Profil épidémio-clinique des atteintes dermatologiques chez le noir africain en hémodialyse chronique
Bibliographic record
Abstract
INTRODUCTION: Dermatologic manifestations are common among patients on chronic hemodialysis and may represent systemic involvement. Our study aims to determine the epidemiological and clinical profile of skin damages in black patients living in Yaounde, Cameroon. METHODS: We conducted a cross sectional study including all patients receiving chronic haemodialysis treatment for at least 3 months in two hemodialysis centers in Yaounde from February to May 2014. Patients underwent an interview and a dermatological examination. Chi-squared tests and Student's t-test (or equivalents) were used for statistical analysis, with significance level at p <0.05. RESULTS: A total of 112 patients (78 (69.9%) men) with an average age of 48.6 ± 13 years and a mean duration of dialysis of 46,3 ± 37 months were included in the study. Skin lesions were present in 94 (83.9%) patients. Xerosis (63.3%), pruritus (37.5%), melanoderma (34.8%), acne (12.5%) and half and half nails (10.7%) were the most common dermatologic manifestations. Xerosis was associated with anuria (p = 0.0001) and advanced age (p = 0.032); melanoderma was associated with anuria (p = 0.042) and time spent on dialysis (p = 0.027) while half and half nails were associated with young age (p = 0.018) and biweekly dialysis (p = 0.01 ). CONCLUSION: Skin damages are frequent and dominated by xerosis, pruritus and melanoderma in patients on chronic hemodialysis living in Yaounde. Biweekly dialysis, advanced age, anuria and time spent on dialysis were associated factors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".