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, , , , , Abstract
Critical Care Science. 2025;37:e20250010
03-14-2025
DOI 10.62675/2965-2774.20250010
, , , , , , , , , , , , , , Agitation is a major problem in the intensive care unit. However, no treatment has clearly emerged as effective and safe. Using target trial emulation, we aimed to test the hypothesis that early intervention with dexmedetomidine would accelerate agitation resolution.
We read clinical notes in an electronic medical records system with natural language processing to identify patients with agitation. We obtained their demographics, trajectories, associations, and outcomes. We used g-formulas to study the possible effects of dexmedetomidine on agitation resolution and key outcomes.
We screened 7525 patients. Overall, 2242 patients (29.8%) developed within-intensive care unit agitation, and 2052 (27.3%) were eligible for inclusion in the target trial emulation, with 314 treated with dexmedetomidine. Dexmedetomidine-treated patients had more severe illness and were more likely to have unplanned emergency admissions with medical diagnoses. However, they achieved higher rates of resolution of within-intensive care unit agitation (94% versus 72%; p < 0.001) and lower 30-day mortality (5% versus 9%; p = 0.033). Early initiation of dexmedetomidine accelerated the resolution of agitation (risk ratio [RR] 1.13 [95%CI 1.03 - 1.21]; risk difference [RD] 9.8% [95%CI 2.6% - 15.4%]); extubation by Day 30 (RR 1.03 [95%CI 1.02 - 1.04]; RD 3.1% [95%CI 2.2% - 4.2%]); and reduced the chance of having a tracheostomy by Day 30 (RR 0.67 [95%CI 0.34 - 0.99]; RD -3.5% [95%CI -7.0% - -0.0%])
Through target trial emulation analysis, early dexmedetomidine was associated with an increased rate of resolution of agitation and extubation and decreased tracheostomy risk.
Abstract
Critical Care Science. 2025;37:e20250010
03-14-2025
DOI 10.62675/2965-2774.20250010
, , , , , , , , , , , , , , Agitation is a major problem in the intensive care unit. However, no treatment has clearly emerged as effective and safe. Using target trial emulation, we aimed to test the hypothesis that early intervention with dexmedetomidine would accelerate agitation resolution.
We read clinical notes in an electronic medical records system with natural language processing to identify patients with agitation. We obtained their demographics, trajectories, associations, and outcomes. We used g-formulas to study the possible effects of dexmedetomidine on agitation resolution and key outcomes.
We screened 7525 patients. Overall, 2242 patients (29.8%) developed within-intensive care unit agitation, and 2052 (27.3%) were eligible for inclusion in the target trial emulation, with 314 treated with dexmedetomidine. Dexmedetomidine-treated patients had more severe illness and were more likely to have unplanned emergency admissions with medical diagnoses. However, they achieved higher rates of resolution of within-intensive care unit agitation (94% versus 72%; p < 0.001) and lower 30-day mortality (5% versus 9%; p = 0.033). Early initiation of dexmedetomidine accelerated the resolution of agitation (risk ratio [RR] 1.13 [95%CI 1.03 - 1.21]; risk difference [RD] 9.8% [95%CI 2.6% - 15.4%]); extubation by Day 30 (RR 1.03 [95%CI 1.02 - 1.04]; RD 3.1% [95%CI 2.2% - 4.2%]); and reduced the chance of having a tracheostomy by Day 30 (RR 0.67 [95%CI 0.34 - 0.99]; RD -3.5% [95%CI -7.0% - -0.0%])
Through target trial emulation analysis, early dexmedetomidine was associated with an increased rate of resolution of agitation and extubation and decreased tracheostomy risk.
Abstract
Critical Care Science. 2024;36:e20240246en
05-08-2024
DOI 10.62675/2965-2774.20240246-en
To discuss the strengths and limitations of ventilator-free days and to provide a comprehensive discussion of the different analytic methods for analyzing and interpreting this outcome.
Using simulations, the power of different analytical methods was assessed, namely: quantile (median) regression, cumulative logistic regression, generalized pairwise comparison, conditional approach and truncated approach. Overall, 3,000 simulations of a two-arm trial with n = 300 per arm were computed using a two-sided alternative hypothesis and a type I error rate of α = 0.05.
When considering power, median regression did not perform well in studies where the treatment effect was mainly driven by mortality. Median regression performed better in situations with a weak effect on mortality but a strong effect on duration, duration only, and moderate mortality and duration. Cumulative logistic regression was found to produce similar power to the Wilcoxon rank-sum test across all scenarios, being the best strategy for the scenarios of moderate mortality and duration, weak mortality and strong duration, and duration only.
In this study, we describe the relative power of new methods for analyzing ventilator-free days in critical care research. Our data provide validation and guidance for the use of the cumulative logistic model, median regression, generalized pairwise comparisons, and the conditional and truncated approach in specific scenarios.
Abstract
Critical Care Science. 2024;36:e20240246en
05-08-2024
DOI 10.62675/2965-2774.20240246-en
To discuss the strengths and limitations of ventilator-free days and to provide a comprehensive discussion of the different analytic methods for analyzing and interpreting this outcome.
Using simulations, the power of different analytical methods was assessed, namely: quantile (median) regression, cumulative logistic regression, generalized pairwise comparison, conditional approach and truncated approach. Overall, 3,000 simulations of a two-arm trial with n = 300 per arm were computed using a two-sided alternative hypothesis and a type I error rate of α = 0.05.
When considering power, median regression did not perform well in studies where the treatment effect was mainly driven by mortality. Median regression performed better in situations with a weak effect on mortality but a strong effect on duration, duration only, and moderate mortality and duration. Cumulative logistic regression was found to produce similar power to the Wilcoxon rank-sum test across all scenarios, being the best strategy for the scenarios of moderate mortality and duration, weak mortality and strong duration, and duration only.
In this study, we describe the relative power of new methods for analyzing ventilator-free days in critical care research. Our data provide validation and guidance for the use of the cumulative logistic model, median regression, generalized pairwise comparisons, and the conditional and truncated approach in specific scenarios.