The Modified Ottawa Score and Clinical Events in Hospitalized Patients with Cancer-Associated Thrombosis from the Swiss VTE Registry
Bibliographic record
Abstract
Abstract The modified Ottawa score (MOS) predicted venous thromboembolism (VTE) recurrence in a cohort of patients with cancer-associated thrombosis mainly managed on an outpatient basis. We aimed to assess the prognostic value of the MOS in hospitalized patients with cancer-associated thrombosis. In 383 hospitalized patients with cancer-associated VTE from the SWIss VTE Registry, 98 (25%) were classified as low risk, 175 (46%) as intermediate risk, and 110 (29%) as high risk for VTE recurrence based on the MOS. Clinical end points were recurrent VTE, fatal VTE, major bleeding, and overall mortality at 90 days. Overall, 179 (47%) patients were female, 172 (45%) had metastatic disease, and 72 (19%) prior VTE. The primary site of cancer was lung in 48 (13%) patients and breast in 43 (11%). According to the MOS, the rate of VTE recurrence was 4.1% for low, 6.3% intermediate, and 5.5% high risk (p = 0.75); the rate of fatal VTE was 0.8, 1.9, and 2.0% (p = 0.69); the rate of major bleeding was 3.1, 4.1, and 3.6% (p = 0.92); and the rate of death was 6.1, 12.0, and 28.2% (p < 0.001), respectively. None of the MOS items was associated with VTE recurrence: female gender hazard ratio (HR) 1.26 (95% confidence interval [CI], 0.53–2.96), lung cancer HR 1.17 (95% CI, 0.35–3.98), prior VTE HR 0.44 (95% CI, 0.10–1.91), breast cancer HR 0.83 (95% CI, 0.19–3.58), and absence of metastases HR 0.74 (95% CI, 0.31–1.74). In hospitalized patients with cancer-associated VTE, the MOS failed to predict VTE recurrence at 3 months but was associated with early mortality.
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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 | 0.005 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".