Reviews in Cardiovascular Medicine (Feb 2023)

Identifying Risk Factors for Prolonged Length of Stay in Hospital and Developing Prediction Models for Patients with Cardiac Arrest Receiving Targeted Temperature Management

  • Wei-Ting Chiu,
  • Lung Chan,
  • Jakir Hossain Bhuiyan Masud,
  • Chien-Tai Hong,
  • Yu-San Chien,
  • Chih-Hsin Hsu,
  • Cheng-Hsueh Wu,
  • Chen-Hsu Wang,
  • Shennie Tan,
  • Chen-Chih Chung

DOI
https://doi.org/10.31083/j.rcm2402055
Journal volume & issue
Vol. 24, no. 2
p. 55

Abstract

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Background: Prolonged length of stay (LOS) following targeted temperature management (TTM) administered after cardiac arrest may affect healthcare plans and expenditures. This study identified risk factors for prolonged LOS in patients with cardiac arrest receiving TTM and explored the association between LOS and neurological outcomes after TTM. Methods: The retrospective cohort consisted of 571 non-traumatic cardiac arrest patients aged 18 years or older, treated with cardiopulmonary resuscitation (CPR), had a Glasgow Coma Scale score <8, or were unable to comply with commands after the restoration of spontaneous circulation (ROSC), and received TTM less than 12 hours after ROSC. Prolonged LOS was defined as LOS beyond the 75th quartile of the entire cohort. We analyzed and compared relevant variables and neurological outcomes between the patients with and without prolonged LOS and established prediction models for estimating the risk of prolonged LOS. Results: The patients with in-hospital cardiac arrest had a longer LOS than those with out-of-hospital cardiac arrest (p = 0.0001). Duration of CPR (p = 0.02), underlying heart failure (p = 0.001), chronic obstructive pulmonary disease (p = 0.008), chronic kidney disease (p = 0.026), and post-TTM seizures (p = 0.003) were risk factors for prolonged LOS. LOS was associated with survival to hospital discharge, and patients with the lowest and highest Cerebral Performance Category scores at discharge had a shorter LOS. A logistic regression model based on parameters at discharge achieved an area under the curve of 0.840 to 0.896 for prolonged LOS prediction, indicating the favorable performance of this model in predicting LOS in patients receiving TTM. Conclusions: Our study identified clinically relevant risk factors for prolonged LOS following TTM and developed a prediction model that exhibited adequate predictive performance. The findings of this study broaden our understanding regarding factors associated with hospital stay and can be beneficial while making clinical decisions for patients with cardiac arrest who receive TTM.

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