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The BIPAP S/T-D 30 System is intended for hospital or institutional use for treatment of obstructive sleep apnea, respiratory failure, or respiratory insufficiency.

The BiPAP S/T-D 30 System is a ventilation support system designed to augment a patient's ability to breathe on a spontaneous basis. It is not intended for life support situations. The BiPAP S/T-D 30 System is intended for hospital or institutional use for treatment of obstructive sleep apnea, respiratory failure, or respiratory insufficiency. The BiPAP S/T- D offers four modes of operation: Continuous Positive Airway Pressure (CPAP), Spontaneous (S) mode, Spontaneous/Timed (S/T) mode, and Timed (T) mode. The BiPAP S/T-D 30 System provides ventilation support by applying a positive pressure (IPAP) during the inspiratory segment of a breathing cycle, and subsequently cycling to a lower pressure level (EPAP) during the expiratory segment of the cycle for spontaneous breaths. The transition point between inspiration and expiration is sensed by the BiPAP System as a function of a decrease in patient flow demand. The BiPAP S/T-D 30 System also senses the transition point between expiration and inspiration. As the patient begins to inhale, the BiPAP System senses the increase in flow and transitions from EPAP to IPAP. These points are called the trigger thresholds. The BiPAP S/T-D 30 System monitors delivered pressure and adjusts flow as applied to the patient circuit to maintain set IPAP and EPAP pressures. The System is also capable of compensating for most leaks around the patient interface.

The provided text describes the BiPAP S/T-D 30 System and its performance, but it does not contain information about the acceptance criteria or a study proving that an AI device meets those criteria. The document is a 510(k) summary for a medical device (a ventilator), not an AI/ML diagnostic tool. Therefore, I cannot provide the requested table and information about AI model validation.

Here's a breakdown of the information that is present, organized to show what could be extracted if this were an AI device, and what is missing because it's a traditional medical device:

1. Table of Acceptance Criteria and Reported Device Performance

If this were an AI device, this table would typically show metrics like sensitivity, specificity, AUC, F1-score, etc., alongside their acceptance thresholds.

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

• Sample Size for Test Set:
  • 31 adult patients for prospective, randomized, controlled clinical studies.
  • 81 patients for prospective, non-randomized studies.
• Data Provenance: The document does not specify the country of origin of the data. The studies were described as "prospective."

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

This information is not applicable/provided as the study described is a clinical study for a medical device (ventilator) and not an AI model requiring ground truth established by experts for image interpretation or similar. The "ground truth" for this device is the patient's respiratory condition and clinical outcomes.

4. Adjudication Method for the Test Set

This information is not applicable/provided as the study described is a clinical study for a medical device and not an AI model requiring adjudication for ground truth establishment.

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

• No, an MRMC comparative effectiveness study was not done. This type of study is specifically relevant for diagnostic AI tools where human readers (e.g., radiologists) interpret cases with and without AI assistance. The document describes clinical studies comparing the device's effectiveness in treating respiratory conditions.
• Effect Size of Human Readers Improve with AI vs. without AI Assistance: Not applicable, as no AI assistance was involved in this study.

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

• Not applicable. The "algorithm" in this context is the control system of a physical ventilator, not a standalone AI diagnostic algorithm. The device itself operates in a standalone manner as a ventilator, but this is distinct from an AI algorithm's standalone performance.

7. The Type of Ground Truth Used

• Clinical Outcomes/Patient Condition: The "ground truth" for this study was the patient's acute respiratory condition and whether the device "successfully treat[ed] these patients." This is derived from clinical observation and patient health status, not expert consensus on an image or pathology. The primary outcome measure was whether noninvasive ventilation using the BiPAP System could successfully treat patients with acute respiratory failure.

8. The Sample Size for the Training Set

• Not applicable/provided. The document describes a traditional medical device, not an AI model that undergoes a "training set" phase.

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

• Not applicable/provided. As it's not an AI model, there isn't a "training set" with established ground truth in the AI/ML sense.

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