Paediatric Dialysis at a Tertiary Hospital in South-West Nigeria: A 4-Year Report
Bibliographic record
Abstract
INTRODUCTION: Dialysis is potentially lifesaving in children with acute kidney injury (AKI) or chronic kidney disease (CKD), but availability is limited in low-income countries and lower-middle-income countries (LMICs). METHODS: In the present study, we perform a 4-year study of patients who received peritoneal dialysis (PD) or haemodialysis (HD) at the Paediatric Nephrology Unit of the University College Hospital Ibadan, Nigeria. Subgroup analysis was performed on patients with sepsis or malaria AKI who underwent HD or PD for predictors of in-hospital mortality. RESULTS: A total of 167 children aged 7 days to 18 years, median 7 (interquartile range 3-12) years, (60.5% males) were studied. In total, 129 (77.2%) had AKI, while 38 had CKD. Regarding AKI, 83 children (64.3%) received HD only, 42 underwent PD only, while 4 underwent both HD and PD. Malaria AKI was treated with HD in 43 (51.8%) or PD in 8 (10.5%), while sepsis AKI was treated with HD in 20 (21.4%) or PD in 33 (78.6%). Mortality in AKI was 16.3% overall, 10.8% in children on HD only, and 26.2% in children on PD only. Patients with sepsis AKI had higher mortality compared to patients with malaria AKI (RR 7.96 [1.70-37.37]). Subgroup analysis showed that age, diagnosis, and dialysis modality were not independent risk factors for mortality. The aetiology of CKD was glomerulonephritis in 26 (68.4%): treatment was HD in 36 and PD in 2 with mortality being 26.3%. CONCLUSIONS: PD for AKI showed relatively good outcomes in a LMIC. However, funding and support for a formal dialysis program for the management of AKI and CKD are needed.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".