ArticleJournal of cardiothoracic surgery2006
Preoperative calculation of risk for prolonged intensive care unit stay following coronary artery bypass grafting.
Article in Journal of cardiothoracic surgery, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.
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Who cites it
25 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The effect of Ulinastatin on postoperative course in cardiopulmonary bypass patients in Asia: a meta-analysis of randomized controlled trials.Journal of cardiothoracic surgery · 2022Pooled it
- Systematic review of factors influencing length of stay in ICU after adult cardiac surgery.BMC health services research · 2016Pooled it
- Representation learning for the prediction of length of stay in infants with congenital heart diseases undergoing cardiac surgery.European heart journal. Digital health · 2026Article
- Ultra-fast extubation following cardiac surgery improves hemodynamic stability and reduces ICU workload.Frontiers in cardiovascular medicine · 2025Article
- Outcomes After Prolonged ICU Stays in Postoperative Cardiac Surgery Patients.Federal practitioner : for the health care professionals of the VA, DoD, and PHS · 2022Article
- Risk factors for prolonged intensive care unit stays in patients after cardiac surgery with cardiopulmonary bypass: A retrospective observational study.International journal of nursing sciences · 2021Article
- Prognostic Value of GDF-15 in Predicting Prolonged Intensive Care Stay following Cardiac Surgery: A Pilot Study.Disease markers · 2021Observational
- Predicting Intensive Care Unit Length of Stay After Acute Type A Aortic Dissection Surgery Using Machine Learning.Frontiers in cardiovascular medicine · 2021Article
- Examining symptom trajectories that predict worse outcomes in post-CABG patients.European journal of cardiovascular nursing · 2019Article
- Effect of Hypoxemia in the Determination of Short-Term Prognosis of Coronary Artery Bypass Graft Patients: A Prospective Study.Anesthesiology and pain medicine · 2019Article
- Predicting Length of Stay in Intensive Care Units after Cardiac Surgery: Comparison of Artificial Neural Networks and Adaptive Neuro-fuzzy System.Healthcare informatics research · 2018Article
- Predictive factors associated with mortality and discharge in intensive care units: a retrospective cohort study.Electronic physician · 2018Article
- Impaired right ventricular ejection fraction after cardiac surgery is associated with a complicated ICU stay.Journal of intensive care · 2018Article
- Understanding clinical prediction models as 'innovations': a mixed methods study in UK family practice.BMC medical informatics and decision making · 2016Article
- Observational
- Pulse waveform hemodynamic monitoring devices: recent advances and the place in goal-directed therapy in cardiac surgical patients.Romanian journal of anaesthesia and intensive care · 2016Review
- Role of senescence marker p16 INK4a measured in peripheral blood T-lymphocytes in predicting length of hospital stay after coronary artery bypass surgery in older adults.Experimental gerontology · 2016Article
- Article
- Self-rated health is associated with the length of stay at the intensive care unit and hospital following cardiac surgery.BMC cardiovascular disorders · 2014Article
- A multicentre Spanish study for multivariate prediction of perioperative in-hospital cerebrovascular accident after coronary bypass surgery: the PACK2 score.Interactive cardiovascular and thoracic surgery · 2013Observational
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivePatients who have prolonged stay in intensive care unit (ICU) are associated with adverse outcomes. Such patients have cost implications and can lead to shortage of ICU beds. We aimed to develop a preoperative risk prediction tool for prolonged ICU stay following coronary artery surgery (CABG).
methods5,186 patients who underwent CABG between 1st April 1997 and 31st March 2002 were analysed in a development dataset. Logistic regression was used with forward stepwise technique to identify preoperative risk factors for prolonged ICU stay; defined as patients staying longer than 3 days on ICU. Variables examined included presentation history, co-morbidities, catheter and demographic details. The use of cardiopulmonary bypass (CPB) was also recorded. The prediction tool was tested on validation dataset (1197 CABG patients between 1st April 2003 and 31st March 2004). The area under the receiver operating characteristic (ROC) curve was calculated to assess the performance of the prediction tool.
results475 (9.2%) patients had a prolonged ICU stay in the development dataset. Variables identified as risk factors for a prolonged ICU stay included renal dysfunction, unstable angina, poor ejection fraction, peripheral vascular disease, obesity, increasing age, smoking, diabetes, priority, hypercholesterolaemia, hypertension, and use of CPB. In the validation dataset, 8.1% patients had a prolonged ICU stay compared to 8.7% expected. The ROC curve for the development and validation datasets was 0.72 and 0.74 respectively.
conclusionA prediction tool has been developed which is reliable and valid. The tool is being piloted at our institution to aid resource management.
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