Clonal Hematopoiesis Is Associated With Long‐Term Adverse Outcomes Following Cardiac Surgery
Bibliographic record
Abstract
Background Cardiac surgery triggers sterile innate immune responses leading to postoperative complications. Clonal hematopoiesis (CH) is associated with short‐term inflammation‐mediated outcomes after cardiac surgery. The impact of CH on long‐term postoperative outcomes remains unknown. Methods and Results In this cohort study, patients undergoing elective cardiac surgery were included from January 2017 to September 2019. Patients were screened for CH using a predefined gene panel of 19 genes. Recorded clinical events were all‐cause death, major adverse cardiac and cerebral events including cardiovascular death, myocardial infarction or nonscheduled coronary revascularization, stroke, and hospitalization for acute heart failure. The primary study outcome was time to a composite criterion including all‐cause mortality and major adverse cardiac and cerebral events. Among 314 genotyped patients (median age: 67 years; interquartile range 59–74 years), 139 (44%) presented with CH, based on a variant allelic frequency ≥1%. Carriers of CH had a higher proportion of patients with a history of atrial fibrillation (26% for CH versus 17% for non‐CH carriers, P =0.022). The most frequently mutated genes were DNMT3A , TET2 , and ASXL1 . After a median follow‐up of 1203 [813–1435] days, the primary outcome occurred in 50 patients. After multivariable adjustment, CH was independently associated with a higher risk for the primary outcome (hazard ratio, 1.88 [95% CI, 1.05–3.41], P =0.035). Most adverse events occurred in patients carrying TET2 variants. Conclusions In patients undergoing cardiac surgery, CH is frequent and associated with a 2‐fold increased long‐term risk for major adverse clinical outcomes. CH is a novel risk factor for long‐term postcardiac surgery complications and might be useful to personalize management decisions. Registration URL: https://www.clinicaltrials.gov ; Unique identifier: NCT03376165.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".