Impact of Thrombus Sidedness on Presentation and Outcomes of Patients with Proximal Lower Extremity Deep Vein Thrombosis
Bibliographic record
Abstract
Abstract Small studies have suggested differences in demographics and outcomes between left- and right-sided deep vein thrombosis (DVT), and also unilateral versus bilateral DVT. We investigated the clinical presentation and outcomes of patients with DVT based on thrombus sidedness. The authors used the data from the Registro Informatizado Enfermedad TromboEmbólica (RIETE) database (2001–2016) to identify patients with symptomatic proximal lower-extremity DVT. Main outcomes included cumulative 90-day symptomatic pulmonary embolism (PE) and 1-year mortality. Overall, 30,445 patients were included. The majority of DVTs occurred in the left leg (16,421 left-sided, 12,643 right-sided, and 1,390 bilateral; p < 0.001 for chi-squared test comparing all three groups). Comorbidities were relatively similar in those with left-sided and right-sided DVT. Compared with those with left-sided DVT, patients with right-sided DVT had higher relative frequency of PE (26% versus 23%, p < 0.001) and 1-year mortality (odds ratio [OR]: 1.08; 95% confidence interval [CI]: 1.00–1.18). This difference in mortality did not persist after multivariable adjustment (OR: 1.01; 95% CI: 0.93–1.1). Patients with bilateral DVT had a greater burden of comorbidities such as heart failure, and recent surgery compared with those with unilateral DVT (p < 0.001), and higher relative frequency of PE (48%), and 1-year mortality (24.1%). Worse outcomes in patients with bilateral DVT were attenuated but persisted after multivariable adjustment for demographics and risk factors (OR: 1.64; 95% CI: 1.43–1.87). Patients with bilateral DVT had worse outcomes during and after discontinuation of anticoagulation. There is a left-sided preponderance for proximal lower-extremity DVT. Compared with those with left-sided DVT, patients with right-sided DVT have slightly higher rates of PE. Bilateral DVT is associated with markedly worse short-term and 1-year outcomes.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".