Causes of Deaths in Children under-Five Years Old at a Tertiary Hospital in Limpopo Province of South Africa
Bibliographic record
Abstract
OBJECTIVE: Accurate and timely information on the causes of child deaths is essential in guiding efforts to improve child survival, by providing data from which health profiles can be constructed and relevant health policies formulated. The purpose of this study was to identify causes of death in children younger than 5 years-old in a tertiary hospital in South Africa. METHODS: Death certificates from the Pietersburg/Mankweng hospital complex, for the period of January 1, 2008 through December 31, 2010, were obtained for all patients younger than 5 years and were retrospectively reviewed. Data were collected using a data collection form designed for the study. Information abstracted included: date of death, age, sex, and cause of death. RESULTS: A total of 1266 deaths were recorded, the sex ratio was 1.26 boys per girl. About 611 (48%) of deaths were listed as neonatal deaths (0-28 days), 387 (31%) were listed as infant deaths (29 days-11 months), and 268 (21%) as children's death (1-4 years). For neonates the leading causes of death were: prematurity/low birth weight, birth asphyxia and pneumonia. For the infant death group, the leading causes of death were pneumonia, diarrhea, and HIV/AIDS; and in the children's group, the leading causes were injuries, diarrhea and pneumonia. There was no statistical significant difference in the proportions of causes of death based on the sex of children. CONCLUSION: The top 10 leading causes of death in children under-5 years old treated at Pietersburg/Mankweng Hospital Complex were in descending order: prematurity/low birth weight, pneumonia, diarrheal diseases, birth asphyxia, and severe malnutrition, HIV/AIDS, hydrocephalus, unintentional injuries, meningitis and other infections. These ten conditions represent 73.9% of causes of death at this facility. A mix of multi-faceted interventions is needed to address these causes of death in children.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".