APOL1 Risk Variants and Subclinical Cardiovascular Disease in Incident Hemodialysis Patients
Bibliographic record
Abstract
Introduction To better understand the impact of APOL1 risk variants in end-stage renal disease (ESRD) we evaluated associations of APOL1 risk variants with subclinical cardiovascular disease (CVD) and mortality among African Americans initiating hemodialysis and enrolled in the Predictors of Arrhythmic and Cardiovascular Risk in ESRD cohort study. Methods We modeled associations of APOL1 risk status (high = 2; low = 0/1 risk alleles) with baseline subclinical CVD (left ventricular [LV] hypertrophy; LV mass; ejection fraction; coronary artery calcification [CAC]; pulse wave velocity [PWV]) using logistic and linear regression and all-cause or cardiovascular mortality using Cox models, adjusting for age, sex, and ancestry. In sensitivity analyses, we further adjusted for systolic blood pressure and Charlson Comorbidity Index. Results Of 267 African American participants successfully genotyped for APOL1 , 27% were high-risk carriers, 41% were women, and mean age was 53 years. At baseline, APOL1 high- versus low-risk status was independently associated with 50% and 53% lower odds of LV hypertrophy and CAC, respectively, and 10.7% lower LV mass. These associations were robust to further adjustment for comorbidities but not systolic blood pressure. APOL1 risk status was not associated with all-cause or cardiovascular mortality (mean follow-up 2.5 years). Conclusion Among African American patients with incident hemodialysis, APOL1 high-risk status was associated with better subclinical measures of CVD but not mortality.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".