JAC-Antimicrobial Resistance

Background and objectives Spontaneous bacterial peritonitis (SBP) is a life-threatening complication of cirrhosis with ascites, carrying one- and two-year mortality rates exceeding 70% and 80%, respectively. Fluoroquinolone prophylaxis is the cornerstone of SBP prevention. Real-world longitudinal data on prescribing practices and clinical outcomes from Indian tertiary care centers are sparse. We aimed to evaluate fluoroquinolone prescribing patterns, guideline adherence, and six-month clinical outcomes in SBP patients at a tertiary academic center in North India. Methods This was a pre-specified sub-analysis of a 15-month analytical longitudinal study at AIIMS Rishikesh. Adults (age >/=18 years) admitted with SBP and initiated on fluoroquinolone prophylaxis were enrolled consecutively and followed for six months. Prescribing practices were compared against EASL and AASLD recommendations. The primary outcome was the rate of guideline-directed prescribing. Secondary outcomes included clinical cure at discharge, six-month cure, relapse, regimen modification, adverse drug reactions, and treatment compliance. Categorical variables were compared by Fisher's exact test or chi-squared test (SPSS). Results Forty-eight SBP patients were included (mean age 44.75 +/- 11.94 years; 85.4% male). Guideline-directed fluoroquinolone prophylaxis was prescribed to all patients (100%). Norfloxacin 400 mg once daily was predominant (85.4%), followed by levofloxacin (10.4%) and moxifloxacin (4.2%). Cure at discharge was 85.4%. At six months, 64.6% maintained sustained cure and 22.9% relapsed. Regimen modification occurred in 22.9%, most commonly antimicrobial substitution. Nausea was the only adverse drug reaction (4.8%). Treatment compliance was 73.8%. No patient underwent therapeutic drug monitoring. Conclusions Fluoroquinolone prescribing for SBP prophylaxis at AIIMS Rishikesh was fully concordant with standard guidelines. Despite complete adherence, a relapse rate of 22.9% and frequent regimen modification underscore the limitations of long-term fluoroquinolone prophylaxis, likely reflecting emerging quinolone resistance. Strengthening antimicrobial stewardship is essential to sustain prophylaxis effectiveness in Indian tertiary care settings.

Background: Antimicrobial resistance (AMR) disproportionately affects low- and middle-income countries (LMICs) such as Pakistan, where obstetric and gynaecological (OBGYN) patients carry high antibiotic exposure. Specialty-specific drug utilization data with concurrent stewardship audit remain scarce. This study evaluated antibiotic prescribing patterns, consumption metrics, and antimicrobial stewardship program (AMS) compliance in OBGYN inpatients at a public sector tertiary care hospital. Methods: A prospective cross-sectional study was conducted in OBGYN wards of Dow University Hospital, Karachi, from 1 September to 31 October 2025. Women receiving [≥]1 systemic antibiotic were included. Daily AMS rounds were conducted by an Infectious Diseases physician and pharmacist. Antibiotic consumption was measured as Defined Daily Doses (DDD) and Days of Therapy (DOT) per 1,000 patient-days (total = 821). Antibiotics were classified by WHO AWaRe (2023) framework. Results: Of 812 total admissions, 278 patients (34.2%) received [≥]1 antibiotic and were enrolled (205 obstetric, 73 gynaecological), generating 636 prescriptions (mean 2.29/patient). Surgical prophylaxis was the predominant documented indication (213, 33.5%); 65.1% carried no documented indication. By AWaRe classification, 53.6% were Access-group and 46.1% Watch-group. Ceftriaxone (38.4%) and metronidazole (36.8%) together represented 75.2% of prescriptions. Combined DDD/1,000 patient-days was 1,758.6 and DOT/1,000 patient-days was 1,852.7. AMS compliance was 0%. Conclusions: This study documents high antibiotic prescribing burden, near-universal documentation failure, and zero AMS compliance in OBGYN inpatients at a Pakistani public sector hospital. The predominance of Watch-group antibiotics and undocumented surgical prophylaxis highlights structural stewardship gaps. Findings support urgent need for institutional OBGYN antibiotic guidelines and structured pharmacist-led AMS programs.

Background and Aims The optimal treatment for first episodes and first recurrences of Clostridioides difficile infections (CDI) is unknown and there is emerging evidence for pulse and taper (P-T) regimens. Therefore, we sought to estimate the relative efficacy of treatment options. Methods MEDLINE and CENTRAL were searched from database inception to May 21, 2025 and unpublished conference abstracts were searched from recent infectious disease conferences. RCTs on the treatment of first episodes or first recurrences of CDI comparing fixed-dose or P-T regimens of fidaxomicin or vancomycin were included. The primary and secondary outcomes were 40- and 56-day CDI recurrence, respectively. A random-effects network meta-analysis on the risk ratio (RR) scale was conducted using a standard regimen (10-14 days) of vancomycin as the comparator. Treatments were ranked using the surface under the cumulative ranking curve (SUCRA). Results 8 RCTs were included comprising a total of 2181 patients. For 40-day recurrence, fidaxomicin P-T had the highest probability of ranking best (RR=0.10, 95%Confidence Interval [95%CI]=0.10-0.49, SUCRA=1.00), followed by vancomycin P-T (RR=0.49, 95%CI=0.32-0.76, SUCRA=0.61), fixed-dose fidaxomicin (RR=0.61, 95%CI=0.49-0.76, SUCRA=0.39), and, finally, fixed-dose of vancomycin (SUCRA=0.00). The treatments ranked in the same order for 56-day recurrence, though only 3 RCTs reported on this timepoint. Conclusion Vancomycin P-T, fidaxomicin P-T, and fixed-dose fidaxomicin were all superior to a fixed-dose vancomycin. Head-to-head comparative effectiveness RCTs are needed to quantify their relative effect sizes of and impact on long-term prevention of recurrent CDI.

Background: Bacteraemia is associated with poor outcomes but the diagnostic gold standard, peripheral blood culture, takes up to 24 hours to become clinically actionable, hampering early management decisions in suspected infection. Single predictors and existing sepsis risk scores discriminate poorly, and few multivariable bacteraemia models have been adequately validated in UK populations. Methods: We developed a logistic regression model, using backwards AIC based selection of predefined candidate predictors routinely available within hours of hospital attendance, in a retrospective cohort of 33,874 hospital encounters at University College London Hospitals (UCLH) between 2019 and 2024. Continuous predictors were modelled using restricted cubic splines and missing data handled using multiple imputation. Model performance was assessed via internal external cross validation and prediction instability analysis, before temporal validation in held-out 2024 UCLH data and external validation in 53,669 hospital encounters from the Infections in Oxfordshire Research Database (IORD). Results: Bacteraemia occurred in 5.2% of UCLH and 8.9% of IORD encounters, respectively. Twenty predictors were retained, spanning demographics, comorbidities, vital signs and blood tests. Discrimination was stable across development time periods (pooled c-statistic 0.82, 95%CI 0.81 to 0.84) and was maintained in temporal (0.83, 0.79 to 0.87) and external validation (0.83, 0.82 to 0.83), with excellent calibration in external validation (calibration slope 1.08 (1.05 to 1.11); calibration-in-the-large 0.01 (-0.02 to 0.04)). The model outperformed single predictors, established risk scores, and a reconstructed comparator model, and showed superior net benefit in decision curve analysis. Performance was consistent across age, sex, ethnicity and socioeconomic subgroups but degraded when blood cultures were sampled more than six hours after attendance and varied by likely infection site. Conclusions: This model accurately predicts bacteraemia using routinely collected data available within hours of hospital attendance, with performance maintained in a large, independent external validation cohort. It offers a generalisable, clinically interpretable tool to support early decision-making in suspected infection, pending further work to establish optimal implementation thresholds.

Background Bloodstream infections are a major cause of mortality, yet the primary testing method, blood cultures, have low positivity (<10%) and turnaround times of 24 - 48 hours. Many are taken from patients at low risk of infection, while some bloodstream infections are diagnosed late or missed entirely. We aimed to develop and externally validate machine learning models to improve targeting of blood culture testing. Methods In this retrospective cohort study, we used routinely collected clinical and laboratory data available around culture collection from a large multi-site NHS trust (Oxford University Hospitals; Infections in Oxfordshire Research Database), between 1 January 2016 and 17 March 2025. All blood cultures taken from adults and children were included. XGBoost models were trained to predict pathogenic blood culture positivity using a temporal split (training before 1 January 2024; held-out test thereafter). External validation used emergency department data (between 1st May 2019 and 30th April 2024) from University College London Hospitals. An additional analysis examined blood culture reallocation towards the highest-risk untested admissions. Findings 294,064 cultures were included (positivity 5.6%). In the temporal hold-out test set (n=46,339), AUROC (Area Under the Receiver Operating Characteristic) was 0.853 (95% CI 0.846 - 0.860), rising to 0.876 in emergency department patients, and the model was well calibrated (slope 1.046). In external validation (n=37,326), AUROC was 0.847 (95% CI 0.839 - 0.856) with preserved calibration. In a simulated resource-neutral reallocation, replacing the 10,000 lowest-risk sent cultures with the highest-risk untested emergency admissions yielded 627 additional positive cultures (28.3% relative increase in yield). Performance was reduced when restricted to data available at the point of culture collection (AUROC 0.769, 95% CI 0.760 - 0.779). Interpretation An externally validated, well calibrated machine learning model built from broadly available, routinely collected data could improve blood culture yield without increasing testing volume, supporting resource-neutral diagnostic stewardship across NHS sites.

BACKGROUND: Half of positive blood cultures in pediatric emergency departments (PEDs) represent contaminants, driving unnecessary hospitalization, antibiotic exposure, and repeat visits. A clinical decision rule derived at CHU Sainte-Justine showed 99% sensitivity and 60% specificity for distinguishing bacteremia from contaminants but had not been externally validated. We sought to validate this rule in an independent pediatric cohort. METHODS: This retrospective diagnostic study spanned from January 2015 to May 2025 at a tertiary PED in Switzerland, using positive blood cultures from patients younger than 16 years. The four predictors (Gram-negative organisms or Gram-positive cocci in pairs or chains; time to positivity <17 hours; indwelling device; suspected osteoarticular infection) classified each case as low, moderate, or high risk. The primary outcome was bacteremia, adjudicated by two independent reviewers, based on organism identity and infectious disease specialist's assessment. Diagnostic accuracy was assessed with 95% CIs. RESULTS: Of 130 children enrolled (median age 3.8 years [IQR 0.9-9.9]; 61.5% male), 78 (60.0%) had true bacteremia. The rule yielded a sensitivity of 97.4% (95% CI, 91.0-99.7), specificity of 69.2% (95% CI, 54.9-81.3), positive predictive value of 82.6% (95% CI, 73.3-89.7), and negative predictive value of 94.7% (95% CI, 82.3-99.4). Both false-negatives were immunocompetent children with methicillin-susceptible Staphylococcus aureus bacteremia without indwelling devices. Among contaminants, 71% received antibiotics under usual care versus 31% classified as moderate or high risk by the rule. CONCLUSIONS: This first external validation supports the Sainte-Justine rule in a distinct pediatric population, preserving sensitivity with higher specificity. Multicenter validation is warranted before adoption.

Background: Urinary tract infection (UTI) is the most common secondary condition among people with spinal cord injury/disease (SCI/D). Intravesical Lacticaseibacillus rhamnosus GG (LGG) is an antibiotic-sparing approach to managing urinary symptoms. Objective: Determine the optimal number of doses of intravesical LGG for urinary symptom reduction. Design: Prospective, randomized, two-arm dosing trial. Setting: National recruitment with a local subsample providing urine samples in Washington, DC, USA. Participants: Adults with SCI/D and neurogenic lower urinary tract dysfunction (NLUTD) who use intermittent catheterization (IC); 177 enrolled and randomized (intention-to-treat), with 76 compliant instillers (39 low-dose, 37 high-dose) in the per-protocol analytic sample. Interventions: Two (2 doses/24 hours) or four (4 doses/36 hours) intravesical LGG regimens, self-initiated in response to cloudier or malodorous urine per the Self-Management Protocol using Probiotics (SMP-Pro). Main Outcome Measures: Primary: proportion achieving [&ge;]20% reduction on the Urinary Symptom Questionnaire for Neurogenic Bladder-Intermittent Catheter version (USQNB-IC). Secondary: urinary biomarkers (leukocyte esterase, nitrite, white blood cells, urinary neutrophil gelatinase-associated lipocalin [uNGAL]) and standard urine culture (SUC) in a local subsample. Results: By Day 2, 57.9% (63.8% low-dose; 51.2% high-dose) achieved [&ge;]20% total symptom reduction; high-dose success rose to 70.0% by Day 4. Thirty percent of high-dose participants did not respond at either time point and could not be distinguished from responders by demographics or urine biomarkers. Urinary biomarkers and SUC were unchanged pre- to post-instillation. No serious adverse events were adjudicated as attributable to intravesical LGG by an independent Data Safety Monitoring Board (DSMB). Conclusions: A two-dose course of intravesical LGG yields clinically meaningful symptom improvement in the majority of people with SCI/D and NLUTD who use IC; four doses benefits a meaningful subgroup of two-day non-responders, while a small cohort remains nonresponsive. These results provide preliminary dosing guidance and support progression to a definitive trial.

Blood banks represent highly controlled healthcare environments where microbiological surveillance has traditionally focused on blood products rather than environmental microbial reservoirs. Despite their critical role in transfusion safety, the ecology of surface-associated microorganisms and the persistence traits that enable their long-term survival remain poorly understood. Here, we combined scanning electron microscopy, culture-based microbiology, phenotypic characterization, MALDI-TOF mass spectrometry, and whole-genome sequencing to investigate whether surfaces within a public blood bank facility constitute reservoirs of environmentally derived bacteria with enhanced persistence potential. Samples collected from a public blood bank in Tucuman, Argentina yielded 37 culturable bacterial isolates, predominantly Gram-positive environmental taxa together with a limited number of opportunistic Gram-negative species. More than 30% of the isolates exhibited multidrug resistance, while several strains displayed strong biofilm formation, amyloid-like fiber production, motility, and hemolytic activity, indicating multiple phenotypic strategies associated with long-term surface persistence. Whole-genome sequencing of six representative isolates confirmed species identity, identified genes related to antimicrobial resistance, adhesion, biofilm formation, stress adaptation, and cytotoxicity, and revealed frequent genotype-phenotype discordance, highlighting the importance of integrating genomic and phenotypic analyses. Notably, one isolate exhibited less than 92% average nucleotide identity with publicly available genomes, suggesting the presence of a previously undescribed environmental species. Thus, blood bank surfaces function as selective ecological niches favoring bacteria with persistence-associated traits rather than simply reflecting contamination from blood products. These microorganisms may constitute latent biosafety hazards if environmental barriers fail, particularly in facilities handling biological materials intended for vulnerable patients. Our results support the incorporation of integrated bioimaging, phenotypic characterization, and genome-resolved environmental surveillance into infection prevention strategies and transfusion biosafety programs within a One Health framework.

Background Coccidioidomycosis is an emerging fungal disease across the arid Americas and a frequent cause of community-acquired pneumonia. Understanding where Coccidioides populations originate, how they move across space, and whether they are expanding is important for interpreting changing patterns of Valley fever and anticipating future infection risk. Methods We prospectively collected and whole-genome sequenced 186 Coccidioides-positive clinical isolates submitted to a national diagnostic laboratory, and included 126 previously sequenced genomes. We applied genomic clustering, time-calibrated phylogenetic reconstruction, ancestral area reconstruction, mating-type assignment, and demographic inference to identify major populations, infer dispersal patterns, assess evidence for recombination and clonality, and reconstruct historical population dynamics. Findings We analyzed 312 genomes (139 C. immitis; 173 C. posadasii) and identified three major genetic populations within each species. C. immitis included two California-centered populations and one Pacific Northwest population, whereas C. posadasii included two Arizona-centered populations and one Texas-centered population. The most recent common ancestor was estimated at approximately 127,000 years for C. immitis and 234,000 years for C. posadasii. Most populations were not fully monophyletic, consistent with retained ancestral variation and/or ongoing gene flow. Inferred dispersal was largely asymmetric, with most movement originating from California in C. immitis and from Arizona and Texas in C. posadasii. Most populations contained both mating types, but one C. immitis population and a Brazilian subgroup of C. posadasii were clonal. All populations showed recent demographic expansion. Interpretation The evolutionary history of Coccidioides is characterized by strong geographic structure, ongoing gene flow, and recent demographic expansion. These processes are likely to influence future patterns of Valley fever endemicity and supports the use of genomic surveillance to detect shifts in disease risk as environmental conditions change.

Background: Travellers visiting friends and relatives (VFRs) experience a disproportionate burden of travel-associated infectious diseases, yet little is known about the complexity of pre-travel consultations required to support their care. We compared enquiries relating to VFR travellers and tourists received by the UK National Travel Health Network and Centre (NaTHNaC) specialist Advice Line to identify differences in traveller characteristics, destinations and clinical complexity. Methods: We conducted a retrospective observational study of enquiries to the NaTHNaC Advice Line between 1 January 2019 and 31 December 2025. Enquiries relating to VFR travellers and tourists were compared using descriptive statistics and appropriate statistical tests. Traveller demographics, travel characteristics, destinations and enquiry management were analysed. Results: Of 16,367 enquiries relating to specific travellers, 3,090 (18.9%) concerned VFR travellers and 7,237 (44.2%) concerned tourists. Compared with tourists, VFR travellers were younger (median age 24 vs 52 years, P<0.001), more likely to undertake long-stay (8.4% vs 1.8%, P<0.001) and last-minute travel (5.0% vs 1.1%, P<0.001), and more frequently travelled to the WHO African Region (56.6% vs 29.2%, P<0.001) and Eastern Mediterranean Region (12.7% vs 2.8%, P<0.001). Pregnancy was substantially more common among VFR travellers (11.6% vs 4.3%, P<0.001). Enquiries concerning VFR travellers were more likely to require a call-back (16.1% vs 13.8%, P=0.012) and escalation to a specialist doctor (13.1% vs 10.5%, P<0.001), indicating greater consultation complexity. General practice generated a higher proportion of VFR-related enquiries than tourist enquiries (69.5% vs 63.9%, P<0.001). Conclusions: VFR travellers generate disproportionately complex pre-travel consultations characterised by higher rates of specialist escalation, distinct travel patterns and travel to destinations associated with the greatest burden of imported infectious diseases. These findings highlight the importance of specialist travel medicine support for healthcare professionals managing VFR travellers and reinforce the need for equitable access to timely, high-quality pre-travel healthcare for this high-risk population.

Introduction: Uganda has the highest number of Malaria cases in East and Southern Africa and accounted for 3% of deaths in 2020. This calls for prevention, early diagnosis and treatment of Malaria most especially among children whose condition can progress to severe Malaria within 24 hours. While numerous interventions have been put into place to prevent malaria transmission, delays in diagnosis and treatment of Malaria when ill can lead to further mortality. Therefore, factors associated with delayed access of care among children under five with malaria and their outcomes need to be explored. Methods: A cross sectional study was carried out. The target population was parents/caretakers to children under five with malaria at Mbale Regional Referral Hospital. A consecutive sampling technique was used on the target population. Quantitative data was collected using researcher administered questionnaires designed consistent with the research objectives. Collected data was analyzed using STATA version 15. Results: Among the 216 children under five admitted at Mbale regional referral hospital with Malaria, 59.26% received care from a health facility 24 hours after symptom onset. The most significant predictors of delay in seeking care were the caregiver/ parent having attained tertiary education (AOR=7.1, p value=0.02) and initially implementing other measures other than giving medication/herbs before taking a child to the health center (AOR=4.1, p value=0.00). Conclusion: Despite the numerous interventions put into place to curb the spread of malaria and to manage malaria, delayed access of care remains a significant contributor to the adverse effects of malaria among children under five. Health education on the impact of delayed access of care should be intensified at all levels of healthcare.

Background: Neonatal meningitis and pneumonia are important causes of morbidity and mortality among hospitalized newborns in low-resource settings. Numerous single-centre studies have been conducted in Ethiopian public hospitals, yet no quantitative synthesis of neonatal meningitis prevalence previously existed, and the depth of the pneumonia-specific evidence base was undocumented. This review aimed to estimate the pooled prevalence of neonatal meningitis, and to establish the state of the evidence base for neonatal pneumonia, among neonates treated at public hospitals in Ethiopia. Methods: A systematic search of PubMed/MEDLINE, PubMed Central, PLOS, BioMed Central, Frontiers, Taylor & Francis Online, and institutional repositories was conducted without date restriction. Cross-sectional and retrospective studies reporting a standalone prevalence of neonatal meningitis or neonatal pneumonia among neonates treated at Ethiopian public hospitals were eligible. Methodological quality was appraised using the JBI Critical Appraisal Checklist for prevalence studies. A random-effects meta-analysis pooled meningitis prevalence; heterogeneity was quantified with I2 and Cochran's Q. Results: Of 26 full-text articles assessed for eligibility, four studies (N = 3,522 neonates) met inclusion criteria for neonatal meningitis; none met inclusion criteria for a standalone neonatal pneumonia prevalence outcome. The pooled prevalence of neonatal meningitis was 6.26% (95% CI: 2.81-13.35%; I2 = 96.6%), with individual study estimates ranging from 1.73% to 19.30%. A sensitivity analysis restricted to the three studies using a "suspected-meningitis" denominator yielded a pooled prevalence of 4.23% (95% CI: 1.92-9.05%). No eligible primary study reported neonatal pneumonia prevalence as a standalone, separately ascertained outcome across the accessible literature, pneumonia is consistently subsumed within composite "neonatal sepsis" case definitions. Conclusion: An estimated 1 in 16 to 1 in 24 neonates tested for suspected meningitis at Ethiopian public hospitals had a culture-confirmed or clinically diagnosed case, with wide variation across settings and case-ascertainment methods. A previously undocumented evidence gap exists for standalone neonatal pneumonia prevalence in Ethiopia. Future primary studies should report pneumonia as a distinct, separately ascertained neonatal outcome to enable future quantitative synthesis.

Scaling HIV pre-exposure prophylaxis (PrEP) services in health systems will require collaboration and clear role distinction among professionals, and between specialist and primary care. This study examined how power dynamics shape efforts to expand PrEP care beyond specialised HIV clinics in Belgium. We conducted semi-structured interviews with 36 HIV clinic providers and two community-based organisation (CBO) representatives, and 16 online group discussions with general practitioners (GPs). We analysed data thematically, guided by the concepts of collaborative and competitive power to examine how providers negotiated expertise and role division in PrEP delivery across professional and organisational boundaries. We found that reimbursement regulations anchored PrEP initiation and follow-up within HIV clinics, embedding specialist jurisdiction in care pathways. HIV specialists reinforced this position by drawing on their recognised expertise in HIV medicine to justify clinical coordination and authority in determining standards of care. GPs emphasised accessibility and preventive care roles but made limited claims to PrEP provision, linked to misaligned organisational incentives, role blurring, limited training opportunities, and the historical concentration of HIV care in specialist services. CBOs facilitated access, enabling coordination between vulnerable communities and clinics while remaining weakly embedded in formal care structures. Findings show that expanding integrated PrEP services beyond specialised care is not only shaped by operational issues such as training and resources but also by the structural dynamics of regulations, institutional mandates, and professional jurisdictions that influence collaboration. Effective scale-up will require policies that align incentives, clarify responsibilities, and support collaboration across specialised, primary care, and community settings.

BACKGROUND: Artificial intelligence (AI) medical scribes rely on speech-to-text (STT) models for transcription. Evaluations of STT models in non-English settings remain scarce. We benchmarked ten STT models on medical consultations from Latin American (LatAm) Spanish and assessed whether fine-tuning improves transcription accuracy. METHODS: Ten YouTube videos depicting medical consultations. Human transcriptions were the ground truth. Five open-source models were evaluated: Whisper Large, Whisper Large v3, Whisper Large v3 Turbo, Voxtral Mini 3B, and Canary 1B v2; and so were five close-source models: gpt-4o-transcribe, gpt-4o-mini-transcribe, gemini-2.5-pro, Eleven Labs, and Assembly AI. Whisper Large v3 was fine-tuned. One video was withheld from training. Performance assessed using Word Error Rate (WER), Character Error Rate (CER), BLEU Score, ROUGE-L, BERT Score, and Semantic Similarity on the one withheld video. RESULTS: None of the fine-tuning iterations outperformed the vanilla Whisper Large v3. With the withheld video, Gemini-2.5-pro was the close-source model with the best performance in four of six metrics. In comparison to the close-source models, the fine-tuned model never outperformed the other models (withheld video); conversely, in comparison to the close-source models, the fine-tuned model showed better performance across metrics, for instance: BLEU score (63% vs to 58% for the second-ranking model), BERT (89% vs to 86%), and semantic similarity (89% vs to 83%), CER (19% vs 20%). CONCLUSIONS: Whisper Large v3 and its fine-tuned variant are the best open-source STT models for transcribing medical conversations in LatAm Spanish. These findings provide an evidence base for developing AI medical scribes tailored to Spanish-speaking LatAm.

Controlled human infection models (CHIMs) are increasingly used in infectious disease research to study pathogen dynamics and evaluate interventions under controlled conditions. However, these studies are resource-intensive and involve ethical and safety constraints, making efficient study design critical. Dose-finding is a key early component in CHIMs, where the aim is to identify a challenge dose that achieves a target infection probability. Traditional rule-based designs are commonly used but can be inefficient, motivating the use of model-based adaptive approaches such as the Bayesian Continual Reassessment Method (CRM). Although CRM has been extensively studied and widely adopted in Phase I oncology trials for identifying the maximum tolerated dose of therapeutics, its application in CHIM settings remains limited, particularly when the endpoint of interest is infection. This tutorial provides step-by-step guidance for implementing a Bayesian CRM in dose-finding CHIMs, using an oropharyngeal Neisseria gonorrhoeae challenge as a motivating case study. The framework outlines key design components, including dose-grid specification, dose-response model, prior elicitation, Bayesian updating, decision rules, and stopping criteria, with particular emphasis on a clinically interpretable parameterisation. Trial operating characteristics are evaluated through simulation studies under multiple dose-response scenarios and prior-predictive analyses, and compared with a commonly used '3+3' type rule-based design. This work highlights the advantages of Bayesian model-based designs for dose-finding in CHIMs over classic rule-based designs and provides a structured, reproducible framework for implementing CRM, supporting their application in future CHIM studies.

Background Hypertension is a major modifiable risk factor for atrial fibrillation (AF), yet blood pressure (BP) control remains suboptimal in older U.S. adults. Objectives This study evaluated how improve systolic BP (SBP) control could affect incident AF, downstream AF ablation demand, Medicare savings, and hospital revenue. Methods A population-based modelling framework was developed to estimate mortality and incident AF hazards across SBP strata: <120, 120-139, 140-159, and ?160 mm/Hg. AF incidence in the SBP <120 mmHg group was set at 2.2 per 1,000 person-year, with hazard ratios of 1.17, 1.42 and 1.64 applied to higher SBP strata. We assumed 25% of incident AF patients would undergo ablation, with a 7.2% complication rate. AF prevalence was projected to increase by 4.6% annually over 10 years. Medicare savings and hospital revenue foregone were estimated under varying procedure cost and contribution-margin assumptions. Results Higher SBP was associated with greater hazards of death and incident AF. Improved SBP control reduced projected AF incidence and ablation demand. Over 10 years, cumulative Medicare savings were projected at $8.7B-$10.9B across the full modelled population. However, reduced ablation volume translated into hospital revenue foregone, ranging from $75M to $377M in the first year, and approximately $1.03B-$5.2B cumulatively over 10 years. Conclusions Improved SBP control may reduce AF incidence, prevent avoidable invasive ablation procedures, relieve pressure on surgical waitlists, and generate substantial Medicare savings. However, these benefits may reduce hospital procedural revenue, highlighting a misalignment between prevention-oriented care and fee-for-service reimbursement incentives.

Histidine-rich protein 2 (HRP2)-based rapid diagnostic tests (RDTs) are central to malaria case management in Africa but fail when Plasmodium falciparum parasites lack the pfhrp2 or pfhrp3 genes. Widespread deletions have been reported in Eritrea, Ethiopia, and Djibouti, yet no systematic data have been available from Somalia. Between May and October 2023, we collected 7148 dried blood spot (DBS) samples from patients with suspected malaria attending eight health facilities across seven regions in Somalia. Field HRP2/pan-lactate dehydrogenase (LDH) RDTs and microscopy were performed, and DNA was extracted from 301 RDT-positive and 173 RDT-negative DBS samples. A multiplex quantitative PCR assay targeting pfldh, pfhrp2, and pfhrp3 was used to identify deletions in pfldh-positive samples lacking pfhrp2 or pfhrp3 amplification, with mixed infections inferred from delta cycle threshold ({Delta}Ct) differences. Of 474 analysed samples, 301 (4.2%, 95% CI 3.7-4.7) were RDT or microscopy positive, and 159 (33.5%) were confirmed pfldh-positive by qPCR. Among these, six (3.8%, 95% CI 1.4-8.1) carried pfhrp2 deletions and 59 (37.1%, 95% CI 29.6-45.1) carried pfhrp3 deletions. Eleven infections (6.9%, 95% CI 3.5-12.1) produced discordant RDT outcomes, HRP-/LDH+ or RDT-negative despite pfldh positivity. Deletions were most frequent in Dolow, Luq, and Bosaso. A single isolate carried the pfk13 R622I mutation, confirming the first report of the emergence of an artemisinin partial resistance-associated in Dolow, Gedo region, Somalia. Pfhrp2/3 deletions causing false RDT results remain low in Somalia and the confidence interval overlaps with the 5% policy threshold for changing RDTs, indicating uncertainty that warrants larger-scale assessment. Pfhrp3 deletions are widespread and compromise the diagnostic redundancy of HRP2-based tests. Most deletion-carrying parasites remain detectable through the pan-LDH line, minimising immediate clinical risk but leading to systematic misclassification of P. falciparum as non-falciparum malaria. These findings support the continued use of HRP2/Pan-LDH RDTs but highlight high risk areas and emphasise the need for periodic and expanded molecular surveillance for prevalence trends to guide timely future diagnostic policy.

Background Staphylococcus aureus bacteraemia (SAB) is clinically heterogeneous. Potential heterogeneous treatment effects (HTE) have recently been identified through analysis of patient subgroups, identified using routine clinical variables.However, the impact of misclassifying patients into these groups is unclear, and practical strategies to improve HTE detection remain uncertain. Methods We performed a simulation study using published data from selected randomised trials and observational studies in SAB. We assessed the impact of varying classification accuracy (70%-100%) on i) power, ii) type I error, and iii) bias in post-hoc analyses of HTE. We then evaluated two strategies to improve performance: enrichment designs, in which only patients predicted to belong to a target subgroup are randomised, and the use of ordinal rather than binary outcomes. Results Even with perfect classification, post-hoc detection of heterogeneous treatment effects remained highly conditional on subgroup prevalence, baseline mortality, and effect size. One subgroup was detectable at moderate sample sizes; however, power was inadequate for all other subgroups even with sample sizes of 20,000. Decreasing classification accuracy reduced power, increased type I error, and introduced bias. Enrichment marginally improved power. Ordinal outcomes substantially improved performance when they matched the treatment-effect structure, but were worse when they did not. Conclusions Detecting HTE in SAB is challenging, but not uniformly infeasible. Feasibility depends on the interaction between subgroup frequency, baseline risk, classifier performance, and outcome choice. To advance stratified medicine in SAB, research should prioritize robust classifiers, outcome measures matched to the expected mechanism and pattern of treatment effect, and trial designs that acknowledge uncertainty in subgroup prevalence and treatment-effect structure.

Objectives: To compare the effectiveness of povidone-iodine ear wash compared to no ear wash and oral cotrimoxazole compared to placebo given in addition to standard topical antibiotic treatment (ciprofloxacin drops) for chronic suppurative otitis media (CSOM) in Australian Aboriginal children. Methods: A randomised, parallel, 2 x 2 factorial design, assessor-blinded clinical trial in the remote Northern Territory of Australia. Aboriginal children with confirmed CSOM were eligible to be randomised into four treatment groups, allowing two primary treatment comparisons in a 2-in-1 trial approach. Participants received standard treatment (twice daily cleaning and topical ciprofloxacin drops) plus: i) either 16 weeks of pre-treatment povidone-iodine ear wash or no povidone-iodine ear wash; and ii) either 16 weeks of oral cotrimoxazole or placebo. Central randomisation with allocation concealment and triple-blinding of the oral antibiotic treatment arms was used. The relative risk (RR) and risk difference (RD) were estimated after adjustment for age, community, and the other intervention. The primary outcome was the proportion of children with any otorrhoea (clinical failure) after 16 weeks of treatment. Secondary outcomes included size of tympanic membrane (TM) perforation and amount of discharge, time to cessation of discharge, proportion of children with respiratory and other pathogens in ear discharge (at baseline and 16 weeks) and hearing levels (at 12 months). Findings: 280 children with CSOM were randomised and 270 had their primary outcome assessed. Clinical failure (presence of any ear discharge) after 16 weeks of treatment was 66/134 (49%) in the povidone-iodine group versus 69/136 (51%) in the no povidone-iodine group (RD= -1% (-12,11), p= 0.93) and 56/134 (42%) in the cotrimoxazole group versus 79/136 (58%) in the placebo group (RD=-16% (-28,-4), p=0.007). The amount of discharge, TM perforation size, the level of hearing impairment, and serious adverse events were not significantly different in both treatment comparisons. Anaerobic growth (24%), Pseudomonas aeruginosa (21%) and Haemophilus influenzae (17%) were the most common pathogens found in the ear discharge before treatment. Fungi or yeast (24%), Staphylococcus aureus (15%), and anaerobic growth (10%) were the common pathogens after 16 weeks of treatment, with no significant differences between groups. At 12 months post-randomisation, 55-60% of children had at least one discharging ear and there was no difference between treatment groups. Interpretation: Povidone-iodine ear washes did not contribute to better ear outcomes in this study. Cotrimoxazole for 16 weeks resulted in more children with clinical improvement to dry ears. Oral cotrimoxazole may play a role in reducing the burden of CSOM in populations with high rates of persistent disease.

Stochastic epidemic models are a cornerstone of infectious disease epidemiology and are often used to study intervention scenarios. However, large run-to-run variability can make intervention effects difficult to estimate precisely. We revisit the epidemic Sellke construction, which assigns each individual an infection threshold for the cumulative infection hazard such that, conditional on the thresholds, the epidemic trajectory becomes deterministic. This enables coupling of simulations with and without an intervention, yielding low-variance effect estimates even when outcomes such as final size or peak incidence vary widely between runs. We develop an exact, event-driven implementation that maintains infection and recovery events in priority queues. Cumulative infection-hazard updates require O(log N) time per event, yielding overall complexity O(Elog N) for E events in a population of size N. The implementation achieves computational performance comparable to the classical Gillespie algorithm while naturally accommodating non-Markovian infectious periods and complex infectiousness profiles. We illustrate the approach using distance-dependent spread of avian influenza between poultry farms in the Netherlands and a multilayer population with households, schools, and workplaces. In both examples, coupling enables efficient within-run comparisons of intervention scenarios across stochastic realisations.