Pre-operative depression predicted longer hospital length of stay among patients undergoing coronary artery bypass graft surgery
Open Access
- 1 May 2019
- journal article
- research article
- Published by Taylor & Francis in Risk Management and Healthcare Policy
- Vol. ume 12, 75-83
Abstract
Purpose: Coronary artery bypass graft surgery (CABG) is a common and remarkably effective treatment for coronary heart disease, improving health status and enhancing quality of life. However, some outcomes after surgery remain unexplained, including psychological factors such as depression. The prevalence rates of pre- and post-operative depression among CABG patients are high, which is associated with negative short- and long-term outcomes. This study explores the impacts of pre-operative depressive symptoms on post-operative hospital length of stay (LOS) among patients undergoing CABG in Jordan. Patients and methods: This was a non-experimental, prospective observational study among 227 CABG patients recruited from 5 hospitals in Amman, Jordan. Depression was measured within an average of two weeks prior and one month after the operation using the Hospital Anxiety and Depression Scale. Length of stay was abstracted from medical records after discharge. Results: The average post-operative LOS was 11.40±10.41 days. The average pre-operative depression level was moderate; 12.76±6.80 and 42.47% complained of varying levels of depressive symptoms. The average post-operative depression level was moderate; 11.11±6.78 and 40.53% complained of varying levels of depressive symptoms. In stepwise regression models, depression scores and female gender were independent predictors that increased post-operative LOS. On the other hand, high income (≥1501$/month) and use of statins had protective effects and decreased post-operative LOS. The model explained 22.4% of the total variance regarding LOS. Conclusion: Pre-operative depressive symptoms increased post CABG LOS. Application of policies and depression assessment protocols prior to CABG by health care providers can identify high-risk groups (eg, females), so appropriate interventions can be designed and implemented to decrease morbidity and mortality.Keywords
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