Medical oncologists’ and palliative care physicians’ opinions towards thromboprophylaxis for inpatients with advanced cancer: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Patients with advanced cancer are increasingly discharged from inpatient settings following focused symptom management admissions. Thromboprophylaxis (TP) is recommended for patients with cancer admitted to acute care settings; less is known about TP use in palliative care (PC) settings. This study explored the opinions of Canadian medical oncologists (MO) and PC physicians regarding the use of TP for inpatients with advanced cancer. METHODS: A fractional factorial survey designed to evaluate the impact of patient factors (age, clinical setting, reason for admission, pre-admission performance status (Eastern Cooperative Oncology Group; ECOG), and risk of bleeding on anticoagulation) and physician demographics on recommending TP was administered by email to Canadian MO and PC physicians. Each respondent received eight vignettes randomly selected from a set of 32. Hierarchical regression was used to evaluate the odds of prescribing TP adjusted for patient factors. RESULTS: 606 MO and 491 PC physicians were surveyed; response rates were 11.1% and 15.0%, respectively. MO were predominantly male (59.7%); PC female (60.3%); most worked in academic environments (90.3% MO; 73.9% PC). Multivariable hierarchical logistic regression demonstrated that all patient factors except age were associated with prescribing TP (ORs range: from 1.34 (95% CI 1.01 to 1.77) for good ECOG, to 2.53 (95% CI 1.9 to 3.37), for reversible reason for admission). Controlling for these factors, medical specialty was independently associated with recommending TP (OR for MO 2.09 (95% CI 1.56 to 2.8)). CONCLUSIONS: MO have higher odds of recommending TP for inpatients with advanced cancer than PC physicians. Further research exploring the drivers of these differing practices is warranted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".