JAC-Antimicrobial Resistance

Background: Antimicrobial resistance is the world's silent pandemic. The public knowledge, attitudes, and practices (KAP) about antibiotic usage are strongly related to the growing problem in Nepal. Methods: A cross-sectional descriptive survey was done to 263 respondents. Information on KAP regarding antibiotics, primary healthcare sources, and demography was collected through a questionnaire. To identify health literacy gaps and characteristics that contribute to improper antibiotic use, this study assessed these variables across an age group from 18 to 60 years. Descriptive statistics analysis was performed to analyze the data. Results: The majority of respondents were between the ages of 18 and 39 (85.1%), female (63.1%), and had at least a bachelor's degree (67.8%). Significant misunderstandings about antibiotics remained, even though 77.6% of respondents correctly recognized antibiotics as effective against bacteria; 44.1% incorrectly believed that antibiotics cure viral diseases, and 87.8% felt that antibiotics should be stopped right away if adverse effects develop. In practice, 52.9% acknowledged quitting antibiotics as soon as symptoms improved, despite 89.4% consulting doctors. Additionally, 43% of respondents said they have taken antibiotics without a prescription, frequently due to pharmacist recommendations (21.67%) and financial or geographical constraints. The main sources of information were doctors (11.07%) and pharmacist-doctor combinations (14.88%), yet 81.8% of respondents said they had never heard of the phrase antimicrobial resistance. Conclusion: There is a significant lack between theoretical understanding and practical application, despite the high levels of fundamental knowledge toward the prohibition of non-prescription sales. Self-medication and early withdrawal are still common inappropriate practices. It is crucial to implement focused teaching initiatives that highlight the differences between bacterial and viral diseases as well as the risks associated with leftover medicine. It is advised to use digital platforms for younger demographics and to strengthen the role of pharmacists in order to reduce AMR.

Methicillin-resistant Staphylococcus (MRS) infections are a significant public health concern. Anterior nares serve as a major reservoir and source of spread of MRS ssp. People living with HIV (PLWHIV) tend to be at higher risk of colonisation with MRS organisms due to frequent healthcare exposure. We assessed the prevalence of MRS nasal carriage and associated factors among PLWHIV at the HIV clinic of Kiruddu National Referral Hospital, Kampala, Uganda, from May to July 2024. Nasal swabs from 256 PLWHIV were cultured, and microbiological isolation was performed at MBN Clinical Laboratories. Prevalence was calculated as proportions, and logistic regression identified associations with clinical and socio-demographic factors (p < 0.05). Of 256 participants, 163 (63.7%) carried Staphylococcus, with 82 (32%) identified as MRS carriers (8.9% MRSA, 23% MRCoNS). Frequent hospital visits ([&ge;]3) (adjusted incidence risk ratio [A-IRR] = 1.18 x 107, p < 0.001), second-line antiretroviral therapy (ART) (A-IRR = 3.82, p = 0.041), and unsuppressed viral load (>1000 copies/mL) (adjusted odds ratio [AOR] = 11.3, 95% CI: 2.11-60.58, p = 0.005) were significantly associated with MRS carriage. Mask-wearing was protective against MRCoNS (A-IRR = 1.66, 95% CI: 1.06-2.58, p = 0.026). MRS isolates exhibited high resistance to erythromycin (81.7%) and trimethoprim-sulfamethoxazole (79.3%), but susceptibility to linezolid (93.9%). MRS nasal carriage is prevalent among PLWHIV. Individuals with frequent health care contact and those on second-line ART regimens are more susceptible to MRS colonization, while individuals who wear face masks and those with an undetectable HIV viral load are less susceptible. Antimicrobial Resistance (AMR) surveillance within HIV programs, enhanced infection control, ART adherence, and targeted screening for high-risk groups are critical to mitigate colonization.

The Epic Sepsis Model version 2 (ESMv2) is a prediction model embedded into the electronic medical record used to warn clinicians which hospitalized patients are at risk for sepsis. We conducted a retrospective cohort study of 31,951 hospitalizations of 25,760 patients to compare analyses conducted at the commonly used patient-level (where a maximum prediction prior to the onset of sepsis is used to measure performance) vs novel prediction-level (where each prediction is used to measure performance). Sepsis, defined by the Sepsis 3 criteria occurred during 1,049 hospitalizations (3.3%). Patient-level analyses suggested excellent discrimination AUC 0.86; [IQR 0.85, 0.87], whereas prediction-level analyses demonstrated lower performance AUC 0.62; [IQR 0.57, 0.65]. Low estimates of the positive predictive value (14.5% at the patient level vs 4% at the prediction level) imply a high number of false alerts. Common evaluation approaches may overstate the performance of dynamic prediction models and mislead clinical decision-making.

Background: Multi-drug resistant Bacterial (MDRB) Infections in the intensive care units (ICUs) substantially elevate patient mortality, prolong hospital stays, and impose heavy healthcare cost burdens. Existing predictive models for ICU-acquired MDRB infection predominantly focus on static admission-risk assessment, lacking the capacity to leverage longitudinal treatment data for dynamic risk re-stratification during the ICU stay. Meanwhile, most models suffer from poor clinical interpretability, overreliance on hard-to-collect biomarkers, or absence of deployable clinical tools, limiting real-world translation. Therefore, there is an urgent need to develop a parsimonious, interpretable tool based on routine cumulative data to guide timely intervention. This study aimed to develop a interpretable model with a web calculator to improve clinical applicability. Methods: In this study, we conducted a retrospective analysis of ICU inpatients at the First Affiliated Hospital of Dali University between January 1, 2023, and January 1, 2026. Using the create Data Partition function in R software (random seed = 42), the dataset was stratified and divided into a training group and a validation group in a 7:3 ratio. Feature selection was performed using the Boruta algorithm to validate variable rationality. A multivariable logistic regression model was constructed and visualized as a nomogram, and its performance was compared with six machine learning algorithms (Random Forest, XG Boost, Neural Network, etc.). Model validation was conducted using receiver operating characteristic curves (ROC), Decision Curve Analysis (DCA), and SHAP value interpretation. Finally, an online R Shiny calculator was developed based on the final model. Results: A total of 3,631 patients were enrolled and divided into a training group (n=2,543) and a validation group (n=1,088) using stratified random sampling. Five independent predictors were identified in the training group, which were hypertension combined with diabetes, antibiotic types, ventilator days, urinary catheter days, and PCT abnormality times. The Logistic regression model achieved an AUC of 0.772 (95%CI: 0.733-0.812) in the validation group, outperforming XG Boost (0.763) and Random Forest (0.703). The model demonstrated excellent calibration (Hosmer-Leme show {chi}{superscript 2} = 1.94, P = 0.9829) and positive net clinical benefit across threshold probabilities of 0%-40%. SHAP analysis aligned with regression-derived variable importance rankings, confirming predictor contributions. An open-access online calculator was successfully deployed (https://dongfangshao666.shinyapps.io/MDR_shiny2/), enabling real-time individualized risk stratification at the bedside. Conclusion: This study developed and validated a dynamic, interpretable multi-drug-resistant bacterial infection risk prediction model requiring only five routinely collected clinical indicators. The model balances robust predictive performance with high transparency, overcoming key limitations of prior tools. The accompanying web calculator supports dynamic risk reassessment throughout the ICU stay, facilitating precise antimicrobial stewardship, targeted infection control interventions, and optimized resource allocation, bridging the gap between statistical modeling and frontline clinical decision-making.

Rationale: Efficacious dose selection for anti-tuberculosis drugs has traditionally relied on achieving plasma exposures above the minimum inhibitory concentration, but this approach has not consistently aligned with clinical outcomes. Objectives: We sought to identify early pharmacokinetic-pharmacodynamic targets most predictive of clinical efficacious dose. Methods: We conducted a back-translational, pharmacokinetic-pharmacodynamic simulation-based analysis of 15 anti-tuberculosis drugs. Using pharmacokinetic data from multiple biological matrices and a range of pharmacodynamic metrics, we established candidate exposure-response targets for attainment. We systematically evaluated the predictive accuracy of each target pair against established clinical doses to formulate a decision-making framework linking key drug properties to the most predictive targets. Measurements and Main Results: Depending on the target used, projected clinical doses varied widely - both within and across compounds - highlighting the importance of target selection for dose projection and go/no-go decisions. In general, targeting cellular lesion-level drug exposures relative to in vivo preclinical potency provided an effective approach for early dose selection. However, for highly penetrating drugs, targeting site-of-action therapeutic exposures in the caseum was more predictive of clinical dose. Based on these findings, we developed a preliminary dose prediction tool that enables drug developers to estimate clinically relevant dose ranges of compounds using in vitro and early in vivo data. Conclusions: This work establishes and validates a simple, evidence-based framework to standardize early translational decision-making on dose selection of anti-tuberculosis candidates in development.

Introduction: The use of artificial intelligence (AI) by clinicians has increased rapidly in recent years, with large language models (LLMs) emerging as tools that can equal clinician diagnostic performance in simulated settings. However, limited data exist regarding physicians use of LLMs in real-world clinical practice. This study aimed to evaluate the frequency of LLM use among practicing hospitalists, identify which LLMs are most commonly utilized, and assess hospitalists' perceptions of the benefits and limitations of LLM use in clinical care. Methods: We conducted a cross-sectional survey study of academic hospital medicine faculty across 8 institutions within the Hospital Medicine Reengineering Network (HOMERuN), a collaborative research consortium. Eligible participants included hospitalists practicing within participating HOMERuN sites during the study period. The survey assessed the frequency of LLM use, types of LLMs used, clinical applications, and physician perceptions regarding usefulness, efficiency, and concerns associated with LLM adoption. Results: 170 respondents (67.1%) reported ever using an LLM in clinical practice. Among LLM users, OpenEvidence was the most used tool (88.9%), followed by ChatGPT (58.5%), Google Gemini (26.9%), and Microsoft Copilot (20.5%). Only a minority of hospitalists reported using LLMs daily while seeing patients. The most common use cases of LLMs were answering diagnostic (77.1%) and management (77.6%) questions. A majority also reported using LLMs to identify or summarize primary literature (60.0%). Lack of trust in outputs (49.8%), uncertainty around institutional policies (48.6%), and lack of access to secure applications (43.1%) were cited as the most frequent barriers to using LLMs in practice. Discussion: The use of LLMs in clinical practice is already widespread, though regular or daily use is not yet typical. Concerns regarding reliability, patient privacy, and safe integration into clinical workflows remain significant barriers to broader adoption. The responsible implementation of LLMs in hospital medicine will require addressing these barriers.

Primary healthcare (PHC) managers are central to the functioning of South Africas healthcare system, yet many assume leadership roles without formal management training. To address this gap, the Aurum Institute developed the Management Development Programme (MDP), a structured leadership and management training intervention aimed at strengthening PHC management competencies. This study evaluated the impact of the MDP on leadership practices, organisational readiness for change, and workplace stress among PHC managers in the Western Cape Province. A non-randomised matched cluster trial was conducted across 20 PHC facilities. Intervention facilities were purposively selected based on participation in the MDP, while matched control facilities were randomly selected. Data were collected using structured and semi-structured surveys administered to facility managers and clinic staff. Leadership competency was assessed using the Leadership Practices Inventory (LPI), which measures five dimensions of exemplary leadership: Model the Way, Inspire a Shared Vision, Challenge the Process, Enable Others to Act, and Encourage the Heart. Organisational readiness for change was measured using Kotters 8-Step Framework, while workplace stress was assessed using a 13-item version of the Brief Job Stress Questionnaire focusing on Job Meaning, Environmental Quality, Autonomy, and Control. Intervention effects were estimated using generalised linear models adjusted for manager age, years in role, matched-pair fixed effects, and cluster-robust standard errors. Outcomes were reported as adjusted risk differences with 95% confidence intervals and two-sided p-values. A total of 20 facility managers (median age 51 years; IQR 42-55; 90% female) and 105 clinic staff members (median age 42 years; IQR 35-50) participated in the study. Managers in both intervention and control facilities reported consistently high self-rated leadership competency scores across all LPI domains, with no statistically significant differences between groups. Similarly, clinic staff rated managers highly across the standard LPI domains, and no significant differences were observed between intervention and control facilities. Despite the absence of significant differences in overall leadership competency scores, staff in intervention facilities reported significantly stronger relational and communication practices among managers compared with staff in control facilities (72.7% vs. 64.0%; adjusted risk difference 22.0%, 95% CI 6.1-37.8; p=.007). After adjustment for age and tenure imbalances, intervention facilities also demonstrated significantly higher scores for institutionalised capability and learning culture (adjusted risk difference 21.3%, 95% CI 0.6-42.0; p=.043). Managers who participated in the MDP further reported stronger perceptions of district support, including improved internal leadership and cultural readiness (adjusted risk difference 22.1%, 95% CI 14.0-30.3; p<.001) and greater district leadership and resource availability (adjusted risk difference 28.1%, 95% CI 15.6-40.6; p<.001). No statistically significant differences were observed in workplace stress across any domain. Although the MDP did not produce measurable short-term improvements in managers self-rated leadership competencies or standard LPI domains as assessed by staff, it was associated with important gains in relational leadership practices, organisational readiness for change, and perceived district support. These findings suggest that structured management training programmes may strengthen critical organisational and interpersonal foundations necessary for sustained performance improvement within PHC settings.

Introduction. Practice coaching is increasingly used to strengthen quality improvement (QI) capacity in primary healthcare (PHC) systems in low and middle income countries (LMICs), yet the causal pathways through which it shifts provider behaviour, and the systemic conditions that enable or constrain those pathways, remain under theorised. Using a theory based qualitative evaluation, we examined how and why a practice coaching intervention influenced QI in cervical cancer screening (CCS) and antenatal care (ANC) within Honduras decentralised PHC system during the third phase of the Salud Mesoamerica Initiative (SMI). Methods. We conducted a within case explanatory case study. A programme theory was reconstructed before data collection and iteratively refined against evidence. Data comprised semi structured interviews with 11 midlevel managers, 6 PHC team medical leads, and 2 regional managers, complemented by direct observation and document review. We applied combined deductive and inductive coding, thematic analysis, and pattern matching, and reporting per COREQ. Results. We identified four causal patterns that refined the initial programme theory. Three were activated pathways: (1) novel professional identity among participating managers; (2) collective efficacy and data driven learning, sustained through verifiable progress on observable indicators, strong for CCS but null for ANC, where outcomes were less attributable to teams actions; and (3) relational coordination, psychological safety, and trust, which provided the interpersonal basis for the first two. A fourth, unanticipated pattern showed structural misalignment between coaching enabling, learning based logic and the directive, punitive logic of Honduras performance based contracting environment, confining gains to localised enabling bubbles. Conclusion. Coaching can activate meaningful QI pathways in LMIC primary care, but sustained, equitable impact requires deliberate alignment between coaching learning oriented principles and the institutional performance management architecture, and matching of coaching investment to clinical processes with observable, attributable outcomes.

Background: Strong management capacity is essential for effective primary healthcare (PHC) service delivery and health system strengthening [1]. The AURUM Management Development Programme (MDP) was implemented to strengthen district and PHC leadership in the Western Cape province of South Africa. This study explored the contextual barriers and enabling conditions influencing the scalability of the programme within district health systems. Methods: This study employed a qualitative exploratory design to investigate barriers and enablers associated with scaling the MDP. In-depth interviews were conducted with purposively selected district health managers from three Western Cape districts. Interviews were audio-recorded, transcribed verbatim, and analysed thematically using NVivo 14. The study explored perceptions regarding programme adaptability, district readiness, implementation challenges, and enabling conditions for sustainability and scale-up. Results: Twenty participants (7 males and 13 females) from the Cape Winelands, Garden Route, and Cape Town Metro district health offices were interviewed. The MDP was viewed as relevant, practical, and adaptable to district health system contexts. District readiness for implementation emerged as an important determinant of perceived programme success. High readiness was characterised by clear team roles, strong management structures, decentralised decision-making, digital tool utilisation, ongoing mentorship systems, and prior exposure to PHC reforms such as the Ideal Clinic Realisation and Maintenance (ICRM) programme. Lower readiness was associated with staff shortages, operational pressures, limited leadership support, and partially functional health systems. Key enabling factors included integration with existing training structures, visible improvements in service delivery, mentorship support, and active engagement from district leadership. Conclusion: The MDP demonstrates potential for scalability within South Africas public health system. However, successful scale-up depends on district-level readiness, supportive leadership structures, integration into existing training and management systems, and sustained mentorship and implementation support.

Background Erythema nodosum leprosum (ENL) is a severe inflammatory complication of lepromatous leprosy characterised by recurrent inflammatory episodes often requiring prolonged immunosuppression. The severity of ENL can be quantified using the validated and reliable ENLIST ENL Severity Scale (EESS). The longitudinal course of ENL and how it is captured using standardised severity measures has not been well described. We prospectively evaluated the changes in ENL severity over time using the EESS in a randomised clinical trial. Methods We conducted a post-hoc analysis of participants enrolled in the Methotrexate and Prednisolone Study in ENL, an international multicentre randomised controlled trial conducted in Ethiopia, India, Indonesia, and Nepal. Adults with severe ENL (EESS score [&ge;]9) were followed for 60 weeks with repeated EESS assessments. Longitudinal trajectories were analysed using mixed-effects regression models. Item-level analyses characterised the clinical phenotype captured by the scale. Associations between EESS score, prednisolone exposure, and dermatology-specific health-related quality of life measured using the Dermatology Life Quality Index (DLQI) were examined. Findings A total of 135 participants contributed 1,958 EESS assessments. Mean EESS declined rapidly during the first four weeks of treatment (-2.10 points/week; 95% CI -2.36 to -1.84; p<0.001), increased modestly during reduction in corticosteroid dose (weeks 4-20), and gradually declined thereafter. Severe ENL (EESS score [&ge;]9) occurred in 20.6% of visits and was characterised primarily by pain and cutaneous inflammatory manifestations. Participants who required additional prednisolone had persistently higher EESS scores and showed limited improvement compared with those who did not receive additional prednisolone. Longitudinal EESS scores were strongly correlated with the DLQI score (Spearmans {rho}=0.75; p<0.001). Conclusion The EESS captures clinically meaningful changes in ENL severity, aligns with treatment decisions, and reflects patient-reported severity over time. These findings support the use of the EESS as a robust tool for monitoring ENL severity in both clinical research and routine care.

Background Outpatient groin hernia repair is widely recommended globally due to clinical and socioeconomic efficiency, yet it remains underutilized in developing healthcare systems like Tunisia. This study aimed to evaluate the feasibility of a newly implemented day-surgery clinical pathway for groin hernias and identify specific predictors associated with outpatient discharge failure. Methods A prospective, observational cohort study was conducted at a Tunisian tertiary hospital between September 2023 and April 2024. A total of 85 consecutive patients scheduled for elective groin hernia repair under an optimized clinical pathway were enrolled. Inclusion criteria spanned ASA classes I-III, age [&ge;]16 years, proximity to the hospital [&le;]50 km), and presence of a literate adult caregiver. Outpatient failure (unanticipated admission) was defined as the inability to achieve discharge within 24 hours post-surgery. Statistical associations were determined using Chi-squared, Fisher's exact, and independent t-tests. Results The cohort primarily comprised males (n = 82, 96.5%) with a mean age of 56 years (range: 19-86). Successful ambulatory discharge was achieved in 80 patients (94.1%), yielding a failure rate of 5.9% (n = 5). Unanticipated admissions were triggered by uncontrolled pain (n = 1), acute anxiety (n = 2), decompensation of comorbidities (n = 1), and a Post-Anesthetic Discharge Scoring System (PADSS) score < 10 (n = 1). Overall 30-day morbidity was low (2.4%), presenting as minor wound or scrotal hematomas managed conservatively; no surgical site infections, acute urinary retention, or mortality occurred. Univariate analysis revealed that a hernial sac size measured at its maximum diameter between 1.5 and 3 cm was significantly associated with ambulatory failure (p = 0.047). General anesthesia showed a trend toward increased failure compared to regional anesthesia (p = 0.08). Conclusion Day-surgery groin hernia repair is highly safe and feasible in resource-constrained environments, even for elderly or stable ASA III patients, provided rigorous social criteria are satisfied. A small hernial sac size (1.5-3 cm) constitutes a major anatomical predictor of failure, likely due to distinct dissection dynamics and localized post-operative pain profiles.

Background: Accurate early identification of sepsis remains a major clinical challenge due to its heterogeneous presentation and overlap of clinical signs with the non-infectious systemic inflammatory response syndrome (SIRS). Timely differentiation is crucial for improving patient outcomes, meeting sepsis bundle requirements and reducing inappropriate antimicrobial use. We hypothesized that clinical and laboratory data available within the first 3 hours of patient presentation could be used to identify patients with sepsis to an actionable level of accuracy, in lieu of traditional microbiology results which would not become available until at least 12-24 hours. Data from two independent studies were used to quantify the diagnostic value of demographic, vital, clinical-laboratory, and microbiological data available at three time points for distinguishing retrospectively diagnosed critically ill patients with either sepsis or non-infectious SIRS. A particular focus of this work was an assessment of the utility of SeptiCyte RAPID (Immunexpress Inc., Seattle, Washington, USA) as an aid to sepsis diagnosis, producing actionable data within 1 hour. Methods: Data from two independent study cohorts were analysed. The 510k cohort consisted of 419 adult patients in intensive care (ICU) (MARS, VENUS, and NEPTUNE trials). The Andalusian cohort consisted of 353 ICU patients from the PANGEA study. Logistic regression models, selected by a greedy search algorithm and validated by repeated cross-validation, were used to determine the contributions of different variables to diagnostic accuracy. Diagnostic performance was quantified by area under the receiver operating characteristic curve (AUC). Results: For the 510k cohort, a baseline AUC of 0.69-0.73 was observed using 5-7 vital and demographic variables assessed immediately upon presentation (time T1). The addition of clinical-laboratory variables, in particular SeptiCyte RAPID, within 1-3 hours post-presentation (time T2) increased the AUC to 0.83-0.85). Finally, the addition of microbiological data 12-24 hours post-presentation (time T3) further improved the AUC to 0.90-0.91. Similar results were obtained for the Andalusian cohort. AUC values at the three time points were as follows: At time T1, AUC = 0.67 based solely on vital signs and demographics; at time T2, AUC = 0.87 based on vitals + demographics + SeptiCyte RAPID or other clinical laboratory data; at time T3, AUC = 0.93 based on vitals + demographics + SeptiCyte RAPID or other clinical laboratory data + microbiology results). For both cohorts, the most significant variables included temperature, mean arterial pressure, respiratory rate, suspected infection site; SeptiCyte RAPID, procalcitonin, confirmed bacterial infection and positive blood culture confirmation. Conclusions: Accuracy of identification of sepsis increases markedly as demographics and vital signs are supplemented with clinical-laboratory information, and ultimately with microbiological culture results. The fastest improvement occurs within the first 3 hours when laboratory data, and in particular SeptiCyte RAPID results, become available. Integrating rapid host-response testing with SeptiCyte RAPID into time-based diagnostic frameworks may enhance early sepsis recognition, improve antimicrobial stewardship, and support guideline-driven clinical decisions.

Overview: SeptiCyte RAPID is an FDA-cleared gene expression test that quantifies host immune response to aid in the diagnosis of sepsis. The test yields a score (the SeptiScore) ranging from 0-15, distributed across four bands (1-4) based on increased likelihood of sepsis. Each band can be characterized by average positive and negative likelihood ratios (LR+, LR- respectively) for the discrimination of sepsis versus the non-infectious systemic inflammatory response syndrome (SIRS). Methods: A retrospective analysis of prospectively collected data from a combined cohort of critically ill patients suspected of sepsis (N=889), recruited across 19 hospitals in the USA and Europe. The analysis quantified the LR+ and LR- parameters as a function of SeptiScore, for discrimination of sepsis vs. SIRS in patients admitted to ICU. Hypotheses: (1) The likelihood ratio (LR) framework provides a clinically useful interpretive approach that complements the previously used SeptiScore banding scheme; (2) Low Band 1 SeptiScores are associated with sufficiently small LR- to support the use of SeptiCyte RAPID as a rule-out test for sepsis; (3) High Band 4 SeptiScores are associated with sufficiently large LR+ to support the use of SeptiCyte RAPID as a rule-in test for sepsis; and (4) SeptiScore-derived LR+ and LR- values can be combined with estimates of pre-test probability (derived from patient characteristics and/or other diagnostic tests) to generate individualized, patient-specific post-test probabilities of sepsis. Results: The SeptiCyte RAPID test demonstrates strong diagnostic performance in distinguishing sepsis from SIRS. The likelihood ratios across different score bands provide clear clinical utility: the median LR+ was 3.26 (range 2.57-4.24) for Band 3, and 6.97 (range 4.35-15.57) for Band 4 providing evidence toward ruling in sepsis at high SeptiScores. Conversely, the median LR- was 0.16 (range 0.14-0.20) for Band 2 and 0.085 (range 0.014-0.16) for Band 1, providing evidence toward ruling out sepsis at low SeptiScores. A higher-resolution analysis of SeptiCyte RAPID performance confirmed these trends by evaluating LR+ and LR- at specific values within each band. The sepsis group was further stratified according to whether patients were classified as blood-culture positive (BC+) or blood culture negative (BC-), and the detailed LR+ and LR- analyses were repeated. A monotonic increase in likelihood ratio with increasing SeptiScore was consistently observed, independent of whether sepsis patients were culture-positive, culture-negative, or unstratified with respect to blood culture status. Conclusion: High SeptiScores have correspondingly high LR+ values, and low SeptiScores have correspondingly low LR- values, both of which may have clinical utility. High likelihood ratios for band 4 SeptiScores, which precede traditional microbiology results, may provide clinicians with early confidence of a sepsis diagnosis and microbiology diagnostic stewardship. Low likelihood ratios for band 1 SeptiScores may prompt clinicians to consider an alternate diagnosis to sepsis. Such results, obtained early in the diagnostic workup process, may lead to fewer missed diagnoses and more efficient use of hospital resources.

Maternal health during pregnancy is critical for favorable birth outcomes and long-term wellbeing of both mothers and infants. Women in rural, malaria-endemic regions face unique biological and socioeconomic challenges that may increase the risk of adverse pregnancy outcomes (APOs). This study investigated the incidence and determinants of APOs among pregnant women attending antenatal care at Webuye sub-County Hospital in Western Kenya, a rural malaria-endemic setting. We conducted a retrospective cohort analysis utilizing previously collected data of 300 women enrolled during early pregnancy and followed through delivery. Maternal demographic, clinical, and infection-related factors were assessed, and associations with APOs were evaluated using chi-square tests and multivariable logistic regression. Maternal age and gestational age at enrollment were significantly associated with malaria history (P<0.001). Maternal BMI abnormality (124.5/1000 pregnancies), anemia (99.3/1000), fetal or neonatal death (81.3/1000), and preterm birth (43.8/1000) were observed (all P<0.001), suggesting a substantial burden. Younger mothers (<20 years) and older mothers (>35 years) were significantly more likely to develop anemia (P =0.026), and prior malaria infection further increased anemia risk (P =0.02). Abnormal urinalysis findings indicative of urinary tract infection were significantly associated with low birthweight (P =0.031). No significant associations were found between APOs and infant sex, parity, gravidity, or maternal ABO blood type. These findings highlight a substantial burden of APOs in this rural population, exceeding national and global estimates. Strengthening malaria prevention, nutritional support, urinary infection screening, and encouraging early antenatal care attendance are critical to improving maternal and neonatal outcomes. Targeted interventions for adolescent and older mothers, along with enhanced point-of-care diagnostics, may reduce preventable complications in similar resource-limited, malaria-endemic settings.

Tuberculosis (TB) remains one of the deadliest infectious diseases, with over a million deaths annually and a growing threat from multidrug-resistant strains (MDR-TB). A major bottleneck in controlling TB is the lack of truly portable, rapid, and user-friendly diagnostic systems that can operate effectively in decentralized, resource-constrained settings. Here, we present a first-of-its-kind, portable nucleic-acid-based diagnostic platform that enables both primary TB screening and detection of drug resistance within the same unified framework, without any change in the operative embodiment. The system integrates loop-mediated isothermal amplification (LAMP) targeting dual Mycobacterium tuberculosis markers (IS6110 and IS1081) with a compact, AI-enabled device and smartphone-based readout, delivering rapid and reliable results at the point-of-care. Clinical evaluation across 105 samples demonstrated high sensitivity and specificity. Further validation through real-world deployment in a primary healthcare setting, using a single-gene (IS6110) configuration operated by minimally trained personnel, yielded 95.60% sensitivity and 100% specificity, benchmarked against GeneXpert. Critically, the same platform architecture, without modification, extends seamlessly to drug-resistance profiling, demonstrated here through a probe-free, allele-specific LAMP approach for identifying key mutations associated with rifampicin (rpoB) and isoniazid (katG) resistance. By combining robust molecular diagnostics with AI-driven automation in a compact and accessible format, this work represents a significant medical advancement toward democratizing TB care. The platform thus holds strong potential to enable early screening, guide timely treatment decisions, reduce transmission, and substantially strengthen global TB elimination efforts, particularly in high-burden, low-resource settings.

Background: Cambodia is a high-TB burden country where over a third of TB cases have gone undetected. The Community Mobilisation Initiatives to End TB (COMMIT) programme, implemented across four provinces and 27 operational districts (ODs) in Cambodia from October 2019 to September 2024, aimed to improve TB case finding, diagnosis, treatment, and prevention through community-driven approaches. This study evaluated the implementation, programme outcomes, and sustainability of COMMIT to inform future TB initiatives. Methods: This mixed-methods explanatory sequential study used the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. Quantitative data were collected from the programme database and the national TB Management Information System (TB-MIS). In-depth interviews, guided by the Theoretical Domains Framework (TDF), explored contextual factors influencing programme implementation and complement quantitative findings. Quantitative data were analysed descriptively to estimate screening coverage, diagnostic yield, and construct care cascades. Qualitative data were transcribed and translated into English, coded, consolidated into a matrix structured using RE-AIM and TDF components, and analysed thematically. Results: COMMIT screened 695,970 people for TB. Key populations were reached, though sex and age disparities in screening participation reflected underlying social and structural barriers. Approximately 98% of those screened underwent diagnostic testing. Treatment initiation (>99%) and completion (>97%) rates were high. COMMIT operationalised contact investigation and evaluation for TB preventive treatment (TPT), screening over 90% of notified contacts. More than 20,000 people were TPT-eligible, of whom 68.7% enrolled in and 86.2% completed TPT. These programme outcomes were supported by strong community engagement, expansion of rapid molecular diagnostics, and programme adaptability during COVID-19. COMMIT was scaled from 10 to 27 ODs, during which it strengthened community capacity by training healthcare workers and expanding peer support groups. Stakeholders emphasised the need to reinforce local ownership and public-private sector collaboration, strengthen integrated services, and de-implement low-value practices such as symptom-based screening. Conclusions: COMMIT improved TB case detection, treatment support, and prevention in Cambodia through community-led strategies and sustained capacity building. Maintaining the programme impact will require continued investment in community systems, de-implementation of low-value practices, and the adoption of efficient, person-centred approaches that address evolving community needs.

Background: Comprehensive assessment of hypertension-mediated organ damage (HMOD) across multiple organ systems remains limited in sub-Saharan Africa. We aimed to determine the prevalence and predictors of multidomain HMOD in a geographically diverse Ghanaian adult population. Methods: This secondary analysis of the Ghana Heart Study included 1,106 adults from four regions. Multidomain HMOD was defined as a pre-specified 9-domain TOD composite score ?2, based on the ESH/ESC 2018 guidelines framework. Logistic regression and ROC analysis were used to identify predictors and compare discriminative performance. Results: Mean age was 46.9 (17.2) years and 58% were female. Multidomain HMOD prevalence was 21.2% (235/1,106) and increased steeply with age: 8.6% (<45 years), 20.6% (45?59 years), and 44.4% (?60 years). Hypertension prevalence was 73% in the HMOD group versus 28% in those without HMOD (p < 0.001). The strongest independent associations were peripheral artery disease (OR 41.2), valvular burden (OR 14.4), and ECG-LVH (OR 9.0). baPWV showed superior discriminative performance (AUC 0.827, 95% CI 0.794?0.860) compared with the ASCVD Pooled Cohort Equations (AUC 0.466; ?AUC +0.351, DeLong test p < 0.001). Conclusions: One in five Ghanaian adults has hypertension-mediated organ damage in ?2 organ systems. baPWV is the strongest predictor and substantially improves risk stratification beyond conventional scores. These findings support the use of baPWV to guide hypertension management and HMOD assessment in West Africa.

Background/Objectives: Influenza infection is a major trigger of pneumonia and acute exacerbations among patients with chronic obstructive pulmonary disease (COPD). However, national laboratory-confirmed evidence on influenza vaccine effectiveness (VE) in this high-risk population remains limited. This study aimed to estimate the effectiveness of seasonal influenza vaccination against influenza-associated pneumonia and COPD exacerbations among patients with COPD in Thailand.Methods: We conducted a nationwide retrospective test-negative design study using administrative healthcare data from the National Health Security Office linked with laboratory-confirmed influenza surveillance data between June 1, 2013, and May 31, 2025, covering twelve influenza seasons (2013-2024). COPD-related clinical episodes among patients aged [&ge;]40 years who presented with pneumonia or acute exacerbation of COPD and underwent RT-PCR testing for influenza were included. Multilevel Poisson regression models were used to estimate adjusted risk ratios (RRs), and VE was calculated as (1 - adjusted RR) x 100.Results: A total of 606,072 COPD-related clinical episodes were included, of which 192,224 (31.7%) were influenza-positive. The overall adjusted VE against influenza-associated pneumonia was 63.2% (95% CI: 62.5-64.0), while VE against influenza-associated COPD exacerbations was 67.0% (95% CI: 48.8-78.8). VE estimates were broadly similar across age groups and remained substantial across COPD severity strata. Although point estimates were numerically higher in severe and very severe COPD, subgroup differences should be interpreted cautiously.Conclusions: Seasonal influenza vaccination was associated with substantial protection against influenza-associated pneumonia and COPD exacerbations among patients with COPD in Thailand.

Background In 2017, Zambia adopted surveillance as a core intervention towards achieving malaria elimination. Among the surveillance strategies is the malaria case investigation and response 1-3-7 (MCIR 1-3-7), which has been piloted in two low-incidence districts in the Southern Province since 2021. The study aimed to assess the implementation of MCIR 1-3-7 under programmatic conditions. It examined the timeliness, and completeness of the MCIR 1-3-7 activities, including the completeness of data entry in surveillance forms, and explored the experiences and perspectives of healthcare workers involved in the pilot. Methods A mixed-methods design was employed to assess the MCIR 1-3-7. Using a descriptive cross-sectional design, quantitative data were collected from 19 healthcare facilities in the two districts to assess the timeliness and completeness of MCIR 1-3-7. Additionally, 12 qualitative interviews were conducted with 29 healthcare workers from 11 of the 19 healthcare facilities. The interviews were voice-recorded and then transcribed manually. A codebook was developed using an iterative process to explore the facilitators and barriers encountered by healthcare workers in implementing the MCIR 1-3-7 intervention. All the visited facilities were purposively selected based on logistical convenience. Results This study retrospectively assessed 510 malaria cases that were diagnosed between January 2022 and June 2023, presenting at 19 health facilities: 283 cases in Chikankata and 227 in Mazabuka districts. A total of 278 cases (54.5%) were deemed to have been imported from outside the district, province, or country, while 45.5% (232/510) of the cases were classified as transmitted locally. Overall, 29.6% of case notification forms were found to be complete. Twelve interviews with 29 healthcare workers revealed a lack of transportation modalities as the main obstacle in executing the MCIR 1-3-7 intervention. The healthcare workers also indicated that monetary incentives, and supportive supervision would help them succeed in implementing this intervention. Conclusions The MCIR 1-3-7 has the potential to accelerate elimination in areas with low-transmission of malaria in Zambia. This study highlights opportunities to improve future implementation of the MCIR 1-3-7 intervention via strengthening supportive supervision, availing job aids, and ensuring access to malaria commodities as the intervention expands.

Background Human challenge trials provide a unique opportunity to quantify pathogen infectivity in terms of the probability of infection given an inoculated dose. However, between-pathogen comparisons are often distorted by individual heterogeneity in host susceptibility and by differences in background immunity across trial populations. We examined how dose-dependent infection risks differ across common respiratory viruses when such heterogeneity is explicitly incorporated. Methods We conducted a systematic review of human challenge trials for four respiratory viruses: respiratory syncytial virus (RSV), influenza virus, rhinovirus, and adenovirus. Using the extracted data, we fitted dose-response models under different distributional assumptions, allowing both continuous susceptibility variation and discrete immune fractions. We compared alternative heterogeneity models and evaluated pathogen-specific dose-response patterns using original and scaled dose metrics. Results All four viruses showed substantial heterogeneity in host susceptibility, and models assuming homogeneous susceptibility were unsupported. RSV and influenza were best described by models with a distinct immune or effectively non-susceptible subgroup, and the estimated immune proportions were approximately 40% and 25%, respectively. In contrast, rhinovirus and adenovirus were better explained by continuously distributed susceptibility, with little evidence of a fully immune subgroup. On a scaled dose axis, rhinovirus and adenovirus showed steeper increases in infection risk with dose than RSV and influenza. Conclusions The structure of susceptibility heterogeneity differs across common respiratory viruses, which in turn shapes dose-dependent infection risks. Incorporating this heterogeneity is essential for valid cross-pathogen comparison and for interpreting human challenge data in epidemiologic and public health contexts.