Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 1 de 1
Filter
Add more filters










Database
Language
Publication year range
1.
Clin Transl Sci ; 14(4): 1578-1589, 2021 07.
Article in English | MEDLINE | ID: mdl-33786999

ABSTRACT

Sepsis is a major cause of mortality among hospitalized patients worldwide. Shorter time to administration of broad-spectrum antibiotics is associated with improved outcomes, but early recognition of sepsis remains a major challenge. In a two-center cohort study with prospective sample collection from 1400 adult patients in emergency departments suspected of sepsis, we sought to determine the diagnostic and prognostic capabilities of a machine-learning algorithm based on clinical data and a set of uncommonly measured biomarkers. Specifically, we demonstrate that a machine-learning model developed using this dataset outputs a score with not only diagnostic capability but also prognostic power with respect to hospital length of stay (LOS), 30-day mortality, and 3-day inpatient re-admission both in our entire testing cohort and various subpopulations. The area under the receiver operating curve (AUROC) for diagnosis of sepsis was 0.83. Predicted risk scores for patients with septic shock were higher compared with patients with sepsis but without shock (p < 0.0001). Scores for patients with infection and organ dysfunction were higher compared with those without either condition (p < 0.0001). Stratification based on predicted scores of the patients into low, medium, and high-risk groups showed significant differences in LOS (p < 0.0001), 30-day mortality (p < 0.0001), and 30-day inpatient readmission (p < 0.0001). In conclusion, a machine-learning algorithm based on electronic medical record (EMR) data and three nonroutinely measured biomarkers demonstrated good diagnostic and prognostic capability at the time of initial blood culture.


Subject(s)
Early Diagnosis , Electronic Health Records/statistics & numerical data , Machine Learning , Sepsis/diagnosis , Aged , Area Under Curve , Biomarkers/blood , Emergency Service, Hospital/statistics & numerical data , Female , Hospital Mortality , Humans , Length of Stay/statistics & numerical data , Male , Middle Aged , Patient Readmission/statistics & numerical data , Prognosis , Prospective Studies , ROC Curve , Sepsis/blood , Sepsis/microbiology , Sepsis/mortality
SELECTION OF CITATIONS
SEARCH DETAIL
...