Evidence map›Paper›PMID 41214528›Full record

ArticleBMC infectious diseases2025

Treatment patterns of empirical antibiotic therapies for critically ill patients with sepsis: a cross-sectional study in Vietnam.

Thi Thanh Huong Trinh, Hong Tham Pham, Minh-Hoang Tran, Ngoc Trinh Huynh

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Article in BMC infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Thi Thanh Huong Trinh *School of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam.
Hong Tham Pham *Faculty of Pharmacy, Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam.
Minh-Hoang TranNTT Hi-Tech Institute, Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam.
Ngoc Trinh HuynhSchool of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam. hntrinh@ump.edu.vn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA systematic description of patterns of empirical antibiotic therapies (EAT) and the factors driving these in critically ill patients with sepsis is lacking in resource-limited settings. We aimed to address this knowledge gap by exploring the EAT patterns and risk factors for deviations from the guidelines in EAT in a Vietnamese hospital.

methodsWe conducted a simple random-sampling cross-sectional study at the intensive care unit (ICU) using medical records of critically ill patients with sepsis. The outcomes were guideline-compliant and guideline-deviant EAT (GcEAT and GdEAT). GcEAT was full compliance (choice and dosage) with local protocol for sepsis management, while GdEAT was any treatment that was not GcEAT. We used descriptive statistics to present data. Risk factors for GdEAT were reported with adjusted odds ratio, 95% confidence interval (OR and 95% CI; using multivariable logistic regression) and E-value (for factors with significant associations).

resultsAmong 93 medical records included for analysis (median age of 68, 41.9% being male, 24.7% being overweight-to-obese). Initiation through the concurrent administration of three antibiotic agents was reported in 37.6% of all cases (96.8% with pseudomonal coverage, 91.4% with anaerobic coverage, 34.4% with MRSA coverage, 49.5% with enterococcal coverage). GcEAT was detected in 62 records (66.7%, 95% CI 56.6% to 75.4%), while GdEAT was in 31 records (33.3%, 95% CI 24.6% to 43.4%). The specific patterns in the GdEAT group were: (1) broader/narrower antibacterial coverage (87.1%) and overlapping targets (12.9%) (for choice of EAT), (2) higher/lower doses (45.2%), longer/shorter dosing intervals (38.7%), and without therapeutic drug monitoring (16.1%) (for dosage of EAT). Acute kidney injury before ICU admission was identified as a potential risk factor for GdEAT (adjusted OR 3.41, 95% CI 1.16 to 10.01; E-value 3.10, lower bound of CI 1.37), which was mainly driven by deviations in the dosage of EAT (adjusted OR 3.45, 95% 1.18 to 10.08; E-value 3.12, lower bound of CI 1.39).

conclusionGdEAT was moderately prevalent in sepsis management of critically ill patients at a Vietnamese healthcare setting, primarily due to deviations in choice and dosage of the EAT. Further research and updated guidelines should address the optimal EAT in patients with acute kidney injury to avoid unstandardised deviations and noncompliances with antimicrobial protocols. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Anti-Bacterial AgentsSepsisAdultAgedAged, 80 and overCritical IllnessCross-Sectional StudiesFemaleGuideline AdherenceHumansIntensive Care UnitsMaleMiddle AgedRisk FactorsVietnamAnti-Bacterial AgentsCritical illnessEmpirical antibioticPerioperative careRisk factorsSepsis

Identifiers

PMID41214528
PMCPMC12604204

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.