Clonal hematopoiesis of indeterminate potential is associated with worse kidney function and anemia in a cohort of patients with advanced chronic kidney disease
Bibliographic record
Abstract
Abstract Background Clonal hematopoiesis of indeterminate potential (CHIP) is an inflammatory premalignant disorder resulting from acquired genetic mutations in hematopoietic stem cells. CHIP is common in aging populations and associated with cardiovascular morbidity and overall mortality, but its role in chronic kidney disease (CKD) has not been investigated. Methods We performed targeted sequencing to detect CHIP mutations in a cohort of 87 adults with eGFR < 60 ml/min/1.73m 2 . Kidney function, hematologic, and mineral bone disease parameters were assessed cross-sectionally at baseline, and a total of 2,091 creatinine measurements and 3,382 hemoglobin measurements were retrospectively collected over the following 12-year period. Results At baseline, 20 of 87 (23%) cohort participants had CHIP detected. Those with CHIP had lower baseline eGFR (22.3 ± 11.2 vs. 28.2 ± 11.5 ml/min/1.73 m 2 , P = 0.04) in age- and sex-adjusted regression models. Individuals with CHIP had a 2.5–fold increased risk of incident 50% decline in eGFR or ESKD in a Cox proportional hazard model adjusted for age and sex (95% confidence interval, 1.3–4.7). The annualized rate of eGFR decline adjusted for age and sex was -2.3 ±1.1 ml/min/1.73m 2 per year in those with CHIP versus -1.6 ±0.5 ml/min/1.73m 2 per year in those without CHIP. Further, those with CHIP had lower hemoglobin at baseline (11.6 ± 0.3 vs. 12.8 ± 0.2 g/dL, P = 0.0003) and throughout the follow-up period despite a greater use of erythropoiesis-stimulating agents. Conclusion In those with pre-existing CKD, CHIP was associated with lower eGFR at baseline, faster progression of CKD, and anemia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".