Critical care medicine · 2024
Heterogeneity in the Effect of Early Goal-Directed Therapy for Septic Shock: A Secondary Analysis of Two Multicenter International Trials.
СтатьяМногоцентровое исследованиеРандомизированное исследованиеНазвание и аннотация: Перевод в очереди
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Shah Faraaz Ali, Talisa Victor B, Chang Chung-Chou H, Triantafyllou Sofia, Tang Lu, Mayr Florian B, Higgins Alisa M, Peake Sandra L, Mouncey Paul, Harrison David A, DeMerle Kimberley M, Kennedy Jason N, Cooper Gregory F, Bellomo Rinaldo, Rowan Kathy, Yealy Donald M, Seymour Christopher W, Angus Derek C, Yende Sachin P
Аннотация
OBJECTIVES: The optimal approach for resuscitation in septic shock remains unclear despite multiple randomized controlled trials (RCTs). Our objective was to investigate whether previously uncharacterized variation across individuals in their response to resuscitation strategies may contribute to conflicting average treatment effects in prior RCTs.
DESIGN: We randomly split study sites from the Australian Resuscitation of Sepsis Evaluation (ARISE) and Protocolized Care for Early Septic Shock (ProCESS) trials into derivation and validation cohorts. We trained machine learning models to predict individual absolute risk differences (iARDs) in 90-day mortality in derivation cohorts and tested for heterogeneity of treatment effect (HTE) in validation cohorts and swapped these cohorts in sensitivity analyses. We fit the best-performing model in a combined dataset to explore roles of patient characteristics and individual components of early goal-directed therapy (EGDT) to determine treatment responses.
SETTING: Eighty-one sites in Australia, New Zealand, Hong Kong, Finland, Republic of Ireland, and the United States.
PATIENTS: Adult patients presenting to the emergency department with severe sepsis or septic shock.
INTERVENTIONS: EGDT vs. usual care.
MEASUREMENTS AND MAIN RESULTS: A local-linear random forest model performed best in predicting iARDs. In the validation cohort, HTE was confirmed, evidenced by an interaction between iARD prediction and treatment ( p < 0.001). When patients were grouped based on predicted iARDs, treatment response increased from the lowest to the highest quintiles (absolute risk difference [95% CI], -8% [-19% to 4%] and relative risk reduction, 1.34 [0.89-2.01] in quintile 1 suggesting harm from EGDT, and 12% [1-23%] and 0.64 [0.42-0.96] in quintile 5 suggesting benefit). Sensitivity analyses showed similar findings. Pre-intervention albumin contributed the most to HTE. Analyses of individual EGDT components were inconclusive.
CONCLUSIONS: Treatment response to EGDT varied across patients in two multicenter RCTs with large benefits for some patients while others were harmed. Patient characteristics, including albumin, were most important in identifying HTE.
DESIGN: We randomly split study sites from the Australian Resuscitation of Sepsis Evaluation (ARISE) and Protocolized Care for Early Septic Shock (ProCESS) trials into derivation and validation cohorts. We trained machine learning models to predict individual absolute risk differences (iARDs) in 90-day mortality in derivation cohorts and tested for heterogeneity of treatment effect (HTE) in validation cohorts and swapped these cohorts in sensitivity analyses. We fit the best-performing model in a combined dataset to explore roles of patient characteristics and individual components of early goal-directed therapy (EGDT) to determine treatment responses.
SETTING: Eighty-one sites in Australia, New Zealand, Hong Kong, Finland, Republic of Ireland, and the United States.
PATIENTS: Adult patients presenting to the emergency department with severe sepsis or septic shock.
INTERVENTIONS: EGDT vs. usual care.
MEASUREMENTS AND MAIN RESULTS: A local-linear random forest model performed best in predicting iARDs. In the validation cohort, HTE was confirmed, evidenced by an interaction between iARD prediction and treatment ( p < 0.001). When patients were grouped based on predicted iARDs, treatment response increased from the lowest to the highest quintiles (absolute risk difference [95% CI], -8% [-19% to 4%] and relative risk reduction, 1.34 [0.89-2.01] in quintile 1 suggesting harm from EGDT, and 12% [1-23%] and 0.64 [0.42-0.96] in quintile 5 suggesting benefit). Sensitivity analyses showed similar findings. Pre-intervention albumin contributed the most to HTE. Analyses of individual EGDT components were inconclusive.
CONCLUSIONS: Treatment response to EGDT varied across patients in two multicenter RCTs with large benefits for some patients while others were harmed. Patient characteristics, including albumin, were most important in identifying HTE.