Antimicrobial Resistance and Infection Control最新文献

Background: The digitalization of information systems allows automatic measurement of antimicrobial consumption (AMC), helping address antibiotic resistance from inappropriate drug use without compromising patient safety.

Objectives: Describe and characterize a new automated AMC surveillance service for intensive care units (ICUs), with data stratified by referral clinic and linked with individual patient risk factors, disease severity, and mortality.

Methods: An automated service collecting data from the electronic medical record was developed, implemented, and validated in a healthcare region in northern Sweden. We performed an observational study from January 1, 2018, to December 31, 2021, encompassing general ICU care for all ≥18-years-olds in a catchment population of 270000 in secondary care and 900000 in tertiary care. We used descriptive analyses to associate ICU population characteristics with AMC outcomes over time, including days of therapy (DOT), length of therapy, defined daily doses, and mortality.

Results: There were 5608 admissions among 5190 patients with a median age of 65 (IQR 48-75) years, 41.2% females. The 30-day mortality was 18.3%. Total AMC was 1177 DOTs in secondary and 1261 DOTs per 1000 patient days and tertiary care. AMC varied significantly among referral clinics, with the highest total among 810 general surgery admissions in tertiary care at 1486 DOTs per 1000 patient days. Case-mix effects on the AMC were apparent during COVID-19 waves highlighting the need to account for case-mix. Patients exposed to more than three antimicrobial drug classes (N = 242) had a 30-day mortality rate of 40.6%, with significant variability in their expected rates based on admission scores.

Conclusion: We introduce a new service and instructions for automating local ICU-AMC data collection. The versatile long-term ICU-AMC metrics presented, covering patient factors, referral clinics and mortality outcomes, are expected to be beneficial in refining antimicrobial drug use.

Background: In the initial phase of the SARS-CoV-2 pandemic, masking has been widely accepted in healthcare institutions to mitigate the risk of healthcare-associated infection. Evidence, however, is still scant and the role of masks in preventing healthcare-associated SARS-CoV-2 acquisition remains unclear.We investigated the association of variation in institutional mask policies with healthcare-associated SARS-CoV-2 infections in acute care hospitals in Switzerland during the BA.4/5 2022 wave.

Methods: SARS-CoV-2 infections in hospitalized patients between June 1 and September 5, 2022, were obtained from the "Hospital-based surveillance of COVID-19 in Switzerland"-database and classified as healthcare- or community-associated based on time of disease onset. Institutions provided information regarding institutional masking policies for healthcare workers and other prevention policies. The percentage of healthcare-associated SARS-CoV-2 infections was calculated per institution and per type of mask policy. The association of healthcare-associated SARS-CoV-2 infections with mask policies was tested using a negative binominal mixed-effect model.

Results: We included 2'980 SARS-CoV-2 infections from 13 institutions, 444 (15%) were classified as healthcare-associated. Between June 20 and June 30, 2022, six (46%) institutions switched to a more stringent mask policy. The percentage of healthcare-associated infections subsequently declined in institutions with policy switch but not in the others. In particular, the switch from situative masking (standard precautions) to general masking of HCW in contact with patients was followed by a strong reduction of healthcare-associated infections (rate ratio 0.39, 95% CI 0.30-0.49). In contrast, when compared across hospitals, the percentage of health-care associated infections was not related to mask policies.

Conclusions: Our findings suggest switching to a more stringent mask policy may be beneficial during increases of healthcare-associated SARS-CoV-2 infections at an institutional level.

Background: Stenotrophomonas maltophilia, a multidrug-resistant gram-negative bacteria (GNB), is an emerging nosocomial pathogen. This study assessed the clinical outcomes of GNB infections in surgical intensive care unit (SICU) patients post-abdominal surgery, focusing on the differences between S. maltophilia and other GNBs, including Pseudomonas aeruginosa.

Methods: A retrospective study was conducted on SICU patients at Kaohsiung Chang Gung Memorial Hospital from 2010 to 2020, who developed GNB infections following abdominal surgery.

Results: Of 442 patients, 237 had S. maltophilia and 205 had non-S. maltophilia GNB infections (including 81 with P. aeruginosa). The overall mortality rate was 44.5%, and S. maltophilia infection emerged as a significant contributor to the mortality rate in patients with GNB infections. S. maltophilia patients had longer mechanical ventilation and SICU stays, with a 30-day mortality rate of 35.4%, higher than the non-S. maltophilia GNB (22.9%) and P. aeruginosa (21%) groups. In-hospital mortality was also higher in the S. maltophilia group (53.2%) compared to the non-S. maltophilia GNB (34.6%) and P. aeruginosa groups (29.6%). Risk factors for acquiring S. maltophilia included a higher Sequential Organ Failure Assessment score and prior broad-spectrum antibiotics use. Older age, polymicrobial infections, and elevated bilirubin were associated with increased 30-day mortality in S. maltophilia patients.

Conclusion: S. maltophilia infections in post-abdominal surgery patients are linked to higher mortality than non-S. maltophilia GNB and P. aeruginosa infections, emphasizing the need for early diagnosis and treatment to improve outcomes.

Background: Carbapenem-resistant E. coli (CREco) pose a significant public health threat due to their multidrug resistance. Colistin is often a last-resort treatment against CREco; however, the emergence of colistin resistance gene mcr-1 complicates treatment options.

Methods: Two E. coli strains (ECO20 and ECO21), recovered from hospitalized patients in distinct wards, exhibited resistance to carbapenems and colistin. Whole-genome sequencing and phenotypic characterization were employed to study resistance patterns, plasmid profiles, transferability of resistance and virulence genes, and siderophore production capabilities. Comparative genome analysis was used to investigate the genetic environment of mcr-1, bla_NDM-7, and virulence clusters.

Results: Both E. coli strains exhibited thr presence of both mcr-1 and bla_NDM-7 genes, showing high resistance to multiple antibiotics. Genomic analysis revealed the clonal transmission of these strains, possessing identical plasmid profiles (pMCR, pNDM, and pVir) associated with colistin resistance, carbapenem resistance, and virulence factors. Conjugation experiments confirmed the transferability of these plasmids, indicating their potential to disseminate resistance and virulence traits to other strains. Comparative genomic analyses unveiled the distribution of mcr-1 (IncX4-type) and bla_NDM (IncX3-type) plasmids across diverse bacterial species, emphasizing their adaptability and threat. The novelty of pVir indicates its potential role in driving the evolution of highly adaptable and pathogenic strains.

Conclusions: Our findings underscore the co-occurrence of mcr-1, bla_NDM-7, and siderophore-producing plasmids in E. coli, which poses a significant concern for global health. This research is crucial to unravel the complex mechanisms governing plasmid transfer and recombination and to devise robust strategies to control their spread in healthcare settings.

Objective: This study aimed to develop and apply a nomogram with good accuracy to predict the risk of CRAB infections in neuro-critically ill patients. In addition, the difficulties and expectations of application such a tool in clinical practice was investigated.

Methods: A mixed methods sequential explanatory study design was utilized. We first conducted a retrospective study to identify the risk factors for the development of CRAB infections in neuro-critically ill patients; and further develop and validate a nomogram predictive model. Then, based on the developed predictive tool, medical staff in the neuro-ICU were received an in-depth interview to investigate their opinions and barriers in using the prediction tool during clinical practice. The model development and validation is carried out by R. The transcripts of the interviews were analyzed by Maxqda.

Results: In our cohort, the occurrence of CRAB infections was 8.63% (47/544). Multivariate regression analysis showed that the length of neuro-ICU stay, male, diabetes, low red blood cell (RBC) count, high levels of procalcitonin (PCT), and number of antibiotics ≥ 2 were independent risk factors for CRAB infections in neuro-ICU patients. Our nomogram model demonstrated a good calibration and discrimination in both training and validation sets, with AUC values of 0.816 and 0.875. Additionally, the model demonstrated good clinical utility. The significant barriers identified in the interview include "skepticism about the accuracy of the model", "delay in early prediction by the indicator of length of neuro-ICU stay", and "lack of a proper protocol for clinical application".

Conclusions: We established and validated a nomogram incorporating six easily accessed indicators during clinical practice (the length of neuro-ICU stay, male, diabetes, RBC, PCT level, and the number of antibiotics used) to predict the risk of CRAB infections in neuro-ICU patients. Medical staff are generally interested in using the tool to predict the risk of CRAB, however delivering clinical prediction tools in routine clinical practice remains challenging.

Introduction: To promote the nation-wide implementation of semi-automated surveillance (AS) of surgical site infection after hip and knee arthroplasty, the Dutch National Institute for Public Health and the Environment (RIVM) deployed a decentralised multifaceted implementation strategy. This strategy consisted of a protocol specifying minimum requirements for an AS system, supported by a user manual, education module, individual guidance for hospitals and user-group meetings. This study describes an effect evaluation and process evaluation of the implementation strategy for AS in five frontrunner hospitals.

Methods: To evaluate the effect of the implementation strategy, the achieved phase of implementation was determined in each frontrunner hospital at the end of the study period. The process evaluation consisted of (1) an evaluation of the feasibility of strategy elements, (2) an evaluation of barriers and facilitators for implementation and (3) an evaluation of the workload for implementation. Interviews were performed as a basis for a subsequent survey quantifying the results regarding the feasibility as well as barriers and facilitators. Workload was self-monitored per profession. Qualitative data were analysed using a framework analysis, whereas quantitative data were analysed descriptively.

Results: One hospital finished the complete implementation process in 240 person-hours. Overall, the elements of the implementation strategy were often used, positively received and overall, the strategy was rated effective and feasible. During the implementation process, participants perceived the relative advantage of AS and had sufficient knowledge about AS. However, barriers regarding complexity of AS data extraction, data-infrastructure, and validation, lack of capacity and motivation at the IT department, and difficulties with assigning roles and responsibilities were experienced.

Conclusion: A decentralised multifaceted implementation strategy is suitable for the implementation of AS in hospitals. Effective local project management, including clear project leadership and ownership, obtaining commitment of higher management levels, active involvement of stakeholders, and appropriate allocation of roles and responsibilities is important for successful implementation and should be facilitated by the implementation strategy. Sufficient knowledge about AS, its requirements and the implementation process should be available among stakeholders by e.g. an education module. Furthermore, exchange of knowledge and experiences between hospitals should be encouraged in user-group meetings.

Introduction: Antibiotic self-medication is a global public health concern contributing to antibiotic resistance. This systematic review and meta-analysis aim to assess the prevalence of antibiotic self-medication and its associated factors in Ethiopia.

Methods: A comprehensive search of electronic databases was conducted from MEDLINE (PubMed), Scopus, Google Scholar and Web of Science to identify relevant studies published between 2000 and 2024. Adult households, undergraduate university students and health care professionals who had taken antibiotics without a prescription in the household setting were included in this review. The primary outcome of this review is antibiotic self- medication. The random-effects model was used to estimate pooled prevalence rates. The outcome measure was analyzed with STATA version 17 software.

Results: A total of nine studies were included in the Meta-analysis, comprising a sample size of 5908 participants. The pooled prevalence of antibiotic self-medication among Ethiopians was found to be 46.14 with 95% Confidence Interval [35.71, 56.57]. The most frequently used classes of self-medicated antibiotics were penicillins, followed by tetracyclines. Community pharmacies were the source of information that individuals utilized. The most common reported reasons for antibiotic self-medication include previous experience of treating a similar illness, to save cost, lack of time and avoiding waiting time for medical services. Participants having less than high school educational level was the most commonly reported factor associated with self-medication antibiotics.

Conclusion: Antibiotic self-medication is a prevalent practice in Ethiopia. This underscores the need for targeted interventions such as educating people about the risks associated with using antibiotics without medical guidance, which results in a reduction in antibiotic resistance.

Background: Antibiotic consumption is a driver for the increase of antimicrobial resistance. The objective of this study is to analyze variations in antibiotic consumption and its appropriate use in Brazil from 2014 to 2019.

Methods: We conducted a time series study using the surveillance information system database (SNGPC) from the Brazilian Health Regulatory Agency. Antimicrobials sold in retail pharmacies were evaluated. All antimicrobials recorded for systemic use identified by the active ingredient were eligible. Compounded products and formulations for topic use (dermatological, gynecological, and eye/ear treatments) were excluded. The number of defined daily doses (DDDs)/1,000 inhabitants/day for each antibiotic was attributed. The number of DDDs per 1,000 inhabitants per day (DDIs) was used as a proxy for consumption. Results were stratified by regions and the average annual percentage change in the whole period studied was estimated. We used the WHO Access, Watch, and Reserve (AWaRe) framework to categorize antimicrobial drugs.

Results: An overall increase of 30% in consumption from 2014 to 2019 was observed in all Brazilian regions. Amoxicillin, azithromycin and cephalexin were the antimicrobials more consumed, with the Southeast region responsible for more than 50% of the antibiotic utilization. Among all antimicrobials analyzed 45.0% were classified as watch group in all Brazilian regions.

Conclusion: We observed a significant increase in antibiotics consumption from 2014 to 2019 in Brazil restricted to the Northeast and Central West regions. Almost half of the antibiotics consumed in Brazil were classified as watch group, highlighting the importance to promote rational use in this country.

Background: A long-term follow-up of close contacts to monitor their infection status is essential to formulate a promising screening strategy. The study aimed to assess the dynamics of tuberculosis (TB) infection using Interferon-γ release assay (IGRA) and determine risk factors associated with TB infection.

Methods: Definite TB patients were interviewed and their household contacts were screened for TB infection by IGRA during 12-month longitudinal investigation.

Results: We included in our analyses 184 household contacts of 92 index TB patients. 87 individuals (47.3%) in contact group progressed to TB infection, of whom 86 developed into IGRA positive within 24 weeks. Close contacts with a higher age and comorbidities are easier to exhibit TB infection. Analysis showed that risk factors for becoming IGRA-positive individuals included residence, older age, comorbidities, BCG scar and high bacterial load. Contacts with BCG scar had a lower IGRA-positive rate.

Conclusion: IGRA conversion generally occurs within 24 weeks after exposure. The TB transmission happens since subclinical TB stage and the presence of BCG scar is an independent protective factor reducing risk of TB infection among close contacts. Repeated IGRA tests are sensible to conducted among close contacts at 24 weeks after exposure to identify the IGRA-positive individuals.

Background: The prevalence of multiple nosocomial infections (MNIs) is on the rise, however, there remains a limited comprehension regarding the associated risk factors, cumulative risk, probability of occurrence, and impact on length of stay (LOS).

Method: This multicenter study includes all hospitalized patients from 2020 to July 2023 in two sub-hospitals of a tertiary hospital in Guangming District, Shenzhen. The semi-Markov multi-state model (MSM) was utilized to analyze risk factors and cumulative risk of MNI, predict its occurrence probability, and calculate the extra LOS of nosocomial infection (NI).

Results: The risk factors for MNI include age, community infection at admission, surgery, and combined use of antibiotics. However, the cumulative risk of MNI is lower than that of single nosocomial infection (SNI). MNI is most likely to occur within 14 days after admission. Additionally, SNI prolongs LOS by an average of 7.48 days (95% Confidence Interval, CI: 6.06-8.68 days), while MNI prolongs LOS by an average of 15.94 days (95% CI: 14.03-18.17 days). Furthermore, the more sites of infection there are, the longer the extra LOS will be.

Conclusion: The longer LOS and increased treatment difficulty of MNI result in a heavier disease burden for patients, necessitating targeted prevention and control measures.