Impact of COVID-19 isolation measures on ICU microbial
resistance dynamics: simulation-based statistical modeling
analysis

J 2025

Impact of COVID-19 isolation measures on ICU microbial resistance dynamics: simulation-based statistical modeling analysis

ŠITINA, Michal; Milada DVOŘÁČKOVÁ; Renata TEJKALOVÁ a Vladimír ŠRÁMEK

Základní údaje

Originální název

Impact of COVID-19 isolation measures on ICU microbial resistance dynamics: simulation-based statistical modeling analysis

Autoři

ŠITINA, Michal; Milada DVOŘÁČKOVÁ; Renata TEJKALOVÁ a Vladimír ŠRÁMEK

Vydání

ANTIMICROBIAL RESISTANCE AND INFECTION CONTROL, LONDON, BMC, 2025, 2047-2994

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

30221 Critical care medicine and Emergency medicine

Stát vydavatele

Velká Británie a Severní Irsko

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 4.400 v roce 2024

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14110/25:00142795

Organizační jednotka

Lékařská fakulta

Klíčová slova anglicky

Antibiotic resistance; Intensive care unit; Cross-transmission; Environmental persistence; Stenotrophomonas maltophilia; Pseudomonas aeruginosa; Infection control; Machine learning

Štítky

14110122, rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 4. 12. 2025 07:21, Mgr. Tereza Miškechová

Anotace

V originále

BackgroundThe transmission of antibiotic-resistant bacteria in intensive care units (ICUs) poses a significant challenge to infection control and patient safety. While direct patient-to-patient transmission is well documented, the relative contributions of endogenous bacterial selection and cross-transmission remain uncertain.MethodsThis retrospective study analyzed microbiological data from two ICUs at St. Anne's University Hospital in Brno, Czech Republic, between 2018 and 2021. Machine learning algorithms and random simulation models were employed to evaluate clustering patterns of resistant bacterial detections and to distinguish between exogenous cross-transmission and endogenous bacterial acquisition. Bacterial findings were compared across three epidemiologically distinct periods-precovid, covid, and intercovid-characterized by differing hygiene protocols and patient populations. The study assumes that the historically unprecedented hygiene measures during the COVID-19 pandemic substantially reduced horizontal cross-transmission, thereby providing a unique opportunity to estimate the relative contributions of exogenous transmission and endogenous acquisition under routine ICU conditions.ResultsThe prevalence of Pseudomonas aeruginosa (PSAE) was four times higher during the covid period than precovid and remained elevated in the intercovid period. Stenotrophomonas maltophilia detections tripled during covid, while Klebsiella pneumoniae and Escherichia coli resistant to cefotaxime doubled. The proportion of first bacterial detections occurring after 48 h of ICU admission was significantly higher during covid. Clustering analysis revealed no significant deviation from random distribution for most bacteria, except for PSAE, which exhibited non-random clustering, particularly in the intercovid period. Stenotrophomonas maltophilia showed a highly uneven distribution between the two ICUs, suggesting long-term environmental persistence.ConclusionOur findings suggest that antibiotic selection pressure is the primary driver of resistant bacteria acquisition in ICUs, while direct cross-transmission appears to play a limited role. However, environmental persistence may contribute to the recurrent detection of Stenotrophomonas maltophilia, emphasizing the need for enhanced decontamination strategies.

Citovat

ŠITINA, Michal; Milada DVOŘÁČKOVÁ; Renata TEJKALOVÁ a Vladimír ŠRÁMEK. Impact of COVID-19 isolation measures on ICU microbial resistance dynamics: simulation-based statistical modeling analysis. ANTIMICROBIAL RESISTANCE AND INFECTION CONTROL. LONDON: BMC, 2025, roč. 14, č. 1, s. 1-17. ISSN 2047-2994. Dostupné z: https://doi.org/10.1186/s13756-025-01649-9.

@article{2537798,
   author = {Šitina, Michal and Dvořáčková, Milada and Tejkalová, Renata and Šrámek, Vladimír},
   article_location = {LONDON},
   article_number = {1},
   doi = {https://doi.org/10.1186/s13756-025-01649-9},
   keywords = {Antibiotic resistance; Intensive care unit; Cross-transmission; Environmental persistence; Stenotrophomonas maltophilia; Pseudomonas aeruginosa; Infection control; Machine learning},
   language = {eng},
   issn = {2047-2994},
   journal = {ANTIMICROBIAL RESISTANCE AND INFECTION CONTROL},
   title = {Impact of COVID-19 isolation measures on ICU microbial resistance dynamics: simulation-based statistical modeling analysis},
   url = {https://link.springer.com/article/10.1186/s13756-025-01649-9},
   volume = {14},
   year = {2025}
}

TY  - JOUR
ID  - 2537798
AU  - Šitina, Michal - Dvořáčková, Milada - Tejkalová, Renata - Šrámek, Vladimír
PY  - 2025
TI  - Impact of COVID-19 isolation measures on ICU microbial resistance dynamics: simulation-based statistical modeling analysis
JF  - ANTIMICROBIAL RESISTANCE AND INFECTION CONTROL
VL  - 14
IS  - 1
SP  - 1-17
EP  - 1-17
PB  - BMC
SN  - 20472994
KW  - Antibiotic resistance
KW  - Intensive care unit
KW  - Cross-transmission
KW  - Environmental persistence
KW  - Stenotrophomonas maltophilia
KW  - Pseudomonas aeruginosa
KW  - Infection control
KW  - Machine learning
UR  - https://link.springer.com/article/10.1186/s13756-025-01649-9
N2  - BackgroundThe transmission of antibiotic-resistant bacteria in intensive care units (ICUs) poses a significant challenge to infection control and patient safety. While direct patient-to-patient transmission is well documented, the relative contributions of endogenous bacterial selection and cross-transmission remain uncertain.MethodsThis retrospective study analyzed microbiological data from two ICUs at St. Anne's University Hospital in Brno, Czech Republic, between 2018 and 2021. Machine learning algorithms and random simulation models were employed to evaluate clustering patterns of resistant bacterial detections and to distinguish between exogenous cross-transmission and endogenous bacterial acquisition. Bacterial findings were compared across three epidemiologically distinct periods-precovid, covid, and intercovid-characterized by differing hygiene protocols and patient populations. The study assumes that the historically unprecedented hygiene measures during the COVID-19 pandemic substantially reduced horizontal cross-transmission, thereby providing a unique opportunity to estimate the relative contributions of exogenous transmission and endogenous acquisition under routine ICU conditions.ResultsThe prevalence of Pseudomonas aeruginosa (PSAE) was four times higher during the covid period than precovid and remained elevated in the intercovid period. Stenotrophomonas maltophilia detections tripled during covid, while Klebsiella pneumoniae and Escherichia coli resistant to cefotaxime doubled. The proportion of first bacterial detections occurring after 48 h of ICU admission was significantly higher during covid. Clustering analysis revealed no significant deviation from random distribution for most bacteria, except for PSAE, which exhibited non-random clustering, particularly in the intercovid period. Stenotrophomonas maltophilia showed a highly uneven distribution between the two ICUs, suggesting long-term environmental persistence.ConclusionOur findings suggest that antibiotic selection pressure is the primary driver of resistant bacteria acquisition in ICUs, while direct cross-transmission appears to play a limited role. However, environmental persistence may contribute to the recurrent detection of Stenotrophomonas maltophilia, emphasizing the need for enhanced decontamination strategies.
ER  -

ŠITINA, Michal; Milada DVOŘÁČKOVÁ; Renata TEJKALOVÁ a Vladimír ŠRÁMEK. Impact of COVID-19 isolation measures on ICU microbial resistance dynamics: simulation-based statistical modeling analysis. \textit{ANTIMICROBIAL RESISTANCE AND INFECTION CONTROL}. LONDON: BMC, 2025, roč.~14, č.~1, s.~1-17. ISSN~2047-2994. Dostupné z: https://doi.org/10.1186/s13756-025-01649-9.

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