Development of Risk Assessment Model for Clostridioides Difficile Infection In Hospitalized Patients at Udon Thani Hospital

Authors

  • Daungsuda Apiwatdamrongkit Student, Master of Pharmacy (Clinical Pharmacy), Faculty of Pharmaceutical Sciences, Khon Kaen University, Thailand
  • Nisachon Saelao Doctor, Department of Emergency, Udon Thani Hospital, Udon Thani, Thailand
  • Supinya Tuntapakul Assistant Professor, Division of Clinical Pharmacy, Faculty of Pharmaceutical Sciences, Khon Kaen University, Thailand
  • Cheardchai Soontornpas Associate Professor, Division of Clinical Pharmacy, Faculty of Pharmaceutical Sciences, Khon Kaen University, Thailand

Keywords:

Antibiotic-associated diarrhea, Clostridioides difficile, Risk assessment model

Abstract

Introduction: Antibiotic-associated diarrhea (AAD) has been an adverse event in patients with antibiotic use and more than 25% of AAD was associated with Clostridioides difficile infection (CDI). The incidence of CDI was increasing worldwide along with problems in treatment, but the data of CDI in Thailand was limited including the incidence and the risk factors for the infection. Methods This study was retrospective descriptive study. Relevant data in electronic medication records of hospitalized patients with CDI diagnosis between 1 October 2016 and 30 September 2019 at Udon Thani Hospital were reviewed and collected. Descriptive statistics were used for analyzing patients’ demographic data and univariate and multivariate analysis were used for analyzing the factors associated with CDI and developing the risk score model for CDI assessment. Results Of 124,061 patients admitted at Udon Thani hospital, 87 adults were diagnosed with CDI (incidence rate was 0.041% per admission or 0.4 case/1,000 patient admissions). Patients had an average age of 60.91 + 14.53 years, and an average BMI of 21.57 ± 3.54 kg/m2. Most of patients with CDI were admitted to the medical ward (78.05%). From the multivariable analysis, only 4 factors showed statistical significance in multiple logistic regression and the equation presented as CDI = -5.128 + 2.958 [Hypoalbuminemia] + 0.989 [Cardiovascular diseases] + 1.449 [Respiratory infections] + 1.158 [Number of anti-infectives ≥ 4 items]. Conclusion This risk assessment model may be a useful assessment tool for predicting CDI in patients with high-risk and needs closely monitoring during hospitalization.

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Published

2024-08-01

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บทความวิจัย