(28 days)
Indicated for use by health care professionals whenever there is a need for monitoring the physiological parameters of patients. Intended for monitoring and recording of and to generate alarms for multiple physiological parameters of adults, pediatrics and neonates in hospital environments. The MP2, MP5, MP5T, MP5SC, X2, MP30, MP40, and MP50 are additionally intended for use in transport situations within hospital environments. The MP2, X2 and MP5 are also intended for use during patient transport outside of a hospital environment.
The Philips IntelliVue Patient Monitor family comprises the multi-parameter patient monitor models: MP2, X2, MP5, MP5T, MP5SC, MP20, MP30, MP40, MP50, 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 pressure, etc., generate alarms, record physiological signals, store derived data, and communicate derived data and alarms to central stations via the Intellivue Clinical Network. The subject modification is the introduction of the models MX600 and MX700 together with a new model of the flexible module server. Additionally the software revision H.04 is made available for the entire IntelliVue Patient Monitors family.
This 510(k) summary describes Philips IntelliVue patient monitors, including the MX600 and MX700 models and software revision H.04. The submission demonstrates substantial equivalence to previously cleared Philips IntelliVue monitors.
Here's an analysis of the provided text in relation to acceptance criteria and study details:
1. Table of Acceptance Criteria and Reported Device Performance
The document does not explicitly present a table of acceptance criteria with corresponding performance metrics. Instead, it states:
"Verification, validation, and testing activities establish the performance, functionality, and reliability characteristics of the modified devices with respect to the predicate. Testing involved system level and regression tests as well as testing from the hazard analysis. Pass/Fail criteria were based on the specifications cleared for the predicate devices and test results showed substantial equivalence. The results demonstrate that the Philips IntelliVue patient monitors meet all reliability requirements and performance claims."
This indicates that the performance of the new devices (MX600, MX700, and software H.04) was assessed against the established specifications and performance of the predicate devices. The "acceptance criteria" are implicitly the already-cleared specifications of the predicate devices, and the "reported device performance" is that the new devices met these requirements, thus showing substantial equivalence.
Without explicit numerical or qualitative criteria and performance values, a table cannot be constructed with specific details. The general statement is that performance and reliability met the predicate device's standards.
2. Sample Size Used for the Test Set and Data Provenance
The document does not specify a distinct "test set" sample size in terms of patient data or case numbers. The testing appears to be centered on system-level and regression testing of the devices, rather than a clinical trial with a specific patient dataset.
- Sample Size: Not specified in terms of patient numbers or clinical cases. The testing appears to be focused on device functionality and software rather than a clinical dataset for a specific diagnostic accuracy.
- Data Provenance: Not specified. Given the nature of the device (a multi-parameter patient monitor), "data provenance" in the sense of country of origin of patient data is not directly relevant to the described testing, which focuses on hardware and software functionality. The testing is internal verification and validation.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications
This information is not provided. The testing described is verification and validation against pre-defined specifications and reliability requirements, rather than a study requiring expert-established ground truth on clinical data.
4. Adjudication Method for the Test Set
Not applicable. There's no mention of a human-reviewed "test set" requiring adjudication. The testing described is focused on the device's technical performance against established specifications.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done, and Effect Size
No, a multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly mentioned. The submission focuses on device functionality and substantial equivalence to predicate devices, not on comparing human reader performance with and without AI assistance. The device is a patient monitor, not an AI-powered diagnostic tool in the sense that would typically warrant such a study.
6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study Was Done
The device itself (patient monitor with physiological measurement capabilities) is a standalone device in its core function (measuring and displaying physiological parameters, alarming, etc.). The software revision H.04 would have undergone standalone testing for its algorithms (e.g., arrhythmia detection, ST segment analysis) to ensure they meet their specifications. However, the document doesn't provide specific details on such standalone studies in terms of methodology or results, other than stating that "test results showed substantial equivalence" and "meet all reliability requirements and performance claims."
7. Type of Ground Truth Used
The "ground truth" for this type of device and submission is its adherence to pre-defined technical specifications, performance requirements, and reliability standards as established for the predicate devices. This isn't clinical "ground truth" derived from expert consensus, pathology, or outcomes data in the usual sense of a diagnostic AI device. The ground truth refers to whether the device correctly measures, displays, and alarms according to its design and the predicate's performance.
8. Sample Size for the Training Set
Not applicable. This submission concerns a patient monitor and its software, not a machine learning or AI algorithm that requires a specific training set in the conventional sense. The "training" for such a system would be its development and rigorous testing against engineering specifications.
9. How the Ground Truth for the Training Set Was Established
Not applicable, as there is no mention of a "training set" in the context of machine learning. The "ground truth" for the device's development would be its engineering and performance specifications.
§ 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.