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Background <p>The heterogeneity of sepsis poses challenges for the individualized treatment of vasoactive drugs.</p> Methods <p>This study used data from ICUs in MIMIC-IV (2008–2019) and eICU (2014–2015) databases, identified sepsis by sepsis-3 criteria, and stratified sepsis into phenotypes by consensus K-means. The norepinephrine equivalence (NEE) formula balance treatment of different vasoactive drugs, with NEE captured hourly for up to 72&#xa0;h to record both time of use and dosage. The logistic regression model, including phenotype–dosage–time interactions, examined heterogeneous treatment effects on hospital mortality. To address confounding, three models were fitted: Model 1 unadjusted, Model 2 adjusted for age and sex, and Model 3 additionally included 7 clinical variables identified via machine learning and directed acyclic graph. Nonlinear dosage was further analyzed based on restricted cubic splines. <i>P</i> values and <i>P</i> for interaction were Bonferroni-adjusted.</p> Results <p>A total of 54,673 sepsis patients were included for phenotype identification, and 8,803 patients were further analyzed to evaluate heterogeneous treatment effect of vasoactive drugs. Four sepsis phenotypes were identified: A, B, C and D. Phenotype D was the most severe subgroup, followed by phenotype C, while phenotypes A and B were mild subgroups. In Model 3, each 0.05 μg/kg/min increase in NEE dosage was linked to higher hospital mortality (OR 1.328, 95% CI 1.314–1.342; <i>p</i> &lt; 0.001). Longer NEE time of use also significantly increased mortality risk (OR 1.006, 95% CI 1.005–1.007; <i>p</i> &lt; 0.001). In addition, these associations varied significantly by phenotype (<i>P</i> for interaction &lt; 0.001). In RCS model, phenotype A consistently showed higher mortality than the other phenotypes at NEE dosages of 0.1–0.5&#xa0;µg/kg/min, with this gap increasing over time, showing a clear dosage–time dependence. Phenotype B displayed lower overall mortality but the steepest relative risk of hospital mortality increased as dosage and time (OR of dosage: 1.309; OR of time: 1.005) in Model 3. Phenotype C reached the highest mortality risk when dosages exceeded 0.5&#xa0;µg/kg/min, which was dosage dependence. Finally, phenotype D followed a U-shaped curve in RCS model, and minimum mortality was around 20% at 0.03–0.05&#xa0;µg/kg/min.</p> Conclusions <p>Sepsis phenotypes differ significantly in their treatment effects of vasoactive drug dosage and time of use, indicating the need for phenotype-specific treatment strategies to improve outcomes.</p>

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Analysis of the heterogeneous treatment effect of vasoactive drug dosage and time on hospital mortality across different sepsis phenotypes: a retrospective cohort study

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  • 发表日期：

    2025年5月24日

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  • Jiacheng Shen,
  • Kun Fang,
  • Jianhong Xie,
  • Dongsheng Sun,
  • Li Li

摘要

Background

The heterogeneity of sepsis poses challenges for the individualized treatment of vasoactive drugs.

Methods

This study used data from ICUs in MIMIC-IV (2008–2019) and eICU (2014–2015) databases, identified sepsis by sepsis-3 criteria, and stratified sepsis into phenotypes by consensus K-means. The norepinephrine equivalence (NEE) formula balance treatment of different vasoactive drugs, with NEE captured hourly for up to 72 h to record both time of use and dosage. The logistic regression model, including phenotype–dosage–time interactions, examined heterogeneous treatment effects on hospital mortality. To address confounding, three models were fitted: Model 1 unadjusted, Model 2 adjusted for age and sex, and Model 3 additionally included 7 clinical variables identified via machine learning and directed acyclic graph. Nonlinear dosage was further analyzed based on restricted cubic splines. P values and P for interaction were Bonferroni-adjusted.

Results

A total of 54,673 sepsis patients were included for phenotype identification, and 8,803 patients were further analyzed to evaluate heterogeneous treatment effect of vasoactive drugs. Four sepsis phenotypes were identified: A, B, C and D. Phenotype D was the most severe subgroup, followed by phenotype C, while phenotypes A and B were mild subgroups. In Model 3, each 0.05 μg/kg/min increase in NEE dosage was linked to higher hospital mortality (OR 1.328, 95% CI 1.314–1.342; p < 0.001). Longer NEE time of use also significantly increased mortality risk (OR 1.006, 95% CI 1.005–1.007; p < 0.001). In addition, these associations varied significantly by phenotype (P for interaction < 0.001). In RCS model, phenotype A consistently showed higher mortality than the other phenotypes at NEE dosages of 0.1–0.5 µg/kg/min, with this gap increasing over time, showing a clear dosage–time dependence. Phenotype B displayed lower overall mortality but the steepest relative risk of hospital mortality increased as dosage and time (OR of dosage: 1.309; OR of time: 1.005) in Model 3. Phenotype C reached the highest mortality risk when dosages exceeded 0.5 µg/kg/min, which was dosage dependence. Finally, phenotype D followed a U-shaped curve in RCS model, and minimum mortality was around 20% at 0.03–0.05 µg/kg/min.

Conclusions

Sepsis phenotypes differ significantly in their treatment effects of vasoactive drug dosage and time of use, indicating the need for phenotype-specific treatment strategies to improve outcomes.