Health Service Utilization in Children With Permanent Hearing Loss: A Nested Case Control Study
Bibliographic record
Abstract
OBJECTIVE: Permanent hearing loss (PHL) is accompanied by disabilities in approximately 40% of children but little is known about health service use. The objective was to compare health service utilization and chronic complex conditions (CCCs) in children with PHL with matched controls. STUDY DESIGN: Nested case-control study: Data from children with PHL were linked to population-based health administrative data between January 1, 1991 and December 31, 2013, before and after implementation of the Early Hearing Detection and Intervention program in 2002. SETTING: Tertiary care pediatric hospital. PATIENTS: Population-based cohort of 591 children with PHL identified from a clinical database and 2951 matched controls. MAIN OUTCOME MEASURES: CCCs and health services encounters unrelated to hearing within 2 years postbirth. In multivariable models, independent variables were number of CCCs and era of PHL diagnosis. RESULTS: PHL cases had more CCCs (39.9%) than matched controls (8.1%; P <.001) and made greater use of health services: by 2 years postbirth, this included more emergency (IRR 1.25, 95% CI: 1.08-1.46) and outpatient (IRR 1.44, 95% CI: 1.37-1.53) visits and longer inpatient hospitalization (IRR 1.62, 95% CI: 1.50-1.76) than controls. The association between PHL status and health services utilization remained significant after controlling for CCCs and era of PHL diagnosis. CONCLUSIONS: Children with PHL have higher health services use in the first 2 years of life, and are more affected by CCCs. Early identification of these children can optimize outcomes and help plan within the health system.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".