American Journal of Infection Control

Objectives: Large language models (LLMs) are increasingly used in medicine, but evaluation is often on multiple choice questions and management of common conditions. Infectious diseases (ID) can present complex scenarios that require considerations beyond guideline-based responses. We assessed LLM performance in these situations including with ID-specific criteria to consider infection control or antimicrobial stewardship (AMS). Methods: We evaluated four LLMs (Claude 3.5 Sonnet, GPT-4o, GPT-o1, and a local instance of Llama 3.1 8B) in October 2024, on five complex ID vignettes. The LLM responses were each evaluated for 18 items by two board-certified ID clinicians and pairwise comparisons were performed between LLMs. Results: There was no significant difference between performance of GPT-o1, GPT-4o and Claude Sonnet on general medical criteria, and were comparable with respect to how often they provided an unsafe response (GPT-o1 30%, GPT-4o 40%, Claude 37%) and contained a critical omission (GPT-o1 27%, GPT-4o 43%, Claude 47%). Llama 3.1 8B had significantly decreased performance for most criteria. On ID-specific criteria, GPT-o1 outperformed other models and all models significantly outperformed Llama for interpreting microbiology results, AMS principles, appropriate antimicrobial spectrum and infection control considerations. Performance was poor in secondary prevention and management of risk factors. Conclusions: On complex ID scenarios, LLM responses were variable. The open-source, smaller Llama 3.1 8B model performed poorly and large, non-reasoning models varied, but more than 30% of responses containing a risk of harm or critical omission. These findings suggest caution is required when deploying these models in ID domains without specialist oversight.

Importance: OPAT is an underutilized strategy in low- and middle-income countries (LMICs). Addressing the knowledge gaps among frontline physicians through structured interventions is vital for optimizing hospital bed utilization and antimicrobial stewardship. Objective: To assess whether a structured multidisciplinary care bundle is associated with improved patient enrollment and clinical care quality in an OPAT program in India. Design, Setting, and Participants: This pre-post quality improvement study was conducted in the Department of General Medicine at a tertiary care referral hospital in Rishikesh, India. Data from patient encounters during a 6-month pre-intervention period (December 1, 2023 to May 31, 2024) were compared with encounters during a 6-month post-implementation period (January 1, 2025 to June 31, 2025). Participants included all postgraduate residents serving as frontline clinical practitioners. Interventions: A structured OPAT bundle comprising a formalized educational curriculum (interactive didactic sessions and bedside practical training), standardized eligibility screening, and a coordinated telephonic monitoring protocol (from June 1, 2024 to December 31, 2024). Main Outcomes and Measures: The primary outcome was the change in the number of eligible patients enrolled in OPAT. Secondary outcomes included clinical process quality indicators (counseling, IV access arrangement, and monitoring compliance), 30-day rehospitalization rates, and therapy-related complications. Results: A total of 20 preintervention patient encounters were compared with 39 postintervention encounters, with similar baseline characteristics between groups (mean age, 37 vs 40 years; male gender, 65% vs 69.2%). Prior to implementation, only 33.3% (20 of 60) of eligible patients received OPAT, whereas 100% (39 of 39) of eligible patients were enrolled following the intervention (p < 0.001). Key clinical processes reached 100% compliance post implementation, including patient counseling (40% vs 100%; p < 0.001), pre-discharge IV access (40% vs 100%; p < 0.001), and daily telephonic monitoring (10% vs 100%; p < 0.001). Safety outcomes remained stable, with no significant differences in readmission rates (5.0% vs 0%; p = 0.34) or drug-related complications. Conclusions and Relevance: This quality improvement study provides evidence that a structured package of OPAT bundle interventions is associated with a transition to universal enrollment of eligible patients and perfect adherence to safety indicators. These results suggest that standardizing the outpatient transition through physician education and coordinated monitoring is a feasible and effective strategy for optimizing hospital resource utilization in LMICs.

This study aimed to clarify aerosol exposure risks throughout the workflow of a Biosafety Level 2 (BSL-2) polymerase chain reaction (PCR) laboratory, validate the suitability of the {Phi}X174 bacteriophage as an indicator virus, and provide evidence for biosafety control measures. The {Phi}X174 bacteriophage was used to simulate viral samples, and a concentration-bacteriophage plaque standard curve was constructed (R2=0.998). Five operational steps in a simulated PCR laboratory were quantitatively monitored for aerosol concentration using double-layer agar plates, with blank controls used to eliminate interference. Statistical analysis was employed to identify risk differences. Sample homogenization ((5.67 {+/-} 1.23) x 104 plaque-forming units (PFU)/m3) and nucleic acid extraction ((3.45 {+/-} 0.89) x 104 PFU/m3) were identified as high-/very high-risk steps. The viral load in the samples was strongly positively correlated with the aerosol concentration (r = 0.926, P <0.001), with aerosol levels linearly decreasing with increasing distance in high-risk steps. The {Phi}X174 bacteriophage demonstrated high detection sensitivity (101 PFU/ml) and demonstrated safety compatibility with BSL-2 laboratories. Aerosol risks in PCR laboratories exhibit step-specific differentiation, and {Phi}X174 serves as an ideal indicator virus. Proposed strategies such as equipment upgrades and personal protective equipment (PPE) grading can reduce exposure risks.

Background. The 2024 international reference standard for urinary tract infection (UTI) research scores four domains - symptoms and signs, systemic criteria, pyuria, and culture - to classify samples as No UTI, Possible UTI, Probable UTI, or Definite UTI. It explicitly identifies spinal cord injury (SCI) as a condition of impaired symptom perception, and states that catheter-associated UTI requires a separate standard. We applied it to verified-asymptomatic samples from adults with neurogenic lower urinary tract dysfunction (NLUTD) due to spinal cord injury or disease (SCI/D) who use intermittent catheterization (IC), to test whether it can identify UTI likelihood in this population. Methods. The reference standard was applied to 224 samples from 99 adults with NLUTD due to SCI/D using IC, all verified asymptomatic by the Urinary Symptom Questionnaire for Neurogenic Bladder-Intermittent Catheter (USQNB-IC) at sampling and for 72 hours prior. Because no participant was febrile and no blood markers are drawn in this population, the systemic-criteria domain scored zero for every sample; the reported classifications are therefore a floor. Pyuria was scored under conservative and inclusive interpretations of categorical urinary white blood cell (WBC) bins. Results. Under conservative interpretation, 40.2% of samples were classified No UTI, 21.9% Possible UTI, and 37.9% Probable UTI; under inclusive interpretation, 11.6% No UTI, 38.4% Possible UTI, and 50.0% Probable UTI. No sample reached Definite UTI - a structural consequence of the empty systemic domain. Conclusions. The consensus reference standard classifies 38-50% of fully asymptomatic NLUTD-IC samples as Probable UTI, a floor estimate that could only rise if blood markers were available. This confirms the 2024 framework's own prediction that a separate standard is needed for populations with altered symptom expression and baseline-positive urinary markers.

Point-of-care Hepatitis C Virus (HCV) RNA assays reduce diagnostic turnaround time but depend on benchtop instrumentation and continuous electricity, limiting their deployment in the harm reduction and community settings where confirmatory testing is most needed, as people who use drugs (PWUD) carry a disproportionate share of the HCV burden in the United States. This is a systemic problem in diagnostic development, where decision-making and design requirements overlook point-of-use stakeholders. Closing the gap requires integrating real-world constraints throughout design rather than validating against user needs once a product already exists. Here, we apply a human-centered design (HCD) approach to inform rigorous, stakeholder-derived design requirements, implementation considerations, and early value proposition for a novel point-of-need HCV RNA test intended for deployment in harm reduction and community settings in Indiana. To determine design specifications grounded in real-world context, our objectives were (1) identifying and characterizing context-specific experiences and barriers to HCV testing among higher-risk populations; (2) assessing the perceived benefits and acceptability of the proposed test within real-world settings across direct and indirect user groups; and (3) translating the user needs and contextual constraints into design requirements and implementation considerations that support the test's clinical, operational, and user-centered value. We conducted 18 semi-structured interviews with frontline staff and HCV testing/treatment pipeline experts (n=11) and people who get tested (n=7) across harm reduction organizations, syringe service programs, and community testing settings, analyzed using Rapid Qualitative Analysis guided by the PARRQA framework. Stakeholders responded positively to a single-encounter point-of-need RNA test, and implementation considerations, including funding restrictions, staffing structures, and diverse deployment settings, directly shaped design requirements spanning turnaround time, sample type and volume, portability, result output, target operator, and ease of use. Benchmarking these stakeholder-derived specifications against the FIND Dx HCV target product profile (TPP) showed that stakeholder input confirmed, modified, or extended several TPP criteria and introduced requirements the TPP does not address. Together, these objectives constitute an upstream, evidence-driven design process that translates contextual and stakeholder knowledge into actionable engineering requirements, highlighting the need for diverse stakeholder engagement at all stages of the design process for closing the translation gap between laboratory-validated diagnostic tools and effective point-of-need deployment.

Background: Vaccine hesitancy and logistical barriers continue to limit influenza vaccination uptake among healthcare personnel. The STRENGTH initiative evaluated employee drivers of influenza vaccine acceptance in healthcare workgroups with lower vaccination compliance. Methods: This mixed-methods program evaluation used a custom Epic electronic medical record dashboard to identify workgroups with lower influenza vaccination rates, followed by focus groups, targeted worksite vaccination clinics, and an anonymous survey. Survey data from 73 respondents were analyzed using descriptive statistics, Mann-Whitney U tests, Kruskal-Wallis tests, chi-square or Fisher exact tests, and Spearman rank correlations. Results: Respondents had a mean age of 44.8 years (SD 11.3); 36 of 70 respondents reporting binary gender were male. Convenience of worksite vaccination received the highest importance ratings (mean 4.72/5), followed by protection from influenza (mean 4.38/5). Both were rated significantly above the neutral midpoint of 3 (Wilcoxon p<0.001). The strongest observed Spearman correlations were between peer pressure and leadership participation (rho=0.47) and between protection from influenza and willingness to receive a future combined influenza/COVID-19 vaccine (rho=0.42). Conclusions: Convenience and perceived protection were the most important vaccination drivers. Employer-sponsored workplace vaccination programs can reduce logistical barriers while providing opportunities for targeted education and trust-building. Keywords: influenza vaccination; healthcare workers; vaccine hesitancy; occupational health; workplace vaccination; employer-sponsored vaccination

Hydroclimate whiplash, defined as the rapid transition between unusually wet and dry conditions, is expected to intensify under climate change, yet its population health impacts remain largely unknown. Here we quantified the association between hydroclimate whiplash and mortality across the contiguous United States from 2003 to 2023 using monthly county-level mortality records, standardized precipitation evapotranspiration index data, and two-stage time-series models. We identified overall and direction-specific dry-to-wet and wet-to-dry whiplash events at seasonal and sub-annual timescales and across 5-, 10-, and 20-year recurrence intervals. More severe whiplash events were associated with higher all-cause mortality risk; 5-, 10-, and 20-year sub-annual overall whiplash events increased mortality risk over five months by 3.4%, 4.5%, and 5.7%, respectively. Elevated risks were observed across cause-specific mortality outcomes, with the strongest association for infectious diseases. We estimated that 103,471 deaths were attributable to overall whiplash during the study period. These findings identify hydroclimate whiplash as an emerging climate-related public health threat and suggest that adaptation strategies focused on single hazards may underestimate the health burden of rapid, sequential hydroclimatic extremes.

Objectives To evaluate two-year, side-by-side outcomes of a prospective audit and feedback (PAF)-based antimicrobial stewardship program (ASP) in a quaternary ICU in Ghana, comparing diagnostic stewardship, antimicrobial prescribing patterns, and clinician adherence to stewardship recommendations between 2024 and 2025. Longitudinal PAF data from low- and middle-income countries (LMIC) quaternary ICUs are scarce; this study addresses that evidence gap. Methods A retrospective comparative analysis of routine Antimicrobial Stewardship (AMS) surveillance data was conducted at the University of Ghana Medical Centre ICU: 102 visits in 2024 and 63 in 2025. Proportions were compared by chi-square or Fishers exact test; continuous variables by Mann-Whitney U. Wilson score 95% confidence intervals (CIs) were computed for primary proportions. Results Biomarker-guided prescribing rose from 86.3% to 100% of visits (p=0.005) and culture and sensitivity testing from 74.5% to 90.5% (p=0.02). Targeted (culture-guided) therapy increased significantly from 23.5% to 41.7% of antibiotic recipients (p=0.03), while empiric prescribing declined correspondingly. Overall antibiotic utilization remained high in both years (96.1% vs 95.2%; p=1.00), and meropenem use rose from 42.9% to 56.7% (p=0.13). AMS interventions were recommended in 67.6% and 63.5% of visits, respectively. Clinician acceptance improved markedly from 40.6% (95% CI: 29.8-52.4%) to 67.5% (95% CI: 52.0-79.9%) (p=0.01). Conclusions Two years of PAF in a Ghanaian quaternary ICU demonstrated progressive program maturation: universal biomarker adoption, a significant shift toward targeted prescribing, and markedly enhanced clinician acceptance. Persistently high antibiotic utilization and rising carbapenem dependence underscore the need for sustained surveillance and carbapenem-sparing strategies in LMIC critical care.

In this study, we analyze viral load data from wastewater treatment plants (WWTPs) across multiple U.S. states and address the challenge of selecting an optimal subset of sites to improve COVID-19 hospitalization forecasts. Using forward (greedy) regression with a baseline ARIMA model, we identify the most informative WWTPs that enhance forecast accuracy while reducing the number of sampling locations. Our analysis, based on NWSS data, shows that the optimal number of sites typically ranges from 2-8, though some states, including NY, IL, and WI, benefit from a larger set (10-20). We also leverage a Virginia-level digital twin model specifically designed for wastewater data modeling and analysis and our results show that for different parameter settings, that forecast accuracy can be achieved with strategically chosen small number of sites, providing

Introduction Patients with nephrolithiasis face challenges in making a high-quality, preference sensitive decision. Our prior work established feasibility and patient acceptance of a software-based decision aid (DA). The objectives for this study were to identify implementation strategies for the DA in routine care and determine whether DA implementation enhances decisional quality for patients. Methods New nephrolithiasis patients were recruited from the institution Medical Center from June 2018 to April 2024 to receive a software-based pre-visit DA that measured care preferences and used decision analysis to rank treatments. The RE-AIM framework and Plan-Do-Study-Act (PDSA) cycles were used to improve implementation outcomes. Patients completed survey instruments evaluating decisional conflict, shared decision-making, care satisfaction, and treatment choice following their provider visit. These metrics were compared in the DA cohort (n=81) to those in a usual care cohort (n=78) with Wilcoxon rank-sum and Chi-square (or Fishers exact) tests. Results Implementation data revealed sustained reach and progressive improvement in fidelity. The DA cohort reported higher decisional quality relative to controls (p=0.003) and reported greater support/advice to make a choice (p=0.005). The DA cohort more often discussed options with their doctor (87.5% vs 69.2%, p=0.005) and were more likely to be promoters of their provider (p<0.001) and health system (p=0.029). The DA cohort was less likely to have switched their treatment preference post-consultation (32.1% vs 71.8%, p<0.001) suggesting greater consistency in decision-making. Conclusions Software-based DAs in nephrolithiasis can mitigate decisional conflict, improve SDM, and improve patient satisfaction. Further work should explore broader implementation and long-term clinical outcomes.

While exposure to volatile organic compounds such as ethylene dichloride and vinyl chloride monomer is a well-established cause of liver disease, particularly hepatic hemangiosarcoma, characterizing real-world exposure profiles in communities surrounding industrial centers remains challenging. Calvert City, Kentucky (population ~2,500), provides a unique setting characterized by both active industrial emissions and legacy sources of air toxics. To address these complexities, this method paper describes the framework for the Biomonitoring and Environmental Assessment for Community Outreach and Neighborhood Safety (BEACON) study. By utilizing a novel, multi-dimensional exposure assessment strategy, BEACON aims to characterize air toxic exposures and provide actionable data for community health and safety. For the BEACON study, we will leverage Kentucky Department of Air Quality measures of air toxics, analyze urine samples in a small cohort of community volunteers, analyze community urine via wastewater in an adjacent community, geocode citizen odor reporting, assess blood markers in wildlife, survey small and large animal veterinarians in the area for anomalies in morbidity and mortality, and work with the regional health system to enhance vigilance for health issues associated with toxicants present in the area. In addition, blood samples will be collected at three time points and biobanked for future analyses. Efforts will be made to link this study to additional large-scale long-term cohorts where possible. Throughout the project, community engagement will play a critical role by raising awareness, fostering collaboration, and ensuring that the voices of affected residents are heard.

Background. Clostridioides difficile infection (CDI) imposes a burden that extends well beyond the gastrointestinal tract, yet existing outcome measures only partially capture the patient experience. We used frontier large language models (LLMs) on patient and caregiver narratives at scale to describe how burden shifts with disease course. Methods. We analyzed 189 testimonials from the Peggy Lillis Foundation corpus, sorted into four cohorts with recurrence (r) and fulminant (f) severity as axes (rfCDI, fCDI, rCDI, non-rfCDI). Two independent LLMs coded eight thematic domains, four fulminant flags, thirteen emerging semantic fields, the dominant dimension, and narrative arcs. Two clinicians independently coded a subset for inter-rater reliability (PABAK, Gwet's AC1). Results. Treatment trajectory was the dominant theme in recurrent disease, whereas death and near-death dominated non-recurrent fulminant narratives. Psychological burden was near-universal in fulminant disease (98.0% in rfCDI, 97.2% in fCDI). Caregiver and bereavement content concentrated in fCDI (66.7%). Diagnostic failure was frequent across recurrent cohorts (47.6 - 56.1%). Bacteriotherapy tracked recurrence (60.2% rfCDI versus 5.6% fCDI). Financial, mental-health, and caregiver burdens were prominent and are currently unaddressed by guidelines. Human-human reliability was substantial (PABAK 0.79 for semantic fields, 0.76 for domains); arc coding was least reliable. Conclusions. Patient narratives reveal a course-dependent, multidimensional burden in CDI. Concrete gaps exist between what patients prioritize, what guidelines recommend, and what therapy access provides. Frontier-LLM coding, validated against clinicians, offers a reproducible route to translate these priorities into research, care, and policy.

Occupational ocular injuries are a preventable yet neglected public health problem, particularly in low- and middle-income countries. Maintenance workers are exposed to diverse ocular hazards daily, yet compliance with protective measures is consistently poor. A descriptive cross-sectional study was conducted among 85 maintenance workers at the Maintenance and Essential Services Organization (MESO) of Kwame Nkrumah University of Science and Technology (KNUST), Ghana, recruited through stratified convenience sampling across seven occupational sections. A structured questionnaire assessed knowledge of ocular hazards and protective equipment, attitudes toward ocular safety, and safety practices. Data were analyzed using IBM SPSS version 26 (IBM Corp., Armonk, NY, USA); chi-square and Fishers exact tests assessed associations (p < 0.05). Participants were predominantly male (84/85, 98.8%), with a mean age of 44.5 {+/-} 10.4 years. Overall knowledge was good (mean 9.40 {+/-} 1.59 out of 11), but attitude and practice scores were average (2.78 {+/-} 0.92 and 3.27 {+/-} 0.93, respectively). Most workers correctly identified goggles and face shields as protective, but only about half recognized that ordinary sunglasses and spectacles offer inadequate protection. Although 97.6% (83/85) recognized the need for ocular protection, only 7.1% (6/85) reported consistent protective eyewear use, and fewer than half (45.9%, 39/85) had received formal ocular safety training. Routine general protective equipment use was significantly associated with ocular protection use (Fishers exact test, p = 0.011). Sand and dust particles were the leading causes of injury and only 25% (5/20) of injured workers sought formal care. Workers demonstrated good knowledge but poor attitudes and practices toward ocular safety, suggesting that knowledge alone does not translate into protective behaviour even within a relatively well-resourced institutional setting. Findings suggest that limited access to task-appropriate protective eyewear may represent an important institutional barrier. Institutional PPE supply and section-specific safety training are essential to bridge this knowledge-practice gap.

Climate and land use change are reshaping the dynamics of vector-borne diseases. West Nile virus (WNV), the most widespread zoonotic arbovirus in the United States, illustrates the need to integrate climate, land cover, and social vulnerability across heterogenous landscapes when assessing spatial risk. We present a nationwide, county-level assessment of WNV risk, using complementary statistical and mechanistic models to (1) identify socio-ecological correlates of current WNV incidence, and (2) project vector species-specific, temperature-dependent transmission suitability under mid- and late-century climate change scenarios. We find that land cover gradients, temperature-driven transmission, and both occupational and residential exposure are associated with WNV incidence, particularly in mixed urban-agricultural landscapes. Future temperature and land cover projections suggest spatially variable shifts in environmental risk, driven by divergent physiological responses among Culex species vectors. Our results highlight temperature and land cover as consistent, mechanistically grounded correlates of WNV risk at the national scale, while underscoring the need for refined, species-specific analyses at local levels. These insights can inform more targeted surveillance, vector control, and climate adaptation strategies. We also identify key knowledge gaps, particularly around host and vector ecology, that must be addressed to improve public health response in the face of ongoing environmental change.

Mass gatherings pose significant public health risks by facilitating the spread of infectious diseases. While wastewater-based surveillance (WBS) has been widely used to monitor pathogens in high-income settings, its use as a practical, multi-pathogen surveillance tool during mass gatherings in low- and middle-income countries remains limited. This study aimed to assess the operational feasibility, epidemiological significance, and public health utility of multi-pathogen WBS during the African Nations Championship (CHAN) football tournament in Uganda. Wastewater surveillance was conducted at Mandela National Stadium during eight match days in August 2025. Moore swabs were deployed at 38 manholes receiving wastewater from different toilet facilities across the stadium to capture representative wastewater samples. Samples were processed using Nanotrap(R) microbiome virus particles to concentrate pathogens, followed by nucleic acid extraction. Samples were analyzed for multiple enteric and respiratory pathogens, including Mpox, using quantitative PCR (qPCR). Descriptive analyses were performed to characterize pathogen detection patterns, positivity rates, and temporal distribution across surveillance sites. A total of 304 wastewater samples were collected and analyzed, of which 259 (85.2%) tested positive for at least one pathogen. Multiple pathogens were consistently detected across sampling days, with enteric pathogens predominating, particularly Shigella spp. (53.6%), Rotavirus A (35.9%) and Enterovirus (32.2%). The mpox virus was also detected in a notable proportion of samples (28.6%) across several sampling days. Respiratory pathogens, including SARS-CoV-2 (11.8%) and Influenza B (8.2%), were identified intermittently at lower frequencies. Pathogen diversity varied over time, with up to eight pathogens detected on a single day, and co-detection of multiple pathogens observed in the majority of positive samples. Cq value distributions further demonstrated variability in detected signal patterns across pathogens. Surveillance findings informed real-time public health interventions, including sanitation reinforcement, intensified hygiene promotion, environmental disinfection, and targeted risk communication, strengthened syndromic surveillance with on-site triage, and targeted environmental health assessments of food handling and wastewater infrastructure. These findings demonstrate the operational feasibility and public health utility of integrating multi-pathogen wastewater-based surveillance into mass-gathering preparedness and response frameworks in low-resource settings. By capturing diverse pathogen signals and informing targeted interventions during the CHAN football tournament, WBS can provide actionable population-level insights that can support outbreak preparedness and response. Scaling WBS within national preparedness systems could strengthen epidemic intelligence, enhance early warning capacity, and support data-driven public health decision-making during future mass gatherings and emerging infectious disease threats.

Objectives: Capturing adequate blood volume for blood cultures is critical for accurate detection of bloodstream infections. Pediatric volume targets vary by age and weight, whereas adult targets are standardized. The BD BACTEC FXI Culture System (FXI) contains an integrated calibrated load cell capable of automatically reporting blood volume measurements for each vial loaded onto the system. This study evaluated the accuracy of the FXI's blood volume measurements in simulated pediatric and adult patients. Methods: Mock pediatric and adult blood draws were performed, using bagged whole blood, to replicate real-world collection protocols. Syringe-collected blood volumes ranged from 2.0 to 15.0 mL for pediatric patients, depending on mock patient weight, and were fixed at 40.0 mL for adults. Samples were inoculated into BD BACTEC Peds Plus/F, Plus Aerobic/F, and Lytic/10 Anaerobic/F Culture Vials, with a target volume of 2.0 to 10.0 mL per bottle. Reference blood volumes were determined gravimetrically using manually obtained pre- and post-inoculation weights with a blood-specific gravity of 1.055 g/mL and were compared to the automatically measured, gravimetric-based blood volumes reported by the BACTEC FXI Culture System. Results: Automated volume estimates were accurate to a mean error of -0.03 mL per bottle (SD, 0.40 mL; n=168; 95% CI, -0.09 mL, 0.03 mL) and -0.08 mL (SD, 0.79 mL; n=72; 95% CI, -0.26 mL, 0.10 mL) when assessing total volume collected per patient. Conclusions: Our findings demonstrate that the automated system can quantify blood volumes in BACTEC culture vials and support blood volume monitoring for pediatric and adult collections. The gravimetric approach is also amenable to full automation for efficient and accurate blood volume determination.

Antimicrobial resistance is a public health challenge, driving the need for rapid, cost-effective diagnostic support tools. Artificial intelligence (AI) may enable prediction of susceptibility to untested antibiotics from known susceptibility results, but prospective clinical validation is required before routine use. We evaluated an AI-based decision support method, trained on invasive isolates from the European Surveillance System (TESSy), for prediction of antibiotic susceptibility in clinical Escherichia coli urine isolates. The evaluation included 99 E. coli isolates from urine samples with diversity in age, sex, and antibiotic susceptibility. Predictions were evaluated for 14 antibiotics using patient metadata and susceptibility results for 4-8 antibiotics as input. Prediction uncertainty was handled using conformal prediction, allowing abstention when confidence was insufficient. EUCAST disk diffusion test results were used as reference and genomic sequence data was used to explore mechanisms of the AI performance. Without conformal prediction, 84% of predictions were correct when susceptibility results of six antibiotics were used to predict susceptibility to eight additional antibiotics. Across all predictions generated using susceptibility results for six antibiotics as input, the major and very major error rates were 19% and 12%, respectively. Prediction errors varied between antibiotics and were associated with certain phenotypic and genotypic resistance patterns. Conformal prediction reduced errors but increased abstentions; at confidence levels of 90%, 95%, and 97.5%, the model abstained in 9.6%, 14%, and 22% of instances. The method showed promising performance, but its clinical use remains limited and may require diagnostic data beyond susceptibility test results and demographic variables.

Background: Children spend more than 90% of their time indoors, and early childhood education settings (ECEs) are an understudied, high-occupant-density indoor microenvironment where exposure to volatile organic compounds, particulate matter, and other toxicants has been documented. Limited knowledge exists on ECE-specific exposures affecting young children and how they compare to exposures in the home. Methods: This prospective, repeated-measures pilot study targeted enrollment of 44 preschool-aged children and 8 ECE staff across two geographically and sociodemographically distinct ECEs in metropolitan Atlanta, Georgia. Paired silicone wristbands, one home-designated and one ECE-designated, were exchanged between settings across three consecutive days and nights beginning at enrollment to characterize microenvironment-specific exposure. A single spot urine sample was also collected from each child. Continuous indoor air quality monitoring was conducted in two classrooms per site. Caregivers and ECE staff completed structured questionnaires assessing home and ECE environmental characteristics, child respiratory risk, and protocol feasibility and acceptability. Feasibility was evaluated using eight pre-specified indicators spanning recruitment and enrollment, wristband wear duration and loss by microenvironment, urine sample collection completeness, and survey completion by instrument and respondent group. Conclusion: This pilot will establish feasibility and acceptability parameters for a paired, multi-matrix silicone wristband protocol across home and ECE microenvironments. Findings will inform the design, sample size, and power calculations for a subsequent study testing indoor air interventions and pediatric respiratory outcomes in ECEs. Feasibility outcomes are reported in a companion manuscript.

Abstract Introduction. Culture data guide orthopedic-infection management, yet the organism spectrum, resistance, and no-growth fraction are reported inconsistently and mostly within proprietary registries. We characterized these in a public, reproducible dataset. Methods. Retrospective cross-sectional study using MIMIC-IV version 3.1, a de-identified single-center US database. Episodes with an International Classification of Diseases diagnosis of prosthetic joint infection (PJI) or native osteomyelitis were identified; organism-spectrum and no-growth analyses were restricted to the 46% with at least one deep musculoskeletal culture (tissue or bone, synovial or joint fluid, implant sonication), so the benchmark describes culture-sampled, not all, coded episodes. Proportions carry exact 95% CIs; variation was tested by logistic regression with Benjamini-Hochberg control, and an out-of-fold logistic model quantified how well no-growth was anticipated by structured data. Results. Of 7697 episodes (median age, 60 years; 35.5% female), 1089 were PJI, 5715 native osteomyelitis, and 893 other device infection. Among 7700 deep specimens (3560 episodes; 2603 patients), 35.7% showed no growth (patient-clustered 95% CI, 34.0%-37.3%). The fraction was higher in PJI than osteomyelitis (48.6% vs 26.6%) but rose with sampling intensity (24.5% to 50.7%), indicating differential ascertainment. S. aureus led (32.5%; 43.3% methicillin-resistant), and PJI was less often polymicrobial than osteomyelitis (adjusted OR, 0.44). No-growth was weakly anticipated by structured data (out-of-fold AUROC, 0.63). Conclusions. About one-third of deep specimens from code-defined orthopedic infection showed no growth. This specimen-level fraction differs from a criterion-confirmed culture-negative-infection rate and depends on sampling intensity; it is released as a re-runnable benchmark on identical open data, not a transferable rate.

Background. Direct livestock exposure is a risk factor for zoonotic influenza, including H5N1 highly pathogenic avian influenza (HPAI) A virus. But whether living in regions of high poultry and swine production intensity (PPI, SPI) increases risk of exposure to zoonotic influenza viruses independent of occupational livestock contact remains unclear. Objectives. To determine whether livestock workers and community members with no occupational livestock exposure in North Carolina, where poultry and swine production are increasingly co-located, are at higher risk of exposure to zoonotic influenza. Methods. Saliva samples from industrial livestock operation worker (ILO-W), ILO neighbor (ILO-N) and metropolitan area (Metro) households were analyzed for mucosal influenza A (H5N1, H1N1, and H3N2) hemagglutinin (HA) IgA and IgG antibodies to determine associations of PPI, SPI, exposure group, and detection of a swine-specific fecal contamination marker (Pig-2-Bac DNA) with influenza A antibody levels. Results. Residing in the highest PPI and SPI tertile was associated with significantly higher mucosal H5 and H1 HA IgA levels, including among residents without occupational livestock exposure. Households with occupational poultry or swine contact had significantly higher H5 IgA and IgG and H1 IgA levels compared to Metro households. In regression models accounting for clustering at the participant level, log10 anti-H5 HA mucosal IgA increased 0.16 (95% CI: 0.06, 0.27, p<0.005) and 0.10 (95% CI: 0.03, 0.17, p<0.005), per log10 increase in PPI and SPI, respectively, and 0.16 (95% CI: 0.03, 0.19, p<0.02) when Pig-2-Bac DNA was detected on household surfaces. Conclusions. Mucosal H5 HA IgA and IgG and H1 HA IgA were consistently elevated across different metrics of livestock exposure intensity, including residential exposure, occupational contact within a household, and a molecular marker of household swine fecal contamination in a state with intensive poultry and swine production.