Liver and renal biochemical profiles of people with sickle cell disease in Africa: a systematic review and meta-analysis of case-control studies
Bibliographic record
Abstract
BACKGROUND: Sickle cell disease (SCD) is a genetic blood disorder characterized by a painful vaso-occlusive crisis due to the sickling of red blood cells in capillaries. Complications often lead to liver and renal dysfunctions, contributing to morbidity and mortality, particularly for children under 5. This systematic review and meta-analysis aimed to evaluate the liver and renal functions of people with SCD (HbSS) compared to those without it (HbAA) in Africa. METHODS: The protocol was registered with PROSPERO (CRD42022346771). We searched PubMed, Embase, Web of Science, and Google Scholar using the keywords "liver function", "renal function", "sickle cell disease", and "Africa" on 6th May 2023 for peer-reviewed articles with abstracts in English. We included case-control studies comparing SCD (HbSS) with controls without hemoglobinopathies (HbAA). We used the random-effect model to calculate the pooled average values for the blood tests of people with SCD in RStudio version 4.2.2. RESULTS: = 87%, p < 0.01) compared to controls. CONCLUSION: ) > 50%, there was substantial variation in the reported articles' results. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42022346771.
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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 | 0.012 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.022 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".