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510(k) Data Aggregation
(29 days)
SELFCARE, INC.
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(24 days)
SELFCARE, INC.
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(24 days)
SELFCARE, INC.
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(28 days)
SELFCARE, INC.
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(24 days)
SELFCARE, INC.
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(16 days)
SELFCARE, INC.
The FastTake® Compact Blood Glucose Monitoring System is intended to be used for the quantitative measurement of glucose in fresh capillary whole blood. The FastTake® System is intended for use outside the body (in vitro diagnostic use) by diabetics at home as an aid to monitor the effectiveness of diabetes control.
The FastTake® system includes four main components:
- FastTake® Test Strips .
- FastTake® Compact Blood Glucose Meter
- FastTake® Control Solution
- Penlet II or Penlet Plus lancing device and FinePoint lancets.
Here's an analysis of the provided text, focusing on the acceptance criteria and study data for the FastTake® Compact Blood Glucose Monitoring System:
1. Table of Acceptance Criteria and Reported Device Performance
The document primarily focuses on demonstrating equivalence to a predicate device, rather than explicit pre-defined "acceptance criteria" for performance. However, based on the Summary of Performance Data provided, we can infer the key performance metrics evaluated and their reported results. The predicate device's performance would serve as the implicit acceptance benchmark.
| Performance Metric | Implied Acceptance Criteria (relative to predicate) | Reported Device Performance (Modified FastTake®) |
|---|---|---|
| Precision | Demonstrates equivalent or better precision at various glucose levels. | Glucose Level 1 (62 mg/dL): SD=1.1 mg/dL, CV=1.7% |
| Glucose Level 2 (87 mg/dL): SD=3.5 mg/dL, CV=4.0% | ||
| Glucose Level 3 (152 mg/dL): SD=3.2 mg/dL, CV=2.1% | ||
| Glucose Level 4 (220 mg/dL): SD=6.3 mg/dL, CV=2.9% | ||
| Glucose Level 5 (378 mg/dL): SD=9.1 mg/dL, CV=2.4% | ||
| (Compared to unmodified FastTake®, indicating equivalence) | ||
| Accuracy (Professional Users vs. YSI) | Equivalent accuracy as measured against a reference method (YSI) | n = 238 |
| $y = 1.04x - 9.2$ | ||
| r = 0.988 | ||
| Sy·x = 13.5 | ||
| Range = 44 to 425 mg/dL | ||
| Accuracy (Lay Users vs. YSI) | Equivalent accuracy as measured against a reference method (YSI) | n = 119 |
| $y = 1.03x - 5.2$ | ||
| r = 0.982 | ||
| Sy·x = 16.69 | ||
| Range = 46 to 425 mg/dL |
2. Sample Size Used for the Test Set and Data Provenance
- Precision Study (Laboratory Study):
- Sample Size: 20 samples (n=20) for each of the 5 glucose levels.
- Data Provenance: The document states "A laboratory study," implying an in-house or controlled laboratory setting. It does not specify the country of origin or whether it's retrospective or prospective, but such laboratory studies are typically prospective.
- Accuracy Study (Clinical Centers):
- Professional Users: n = 238.
- Lay Users: n = 119.
- Data Provenance: "clinical centers" (plural, suggesting multiple sites). The context implies these are prospective clinical studies. The country of origin is not explicitly stated, but the submission is to the US FDA, making it highly probable the studies were conducted in the US or under US regulatory standards. The participants were "people with diabetes."
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
This type of device (blood glucose monitor) does not typically rely on human expert interpretation for ground truth. The gold standard for glucose measurement is usually a highly accurate laboratory reference method.
- Ground Truth Method: The text explicitly states "Accuracy of Professional users compared to YSI" and "Accuracy of Lay users compared to YSI." YSI (Yellow Springs Instruments) is a well-known brand for laboratory-grade glucose analyzers, serving as the reference method or "ground truth" in these studies.
- Number/Qualifications of Experts: Not applicable, as the ground truth was established by laboratory instrumentation (YSI), not human experts.
4. Adjudication Method for the Test Set
Not applicable. Adjudication methods (like 2+1 or 3+1) are typically used when human experts are establishing ground truth, especially for subjective assessments (e.g., image interpretation). Since the ground truth was instrumental (YSI), no human adjudication method was needed or performed.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
No, an MRMC comparative effectiveness study was not done. This type of study (comparing human reader performance with and without AI assistance) is relevant for diagnostic imaging AI devices where human interpretation is a primary component. For a blood glucose monitor, the focus is on the device's direct measurement capability, both by professional and lay users, against a laboratory reference.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
Yes, implicitly. The performance data presented (precision and accuracy) represents the device's performance. While "lay users" and "professional users" are involved in operating the device, the metrics themselves ($y=mx+b$, r-value, S_yx, SD, CV%) are a standalone reflection of the device's measurement precision and accuracy compared to a reference standard (YSI). There isn't a separate "algorithm" being evaluated beyond the functioning of the glucose meter and test strips.
7. The Type of Ground Truth Used
The ground truth used was an objective laboratory reference method, specifically a YSI glucose analyzer. This is considered a highly accurate and precise instrumental measurement, often serving as the gold standard for glucose concentration.
8. The Sample Size for the Training Set
The document does not mention a "training set" in the context of device development or performance evaluation. Blood glucose monitoring systems typically do not involve machine learning algorithms that require separate training sets in the way AI/ML medical devices do. The performance data presented is from verification and validation studies on the final product.
9. How the Ground Truth for the Training Set Was Established
Not applicable, as there is no mention or indication of a training set as understood in AI/ML development. The ground truth for the performance studies was established by a laboratory reference instrument (YSI).
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(142 days)
SELFCARE, INC.
Excel™ GE Blood Glucose Test Strips quantitatively measure glucose in fresh capillary whole blood and give results that are comparable to laboratory methods. They are intended for in vitro diagnostic (external) use . by people with diabetes for self-monitoring of blood glucose. The Excel™ GE Blood Glucose Test Strips are designed to be used with Glucometer Elite® Blood Glucose Meters only.
Excel™ GE Blood Glucose Test Strips quantitatively measure glucose in fresh capillary whole blood and give results that are comparable to laboratory methods. They are intended for in vitro diagnostic (external) use by people with diabetes for self-monitoring of blood glucose. The Excel™ GE Blood Glucose Test Strips are designed to be used with Glucometer Elite® Blood Glucose Meters only.
The provided text describes the performance data for the Excel™ GE Blood Glucose Test Strips and Code Strip. Here's an analysis based on your request:
1. Table of Acceptance Criteria and Reported Device Performance
The submission does not explicitly state "acceptance criteria" with numerical thresholds. However, it implicitly demonstrates performance through comparison with established laboratory methods (YSI) and aims for "equivalent performance" to a predicate device. Interpreting the presented data as the reported performance that met the implicit acceptance for substantial equivalence:
| Performance Metric | Reported Device Performance (Excel™ GE Blood Glucose Test Strips) |
|---|---|
| Precision | |
| Glucose Level 1 (e.g., ~45 mg/dL) | SD: 1.2 mg/dL, CV: 2.6-2.7% |
| Glucose Level 2 (e.g., ~80 mg/dL) | SD: 2.2-2.3 mg/dL, CV: 2.7-3.0% |
| Glucose Level 3 (e.g., ~150 mg/dL) | SD: 3.2-3.6 mg/dL, CV: 2.2% |
| Glucose Level 4 (e.g., ~345 mg/dL) | SD: 6.4-7.0 mg/dL, CV: 1.8-2.0% |
| Accuracy (Professional Users vs. YSI) | |
| n | 252-253 |
| Regression Equation (y = mx + b) | y = 0.91x + 0.18 to y = 0.93x + 1.24 |
| Correlation Coefficient (r) | 0.9877 - 0.9949 |
| Standard Error of Estimate (Sy.x) | 7.55 - 11.45 |
| Range | 51 - 374 mg/dL |
| Accuracy (Lay Users vs. YSI) | |
| n | 128 |
| Regression Equation (y = mx + b) | y = 0.92x + 6.99 to y = 0.95x + 3.92 |
| Correlation Coefficient (r) | 0.9883 - 0.9941 |
| Standard Error of Estimate (Sy.x) | 8.31 - 11.38 |
| Range | 51 - 374 mg/dL |
2. Sample Size for the Test Set and Data Provenance
- Precision Study:
- Sample Size: 20 for each glucose level, on each meter model (total of 20 x 4 x 2 = 160 tests, not distinct samples). The text states "20 samples" implying 20 distinct blood samples, each tested across 4 glucose levels and two meter models.
- Data Provenance: Not specified, but described as a "laboratory study."
- Accuracy Studies (Professional and Lay Users):
- Sample Size:
- Professional Users: 252 (Model 3901A) and 253 (Model 3901M) patient samples.
- Lay Users: 128 patient samples.
- Data Provenance: "128 patients with diabetes at three clinical centers." This indicates a prospective clinical study involving actual patient samples. The country of origin is not specified.
- Sample Size:
3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications
Not applicable. This device is an in vitro diagnostic (IVD) for measuring blood glucose. The "ground truth" is established by a reference laboratory method, not human expert interpretation of images or clinical findings.
4. Adjudication Method for the Test Set
Not applicable. As noted above, the ground truth is established by a laboratory reference method (YSI), not through human adjudication of differing interpretations.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size
No. This is an IVD device for measuring blood glucose, not an imaging device or AI-assisted diagnostic tool that would typically involve a multi-reader multi-case study. The performance is assessed against a laboratory reference method and compared to a predicate device.
6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done
Yes, in essence, the device's performance (Excel™ GE Blood Glucose Test Strips used with Glucometer Elite® Glucose Meters) is evaluated in a standalone manner against the YSI laboratory reference method. The "algorithm" here is the combined chemistry and meter reading. The accuracy studies demonstrate the device's performance without human interpretation influencing the measurement result itself, though human professionals and lay users perform the blood application.
7. The Type of Ground Truth Used
- Precision Study: The "ground truth" for precision is the mean glucose value obtained by the device itself, allowing for calculation of standard deviation and coefficient of variation.
- Accuracy Studies: The "ground truth" was established using a YSI (Yellow Springs Instruments) laboratory method, which is a recognized reference standard for glucose measurement.
8. The Sample Size for the Training Set
The document does not explicitly mention a "training set" in the context of machine learning or AI algorithm development. For this type of IVD, the development process typically involves optimizing the strip chemistry and meter calibration using various samples, but these are not usually referred to as a "training set" in the same way as for AI. The data presented are performance validation data.
9. How the Ground Truth for the Training Set Was Established
As no specific "training set" for an AI or machine learning algorithm is mentioned, this question is not directly applicable. For the development of the test strip and meter, the ground truth for calibration and initial development would also typically rely on established laboratory reference methods like YSI.
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(34 days)
SELFCARE, INC.
The Ovulation Predictor test is used for the qualitative measurement of LH and the detection of LH surge in a woman's urine as an aid in conception by accurately and reliably predicting ovulation. The Ovulation Predictor test is intended for use outside the body (in vitro diagnostic use) by women at home. The Ovulation Predictor test is an over the counter (OTC) device that will be sold under the name Inverness Medical Early Ovulation Predictor, an under various private labels as One Step Ovulation Predictor or Ovulation Predictor.
The Ovulation Predictor test is used for the qualitative measurement of LH and the detection of LH surge in a woman's urine as an aid in conception by accurately and reliably predicting ovulation. The Ovulation Predictor test is intended for use outside the body (in vitro diagnostic use) by women at home. The Ovulation Predictor test is an over the counter (OTC) device that will be sold under the name Inverness Medical Early Ovulation Predictor, an under various private labels as One Step Ovulation Predictor or Ovulation Predictor. The technological characteristics are the same because both devices are One-step urine tests that measure LH immunochromatographically, and have the same safety and effectiveness.
The provided text describes the K991386 submission for the Early Ovulation Predictor (stick), One Step Ovulation Predictor (stick), and Ovulation Predictor (stick). Here's a breakdown of the acceptance criteria and study information:
Acceptance Criteria and Reported Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| 99% accuracy | 99% accuracy |
Explanation: The document explicitly states, "Both devices are 99% accurate," referring to the new device and the predicate device. This establishes the 99% accuracy as the critical performance metric for substantial equivalence.
Study Information:
1. Sample size used for the test set and the data provenance:
- Test Set Sample Size: Not specified. The document generally refers to "clinical studies tests" without providing specific numbers for the test set.
- Data Provenance: Not specified. It's unclear if the data was retrospective or prospective, or the country of origin.
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Not specified. The document does not describe the nature of clinical studies in enough detail to determine how ground truth was established, nor does it mention experts.
3. Adjudication method for the test set:
- Not specified. There is no information regarding any adjudication process for the test set.
4. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:
- No, an MRMC study was not done. This device is an in-vitro diagnostic (IVD) for home use, which typically does not involve human readers in the same way an imaging AI device would. The core claim is about the device's ability to detect LH levels, not about assisting human interpretation of complex medical data.
5. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:
- Yes, by nature. The device is a "One-step urine test that measure LH immunochromatographically," intended for home use by women. It provides a direct result (qualitative measurement of LH), meaning its performance is inherently standalone, without a "human-in-the-loop" to interpret an algorithm's output. The comparison is between the new device and a predicate device, both operating as standalone tests.
6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- Implied ground truth related to LH detection. While not explicitly stated, the ground truth would likely be established through a validated laboratory method for measuring Luteinizing Hormone (LH) levels in urine. This would serve as the reference standard against which both the new device and the predicate device's results are compared to determine their "accuracy" in detecting LH surge.
7. The sample size for the training set:
- Not specified. The document only mentions "Laboratory and clinical studies tests" without detailing training sets.
8. How the ground truth for the training set was established:
- Not specified. As the training set size and characteristics are not provided, the method for establishing its ground truth is also unknown. It would presumably involve similar laboratory methods for LH detection as the ground truth for the test set.
In summary, the provided submission focuses on establishing substantial equivalence to a predicate device (ClearPlan® Easy ovulation test) based on identical technological characteristics and demonstrated equivalent performance (99% accuracy) through laboratory and clinical studies. However, detailed methodological information regarding sample sizes, ground truth establishment, and study design elements common in more complex AI/imaging device submissions is largely absent.
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(28 days)
SELFCARE, INC.
The Ovulation Predictor test is used for the qualitative measurement of LH and the detection of LH surge in a woman's urine as an aid in conception by accurately and reliably predicting ovulation. The Ovulation Predictor test is intended for use outside the body (in vitro diagnostic use) by women at home. The Ovulation Predictor test is an over the counter (OTC) device that will be sold under the name Inverness Medical Early Ovulation Predictor, and under various private labels as Early Ovulation Predictor or Ovulation Predictor.
The Ovulation Predictor test is used for the qualitative measurement of LH and the detection of LH surge in a woman's urine as an aid in conception by accurately and reliably predicting ovulation. The Ovulation Predictor test is intended for use outside the body (in vitro diagnostic use) by women at home. The Ovulation Predictor test is an over the counter (OTC) device that will be sold under the name Inverness Medical Early Ovulation Predictor, and under various private labels as Early Ovulation Predictor or Ovulation Predictor.
The provided text describes an Ovulation Predictor (cassette) device. Here's an analysis of the acceptance criteria and the study that proves the device meets them:
1. Table of Acceptance Criteria and Reported Device Performance:
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Accuracy | 99% accuracy |
2. Sample Size Used for the Test Set and Data Provenance:
- Sample Size: Not explicitly stated. The text only mentions "Laboratory and clinical studies tests."
- Data Provenance: Not explicitly stated. The text does not specify the country of origin of the data or whether the studies were retrospective or prospective.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications:
- Number of Experts: Not mentioned.
- Qualifications: Not mentioned.
4. Adjudication Method for the Test Set:
- The text does not mention any adjudication method.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
- Was it done?: No. This device is an in-vitro diagnostic test for qualitative measurement of LH, not an imaging device requiring human reader interpretation in the same way as an MRMC study. The comparison was against a predicate device's performance.
- Effect Size: Not applicable.
6. Standalone (Algorithm Only) Performance:
- Was it done?: Yes. The "Summary of Performance Data" states that "Laboratory and clinical studies tests demonstrate that Ovulation Predictor (cassette) provides equivalent performance to the ClearPlan® Easy ovulation test." The reported 99% accuracy is for the device itself.
7. Type of Ground Truth Used:
- The ground truth is implied to be based on the established accuracy and performance of the predicate device (ClearPlan® Easy ovulation test). For ovulation prediction tests, the ground truth for "accuracy" typically refers to the device's ability to correctly identify the LH surge when compared to a reference method or clinical ovulation event. The text does not specify the exact method used to establish ground truth (e.g., direct measurement of LH in a lab setting, correlation with actual ovulation confirmed by other means).
8. Sample Size for the Training Set:
- Not applicable. This device is described as an immunochromatographic assay, not an AI or machine learning model that requires a training set in the conventional sense. Its "training" would be more akin to assay development and optimization rather than machine learning training.
9. How Ground Truth for the Training Set Was Established:
- Not applicable, as there is no mention of a machine learning training set.
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(29 days)
SELFCARE, INC.
The FastTake® Compact Blood Glucose Monitoring System is intended to be used for the quantitative measurement of glucose in fresh capillary whole blood. The FastTake® System is intended for use outside the body (in vitro diagnostic use) by diabetics at home as an aid to monitor the effectiveness of diabetes control.
The FastTake® system includes four main components:
- · FastTake® Test Strips
- FastTake® Compact Blood Glucose Meter .
- · FastTake® Control Solution
- · Penlet II or Penlet Plus lancing device and FinePoint lancets.
Here's an analysis of the provided text regarding the FastTake® Compact Blood Glucose Monitoring System's acceptance criteria and studies:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Visual confirmation of sufficient blood sample on test strip | Patients detected under-filled and correctly filled strips with 99% accuracy. |
| Ability of intended users (diabetic patients) to utilize the new feature independently | Demonstrated ability of individual patients to test independently. |
| Equivalence in performance to the unmodified predicate device | Verification and validation tests demonstrate that the modified system has equivalent performance to the unmodified FastTake Compact Blood Glucose Monitoring System. |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size: 19 diabetic patients.
- Data Provenance: The study was a "consumer-use study," implying real-world or simulated home use. The location/country of origin is not explicitly stated, but Selfcare, Inc. is located in Waltham, MA, USA, suggesting a US-based study. It was a prospective study as it evaluated users interactively with the device feature.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
This information is not provided in the given text. The study focused on consumer perception and ability to detect correct filling, implying the "ground truth" for the confirmation window's effectiveness was based on the physical state of the strip (correctly filled vs. under-filled), which would likely be objectively observable or determined by the study administrators rather than expert consensus on a diagnosis.
4. Adjudication Method for the Test Set
This information is not provided in the given text. As the "ground truth" likely related to objective observation of the test strip filling, a formal adjudication method like 2+1 or 3+1 might not have been necessary for this specific performance metric.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
No, a MRMC comparative effectiveness study was not done. The study was a consumer-use study to evaluate the usability and effectiveness of a visual confirmation window, not a comparison of human reader performance with and without AI assistance for diagnosis.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
This device, a blood glucose monitoring system, is a diagnostic device that requires human interaction (applying blood to the strip). There is no mention of a standalone algorithm-only performance study independent of human use for the FastTake® Compact Blood Glucose Monitoring System as described. The "confirmation window" is a visual aid for the user, not an automated algorithm to interpret results.
7. The Type of Ground Truth Used
The ground truth for the consumer-use study regarding the confirmation window was based on the adequacy of sample filling (i.e., whether the strip was correctly filled or under-filled). This is an objective characteristic of the test strip's physical state rather than a medical diagnosis.
8. The Sample Size for the Training Set
This information is not applicable and therefore not provided. This device is not an AI/ML-based system requiring a training set in the typical sense. The "FastTake® strips with the new confirmation window feature" were evaluated, implying a design change rather than a learned model.
9. How the Ground Truth for the Training Set Was Established
This information is not applicable as there is no training set for an AI/ML model for this device.
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