Outpatient Management of Cancer-Associated Pulmonary Embolism: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction Outpatient management of pulmonary embolism (PE) remains controversial in patients with cancer due to their higher risks of mortality, recurrent venous thromboembolism (VTE) and bleeding complications. This systematic review and meta-analysis aimed to evaluate the safety and feasibility of outpatient management of cancer-associated PE. Methods We searched MEDLINE, Embase, Cochrane Central, and Scopus databases from inception to May 30, 2024, for studies on outpatient management of cancer-associated PE. Eligible studies included randomized controlled trials, cohort studies, and case-control studies with ≥10 patients. The primary outcome was 30-day-all-cause mortality; secondary outcomes included VTE-related mortality, major bleeding and recurrent VTE at 30 days. Meta-analysis was performed using random effects models, and heterogeneity was assessed with the I2statistic. Results Nineteen studies (13 full-article, 6 abstract-only) with a total of 1589 patients managed as outpatients were identified. Criteria for outpatient management of cancer-associated PE were reported in 14 studies. The pooled 30-day all-cause mortality rate was 1.74% (95% CI: 0.99–3.03; I2=0%, 691 patients, 6 full-article). The 30-day major bleeding pooled rate was 2.71% (95% CI: 1.51–4.83; I2=0%; 406 patients, 6 full-article), and the 30-day recurrent VTE pooled rate was 1.26% (95% CI: 0.53–3.00; I2=0%; 396 patients, 5 full-article). Conclusion Selected patients with cancer-associated PE managed as outpatients appear to have low short-term rates of mortality, major bleeding and recurrent VTE suggesting this may be a safe strategy. Further research with larger, prospective studies is needed to confirm these findings and refine risk stratification protocols.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.039 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".