Six subphenotypes in septic shock: Latent class analysis of the PROWESS Shock study
| Autor: | B. Taylor Thompson, Carl F. Pieper, Bengt Gårdlund, John C. Marshall, Simon Finfer, Natalia O. Dmitrieva |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Adult
Male ARDS medicine.medical_specialty Multiple Organ Failure Kaplan-Meier Estimate Critical Care and Intensive Care Medicine Article Sepsis Cohort Studies 03 medical and health sciences 0302 clinical medicine Internal medicine Intensive care medicine Humans 030212 general & internal medicine Respiratory Distress Syndrome Respiratory distress Septic shock business.industry Hemodynamics Shock 030208 emergency & critical care medicine Pneumonia Middle Aged medicine.disease Shock Septic Latent class model Phenotype Latent Class Analysis Shock (circulatory) Data Interpretation Statistical Female medicine.symptom business Multiple organ dysfunction syndrome |
| Zdroj: | J Crit Care |
| ISSN: | 1557-8615 |
| Popis: | Purpose Septic shock is a highly heterogeneous condition which is part of the challenge in its diagnosis and treatment. In this study we aim to identify clinically relevant subphenotypes of septic shock using a novel statistic al approach. Methods Baseline patient data from a large global clinical trial of septic shock (n = 1696) was analysed using latent class analysis (LCA). This approach allowed investigators to identify subgroups in a heterogeneous population by estimating a categorical latent variable that detects relatively homogeneous subgroups within a complex phenomenon. Results LCA identified six different, clinically meaningful subphenotypes of septic shock each with a typical profile: (1) “Uncomplicated Septic Shock, (2) “Pneumonia with adult respiratory distress syndrome (ARDS)”, (3) “Postoperative Abdominal”, (4) “Severe Septic Shock”, (5): “Pneumonia with ARDS and multiple organ dysfunction syndrome (MODS)”, (6) “Late Septic Shock”. The 6-class solution showed high entropy approaching 1 (i.e., 0.92), indicating there was excellent separation between estimated classes. Conclusions LCA appears to be an applicable statistical tool in analysing a heterogenous clinical cohort of septic shock. The results may lead to a better understanding of septic shock complexity and form a basis for considering targeted therapies and selecting patients for future clinical trials. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect