(46 days)
The A&D Medical UA-1000 family digital blood pressure monitors are intended for used by adults with 12 years older to measure the systolic and diastolic blood pressure and pulse rate.
Measure blood pressure (systolic and diastolic) and pulse rate.
UA-1000 family uses an inflatable cuff which is wrapped around the patient's upper arm. The cuff is inflated automatically by an internal pump in the device. The systolic and diastolic blood pressures are determined by oscillometric method. The deflation rate is controlled by the internal electronic-controlled exhaust valve. There is a quick exhaust mechanism so that the pressure of the cuff can be completely released. There is a maximum pressure safety setting at 300mmHg. The device will not inflate the cuff higher than 300mmHg. The UA-1000 family will turn on an irregular heartbeat indicator if an irregular heartbeat was detected during the measurement process. At the end of the measurement, the systolic and diastolic pressures with pulse rate are shown on the LCD and stored in the device memory. For UA-1030T, the results is also annoucment in voice. The cuff is also deflated automatically at the same time. There are two memory banks to separate the measurements in the morning time and in the evening time. UA-1020 and UA-1030T can conduct average function for 3 consecutive measurmenets automatically.
Here's an analysis of the provided text regarding the A&D Medical UA-1000 Family Digital Blood Pressure Monitors, structured to answer your questions:
Acceptance Criteria and Device Performance
1. Table of Acceptance Criteria and Reported Device Performance
The provided text focuses on demonstrating substantial equivalence to predicate devices rather than detailing specific acceptance criteria and their direct fulfillment through a standalone study. The key "acceptance criteria" inferred here are the Accuracy specifications, which are stated as unchanged from the predicate devices.
| Parameter | Acceptance Criteria (Predicate) | Reported Device Performance (UA-1000 Family) |
|---|---|---|
| Accuracy | BP: +/- 3mmHg or +/- 2% of measured value, whichever is greater | No change - the same (implicitly meets predicate's criteria) |
| Pulse: +/- 5 % (pulse) | No change - the same (implicitly meets predicate's criteria) | |
| IHB (Irregular Heartbeat Detection) | More than +/-25% to the mean interval of all pulse intervals | No change - the same (implicitly meets predicate's criteria) |
Note: The document explicitly states "No change - the same" for these critical performance parameters, indicating that the UA-1000 family is expected to perform identically to the previously cleared predicate devices for which these criteria were established and met. No new performance data for these specific criteria are provided in this summary.
2. Sample Size Used for the Test Set and Data Provenance
The provided 510(k) summary does not contain information about the sample size used for a test set or the data provenance (e.g., country of origin, retrospective/prospective) for proving device performance. The submission relies on establishing substantial equivalence to previously cleared devices rather than providing new clinical or performance study data for the UA-1000 family.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications
The 510(k) summary does not mention the use of experts or the establishment of ground truth for a test set. As noted above, the submission focuses on substantial equivalence. For blood pressure monitors, ground truth is typically established using a reference method (e.g., auscultatory readings by trained observers) rather than expert consensus on images or data.
4. Adjudication Method for the Test Set
The 510(k) summary does not describe any adjudication method for a test set.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. This type of study is typically used for diagnostic imaging devices where human readers interpret medical images with and without AI assistance to assess the AI's impact on diagnostic accuracy. This is not applicable to a blood pressure monitor.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
The concept of "standalone performance" as typically applied to AI algorithms (without human-in-the-loop) does not directly apply in this context for a blood pressure monitor. The device's primary function is to measure blood pressure using an oscillometric method. Its "standalone performance" is inherently its ability to accurately measure blood pressure on its own. The accuracy specifications (BP: +/- 3mmHg or +/- 2%; Pulse: +/- 5%) are the standalone performance metrics. The document states that these are "No change - the same" as the predicate devices, implying prior validation of these metrics.
7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)
For blood pressure monitors, the ground truth for accuracy studies is typically established by simultaneous measurements using a recognized reference standard, such as:
- Auscultation by trained observers: This involves two or more trained observers simultaneously taking blood pressure readings using a mercury sphygmomanometer (or an equivalent validated device) while being blinded to each other's readings and the test device's readings.
- Intra-arterial measurements: In highly controlled research settings, direct intra-arterial measurements can serve as the gold standard.
The provided 510(k) summary does not detail how the ground truth was established for the original predicate devices or for any implied re-validation of the UA-1000 family. It simply states that the "Accuracy" is "No change - the same" as the predicates, meaning the original ground truth methods used for the predicates are presumed to apply.
8. The Sample Size for the Training Set
The 510(k) summary does not provide any information regarding a training set sample size. This type of information would be relevant for devices employing machine learning or AI algorithms that require training data. While the device uses an oscillometric algorithm, it is a well-established method not typically referred to as an "AI algorithm" in this context that undergoes iterative training with a distinct "training set" in the modern sense of deep learning.
9. How the Ground Truth for the Training Set Was Established
As there is no mention of a training set in the context of an AI/ML algorithm requiring separate training and testing phases, this question is not applicable based on the provided document. The oscillometric method is a deterministic algorithm rather than a learned one in the contemporary AI sense.
§ 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).