ArticleSurgery today2019
Predicting mortality in patients admitted to the intensive care unit after open vascular surgery.
Article in Surgery today, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Risk Prediction Models for Peri-Operative Mortality in Patients Undergoing Major Vascular Surgery with Particular Focus on Ruptured Abdominal Aortic Aneurysms: A Scoping Review.Journal of clinical medicine · 2023Article
- Delirium in the intensive care unit and its importance in the post-operative context: A review.Frontiers in medicine · 2023Review
- Red Blood Cell Distribution Width Predicts Myocardial Infarction and Mortality After Vascular Surgery-A Prospective Cohort Study.World journal of surgery · 2022Article
- Validation of the PreOperative Score to predict Post-Operative Mortality (POSPOM) in Dutch non-cardiac surgery patients.BMC anesthesiology · 2022Article
- Effect of Preoperative Chronic Opioid Use on Mortality and Morbidity in Vascular Surgical Patients.Cureus · 2021Article
- The effect of cognitive dysfunction on mid- and long-term mortality after vascular surgery.BMC geriatrics · 2021Observational
- The level of postoperative care influences mortality prediction by the POSPOM score: A retrospective cohort analysis.PloS one · 2021Article
- Validation of the Preoperative Score to Predict Postoperative Mortality (POSPOM) in Germany.PloS one · 2021Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposesVascular surgery (VS) has a higher perioperative mortality than other types of surgery. We compared different scores for predicting mortality in patients admitted to the intensive care unit (ICU) after open VS.
methodsPatients admitted to the ICU after open VS from 2006 to 2013 were included. We calculated the Acute Physiology and Chronic Health Evaluation (APACHE), Simplified Acute Physiology Score (SAPS), Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (POSSUM) and Preoperative Score to Predict Postoperative Mortality (POSPOM). We performed multivariate logistic regression to assess independent factors with the calculation of odds ratios (ORs) and 95% confidence intervals (CIs). We tested the predictive ability of the scores using the area under the receiver operating characteristics curve (AUROC).
resultsA total of 833 consecutive patients were included. Hospital mortality was 5.1% (1.3% after intermediate-risk and 8.4% after high-risk surgery). In the multivariate analysis, the age (OR 1.04, 95% CI 1.01-1.08, p = 0.013), smoking status (OR 2.46, 95% CI 1.16-5.21, p = 0.019), surgery risk (OR 2.92, 95% CI 1.05-8.08, p = 0.040), serum sodium level (OR 1.17, 95% CI 1.10-1.26, p < 0.001), urea (OR 1.01, 95% CI 1.01-1.02, p = 0.001) and leukocyte count (OR 1.05, 95% CI 1.01-1.10, p = 0.009) at admission were considered independent predictors. Hematocrit (0.86, 95% CI 0.80-0.93, p < 0.001) was considered an independent protective factor. The AUROC of our model was 0.860, compared to SAPS (0.752), APACHE (0.774), POSPOM (0.798) and POSSUM (0.829).
conclusionThe observed mortality was within the predicted range (1-5% after intermediate-risk and > 5% after high-risk surgery). POSSUM and POSPOM had slightly better predictive capacity than SAPS or APACHE.
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