Adherence to thrombophilia testing guidelines and its influence on anticoagulation therapy: A single-center cross-sectional study
Bibliographic record
Abstract
INTRODUCTION: The collected evidence on thrombophilia guidelines is scarce and data about their impact on clinical decisions are unknown. We aimed to investigate the adherence to thrombophilia testing guidelines, its therapeutic impact in patients with guideline-adherent and non-adherent testing and identify the patients' clinical characteristics mostly associated with treatment decisions. MATERIALS AND METHODS: We conducted a single-center cross-sectional study of patients referred for thrombophilia testing at the outpatient clinic of a tertiary hospital between 01/2010-10/2020. We systematically evaluated the adherence of thrombophilia testing to internal guidelines and the influence of test results on anticoagulation therapy. Using multivariable logistic regression, we evaluated the association between clinical characteristics and influence of thrombophilia tests on anticoagulation therapy in the entire cohort and by indication for referral. RESULTS: Of 3686 included patients, mostly referred for venous thromboembolism (2407, 65 %) or arterial thrombosis (591, 16 %), 3550 patients (96 %) underwent thrombophilia testing. Indication for testing was according to guidelines in 1208 patients (33 %). Test results influenced treatment decisions in 56 of 1102 work-ups (5.1 %) that were adherent to guidelines, and in 237 of 2448 (9.7 %) non-adherent work-ups (absolute difference, 4.3 %; 95 % confidence interval, 2.9-6.3 %). Age < 50 years, female sex, absence of risk factors and co-morbidities, weakly provoked venous thromboembolism and referral indication other than venous thromboembolism were associated with influence on anticoagulation therapy. CONCLUSIONS: Adherence to guidelines for thrombophilia testing was poor and did not have an impact on treatment decisions. Refinement of selection criteria is needed to increase the therapeutic impact of thrombophilia testing.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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".