Literature DB >> 11174363

Determinants of intensive care unit length of stay after coronary artery bypass graft surgery.

L V Doering1, F Esmailian, F Imperial-Perez, S Monsein.   

Abstract

OBJECTIVE: The purpose of this study is to identify independent preoperative, intraoperative, and postoperative determinants of intensive care unit (ICU) length of stay in patients undergoing coronary artery bypass graft (CABG) surgery and to evaluate the usefulness of a mortality risk scoring system, the Parsonnet score, as a prognostic indicator of ICU length of stay after CABG.
METHODS: A prospective nonrandomized sample of 109 consecutive patients was enrolled before CABG and followed prospectively until ICU discharge. Multivariate linear regression was used to identify factors independently associated with ICU length of stay.
RESULTS: One preoperative variable (Parsonnet score) and 4 postoperative variables (length of intubation, presence of arrhythmias, early hemodynamic instability, and 12-hour fluid balance) explained 45.6% of the variance in ICU length of stay. Intraoperative variables were not independent correlates of ICU length of stay. Classification as "extremely high" risk by Parsonnet scoring (score 20) yielded a positive predictive value of 84% for ICU stay >1 day. Negative predictive value was 42.8%.
CONCLUSIONS: Preoperative and postoperative variables explained a large portion of the variance in ICU stay after CABG. Although the Parsonnet score was not helpful in identifying patients who require only a short ICU stay, it may help clinicians screen for patients likely to require stays >1 day and plan appropriate use of resources in the ICU.

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Year:  2001        PMID: 11174363     DOI: 10.1067/mhl.2001.112502

Source DB:  PubMed          Journal:  Heart Lung        ISSN: 0147-9563            Impact factor:   2.210


  7 in total

1.  Comparison of Four Machine Learning Techniques for Prediction of Intensive Care Unit Length of Stay in Heart Transplantation Patients.

Authors:  Kan Wang; Li Zhao Yan; Wang Zi Li; Chen Jiang; Ni Ni Wang; Qiang Zheng; Nian Guo Dong; Jia Wei Shi
Journal:  Front Cardiovasc Med       Date:  2022-06-21

2.  Inclusion of 'ICU-Day' in a Logistic Scoring System Improves Mortality Prediction in Cardiac Surgery.

Authors:  Fabian Doerr; Matthias B Heldwein; Ole Bayer; Anton Sabashnikov; Alexander Weymann; Pascal M Dohmen; Thorsten Wahlers; Khosro Hekmat
Journal:  Med Sci Monit Basic Res       Date:  2015-07-03

3.  Risk Factors for Prolonged Intensive Care Unit Stay After Open Heart Surgery in Adults.

Authors:  Muzaffer Tunç; Cengiz Şahutoğlu; Nursen Karaca; Seden Kocabaş; Fatma Zekiye Aşkar
Journal:  Turk J Anaesthesiol Reanim       Date:  2018-05-02

4.  Predictors of Prolonged Stay in the Intensive Care Unit following Cardiac Surgery.

Authors:  Rokeia Eltheni; Konstantinos Giakoumidakis; Hero Brokalaki; Petros Galanis; Ioannis Nenekidis; George Fildissis
Journal:  ISRN Nurs       Date:  2012-06-27

5.  Determinants of length of stay in surgical ward after coronary bypass surgery: glycosylated hemoglobin as a predictor in all patients, diabetic or non-diabetic.

Authors:  Mahdi Najafi; Hamidreza Goodarzynejad
Journal:  J Tehran Heart Cent       Date:  2012-11-30

6.  Predicting Intensive Care Unit Length of Stay After Acute Type A Aortic Dissection Surgery Using Machine Learning.

Authors:  Qiuying Chen; Bin Zhang; Jue Yang; Xiaokai Mo; Lu Zhang; Minmin Li; Zhuozhi Chen; Jin Fang; Fei Wang; Wenhui Huang; Ruixin Fan; Shuixing Zhang
Journal:  Front Cardiovasc Med       Date:  2021-07-12

7.  Factors associated with long intensive care unit (ICU) admission among inpatients with and without diabetes in South Western Sydney public hospitals using the New South Wales admission patient data collection (2014-2017).

Authors:  Uchechukwu L Osuagwu; Matthew Xu; Milan K Piya; Kingsley E Agho; David Simmons
Journal:  BMC Endocr Disord       Date:  2022-01-20       Impact factor: 2.763

  7 in total

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