Trends in the epidemiology of childhood nephrotic syndrome in Africa: A systematic review
Bibliographic record
Abstract
Background: Childhood nephrotic syndrome, if left untreated, leads to progressive kidney disease or death. We quantified the prevalence of steroid-sensitive nephrotic syndrome, steroid-resistant nephrotic syndrome, and histological types as the epidemiology of nephrotic syndrome in Africa remains unknown, yet impacts outcomes. Methods: We searched MEDLINE, Embase, African Journals Online, and WHO Global Health Library for articles in any language reporting on childhood nephrotic syndrome in Africa from January 1, 1946 to July 1, 2020. Primary outcomes included steroid response, biopsy defined minimal change disease, and focal segmental glomerulosclerosis (FSGS) by both pooled and individual proportions across regions and overall. Findings: There were 81 papers from 17 countries included. Majority of 8131 children were steroid-sensitive (64% [95% CI: 63-66%]) and the remaining were steroid-resistant (34% [95% CI: 33-35%]). Of children biopsied, pathological findings were 38% [95% CI: 36-40%] minimal change, 24% [95% CI: 22-25%] FSGS, and 38% [95% CI: 36-40%] secondary causes of nephrotic syndrome. Interpretation: Few African countries reported on the prevalence of childhood nephrotic syndrome. Steroid-sensitive disease is more common than steroid-resistant disease although prevalence of steroid-resistant nephrotic syndrome is higher than reported globally. Pathology findings suggest minimal change and secondary causes are common. Scarcity of data in Africa prevents appropriate healthcare resource allocation to diagnose and treat this treatable childhood kidney disease to prevent poor health outcomes. Funding: Funding was provided by the Canadian Institute for Health Research (CIHR) and the National Institute of Health (NIH) for the H3 Africa Kidney Disease Research Network. This research was undertaken, in part, from the Canada Research Chairs program.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.014 | 0.020 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".