Measurement of D-dimer as aid in risk evaluation of VTE in elderly patients hospitalized for acute illness: A prospective, multicenter study in China
Bibliographic record
Abstract
PURPOSE: Advanced age and hospitalization are associated with increasing risk of venous thromboembolic (VTE) events. The aim of this study was to investigate whether elevated D-dimer levels could predict VTE events in elderly patients hospitalized for acute illness. METHODS: 458 consecutive patients (65% men; mean age, 77 ± 7 years) who were older than 60 years, immobilized for ≥ 3 days, and hospitalized for heart failure, respiratory failure, acute ischemic stroke, or acute infectious disease without pharmacological prophylaxis or recent major surgery, were enrolled. Elevated D-dimer levels were defined as > 500 ng/ml. VTE events included symptomatic VTE within 90 days or asymptomatic deep venous thrombosis screened by compression ultrasonography at enrollment and 3-week follow-up. The association between baseline D-dimer levels and subsequent VTE events, adjusted for age, sex, ethnicity, body mass index, co-morbidities, and acute disease status, was assessed using multivariate Cox proportional hazard models. RESULTS: 49.1% (n = 225) of patients had elevated baseline D-dimer levels, and of these patients, 14.2% (n = 32) developed VTE during the 90-day follow-up. In contrast,only 5.6% (n = 13) of patients with normal D-dimer levels developed VTE. Multivariate analysis showed that patients with elevated D-dimer levels had a 3.2-fold increased risk of developing VTE (95% confidence interval, 1.5-6.5; P = 0.002) in comparison with patients with normal levels. CONCLUSIONS: In elderly patients who were hospitalized for acute medical illness, elevated D-dimer levels are associated with subsequent VTE events. Our data suggest that measurement of D-dimer, a widely-performed objective test, may help clinicians address high-risk individuals for VTE.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".