Characteristics and Cluster Analysis of 18,030 Sepsis Patients Who Were Admitted to Thailand's Largest National Tertiary Referral Center during 2014-2020 to Identify Distinct Subtypes of Sepsis in Thai Population.
Journal
Critical care research and practice
ISSN: 2090-1305
Titre abrégé: Crit Care Res Pract
Pays: Egypt
ID NLM: 101539357
Informations de publication
Date de publication:
2024
2024
Historique:
received:
14
11
2023
revised:
26
06
2024
accepted:
18
07
2024
medline:
7
8
2024
pubmed:
7
8
2024
entrez:
7
8
2024
Statut:
epublish
Résumé
This study aimed to investigate the demographic, clinical, and laboratory characteristics of sepsis patients who were admitted to our center during 2014-2020 and to employ cluster analysis, which is a type of machine learning, to identify distinct types of sepsis in Thai population. Demographic, clinical, laboratory, medicine, and source of infection data of patients admitted to medical wards of Siriraj Hospital (Bangkok, Thailand) during 2014-2020 were collected. Sepsis was diagnosed according to the Sepsis-3 criteria. Nineteen demographic, clinical, and laboratory variables were analyzed using hierarchical clustering to identify sepsis subtypes. Of 98,359 admissions, 18,030 (18.3%) had sepsis. Respiratory tract was the most common site of infection. The mean Sequential Organ Failure Assessment (SOFA) score was 4.21 ± 2.24, and the median serum lactate level was 2.7 mmol/L [range: 0.4-27.5]. Twenty percent of admissions required vasopressor. In-hospital mortality was 19.6%. Ten sepsis subtypes were identified using hierarchical clustering. Three clusters (clusters L1-L3) were considered low risk, and seven clusters (clusters H1-H7) were considered high risk for in-hospital mortality. Cluster H1 had prominent hematologic abnormalities. Clusters H3 and H5 had younger ages and significant hepatic dysfunction. Cluster H5 had multiple organ dysfunctions, and a higher proportion of cluster H5 patients required vasopressor, mechanical ventilation, and renal replacement therapy. Cluster H6 had more respiratory tract infection and acute respiratory failure and a lower SpO Cluster analysis revealed 10 distinct subtypes of sepsis in Thai population. Furthermore, the study is needed to investigate the value of these sepsis subtypes in clinical practice.
Sections du résumé
Background
UNASSIGNED
This study aimed to investigate the demographic, clinical, and laboratory characteristics of sepsis patients who were admitted to our center during 2014-2020 and to employ cluster analysis, which is a type of machine learning, to identify distinct types of sepsis in Thai population.
Methods
UNASSIGNED
Demographic, clinical, laboratory, medicine, and source of infection data of patients admitted to medical wards of Siriraj Hospital (Bangkok, Thailand) during 2014-2020 were collected. Sepsis was diagnosed according to the Sepsis-3 criteria. Nineteen demographic, clinical, and laboratory variables were analyzed using hierarchical clustering to identify sepsis subtypes.
Results
UNASSIGNED
Of 98,359 admissions, 18,030 (18.3%) had sepsis. Respiratory tract was the most common site of infection. The mean Sequential Organ Failure Assessment (SOFA) score was 4.21 ± 2.24, and the median serum lactate level was 2.7 mmol/L [range: 0.4-27.5]. Twenty percent of admissions required vasopressor. In-hospital mortality was 19.6%. Ten sepsis subtypes were identified using hierarchical clustering. Three clusters (clusters L1-L3) were considered low risk, and seven clusters (clusters H1-H7) were considered high risk for in-hospital mortality. Cluster H1 had prominent hematologic abnormalities. Clusters H3 and H5 had younger ages and significant hepatic dysfunction. Cluster H5 had multiple organ dysfunctions, and a higher proportion of cluster H5 patients required vasopressor, mechanical ventilation, and renal replacement therapy. Cluster H6 had more respiratory tract infection and acute respiratory failure and a lower SpO
Conclusions
UNASSIGNED
Cluster analysis revealed 10 distinct subtypes of sepsis in Thai population. Furthermore, the study is needed to investigate the value of these sepsis subtypes in clinical practice.
Identifiants
pubmed: 39108993
doi: 10.1155/2024/6699274
pmc: PMC11303049
doi:
Types de publication
Journal Article
Langues
eng
Pagination
6699274Informations de copyright
Copyright © 2024 Phuwanat Sakornsakolpat et al.
Déclaration de conflit d'intérêts
All authors declare no personal or professional conflicts of interest relating to any aspect of this study.