(218 days)
The ABPM 7100 is an automated, microprocessor controlled ambulatory blood pressure monitor (ABPM) which records, accumulates and stores: heart beat (rate), systolic and diastolic data of an individual patient (in the patient's environment) for a session which may last 24 hours. Ambulatory monitoring is not supported for the 14-20 cm cuff size.
It is used with a standard upper-arm cuff for blood pressure measurement.
The ABPM 7100 in combination with the Hypertension Management Software (HMS) provides a derived ascending aortic blood pressure wave form and a range of central indices. It is used in those adult patients, where information related to the ascending aortic blood pressure is desired, but in the physician, the risk of cardiac catheterization procedure or other invasive monitoring may outweigh the benefits.
The ABPM 7100 applies the oscillometric principle for blood pressure measurements. The ABPM 7100 consists of the following hardware:
- the ABPM 7100 recorder -
- the brachial blood pressure cuff -
The ABPM 7100 is available with five different cuff sizes to adapt to the patient's arm size.
Initially, the device is prepared for a new patient and measurements are started. Measurement data is recorded and stored in the device's memory. The data can then be transmitted to a computer in the physician's office via Bluetooth or cable for storage, presentation and analysis.
Central Blood Pressure (CBP) calculation is realized through Pulse Wave Analysis, conducted by the Hypertension Management Software with CBP Upgrade.
Here's an analysis of the acceptance criteria and study details for the ABPM 7100, Hypertension Management Software version 5.0, based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
The device's performance was evaluated against the accuracy requirements of ISO 81060-2.
| Criterion | Acceptance Criteria | Reported Device Performance (Same Arm Sequential Measurements) | Reported Device Performance (Ambulatory Monitoring - Ergometer Validation) | Judgment (Both) |
|---|---|---|---|---|
| Criterion 1: Mean error of determination | ||||
| SBP Mean Error | $\pm 5.0$ mmHg | 1.9 mmHg | -0.2 mmHg | Pass |
| SBP Standard Deviation (within Criterion 1) | $8.0$ mmHg | 6.6 mmHg | 7.2 mmHg | Pass |
| DBP Mean Error | $\pm 5.0$ mmHg | -2.0 mmHg | -1.2 mmHg | Pass |
| DBP Standard Deviation (within Criterion 1) | $8.0$ mmHg | 5.5 mmHg | 6.3 mmHg | Pass |
| Criterion 2: Standard deviation of averaged paired determination per subject | ||||
| SBP Standard Deviation | Maximum permissible: 6.68 mmHg | 5.44 mmHg | 4.00 mmHg | Pass |
| DBP Standard Deviation | Maximum permissible: 6.65 mmHg | 4.48 mmHg | 4.04 mmHg | Pass |
2. Sample Size Used for the Test Set and Data Provenance
The document does not explicitly state the specific number of subjects or measurements used for the test sets (both same arm sequential and ambulatory monitoring). It mentions the accuracy testing covered adults and children (age group 3-12 years) and included the new cuff size (14-20 cm) in the same-arm sequential measurements. The source or country of origin of this clinical data is not specified, but the device manufacturer is based in Germany. The study appears to be prospective as it's a clinical validation performed for regulatory submission.
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 document. For blood pressure measurement device validation, the ground truth is typically established by trained technicians or clinicians using validated reference devices.
4. Adjudication Method for the Test Set
The document mentions "averaged paired determination per subject" but does not detail an adjudication method involving multiple experts for discrepant readings. For blood pressure studies according to ISO 81060-2, typically multiple measurements are taken by trained operators, and statistical methods are applied to assess accuracy, rather than an "adjudication" by experts in the context of diagnostic interpretation.
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, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. This device is a non-invasive blood pressure monitor with software for pulse wave analysis, not an AI-powered diagnostic imaging tool that would typically involve human readers. The primary evaluation is focused on the accuracy of its measurements compared to reference standards.
6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) was Done
Yes, a standalone performance evaluation was done. The accuracy tests (ISO 81060-2) assess the device's (ABPM 7100 hardware and embedded software) ability to accurately measure blood pressure independently. The "software testing" for the Hypertension Management Software (HMS) also falls under standalone validation according to FDA Guidance "General Principles of Software Validation," ensuring the software's functionality and calculations are correct.
7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)
The ground truth for the blood pressure measurements was established by reference to a validated reference blood pressure measurement method, as specified by ISO 81060-2. This standard typically requires simultaneous or sequential measurements using a trained observer with a auscultatory method or another validated reference device.
8. The Sample Size for the Training Set
The document does not mention a training set. This type of medical device (blood pressure monitor) is typically validated against a known standard and its accuracy demonstrated, rather than employing machine learning algorithms that require separate training and test sets. The software verification and validation would be based on functional requirements and technical specifications.
9. How the Ground Truth for the Training Set Was Established
Since there is no mention of a "training set" in the context of machine learning, this question is not applicable. The device's underlying algorithms for blood pressure measurement are based on established oscillometric principles and are not described as being "trained" in a conventional machine learning sense from a dataset with established ground truth labels.
§ 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).