Individualised treatment effects of enhanced early mobilisation in mechanically ventilated patients: a secondary analysis of the TEAM trial
Year: 2025
Type: article
Abstract: PURPOSE: Benefit or harm from early mobilisation (EM) in mechanically ventilated patients may vary by individual patient characteristics. We used machine learning to predict individualised treatment effects (ITEs) in the "Early Active Mobilization during Mechanical Ventilation in the ICU" (TEAM) trial. METHODS: This was a secondary analysis of the TEAM trial using a causal inference approach to estimate ITEs, which compared enhanced EM to usual care EM. Baseline variables in the original publication were used as predictor variables. The primary outcome was death by day 180. The dataset was randomly split into two halves (train and test) by site. In the training data, fivefold cross-validation was used to compare six candidate machine learning algorithms. The best-performing model was evaluated in the test dataset. Patients were stratified into tertiles based on predicted ITEs, reflecting estimated benefit, no effect or harm. RESULTS: We included 687 patients from 40 sites, and 141 (20.5%) patients died by day 180. Predicted ITEs in the test cohort ranged from an absolute 34.0% reduction to a 39.3% increase in mortality with enhanced EM. The interaction term between the model predictions and treatment assignment demonstrated significant heterogeneity of treatment effect (p = 0.006). Patients predicted to respond poorly to enhanced EM therapy were more likely to receive vasopressors, have diabetes and have lower RASS scores at baseline, compared to patients predicted to have benefit. CONCLUSION: Using baseline characteristics, a machine learning model identified patients with estimated benefit or harm with enhanced EM. Future testing of a personalised approach to mobilisation in the ICU is warranted.
Source: Intensive Care Medicine
Authors: Carol L. Hodgson, Alexandra B. Spicer, Tessa Broadley, Michael Bailey, Rinaldo Bellomo, Kathy Brickell, Heidi Buhr, Belinda J. Gabbe, Doug W. Gould, Meg Harrold, Alisa M. Higgins, Sally Hurford, Theodore J. Iwashyna, Ary Serpa Neto, Alistair D. Nichol, Jeffrey J. Presneill, Stefan J. Schaller, Janani Sivasuthan, Claire J. Tipping, Steven Webb, Emma J. Graham Linck, Pratik Sinha, Matthew W. Semler, Paul J. Young, Matthew M. Churpek
Institutions: The University of Melbourne, The Alfred Hospital, The George Institute for Global Health, Monash University, University of Wisconsin–Madison, The Royal Melbourne Hospital, Austin Hospital, Austin Health, University College Dublin, St. Vincent's University Hospital, Royal Prince Alfred Hospital, Sydney Local Health District, Intensive Care National Audit & Research Centre, Curtin University, Royal Perth Hospital, East Metropolitan Health Service, Royal Perth Bentley Group, Medical Research Institute of New Zealand, Johns Hopkins University, Humboldt-Universität zu Berlin, Medical University of Vienna, Charité - Universitätsmedizin Berlin, St John of God Subiaco Hospital, Washington University in St. Louis, Vanderbilt University, Vanderbilt University Medical Center, Wellington Hospital
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $5,190
Awards: G1853596577, Improving the quality of survival after critical illness , Research programs and pivotal trials to improve outcomes in critical care medicine. , Treatment of invasively ventilated adults with Early Activity and Mobilisation, Healthcare resource utilisation and long term outcomes following critical illness, G9000026873
OpenAlex ID: W4416606170