Polysomnography in hospitalized children: Characteristics and clinical practice at a single tertiary care center
Bibliographic record
Abstract
BACKGROUND: Polysomnography (PSG) is the gold standard for the diagnosis of pediatric sleep-disordered breathing (SDB). However, the literature characterizing the indications for inpatient PSGs and the impact on clinical decision-making is limited. OBJECTIVE: To determine the indications, results, and outcomes for children undergoing inpatient PSGs at our institution. METHODS: We performed a retrospective review of children aged 0-18 years who underwent inpatient diagnostic PSGs between July 2018 and July 2021 at SickKids, Toronto, Canada. Baseline characteristics, indications, and management were reviewed and characterized by descriptive statistics. RESULTS: Eighty-eight inpatient PSGs were performed in 75 children (male 62.7%). Median (interquartile range) age and body mass index z-score were 1.5 (0.2, 10.8) years and 0.27 (-1.58, 2.66), respectively. The most common indication for inpatient PSG was initiation and titration of ventilation (n = 34/75, 45.3%). Of the 75 children, 48 (64%) had multiple complex chronic conditions (CCCs). Sixty children (80%) underwent a baseline PSG for either the entire night or a portion of the night. Of these studies, 54 (90%) had clinically significant SDB of which isolated obstructive sleep apnea (OSA; 17/60, 28.3%) was the most common. The following management was undertaken for the 54 patients with SDB; respiratory technology (88.9%), surgical intervention (31.5%), positional therapy (1.9%), intranasal steroids (3.7%), and no further intervention (5.6%), respectively. CONCLUSIONS: Our study highlights that inpatient PSG was an important diagnostic tool resulting in directed medical and surgical management. Future multicenter studies are needed to compare indications for inpatient PSGs across institutions to develop evidence-based clinical practice guidelines.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".