Prevalence and predictors of C. difficile infections in hospitalized patients with major surgical procedures in the USA: Analysis using traditional and machine learning methods

•C.Difficile in the adults who underwent major surgical procedure may result in significant morbidity and mortality.•We used traditional and machine learning approach to assess association of C.Difficile infection and several variables.•We found that Machine Learning approach can be used to identify...

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Bibliographic Details
Published in:The American journal of surgery 2019-09, Vol.218 (3), p.661-662
Main Authors: Allareddy, Veerajalandhar, Wang, Tong, Rampa, Sankeerth, Caplin, Jennifer, Nalliah, Romesh, Badheka, Aditya, Allareddy, Veerasathpurush
Format: Article
Language:English
Subjects:
Adult
African Americans
Age
Aged
Artificial intelligence
Bayesian analysis
Clostridium difficile
Clostridium Infections - epidemiology
Comorbidity
Conflicts of interest
Cross Infection - epidemiology
Female
Government programs
Hospitalization
Humans
Identification methods
Insurance
Learning algorithms
Machine Learning
Male
Mathematical models
Medicaid
Middle Aged
Minority & ethnic groups
Pacific Islander people
Patients
Prevalence
Regression analysis
Regression models
Retrospective Studies
Tables
Teaching hospitals
Uninsured people
United States
Variables
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Description
Summary:•C.Difficile in the adults who underwent major surgical procedure may result in significant morbidity and mortality.•We used traditional and machine learning approach to assess association of C.Difficile infection and several variables.•We found that Machine Learning approach can be used to identify the adults at risk to develop C.Difficile infection.
ISSN:0002-9610
1879-1883
DOI:10.1016/j.amjsurg.2018.11.014