Screening for Non-invasive Ventilatory Requirements in Children With Spinal Muscular Atrophy
Bibliographic record
Abstract
Introduction: Despite disease modifying treatments (DMT) in Spinal Muscular Atrophy (SMA), ongoing ventilatory requirements are common. Current guidelines suggest screening with oximetry with transcutaneous carbon dioxide (TcCO2). Aim: To determine the utility of pulse oximetry with TcCO2 as a screening tool for sleep disordered breathing (SDB) and need for Polysomnography(PSG)/Non-invasive ventilation (NIV) in children with SMA. Methods: A prospective cohort study was conducted in Queensland, Australia with diagnostic PSG completed in DMT naïve children. Transcutaneous carbon dioxide and pulse oximetry were recorded and extracted. Apnoea-hypopnoea indices (AHI) criteria, stratified by age, were applied to define normalcy and indication for non-invasive ventilation (NIV). Abnormal was defined as: ≤3 months of age [mo] AHI≥10 events/hour; > 3mo AHI ≥ 5events/hour. Receiver operating characteristic (ROC) curves and clinically meaningful cut-points were calculated for abnormal PSG and a variety of pulse oximetry/TcCO2 variables. Sensitivity, specificity, and predictive values are reported. Results: Total of45 children recruited (see table 1). The odds ratio of an abnormal PSG if the ODI4≥20 events/hour and a McGill score ≥ 2 was10.1 (95% CI 1.1-89.9; p=0.04). Conclusion: This is the first study to assess utility of pulse oximetry/TcCO2 to screen for need for NIV in children with SMA; particularly important where access to gold standard full diagnostic PSG is limited. TcCO2 adds limited information. Advantages of pulse oximetry: tolerated by children; versatile (e.g. ward/home); may avoid need for a diagnostic PSG(positive screen directed to NIV titration PSG) for some children. Findings need to be validated prospectively. Grant Support: Nil. This abstract is funded by: Nil.
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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 | 0.002 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".