(95 days)
The Microlife Upper Arm Automatic Digital Blood Pressure Monitor, Model BP3MQ1-2D is a device intended to measure the systolic and diastolic blood pressure and pulse rate of an adult individual by using a non-invasive oscillometric technique in which an inflatable cuff is wrapped around the upper arm.
The device detects the appearance of atrial fibrillation during measurement and gives a warning signal with the reading once the atrial fibrillation is detected.
Microlife Upper Arm Automatic Digital Blood Pressure Monitor, Model BP3MQ1-2D is designed to measure the systolic and diastolic blood pressure and pulse rate of an individual by using a non-invasive MAM (Microlife Average Mode) technique in which an inflatable cuff is wrapped around the upper arm. Our method to define systolic and diastolic pressure is similar to the auscultatory method but uses an electronic capacitive pressure sensor rather than a stethoscope and mercury manometer. The sensor converts tiny alterations in cuff pressure to electrical signals, by analyzing those signals to define the systolic and diastolic blood pressure and calculating pulse rate, which is a well - known technique in the market called the "oscillometric method".
The device detects the appearance of atrial fibrillation during measurement and the atrial fibrillation symbol "~ " is displayed on the LCD screen if any atrial fibrillation signal has been detected.
Here's a detailed breakdown of the acceptance criteria and the study proving the device meets them, based on the provided text:
Acceptance Criteria and Device Performance
The core acceptance criteria for the atrial fibrillation (AF) detection function of the Microlife Upper Arm Automatic Digital Blood Pressure Monitor, Model BP3MQ1-2D, are related to its sensitivity and specificity in detecting AF when compared to an electrocardiogram (ECG) as ground truth. While no explicit quantitative "acceptance criteria" are stated as a minimum threshold in the document, the studies demonstrate the device's performance against expected clinical measures.
The studies compared two methods of analyzing the BP3MQ1-2D readings: individual readings and combined (three sequential) readings. The combined readings generally show higher performance, likely reflecting how a user might be instructed to use the device (e.g., taking multiple readings for confirmation).
| Acceptance Criteria (Implied) | Individual Readings Performance (Combined TRIPPS 1.0 & 1.1) | Combined Three Sequential Readings Performance (Combined TRIPPS 1.0 & 1.1) |
|---|---|---|
| Sensitivity for AF Detection | 96.1% (95% CI: 94-98%) | 97.7% (95% CI: 91-100%) |
| Specificity for AF Detection | 85.2% (95% CI: 83-88%) | 87.7% (95% CI: 83-91%) |
Note: The document also references a prior test of the AfibAlert™ algorithm (the underlying AF detection component), which showed 92% sensitivity and 96% specificity against the MIT-BIH AFIB database. This indicates a pre-existing level of performance for the core algorithm, which was then validated within the new device.
Study Details Proving Device Meets Acceptance Criteria:
2. Sample size used for the test set and the data provenance:
- TRIPPS 1.0: 205 subjects
- TRIPPS 1.1: 157 subjects
- Combined Studies: 362 subjects (205 + 157)
- Data Provenance: The document does not explicitly state the country of origin for the TRIPPS studies. The studies are described as "clinical trials," implying prospective data collection for the purpose of validating the device. The MIT-BIH AFIB database for the AfibAlert™ algorithm is a publicly available, retrospective database of ECG recordings, but this was for the underlying algorithm, not the device's clinical validation.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- The document states that the ECG readings were "read in a blinded fashion" to establish ground truth.
- Number of experts: Not explicitly stated.
- Qualifications of experts: Not explicitly stated.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
- The document does not explicitly describe an adjudication method for disagreements in ECG interpretation, only that ECG readings were obtained and "read in a blinded fashion."
5. 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 comparative effectiveness study involving human readers with and without AI assistance was not done.
- The clinical studies described (TRIPPS 1.0 and 1.1) were standalone performance studies of the device's AF detection capabilities against an ECG reference.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
- Yes, a standalone performance evaluation was conducted. The entire purpose of the clinical trials (TRIPPS 1.0 and 1.1) was to evaluate the device's automatic AF detection capabilities (algorithm only) compared to the ECG ground truth. The tables provided (Table 1 and Table 2) directly present the standalone performance of the BP3MQ1-2D in detecting AF.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- Electrocardiogram (ECG) readings. For the clinical validation studies (TRIPPS 1.0 and 1.1), the rhythm determined by an ECG was used as the ground truth.
8. The sample size for the training set:
- The document does not specify the sample size for any training set related to the BP3MQ1-2D's algorithm. It mentions that the "AfibAlert™ algorithm was tested using published available annotated MIT-BIH AFIB database," which would be a test or validation set for that specific algorithm, not necessarily a training set for the overall device's AF detection function. For the BP3MQ1-2D itself, no training set information is provided in this document.
9. How the ground truth for the training set was established:
- As the training set information is not provided for the BP3MQ1-2D's AF detection algorithm, the method for establishing its ground truth also cannot be determined from this document. If we assume the AfibAlert™ algorithm was "trained" on data, the MIT-BIH AFIB database is mentioned as an "annotated" database, implying expert annotations for ground truth, but this is used for testing and not explicitly stated as training.
§ 870.1130 Noninvasive blood pressure measurement system.
(a)
Identification. A noninvasive blood pressure measurement system is a device that provides a signal from which systolic, diastolic, mean, or any combination of the three pressures can be derived through the use of tranducers placed on the surface of the body.(b)
Classification. Class II (performance standards).