Articles: phenotype.
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Trajectories of bedside vital signs have been used to identify sepsis subphenotypes with distinct outcomes and treatment responses. The objective of this study was to validate the vitals trajectory model in a multicenter cohort of patients hospitalized with COVID-19 and to evaluate the clinical characteristics and outcomes of the resulting subphenotypes. ⋯ By using bedside vital signs available in even low-resource settings, we found novel subphenotypes associated with distinct manifestations of COVID-19, which could lead to preemptive and targeted treatments.
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Multicenter Study Observational Study
Discovery of distinct cancer cachexia phenotypes using an unsupervised machine-learning algorithm.
Cancer cachexia is a debilitating condition with widespread negative effects. The heterogeneity of clinical features within patients with cancer cachexia is unclear. The identification and prognostic analysis of diverse phenotypes of cancer cachexia may help develop individualized interventions to improve outcomes for vulnerable populations. The aim of this study was to show that the machine learning-based cancer cachexia classification model generalized well on the external validation cohort. ⋯ Machine learning is valuable for phenotype classifications of patients with cancer cachexia. Detection of clinically distinct clusters among cachexic patients assists in scheduling personalized treatment strategies and in patient selection for clinical trials.
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Randomized Controlled Trial Multicenter Study
Phenotypic features of pediatric bronchiectasis exacerbations associated with symptom resolution after 14-days of oral antibiotic treatment.
Respiratory exacerbations in children and adolescents with bronchiectasis are treated with antibiotics. However, antibiotics can have variable interindividual effects when treating exacerbations. ⋯ Children with Indigenous ethnicity, milder bronchiectasis, mild exacerbations (low reported cough scores), or new abnormal auscultatory signs are more likely to respond to appropriate oral antibiotics than those without these features. These patient and exacerbation phenotypes may assist clinical management and development of biomarkers to identify those whose symptoms are more likely to resolve after 14 days of oral antibiotics.
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Critical care medicine · Dec 2023
Multicenter StudyElevated Plasma Interleukin-18 Identifies High-Risk Acute Respiratory Distress Syndrome Patients not Distinguished by Prior Latent Class Analyses Using Traditional Inflammatory Cytokines: A Retrospective Analysis of Two Randomized Clinical Trials.
Interleukin-18 (IL-18) plasma level and latent class analysis (LCA) have separately been shown to predict prognosis and treatment response in acute respiratory distress syndrome (ARDS). IL-18 is a measure of inflammasome activation, a pathway potentially distinct from inflammation captured by biomarkers defining previously published LCA classes. We hypothesized that elevated IL-18 would identify distinct "high-risk" patients not captured by prior LCA classifications. ⋯ Plasma IL-18 level provides important additional prognostic information to LCA subphenotypes defined largely by traditional inflammatory biomarkers in two large ARDS cohorts.
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Critical care medicine · Dec 2023
Multicenter StudyAnalysis of Protein Biomarkers From Hospitalized COVID-19 Patients Reveals Severity-Specific Signatures and Two Distinct Latent Profiles With Differential Responses to Corticosteroids.
To identify and validate novel COVID-19 subphenotypes with potential heterogenous treatment effects (HTEs) using electronic health record (EHR) data and 33 unique biomarkers. ⋯ In this multicenter study combining EHR data with research biomarker analysis of patients with COVID-19, we identified novel profiles with divergent clinical outcomes and differential treatment responses.