Preliminary Estimates of the Diagnostic Characteristics of Video Clips for Obstructive Sleep Apnea in Children
Bibliographic record
Abstract
Abstract RATIONALE Obstructive sleep apnea (OSA) is associated with adverse cardiovascular, neurocognitive, and mental health outcomes. However, diagnosis is challenging due to long wait times for polysomnography (PSG), the gold standard lab test. With the increasing availability of smartphones, parent-recorded video clips have emerged as a potential screening tool for moderate-severe OSA in children. These video clips could expedite the triage process for PSG, but their diagnostic accuracy has not been fully investigated. AIM This study aimed to assess the diagnostic accuracy of video clip scores compared to PSG for detecting moderate-severe OSA. METHODS Children aged 2-18 years referred for PSG evaluation of suspected OSA were enrolled. Parents recorded 3-minute video clips of their child sleeping using their smartphone device and completed the Pediatric Sleep Questionnaire (PSQ). Two independent, blinded clinicians scored the videos for OSA severity using the Monash Obstructive Sleep Apnea video score. All participants subsequently underwent PSG testing, with OSA severity scored using the obstructive apnea hypopnea index (OAHI). Oximetry metrics, including the McGill Oximetry Score (MOS) and 3% Oxygen Desaturation Index (ODI3) were also measured. The sensitivity and specificity of the video score, PSQ, MOS, and ODI3 were compared for the detection of moderate-severe OSA (OAHI ≥5 events/hour), with ROC curve and AUC analyses conducted. RESULTS A total of 41 children (median age 7.0 years, 49% female) participated. The median OAHI was 0.6 events/hour (IQR 0.3, 3.1), with 39% (n=16) having OAHI ≥ 1.5, 12% (n=5) having OAHI ≥ 5. The PSQ identified 36 (88%) of participants as having a score > 0.33. One child had a MOS ≥ 2 and ODI3 was > 4.3 in 8 (20%) and > 7 in 6 (15%). The median Monash video score was 3.0 (IQR 2.0, 5.0). The Monash video score had 100% sensitivity and 20% specificity for detecting moderate-severe OSA. A combination of the Monash score and ODI3 improved diagnostic accuracy with an AUC of 98.3. CONCLUSION The Monash video score demonstrated high sensitivity but low specificity for the detection of moderate-severe OSA. While video scores outperformed the PSQ, they were less accurate than oximetry metrics. Combining video scoring and ODI3 yielded the strongest diagnostic results. Video scores may ultimately prove useful to screen for pediatric OSA.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".