Reproducible clinical archetypes in acute respiratory failure: a multi-cohort trajectory analysis

PURPOSE: Acute hypoxemic respiratory failure (AHRF) is common and biologically heterogeneous. Static phenotyping at a single time point does not capture illness evolution and risks stage-mixing; reproducible clinical course archetypes may address this. We aimed to identify, externally validate, and predict trajectory classes (TCs) of persistent AHRF. METHODS: to day 14 and time to ICU discharge/death were jointly modelled using a competing-risk latent class mixed model. Early TC prediction used a 12-variable XGBoost model. We explored prevalence of ARDS and hyperinflammatory subphenotypes between TCs. RESULTS: A four-class model provided optimal fit: (TC1) early recovery (0.3% 14-day mortality); (TC2) stable persistence (8% 14-day mortality); (TC3) biphasic improvement-deterioration (17% 14-day mortality); and (TC4) rapid decline (100% 14-day mortality). These archetypes generalized to external cohorts with high assignment certainty. TCs demonstrated distinct patterns in other clinical biomarker trajectories. TC4 was enriched for the hyperinflammatory subphenotype (41-53%), while TC2 was most common in patients with ARDS (50%). Early TC prediction models achieved mean AUCs ≥ 0.78 (0.70-0.86) by day 3 in external validation. CONCLUSIONS: Four reproducible oxygenation archetypes capture the 14-day course of persistent respiratory failure. By providing early prognostic value distinct from static baseline severity, these trajectories have the potential to guide therapeutic strategies, reduce patient heterogeneity in trials, and direct biological phenotyping.

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Publication Details

Journal
Intensive Care Medicine
Published
2026-05-17
DOI
https://doi.org/10.1007/s00134-026-08441-2
Primary Topic
Sepsis Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00

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article

Reproducible clinical archetypes in acute respiratory failure: a multi-cohort trajectory analysis

B. Patel, Matthieu Komorowski, Sonali Parbhoo, Dominic C. Marshall et al.
Intensive Care Medicine
Sepsis Diagnosis and Treatment
article

Reproducible clinical archetypes in acute respiratory failure: a multi-cohort trajectory analysis

B. Patel, Matthieu Komorowski, Sonali Parbhoo, Dominic C. Marshall, Ashleigh D. Green, David B. Antcliffe
article en

Abstract

PURPOSE: Acute hypoxemic respiratory failure (AHRF) is common and biologically heterogeneous. Static phenotyping at a single time point does not capture illness evolution and risks stage-mixing; reproducible clinical course archetypes may address this. We aimed to identify, externally validate, and predict trajectory classes (TCs) of persistent AHRF. METHODS: to day 14 and time to ICU discharge/death were jointly modelled using a competing-risk latent class mixed model. Early TC prediction used a 12-variable XGBoost model. We explored prevalence of ARDS and hyperinflammatory subphenotypes between TCs. RESULTS: A four-class model provided optimal fit: (TC1) early recovery (0.3% 14-day mortality); (TC2) stable persistence (8% 14-day mortality); (TC3) biphasic improvement-deterioration (17% 14-day mortality); and (TC4) rapid decline (100% 14-day mortality). These archetypes generalized to external cohorts with high assignment certainty. TCs demonstrated distinct patterns in other clinical biomarker trajectories. TC4 was enriched for the hyperinflammatory subphenotype (41-53%), while TC2 was most common in patients with ARDS (50%). Early TC prediction models achieved mean AUCs ≥ 0.78 (0.70-0.86) by day 3 in external validation. CONCLUSIONS: Four reproducible oxygenation archetypes capture the 14-day course of persistent respiratory failure. By providing early prognostic value distinct from static baseline severity, these trajectories have the potential to guide therapeutic strategies, reduce patient heterogeneity in trials, and direct biological phenotyping.

Intensive Care Medicine
Cleveland Clinic London (GB), Imperial College London (GB), Health and Safety Executive (GB)
National Institute for Health and Care Research, Medical Research Council
Good health and well-being
Openalex Percentile: Top 5%
Sepsis Diagnosis and Treatment
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