Linezolid-non-susceptible Enterococcus faecalis (LNSEf) has emerged as a critical clinical concern worldwide, yet data from Latin American settings remain scarce. This study aimed to investigate the molecular epidemiology and mechanisms underlying LNSEf in a Mexican tertiary care university hospital, focusing on clinical correlates and clonal relationships. A total of 392 non-duplicated E. faecalis isolates were collected over 12 months, of which 24 with minimum inhibitory concentrations ≥4 µg/mL underwent whole-genome sequencing to identify specific resistance determinants (optrA, cfrA, 23S rRNA mutations) and to perform multilocus sequence typing (MLST) and phylogenetic analyses. Of the 392 isolates, 6.12% showed linezolid non-susceptibility, predominantly linked to plasmid- or chromosomally encoded optrA; only two isolates carried cfrA. No mutations were detected in 23S rRNA domain V or ribosomal proteins L3/L4. Clinically, LNSEf strains were associated with immunosuppression, previous surgical interventions, and prolonged hospital stays. Although most LNSEf isolates retained susceptibility to ampicillin, vancomycin, and daptomycin, they exhibited high rates of resistance to other antibiotic classes, particularly aminoglycosides and fluoroquinolones. These findings underscore the emergence of LNSEf in this region, highlighting the need for robust genomic surveillance, strict infection control, and judicious antimicrobial stewardship to curb further dissemination.

Background/Objectives: The rise in multidrug-resistant pathogens complicates UTI management, particularly in empirical therapy. This study aimed to develop and describe a Bayesian hierarchical weighted-incidence syndromic combination antibiogram (WISCA) model to optimize antibiotic selection for adult patients with community-onset UTIs. Methods: A retrospective study was conducted using a Bayesian hierarchical model. Data from microbiology laboratory records and medical databases were analyzed, focusing on age, prior antibiotic exposure, and clinical characteristics. Clinical outcomes, including extended hospital stays and in-hospital mortality, were evaluated before WISCA model development. Unlike traditional antibiograms, a WISCA integrates patient-specific factors to improve antimicrobial coverage estimations. A total of 11 monotherapies and 18 combination therapies were tested against 15 pathogens, with posterior coverage probabilities and 95% highest density intervals (HDIs) used to assess coverage. Results: Inappropriate final antibiotic treatment was associated with worse outcomes. The Bayesian framework improved estimations, particularly for rare pathogen–antibiotic interactions, increasing model applicability in high-resistance settings. Combination regimens showed superior coverage, especially in MDR cases and older adults. Conclusions: This study employed a comprehensive methodological approach for WISCA development, enhancing empirical antibiotic selection by incorporating local resistance data and patient-specific factors in a middle-income Latin American country with a high antimicrobial resistance profile. These findings provide a foundation for future clinical applications and antimicrobial stewardship strategies in high-resistance environments.

Background/Objectives: The rise of multidrug-resistant pathogens complicates the management of urinary tract infections (UTIs), particularly in empirical antibiotic therapy. This study aimed to develop Weighted Incidence Syndromic Combination Antibiogram (WISCA) models to optimize antibiotic therapy for adult patients with community-onset UTIs presenting to emergency care settings at our institution. Methods: A retrospective study was conducted using a hierarchical Bayesian model to develop WISCA models for UTI management. Data were extracted from microbiology laboratory records and medical databases, focusing on adult patients stratified by age, prior antibiotic exposure, and clinical characteristics. Clinical outcomes, such as extended hospital stays and in-hospital mortality, were evaluated before WISCA model development. Eleven monotherapies and 18 combination therapies were tested against 15 pathogens, with posterior coverage probabilities and 95% highest density intervals (HDIs) used to assess antibiotic coverage. Results: Inappropriate antibiotic treatment (both empirical and directed) was initially associated with worse clinical outcomes. After adjusting for covariates, inappropriate directed treatment during the UTI episode was significantly associated with in-hospital mortality, highlighting the need for tailored therapeutic strategies. WISCA models provided robust estimates of antibiotic coverage probabilities, revealing subgroup differences. Combination regimens demonstrated superior coverage, particularly in patients with multidrug-resistant pathogens, older adults, and those with conditions linked to MDR organisms. Conclusions: WISCA models show promise in optimizing antibiotic selection for UTIs requiring hospitalization by integrating local resistance patterns and patient-specific factors. These findings support WISCA-informed strategies to potentially improve clinical outcomes and mitigate antibiotic resistance in UTIs.

Background: Linezolid-non-susceptible Enterococcus faecalis (LNSEf) has emerged as a critical clinical concern worldwide; however, data from Latin American settings remain scarce. Methods: We investigated 392 non-duplicated E. faecalis isolates collected over 12 months in a Mexican tertiary care hospital. Antimicrobial susceptibility was assessed phenotypically, and 24 isolates with linezolid minimum inhibitory concentrations ≥4 µg/mL underwent whole-genome sequencing. Bioinformatic analyses included multilocus sequence typing (MLST), detection of linezolid resistance mechanisms (optrA, cfrA, 23S rRNA mutations), and phylogenetic reconstruction. Results: Of the 392 isolates, 6.12% demonstrated linezolid non-susceptibility, predominantly associated with plasmid- or chromosomally encoded optrA, with only two isolates harboring cfrA. No mutations were detected in 23S rRNA domain V or ribosomal proteins L3/L4. Clinically, LNSEf isolates were linked to immunosuppression, prior surgical procedures, and extended hospital stays. MLST revealed broad genetic diversity, indicating both clonal expansion and independent acquisitions of resistance. Despite retaining susceptibility to ampicillin, vancomycin, and daptomycin, most LNSEf isolates possessed extensive resistance to other classes of antibiotics, particularly aminoglycosides and fluoroquinolones. Conclusions: LNSEf poses a growing threat in this region, driven largely by optrA. Strengthened genomic surveillance, stringent infection control, and optimized antimicrobial stewardship are vital to contain its spread.

Background/Objectives: Methicillin-resistant Staphylococcus aureus (MRSA) remains a major cause of both community-onset and hospital-acquired infections, yet longitudinal data from Latin American hospitals spanning the COVID-19 pandemic are scarce. We characterized temporal trends, seasonality, and the impact of the COVID-19 pandemic on MRSA prevalence and incidence density among clinical S. aureus isolates at a tertiary-care hospital in western Mexico over 9.5 years. Methods: We analyzed 6625 non-duplicate clinical S. aureus isolates (6609 with valid resistance data) from June 2016 to December 2025. Temporal trends were assessed using Mann–Kendall tests, Theil–Sen estimation, and binomial generalized linear models. Seasonality was evaluated through STL decomposition, generalized additive models, and Fourier analysis. An interrupted time series (ITS) model with GLS-AR(1) and Newey–West corrections compared three COVID-19 phases: pre-pandemic (2016–2020), high viral circulation (2020–2022), and post-peak stabilization (2022–2025). Exposure-adjusted incidence densities (per 1000 patient-days) were analyzed in parallel. Results: MRSA prevalence declined from 28.1% pre-pandemic to 14.0% post-peak (Mann–Kendall z = −9.03, p < 0.001; OR = 0.85 per year, 95% CI: 0.829–0.871). MRSA incidence density decreased by 50%, from 1.27 to 0.63 per 1000 patient-days, while aggregate S. aureus incidence density remained stable (z = −0.17, p = 0.868). The ITS joint Wald test confirmed a significant cumulative shift in MRSA trajectory post-pandemic (p = 0.019 counts; p = 0.012 incidence density), with a significant post-peak level drop (p = 0.008). S. aureus exhibited moderate seasonality peaking in May–July (GAM edf = 7.26, p < 0.001), whereas MRSA showed only marginal seasonal variation. Conclusions: MRSA declined markedly across the study period, with the steepest reduction following the Omicron peak. The decline persisted after adjustment for pandemic-related fluctuations in hospital volume, supporting periodic reassessment of empiric anti-MRSA prescribing policies in similar settings.