Role of Gender in the Clinical Presentation of a First Deep Venous Thrombosis (DVT) in Outpatients.
Bibliographic record
Abstract
Abstract BACKGROUND: As clinical assessment of pretest probability (PTP) is now considered the first step in the diagnostic evaluation of DVT it is important to know if the clinical features of DVT are the same in men and women. OBJECTIVES: We sought to answer the following questions: 1) Is the prevalence of DVT the same in men and women who are referred for diagnostic testing? 2) Are the clinical features of DVT the same in men and women? 3) Does the Wells’ clinical prediction model for first DVT perform similarly in men and women? METHODS: We performed a retrospective analysis of individual patient data from three studies that evaluated diagnostic testing in outpatients with a suspected first episode of DVT. Associations were assessed using univariable and multivariable analyses. RESULTS: A total of 1838 patients were eligible for final analyses, of whom 1132 (62%) were women and 706 (38%) were men. DVT was objectively diagnosed in 208 patients (11%). QUESTION 1: The prevalence of DVT was higher in men (14%) than in women (9%) (p=0.001). In a multivariable analysis that included eleven other clinical variables male gender was independently associated with a higher prevalence of DVT (OR 1.5, 95% CI 1.1–2.1). QUESTION 2: Of the confirmed episodes of DVT, “swelling of the entire leg” was observed more often in women (41%) than in men (16%) (p<0.001). This difference was partly explained by more extensive thrombosis in women than in men; the common femoral vein was involved on ultrasound in 48% of women and 22% of men (p< 0.001). The frequency of other clinical features was similar in men and women. QUESTION 3: The prevalence of DVT was higher in men than in women who were categorized by the Wells model as having a low PTP (6.9% vs 3.6%; p=0.025) or a moderate PTP (16.9% vs. 8.7%; p<0.001), but similar in the high PTP category (40% vs 44%; p=0.6). Five clinical features were more strongly associated with presence of DVT in women than in men: “swelling of the entire leg” (OR 7.7 vs. 1.6; p<0.001), “difference in calf circumference >3cm” (OR 8.2 vs. 2.9; p<0.001), “pitting edema” (OR 4.4 vs. 1.8; p=0.004), “age > 60 yrs” (OR 1.8 vs. 0.9; p=0.02) and “bedridden for greater than 3 days” (OR 3.7 vs. 1.4; p=0.05). CONCLUSIONS: Among outpatients referred with a suspected first episode of DVT, the prevalence of DVT is higher in men than in women but DVT is more extensive in women. Entire leg swelling is a more common and important sign of DVT in women than in men and the Wells prediction rule behaves differently in men than in women.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".