(571 days)
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
| Acceptance Criteria (Stated Goal) | Reported Device Performance (from CIP-006) |
|---|---|
| Reduction in sleep latency to Stage 1 sleep | 12-minute reduction in sleep latency to Stage 1 sleep (p=0.004) compared to sham. |
| Reduction in sleep latency to Stage 2 sleep | 12-minute reduction in sleep latency to Stage 2 sleep (p=0.008) compared to sham. |
| No statistically significant differences in primary endpoints (latency to persistent sleep, sleep efficiency) | Confirmed: No statistically significant differences between Cerêve and sham groups for original primary endpoints (latency to persistent sleep and sleep efficiency). |
| No statistically significant differences in secondary endpoints (Stage 3 NREM sleep, subjective sleep quality) | Confirmed: No statistically significant differences between Cerêve and sham groups for original secondary endpoints. |
| Safety – Low rate of adverse events | Low rate of AEs (3 possibly/probably device-related AEs in Cerêve group, 1 in sham group). No serious AEs observed. |
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).
§ 882.5700 Thermal system for insomnia.
(a)
Identification. A thermal system for insomnia is a prescription device for use in patients with insomnia that is used to apply a specified temperature to the skin surface.(b)
Classification. Class II (special controls). The special controls for this device are:(1) The patient-contacting components of the device must be demonstrated to be biocompatible.
(2) Performance testing must demonstrate electromagnetic compatibility and electrical safety.
(3) Non-clinical performance testing must demonstrate that the device performs as intended under anticipated conditions of use. The following performance characteristics must be evaluated:
(i) Thermal performance of the device, including maintenance of the target temperature, must be evaluated under simulated use conditions.
(ii) Mechanical testing to demonstrate the device can withstand forces under anticipated use conditions.
(iii) Mechanical testing to demonstrate the device is resistant to leakage under anticipated use conditions.
(4) Software verification, validation, and hazard analysis must be performed.
(5) Patient labeling must be provided to convey information regarding safe use of the device, including instructions for assembly.