Association of Clonal Hematopoiesis of Indeterminate Potential with Worse Kidney Function and Anemia in Two Cohorts of Patients with Advanced Chronic Kidney Disease
Bibliographic record
Abstract
BACKGROUND: Clonal hematopoiesis of indeterminate potential (CHIP) is an inflammatory premalignant disorder resulting from acquired genetic mutations in hematopoietic stem cells. This condition is common in aging populations and associated with cardiovascular morbidity and overall mortality, but its role in CKD is unknown. METHODS: . We also assessed kidney function, hematologic, and mineral bone disease parameters cross-sectionally at baseline, and collected creatinine measurements over the following 5-year period. RESULTS: At baseline, CHIP was detected in 18 of 87 (21%) and 25 of 85 (29%) cohort participants. Participants with CHIP were at higher risk of kidney failure, as predicted by the Kidney Failure Risk Equation (KFRE), compared with those without CHIP. Individuals with CHIP manifested a 2.2-fold increased risk of a 50% decline in eGFR or ESKD over 5 years of follow-up (hazard ratio 2.2; 95% confidence interval, 1.2 to 3.8) in a Cox proportional hazard model adjusted for age, sex, and baseline eGFR. The addition of CHIP to 2-year and 5-year calibrated KFRE risk models improved ESKD predictions. Those with CHIP also had lower hemoglobin, higher ferritin, and higher red blood cell mean corpuscular volume versus those without CHIP. CONCLUSIONS: In this exploratory analysis of individuals with preexisting CKD, CHIP was associated with higher baseline KFRE scores, greater progression of CKD, and anemia. Further research is needed to define the nature of the relationship between CHIP and kidney disease progression.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".