Observational studyAntimicrobial resistance and infection control2020
Estimating length of stay and inpatient charges attributable to hospital-acquired bloodstream infections.
Observational study in Antimicrobial resistance and infection control, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Geographical mapping and temporal trends of Acinetobacter baumannii carbapenem resistance: A comprehensive meta-analysis.PloS one · 2024Pooled it
- Exploring the Factors Influencing the Non-Prescription Use of Medication in Bangladesh: A Cross-Sectional Study.Health science reports · 2026Article
- The economic burden of Hospital-Acquired Infections on cancer patients under China's pioneering Diagnosis-Intervention Packet payment model: a retrospective study.Frontiers in public health · 2026Article
- Clinical and Economic Outcomes Associated with Rapid Antimicrobial Susceptibility Reporting and Dual-Card Testing in ICU Bloodstream Infections.Infection and drug resistance · 2026Article
- An Algorithm for Rapid and Low-Cost Detection of Carbapenemases Directly from Positive Blood Cultures Using an Immunochromatographic Test.Antibiotics (Basel, Switzerland) · 2025Article
- Bacteriophage therapy to combat MDR non-fermenting Gram-negative bacteria causing nosocomial infections: recent progress and challenges.Naunyn-Schmiedeberg's archives of pharmacology · 2025Review
- Development of a Nomogram to Classify In-Hospital Atrial Fibrillation Among Patients Hospitalized With Acute Myocardial Infarction: A Retrospective Case-Control Study.Reviews in cardiovascular medicine · 2025Article
- The impact of optimizing microbial diagnosis processes on clinical and healthcare economic outcomes in hospitalized patients with bloodstream infections.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2024Article
- Prognostic Factors That Affect Mortality Patients withInfection and drug resistance · 2024Article
- Incremental costs of hospital-acquired infections in COVID-19 patients in an adult intensive care unit of a tertiary hospital from a low-resource setting.Antimicrobial resistance and infection control · 2023Article
- Hospital length of stay for COVID-19 patients: a systematic review and meta-analysis.Multidisciplinary respiratory medicine · 2022Article
- Multidrug-ResistantThe Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale · 2022Article
- Article
- Stenotrophomonas maltophilia bacteremia in children: risk factors and mortality rate.Antimicrobial resistance and infection control · 2021Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHospital-acquired bloodstream infection (BSI) is associated with high morbidity and mortality and increases patients' length of stay (LOS) and hospital charges. Our goals were to calculate LOS and charges attributable to BSI and compare results among different models.
methodsA retrospective observational cohort study was conducted in 2017 in a large general hospital, in Beijing. Using patient-level data, we compared the attributable LOS and charges of BSI with three models: 1) conventional non-matching, 2) propensity score matching controlling for the impact of potential confounding variables, and 3) risk set matching controlling for time-varying covariates and matching based on propensity score and infection time.
resultsThe study included 118,600 patient admissions, 557 (0.47%) with BSI. Six hundred fourteen microorganisms were cultured from patients with BSI. Escherichia coli was the most common bacteria (106, 17.26%). Among multi-drug resistant bacteria, carbapenem-resistant Acinetobacter baumannii (CRAB) was the most common (42, 38.53%). In the conventional non-matching model, the excess LOS and charges associated with BSI were 25.06 days (P < 0.05) and US$22041.73 (P < 0.05), respectively. After matching, the mean LOS and charges attributable to BSI both decreased. When infection time was incorporated into the risk set matching model, the excess LOS and charges were 16.86 days (P < 0.05) and US$15909.21 (P < 0.05), respectively.
conclusionThis is the first study to consider time-dependent bias in estimating excess LOS and charges attributable to BSI in a Chinese hospital setting. We found matching on infection time can reduce bias.
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