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Heterogeneity in the Effect of Early Goal-Directed Therapy for Septic Shock: A Secondary Analysis of Two Multicenter International Trials.
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.
Afiliação
  • Shah FA; Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA.
  • Talisa VB; Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA.
  • Chang CH; Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA.
  • Triantafyllou S; Division of General Internal Medicine, University of Pittsburgh, Pittsburgh, PA.
  • Tang L; Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA.
  • Mayr FB; Department of Mathematics and Applied Mathematics, University of Crete, Heraklion, Crete, Greece.
  • Higgins AM; Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA.
  • Peake SL; Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA.
  • Mouncey P; Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA.
  • Harrison DA; Australian and New Zealand Intensive Care Research Centre, Monash University, Melbourne, VIC, Australia.
  • DeMerle KM; Australian and New Zealand Intensive Care Research Centre, Monash University, Melbourne, VIC, Australia.
  • Kennedy JN; Intensive Care National Audit & Research Centre, London, United Kingdom.
  • Cooper GF; Intensive Care National Audit & Research Centre, London, United Kingdom.
  • Bellomo R; Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA.
  • Rowan K; Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA.
  • Yealy DM; Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA.
  • Seymour CW; Australian and New Zealand Intensive Care Research Centre, Monash University, Melbourne, VIC, Australia.
  • Angus DC; Department of Critical Care, University of Melbourne, Melbourne, VIC, Australia.
  • Yende SP; Department of Intensive Care, Austin Hospital, Melbourne, VIC, Australia.
Crit Care Med ; 2024 Oct 23.
Article em En | MEDLINE | ID: mdl-39440873
ABSTRACT

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.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article