Kidney function by creatinine and cystatin c and adverse cardiovascular outcomes in patients with atrial fibrillation
Bibliographic record
Abstract
Abstract Background Atrial fibrillation (AF) patients with chronic kidney disease are at an increased risk for ischemic and bleeding events and all-cause mortality. Accurate kidney function estimation is key for risk assessment. Creatinine is commonly used to calculate the Glomerular Filtration Rate (GFR). However, cystatin c has been described to be more sensitive than creatinine independent of muscle mass, autoimmune disease, inflammation or consuming diseases. Thus, cystatin C might be superior for risk assessment in patients with AF. Aim We aimed to investigate the associations between kidney function, assessed by creatinine and cystatin c, and major adverse cardiovascular events (MACE), its individual components, and major bleedings. Methods We enrolled 3865 AF patients into two prospective, multicenter cohort studies. Creatinine and cystatin c were measured at baseline and clinical outcome events were assessed yearly. We calculated GFR using the Chronic Kidney Disease Epidemiology Collaboration [CKD-EPI] formula based on either creatinine (GFRcr), cystatin c (GFRcy) or both (GFRc2). Primary outcome was MACE, defined as a composite of stroke or systemic embolism, myocardial infarction and cardiovascular death. Secondary outcomes were the individual components of MACE and major bleeding. Multivariable adjusted Cox regression analyses were built to investigate the associations between kidney function and adverse outcome events. Results Mean age was 71 ± 10 years and 28% were female. Mean creatinine and cystatin levels were 103 ± 32 μmol/l and 1.2 ± 0.4 mg/l, respectively, translating to a GFRc2 of 63.8 ± 21.7 ml/min/1.73 m2. Over a median follow-up of 6 years, the incidence rates for MACE (per 100 person-years) across quartiles (Q1-Q4) of GFRc2 were 22.0, 19.6, 17.4 and 15.9, respectively (Figure). When using multivariable adjusted Cox regression analysis, MACE was significantly associated with GFRcr (per 1 standard deviation: HR 0.87 (95%CI 0.77; 0.97) p=0.01), GFRcy (HR 0.68 (CI 0.58; 0.78), p<0.001) and GFRc2 (HR 0.75 (CI 0.66; 0.86), p<0.001). This association was mainly driven by cardiovascular death (Table). Major bleeding was associated with GFRcy (HR 0.73 (0.60-0.88) p=0.001) and GFRc2 (HR 0.80 (0.67-0.95), p=0.01), but not with GFRcr (HR 0.91 (95% CI 0.78-1.07) p=0.25). Conclusion Among AF patients, GFR equations including cystatin c were associated both with MACE and bleeding events, while creatinine based GFR equations were only associated with MACE. Therefore, Cystatin c based GFR equations might offer more comprehensive risk stratification in AF patients.Figure 1Table 1
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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) | 0.001 | 0.001 |
| 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 | 0.001 | 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".