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The Spacelabs Medical, mCare 300, Model 91220, Vital Signs Monitor is indicated for use in adult, pediatric and neonate patient populations wherever there is a need for the monitoring of ECG, respiration, invasive or noninvasive blood pressures, body temperature, functional arterial oxygen saturation, or expired or minimum inspire CO2.
The Spacelabs Medical, mCare 300, Model 91220, Vital Signs Monitor is a prescription device intended to be used by healthcare professionals in all areas of a healthcare facility.

The Spacelabs Medical mCare 300 Vital Signs Monitor Model 91220 (mCare 300), is a portable patient monitoring device intended to be used by clinicians and medically qualified personnel for monitoring physiological parameters; ECG, respiration, noninvasive and invasive blood pressure, body temperature, SpO2, or End tidal CO2 or ETCO2; in neonatal, of pediatric and adult patients.
This device is designed to be used in all general hospital and alternate care environments. This device is available for sale only upon the order of a physician or licensed health care professional.

The provided text describes a 510(k) submission for the Spacelabs Medical mCare 300 Vital Signs Monitor, Model 91220. The submission is primarily focused on a change in the Non-Invasive Blood Pressure (NIBP) module from a Welch Allyn module to an Omron M3200 NIBP module.

Based on the information provided, here's a breakdown regarding acceptance criteria, performance, and study details:

1. A table of acceptance criteria and the reported device performance

The document does not explicitly state specific quantitative acceptance criteria (e.g., accuracy ranges for blood pressure readings) in the provided text. It mentions that the NIBP module revision was "validated through rigorous testing that, in part, supports the compliance of the mCare 300 to the various standards identified in this submission." However, the exact standards or performance metrics are not detailed.

Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document does not provide details on the sample size used for the test set or the data provenance. It only broadly refers to "rigorous testing."

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

No information is provided regarding experts, their number, or qualifications for establishing ground truth. The testing mentioned appears to be related to technical validation of the NIBP module's performance against standards, rather than expert-driven clinical evaluation for diagnostic accuracy.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

No information is provided regarding any adjudication methods.

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

This is not applicable. The device is a vital signs monitor, not an AI-assisted diagnostic tool for human readers. Therefore, an MRMC comparative effectiveness study involving AI assistance would not be relevant.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

This is not applicable in the context of an NIBP module in a vital signs monitor. The performance of the NIBP module itself is typically assessed in isolation (i.e., its accuracy in measuring blood pressure) through technical and physiological testing. The document states "The NIBP module revision to the mCare 300 was validated through rigorous testing," implying standalone validation of the module's performance.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

The document does not explicitly state the type of ground truth. For NIBP measurements, the "ground truth" would typically involve invasive arterial pressure measurements or highly accurate non-invasive reference methods to compare against the device's readings as part of its validation against relevant performance standards. The general statement "supports the compliance of the mCare 300 to the various standards identified in this submission" suggests that the ground truth would be defined by the requirements of those standards (e.g., ISO, AAMI standards for NIBP accuracy).

8. The sample size for the training set

This is not applicable. The device is a vital signs monitor, and the submission concerns a hardware module change and associated software validation, not a machine learning model that requires a training set.

9. How the ground truth for the training set was established

This is not applicable, as there is no training set for a machine learning model.

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