Canadian Journal of Infectious Diseases & Medical Microbiology最新文献

Background: Methicillin-resistant Staphylococcus aureus (MRSA) is a strain resistant to certain antibiotics, making it difficult to treat. MRSA infections can occur in healthcare settings and in the wider community. The prevalence of MRSA strains has significantly increased in Saudi Arabia over the last 2 decades. Objective: This study investigated the molecular epidemiology of MRSA isolates from patients at Gurayat General Hospital in Northern Saudi Arabia. Methods: Ninety-seven MRSA isolates were collected from patients in 2018-2019. MRSA isolates were subjected to antibiotic susceptibility testing, SCCmec typing, spa typing, and pvl gene detection. Results: All strains were susceptible to vancomycin, teicoplanin, and linezolid. Resistance to clindamycin (33%) and erythromycin (44%) was common. Resistance to ciprofloxacin (19%), gentamicin (14%), and tetracycline (19%) was also observed. Forty-four spa types were identified, with t304 (11.4%), t044 (8.4%), and t0127 (8.4%) being the most common. SCCmec types IVd (39%), IVc (27%), and V (24%) were most frequent. Additionally, the pvl gene was detected in 49% of the isolates. Conclusion: Community-acquired MRSA clones are prevalent in the healthcare setting. The predominant genotype was t304 (10%), followed by t044 (7%) and t0127 (7%). The SCCmec IVd type was the most common type frequently associated with spa type t304, whereas SCCmec type IVc was primarily associated with spa type t044. Isolates harboring SCCmec type IVd showed more nonsusceptible phenotypes to ciprofloxacin than other SCCmec types. Most MRSA isolates were resistant to erythromycin and clindamycin. These findings provide valuable insights into the molecular epidemiology of MRSA in the northern region of Saudi Arabia and highlight the prevalence of specific MRSA strains and their antibiotic resistance profiles. This information is essential for monitoring and addressing the spread of MRSA in healthcare settings.

Introduction: Contaminated paper currency may serve as a potential source for multidrug-resistant pathogens, posing risks not only to individuals who handle cash but also to public health. This study aimed to evaluate the knowledge, attitudes, and practices (KAP), and microbial contamination of paper currency and biofilm formation in the wallet as a reservoir of contamination in Saudi Arabia (KSA). Methods: Data were collected through an online survey assessing the KAP of the Saudi population regarding the use of contaminated notes across various provinces from February to April 2018. The analysis was conducted using EPI INFO V7 software. Microorganisms were isolated and identified from paper and plastic currency collected from slaughterhouses, gas stations, and hospital cafeterias. The MicroScan WalkAway system was utilized for confirmation and antimicrobial resistance (AMR) testing, while scanning electron microscopy (SEM) was employed to visualize biofilms present in wallets. Results: Among the 1415 adult Saudi citizens surveyed, 75% lacked awareness about contaminated currency. Over 50% reported not washing their hands after handling contaminated notes, with 78% of those being male. Fifteen different microbial species were isolated from contaminated notes, including Staphylococcus and fecal coliforms. Multidrug-resistant Staphylococcus and Enterobacter were detected in nearly all paper notes, while extended-spectrum beta-lactamase (ESBL) E. coli was found only in 50-riyal notes. Plastic notes showed no bacterial contamination. SEM images of the interior surfaces of wallets revealed the presence of extracellular polymeric substances (EPSs) in biofilms, along with cocci-shaped bacteria. Conclusion: To mitigate health risks, it is recommended that paper notes be replaced with plastic currency, and efforts should be made to raise awareness among the Saudi population regarding the dangers posed by contaminated notes.

Restaurants have played a vital role in spreading the respiratory virus due to the invalidation of certain preventive behaviors such as mask wearing. We analyzed a coronavirus disease 2019 (COVID-19) outbreak involving two clusters in a restaurant to analyze SARS-CoV-2 transmission by airborne droplets, including aerosols, in a restaurant outbreak. Computational fluid dynamics (CFD) was used to simulate the spread of respiratory droplets generated by coughing. The cough jet was modeled as a turbulent jet to study the dispersion of expiratory droplets, with the realizable k-ε model being applied in this simulation. This outbreak involved six diners (A, B, D, E, F, and G) in two clusters (X and Y). But the two clusters were seated at two tables separated by over 3 m from each other, while none of the 18 patrons at the other seven tables, even patrons at neighboring tables, became infected. Upon further investigation, we found that the index case in Cluster X coughed violently with his head facing posterior to the right when Diner F entered the restaurant and passed the posterior side of the index case. Adequate droplets were ejected from the index case and were inhaled by Diner F or trapped by the surfaces of Diner F's hands, clothing, and belongings. The virus-laden droplets and aerosols generated by coughing can be responsible for inhalation or contamination of surfaces that they fall onto, leading to spread of the disease.

Background: Extrapulmonary tuberculosis (EPTB) is a significant health problem which can lead to severe morbidity and mortality. In clinical practice, EPTB can have a variety of nonspecific clinical manifestations and can be concurrent with other types of EPTB. As information pertaining to concurrent EPTB is scarce, research efforts are needed to find concurrent EPTB types and to explore the association networks and rules of concurrent EPTB. Materials and Methods: An observational multicenter study was carried out at 21 hospitals from 15 provinces in China from Jan 1, 2011, to Dec 31, 2017. All the adult EPTB inpatients (≥ 15 years) were included. Multivariable logistic regression analysis was used to examine the associations of gender and age group for concurrent EPTB. The association network and rules for concurrent EPTB were analyzed by the Apriori algorithm. Results: A total of 75,993 adult EPTB inpatients (not including EPTB concurrent with PTB) were included. The ratio of male:female was 1.32. The most common types of EPTB lesions were tuberculous pleurisy (46.47%). In the fully adjusted multivariable logistic regression models, it was found that female EPTB patients (aOR = 1.129, 95% CI: 1.081-1.178) were more likely to have concurrent EPTB. As age increased, the risk of concurrent EPTB decreased (aOR < 1, p value for trend < 0.001). The association network graph showed that almost all the EPTB diseases may be concurrent with other types of EPTB. Ureteric tuberculosis and sacral tuberculosis diseases existed mainly in concurrence with other types of EPTB (about 80%). Tuberculous pleurisy and tuberculous lymphadenitis of the neck could be concurrent with more than 60 other types of EPTB disease. The most common concurrent EPTB types were tuberculous peritonitis concurrent with tuberculous pleurisy (1.64%). Sacral tuberculosis concurrentwith lumbar vertebra tuberculosis had the highest confidence value (68.56%). The strongest association rule was found for vesical tuberculosis concurrent with ureteric tuberculosis (lift = 166.18) and ureteric tuberculosis concurrent with vesical tuberculosis (lift = 166.18). Conclusion: The present study revealed the occurrence of concurrent EPTB types and analyzed the association network and rules among adult EPTB for the first time in a large sample population. Clinicians should be alert to the incidence of concurrent EPTB and that these patients require administration of customized treatment regimens in order to achieve the best outcomes.

Introduction: Antimicrobial resistance remains a global threat, with increasing infection and death rates. The World Health Organization identified Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp. (ESKAPE) as priority pathogens due to their increased antibiotic resistance development. This study assessed the resistance patterns of ESKAPE pathogens from 2015 to 2022 in Mbarara Regional Referral Hospital, Uganda. Methods: A retrospective study was conducted by reviewing retrieved data from WHONET. This is the laboratory software used in the microbiology laboratory in the Department of Microbiology, Mbarara University of Science and Technology (MUST), which receives samples from both the outpatient and the inpatient departments of Mbarara Regional Referral Hospital. Results: A total of 5733 bacterial isolates were recovered, of which, 4822 were ESKAPE pathogens from the collected clinical specimens including blood, stool, urine, swabs, cerebral spinal fluid, wounds, and sputum. Staphylococcus aureus (4291, 74.8%) was the most frequently isolated pathogen followed by Klebsiella pneumoniae (345, 6.0%). The bacteria categorized as ESKAPE pathogens showed significant rates of multidrug resistance. Ampicillin showed the highest resistance followed by ciprofloxacin. Conclusion: The significant prevalence of antimicrobial resistance to penicillin, ciprofloxacin, and tetracycline in ESKAPE bacteria emphasizes the significance of enhancing antimicrobial surveillance and infection-prevention and management initiatives within the country.

Background: The mortality rate is very high in patients with severe COVID-19. Nearly 32% of COVID-19 patients are critically ill, with mortality rates ranging from 8.1% to 33%. Early risk factor detection makes it easier to get the right care and estimate the prognosis. This study aimed to develop and validate a model to predict the risk of mortality based on hematological parameters at hospital admission in patients with severe COVID-19. Methods: The study retrospectively collected clinical data and laboratory test results from 396 and 112 patients with severe COVID-19 in two tertiary care hospitals as Cohort 1 and Cohort 2, respectively. Cohort 1 was to train the model. The LASSO method was used to screen features. The models built by nine machine learning algorithms were compared to screen the best algorithm and model. The model was visualized using nomogram, followed by trend analyses, and finally subgroup analyses. Cohort 2 was for external validation. Results: In Cohort 1, the model developed by the LR algorithm performed the best, with an AUC of 0.852 (95% CI: 0.750-0.953). Five features were included in the model, namely, D-dimer, platelets, neutrophil count, lymphocyte count, and activated partial thromboplastin time. The mode had higher diagnostic accuracy in patients with severe COVID-19 > 65 years of age (AUC = 0.814), slightly lower than in patients with severe COVID-19 ≤ 65 years of age (AUC = 0.875). The ability of the model to predict the occurrence of mortality was validated in Cohort 2 (AUC = 0.841). Conclusions: The risk prediction model for mortality for patients with severe COVID-19 was constructed by the LR algorithm using only hematological parameters in this study. The model contributes to the timely and accurate stratification and management of patients with severe COVID-19.

Objectives: Adequate ventilation and air filtration in the operating theatre are essential measures to prevent surgical site infections, which impact on hospital stay, healthcare costs and increased risk of mortality. The aim of the study is to assess how other factors, such as the number of operators and the opening of doors during surgery, affect microbiological airborne contamination. Methods: The data were extrapolated from 105 reports of operational controls conducted in the operating rooms in Siena's Teaching Hospital, Italy, from 2018 to 2021. The number of colonies incubated at 22°C and 36°C, was related by Spearman correlation analysis to the number of operators in the rooms and the number of air changes. The Mann-Whitney test was used to assess the difference between the mean of colonies detected with doors closed and opened. Results: The number of colonies incubated at 22°C was correlated only with air changes (Spearman ρ = -0.441; p < 0.001). In contrast, those incubated at 36°C were correlated with air changes (ρ = -0.394; p < 0.001) and the number of operators (ρ = +0.249; p=0.011). For colonies incubated at 22°C, the mean difference between opened and closed doors was not statistically significant (p=0.575). In contrast, the difference was statistically significant for those incubated at 36°C (p=0.013). In terms of airflow, our study showed a statistically significant difference (p < 0.001) between laminar and turbulent flow rooms for both colonies. Conclusion: Continuous monitoring of airflows, correlated with door opening and closing and the number of operators, can help predict levels of microbiological air contamination and thus prevent surgical infections.

Escherichia coli is a leading cause of both community-acquired and nosocomial infections. In particular, E. coli is responsible for 90% of all uncomplicated urinary tract infections (UTIs) and 65% of complicated UTIs. Among complicated UTIs, those caused by third-generation cephalosporin (3GC)-resistant E. coli strains, expressing extended-spectrum beta-lactamases (ESBLs), are on the rise. These strains show often a multidrug-resistant (MDR) phenotype, limiting the therapeutic options and the increasing incidence of MDR E. coli in Algeria is concerning. This study aims to compare the antibiotic resistance rates and profiles as well as the virulence traits between 3CG-resistant E. coli isolates, collected from Algerian inpatients (IPs) and outpatients (OPs). Our analyses include phenotypic and genotypic resistance factor detection, strains classification by genotyping and phylogrouping, as well as genotypic and phenotypic virulence factor evaluation. Among 42 E. coli isolates, 76.20% caused UTIs. ESBL producers (n = 35) carried all the bla _CTX-M, while bla _TEM was found in 69.04% of isolates. All isolates were MDR, and no significant differences in type and rate of antibiotic resistance were observed between IP- and OP-isolates. OP-isolates demonstrated greater virulence, exhibiting higher motility and biofilm production, compared to IP-isolates. Moreover, pathogenic Phylogroup B2 was prevalent among OP-isolates, while IP-isolates belonged predominantly to Phylogroup A. Our data suggest a uniform spreading of antibiotic-resistant genes within hospitals and communities. However, hospital environment selects for less virulent strains with increasing level of resistance; differently, communities host more virulent strains. This study highlights the urgent need to implement the surveillance of 3CG-resistant E. coli and to adopt the One Health approach to monitor the antimicrobial resistance (AMR) in the country.

The global HIV/AIDS pandemic remains a profound public health challenge, with substantial impacts on mortality and morbidity worldwide. In Ghana, where HIV prevalence persists, understanding disease progression among patients receiving antiretroviral therapy (ART) is crucial. This study, conducted in the Ashanti Region, employs a 5-state continuous-time Markov multistate model to analyze HIV progression based on CD4 cell counts, employing tuberculosis (TB) coinfection as a covariate. A retrospective cohort of 416 patients from St. Martins Catholic Hospital between 2000 and 2019 was studied. Transition intensities, sojourn time and probabilities between CD4 states, and the impact of TB coinfection were evaluated. The results showed that patients with CD4 counts ≥ 500 cells/mm³ spent more time before transitioning to lower CD4 levels, indicating the effectiveness of ART in controlling the disease at this level. However, the transition from 200-350 cells/mm³ to death was more likely than recovery to CD4 counts ≥ 500 cells/mm³, indicating the increased risk of mortality once CD4 counts drop significantly. TB coinfection did not significantly alter these transition probabilities, which may be due to the effective management of both HIV and TB in this cohort, emphasizing the need for integrated care strategies. This study emphasizes the importance of tailored interventions to manage HIV/AIDS effectively, particularly in regions with high disease burden. It is recommended that initiating treatment quickly can help maintain higher CD4 counts and improve survival.

Cervical cancer (CC) is a public health concern related to the human papillomavirus (HPV) persistent infection. Minichromosome maintenance 2 (MCM2) has been postulated as a surrogate marker for HPV infection. Thymopoietin (TMPO) is a nuclear protein regulated by E2F such as MCM2 or p16. TMPO can give rise to six different isoforms. Herein, both the mRNA and protein levels of TMPO isoforms were analyzed in cervical cells. TMPO expression was selected and analyzed through in silico in several databases from the healthy cervix and cervical lesions. TMPO RNA expression was evaluated in cervical samples and cell lines by RT-PCR and protein expression by Western-blot and immunohistochemistry assays. TMPO and MCM2 immunostaining were evaluated in cervical smears. The clinical-pathological correlation analysis was performed using Kruskal-Wallis or Χ ² tests. TMPO is overexpressed in 74% of CC cells and all CC cell lines. Moreover, negative immunostaining was observed in normal cervical tissue, compared to strong expression for cervical lesions. Interestingly, TMPO-α, -β, -δ, -ε, and -γ are expressed in all cervical cells and tissues, but a differential expression for α, -β, and -γ isoforms among the cervical cells was observed as overexpressed when HPV is present. Also, the immunostaining of both MCM2 and TMPO was quite similar, but TMPO expression was more sensitive and specific than MCM2 protein. The present study has revealed that TMPO protein expression could be a potential molecular marker for cervical transformed cells, highlighting the TMPO-α, -β, and -γ isoforms as a promising molecular marker of HPV infection.