Intensive care patients receiving vasoactive medications: A retrospective cohort study. Issue 5 (September 2022) - Hunter, Stephanie
Abstract: Background: Vasoactive medications are high-risk drugs commonly used in intensive care units (ICUs), which have wide variations in clinical management. Objectives: The aim of this study was to describe the patient population, treatment, and clinical characteristics of patients who did and did not receive vasoactive medications while in the ICU and to develop a predictive tool to identify patients needing vasoactive medications. Methods: A retrospective cohort study of patients admitted to a level three tertiary referral ICU over a 12-month period from October 2018 to September 2019 was undertaken. Data from electronic medical records were analysed to describe patient characteristics in an adult ICU. Chi square and Mann–Whitney U tests were used to analyse data relating to patients who did and did not receive vasoactive medications. Univariate analysis and Pearson's r 2 were used to determine inclusion in multivariable logistic regression. Results: Of 1276 patients in the cohort, 40% (512/1276) received a vasoactive medication for haemodynamic support, with 84% (428/512) receiving noradrenaline. Older patients (odds ratio [OR] = 1.02; 95% confidence interval [CI] = 1.01–1.02; p < 0.001) with higher Acute Physiology and Chronic Health Evaluation (APACHE) III scores (OR = 1.04; 95% CI = 1.03–1.04; p < 0.001) were more likely to receive vasoactive medications than those not treated with vasoactive medications during an intensive care admission. A model developed using multivariable analysis predicted that patients admitted with sepsis (OR = 2.43; 95% CI = 1.43–4.12; p = 0.001) or shock (OR = 4.05; 95% CI = 2.68–6.10; p < 0.001) and managed on mechanical ventilation (OR = 3.76; 95% CI = 2.81–5.02; p < 0.001) were more likely to receive vasoactive medications. Conclusions: Mechanically ventilated patients admitted to intensive care for sepsis and shock with higher APACHE III scores were more likely to receive vasoactive medications. Predictors identified in the multivariable model can be used to direct resources to patients most at risk of receiving vasoactive medications.