Insights into Candida Colonization in Intensive Care Unit Patients: A Prospective Multicenter Study

Author:

Nascimento Teresa12ORCID,Inácio João3,Guerreiro Daniela2ORCID,Patrício Patrícia4,Proença Luís2ORCID,Toscano Cristina5,Diaz Priscila6,Barroso Helena2ORCID

Affiliation:

1. Unidade de Microbiologia Médica, Global Health and Tropical Medicine (GHTM), Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, 1349-008 Lisboa, Portugal

2. Egas Moniz Center for Interdisciplinary Research (CiiEM), Egas Moniz School of Health & Science, Caparica, 2829-511 Almada, Portugal

3. School of Applied Sciences, University of Brighton, Brighton BN2 4GJ, UK

4. Hospital Beatriz Ângelo, 2674-514 Loures, Portugal

5. Centro Hospitalar Lisboa Ocidental Hospital Egas Moniz, 1349-019 Lisboa, Portugal

6. Hospital Prof. Doutor Fernando da Fonseca, 2720-276 Amadora, Portugal

Abstract

The skin mycobiota plays a significant role in infection risk, pathogen transmission, and personalized medicine approaches in intensive care settings. This prospective multicenter study aimed to enhance our understanding of intensive care units’ (ICUs’) Candida colonization dynamics, identify modifiable risk factors, and assess their impact on survival risk. Specimens were taken from 675, 203, and 110 patients at the admission (D1), 5th (D5), and 8th (D8) days of ICU stay, respectively. The patient’s demographic and clinical data were collected. Candida isolates were identified by conventional culture-based microbiology combined with molecular approaches. Overall, colonization was 184/675 (27.3%), 87/203 (42.8%), and 58/110 (52.7%) on D1, D5, and D8, respectively. Candida colonization dynamics were significantly associated with ICU type (odds ratio (OR) = 2.03, 95% CI 1.22–3.39, p = 0.007), respiratory infection (OR = 1.74, 95% CI 1.17–2.58, p = 0.006), hemodialysis (OR = 2.19, 95% CI 1.17–4.10, p = 0.014), COVID-19 (OR = 0.37, 95% CI 0.14–0.99, p = 0.048), and with a poor 3-month outcome (p = 0.008). Skin Candida spp. colonization can be an early warning tool to generate valuable insights into the epidemiology, risk factors, and survival rates of critically ill patients, and should be considered for epidemiological surveillance.

Funder

FCT/MCTES

Publisher

MDPI AG

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