A Journey Undertaken by Families to Access General Surgical Care for their Children at Muhimbili National Hospital, Tanzania; Prospective Observational Cohort Study
Bibliographic record
Abstract
BACKGROUND: A majority of the 2 billion children lacking access to safe, timely and affordable surgical care reside in low-and middle-income countries. A barrier to tackling this issue is the paucity of information regarding children's journey to surgical care. We aimed to explore children's journeys and its implications on accessing general paediatric surgical care at Muhimbili National Hospital (MNH), a tertiary centre in Tanzania. METHODS: A prospective observational cohort study was undertaken at MNH, recruiting patients undergoing elective and emergency surgeries. Data on socio-demographic, clinical, symptoms onset and 30-days post-operative were collected. Descriptive statistics and Mann-Whitney, Kruskal-Wallis and Fisher's exact tests were used for data analysis. RESULT: We recruited 154 children with a median age of 36 months. The majority were referred from regional hospitals due to a lack of paediatric surgery expertise. The time taken to seeking care was significantly greater in those who self-referred (p = 0.0186). Of these participants, 68.4 and 31.1% were able to reach a referring health facility and MNH, respectively, within 2 h of deciding to seek care. Overall insurance coverage was 75.32%. The median out of pocket expenditure for receiving care was $69.00. The incidence of surgical site infection was 10.2%, and only 2 patients died. CONCLUSION: Although there have been significant efforts to improve access to safe, timely and affordable surgical care, there is still a need to strengthen children's surgical care system. Investing in regional hospitals may be an effective approach to improve access to children 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".