Risk factors predicting the need for intensive care unit admission within forty-eight hours of emergency department presentation: A case-control study

Ahmad Nasser; Blake J de Zwart; David J Stewart; Anne M Zielke; Katrina Blazek; Anita E Heywood; Adam T Craig

doi:10.1016/j.aucc.2024.01.012

Risk factors predicting the need for intensive care unit admission within forty-eight hours of emergency department presentation: A case-control study

Aust Crit Care. 2024 Apr 6:S1036-7314(24)00028-6. doi: 10.1016/j.aucc.2024.01.012. Online ahead of print.

Authors

Ahmad Nasser¹, Blake J de Zwart², David J Stewart³, Anne M Zielke², Katrina Blazek⁴, Anita E Heywood⁴, Adam T Craig⁵

Affiliations

¹ Intensive Care Unit, Queen Elizabeth II Jubilee Hospital, Coopers Plains, Queensland, Australia; Faculty of Medicine, University of Queensland, Herston, Queensland, Australia. Electronic address: ahmad.nasser@health.qld.gov.au.
² Intensive Care Unit, Queen Elizabeth II Jubilee Hospital, Coopers Plains, Queensland, Australia.
³ Intensive Care Unit, Queen Elizabeth II Jubilee Hospital, Coopers Plains, Queensland, Australia; School of Medicine, Griffith University, Meadowbrook, Queensland, Australia.
⁴ School of Population Health, Faculty of Medicine and Health, UNSW Sydney, New South Wales, Australia.
⁵ Faculty of Medicine, University of Queensland, Herston, Queensland, Australia; School of Population Health, Faculty of Medicine and Health, UNSW Sydney, New South Wales, Australia.

PMID: 38584063
DOI: 10.1016/j.aucc.2024.01.012

Abstract

Background: Patients admitted from the emergency department to the wards, who progress to a critically unwell state, may require expeditious admission to the intensive care unit. It can be argued that earlier recognition of such patients, to facilitate prompt transfer to intensive care, could be linked to more favourable clinical outcomes. Nevertheless, this can be clinically challenging, and there are currently no established evidence-based methods for predicting the need for intensive care in the future.

Objectives: We aimed to analyse the emergency department data to describe the characteristics of patients who required an intensive care admission within 48 h of presentation. Secondly, we planned to test the feasibility of using this data to identify the associated risk factors for developing a predictive model.

Methods: We designed a retrospective case-control study. Cases were patients admitted to intensive care within 48 h of their emergency department presentation. Controls were patients who did not need an intensive care admission. Groups were matched based on age, gender, admission calendar month, and diagnosis. To identify the associated variables, we used a conditional logistic regression model.

Results: Compared to controls, cases were more likely to be obese, and smokers and had a higher prevalence of cardiovascular (39 [35.1%] vs 20 [18%], p = 0.004) and respiratory diagnoses (45 [40.5%] vs 25 [22.5%], p = 0.004). They received more medical emergency team reviews (53 [47.8%] vs 24 [21.6%], p < 0.001), and more patients had an acute resuscitation plan (31 [27.9%] vs 15 [13.5%], p = 0.008). The predictive model showed that having acute resuscitation plans, cardiovascular and respiratory diagnoses, and receiving medical emergency team reviews were strongly associated with having an intensive care admission within 48 h of presentation.

Conclusions: Our study used emergency department data to provide a detailed description of patients who had an intensive care unit admission within 48 h of their presentation. It demonstrated the feasibility of using such data to identify the associated risk factors to develop a predictive model.

Keywords: Emergency departments; Intensive care units; Logistic models; Risk factors.