Is Low Body Weight a Novel Risk Factor for Thromboembolic Events in Patients With Non-Valvular Atrial Fibrillation?
Bibliographic record
Abstract
In this issue of the Journal, Hamatani et al 5 address this important issue by analyzing data from the Fushimi AF Registry, a community-based Japanese prospective cohort.Patients with low body weight (LBW: ≤50 kg) showed a higher risk profile and a higher incidence of stroke/SE, but no difference in the incidence of major bleeding compared with those over 50 kg using multivariate and propensity score matching analyses.Although there have been several studies investigating the effect of obesity or overweight on the outcome for AF patients in Caucasian populations, the influence of LBW or low body mass index (BMI) has not been evaluated, because patients with low BMI (<18.5 kg/m 2 ) have been excluded from such studies.6-8 Furthermore, their conflicting results suggest that it is still uncertain whether obesity or overweight is a risk factor for thromboembolic events in AF patients.In an Asian population, Wang et al showed that underweight AF patients (BMI <18.5 kg/m 2 ) had a higher rate of cardiovascular mortality than either overweight or obese AF patients (BMI ≥24 kg/m 2 ), revention of cardioembolic stroke and systemic embolism (SE) in patients with atrial fibrillation (AF) is of significance importance in the super-aging Japanese society, and therefore appropriate risk assessment and the following sufficient anticoagulation treatment are encouraged.The CHADS2 or CHA2DS2-VASc score has been used as a risk stratification scheme for non-valvular AF (NVAF) patients worldwide.1-4 In Europe and the United States, the CHA2DS2-VASc score is recommended (Figure 1), 1,2 whereas in Japan and Canada, the modified risk scheme based on the CHADS2 score is used.3,4 Female sex is not included as a risk in the Japanese or Canadian guidelines.Importantly, neither CHADS2 nor CHA2DS2-VASc includes body weight or related factors, because it is uncertain whether body weight itself is a risk factor for thromboembolic events in NVAF patients.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| 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".