ArticleJournal of the American Heart Association2020
Derivation and Validation of a Clinical Model to Predict Intensive Care Unit Length of Stay After Cardiac Surgery.
Article in Journal of the American Heart Association, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Development and external validation of an interpretable machine learning model for predicting prolonged postoperative ICU length of stay in coronary artery bypass grafting patients using MIMIC-IV 3.1 and eICU-CRD 2.0.BMC medical informatics and decision making · 2026Article
- Analysis of risk factors and adverse outcomes for hyperlacidemia following acute Stanford A aortic dissection.Journal of cardiothoracic surgery · 2026Article
- Risk factors for prolonged postoperative ICU stay in the patients with Stanford type A aortic dissection.Journal of cardiothoracic surgery · 2024Article
- Derivation and validation of predictive indices for cardiac readmission after coronary and valvular surgery - A multicenter study.American heart journal plus : cardiology research and practice · 2023Article
- Association Between Handover of Anesthesiology Care and 1-Year Mortality Among Adults Undergoing Cardiac Surgery.JAMA network open · 2022Article
- An explainable machine learning framework for lung cancer hospital length of stay prediction.Scientific reports · 2022Article
- Data Science Trends Relevant to Nursing Practice: A Rapid Review of the 2020 Literature.Applied clinical informatics · 2022Review
- Derivation and validation of predictive indices for 30-day mortality after coronary and valvular surgery in Ontario, Canada.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2021Article
- Derivation and validation of a clinical model to predict death or cardiac hospitalizations while on the cardiac surgery waitlist.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2021Article
- Cardiovascular Care Delivery During the Second Wave of COVID-19 in Canada.The Canadian journal of cardiology · 2021Review
- Derivation and Validation of a Clinical Model to Predict Intensive Care Unit Length of Stay After Cardiac Surgery.Journal of the American Heart Association · 2020Article
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Background Across the globe, elective surgeries have been postponed to limit infectious exposure and preserve hospital capacity for coronavirus disease 2019 (COVID-19). However, the ramp down in cardiac surgery volumes may result in unintended harm to patients who are at high risk of mortality if their conditions are left untreated. To help optimize triage decisions, we derived and ambispectively validated a clinical score to predict intensive care unit length of stay after cardiac surgery. Methods and Results Following ethics approval, we derived and performed multicenter valida tion of clinical models to predict the likelihood of short (≤2 days) and prolonged intensive care unit length of stay (≥7 days) in patients aged ≥18 years, who underwent coronary artery bypass grafting and/or aortic, mitral, and tricuspid value surgery in Ontario, Canada. Multivariable logistic regression with backward variable selection was used, along with clinical judgment, in the modeling process. For the model that predicted short intensive care unit stay, the c-statistic was 0.78 in the derivation cohort and 0.71 in the validation cohort. For the model that predicted prolonged stay, c-statistic was 0.85 in the derivation and 0.78 in the validation cohort. The models, together termed the
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