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A Journal on Cardiac, Vascular and Thoracic Surgery

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The Journal of Cardiovascular Surgery 2018 Feb 08

DOI: 10.23736/S0021-9509.18.09847-6


language: English

Models to predict length of stay in the intensive care unit after coronary artery bypass grafting: a systematic review

Alireza ATASHI 1, 2, 3, Ilona W. VERBURG 4, Hesam KARIM 5, Mirmohammad MIRI 6, Ameen ABU-HANNA 4, Evert de JONGE 7, Nicolette F. de KEIZER 4, Saeid ESLAMI 4, 8, 9

1 Mashhad University of Medical Sciences, Mashhad, Iran; 2 Medical Informatics Department, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran, Iran; 3 E-health Department, Virtual School, Tehran University of Medical Sciences, Tehran, Iran; 4 Academic Medical Center, Department of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands; 5 Department of Health Information Management, Faculty of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran; 6 Anesthesiology and Critical Care Department, Emam Hossein Hospital, Shahid Beheshti Medical University, Tehran, Iran; 7 Department of Intensive Care, Leiden University Medical Center, Leiden, The Netherlands; 8 Pharmaceutical Research Center, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran; 9 Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran


INTRODUCTION: ICU Length of stay (LoS) prediction models are used to compare different institutions and surgeons on their performance, and is useful as an efficiency indicator for quality control. There is little consensus about which prediction methods are most suitable to predict (ICU) length of stay. The aim of this study is to systematically review models for predicting ICU LoS after coronary artery bypass grafting and to assess the reporting and methodological quality of these models to apply them for benchmarking.
EVIDENCE ACQUISITION: A general search was conducted in Medline and Embase up to 31-12-2016. Three authors classified the papers for inclusion by reading their title, abstract and full text. All original papers describing development and/or validation of a prediction model for LoS in the ICU after CABG surgery were included. We used a checklist developed for critical appraisal and data extraction for systematic reviews of prediction modeling and extended it on handling specific patients subgroups. We also defined other items and scores to assess the methodological and reporting quality of the models.
EVIDENCE SYNTHESIS: Of 5181 uniquely identified articles, fifteen studies were included of which twelve on development of new models and three on validation of existing models. All studies used linear or logistic regression as method for model development, and reported various performance measures based on the difference between predicted and observed ICU LoS. Most used a prospective (46.6%) or retrospective study design (40%). We found heterogeneity in patient inclusion/exclusion criteria; sample size; reported accuracy rates; and methods of candidate predictor selection. Most (60%) studies have not mentioned the handling of missing values and none compared the model outcome measure of survivors with non-survivors. For model development and validation studies respectively, the maximum reporting (methodological) scores were 66/78 and 62/62 (14/22 and 12/22).
CONCLUSIONS: There are relatively few models for predicting ICU length of stay after CABG. Several aspects of methodological and reporting quality of studies in this field should be improved. There is a need for standardizing outcome and risk factor definitions in order to develop/validate a multi- institutional and international risk scoring system.

KEY WORDS: Intensive care unit - Length of stay - Coronary artery bypass - Prediction models

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Publication History

Article first published online: February 8, 2018
Manuscript accepted: February 6, 2018
Manuscript revised: January 16, 2018
Manuscript received: December 19, 2016

Cite this article as

Atashi A, Verburg IW, Karim H, Miri M, Abu-Hanna A, De Jonge E, et al. Models to predict length of stay in the intensive care unit after coronary artery bypass grafting: a systematic review. J Cardiovasc Surg 2018 Feb 08. DOI: 10.23736/S0021-9509.18.09847-6

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