Factors associated with resource-intensive planned critical care admissions after elective surgery in patients with a planned admission to the intensive care unit.

Walker, Humphrey G M; Dalton, Nathan S; Coulson, Tim; Ross, Paul; Pilcher, David; Brown, Alastair J · Br J Anaesth · 2026

retrospective_cohort · Level III

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Abstract

There are limited risk prediction tools to help clinicians assess an appropriate disposition for postoperative patients. The utility of admitting lower-risk, elective surgical cases to the ICU after surgery has been questioned. Therefore, the primary aim of this study was to identify factors associated with a resource intensive admission. A registry-based study utilising the Australia and New Zealand Intensive Care Society Adult Patient Database and Critical Care Resources Survey was conducted. All patients with a planned ICU admission after elective surgery between 2018 and 2022 were eligible for inclusion. The primary outcome was the proportion of patients with a resource intensive admission (defined as the need for classical ICU supports, an ICU length of stay >24 h, readmission within 3 days, or in-hospital death). A mixed-effects multivariate regression model was used to assess factors associated with resource intensive admissions. A total of 75 390 admissions were included. Mean age was 63 (range, 16-103) yr, and 42 382 (56%) were male. Of the total admissions, 36 053 (47.8%) patients had resource intensive admissions. Resource intensive admissions were associated with longer hospital length of stay and lower rate of discharge home. Factors independently associated with an increased risk of a resource intensive admission included co-morbidities (such as chronic respiratory or renal disease), frailty, and major vascular and gastrointestinal surgery. Fewer than 50% of patients with a planned ICU admission after elective surgery experienced a resource intensive admission. Alongside surgery type, frailty state and chronic co-morbidities were associated with resource intensive admissions. Further work to develop accurate prediction tools for resource intensive ICU admissions is needed.

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