Epidemiology of chronic kidney disease in northern region of Senegal: a community-based study in 2012
Bibliographic record
Abstract
INTRODUCTION: Chronic kidney disease (CKD) is an emerging worldwide epidemic but few data are available in African populations. We aimed to assess prevalence of CKD in adult populations of Saint-Louis (northern Senegal). METHODS: In a population-based survey between January and May 2012, we included 1,037 adults aged=18 years living in Saint-Louis. Socio-demographical, clinical and biological data were collected during household visits. Serum creatinine was measured by Jaffé method. We estimated glomerular filtration rate (eGFR) using the 4-variables MDRD equation and CKD was defined by eGFR<60 mL/min/1.73 m2 and/or albuminuria>1g/L. A multivariate logistic regression was performed to identify factors associated with CKD. RESULTS: Mean participants' age was 47.9±16.9 years (18-87) and sex-ratio was 0.52. Majority of participants lived in urban areas (55.3% rural) and had school education (65.6%). Overall prevalences of hypertension, diabetes and obesity were 39.1%, 12.7% and 23.4% respectively. Prevalence of CKD was 4.9% (95% CI=3.5-6.2) and 0.9% had GFR<30 mL/min/1.73 m2. Albuminuria>1g/l was found in 3.5% of people. CKD was significantly more frequent among hypertensive patients compared to normotensive participants. Only 23% of patients were aware of their disease before the survey. After multivariate logistic analysis, presence of CKD was significantly associated with hypertension (OR=1.12, p=0.02) and age (OR=1.03, p=0.02). CONCLUSION: CKD is frequent in adult population living Northern Senegal. Main associated factors are hypertension and age. Prevention strategy is urgently needed to raise awareness and promote CKD detection and early treatment in both urban and rural areas.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".