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The monitor is indicated for use by healthcare professionals whenever there is a need for monitoring the physiological parameters of patients. The monitor is intended to be used for monitoring and recording of, and to generate alarms, for, multiple physiological parameters of adults, pediatrics, and neonates. The monitor is intended for use by trained healthcare professionals in a hospital environment. The monitor is also intended for use during patient transport inside and outside of the hospital environment. The monitor is only for use on one patient at a time. It is not intended for home use. Not a therapeutic device. The monitor is for prescription use only. The ECG measurement is intended to be used for diagnostic recording of rhythm and detailed morphology of complex cardiac complexes (according to AAMI EC 11). ST segment monitoring is intended for use with adult patients only and is not clinically validated for use with neonatal and pediatric patients. The Predictive Temperature unit is intended for use with adult and pediatric patients in a hospital environment. The SSC Sepsis Protocol, in the ProtocolWatch clinical decision support tool, is intended for use with adult patients only. The derived measurement Pulse Pressure Variation (PPV) is intended for use with sedated patients receiving controlled mechanical ventilation and mainly free from cardiac arrhythmia. The PPV measurement has been validated only for adult patients. The transcutaneous gas measurement (tcGas) is restricted to neonatal patients only. BIS is intended for use under the direct supervision of a licensed health care practitioner or by personnel trained in its proper use. It is intended for use on adult and pediatric patients within a hospital or medical facility providing patient care to monitor the state of the brain by data acquisition of EEG signals. The BIS may be used as an aid in monitoring the effects of certain anesthetic agents. Use of BIS monitoring to help guide anesthetic administration may be associated with the reduction of the incidence of awareness with recall in adults during general anesthesia and sedation.

The Philips IntelliVue Patient Monitors family comprises the multiparameter patient monitor series: MP2, X2, MP5, MP5T, MP5SC, MP20, MP30, MP40, MP50, MP60, MP70, MP80, MP90 and MX600, MX700, and MX800. Each monitor consists of a display unit including built-in or separate central processing unit (CPU) and physiological measurement modules. All monitors share the same architecture of CPU units and exactly the same software is executed on each monitor. The monitors measure physiological parameters such as: Sp02, pulse, ECG, arrhythmia, ST, QT, respiration, invasive and noninvasive blood pressure, temperature, CO2, spirometry, C.O., CCO, tcp02/ tcpCO2, S02, Sv02, Scv02, EEG, and BIS. They generate alarms, record physiological signals, store derived data, and communicate derived data and alarms to the central station. IntelliVue series MP2, X2, MP5, MP5T, MP5SC, MP20, and MP30 are robust, portable, lightweight, compact in size and modular in design patient monitors with interfaces to dedicated external measurement devices. Models MP2, X2, MP5, MP5T, and MP5SC also incorporate multiple built-in physiological measurements. IntelliVue series MP40, MP50, MP60, MP70, MX600, MX700, and MX800 are patient monitors with built-in central processing unit, flat panel display and interfaces to dedicated external measurement devices. Models MX600, MX700, and MX800 have widescreen displays. IntelliVue series MP80 and MP90 are patient monitors with flat panel display and central processing unit as separate components. They have interfaces to dedicated external measurement devices.

Here's a breakdown of the acceptance criteria and the study information based on the provided text, structured as requested:

Acceptance Criteria and Device Performance Study for Philips IntelliVue Patient Monitors (Software Revision J.04)

Overview:
The submission describes a software modification to existing Philips IntelliVue Patient Monitors (MP2, X2, MP5, MP5T, MP5SC, MP20, MP30, MP40, MP50, MP60, MP70, MP80, MP90, MX600, MX700, and MX800) to introduce a new SpO2 intelligent alarm delay feature called 'Smart Alarm Delay'. The study aims to demonstrate that this modified device is as safe and effective as the predicate devices.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a quantitative table of acceptance criteria with corresponding performance metrics for the 'Smart Alarm Delay' feature in the format often seen for diagnostic devices (e.g., sensitivity, specificity, accuracy). However, the "Summary of V&V activities" section outlines the general performance goals and outcomes.

2. Sample Size and Data Provenance for the Test Set

• Sample Size: The document does not specify the exact number of individuals (test persons) involved in the clinical evaluation. It refers to "two user groups - one consisting of physicians and one consisting of nurses" and later "the vast majority of test persons." This suggests a qualitative assessment rather than a statistically powered performance study.
• Data Provenance: Not explicitly stated, but clinical evaluation of user understanding implies prospective testing with healthcare professionals. The country of origin for this specific clinical evaluation is not mentioned.

3. Number of Experts and Qualifications for Ground Truth of the Test Set

• The "clinical evaluation" appears to focus on user comprehension and acceptance, not on establishing a traditional clinical "ground truth" for diagnostic accuracy.
• Number of Experts: Two user groups were formed: "one consisting of physicians and one consisting of nurses." The exact number of individuals within each group is not provided.
• Qualifications of Experts:
  • Physicians
  • Nurses
  • No specific years of experience or subspecialty are mentioned.

4. Adjudication Method for the Test Set

Not applicable. The clinical evaluation described is a qualitative assessment of user understanding and perception, not a diagnostic accuracy study requiring adjudication of results.

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

No. The document describes a software modification to an existing patient monitor to add an intelligent alarm delay feature. The "clinical evaluation" focused on user understanding and acceptance of this feature, not on comparing reader performance with and without AI assistance.

6. Standalone Performance Study (Algorithm Only)

No, not in the traditional sense of a standalone diagnostic algorithm performance study. The modification is an alarm delay feature within an existing monitoring system. The document states:

• "The new 'Smart Alarm Delay' feature is isolated from the SpO2 measurement algorithm, i.e. signal acquisition and numeric processing."
• "The devices hardware and all accessories including, but not limited to the SpO2 sensors remain completely unchanged."
• "The modification does not affect device performance in general and device accuracy in particular."
• Performance aspects covered by ISO 9919 from prior V&V are considered still valid.

This indicates that the fundamental SpO2 measurement accuracy itself was not re-evaluated as a standalone algorithm performance, as the algorithm for SpO2 measurement remained unchanged. The focus was on the alarm delay logic and its user-facing implications.

7. Type of Ground Truth Used

For the "clinical evaluation" regarding the 'Smart Alarm Delay' feature, the "ground truth" appears to be user understanding and subjective opinion as gathered directly from physicians and nurses. For the core SpO2 measurement, the ground truth and performance validation are based on prior verification and validation activities conducted according to ISO 9919 for the predicate device, which are deemed still valid.

8. Sample Size for the Training Set

Not applicable. This submission is for a software modification adding an alarm delay feature, not a machine learning or AI algorithm that requires a dedicated training set for model development. The 'Smart Alarm Delay' is described as being "based on the same fundamental principle" as the predicate's 'SatSeconds' alarm management technique, implying a rule-based or empirically derived logic rather than a learned model.

9. How the Ground Truth for the Training Set Was Established

Not applicable, as no training set for a machine learning model was described or used.

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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, X2, MP20, MP30, MP40, and MP50 are additionally intended for use in transport situations within hospital environments. The MP5 is also intended for use during patient transport outside of a hospital environment.

The Philips MP2, X2, MP5, MP20, MP30, MP40, MP50, MP60, MP70, MP80, and MP90 IntelliVue Patient Monitors. The modification is the introduction of the models MP2 and X2 IntelliVue Patient Monitors and the introduction of software release F.00 for the entire IntelliVue Patient Monitors family, models MP2, X2, MP5, MP20, MP30, MP40, MP50, MP60, MP70, MP80, and MP90.

The Philips IntelliVue Patient Monitors (models MP2, X2, MP5, MP20, MP30, MP40, MP50, MP60, MP70, MP80, and MP90, with software release F.00) are intended for monitoring and recording multiple physiological parameters and generating alarms for adults, pediatrics, and neonates in hospital environments. Some models (MP2, X2, MP20, MP30, MP40, MP50) are also for hospital transport, and the MP5 is for transport outside the hospital. They are intended for use by healthcare professionals.

Acceptance Criteria and Device Performance:

The provided 510(k) summary states that "Pass/Fail criteria were based on the specifications cleared for the predicate devices." However, it does not provide specific quantitative acceptance criteria or detailed reported device performance metrics in a table. It generally states that "test results showed substantial equivalence" and that the "results demonstrate that the Philips IntelliVue Patient Monitors meet all reliability requirements and performance claims."

Study Details:

1. Sample size for the test set and data provenance:
   The document does not specify the sample size for the test set or the data provenance (e.g., country of origin, retrospective/prospective). It only mentions "system level and regression tests, safety and performance tests, EMC and environmental tests, such as testing from the hazard analysis."

2. Number of experts used to establish the ground truth for the test set and qualifications:
   This information is not provided in the document.

3. Adjudication method for the test set:
   This information is not provided in the document.

4. Multi-reader multi-case (MRMC) comparative effectiveness study:
   No MRMC comparative effectiveness study is mentioned. The submission focuses on demonstrating substantial equivalence to predicate devices through technical verification and validation, not comparative effectiveness with human readers.

5. Standalone (algorithm only without human-in-the-loop performance) study:
   The submission describes testing activities for the device itself ("Verification, validation, and testing activities establish the performance, functionality, and reliability characteristics of the modified devices"). This implies standalone performance testing of the device's functions, but details on specific standalone performance metrics or a study explicitly labeled as such are not provided. The device is a patient monitor, implying continuous monitoring of physiological parameters by the device itself before human interpretation.

6. Type of ground truth used:
   The document does not explicitly state the type of ground truth used for performance evaluation, beyond stating that "Pass/Fail criteria were based on the specifications cleared for the predicate devices." For physiological monitoring, ground truth would typically come from calibrated reference measurements or expert clinical assessment for phenomena like arrhythmia detection.

7. Sample size for the training set:
   This information is not provided. The document describes verification and validation activities for the device, but does not mention "training sets," which implies that this device might not incorporate machine learning or AI that requires a distinct training phase in the way a diagnostic imaging AI would.

8. How the ground truth for the training set was established:
   As no training set is explicitly mentioned or implied to be relevant to the device's development as described, this information is not provided.

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Indicated for central monitoring of multiple adult, pediatric, and neonatal patients; and where the clinician decides to monitor cardiac arrhythmia of adult, pediatric, and neonatal patients nond/or ST segment of adult patients to gain information for treatment, to monitor adequacy of treatment, or to exclude causes of symptoms.

The modification is a change that provides support for the MRx Monitor/Defibrillator and the M3177 Trend Display.

The provided document, K062271, is a 510(k) summary for the Philips Medical Systems M3290A IntelliVue Information Center Software Release J.00. This document primarily describes the substantial equivalence of the new device to previously cleared predicate devices and the scope of its intended use. It largely refers to previous clearances and does not detail new, specific performance studies with acceptance criteria for this particular software release.

The relevant section for performance claims is Section 7 of the 510(k) Summary, which states: "Verification, validation, and testing activities establish the performance, functionality, and reliability characteristics of the new device with respect to the predicate. Testing involved system level tests, integration tests, environmental tests, and safety testing from hazard analysis. Pass/Fail criteria were based on the specifications cleared for the predicate device and test results showed substantial equivalence. The results demonstrate that web software interface functionality meets all reliability requirements and performance claims."

Based on this, the document asserts that the new software release meets the same performance standards as its predicate devices, but it does not provide specific numerical acceptance criteria or detailed study results within this particular submission.

Therefore, for this specific 510(k) submission, the requested information detailing acceptance criteria and studies proving the device meets them cannot be fully provided as it is not explicitly present in the given text. The submission instead relies on the equivalence to previously cleared devices which presumably had such studies.

Here's a breakdown of what can be inferred or explicitly stated from the provided text, and where information is missing:

1. Table of Acceptance Criteria and Reported Device Performance

Limitations: The document does not provide specific numerical or qualitative acceptance criteria for these metrics, nor does it present detailed performance results beyond a statement of substantial equivalence to the predicate and meeting reliability requirements.

2. Sample Size Used for the Test Set and Data Provenance

The document does not specify the sample size for any test sets used in verification and validation. It also does not provide information on the data provenance (e.g., country of origin, retrospective/prospective). The testing focused on system-level, integration, environmental, and safety tests, which typically do not involve patient data in the same way clinical studies might.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

This information is not provided in the document. Given the nature of the device (information center software that supports monitoring, including arrhythmia and ST segment), ground truth would likely be established based on accepted clinical standards or reference devices, but the process is not detailed here.

4. Adjudication Method for the Test Set

This information is not provided in the document.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No MRMC study is mentioned. The document describes system-level, integration, environmental, and safety testing, not comparative effectiveness studies with human readers.

6. If a Standalone (Algorithm-Only Without Human-in-the-Loop Performance) Study Was Done

The document refers to verification, validation, and testing activities, including system-level functional tests. This implies that the software's performance was evaluated independently against its specifications. However, specific details of an "algorithm-only" performance study (e.g., for arrhythmia detection accuracy independent of clinician interpretation) are not provided. The device itself is an "Information Center Software," implying it presents data to a clinician, so its performance is inherently linked to human interpretation to some degree.

7. The Type of Ground Truth Used

The document does not specify the type of ground truth used. For monitoring devices like this, ground truth would typically come from:

• Reference measurements: Gold-standard devices or manual assessment using established clinical protocols for physiological parameters.
• Consensus: For subjective interpretations or complex events like arrhythmias, expert consensus could be used if human review was part of the ground truth process.
  The provided text does not elaborate on how ground truth was established for the tests mentioned.

8. The Sample Size for the Training Set

This information is not applicable. The device is described as "software release J.00" for an information center, supporting existing monitors. There is no indication that this software uses machine learning algorithms that would require a "training set" in the conventional sense. The testing focuses on system functionality, integration, and reliability, rather than the performance of a newly developed predictive algorithm.

9. How the Ground Truth for the Training Set Was Established

This information is not applicable, as no training set for machine learning is indicated.

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