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AirStrip ONE Web Client with ACM is intended to allow clinicians to capture and display waveforms (such as ECG, SpO2, ART), discrete parameters, patient demographics, alarms, and other information from medical devices on a desktop device. This software is intended as a diagnostic aid to provide access for professional staff to view patient clinical data when the professional cannot observe the source system directly. AirStrip ONE Web Client with ACM does not store Protected Healthcare Information on the device accessing the data. Data available on the web viewer is in "near real time" and is displayed to show a full range of clinical data available, even when the data sources are obtained from different devices.

AirStrip ONE Web Client with ACM gathers data from the medical devices that are connected to the patient. AirStrip ONE Web Client with ACM is not directly connected to the individual, but to a networked medical device receiving data, and connects that data to individuals by medical record number or defined patient ID. AirStrip ONE Web Client with ACM is intended to be used by clinicians for the following purposes:

• To visualize physiological data using a web viewer to assess clinical status of a patient when the source system cannot be observed directly by the clinician.

• · To view the near real-time and historic waveforms.
  · To view other near real-time patient data from a monitored system.

· To provide a request for remote consultation regarding a patient's waveform or other data.

• · To send electronic images of the cardiac rhythm to the medical record.
• · To allow clinicians to manage secondary alarm transmission by suppressing non-critical alarms.

AirStrip ONE Web Client with ACM is appropriate for use in pediatric (0-21 years), adult and geriations, as the networked medical devices AirStrip collects data from are already cleared for these populations. AirStrip ONE Web Client with ACM software can display the following physiologic parameters and waveforms captured by other cleared medical devices:

• · ECG Waveform
• · Heart Rate
• · Respiratory Rate
• · Oxygen Saturation
• Intracranial Pressure
• · Central Venous Pressure
• Pulmonary Capillary Wedge Pressure
• Pulmonary Artery Pressure
• Cardiac Index
• Cardiac Output
• · Cerebral Perfusion Pressure
• · Temperature
• · Temperature Source o Bispectral index (BIS) o Umbilical Artery
  • o Body Weight
• Systolic Blood Pressure Invasive
• · Mean Arterial Pressure Invasive
• Diastolic Blood Pressure Invasive
• · Systolic Blood Pressure Cuff
• · Mean Arterial Pressure Cuff
• · Diastolic Blood Pressure Cuff
• Vasoactive Infusions
• Ventilators
• · Allergies
• IV Fluid Delivery Rate
• IV Medication Dose
• Pulse Rate
• Bispectral Parameters
• Monitored Events
• Right Atrial Pressure
• · Left Atrial Pressure
• · Laboratory Data, including
  • o Blood Gas
  • o Chemistry
  • o Hematology
  • o Coagulation
• · Hemodynamic Calculated Values
• · Medications
• IV Volume Infused
• · ETCO2
• · Fractional Inspired Concentration O2, CO2
• Case Consumption Liquid Medications
• · Case Consumption Respiratory Gas

The AirStrip Technologies, Inc. (AirStrip) ONE Web Client, the predicate device being modified to include the AirStrip Alarm Communication Management (ACM), provides visualization of monitoring data, waveforms, and events for clinicians who are away from the bedside to support and enhance their collaboration with other care team members who are with the patient.

All data, waveforms and events displayed by AirStrip ONE Web Client are generated by primary monitors, not by AirStrip ONE Web Client. Events that triggered alarms by the primary monitor system populate in AirStrip ONE Web Client in near real time so a remote (i.e. not at bedside) clinician can review these items while they are collaborating with other care team members.

The AirStrip ONE Web Client remote patient monitoring is a visualization and collaboration aid. It allows for the display of waveform, monitoring data, and events that triggered primary patient monitor alarms without itself originating alarms. The clinical use of AirStrip ONE Web Client presupposes nurses or other clinicians will be at the hospital, either at the bedside or a near-by monitoring station.

The AirStrip ONE Web Client with Alarm Communication Management (ACM) module is a "rules engine" module that, when used in conjunction with, and as a part of, the existing AirStrip ONE Web Client to gather alarms from various alarm sources, processes the alarms through a rules configuration tool (the proposed device) using clinical rules established by the customer, typically a healthcare institution, to filter and distribute those alarms to a third-party server connected to mobile devices carried by healthcare providers. The display device stays in a notification state until the healthcare provider dispositions the alarm.

The provided text describes the regulatory clearance of a medical device, the AirStrip ONE Web Client with Alarm Communication Management (ACM), and highlights its substantial equivalence to a predicate device. However, it does not contain the specific details required to answer the prompt regarding acceptance criteria and a study proving the device meets those criteria, particularly in the context of an AI/algorithm-driven diagnostic aid.

The device described is primarily a visualization and communication system for existing physiological monitoring data, with an added "rules engine" for alarm management. It does not appear to be an AI/algorithm for diagnostic purposes, nor does it conduct standalone diagnostic assessments. Therefore, detailed information about acceptance criteria for diagnostic performance (like sensitivity, specificity, AUC), ground truth establishment by experts, MRMC studies, or training/test set sample sizes for an AI model are not present in this document because they are likely not applicable to the device's function.

The "Summary of Performance Testing" section focuses on software development processes, risk management, and cybersecurity, not on clinical performance metrics typically associated with AI/diagnostic algorithms.

Given the information provided, here's what can be inferred and what cannot be answered:

What Can Be Inferred/Answered (based on the document's content):

• 1. A table of acceptance criteria and the reported device performance: Not explicitly provided in terms of diagnostic performance metrics. The performance testing section mentions "complies with its predetermined specifications" and "complies with internal requirements" related to software development, risk control, and cybersecurity (e.g., ISO/IEC 27001 certification, code analysis, network test scan, interoperability verification). These are acceptance criteria for software quality and security, not for diagnostic accuracy.
• 2. Sample sized used for the test set and the data provenance: Not mentioned, as it's not a diagnostic performance study. The data provenance (country, retrospective/prospective) is also not specified for any testing.
• 3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable and not mentioned, as there's no diagnostic ground truth being established by experts for algorithmic performance.
• 4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable and not mentioned for the same reasons as above.
• 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: Not applicable and not mentioned. The device is not an AI assistance for human reader interpretation. It's a data visualization and alarm management tool.
• 6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable and not mentioned. The device is explicitly stated as an "adjunct to and not a replacement for direct viewing of the monitoring medical device(s)." Its purpose is to display data from other devices.
• 7. The type of ground truth used: Not applicable in the context of algorithmic diagnostic performance. For software validation, the "ground truth" would be compliance with specifications, which is verified through testing like "Risk Control Measure Verification," "Dynamic Code Analysis," etc.
• 8. The sample size for the training set: Not applicable and not mentioned, as this is not an AI/ML device that requires a training set of data.
• 9. How the ground truth for the training set was established: Not applicable and not mentioned.

Conclusion:

The provided FDA 510(k) clearance document for the AirStrip ONE Web Client with ACM describes a medical device focused on data display and alarm communication management, not a diagnostic AI/algorithm. Therefore, the detailed information requested regarding diagnostic acceptance criteria, expert-established ground truth, MRMC studies, and training/test set specifics for AI performance are not present in this document as they are not relevant to the device's function and regulatory review. The "performance testing" mentioned relates to software validation, cybersecurity, and adherence to internal specifications and relevant guidance documents (e.g., IEC 62304, ISO 14971, ISO/IEC 27001).

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AirStrip RPM is software capable of displaying physiologic and other patient information. This information is generated by other medical devices and patient information system, and not by AirStrip RPM. AirStrip RPM captures this information from these other systems and displays it for clinicians.
AirStrip RPM is intended to be used by clinicians for the following purposes:
• By using a cellular telephone or other device on which AirStrip RPM is installed, to review physiologic data of a patient when the clinician is not at the hospital
• To view the near real-time waveforms remotely
• To remotely review other standard or critical near real-time patient data from the monitored system
• To provide a request for remote consultation regarding a patient's waveform or other data

The AirStrip RPM software can display the following the physiologic data captured by other medical devices:

• ECG Waveform
• Heart Rate Monitored
• Respiratory Rate
• Oxygen Saturation
• Intracranial Pressure
• Central Venous Pressure
• Pulmonary Capillary Wedge Pressure
• Cardiac Index
• Cardiac Output
• Cerebral Perfusion Pressure
• Urine Output
• Urine/Stool Mix Output
• Systolic Blood Pressure Invasive
• Mean Arterial Pressure Invasive
• Diastolic Blood Pressure Invasive
• Systolic Blood Pressure Cuff
• Mean Arterial Pressure Cuff
• Diastolic Blood Pressure Cuff
• Vasoactive Infusions
• Antiarrhythmics
• Sedation
• Paralytics
• Laboratory Data including

• Blood Gas
• Chemistry
• Hematology
• Coagulation
  • Allergies
  • Medications

Contraindications
AirStrip RPM software is intended for installation on cellular telephones and other wireless devices, and is not intended for use anywhere cellular telephones or wireless devices are prohibited. AirStrip RPM is intended for use by clinicians when they cannot be at the hospital. AirStrip RPM is intended for use by clinicians as a diagnostic aid, and not as a replacement for direct viewing of any of the monitoring devices from which it obtains its data.

The AirStrip RPM InvisionHeart Adapter is a software application that interfaces with the InvisionECG System in hospitals to allow health care professionals the ability to view near real-time patient data remotely. AirStrip RPM works by retrieving patient data from the InvisionECG System monitoring system and providing that data to the end user's device via Wi-Fi or cellular modem over the Internet.

The AirStrip RPM InvisionHeart Adapter is a software application that interfaces with the InvisionECG System to display near real-time patient data remotely to healthcare professionals.

Here's an analysis of the acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not specify a numerical sample size for a test set in terms of patient data or clinical cases. The performance evaluation primarily focuses on demonstrating substantial equivalence through non-clinical testing of the software's functionality, interoperability, and adherence to standards.

The data provenance for any internal testing is not explicitly mentioned, but the system is designed to interface with the InvisionECG System, which handles patient data. The context implies that the testing involves how the adapter processes and displays data originating from the InvisionECG System, which in turn acquires data from actual patients in a hospital setting. The study is retrospective in the sense that it evaluates the software's ability to display data that has already been generated by other medical devices.

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

This information is not provided in the document. Given that no formal clinical study with human interpretation of results is detailed, there's no mention of experts establishing ground truth for a test set. The evaluation is focused on the technical performance of the software in accurately displaying information from the source system.

4. Adjudication Method for the Test Set

This information is not applicable as there is no mention of a human-centric test set requiring adjudication. The evaluation centers on software verification and validation.

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 conducted or reported in this submission explicitly. The device's purpose is to display data to clinicians, not to perform interpretations or make diagnoses itself. Therefore, a study to measure human reader improvement with AI assistance (as the device is a medical device data system, not an AI diagnostic tool) is not relevant to its stated function or the type of evaluation presented.

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

The evaluation conducted is essentially a standalone (algorithm only) performance assessment, though not in the typical sense of a diagnostic algorithm. The device itself is software that transmits and displays data. The "performance" tested is its adherence to technical specifications, cybersecurity, risk management, and the accurate rendering of data (ECG waveforms, other physiological parameters) from a source system. The "algorithm" here refers to the software's logic for data capture, processing, and presentation, rather than a diagnostic algorithm.

7. The Type of Ground Truth Used

The ground truth for the non-clinical tests appears to be the predetermined specifications of the software and the expected output or behavior when interfacing with the InvisionECG System, as well as adherence to relevant standards (e.g., DICOM, ISO 14971). For example, the ground truth for DICOM compliance is the DICOM standard itself. For accurate waveform display, the ground truth would be the waveform as generated by the InvisionECG System.

8. The Sample Size for the Training Set

The document does not mention a training set as this device is a data display and communication system, not a machine learning or AI model that typically requires training data. Its functionality is based on established software engineering principles and interoperability standards.

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

As no training set is mentioned or implied for this type of medical device data system, this point is not applicable.

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This device is intended to be used by clinicians for the following purposes:

• To view the near real-time waveforms remotely
• To remotely review other standard or critical near real-time patient data from the monitored system
• To provide a request for remote consultation regarding a patient's waveform or other data

This device software can display the following the physiologic data captured by other medical devices:

• ECG Waveform
• Heart Rate Monitored
• Respiratory Rate
• Oxygen Saturation
• Intracranial Pressure
• Central Venous Pressure
• Pulmonary Capillary Wedge Pressure
• Cardiac Index
• Cardiac Output
• Cerebral Perfusion Pressure
• Systolic Blood Pressure Invasive
• Mean Arterial Pressure Invasive
• Diastolic Blood Pressure Invasive
• Systolic Blood Pressure Cuff
• Mean Arterial Pressure Cuff
• Diastolic Blood Pressure Cuff

Not Found

The provided document is a 510(k) premarket notification letter from the FDA for the Airstrip ONE Web Client, a cardiac monitor. This document primarily focuses on FDA's determination of substantial equivalence and does not contain specific details about acceptance criteria for device performance or the study that proves the device meets those criteria.

The information typically found in such a study (acceptance criteria, sample size, ground truth establishment, expert qualifications, etc.) is not present in this regulatory letter. This letter is a formal communication from the FDA stating that the device has been cleared for marketing based on its substantial equivalence to a legally marketed predicate device, and it outlines the regulatory obligations of the manufacturer.

Therefore, I cannot extract the requested information from the provided text.

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The Sense4Baby System Model B+ is indicated for conventional antepartum fetal monitoring applications in pregnancies greater than or equal to 24 weeks gestation. It may be used for antenatal monitoring (e.g., non-stress testing and/or uterine activity monitoring) in a health care setting or home.

It is to be used by health care professionals and patients on the order of a physician.

Before the Sense4Baby System Model B+ is prescribed for home use, the user (patient) must be instructed/trained in proper use of the equipment.

Home uterine activity monitoring has not been shown to prevent the onset of preterm labor nor will it prevent the occurrence of preterm birth.

The Sense4Baby System, Model B+ (MSA) is a non-invasive, wireless, external monitoring system used to measure fetal heart rate, maternal heart rate, and uterine contractions during antepartum (non-stress) testing. The system transmits the measured data to a gateway device, and then a HIPAA Compliant web based portal for storage and physician review.

The provided document is a 510(k) premarket notification for the Sense4Baby System Model B+ (MSA), a home uterine activity monitor. It focuses on demonstrating substantial equivalence to a predicate device (Huntliegh Healthcare Limited Fetal Assist, K020390) rather than presenting a detailed study proving the device meets specific acceptance criteria based on clinical performance metrics like sensitivity or specificity.

The document discusses various tests for safety, technical characteristics, and usability, but does not provide quantitative clinical performance data against specific acceptance criteria for fetal heart rate or uterine activity monitoring accuracy. Therefore, a table of acceptance criteria and reported device performance related to diagnostic accuracy cannot be created from this document.

Here's an analysis of the information provided, addressing the requested points where possible, and noting where information is absent:

1. Table of Acceptance Criteria and Reported Device Performance

This document does not provide specific numerical acceptance criteria for clinical performance (e.g., accuracy, sensitivity, specificity for detecting fetal heart rate anomalies or uterine contractions) or the reported device performance against such metrics. The focus is on demonstrating substantial equivalence to a predicate device based on technical characteristics, safety standards, and usability.

The document states: "Verification and validation activities established the performance, functionality, and reliability characteristics of the device with respect to the predicate. Testing involved sub-system, as well as system level tests. Pass/Fail criteria were based on the specifications cleared for the predicate devices and test results demonstrated substantial equivalence." However, the specific "specifications cleared for the predicate devices" and the numerical outcomes for comparison are not detailed.

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

• Sample Size for Clinical Performance (if any): Not explicitly stated for specific clinical performance studies in this document. The document mentions "two separate studies to determine the ability of the user to operate the device in the home environment" (usability studies), but does not provide sample sizes for these or any other clinical tests.
• Data Provenance: Not specified for clinical performance data. The device is intended for "antenatal monitoring... in a health care setting or home."

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

Not applicable based on the provided document. The document does not describe a clinical study where experts established ground truth for a test set to evaluate the device's diagnostic performance. The document focuses on technical safety, functional characteristics, and usability.

4. Adjudication Method for the Test Set

Not applicable. No clinical test set requiring ground truth adjudication is described in the provided text.

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

No. The document does not describe an MRMC comparative effectiveness study where human readers' performance with and without AI assistance was evaluated. The device itself is a monitoring system, not explicitly an AI-driven diagnostic interpretation tool in the context of reader study.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

The device is a "monitoring system" that measures and transmits data for "physician review." It is not an algorithm designed for standalone diagnostic performance (i.e., making a diagnosis without human interpretation). Therefore, a standalone algorithm-only performance study as typically understood for AI/ML diagnostic devices is not applicable or described. The document states it is "to be used by health care professionals and patients on the order of a physician," implying human-in-the-loop operation.

7. The Type of Ground Truth Used

Not applicable. The document does not describe clinical studies that established ground truth for diagnostic accuracy (e.g., pathology, outcomes data, expert consensus). The "ground truth" implicitly referred to in the context of "predicate comparison testing" would be the performance characteristics of the predicate device. For usability studies, the "ground truth" would be successful operation of the device by users.

8. The Sample Size for the Training Set

Not applicable. This device is a physiological monitoring system, not an AI/ML device that requires a training set in the typical sense for developing a diagnostic algorithm.

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

Not applicable, as there is no mention of a training set for an AI/ML algorithm.

Summary of Device Evaluation in the Document:

The 510(k) submission for the Sense4Baby System Model B+ (MSA) focuses on demonstrating substantial equivalence to a predicate device (Huntliegh Healthcare Limited Fetal Assist, K020390) by comparing:

• Indications for Use: Found to be largely similar, with minor differences in gestation age for monitoring (Sense4Baby >= 24 weeks vs. Fetal Assist approx. 26 weeks).
• Technological Characteristics: Both use Doppler Ultrasound for FHR and relative pressure sensors for uterine activity. Minor differences in ultrasound frequency (1 MHz vs 1.5 MHz) and burst rate (3125 Hz vs 3200 Hz) are discussed and deemed not to raise new safety/effectiveness concerns.
• Safety and Performance Standards Compliance: The device claims compliance with numerous international standards for electrical safety, EMC, biocompatibility, risk management, and environmental testing (e.g., IEC 60601 series, ISO 10993 series, ASTM D4169, ISO 14971, ISO 13485).
• Usability Studies: Two such studies (formative and summative) were conducted to ensure lay users could operate the device in a home environment with a "statistically equivalent" success rate to that in a healthcare provider environment. However, specific performance metrics or sample sizes for these usability studies are not detailed.

The document does not provide a traditional clinical performance study with defined acceptance criteria for diagnostic accuracy (e.g., sensitivity, specificity) against a clinical ground truth. Instead, it relies on demonstrating that the device's technical specifications and safety profile are comparable to a legally marketed predicate device.

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AirStrip RPM for LIFENET Consult is an optional data transmission system that provides the capability to receive notifications at a remote location. Data is received from the field and can be used for diagnosis, disposition, and therapy decisions by qualified medical personnel.

Not Found

This looks like a 510(k) clearance letter for the AirStrip Remote Patient Monitoring (RPM) for LIFENET® Consult device. Unfortunately, the provided document does not contain the detailed information required to answer your request about acceptance criteria, study details, sample sizes, expert qualifications, or ground truth establishment.

This type of FDA letter typically confirms that a device is substantially equivalent to a predicate device and is cleared for marketing. It usually does not include the detailed scientific study results that demonstrate how the device meets specific performance acceptance criteria. Such information would typically be found in the original 510(k) submission, which is a much more extensive document.

Therefore, I cannot provide the requested table and study details.

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