Journal article
Individualized Treatment Effects of Bougie vs Stylet for Tracheal Intubation in Critical Illness
American journal of respiratory and critical care medicine, Vol.207(12), pp.1602-1611
06/15/2023
DOI: 10.1164/rccm.202209-1799oc
PMCID: PMC10273111
PMID: 36877594
Abstract
Rationale: A recent randomized trial found that using a bougie did not increase the incidence of successful intubation on first attempt in critically ill adults. The average effect of treatment in a trial population, however, may differ from effects for individuals. Objective: We hypothesized that application of a machine learning model to data from a clinical trial could estimate the effect of treatment (bougie vs. stylet) for individual patients based on their baseline characteristics ("individualized treatment effects"). Methods: This was a secondary analysis of the BOUGIE (Bougie or Stylet in Patients Undergoing Intubation Emergently) trial. A causal forest algorithm was used to model differences in outcome probabilities by randomized group assignment (bougie vs. stylet) for each patient in the first half of the trial (training cohort). This model was used to predict individualized treatment effects for each patient in the second half (validation cohort). Measurements and Main Results: Of 1,102 patients in the BOUGIE trial, 558 (50.6%) were the training cohort, and 544 (49.4%) were the validation cohort. In the validation cohort, individualized treatment effects predicted by the model significantly modified the effect of trial group assignment on the primary outcome (P value for interaction = 0.02; adjusted qini coefficient, 2.46). The most important model variables were difficult airway characteristics, body mass index, and Acute Physiology and Chronic Health Evaluation II score. Conclusions: In this hypothesis-generating secondary analysis of a randomized trial with no average treatment effect and no treatment effect in any prespecified subgroups, a causal forest machine learning algorithm identified patients who appeared to benefit from the use of a bougie over a stylet and from the use of a stylet over a bougie using complex interactions between baseline patient and operator characteristics.
Details
- Title: Subtitle
- Individualized Treatment Effects of Bougie vs Stylet for Tracheal Intubation in Critical Illness
- Creators
- Kevin P. Seitz - Pulmonary and Allergy AssociatesAlexandra B Spicer - University of Wisconsin–MadisonJonathan D Casey - Pulmonary and Allergy AssociatesKevin G. Buell - University of ChicagoEdward T. Qian - Pulmonary and Allergy AssociatesEmma J. Graham LinckBrian E. DriverWesley H Self - Vanderbilt University Medical CenterAdit A Ginde - University of Colorado DenverStacy A. Trent - Denver Health Medical CenterSheetal Gandotra - Pulmonary and Allergy AssociatesLane M. Smith - Atrium Medical CenteDavid B. Page - Pulmonary and Allergy AssociatesDerek J Vonderhaar - Ochsner Health SystemJason R. West - Lincoln Medical CenterAaron M Joffe - University of WashingtonKevin C Doerschug - University of IowaChristopher G. Hughes - University of WashingtonMicah R WhitsonMatthew E Prekker - Hennepin County Medical CenterTodd W Rice - Pulmonary and Allergy AssociatesPratik Sinha - Washington University in St. LouisMatthew W Semler - Pulmonary and Allergy AssociatesMatthew M Churpek - University of Wisconsin–Madison
- Resource Type
- Journal article
- Publication Details
- American journal of respiratory and critical care medicine, Vol.207(12), pp.1602-1611
- Publisher
- American Thoracic Society
- DOI
- 10.1164/rccm.202209-1799oc
- PMID
- 36877594
- PMCID
- PMC10273111
- ISSN
- 1073-449X
- eISSN
- 1535-4970
- Grant note
- DOI: 10.13039/100000002, name: NIH, award: T32HL087738, K23HL153584, UL1 RR024975; DOI: 10.13039/100000002, name: National Heart, Lung, and Blood Institute, award: K23HL143053, R01HL157262
- Language
- English
- Electronic publication date
- 03/06/2023
- Date published
- 06/15/2023
- Academic Unit
- Pulmonary, Critical Care, and Occupational Medicine; Internal Medicine
- Record Identifier
- 9984528102302771
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