The progression and distribution of the SARS-CoV-2 pandemic are continuously changing over time and can be traced by blood donors’ serological survey. Here, we investigated the seroprevalence of anti-SARS-CoV-2 antibodies in blood donors in Nuevo Leon, Mexico during 2020 as a strategy for the rapid evaluation of the spread of SARS-CoV-2 and asymptomatic case detection. We collected residual plasma samples from blood donors who attended two regional donation centers from January to December of 2020 to identify changes in anti-SARS-CoV-2 IgG prevalence. Plasma samples were analyzed on the Abbott Architect instrument using the commercial Abbott SARS-CoV-2 IgG chemiluminescent assay. We found a total of 99 reactive samples from 2068 analyzed plasma samples, resulting in a raw prevalence of 4.87%. Donors aged 18–49 years were more likely to be seropositive compared to those aged >50 years (p < 0.001). Weekly seroprevalence increased from 1.8% during the early pandemic stage to 27.59% by the end of the year. Prevalence was 1.46-fold higher in females compared to males. Case geographical mapping showed that Monterrey city recorded the majority of SARS-CoV-2 cases. These results show that there is a growing trend of seroprevalence over time associated with asymptomatic infection that is unnoticed under the current epidemiological surveillance protocols.

Summary: Background: The progression and distribution of SARS-CoV-2 is unknown because typically only symptomatic individuals are diagnosed. Aim: We evaluated the seroprevalence of anti-SARS-CoV-2 in blood donors in Nuevo Leon, Mexico as a strategy for asymptomatic case detection of COVID-19 and epidemic progression. Methods/Materials: We tested 1968 blood donors that attended two regional donation centers in Northeast Mexico from January 1 ^st to August 30, 2020, to identify anti-SARS-CoV-2 IgG by chemiluminescent immunoassay. Additionally, routine tests for donors including Brucella, Chagas, HCV, VDRL, HIV-1, and HBsAg identification were performed. Results: We found 77 donors reactive for anti-SARS-CoV-2 IgG (seroprevalence 3.99%) and none of them had reported recent COVID-19 symptoms. Donors aged 18 to 49 years (89.5%) were more likely to be seropositive compared to those aged 50 years or older (10.5%) (P<0.001). Prevalence of antibodies increased each epidemiological (EPI) week, parallel to the report of confirmed cases by RT-PCR, identifying the highest prevalence between EPI week 33 and 35 (10.2% to 19%). The metropolitan area of Monterrey recorded the highest number of cases. Routine tests showed that the prevalence of anti-Brucella was 0.13%, anti-HCV 0.5%, anti-HIV-1-2 0.14%, HBsAg 0.16%, Chagas 0.48% and syphilis 1.06%. Conclusions: There is a growing trend of seroprevalence over time, parallel to the constantly increasing epidemic curve in our region and it was higher under 49 years of age associated with asymptomatic infection in donors from the Nuevo Leon area. Detection of anti-SARS-CoV-2 in blood donors is a potential tool for tracking the progression and identifying population exposure during the SARS-CoV-2 outbreak.

Background and Objectives: Interpreting acid–base disorders is challenging, particularly in complex or mixed cases. Given the growing potential of large language models (LLMs) to assist in cognitively demanding tasks, this study evaluated their performance in interpreting arterial blood gas (ABG) results. Materials and Methods: In this single-center retrospective study, 200 ABG datasets were curated to include 40 cases in each of five diagnostic categories: metabolic acidosis, respiratory acidosis, metabolic alkalosis, respiratory alkalosis, and no acid–base disorder. Three medical students, each assigned to one LLM (ChatGPT GPT-4o, Copilot GPT-4, or Gemini 1.5-flash/2.5-flash), perform ABG interpretation using two evaluation methods: interpretation (LLM-I) and interpretation with supervision model (LLM-S). Two clinical pathologists independently performed the conventional evaluation to serve as the reference standard. Results: Agreement for identifying the primary acid–base (APD) disorder was strong across all approaches (Cohen’s κ ≥ 0.88). For identifying both primary and secondary disorders regardless of order (APSD), LLM-I showed moderate agreement (ChatGPT κ = 0.65, Copilot κ = 0.61, Gemini κ = 0.62), whereas LLM-S achieved strong agreement (ChatGPT κ = 0.91, Copilot κ = 0.81, Gemini κ = 0.81). Conclusions: LLM-assisted ABG interpretation demonstrates strong concordance with expert interpretation in detecting primary acid–base disorders. These tools may enhance the understanding of acid–base disorders while reducing calculation-related errors among medical students.

Background: The diagnostic performance of sepsis biomarkers may vary according to the clinical comparator population. We evaluated 11 routinely available inflammatory and hematologic biomarkers in two matched diagnostic settings. Methods: We conducted a retrospective observational study using linked MIMIC-IV, MIMIC-IV-ED, and MIMIC-IV-Note data. Adult emergency department episodes were classified as sepsis, suspected infection without sepsis, or controls without suspected infection. Comparison-specific profile matching retained the same 525 sepsis episodes in both analyses, together with 214 controls without suspected infection and 315 episodes with suspected infection without sepsis. Biomarker discrimination was assessed using area under the receiver operating characteristic curve (AUROC) with DeLong inference. Results: Against controls without suspected infection, C-reactive protein (CRP) had the highest AUROC (0.786; 95% CI, 0.748–0.823), followed by absolute lymphocyte count (0.654; 0.613–0.696) and the neutrophil-to-lymphocyte ratio (NLR; 0.636; 0.594–0.677). Against suspected infection without sepsis, absolute lymphocyte count had the highest AUROC (0.677; 0.641–0.714), followed by NLR (0.626; 0.588–0.664), whereas CRP discrimination decreased to 0.555 (0.514–0.595). The cross-setting difference for CRP was 0.231 (95% CI, 0.183–0.278; Holm-adjusted p <0.001). Sensitivity analyses produced similar qualitative findings. Conclusions: Biomarker discrimination for sepsis varied according to the clinical comparator population, with the magnitude of cross-setting change differing across biomarkers. CRP showed the largest change, whereas absolute lymphocyte count retained modest discrimination in both settings. These findings emphasize the importance of interpreting biomarker performance within clinically relevant diagnostic contrasts.