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The Cerêve Sleep System is indicated to reduce sleep latency to Stage 1 and Stage 2 sleep in patients with primary insomnia.

The Cereve Sleep System is a cooling device comprised of three components: the bedside unit, the forehead pad, and headgear. The device pumps chilled fluid through the forehead pad, at patient selectable temperatures in a narrow range between 14 and 16 °C.

The Cerêve Sleep System is intended to reduce sleep latency to Stage 1 and Stage 2 sleep in patients with primary insomnia. The device’s performance was evaluated through a pivotal study, CIP-006, along with two supporting studies, CIP-003 and CIP-004.

Here's a breakdown of the acceptance criteria and study details:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The initial co-primary endpoints of the pivotal study (latency to persistent sleep and sleep efficiency) were not met with statistical significance. However, additional data analysis identified statistically significant improvements in sleep latency to Stage 1 and Stage 2 sleep, which became the basis for the device's indications for use and acceptance criteria.

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

• Sample Size (Test Set): 116 adult subjects with primary insomnia for the pivotal study (CIP-006).
• Data Provenance: Retrospective analysis of prospectively collected data from a randomized, multi-center (7 U.S. sites), sham-controlled study conducted in the United States.

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

The document does not explicitly state the number of experts or their specific qualifications for establishing ground truth for individual sleep stages in the test set. However, the ground truth for sleep staging (latency to persistent sleep, sleep efficiency, Stage 1, Stage 2, Stage 3 NREM sleep) was based on Polysomnography (PSG) data. PSG is a comprehensive sleep study that involves monitoring various physiological functions during sleep, which are then analyzed and scored by trained polysomnography technologists, typically under the supervision of a sleep physician. The diagnostic criteria for primary insomnia were based on the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM IV), International Classification of Sleep Disorders (ICSD), and Research Diagnostic Criteria (RDC) insomnia disorder criteria, indicating expert clinical diagnosis.

4. Adjudication Method for the Test Set

The document does not explicitly detail an adjudication method for the PSG scoring or subject inclusion/exclusion criteria beyond their initial establishment. The PSG data would typically be scored according to standardized guidelines, and quality control procedures often involve a second read or review by another technologist or sleep physician, but this is not specifically described as an "adjudication method" in the provided text.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. This device is a therapeutic system (thermal system) for insomnia and not an AI-powered diagnostic or interpretive tool that would typically involve human readers interpreting cases with or without AI assistance. The study design focused on the direct effect of the device on physiological sleep measures compared to a sham device.

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

Yes, a standalone study was done in the sense that the device's performance was evaluated based on the physiological measurements (PSG) taken while subjects used the device or a sham device, without direct human intervention in the device's mechanism of action or interpretation of the immediate results. The device itself is an automated system that delivers a controlled thermal therapy.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

The primary ground truth for evaluating the device's effectiveness was Polysomnography (PSG) data, which is considered objective physiological outcomes data for sleep staging. The diagnosis of primary insomnia for subject inclusion was based on expert clinical diagnostic criteria (DSM IV, ICSD, RDC insomnia disorder criteria). Subjective sleep quality was assessed via self-reported questionnaires (Pittsburgh Sleep Diary), which can be considered patient-reported outcomes data.

8. The Sample Size for the Training Set

The document describes clinical studies that served as efficacy trials. It does not mention a separate "training set" for an algorithm, as this device is a physical therapeutic system, not an AI/ML-based diagnostic or predictive algorithm requiring a distinct training phase in the context of clinical validation. The device's control system (firmware) was developed and validated through software verification and non-clinical bench testing, not through a "training set" in the machine learning sense.

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

As there was no "training set" in the context of an AI/ML algorithm for clinical efficacy, this question is not applicable. The device's design, including its temperature regulation capabilities, was established through engineering specifications, software development, and verified through non-clinical bench testing (e.g., fluid flow rate, time to reach target temperature, maintenance of target temperature).

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