(19 days)
The monitors are indicated for use by health care professionals whenever there is a need for monitoring the physiological parameters of patients. The monitors are intended to be used for monitoring and recording of, and to generate alarms for, multiple physiological parameters of adults, pediatrics, and neonates. The monitors are intended for use by trained healthcare professionals in a hospital environment. The monitors are only for use on one patient at a time. They are not intended for home use. Not therapeutic devices. The monitors are for prescription use only.
The Philips IntelliVue Patient Monitor family comprises the multi-parameter patient monitor models: X2, MP2, MP5, MP5T, MP5SC, MP20, MP30, MP40, MP50, MP60, MP70, MP80, MP90, MX600, MX700 and MX800 IntelliVue Patient Monitors that consist of display units including built-in or separate flat panel displays and central processing units (CPU) and physiological measurement modules. All monitors share the same system architecture and exactly the same software is executed on each monitor. The IntelliVue Patient Monitors measure multiple physiological parameters such as surface ECG; invasive and non-invasive generate alarms, record physiological pressure, a etc., signals, store derived data, and communicate derived data and central stations via the IntelliVue Clinical alarms to Network. The subject modification extends the capability of IntelliVue MP40, MP50, MP60, MP70, MP80, MP90, and MX600, MX700 and MX800' patient monitors to communicate with the new NMT module. The IntelliVue NMT Module is intended to be used as an objective neuromuscular transmission monitor, using accelerometry for measuring the muscle contraction following an electrical stimulation of a peripheral nerve. The NMT Module is intended to be used with adult and pediatric patients. The NMT has been added to list for MP20 - MP90, and MX600 -MX800 IntelliVue Patient Monitors Additionally the software revision J.08 is made available for the entire IntelliVue Patient Monitors family.
The Philips IntelliVue Patient Monitors (models X2, MP2, MP5, MP5T, MP5SC, MP20, MP30, MP40, MP50, MP60, MP70, MP80, MP90, MX600, MX700, and MX800) with software revision J.08, and the IntelliVue NMT Module, underwent verification, validation, and testing activities.
1. Table of Acceptance Criteria and Reported Device Performance:
The provided document does not explicitly list specific numerical acceptance criteria or detailed performance metrics for each parameter. Instead, it states that "Pass/Fail criteria were based on the specifications cleared for the predicate devices and test results showed substantial equivalence." The overall conclusion from this study is that "The results demonstrate that the Philips IntelliVue patient monitors meet all reliability requirements and performance claims."
Therefore, based on the provided text, the table would look like this:
| Acceptance Criteria Category | Reported Device Performance |
|---|---|
| System Reliability | Met all reliability requirements. |
| Performance Claims | Met all performance claims. |
| Functionality | Established. |
| Legally Marketed Predicate Device Specifications | Test results showed substantial equivalence to predicate devices. |
2. Sample Size Used for the Test Set and Data Provenance:
The document does not explicitly state the sample size used for the test set. It mentions "Testing involved system level and as well as testing from the hazard analysis." The data provenance (e.g., country of origin of the data, retrospective or prospective) is not specified.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Those Experts:
The document does not provide information on the number of experts used or their qualifications for establishing ground truth for a test set. The nature of the device (physiological monitors) suggests that "ground truth" would likely be established through physical measurements, calibration standards, or comparisons to known clinical gold standards rather than expert consensus on subjective interpretations of data, as might be the case for imaging devices.
4. Adjudication Method for the Test Set:
The document does not describe any adjudication method.
5. If a Multi-reader Multi-case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs Without AI Assistance:
No MRMC comparative effectiveness study is mentioned, nor is there any discussion of AI assistance or human reader improvement. The device described is a patient monitor, not an AI-assisted diagnostic tool.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:
The "performance" of patient monitors is inherently standalone in terms of data acquisition and initial processing. The document indicates that "Testing involved system level" which would include the device's algorithmic performance. However, there's no explicit separate "standalone" study described as would be the case for a diagnostic algorithm. The device functions as an algorithmic and hardware system to measure and display physiological parameters.
7. The Type of Ground Truth Used:
The document implies that ground truth was established by comparing the modified devices' performance against "specifications cleared for the predicate devices" and other "reliability requirements and performance claims." This suggests that the "ground truth" would be established through a combination of:
- Calibration Standards: For quantitative measurements (e.g., blood pressure, temperature, heart rate).
- Engineering Specifications: For functionality and alarm accuracy.
- Predicate Device Performance: For establishing substantial equivalence.
There is no mention of pathology, expert consensus (in the sense of subjective medical opinion on data interpretation), or outcomes data being directly used to establish ground truth in this summary.
8. The Sample Size for the Training Set:
The document does not mention a "training set" or "training data" in the context of machine learning or AI, as the device is a patient monitor and not a machine learning model requiring such a set.
9. How the Ground Truth for the Training Set Was Established:
As there is no mention of a training set, the method for establishing its ground truth is not applicable.
§ 870.1025 Arrhythmia detector and alarm (including ST-segment measurement and alarm).
(a)
Identification. The arrhythmia detector and alarm device monitors an electrocardiogram and is designed to produce a visible or audible signal or alarm when atrial or ventricular arrhythmia, such as premature contraction or ventricular fibrillation, occurs.(b)
Classification. Class II (special controls). The guidance document entitled “Class II Special Controls Guidance Document: Arrhythmia Detector and Alarm” will serve as the special control. See § 870.1 for the availability of this guidance document.