ONETOUCH ULTRA, INDUO AND ULTRASMART BLOOD GLUCOSE MONITORING SYSTEM
K043197 · Lifescan, Inc. · CGA · May 20, 2005 · Clinical Chemistry
Device Facts
Record ID
K043197
Device Name
ONETOUCH ULTRA, INDUO AND ULTRASMART BLOOD GLUCOSE MONITORING SYSTEM
Applicant
Lifescan, Inc.
Product Code
CGA · Clinical Chemistry
Decision Date
May 20, 2005
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 862.1345
Device Class
Class 2
Indications for Use
The OneTouch® Ultra® Family of Systems are intended to be used for quantitative measurement of glucose in fresh capillary whole blood. The OneTouch Ultra Family of Systems are intended for use outside the body (in vitro diagnostic use) by people with diabetes at home and healthcare professionals in a clinical setting as an aid to monitor the effectiveness of diabetes control. The OneTouch Ultra Family of Blood Glucose Monitoring System is specifically indicated for use on the finger, arm or palm.
Device Story
System uses glucose oxidase biosensor test strips and reflectance photometer to measure capillary blood glucose. User applies blood to strip; reagents generate electrical current proportional to glucose concentration; meter calculates and displays result. Used by patients at home or clinicians in clinical settings. Provides quantitative glucose readings to aid diabetes management. Includes electronic logbook (UltraSmart) and integrated insulin dosing cap (InDuo). Palm testing requires steady-state conditions; fingertip testing preferred for rapid glucose changes or suspected hypoglycemia. Data port allows download to PC for analysis.
Clinical Evidence
Clinical testing demonstrated that palm and finger glucose measurements are equivalent during steady state. No other clinical data provided; performance characteristics remain unchanged from predicate devices.
Technological Characteristics
In vitro diagnostic system; glucose oxidase electrochemical biosensor; reflectance photometer; capillary blood sample; data management software; PC connectivity via data port; integrated insulin doser (InDuo model); electronic logbook (UltraSmart model).
Indications for Use
Indicated for quantitative glucose measurement in fresh capillary whole blood for people with diabetes at home or clinical settings. Specifically indicated for use on finger, arm, or palm. Contraindicated for palm testing if glucose is rapidly changing (e.g., within 2 hours of meals, exercise, or rapid-acting insulin) or if hypoglycemia is suspected.
Regulatory Classification
Identification
A glucose test system is a device intended to measure glucose quantitatively in blood and other body fluids. Glucose measurements are used in the diagnosis and treatment of carbohydrate metabolism disorders including diabetes mellitus, neonatal hypoglycemia, and idiopathic hypoglycemia, and of pancreatic islet cell carcinoma.
Special Controls
*Classification.* Class II (special controls). The device, when it is solely intended for use as a drink to test glucose tolerance, is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 862.9.
OneTouch® Ultra® Blood Glucose Monitoring System (K043197)
OneTouch® InDuo® Blood Glucose Monitoring System (K043197)
OneTouch® UltraSmart® Blood Glucose Monitoring System (K043197)
Submission Summary (Full Text)
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# 510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION DECISION SUMMARY ASSAY ONLY TEMPLATE
A. 510(k) Number:
k043197
B. Purpose for Submission:
Clearance of new claim for alternate site testing on the palm when the patient is in the steady state
C. Measurand:
Capillary blood glucose
D. Type of Test:
Quantitative enzymatic (glucose oxidase) electrochemical assay
E. Applicant:
Lifescan, Inc.
F. Proprietary and Established Names:
OneTouch Ultra, Induo, and Ultrasmart Blood Glucose Monitoring Systems
G. Regulatory Information:
1. Regulation section:
21 CFR §862.1345, Glucose test system
2. Classification:
Class II
3. Product code:
NBW, System, test, blood glucose, over the counter
CGA, glucose oxidase, glucose
4. Panel:
Clinical Chemistry (75)
H. Intended Use:
1. Intended use(s):
The OneTouch Ultra, Induo, and Ultrasmart Blood Glucose Monitoring Systems are intended to be used for quantitative measurement of glucose in fresh capillary whole blood. The OneTouch Ultra, Induo, and Ultrasmart Blood Glucose Monitoring Systems are intended for use outside the body (in vitro diagnostic use) by people with diabetes at home and healthcare professionals in a clinical setting as an aid to monitor the effectiveness of diabetes control.
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2. **Indication(s) for use:**
The OneTouch Ultra, Induo, and Ultrasmart Blood Glucose Monitoring Systems are intended to be used for quantitative measurement of glucose in fresh capillary whole blood. The OneTouch Ultra, Induo, and Ultrasmart Blood Glucose Monitoring Systems are intended for use outside the body (in vitro diagnostic use) by people with diabetes at home and healthcare professionals in a clinical setting as an aid to monitor the effectiveness of diabetes control.
The OneTouch Ultra, Induo, and Ultrasmart Blood Glucose Monitoring Systems are specifically indicated for use on the finger, arm or palm.
3. **Special conditions for use statement(s):**
For over-the-counter or professional use
Patients should not test on the palm when they think their blood glucose is rapidly falling, such as within two hours of exercise or a rapid-acting insulin injection or insulin pump bolus. Testing with a fingertip sample may identify a hypoglycemic (low blood sugar) level sooner than a test with a forearm or palm sample.
Patients should not test on the palm when it has been less than two hours after a meal, a rapid-acting insulin injection or insulin pump bolus, physical exercise, or they think their glucose level is changing rapidly.
Patients should not test on the palm when they are concerned about the possibility of hypoglycemia.
The OneTouch® InDuo® Blood Glucose Meter also functions as the cap for the InDuo® Insulin Doser. The two devices fit together to form a single unit for user convenience.
The OneTouch UltraSmart® Blood Glucose Monitoring System provides the user with electronic logbook functions that store data such as insulin and oral medication doses, food intake, amount of exercise, and health information such as illness. The meter includes a data port that enables the user to download electronic data to a personal computer.
4. **Special instrument requirements:**
OneTouch Ultra, Induo, or Ultrasmart Blood Glucose Monitoring Systems
I. **Device Description:**
The OneTouch Ultra, Induo, and Ultrasmart Blood Glucose Monitoring Systems are in vitro diagnostic products consisting of a test strip impregnated with reagents and a reflectance photometer for the determination of glucose in whole blood. A quality control solution, ancillary devices to aid obtaining a capillary blood sample (lancets and lancing device), and data management computer software are also available.
J. **Substantial Equivalence Information:**
1. **Predicate device name(s):**
Lifescan OneTouch Ultra Blood Glucose Monitoring System
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Lifescan OneTouch UltraSmart Blood Glucose Monitoring System
Lifescan OneTouch Ultra and OneTouch InDuo Blood Glucose Monitoring Systems
Lifescan InDuo Blood Meter
Freestyle Blood Glucose Monitoring System
BD Logic and Paradigm Link Blood Glucose Monitoring Systems
2. Predicate 510(k) number(s):
k002134, k021819, k024194, k011616, k031260, k041478
3. Comparison with predicate:
The device is the same device as the predicate OneTouch Ultra Blood Glucose Monitoring System except that the Indications for Use have been expanded to include palm alternate site testing when the patient is in the steady state.
K. Standard/Guidance Document Referenced (if applicable):
FDA Guidance Document: Review Criteria for Assessment of Portable Blood Glucose In Vitro Diagnostic Devices Using Glucose Oxidase, Dehydrogenase, or Hexokinase Methodology
ISO 15197: Requirements for blood-glucose monitoring systems for self-testing in managing diabetes mellitus
L. Test Principle:
The test system works by using glucose oxidase biosensor technology. When blood is applied to a test strip inserted into the meter port, the reagents on the strip react with the glucose in the blood to generate small electrical currents. The meter automatically starts and controls the test timing. It measures the electrical currents that are produced to calculate the glucose result.
M. Performance Characteristics (if/when applicable):
1. Analytical performance:
a. Precision/Reproducibility:
Not applicable. Analytical Performance Characteristics cleared in previous 510(k) submissions (e.g. k002134, k021819, and k024194)
b. Linearity/assay reportable range:
Not applicable. Analytical Performance Characteristics cleared in previous 510(k) submissions (e.g. k002134, k021819, and k024194)
c. Traceability, Stability, Expected values (controls, calibrators, or methods):
Not applicable. Analytical Performance Characteristics cleared in previous 510(k) submissions (e.g. k002134, k021819, and k024194)
d. Detection limit:
Not applicable. Analytical Performance Characteristics cleared in previous 510(k) submissions (e.g. k002134, k021819, and k024194)
e. Analytical specificity:
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Not applicable. Analytical Performance Characteristics cleared in previous 510(k) submissions (e.g. k002134, k021819, and k024194)
f. Assay cut-off: Not applicable
2. Comparison studies:
a. Method comparison with predicate device:
See Matrix Comparison below for a comparison of fingertip and palm testing.
b. Matrix comparison:
To evaluate the lay-user performance of alternate site testing in the steady state using the palm, test subjects (diabetic lay users) were provided with the device and asked to do a minimum of two blood glucose tests daily using the palm (one from the thenar and one from the hypothenar). Subjects were instructed not to make any treatment decisions based on the test results.
For the second phase of the study, test subjects reported to the study site in a steady state condition (defined as at least 2 ours after a meal, insulin dose, or physical exercise). The subjects tested themselves using blood from the palm under the observation of a healthcare professional. The healthcare professional then performed tests from the palm and two fingertips. The subjects then consumed a meal and took their usual insulin dose or hypoglycemic medication. The subjects were tested again by the healthcare professionals at predetermined time points over 4 hours for adults or 2 hours for pediatric subjects. At one of time points (chosen randomly), the subject performed their own tests. Hypoglycemic is defined as glucose concentration $\leq 60\mathrm{mg / dL}$ , Euglycemic is defined as glucose concentration $>60$ and $\leq 140\mathrm{mg / dL}$ , and Hyperglycemic is defined as glucose concentration $>140\mathrm{mg / dL}$ . Results, summarized below, support the performance of alternate site testing on the palm when the patient is in the steady state.
| Reference Blood Glucose | Steady State Data - Difference, Palm - Finger (in % if reference concentration > 75 mg/dL, else in mg/dL) | | | | | | | | | | Total |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | >20 | | ±20 | | ±15 | | ±10 | | ±5 | | |
| | n | % or mg/dL | n | % or mg/dL | n | % or mg/dL | n | % or mg/dL | n | % or mg/dL | n |
| ≤75 mg/dL | 1 | 3.2 | 30 | 96.8 | 28 | 90.3 | 25 | 80.6 | 14 | 45.2 | 31 |
| >75 mg/dL | 29 | 3.9 | 718 | 96.1 | 669 | 89.6 | 550 | 73.6 | 333 | 44.6 | 747 |
| All | 30 | 3.9 | 748 | 96.1 | 697 | 89.6 | 575 | 73.9 | 347 | 44.6 | 778 |
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| Steady state data | palm to finger | | finger to finger | |
| --- | --- | --- | --- | --- |
| | # points | % pass** | # points | % pass** |
| Subject only | 106 | 93.3 % | 106 | 97.1 % |
| HCP* | 672 | 96.2 % | 675 | 97.6 % |
| HCP + Subj. | 778 | 95.8 % | 781 | 97.5 % |
* HCP = healthcare professional
** acceptable results are defined as being within 15 mg/dL in samples ≤ 75 mg/dL glucose or within 20% in samples > 75 mg/dL glucose
Deming regression analysis on the data from the matched palm and fingertip samples was performed. Regression statistics are summarized below:
| | Intercept | Lower 95% CI | Upper 95% CI | Slope | Lower 95% CI | Upper 95% CI |
| --- | --- | --- | --- | --- | --- | --- |
| Steady State | 1.24 | 0.31 | 2.45 | 0.9704 | 0.9643 | 0.9765 |
Results, analyzed to compare two palm sites (thenar and hypothenar), are summarized below:
| Data Set | Steady State Data | | | |
| --- | --- | --- | --- | --- |
| | palm to finger | | finger to finger | |
| | # points | % pass* | # points | % pass* |
| Hypothenar | 403 | 95.0 % | 407 | 97.2 % |
| Thenar | 375 | 96.8 % | 374 | 97.8 % |
* passing results are defined as being within 15 mg/dL in samples ≤ 75 mg/dL glucose or within 20% in samples > 75 mg/dL glucose
Results comparing data from adult subjects to pediatric subjects is summarized below. The device seems to perform equivalently in pediatric subjects and adults.
| Data Set | Steady State Data | | | |
| --- | --- | --- | --- | --- |
| | palm to finger | | finger to finger | |
| | # points | % pass* | # points | % pass* |
| Pediatric | 99 | 98.99% | 99 | 96.97 % |
| Adult | 679 | 95.43 % | 682 | 97.65 % |
* passing results are defined as being within 15 mg/dL in samples ≤ 75 mg/dL glucose or within 20% in samples > 75 mg/dL glucose
An analysis of the Mean Absolute Percentage Error (MAPE) was performed to examine the differences between Palm and Reference Finger compared to differences between Comparator Finger and Reference Finger. Data are summarized below:
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| Data Subset | | N | MAPE | SD | Stand Error | Lower 95% CI | Upper 95% CI |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Total | Palm | 778 | 7.49 | 6.84 | 0.25 | 7.01 | 7.97 |
| | Finger | 781 | 6.34 | 6.07 | 0.22 | 5.91 | 6.76 |
| HCP Tests | Palm | 672 | 7.42 | 6.76 | 0.26 | 6.91 | 7.93 |
| | Finger | 675 | 6.30 | 5.43 | 0.21 | 5.89 | 6.71 |
| Subj Tests | Palm | 106 | 7.92 | 7.31 | 0.71 | 6.51 | 9.32 |
| | Finger | 106 | 6.58 | 9.21 | 0.89 | 4.80 | 8.35 |
| Pediatrics | Palm | 99 | 6.63 | 4.75 | 0.48 | 5.68 | 7.58 |
| | Finger | 99 | 6.75 | 5.00 | 0.50 | 5.75 | 7.74 |
| Adults | Palm | 679 | 7.61 | 7.08 | 0.27 | 7.08 | 8.15 |
| | Finger | 682 | 6.28 | 6.21 | 0.24 | 5.81 | 6.74 |
| Hypothenar | Palm | 403 | 7.73 | 7.73 | 6.87 | 0.34 | 7.05 |
| | Finger | 407 | 5.86 | 5.12 | 0.25 | 5.36 | 6.36 |
| Thenar | Palm | 375 | 7.23 | 6.81 | 0.35 | 6.54 | 7.92 |
| | Finger | 374 | 6.86 | 6.93 | 0.36 | 6.15 | 7.56 |
# 3. Clinical studies:
a. Clinical Sensitivity:
See Matrix Comparison above for clinical information.
b. Clinical specificity:
See Matrix Comparison above for clinical information.
c. Other clinical supportive data (when a. and b. are not applicable):
During the study, palm testing was first conducted at home to provide subjects an opportunity to read the investigational labeling and experience palm testing prior to reporting to the clinic for observation and equivalency testing. All data was self-reported. This phase of the study involved initial exposure to palm lancing. The palm testing evaluation (Study Visit) incorporated a human factors evaluation as well as provided a controlled formal evaluation of palm lancing. Subjects performed a test on the palm under the observation of a Health Care Professional (HCP) using only the labeling as a guide. This testing was done at the beginning of the study visit, prior to the palm equivalency testing performed by the HCPs. Targeted aspects of subject performance were recorded by the HCP. A total of 181 subjects performed blood glucose self-tests on the palm using the device and investigational labeling. HCPs
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observed and evaluated the test without providing assistance or guidance to the subjects. Subjects were allowed up to two tests to obtain a numeric result. If the subjects did not obtain a numeric result on the first test, they were instructed to re-read the investigational AST Booklet and repeat the test on the palm. The subject could choose the area of the palm to test. Of the 181 subjects participating in the study, 152 (84.0%) of subjects were able to obtain a numeric result after the 1st attempt. A total of 29 (16%) subjects, who did not obtain a numeric result on the 1st attempt, re-read the labeling and repeating the test. After the 2nd attempt all but 3 subjects were able to obtain a numeric result. Analysis of the data suggested that problems were a result of patients using the wrong cap on the lancet despite labeling. To address this, additional emphasis and clarity were added to the labeling regarding 1) obtaining a sufficient blood sample from the palm and 2) which sampler cap to use for alternative site testing.
4. Clinical cut-off: Not applicable
5. Expected values/Reference range: The expected blood glucose levels for people without diabetes are as follows:
| Time | Range (mg/dL) |
| --- | --- |
| Before breakfast | 70 – 105 |
| Before lunch or dinner | 70 – 110 |
| 1 hour after meals | < 160 |
| 2 hours after meals | < 120 |
| Between 2 and 4 AM | > 70 |
N. Proposed Labeling:
The labeling is sufficient and it satisfies the requirements of 21 CFR Part 809.10.
O. Conclusion:
The submitted information in this premarket notification is complete and supports a substantial equivalence decision.
Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.