Access to pediatric surgery delivered by general surgeons and anesthesia providers in Uganda: Results from 2 rural regional hospitals
Bibliographic record
Abstract
BACKGROUND: Significant limitations in pediatric surgical capacity exist in low- and middle-income countries, especially in rural regions. Recent global children's surgical guidelines suggest training and support of general surgeons in rural regional hospitals as an effective approach to increasing pediatric surgical capacity. METHODS: Two years of a prospective clinical database of children's surgery admissions at 2 regional referral hospitals in Uganda were reviewed. Primary outcomes included case volume and clinical outcomes of children at each hospital. Additionally, the disability-adjusted life-years averted by delivery of pediatric surgical services at these hospitals were calculated. Using a value of statistical life calculation, we also estimated the economic benefit of the pediatric surgical care currently being delivered. RESULTS: From 2016 to 2019, more than 300 surgical procedures were performed at each hospital per year. The majority of cases were standard general surgery cases including hernia repairs and intussusception as well as procedures for surgical infections and trauma. In-hospital mortality was 2.4% in Soroti and 1% in Lacor. Pediatric surgical capacity at these hospitals resulted in over 12,400 disability-adjusted life-years averted/year. This represents an estimated economic benefit of 10.2 million US dollars/year to the Ugandan society. CONCLUSION: This investigation demonstrates that lifesaving pediatric procedures are safely performed by general surgeons in Uganda. General surgeons who perform pediatric surgery significantly increase surgical access to rural regions of the country and add a large economic benefit to Ugandan society. Overall, the results of the study support increasing pediatric surgical capacity in rural areas of low- and middle-income countries through support and training of general surgeons and anesthesia providers.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".