Caractéristiques socio-démographiques et cliniques de la goutte en population Afro-descendante : une revue systématique de la littérature
Bibliographic record
Abstract
INTRODUCTION: Findings regarding gout in African Americans (AA) are often influenced by socio-economic factors and comorbidities associated with these populations. The sole ethnicity is insufficient to explain the increased risk of developing gout in the AA population. To date, there are few data regarding demographic characteristics and the clinical features (comorbidities and cardiovascular risk factors) in patients of African descent with gout. However, management of the comorbidities associated with gout is a critical component of the multidisciplinary management of gouty patients. METHODS: We conducted a systematic review of the literature focusing on clinical and demographic features of gout in the African-descent population. Two independent reviewers used PRISMA methodology and COVIDENCE software for title and abstract screening, followed by text screening. Quality of studies was assessed using the Newcastle-Ottawa Scale. Quantitative data were expressed as mean +/- standard deviation, and binary variables as percentage. Preliminary comparative data were obtained using logistic regression analysis (univariate analysis). RESULT: We identified 21 studies. A wide variability in clinical and demographic characteristics was reported between the AA and Sub-Saharan Africa (SSA) cohorts. The proportion of female patients, hypertension and diabetes appeared to be lower in SSA gout patients. Within the same geographical area, such features also differed: patients from the USA and patients from SSA. Socioeconomic data showed some discrepancies within SSA patients, and AA goutty patients were no different from Caucasians in terms of educational status in the only U.S. study on the topic. DISCUSSION: This is the first review of the literature regarding demographic and clinical profiles of gout in Afro-descendant populations. We report significant discrepancies in these characteristics between AA and SSA patients, as well as within the same geographical area (SSA and USA). These data suggest an influence of geolocation on gout-associated comorbidities in Afro-descendant populations and raise concerns regarding use of the ethnicity as a proxy to understand specific phenotypes that might occur in “black” goutty populations.
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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 | 0.025 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.034 | 0.032 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".