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Assessment of independent comorbidities and comorbidity measures in predicting healthcare facility-onset Clostridioides difficile infection in Kenya

Bibliographic Data

ID19590840
AuthorsWinnie C Mutai (0000-0003-0612-9430, University of Nairobi, corresponding author), Marianne Mureithi (0000-0001-9119-3167, University of Nairobi), Omu Anzala (0000-0001-5186-1415, University of Nairobi), Brian Kullin (0000-0001-5460-1977, University of Cape Town), Robert Ofwete (0000-0002-3758-624X, University of Nairobi), Cecilia Kyany’a (0000-0001-6293-5264), Cecilia Kyany’ a (United States Army Medical Research Directorate - Africa), Erick Odoyo (0000-0002-9533-2803, United States Army Medical Research Directorate - Africa), Lillian Musila (0000-0003-1418-6523, United States Army Medical Research Directorate - Africa), Gunturu Revathi (0000-0002-6938-8387, Aga Khan University Hospital Nairobi)
EditorsBen Pascoe (0000-0001-6376-5121)
Year2022
Volume2
Issue1
Pagese0000090
Publication date2022-01-31
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenuePLOS Global Public Health (JOURNAL)
Journal identifiersISSN: 2767-3375 • E-ISSN: 2767-3375
PublisherPublic Library of Science (PLoS) (PUBLISHER)
DOI10.1371/journal.pgph.0000090
PMID36962261
OpenAlexW4210496442
LanguageEN
References cited51

Introduction Clostridioides difficile is primarily associated with hospital-acquired diarrhoea. The disease burden is aggravated in patients with comorbidities due to increased likelihood of polypharmacy, extended hospital stays and compromised immunity. The study aimed to investigate comorbidity predictors of healthcare facility-onset C . difficile infection (HO-CDI) in hospitalized patients. Methodology We performed a cross sectional study of 333 patients who developed diarrhoea during hospitalization. The patients were tested for CDI. Data on demographics, admission information, medication exposure and comorbidities were collected. The comorbidities were also categorised according to Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI). Comorbidity predictors of HO-CDI were identified using multiple logistic regression analysis. Results Overall, 230/333 (69%) patients had comorbidities, with the highest proportion being in patients aged over 60 years. Among the patients diagnosed with HO-CDI, 63/71(88.7%) reported comorbidities. Pairwise comparison between HO-CDI patients and comparison group revealed significant differences in hypertension, anemia, tuberculosis, diabetes, chronic kidney disease and chronic obstructive pulmonary disease. In the multiple logistic regression model significant predictors were chronic obstructive pulmonary disease (odds ratio [OR], 9.51; 95% confidence interval [CI], 1.8–50.1), diabetes (OR, 3.56; 95% CI, 1.11–11.38), chronic kidney disease (OR, 3.88; 95% CI, 1.57–9.62), anemia (OR, 3.67; 95% CI, 1.61–8.34) and hypertension (OR, 2.47; 95% CI, 1.–6.07). Among the comorbidity scores, CCI score of 2 (OR 6.67; 95% CI, 2.07–21.48), and ECI scores of 1 (OR, 4.07; 95% CI, 1.72–9.65), 2 (OR 2.86; 95% CI, 1.03–7.89), and ≥ 3 (OR, 4.87; 95% CI, 1.40–16.92) were significantly associated with higher odds of developing HO-CDI. Conclusion Chronic obstructive pulmonary disease, chronic kidney disease, anemia, diabetes, and hypertension were associated with an increased risk of developing HO-CDI. Besides, ECI proved to be a better predictor for HO-CDI. Therefore, it is imperative that hospitals should capitalize on targeted preventive approaches in patients with these underlying conditions to reduce the risk of developing HO-CDI and limit potential exposure to other patients

Anemia · Comorbidity · Confidence interval · Diabetes mellitus · Kidney disease · Logistic regression · Odds ratio · Antibiotic Use and Resistance · Clostridium difficile and Clostridium perfringens research · Medicine · Nosocomial Infections in ICU · Internal Medicine

  • Defining Comorbidity

    Open Access•Jose M Valderas, Barbara Starfield et al.•The Annals of Family Medicine•2009

  • Risk Factors for Primary Clostridium difficile Infection; Results From the Observational Study of Risk Factors for Clostridium difficile Infection in Hospitalized Patients With Infective Diarrhea (ORCHID)

    Open Access•Kerrie Davies, Jody Lawrence et al.•Frontiers in Public Health•2020

  • Risk factors for Clostridium difficile infections – an overview of the evidence base and challenges in data synthesis

    Open Access•Paul Eze, Evelyn Balsells et al.•Journal of Global Health•2017

Citation velocityhistorical
Highly citedNo
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