ABSTRACT
BACKGROUND: The association between allogeneic blood transfusion and healthcare-associated infection (HAI) is considered dose-dependent. However, this association may be confounded by transfusion duration, as prolonged hospitalization stay increases the risk of HAI. Also, it is not clear whether specific blood products have different dose-response risks. METHODS: In this retrospective cohort study, a logistic regression was used to identify confounding factors, and the association between specific blood products and HAI were analyzed. Then Cox regression and restricted cubic spline regression was used to visualize the hazard of HAI per transfusion product. RESULTS: Of 215,338 inpatients observed, 4.16% were transfused with a single component blood product. With regard to these transfused patients, 480 patients (5.36%) developed a HAI during their hospitalization stay. Logistic regression showed that red blood cells (RBCs) transfusion, platelets transfusion and fresh-frozen plasmas (FFPs) transfusion were risk factors for HAI [odds ratio (OR) 1.893, 95% confidence interval (CI) 1.656-2.163; OR 8.903, 95% CI 6.646-11.926 and OR 1.494, 95% CI 1.146-1.949, respectively]. However, restricted cubic spline regression analysis showed that there was no statistically dose-response relationship between different transfusion products and the onset of HAI. CONCLUSIONS: RBCs transfusion, platelets transfusion and FFPs transfusion were associated with HAI, but there was no dose-response relationship between them.
Subject(s)
Blood Transfusion , Cross Infection/epidemiology , Adult , Aged , Aged, 80 and over , China/epidemiology , Erythrocyte Transfusion/adverse effects , Humans , Length of Stay , Middle Aged , Platelet Transfusion/adverse effects , Retrospective Studies , Risk Factors , Tertiary Care CentersABSTRACT
BACKGROUND: In 2018, diagnosis-related group-based prospective payment system (DRG-PPS) was implemented nationwide by China that did not fully consider the additional costs caused by healthcare-associated infections (HAIs). HAIs can increase hospitalization costs, but only a few studies have been conducted in China. We aimed to assess the additional costs caused by HAIs. METHODS: A retrospective matched case-control (1:1) study was performed in one of the largest tertiary hospitals in Sichuan Province, China. A multiple linear regression was used to identify confounding factors, and the propensity score matching (PSM) method was used to balance confounding factors between cases and controls. On this basis, we estimated the additional costs caused by HAIs. RESULTS: Of the 109,294 inpatients observed, 1912 had HAI. After the PSM method was implemented, 1686 cases were successfully matched. Median hospitalization costs were 5613.03 for patients with HAIs and 3414.83 for patients without HAIs (P < 0.001), resulting in an absolute difference of 2198.19. With the exception of pathological diagnosis costs, surgical treatment costs and disposable medical material costs for surgery, all other types of costs for the cases with HAIs were larger. CONCLUSIONS: Patients with HAIs incurred greater hospitalization costs than non-HAI patients, which warrants closer attention if we are to reform the payment method of medical insurance in China.
Subject(s)
Cross Infection/economics , Hospital Costs , Hospitalization/economics , Adult , Aged , Aged, 80 and over , Case-Control Studies , China , Cross Infection/diagnosis , Female , Health Expenditures , Hospitalization/statistics & numerical data , Humans , Length of Stay , Male , Middle Aged , Propensity Score , Retrospective Studies , Tertiary Care CentersABSTRACT
Background: On January 7, 2019, we observed an outbreak of healthcare-associated infection (HAI) caused by Carbapenem-resistant Acinetobacter baumannii (CRAB) in the neurosurgical intensive care unit (NSICU). A follow-up epidemiological investigation was conducted, and an emergency response was initiated. We aimed to study the clonal transmission of CRAB and its possible source. Methods: A matched case-control (1:2) study was performed to identify the possible predisposing factors. A multifaceted intervention was implemented to control the outbreak. We collected environmental samples from patients' rooms and living area of the staff. CRAB isolates were tested for genetic relatedness by Pulsed-Field Gel Electrophoresis (PFGE). Results: Environmental sampling showed that a faucet aerator was contaminated with A. baumannii. Molecular typing revealed the only outbreak strain, which was isolated from tracheal aspirate cultures of the first case of community-acquired infection and 3 cases of HAI. In environmental samples, the outbreak strain was found only in the faucet aerator of the dining room. This CRAB outbreak was discovered in time, and further progress of this outbreak was prevented through a pre-set emergency response procedure. Conclusions: The faucet aerator acted as a reservoir for bacteria in the outbreak, and contamination of the faucet aerator might have occurred from splashes originating from handwashing by the healthcare workers (HCWs). In high-risk areas, such as NSICU, the faucet aerators should not be used during an outbreak or they should be regularly cleaned and disinfected. The start-up criteria for the emergency response played a key role in controlling the CRAB outbreak, and its settings should be discussed more widely.
