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The Welch Allyn ABPM 6100 is a non-invasive oscillometric ambulatory blood pressure monitor that is to be used with ABPM 6100 Software, a PC based computer program. The ABPM 6100 is capable of recording and displaying up to 250 measurements of systolic and diastolic blood pressure and heart rate. It is intended for use as an aid or adjunct to diagnosis and treatment when it is necessary to measure adult or pediatric patients systolic and diastolic blood pressures over an extended period of time. The system is only for measurement, recording, and display. It makes no diagnosis.

The Welch Allyn ABPM 6100 is a microprocessor based ambulatory blood pressure monitor that uses an oscillometric step deflation technique to determine blood pressure. An internal electric pump is used to inflate the cuff and two valves control deflation. During cuff deflation, small cuff pressure changes (resulting from arterial blood pressure pulses) are analyzed by the microprocessor, in order to determine the blood pressure. The Welch Allyn ABPM 6100 has the ability to make blood pressure determinations at predetermined intervals (normally from a schedule determined by the physician), or on demand (by using the stop/start key). Each reading is stored in memory, allowing the physician to download all the results obtained during the study period after the study has concluded to be analyzed by PC software. The readings can be displayed on the LCD or the LCD can be disabled to prevent the patient from seeing the readings (see attachment I for photographs of the device).

The Welch Allyn ABPM 6100 is an ambulatory blood pressure monitor. The acceptance criteria and supporting study are described below.

1. Acceptance Criteria and Reported Device Performance

The device's performance is demonstrated by its compliance with recognized standards. The standards themselves contain the acceptance criteria for blood pressure monitors. The submission states that the device meets the requirements called out in these standards.

2. Sample Size and Data Provenance

The submission does not explicitly state the sample size used for any test set or the data provenance (e.g., country of origin, retrospective or prospective nature). The claim of meeting the standards implies that testing was conducted, but details are not provided.

3. Number and Qualifications of Experts for Ground Truth

Details regarding the number and qualifications of experts used to establish ground truth are not provided in the document.

4. Adjudication Method

The adjudication method is not mentioned in the provided text.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

There is no mention of a Multi-Reader Multi-Case (MRMC) comparative effectiveness study, nor any effect size information regarding human readers' improvement with or without AI assistance. This is expected as the device is a blood pressure monitor, not an AI diagnostic tool for image interpretation.

6. Standalone Performance Study

The submission indicates that the device's performance aligns with the requirements of the listed standards (EN60601-1, EN60601-1-1, EN60601-1-2, EN60601-2-30, and AAMI SP10). These standards typically involve standalone testing of the device's accuracy and functionality. Therefore, a standalone performance study was done by virtue of meeting these standards, although specific details of the study are not included in the provided text.

7. Type of Ground Truth Used

For blood pressure monitors, the ground truth typically involves a reference blood pressure measurement device (e.g., a mercury sphygmomanometer used by trained personnel) against which the device under test is compared. The specific type of ground truth used is not explicitly stated in the document, but it would align with the methodologies prescribed by the AAMI SP10 standard for automated sphygmomanometers, which involves comparison to a simultaneously measured reference.

8. Sample Size for the Training Set

The device is a non-AI/ML blood pressure monitor. Therefore, there is no training set in the context of machine learning. Its operation is based on an oscillometric step deflation technique and microprocessor analysis of cuff pressure changes.

9. How Ground Truth for the Training Set Was Established

As noted in point 8, this device does not utilize a training set in the machine learning sense. The underlying physiological principles and algorithms are established through extensive medical and engineering research, not by "training" with a dataset that requires specific ground truth establishment.

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