Overnight oximetry as a screening tool for moderate to severe obstructive sleep apnoea in South African children
Bibliographic record
Abstract
BACKGROUND: Obstructive sleep apnoea (OSA) is common in children yet often overlooked, as symptom-based screening is unreliable. Polysomnography is regarded as the gold standard for the diagnosis of OSA, but is not widely available in South Africa (SA). Overnight oximetry is a validated screening tool for OSA. OBJECTIVES: To describe the impact and utility of overnight oximetry at a tertiary children's hospital in SA. METHODS: A retrospective descriptive study was conducted of patients screened for OSA by overnight oximetry at a paediatric referral hospital from December 2012 to December 2014. Clinical data were retrieved from the oximetry database and medical records. Recordings of ≥6 hours were considered adequate and included in the study. OSA severity was determined using the McGill score. Details on management and outcome were documented. RESULTS: Oximetry studies in 137 of 153 patients were suitable for analysis (88 males (64.2%), median age 31.4 months (interquartile range (IQR) 15.8 - 65.8). Adenotonsillar hypertrophy was common (n=97, 70.8%), and 65 children (47.4%) had two or more underlying OSA risk factors. McGill's score classified patients as follows: no/mild OSA n=55 (40.1%), moderate OSA n=23 (16.8%), severe OSA n=23 (16.8%) and very severe OSA n=36 (26.3%). Male gender, adenotonsillar hypertrophy and a lower weight-for-age z-score (-1.3 v. -0.7; p=0.038) were associated with severe to very severe OSA. Seventy-eight children (56.9%) were referred for surgery, 33 (24.1%) receiving urgent surgery within a median of 6 days (IQR 4 - 12). In contrast, 59 children (43.1%) with suspected OSA did not require surgical intervention. CONCLUSIONS: Overnight oximetry is a simple low-cost tool to assess severity of OSA and prioritise appropriate OSA management in resource-constrained settings such as SA.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".