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BACKGROUND: Prediction models help to target patients at risk of multidrug-resistant organism (MDRO) colonization or infection and could serve as tools informing clinical practices to prevent MDRO transmission and inappropriate empiric antibiotic therapy. However, there is limited evidence to identify which among the available models are of low risk of bias and suitable for clinical application. OBJECTIVES: To identify, describe, appraise, and summarise the performance of all prognostic and diagnostic models developed or validated for predicting MDRO colonization or infection. DATA SOURCES: Six electronic literature databases and clinical registration databases were searched until April 2022. STUDY ELIGIBILITY CRITERIA: Development and validation studies of any multivariable prognostic and diagnostic models to predict MDRO colonization or infection in adults. PARTICIPANTS: Adults (≥ 18 years old) without MDRO colonization or infection (in prognostic models) or with unknown or suspected MDRO colonization or infection (in diagnostic models). ASSESSMENT OF RISK OF BIAS: The Prediction Model Risk of Bias Assessment Tool was used to assess the risk of bias. Evidence certainty was assessed using the Grading of Recommendations Assessment, Development, and Evaluation approach. METHODS OF DATA SYNTHESIS: Meta-analyses were conducted to summarize the discrimination and calibration of the models' external validations conducted in at least two non-overlapping datasets. RESULTS: We included 162 models (108 studies) developed for diagnosing (n = 135) and predicting (n = 27) MDRO colonization or infection. Models exhibited a high-risk of bias, especially in statistical analysis. High-frequency predictors were age, recent invasive procedures, antibiotic usage, and prior hospitalization. Less than 25% of the models underwent external validations, with only seven by independent teams. Meta-analyses for one diagnostic and two prognostic models only produced very low to low certainty of evidence. CONCLUSIONS: The review comprehensively described the models for identifying patients at risk of MDRO colonization or infection. We cannot recommend which models are ready for application because of the high-risk of bias, limited validations, and low certainty of evidence from meta-analyses, indicating a clear need to improve the conducting and reporting of model development and external validation studies to facilitate clinical application.
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Objectives: To evaluate the impact of pay-for-performance on antimicrobial consumption and antimicrobial expenditure in a large teaching hospital in Guangzhou, China. Methods: We collected data from hospital information system from January 2018 through September 2022 in the inpatient wards. Antimicrobial consumption was evaluated using antibiotic use density (AUD) and antibiotic use rate (AUR). The economic impact of intervention was assessed by antimicrobial expenditure percentage. The data was analyzed using interrupted time series (ITS) analysis. Results: Following the implementation of the intervention, immediate decreases in the level of AUD were observed in Department of Hematology Unit 3 (ß = -66.93 DDDs/100PD, P = 0.002), Urology (ß = -32.80 DDDs/100PD, P < 0.001), Gastrointestinal Surgery Unit 3 (ß = -11.44 DDDs/100PD, P = 0.03), Cardiac Surgery (ß = -14.30 DDDs/100PD, P = 0.01), ICU, Unit 2 (ß = -81.91 DDDs/100PD, P = 0.02) and Cardiothoracic Surgery ICU (ß = -41.52 DDDs/100PD, P = 0.05). Long-term downward trends in AUD were also identified in Organ Transplant Unit (ß = -1.64 DDDs/100PD, P = 0.02). However, only Urology (ß = -6.56 DDDs/100PD, P = 0.02) and Gastrointestinal Surgery Unit 3 (ß = -8.50 %, P = 0.01) showed an immediate decrease in AUR, and long-term downward trends in AUR were observed in Pediatric ICU (ß = -1.88 %, P = 0.05) and ICU Unit 1 (ß = -0.55 %, P = 0.02). Conclusion: This study demonstrates that the adoption of pay-for-performance effectively reduces antibiotic consumption in specific departments of a hospital in Guangzhou in the short term. However, it is important to recognize that the long-term impact of such interventions is often limited. Additionally, it should be noted that the overall effectiveness of the intervention across the entire hospital was not significant.
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OBJECTIVES: The COVID-19 pandemic has posed a significant threat to the global healthcare system, presenting a major challenge to antimicrobial stewardship worldwide. This study aimed to provide a comprehensive and up-to-date picture of global antimicrobial resistance (AMR) and antibiotic use in COVID-19 patients. METHODS: We conducted a systematic review to determine the prevalence of AMR and antibiotic usage among COVID-19 patients receiving treatment in healthcare facilities. Our search encompassed the PubMed, Web of Science, Embase, and Scopus databases, spanning studies published from December 2019 to May 2023. We utilized random-effects meta-analysis to assess the prevalence of multidrug-resistant organisms (MDROs) and antibiotic use in COVID-19 patients, aligning with both the WHO's priority list of MDROs and the AWaRe list of antibiotic products. Estimates were stratified by region, country, and country income. Meta-regression models were established to identify predictors of MDRO prevalence and antibiotic use in COVID-19 patients. The study protocol was registered with PROSPERO (CRD 42023449396). RESULTS: Among the 11,050 studies screened, 173 were included in the review, encompassing a total of 892,312 COVID-19 patients. MDROs were observed in 42.9% (95% CI 31.1-54.5%, I2 = 99.90%) of COVID-19 patients: 41.0% (95% CI 35.5-46.6%) for carbapenem-resistant organisms (CRO), 19.9% (95% CI 13.4-27.2%) for methicillin-resistant Staphylococcus aureus (MRSA), 24.9% (95% CI 16.7-34.1%) for extended-spectrum beta-lactamase-producing organisms (ESBL), and 22.9% (95% CI 13.0-34.5%) for vancomycin-resistant Enterococcus species (VRE), respectively. Overall, 76.2% (95% CI 69.5-82.9%, I2 = 99.99%) of COVID-19 patients were treated with antibiotics: 29.6% (95% CI 26.0-33.4%) with "Watch" antibiotics, 22.4% (95% CI 18.0-26.7%) with "Reserve" antibiotics, and 16.5% (95% CI 13.3-19.7%) with "Access" antibiotics. The MDRO prevalence and antibiotic use were significantly higher in low- and middle-income countries than in high-income countries, with the lowest proportion of antibiotic use (60.1% (95% CI 52.1-68.0%)) and MDRO prevalence (29.1% (95% CI 21.8-36.4%)) in North America, the highest MDRO prevalence in the Middle East and North Africa (63.9% (95% CI 46.6-81.2%)), and the highest proportion of antibiotic use in South Asia (92.7% (95% CI 90.4-95.0%)). The meta-regression identified antibiotic use and ICU admission as a significant predictor of higher prevalence of MDROs in COVID-19 patients. CONCLUSIONS: This systematic review offers a comprehensive and current assessment of MDRO prevalence and antibiotic use among COVID-19 patients in healthcare facilities. It underscores the formidable challenge facing global efforts to prevent and control AMR amidst the backdrop of the COVID-19 pandemic. These findings serve as a crucial warning to policymakers, highlighting the urgent need to enhance antimicrobial stewardship strategies to mitigate the risks associated with future pandemics.
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Antibacterianos , Gestão de Antimicrobianos , COVID-19 , SARS-CoV-2 , Humanos , Antibacterianos/uso terapêutico , COVID-19/epidemiologia , Instalações de Saúde/estatística & dados numéricos , Farmacorresistência Bacteriana Múltipla , Saúde Global , Prevalência , Staphylococcus aureus Resistente à Meticilina/efeitos dos fármacosRESUMO
Objectives: The emergency response to the COVID-19 pandemic may disrupt hospital management activities of antimicrobial resistance (AMR). This study aimed to determine the changing AMR trend over the period in China when stringent COVID-19 response measures were implemented. Methods: This retrospective study was conducted in a designated hospital for COVID-19 patients in Guangzhou, China from April 2018 to September 2021. The prevalence of 13 antimicrobial-resistant bacteria was compared before and after the COVID-19 responses through Chi-square tests. Interrupted time series (ITS) models on the weekly prevalence of AMR were established to determine the changing trend. Controlled ITS models were performed to compare the differences between subgroups. Results: A total of 10,134 isolates over 1,265 days were collected. And antimicrobial-resistant strains presented in 38.6% of the testing isolates. The weekly AMR prevalence decreased by 0.29 percentage point (95% CI [0.05-0.80]) after antimicrobial stewardship (AMS) policy, despite an increase in the prevalence of penicillin-resistant Streptococcus pneumoniae (from 0/43 to 15/43, p < 0.001), carbapenem-resistant Escherichia coli (from 20/1254 to 41/1184, p = 0.005), and carbapenem-resistant Klebsiella pneumoniae (from 93/889 to 114/828, p = 0.042). And the changing trend did not vary by gender (male vs. female), age (<65 vs. ≥65 years), service setting (outpatient vs. inpatient), care unit (ICU vs. non-ICU), the primary site of infection (Lung vs. others), and Gram type of bacteria (positive vs. negative). Conclusion: The response to COVID-19 did not lead to an increase in overall AMR; however, it appears that management strategy on the prudent use of antimicrobials likely contributed to a sizable long-term drop. The frequency of several multidrug-resistant bacteria continues to increase after the COVID-19 epidemic. It is crucial to continue to monitor AMR when COVID-19 cases have surged in China after the relaxation of restriction measures.