation (%) | Pulmonary complications (%) | Cardiac arrest (%) | Myocardial infarction (%) | New-onset atrial fibrillation (%) | Renal failure (%) | Stroke (%) | Discharge location (%) | Atrial septal leakage (%) or Postoperative residual flow (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | | | | | | | | Thromboembolism: 0 | | | | | | | | |
| | | p-value R/S | | <0.0001 | <0.0001 | | 0.06 | 0.56 0.11 | 0.36 | | <0.0001 | 0.16 | 0.28 | | | |
| MVR concomitant with PFO | 21. Zheng (2022) Comparative retro. Matched | Robotic | 69 | 85 (IQR 73-105) | 57 (IQR 48-67) | NR | 1.4 | Pleural effusion req. drainage: 0 Pneumothorax: 0 Pneumonia: 0 | NR | 24.6 | NR | | | | | |
| | | Mini-Thoracotomy | 69 | 88 (IQR 75-108) | 47 (IQR 37-58) | | 0 | Pleural effusion req. drainage: 4.3 Pneumothorax: 2.9 Pneumonia: 1.4 | | | | | | | | 34.8 |
| | | p-value R/MT | | 0.27 | <0.001 | | >0.99 | 0.25 0.5 >0.99 | | | | | | | | 0.19 |

Table 7: da Vinci Robotic-Assisted Extirpative Main Clinical Outcomes

| Cardiac Procedure | Author | Study Arms | Study Size (N) | Operating time (minutes) | Conversion to open surgery (%) | Blood transfusion (%) | Number of transfused units, n | ICU LOS (days) | LOS (days) | Postop. complications 30-d (%) | | Mortality 30-d (%) | Readmission 30-d (%) | Reoperation for bleeding 30-d (%) | Reoperation for any reason 30-d (%) | Postop. Ejection Fraction (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Myxoma Excision | 8. Kesavuori (2015) Comparative retro. | Robotic | 9 | 226 ± 39 | 0 | RBC: 44 | RBC: 1.67 ± NR | 1 (IQR 0) | 5.8 ± 1 | NR | 0 | NR | 56.8 ± 8.3 | | | |
| | | Sternotomy | 18 | 139 ± 33 | NA | RBC: 72 | RBC: 2 ± NR | 1 (IQR 0) | 7 ± 1.6 | | 0 | | | | | 50.9 ± 6.3 |
| | | p-value R/S | | <0.001 | NA | 0.219 | 0.403 | 0.495 | 0.023 | | NA | | | | | 0.235 |
| Myxoma Excision | 9. Li (2017) Comparative retro. | Robotic | 53 | NR | 7/53 | NR | | | | | | | | | | |
| | | Sternotomy | 84 | | | | | | | | 11/84 | | | | | |
| | | Mini-thoracotomy | 10 | | | | | | | | 2/10 | | | | | |
| | | p-value R/S/MT | | | | | | | | | 0.835 | | | | | |
| Myxoma Excision | 10. Liu (2023) Comparative retro. | Robotic | 31 | 225.39 ± 33.83 | 0 | 64.5 | Total: 3 (IQR 0-4) | 20h (IQR 19h-41h) | 9 (IQR 8-11) | In-hospital: 0 | 0 | NR | 0 | NR | | |
| | | Mini-thoracotomy | 15 | 297.13 ± 98.7 | 0 | 66.7 | Total: 3.5 (IQR 0-4.5) | 39h (IQR 38h-44h) | 9 (IQR 8-13) | In-hospital: 0 | 0 | | 0 | | | |
| | | p-value R/T | | 0.015 | NA | 0.886 | 0.725 | 0.006 | 0.422 | NA | NA | | NA | | | |
| Myxoma Excision | 11. Liu (2024) | Robotic | 30 | 226.4 ± 33 | 0 | NR | 3.5 (IQR 0-4) | 20h (IQR 18.8h-41h) | 9 (IQR 8-11.3) | NR | 0 | NR | 0 | NR | | |

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| Cardiac Procedure | Author | Study Arms | Study Size (N) | Operating time (minutes) | Conversion to open surgery (%) | Blood transfusion (%) | Number of transfused units, n | ICU LOS (days) | LOS (days) | Postop. complications 30-d (%) | | Mortality 30-d (%) | Readmission 30-d (%) | Reoperation for bleeding 30-d (%) | Reoperation for any reason 30-d (%) | Postop. Ejection Fraction (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | Comparative retro. | Sternotomy | 64 | 227.41 ± 35.88 | 0 | | 3.5 (IQR 2-4) | 21h (IQR 18h-41.5h) | 10 (IQR 8-14) | | 1.6 | | 0 | | | |
| | | p-value R/S | | 0.897 | NA | | 0.39 | 0.556 | 0.04 | | 1 | | NA | | | |
| Myxoma Excision | 12. Shilling (2012) Comparative retro. | Robotic | 16 | 2.7h ± 0.3h | NR | 13 | NR | 30.9h ± 18.4h | 3.6 ± 0.8 | NR | 0 | NR | 0 | 0 | NR | |
| | | Sternotomy | 29 | 3.5h ± 0.9h | | 26 | | 47.7h ± 52.1h | 6.2 ± 5.1 | | 0 | | 0 | 3 | | |
| | | p-value R/S | | 0.02 | | 0.3 | | 0.15 | 0.05 | | NA | | NA | 0.44 | | |

Table 8: da Vinci Robotic-Assisted Extirpative Secondary Clinical Outcomes

| Cardiac Procedure | Author | Study Arms | Study Size (N) | CPB time (minutes) | XC time (minutes) | Ventilation time (hours) | Prolonged mechanical ventilation (%) | Pulmonary complications (%) | Cardiac arrest (%) | Myocardial infarction (%) | New-onset atrial fibrillation (%) | Renal failure (%) | Stroke (%) | Discharge location (%) | Myxoma recurrence (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Myxoma Excision | 8. Kesavuori (2015) Comparative retro. | Robotic | 9 | 124 ± 30 | 67 ± 21 | 14.6 ± 5 | NR | Pneumonia: 0 | NR | 0 | NR | 0 | NR | 0 | |
| | | Sternotomy | 18 | 54 ± 21 | 34 ± 15 | 9 ± 3 | | Pneumonia: 0 | | 6 | | | | 0 | 0 |
| | | p-value R/S | | <0.001 | <0.001 | 0.001 | | 1 | | 1 | | | | 1 | NA |
| Myxoma Excision | 9. Li (2017) Comparative retro. | Robotic | 53 | 72.9 ± 26.7 | 37.9 ± 15.1 | NR | Thoracic: 2/53 | NR | Arrhythmia: 4/53 | NR | | | | | |
| | | Sternotomy | 84 | 65.1 ± 21.9 | 37.1 ± 16.2 | | | | | | | | | Thoracic: 1/84 | Arrhythmia: 5/84 |
| | | Mini-thoracotomy | 10 | 87.4 ± 23.2 | 45.3 ± 17.5 | | | | | | | | | Thoracic: 0/10 | Arrhythmia: 2/10 |
| | | p-value R/S/MT | | 0.008 | 0.266 | | | | | | | | | 0.645 | 0.212 |
| Myxoma Excision | 10. Liu (2023) Comparative retro. | Robotic | 31 | 97.9 ± 24.48 | 55 (IQR 44-69.5) | 6 (IQR 3-15) | >24h: 0 | Pneumonia: 6.5 | NR | 19.4 | 0 | 3.2 | NR | | |
| | | Mini-thoracotomy | 15 | 118.27 ± 38.82 | 70 (IQR 51-78) | 13 (IQR 5-19) | >24h: 6.7 | Pneumonia: 0 | | | 13.3 | 6.7 | | | 0 |
| | | p-value R/T | | 0.035 | 0.124 | 0.035 | 0.326 | 1 | | | 0.928 | 0.326 | | | 1 |
| Myxoma Excision | 11. Liu (2024) Comparative retro. | Robotic | 30 | 99.93 ± 22.3 | 57.8 ± 20.27 | 4.8 (IQR 2.8-12) | >24h: 0 | Pneumonia: 6.7 | NR | 16.7 | 0 | 3.3 | NR | 0 | |
| | | Sternotomy | 64 | 76.28 ± 24.92 | 47.89 ± 18.1 | 8 (IQR 6-16) | >24h: 4.7 | Pneumonia: 6.3 | | | 18.8 | 1.6 | | 0 | 0 |
| | | p-value R/S | | <0.001 | 0.019 | 0.005 | 0.549 | 1 | | | 0.807 | 1 | | 0.319 | NA |
| Myxoma Excision | 12. Shilling (2012) Comparative retro. | Robotic | 16 | Perfusion: 91.3 ± 45.2 | 49.4 ± 37.6 | NR | >24h: 6 | Pneumonia: 0 Pulmonary embolism: 0 | NR | 0 | 0 | 0 | NR | | |
| | | Sternotomy | 29 | Perfusion: 96.8 ± 42.1 | 52.1 ± 39.6 | | >24h: 11 | Pneumonia: 4 Pulmonary embolism: 0 | | | 17 | 10 | | | 0 |
| | | p-value R/S | | 0.68 | 0.82 | | 1 | 1 | | | 0.14 | 0.54 | | | NA |

Table 9: da Vinci Robotic-Assisted Valve Repair Main Clinical Outcomes

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| Cardiac procedure | Author | Study…