Predictors of 90-Day Mortality in Patients with Acute Pulmonary Embolism- a 5-Year Retrospective Cohort Study of Patients in One Canadian Health Region
Bibliographic record
Abstract
BACKGROUND Acute pulmonary embolism (PE) can be fatal if not treated. PE is linked to major co-morbidities such as cancer and ischemic heart disease. Recurrence of PE may occur and is linked to high morbidity and death. Although acute PE is a common diagnosis, the incidence is still unknown in our health region. Published studies from other countries indicate an annual incidence between 0.2 and 0.8 /1000 persons, where the variation may be related to different inclusion criteria. Our knowledge about the association between concomitant diseases and PE and its outcomes is mostly based on data from clinical trials, and these patients may not fully represent real-life PE patients. This potentially limits our understanding of concomitant disorders that are associated to PE. We sought to determine 90-day survival and predictors of mortality for patients with acute PE in a real world setting. METHODS We retrospectively analyzed a cohort of adult outpatients aged ≥18 years with objectively confirmed acute PE between 2014 and 2019. PE was identified by positive diagnostic imaging from radiology reports obtained via search of the Picture Archiving and Communication System (PACS) database in the Eastern Health Region of Newfoundland and Labrador, Canada. We defined the clinical end-point as all-cause death within 90 days of PE diagnosis at a health facility in the health region. Cox-regression analysis was used to study the impact of patient characteristics and comorbidities on 90-day survival after the episode of acute PE. RESULTS A total of 1184 patients were identified as having acute PE between 2014 and 2019 within the Eastern Health Region. The annual incidence of PE among adults was estimated at 0.95/1000 persons. Of the total, 785 patients were diagnosed with acute PE as outpatients and were included in our study. Mean age was [SD] 63.4 ± 15.9 years, weight [SD] 92.0 ± 30.4 kilograms, and 42.3% were men. Patients were followed for 67274 person-days and 61 (7.8%) of outpatients died. Surgery ≤ 2 weeks prior to acute PE (44.6%), cancer (44.2%) and previous venous thromboembolism (15.2%) were most prevalent comorbid conditions among the patients [Table 1]. Male patients had a multivariate-adjusted hazard ratio (HR) of 5.63 (95% CI: 1.49 - 21.32); p = 0.011; 3.24 (95%CI: 1.47 - 7.14); p=0.004 and 2.48 (95% CI: 1.39-4.42); p=0.002 for 7, 30 and 90-day mortality respectively compared to females. Patients who had surgery ≤ 2 weeks prior to acute PE were associated with HR: 6.29 (95%CI: 1.31 - 30.29) p=0.0218; HR: 4.34 (95%CI: 1.79 - 10.48) p=0.001 and HR: 2.00 (95%CI: 1.18 - 3.52); p=0.010 higher risk of 7, 30 and 90 day-mortality, respectively. Having cancer was associated with increased risk of 30-day (HR: 6.13[95%CI: 1.81 - 20.72]; p=0.004) and 90-day (HR; 4.27 [95%CI: 1.87 - 9.72]; p<0.001) mortality. An increase in weight is associated with lower risk of 30 (HR; 0.95 [95%CI: 0.94 - 0.99]; p=0.007) and 90-day mortality (HR: 0.97[95%CI: 0.95 - 0.99]; p<0.001) respectively [Figure 1]. CONCLUSIONS Male sex, surgery ≤ 2 weeks prior to PE, cancer and weight are factors that predicted 90-mortality among patients with acute PE. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".