The impact of polysomnograms and family-centred decision making in children with medical complexity
Bibliographic record
Abstract
Objectives: To determine whether a change in clinical management (e.g., new tracheostomy or adenotonsillectomy) occurred following a polysomnogram (PSG) in children with medical complexity (CMC) and to explore whether families' goals of care (regarding results and treatment implications) were discussed prior to the completion of a PSG. Methods: All CMC enrolled in a complex care program at the Hospital for Sick Children, Canada, who underwent a baseline PSG from 2009 to 2015 were identified. Exclusion criteria included (1) PSGs for ventilation titration and (2) PSGs outside the study time frame. Health records were retrospectively reviewed to determine demographics, medical histories, families' wishes, PSG results, and their impact on clinical care. Descriptive statistics were used to summarize results. Results: Of 145 patients identified, 96 patients met inclusion criteria. Fifty (52%) were male. Median age was 3 years. Forty-eight (50%) were diagnosed with clinically significant (i.e., moderate to severe obstructive sleep apnea, central sleep apnea, and/or hypoventilation) sleep-related breathing disorders. Of those diagnosed, 9 (19%) had surgery, 25 (52%) underwent respiratory technology initiation, and 3 (6%) underwent both. In the remaining 11 (23%) patients, treatment was either considered too risky or did not align with the families' wishes. Only 3 of 96 patients had clear documentation of their families' wishes prior to PSG completion. Conclusion: Recognizing the burden of medical tests for both the child and the health care system, a process of shared-decision making that includes clarifying a family's wishes may be prudent prior to conducting a PSG.
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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 | 0.002 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".