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Observational Study
. 2016 Jun 8;6(6):e010764.
doi: 10.1136/bmjopen-2015-010764.

Factors associated with prolonged length of stay following cardiac surgery in a major referral hospital in Oman: a retrospective observational study

Ahmed Almashrafi  1 , Hilal Alsabti  2 , Mirdavron Mukaddirov  2 , Baskaran Balan  2 , Paul Aylin  1
Affiliations
Observational Study

Factors associated with prolonged length of stay following cardiac surgery in a major referral hospital in Oman: a retrospective observational study

Ahmed Almashrafi et al. BMJ Open. .

Abstract

Objectives: Two objectives were set for this study. The first was to identify factors influencing prolonged postoperative length of stay (LOS) following cardiac surgery. The second was to devise a predictive model for prolonged LOS in the cardiac intensive care unit (CICU) based on preoperative factors available at admission and to compare it against two existing cardiac stratification systems.

Design: Observational retrospective study.

Settings: A tertiary hospital in Oman.

Participants: All adult patients who underwent cardiac surgery at a major referral hospital in Oman between 2009 and 2013.

Results: 30.5% of the patients had prolonged LOS (≥11 days) after surgery, while 17% experienced prolonged ICU LOS (≥5 days). Factors that were identified to prolong CICU LOS were non-elective surgery, current congestive heart failure (CHF), renal failure, combined coronary artery bypass graft (CABG) and valve surgery, and other non-isolated valve or CABG surgery. Patients were divided into three groups based on their scores. The probabilities of prolonged CICU LOS were 11%, 26% and 28% for group 1, 2 and 3, respectively. The predictive model had an area under the curve of 0.75. Factors associated with prolonged overall postoperative LOS included the body mass index, the type of surgery, cardiopulmonary bypass machine use, packed red blood cells use, non-elective surgery and number of complications. The latter was the most important determinant of postoperative LOS.

Conclusions: Patient management can be tailored for individual patient based on their treatments and personal attributes to optimise resource allocation. Moreover, a simple predictive score system to enable identification of patients at risk of prolonged CICU stay can be developed using data that are routinely collected by most hospitals.

Keywords: ICU prolonged stay; determinants of hospital stay; hospital resource planning; prediction model.

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