BMC Infectious Diseases最新文献

Background: Staphylococcus aureus is a major pathogen responsible for both community-acquired and hospital-acquired infections. However, disseminated infections complicated by pulmonary abscesses and osteomyelitis are rare in otherwise healthy children.

Case presentation: We report a case of a previously healthy 12-year-old boy who presented with a 7-day history of cough and a 5-day history of fever and progressive swelling of the left upper limb after self-manipulating a right forearm furuncle. Physical examination and imaging revealed multifocal pulmonary abscesses and osteomyelitis of the left humerus. Blood cultures confirmed the presence of methicillin-resistant Staphylococcus aureus (MRSA). Despite initial empirical antibiotic therapy, the patient's symptoms persisted, necessitating four surgical interventions. The first two surgeries involved debridement with antibiotic-loaded calcium sulfate implantation. Nineteen months later, due to nonunion of the proximal humerus, the patient underwent open reduction and internal fixation with autologous iliac bone grafting, followed by subsequent removal of the internal fixation two years later. This staged approach, starting with infection control followed by delayed reconstruction, led to successful bone union, with complete resolution of the pulmonary abscesses on follow-up imaging.

Conclusion: This case highlights the potential for rapid hematogenous dissemination of Staphylococcus aureus leading to complex multi-organ involvement even in healthy pediatric patients. Prompt diagnosis, multidisciplinary management, and combined surgical and antibiotic therapy are critical for favorable outcomes.

Clinical trial number: Not applicable.

Introduction: Evidence of whether smoking affects the risk for SARS-CoV-2 infection is mixed. We aimed to clarify the inconsistencies in previous findings and whether the association is potentially causal using different Mendelian randomization (MR) methods.

Methods: We examined associations between smoking traits (initiation, cessation, and intensity) and SARS-CoV-2 infection in multivariable logistic regression, and one-sample and two-sample MR analyses. The study included n = 47,506 female and n = 28,229 male study subjects from the Norwegian Mother, Father, and Child Cohort Study (MoBa) with questionnaire data and genotype information. SARS-CoV-2 infection status was obtained by data linkage to the national health registry MSIS.

Results: We found no clear evidence of an association between smoking initiation and SARS-CoV-2 infection (multivariable regression: OR 1.08, 95% CI 0.96 to 1.20, one-sample multivariable MR analysis: OR 1.02, 95% CI 0.96 to 1.09, two-sample MR: OR 1.10 (95% CI 1.06 to 1.13). Also, we found no clear evidence of an association with smoking intensity (multivariable regression: OR 0.78, 95% CI 0.62 to 0.96, one-sample multivariable MR: OR 1.04, 95% CI 0.76 to 1.42, two-sample MR: OR 1.01, 95% CI 0.95 to 1.09, per 1 SD increase in number of cigarettes per day). Nor was there any association with smoking cessation. These findings did not change after accounting for educational level, BMI or risk-taking behavior in multivariable MR analyses.

Conclusions: We did not find robust evidence of causal associations between smoking and SARS-CoV-2 infection. Our investigation of potential violations to MR assumptions highlights the limitations of this approach to examine infection risk associated with smoking.

Background: Sepsis remains a significant cause of morbidity and mortality worldwide, particularly in resource-limited settings where early and accurate pathogen identification is critical for timely treatment. Traditional diagnostic methods often fall short in identifying causative agents with sufficient speed and precision. This study aimed to assess the diagnostic accuracy of the Agata Sepsis^® Platform, developed by the companies Alfa S.A.B. de C.V. (Nuevo Leon, Mexico), and Labcitec (Estado de Mexico, Mexico) a Next-Generation Sequencing-based tool, for identifying sepsis-causing bacteria in clinical blood culture samples from patients diagnosed with sepsis in hospitals in Mexico.

Methods: A retrospective analysis of 366 blood culture samples was conducted in two phases. Phase 1 employed biochemical tests to identify sepsis-causing bacteria, while Phase 2 assessed the performance of the Agata Sepsis^® Platform compared to traditional biochemical tests and the MALDI Biotyper^® system on clinical samples. Samples with inconsistent results underwent sequencing of the 16 S rDNA, rpoB, recA, and gyrB genes for definitive confirmation.

Results: The Agata Sepsis^® Platform demonstrated complete agreement with biochemical tests at the genus level (100%) and outperformed biochemical tests at the species level, achieving an overall identification rate of 56.13%. The addition of MALDI Biotyper^® improved biochemical test accuracy to 96.73%, but 12 isolates remained unidentified. Gene sequencing confirmed that the Agata Sepsis^® Platform correctly identified all 12 isolates, including species often misclassified by biochemical tests, such as Staphylococcus epidermidis and Staphylococcus hominis.

Conclusions: The Agata Sepsis^® Platform offers a reliable and highly accurate alternative to traditional methods for identifying sepsis-causing bacteria, specially difficult-to-identify pathogens. Its automated bioinformatic analysis of genomic data enhances taxonomic identification and shows strong potential for use as a complementary molecular tool in clinical diagnostics. Expanding its application and including antimicrobial resistance profiling could further increase its clinical value.

Clinical trial: Not applicable.

Background: Candida parapsilosis complex is an emerging opportunistic pathogen associated with bloodstream infections and healthcare‑associated outbreaks, particularly in intensive care units. Rising antifungal resistance underscores the need for continuous surveillance. This multicenter study assessed the in vitro susceptibility of eight antifungal agents against clinical, environmental, and healthcare worker isolates of the C. parapsilosis complex and investigated potential molecular mechanisms of resistance.

Methods: A total of 2,600 samples were collected between May 2023 and December 2024, including 2,180 clinical specimens, 330 environmental samples, and 90 hand swabs from healthcare workers. From these, 527 C. parapsilosis isolates were recovered. Identification was performed using conventional and molecular approaches. Antifungal susceptibility testing followed CLSI M27 (4th edition) guidelines. Isolates exhibiting resistance were further analyzed by sequencing the ERG11 and FKS1 genes.

Results: Among the 527 isolates, 510 originated from clinical settings, 6 from reusable breast pump sets, and 11 from healthcare worker hands. Overall, 10 isolates (1.9%) demonstrated resistance according to CLSI breakpoints, all of which were clinical in origin. Resistance was detected to fluconazole (0.38%), caspofungin (0.95%), and combined caspofungin-anidulafungin resistance (0.57%). The MIC values for fluconazole and caspofunginwere 4 µg/mL, indicating reduced susceptibility among clinical isolates. Voriconazole, clotrimazole, and amphotericin B exhibited strong in vitro activity. No resistance‑associatedmutations were identified in ERG11 or FKS1.

Conclusions: Despite the absence of detectable ERG11 or FKS1 mutations, reduced susceptibility to azoles and echinocandins was observed, primarily among clinical isolates. Environmental and healthcare worker isolates showed lower MIC values, suggesting minimal antifungal selection pressure outside patient care environments. These findings point to emerging antifungal resistance in C. parapsilosis clinical isolates in Iran and emphasize the importance of ongoing surveillance and molecular monitoring to inform therapeutic and infection control strategies. However more studies are required to correlate these findings with clinical outcomes.

Background: The lactate-to-albumin ratio (LAR) is correlated with mortality in critically ill patients; however, its predictive value for sepsis in the elderly remains underexplored.

Methods: This retrospective cohort study used the data from the MIMIC-IV database. The primary outcome was 28-day ICU mortality in elderly patients with sepsis. We used multivariate logistic regression, restricted cubic splines (RCS), subgroup analyses, and machine learning (LightGBM/XGBoost/SVM) to assess the predictive capacity of LAR.

Results: Among 5,115 eligible patients, elevated log (LAR) independently predicted mortality, as a continuous variable (adjusted odds ratio [OR] = 3.29; 95% confidence interval [CI]: 2.51-4.31; p < 0.001) and in quartiles (Q4 vs. Q1: adjusted OR = 2.11; 95% CI: 1.72-2.59). The RCS indicated a linear LAR-mortality association (p for nonlinear = 0.12). Subgroup analyses confirmed consistency across strata (interaction, p > 0.05). The LightGBM model achieved optimal discriminative performance (area under the curve = 0.788), with log (LAR) as the second-most important feature after the Simplified Acute Physiology Score II.

Conclusion: LAR is an independent predictor of 28-day mortality in elderly patients with sepsis, despite its limited standalone use. Our LightGBM-based integrative model demonstrated a robust prognostic performance and may aid in clinical decision-making and pending external validation.

Clinical trail number: Not applicable.