Waiting Too Long: The Contribution of Delayed Surgical Access to Pediatric Disease Burden in Somaliland
Bibliographic record
Abstract
BACKGROUND: Delayed access to surgical care for congenital conditions in low- and middle-income countries is associated with increased risk of death and life-long disabilities, although the actual burden of delayed access to care is unknown. Our goal was to quantify the burden of disease related to delays to surgical care for children with congenital surgical conditions in Somaliland. METHODS: We collected data from medical records on all children (n = 280) receiving surgery for a proxy set of congenital conditions over a 12-month time period across all 15 surgically equipped hospitals in Somaliland. We defined delay to surgical care for each condition as the difference between the ideal and the actual ages at the time of surgery. Disability-adjusted life years (DALYs) attributable to these delays were calculated and compared by the type of condition, travel distance to care, and demographic characteristics. RESULTS: We found long delays in surgical care for these 280 children with congenital conditions, translating to a total of 2970 attributable delayed DALYs, or 8.4 avertable delayed DALYs per child, with the greatest burden among children with neurosurgical and anorectal conditions. Over half of the families seeking surgical care had to travel over 2 h to a surgically equipped hospital in the capital city of Hargeisa. CONCLUSIONS: Children with congenital conditions in Somaliland experience substantial delays to surgical care and travel long distances to obtain care. Estimating the burden of delayed surgical care with avertable delayed DALYs offers a powerful tool for estimating the costs and benefits of interventions to improve the quality of surgical care.
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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 | 0.004 |
| 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 | 0.000 |
| 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".