Infection

Background The COVID-19 pandemic has caused significant global mortality. Despite declining infection rates, new variants of SARS-CoV-2 continue to emerge, necessitating new prevention strategies. Objective This study aimed to evaluate the effect of four over-the-counter (OTC) antiseptic mouthwash/gargling solutions in the U.S., compared with a distilled water control, on SARS-CoV-2 viral load across multiple oral and oropharyngeal sample types. Methods This pilot single-center randomized controlled clinical trial enrolled adults in the San Francisco Bay Area, California, who tested positive for COVID-19. Participants were randomized to distilled water, chlorine dioxide, hydrogen peroxide, cetylpyridinium chloride, and essential oils. Participants were instructed to rinse and gargle four times daily for four weeks using standardized instructions to ensure protocol adherence. Samples were collected on Days 1, 7, and 28 and analyzed using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The primary outcome was the change in SARS-CoV-2 viral load from baseline to Day 28, assessed using cycle threshold (Ct) values. Secondary outcomes included self-reported clinical symptoms and hospitalization. Results Forty-nine participants completed the study. No mouthwash demonstrated a statistically significant reduction in SARS-CoV-2 viral load over time. Cetylpyridinium chloride showed a transient increase in Ct values on Day 7 that was not sustained on Day 28. At baseline, throat swab samples had the lowest Ct values across all sample types. Due to limited subgroup sample sizes for secondary outcome measures, no statistical or moderator analyses were conducted. Conclusion Further large-scale randomized trials are needed before recommending antiseptic mouthwashes for SARS-CoV-2 prevention or management.

Objective: To identify Dickkopf-1 (DKK1) as a prognostically relevant candidate in head and neck squamous cell carcinoma and to evaluate whether DKK1 and cytoskeleton-associated protein 4 (CKAP4) expression is associated with cervical lymph node metastasis in tongue squamous cell carcinoma (TSCC). Methods: DKK1 was screened using the Human Protein Atlas Pathology Atlas. Immunohistochemical expression of DKK1 and CKAP4 was examined in 54 patients with primary TSCC (cT1-4N0) treated surgically between 2015 and 2020. Nine cases were excluded because of insufficient tissue blocks or inadequate staining quality, leaving 45 evaluable cases. Associations with delayed cervical lymph node metastasis were assessed together with conventional clinicopathological factors, including infiltrative growth pattern (INF) and pathological depth of invasion (pDOI). Results: In public database analysis, high DKK1 expression was associated with poorer overall survival in head and neck squamous cell carcinoma. In the TSCC cohort, pDOI [≥]5 mm and INF pattern c were significantly associated with cervical lymph node metastasis. Positive DKK1 and CKAP4 expression were also significantly associated with cervical lymph node metastasis. Furthermore, combined DKK1/CKAP4 positivity, when incorporated with INF and pDOI, provided additional risk stratification, and cases with all 3 factors showed a markedly increased likelihood of cervical lymph node metastasis. Conclusions: Expression of DKK1 and CKAP4 was associated with cervical lymph node metastasis in TSCC. Combined assessment of DKK1/CKAP4 expression with INF and pDOI may improve pathological risk stratification and may help identify patients who require closer neck evaluation and postoperative management.

Introduction: Viral load (VL) monitoring is the gold standard for antiretroviral therapy (ART) monitoring. Still, due to limited funds and infrastructure, many people living with HIV (PLHIV) in low- and middle-income countries do not receive timely VL testing. We evaluated the clinical performance and end-user acceptability of a prototype interferon gamma-induced protein 10 (IP-10) point-of-care (POC) test as a rule-out triage tool to identify individuals unlikely to have unsuppressed VL in PLHIV in Mozambique. Methods: A mixed-methods study was conducted between November 2023 and November 2024 at two primary healthcare facilities in Maputo Province. We enrolled 1,057 PLHIV on ART from stable and specialized risk clinics. Clinical performance of the IP-10 POC test (index test) was compared against plasma HIV VL (reference test; unsuppressed defined as >1000 copies/mL). Socio-demographic and clinical predictors of false-positive results were identified using multivariable logistic regression. Immediate acceptability was assessed through exit interviews on a subset of 43 PLHIV. Results: Among participants (71.7% female; median age 41.4 years), 12.0% had unsuppressed VL. The IP-10 POC test demonstrated high sensitivity (90.6%) and moderate specificity (35.6%). Specificity was higher in clinics treating stable patients (44.5% 95%CI: 39.7-49.3) compared to specialized risk clinics (26.5% 95%CI: 21.1-28.9). The proportion of false-positive results was also higher in patients attending specialized risk clinics. Independent predictors of false positivity included enrolment in a one-stop TB/HIV clinic (aOR=2.99 95%CI: 1.09-8.15), cotrimoxazole use (aOR=2.16, 95% CI: 1.13-4.13), and obesity (aOR=3.47 95%CI: 1.74-6.93). Acceptability was high: 70% of participants appreciated the test simplicity and rapid results, and 95.3% expressed interest in future testing. Most patients preferred finger-prick collection over venous draws. Conclusions: The IP-10 POC test is a highly sensitive triage tool, demonstrating superior performance among stable PLHIV enrolled in differentiated service delivery models like six-month multi-month dispensing. While factors associated with co-infections can reduce specificity, the test's high acceptability and potential to reduce confirmatory VL test demand suggests it could serve as a viable triage strategy for optimizing resources particularly in stable care pathways with a lower prevalence of inflammatory comorbidities. This could enable health systems to reallocate intensive monitoring toward higher-risk populations.

Background: Periodontitis is defined by cumulative, irreversible tissue destruction, yet population-based measurement typically relies on cross-sectional indicators derived from retained teeth. Destruction that occurred earlier in life, particularly disease severe enough to result in tooth loss, is structurally excluded from these measures, potentially leading to systematic underestimation of lifetime periodontal burden. Objective: To develop and evaluate a measurement framework that estimates lifetime periodontal burden from cross-sectional data by explicitly incorporating informative tooth loss under etiological uncertainty. Methods: Data were drawn from 10,324 adults aged [≥]30 years participating in the 20090-2016 National Health and Nutrition Examination Survey (NHANES) who completed full-mouth periodontal examination and glycated hemoglobin (HbA1c) testing. Lifetime periodontal burden was estimated by combining observed clinical attachment loss in retained teeth with probabilistic contributions from missing teeth, using three alternative age-stratified attribution schedules derived from epidemiological studies of periodontal extraction. Performance was compared with conventional measures of periodontal severity and extent using distributional analyses, correlations with HbA1c, discrimination of diabetes status, and relative importance analysis. Age-adjusted models were treated as sensitivity analyses. Results: Estimated lifetime periodontal burden exhibited strong, monotonic age gradients across glycemic categories, in contrast to more attenuated patterns observed for severity and extent. Across attribution schedules, lifetime burden showed stronger correlations with HbA1c ({rho} = 0.30-0.32) than conventional measures. In multivariable models including all indices, lifetime burden retained an independent association with HbA1c, whereas severity and extent contributed little unique information. Discriminative performance for diabetes status was consistently higher for lifetime burden than for conventional measures and remained stable across attribution schedules. Conclusions: Lifetime periodontal burden can be estimated from cross-sectional data by explicitly modelling informative tooth loss rather than restricting measurement to retained teeth. Incorporating historical tissue loss under uncertainty yields a more coherent representation of cumulative periodontal destruction than snapshot-based measures and provides a methodological basis for life-course-oriented periodontal epidemiology.

Background: Community-acquired pneumonia (CAP) remains a major global health burden disproportionately affecting older adults and people with comorbidities, with Streptococcus pneumoniae as one of the leading bacterial causes in Europe. The Hungarian Occurrence and Burden of PnEumonia (Hungarian-HOPE) study examined the incidence, hospitalization rates, and mortality of CAP between 2016 and 2020 in Hungary. Methods: The National Health Insurance Fund database was used to identify adult CAP patients (all-cause) based on ICD-10 codes J10-18. Outcomes included CAP incidence, 0-15-day hospitalization, and 0-30-day mortality after hospitalization, stratified by age, sex, and comorbidities (chronic obstructive pulmonary disease [COPD], asthma, cardiovascular disease [CVD], and type 1 and 2 diabetes [T1DM, T2DM]). Risk maps visualized relative risk gradients across population strata. Results: During the pre-pandemic period (2016-2019), over 100,000 CAP cases and more than 50,000 hospitalizations were recorded annually. In 2020, recorded cases fell to approximately 98,000, while hospitalizations increased to 66,200. Hospitalization rates increased from 25.1% in 2016 to 29.1% in 2019, then increased to 43.1% in 2020. The 30-day mortality among hospitalized patients rose from 22.7% in 2016 to 23.6% in 2019. Incidence, hospitalization, and mortality all increased with age. Relative to healthy males aged 30-39 years, CAP risk escalated steeply in the [≥]80 years cohort (incidence 5-15-fold; hospitalization >3-fold; mortality 11-24-fold) and was further amplified by COPD, CVD, or T2DM, with a lesser effect for T1DM. Conclusions: The results highlight the substantial age- and comorbidity-driven CAP burden in Hungary and support prioritization of preventive strategies including pneumococcal vaccination for older adults and high-risk groups.

Nasopharyngeal (NP) swabs remain the dominant gold standard for respiratory infection diagnostics. While there has been increased use of alternative sample types since the COVID-19 pandemic, guidance on their use for detecting respiratory viruses is not yet definitive, especially for children. In this systematic review and meta-analysis, we aimed to compare the diagnostic accuracy and tolerability of multiple respiratory specimen types for detecting respiratory viruses in pediatric populations. Searches were conducted on July 17, 2025 in MEDLINE, Embase, Web of Science, and Scopus, with screening and data extraction performed in Covidence. English-language primary research articles published since 2000 comparing respiratory virus detection rates in children, using nucleic acid amplification tests between paired respiratory specimens, were included. Risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies criteria. We calculated pooled sensitivities and specificities of index specimens: nasopharyngeal aspirates (NPA), mid-turbinate swabs (MT), anterior nasal swabs (ANS), oropharyngeal swabs (OP), and bronchoalveolar lavage fluid (BAL), as compared to the reference, NP swabs, using random-effects modeling, firstly without discrimination by virus. Index specimens were then grouped by sample collection site as nasal, oral, and lower respiratory tract (LRT) specimens for virus-specific analyses. Overall performance and statistical validity were evaluated by hierarchical summary receiver operating characteristic (HSROC) analysis. Data regarding sampling tolerability was also assessed. We screened 2,448 studies and identified 36 publications (total N participants = 10,687) that reported diagnostic test accuracy using paired index-reference data in children. Of these, 18 (total N participants = 4,310) used NP specimens as the reference and were included in the diagnostic test accuracy analysis. Virus-agnostic pooled sensitivity estimates indicated that MT (0.92%) performed most similarly to NP, though sensitivities of ANS (0.79%) and OP (0.70%) were also moderately high for detection of any respiratory virus. BAL sensitivity was the lowest (0.37%). All sample types demonstrated high specificity (0.98%-0.99%). Group estimates and HSROC statistics found that nasal specimens, when grouped, had the highest sensitivity and accuracy for all examined viruses, including for influenza (92%) and RSV (90%). By comparison, oral and LRT specimens performed less well, with more variability, though both showed moderately high sensitivities for RSV (78%, 76%, respectively) and influenza (82%, 80%, respectively), and LRT samples showed high sensitivity for HMPV (82%). Analysis of sample tolerability found that NP swabs consistently ranked as the least comfortable and least preferred, while nasal swabs and saliva both performed well. Datasets for LRT and oral specimens were sparser than for nasal, and this contributed to greater variability, underscoring the need for further diagnostic accuracy studies on alternatives to NP sampling. These data support the viability of nasal and oral alternatives to NP swabs and affirm their application in pediatric care, particularly in outpatient settings. Such alternatives could greatly improve sampling tolerability and increase global access, including in resource-limited settings, to accurate diagnostic methods for respiratory infections.

Aim: Cross-sectional summaries of periodontitis based on clinical attachment loss (CAL) are, by definition, conditioned on surviving teeth. Because the most severely affected teeth are more likely to have been lost, these measures may underestimate cumulative disease burden and show an artificial flattening (attenuation) of severity with age. We hypothesised that measures more sensitive to severe attachment loss would show greater attenuation at older ages than measures defined across a broader range of sites. Materials and Methods: Using nationally representative data from adults aged 30+ years in NHANES 2009-2014, we examined age-specific trajectories across multiple continuous measures of periodontal severity and assessed whether divergence between measures followed the pattern predicted under severity-dependent tooth loss. Results: The proportion of observable sites declined from 93% at ages 30-34 to 68% at 80+ years, establishing the structural basis for the divergence observed across severity measures. All severity measures showed nonlinear attenuation with age, with distortion increasing with severity threshold. Higher-threshold measures exhibited the greatest attenuation, while lower-threshold measures showed more stable trajectories. Conclusions: Cross-sectional summaries of periodontitis reflect disease among surviving teeth rather than cumulative damage across teeth originally at risk. Attenuation at older ages is consistent with depletion of the most severely affected teeth rather than biological slowing. Distortion varies by measure, with higher-threshold and mean-based indices most affected, whereas the CAL 3+ mm threshold provides a more stable basis for age comparisons.

Background One in four surgical patients carries a drug allergy label, of which an estimated 90% are incorrect. Avoidance of first-choice drug therapies may lead to worse postoperative outcomes. We sought to determine the nature and extent of any association between drug allergy labels and postoperative complications. Methods A multicentre observational study in 21 NHS hospitals. Eligible patients were 18 years or older, undergoing common surgical procedures: primary hip or knee replacement; internal fixation of closed long bone fracture; colorectal resection; trans-urethral resection of prostate or bladder tumour; caesarean section; hysterectomy. Exclusion criteria: use of antibiotics in the two weeks prior to surgery, previous participation in the study. Primary outcome was postoperative complications within 30 days following surgery, a composite outcome comprising: all postoperative infections, anastomotic leak, acute respiratory distress syndrome, myocardial infarction, postoperative bleed, pulmonary embolism, stroke, antimicrobial side effects, death. Results Among 13,646 patients, 3924 (29%) carried greater than or equal to1 drug allergy labels. Labelled patients were more likely to develop postoperative complications (989/3924 (25%) vs 1926/9722 (20%); OR 1.21 [1.10-1.34]; p<0.001). They were more likely to develop surgical site infections (337/3924 (9%) vs 760/9722 (8%); OR 1.19 [1.03 -1.38]; p<0.018), and any postoperative infection (750/3924 (19%) vs 1472/9722 (15%); OR 1.24 [1.11-1.38] p<0.001). Labelled patients experienced increased risk of allergic drug reactions (31/3924 (0.01%) vs 29/9722 (<0.01%); OR 3.00 [1.77-5.09]; p<0.001), but no increase in mortality. Conclusions Drug allergy labels are common, but often incorrect. Labelled patients experience worse postoperative outcomes, including infective and non-infective complications and increased risk of allergic drug reactions. Trial registration Registered with ISRCTN registry, ISRCTN15775657.

Background: Colon capsule endoscopy (CCE) has been proposed as a non-invasive alternative to colonoscopy for colorectal cancer (CRC) screening, offering greater patient comfort and potentially reducing healthcare burden. However, its cost-effectiveness in population-based screening remains uncertain. Methods: This study used a state-transition (Markov) model to simulate lifetime outcomes of CRC screening in Denmark, Scotland, and Spain, comparing the standard pathway based on fecal immunochemical testing (FIT) followed by colonoscopy with an alternative pathway replacing colonoscopy with CCE after a positive FIT result. The model incorporated costs (2024 euros), quality-adjusted life-years (QALYs), and CRC cases avoided, applying a yearly discount rate of 3%. Deterministic sensitivity analyses explored uncertainty in capsule cost, adherence, and reinvestigation rates for non-advanced polyps. Results: Across all settings, CCE resulted in higher costs but slightly increased effectiveness and utility (mean QALYs 28.7 vs. 28.8; CRC detected 0.032-0.034 vs. 0.035-0.037 per person). Incremental cost-effectiveness ratios (ICER) ranged from 43,538EUR in Spain to 136,930EUR in Denmark per additional CRC detected. Capsule cost was the main driver of ICER variation, whereas adherence rates had minimal effect on cost-effectiveness. Changes in the prevalence of non-advanced polyps had a modest impact, except when capsule prices were high. Conclusions: Overall, replacing colonoscopy with CCE slightly increases detection and health gains at the expense of higher costs. Cost-effectiveness largely depends on capsule price and adherence. Artificial intelligence-assisted CCE interpretation may further improve diagnostic and economic performance, potentially supporting adoption in large-scale CRC screening programs.

Introduction. Lateral flow assays (LFAs) are indispensable rapid diagnostic tools in healthcare, enabling point-of-care diagnosis critical for patient management and support disease burden assessment and surveillance when results are properly recorded. However, misinterpretation errors and unreported cases remain a concern. A quality-assured, affordable Ai-powered tool, supporting the decision-making during result interpretation could promote proper disease monitoring and epidemiological surveillance. Here, we describe the performance of a universal AI model to digitize and interpret results from multiple LFA types through a smartphone application, a step that could ultimately enable standardized and digitally reportable test outcomes. Methods. The AI algorithm was evaluated in 17 LFA types, including both 2-band and 3-band tests for different diseases and manufacturers. The model was trained on a dataset of 22,576 images captured under diverse lighting conditions with different smartphone models and using a custom mobile application, TiraSpot (Spotlab, Madrid, Spain). To assess generalizability, a leave-one-out cross-validation was applied, where in each LFA type was iteratively excluded from training and used for testing. Model performance was evaluated using bootstrapping on the inference dataset. Results. In the assessment of the model's ability to generalize to new LFA types not previously analyzed (not included during development), the model achieved an overall AUC of 94.3% for second band detection. This overall performance was enhanced to 99.3% (Sensitivity=98,6%; Specificity=98%) after training with 50 images of each LFA type, highlighting the benefit of additional data for specific LFA types. For the third band detection, where less training data was available, the system achieved an overall AUC of 83.9% for unseen LFAs, improving to 94.2% (Sensitivity=92.9%; Specificity=87,9%) after training with 50 images of each LFA type. Conclusion. This system demonstrates the feasibility of an AI-powered universal digital reader for interpreting LFA results from diverse test types using smartphone-captured images. Its compatibility with standard smartphones makes it a universal tool, enabling reliable LFA interpretation across devices and settings. By standardizing test interpretation and digitizing results, this tool could support decision making in result interpretation, enhancing epidemiological surveillance, particularly in resource-limited settings. Its adaptability across various infections highlights its potential to improve diagnostic consistency and support disease management in diverse healthcare settings.

Background. Respiratory complaints account for a substantial share of adult ambulatory care visits, and triaging them accurately has direct consequences for antibiotic stewardship and pathogen-specific therapy. Prior work has investigated voice as a triage signal, but that literature is dominated by single-condition detection from scripted speech in crowdsourced or controlled clinical settings and has not been evaluated at primary care scale on conversational ambient audio. Methods. A dataset of 514,377 ambient-recorded primary care visits from 379,225 adult patients at a US clinic network was used, with per-visit clinically assigned ICD-10 diagnosis codes and de-identified demographic and geographic metadata. Patient audio was extracted from each doctor-patient conversation, and spectral, voice quality, and prosodic features were computed. Eleven binary classification tasks were defined, aligned with a respiratory triage cascade (e.g., acute respiratory versus acute non-respiratory illness, and lower versus upper respiratory tract infection). An acoustic model (feed-forward network) was trained independently for each task using patient-stratified five-fold cross-validation and evaluated on a held-out test set. Each task's model was also compared against six non-acoustic baselines using a single demographic, geographic, or temporal variable. The 11 trained classifiers were composed into a hierarchical cascade and illustrated as case studies on selected patients. Results. Test-set AUC across the 11 tasks ranged from 0.602 (95% CI: 0.588-0.614) to 0.745 (95% CI: 0.742-0.748), with a mean expected calibration error of 0.018. Six of eleven binaries outperformed all confounder baselines. Four binaries showed median within-stratum AUC of 0.62-0.70 when the confounder was held fixed, indicating acoustic discrimination beyond what the confounder alone explains. The exception was the pneumonia versus non-pneumonia lower respiratory tract infection binary, which failed against the patient-city confounder baseline, plausibly reflecting a clinic-level difference in ICD-10 coding. Conclusion. Conversational primary care audio carries acoustic signal that discriminates clinically meaningful respiratory contrasts. Absolute performance is moderate, but the conditions are stricter than prior work: conversational speech and differential-diagnosis contrasts among sick patients. This pilot study is a baseline for voice-based clinical AI moving beyond sick-versus-healthy detection toward differential-diagnosis panels and a proof-of-concept for hierarchical reasoning.

Background: Wide-spread mast cell (MC)-associated symptoms and MC activation syndrome (MCAS) are often reported in patients with hypermobile Ehlers-Danlos syndrome (hEDS) and hypermobility spectrum disorders (HSD). The goal of this study was to develop a novel MC score based on 11 self-reported MC-related conditions with clinical and research utility to better understand MC symptoms in hEDS and HSD patients. Methods: From November 1, 2019, to June 13, 2025, patients (n=2,141) filled out an Intake Questionnaire at the Mayo Clinic Florida EDS Clinic that included 11 self-reported questions related to categories of MC-related conditions for a MC score ranging from 0/11 to 11/11. Based on the MC score distribution in hEDS and HSD patients, a MC score of 0-1 was considered a low MC score and [&ge;]5 was considered a high MC score. Symptoms/comorbidities were compared between patients with high vs. low MC scores. Results: From the 2,141 hEDS/HSD patients, 535 (25.0%) had a MC score [&ge;]5 (Hi MC). MCAS-specific symptoms such as nausea and vomiting were reported more often in hEDS/HSD patients with a high vs. low MC score (p<0.0001). Random clinical blood tryptase and urinary MC markers were not elevated in patients with high MC scores (n=50/group), although high MC scores were found to significantly reduce urinary creatinine levels indicating that the protein used to normalize data was affected by MC activity. In contrast, random blood IgE, tryptase and major basic protein (MBP) by ELISA were increased in patients with high MC scores (e.g., IgE hEDS p=0.0004, HSD p=0.003). Of note, the percentage of patients reporting abuse or post-traumatic stress disorder was nearly doubled in patients with high vs. low MC scores (Abuse and PTSD: hEDS p < 0.0001; HSD p < 0.0001). Overall, 109/135 (80.7%) in hEDS and 129/135 (95.6%) in HSD reported more symptoms/comorbidities if they had a high MC score. Conclusions: We found that hEDS/HSD patients with high MC scores self-reported more widespread symptoms/comorbidities and higher MC-related blood markers than patients with low MC scores indicating the utility of this tool to evaluate the level of widespread MC activity in hEDS, HSD and other patients.

Introduction: Trans and gender-diverse (TGD) individuals often face stigma and discrimination in healthcare, hindering access to gender-affirming care. Training healthcare workers on TGD health aims to foster inclusive and affirming care practices. This review aimed to evaluate the effectiveness of TGD health training programs for healthcare workers. Methods: This systematic review followed the PRISMA guidelines and was registered with PROSPERO (CRD42023443288). We searched 13 databases for studies up to March 2024, with no language/geographic restrictions. Ten reviewers screened studies in pairs, resolving discrepancies via discussion or third-reviewer input. We included randomized/non-randomized comparative and before-after studies for quantitative analysis (mean difference [MD] or standardized mean difference [SMD] with 95% CIs) and qualitative/mixed-methods studies for thematic synthesis. Evidence certainty was assessed using GRADE (quantitative) and GRADE-CERQual (qualitative). Outcomes included knowledge, attitudes, skills, discrimination, competence, comfort, TGD quality of life, and stakeholder preferences. Results: From 20,188 records, 85 studies were included. Training appears to have improved healthcare workers' knowledge (SMD=1.08, 95% CI 0.78-1.39), attitudes (SMD=0.22, 95% CI 0.05-0.39), skills (SMD=0.96, 95% CI 0.56-1.37), competence (SMD=0.55, 95% CI 0.29-0.81), and comfort (SMD=0.69, 95% CI 0.17-1.21). Qualitative analysis of 130 findings identified 18 categories and four key themes on intervention design and impact. Conclusions: TGD training programs may enhance health workers' knowledge, attitudes, skills, competence, and comfort. Well-structured, interactive, and inclusive programs showed promise, but evidence certainty was low with limited follow-up. Further high-quality research is needed to confirm these findings.

Background: Higher education has been transformed by the rapid integration of generative artificial intelligence (GenAI) tools into academia. The objective of the present study was to examine how and for what purposes senior undergraduate dental students use GenAI tools in academic assignments. Methods: This cross-sectional study uses data from three written assignments submitted by two consecutive cohorts of graduating fourth-year dental students at the Faculty of Dentistry at the University of British Columbia, for a total of 120 students. The assignments focused on different subjects where students had to offer their views, including community water fluoridation. When using GenAI, students were asked to disclose whether and how such tools were used, and for what purpose. Descriptive statistics (e.g., means, frequencies, and proportions) were conducted via IBM SPSS Statistics (Version 27.0). Results: From the two cohort of students, 102 (85%) disclosed the use of GenAI tools in at least one assignment; of these, 69 (67.6%) reported using these tools in all three assignments. ChatGPT was by far the most frequently used GenAI tool, reported by 89 students (87.2%). Nine students (8.8%) did not specify which tool they had used. The majority of the students (91.2%, n = 93) reported using GenAI for proofreading or grammatical editing. About 9.8% of the students (n = 10) reported more substantive uses, such as relying on GenAI to generate in part or in full the assignment, and/or assessing the credibility of references. Conclusions: In our study, the use of GenAI tools was highly prevalent among senior undergraduate dental students for editorial purposes. A smaller but notable proportion of students engaged in more substantive uses that may carry academic and ethical risks. There is a need for structured AI literacy training and clear, dentistry-specific guidelines to promote responsible and transparent use while safeguarding critical thinking, academic integrity, and professional judgment in dental education.

Introduction: Differentiated service delivery (DSD) models aim to reduce time healthcare providers spend with DSD clients, increasing time available for non-DSD clients. We measured nurses' time allocation and explored their experiences with DSD models in South Africa. Methods: We conducted time and motion observations and surveyed nurses at 24 public primary healthcare facilities across two SENTINEL study rounds (09/2022-07/2023 and 11/2023-07/2024). We report median time nurses spent by activity, model of care, and interaction type. Log binomial regression investigated factors associated with high direct nurse-client interaction (above median minutes) and extended work-days ([&ge;]9 hours), and estimated adjusted risk ratios (aRR). Survey questions were related to client care, additional time availability, and policy changes post DSD implementation, with key themes presented alongside illustrative quotes. Results: 176 nurses (88% female, median age 44) were observed for 344 working days; of these, 60 (34%) participated in the provider survey. Nurses spent a median of 293 minutes (53% of their work-day) on direct nurse-client interaction, 89 minutes (22%) on client-support or facility-related tasks, and the remainder on other activities including personal breaks. Time spent per client was similar across conventional care clients (11 [IQR: 8-15] minutes) but ranged between 9 (7-13) to 11 (8-15) minutes for DSD clients; number of direct nurse-client interactions did not differ meaningfully. Nurses at facilities with 2,000-3,999 total remaining on ART (TROA) (aRR 1.56, 95% CI: 1.02-2.37) and in urban areas (aRR 1.43, [1.08-1.89]) had more direct nurse-client interactions than those at facilities with <1,999 TROA and in rural areas, respectively. Nurses at facilities with 4,000+ TROA (aRR 2.22, [1.36-3.63]) and those observed in SENTINEL 3.0 (aRR 1.53, [1.13-2.07]) were more likely to work standard or longer workdays than those at lower TROA facilities (<1,999), those in SENTINEL 2.0 and urban areas. Nurses reported DSD models improved client care (90%), freed up time (60%), and changed clinic procedures and policies (60%). Conclusions: While DSD models did not significantly reduce direct nurse-client interaction time, nurses reported improved client care and gained additional time. DSD impact may vary by facility context. As DSD implementation expands, effective time reallocation may enhance facility performance and provider productivity.

Background: Advanced HIV disease (AHD) remains a major contributor to HIV-related morbidity and mortality despite widespread antiretroviral therapy (ART) access in sub-Saharan Africa. Although treatment-related adverse drug reactions (ADRs) may compromise treatment outcomes, evidence on the relationship between AHD and ADR occurrence remains limited. This study aimed to determine the prevalence and identify factors associated with AHD, characterize treatment-related ADR and assess the association between AHD and ADR occurrence among people living with HIV receiving ART in Dar es Salaam, Tanzania. Methods: We conducted a multicenter cross-sectional study among 1,513 people living with HIV receiving ART at selected HIV care and treatment clinics in Dar es Salaam, TanzaniaFor this adolescent/adult cohort, AHD was operationally defined as WHO clinical stage III/IV disease and/or baseline CD4 count <200 cells/mm3. Treatment-related ADRs were defined as participant-reported and/or clinically documented ART-related adverse events identified during routine HIV care, including both current and retrospectively reported events. Modified Poisson regression with robust standard errors was used to estimate crude and adjusted risk ratios (RRs) with 95% confidence intervals (CIs). Results: Among 1,508 participants with sufficient information for classification, 961 (63.7%) had AHD. Factors independently associated with AHD included age [&ge;]50 years (aRR 1.10, 95% CI 1.01-1.20), underweight nutritional status (aRR 1.17, 95% CI 1.00-1.35), and concomitant medication use (aRR 1.19, 95% CI 1.03-1.37), while DTG-based ART was associated with lower AHD prevalence (aRR 0.78, 95% CI 0.68-0.90). Overall, 569 participants (38.0%) reported at least one ADR. Composite AHD was not independently associated with ADR occurrence (aRR 0.95, 95% CI 0.82-1.11), but baseline CD4 <200 cells/mm3 was associated with increased ADR risk (aRR 1.20, 95% CI 1.02-1.41). Comorbidity (aRR 1.66, 95% CI 1.42-1.93) was the strongest correlate of ADR occurrence. Conclusion: AHD remains highly prevalent among people living with HIV receiving ART in Tanzania. While composite AHD was not independently associated with ADR occurrence, severe immunosuppression, comorbidity burden, and concomitant medication exposure were associated with increased ADR risk. These findings suggest that immunologic severity and broader clinical complexity may be more informative predictors of ART-related toxicity than composite syndromic AHD classification alone. Strengthened early diagnosis, differentiated advanced HIV care, integrated pharmacovigilance strategies, and routine medication risk assessment are needed.

Introduction Viral load monitoring is central to assessing antiretroviral therapy (ART) effectiveness, yet timely access remains challenging in resource-constrained settings. Point-of-care (POC) triage tests may improve ART monitoring efficiency by identifying clients requiring confirmatory viral load testing while reducing unnecessary testing among those likely to be virally suppressed. We explored perceptions of integrating a POC triage test that measures interferon-gamma-induced protein 10 (IP-10) - a chemokine strongly correlated with HIV viral load - into routine ART monitoring among people living with HIV (PLHIV) on ART, healthcare providers, and HIV programme stakeholders. Methods This qualitative study was nested within a clinical evaluation of the IP-10 POC triage test in two primary healthcare facilities in Maputo Province, Mozambique (2023-2024). We conducted three rounds of interviews with PLHIV on ART who underwent IP-10 testing, and one-off interviews with healthcare providers and HIV programme stakeholders across different health system levels. PLHIV were purposively sampled to capture diverse IP-10 and viral load outcomes. Interviews explored experiences of ART monitoring, perceptions of the IP-10 POC test, and implementation considerations. Data were analysed thematically using an inductive-deductive approach. Results Routine viral load monitoring was widely valued and understood as essential for treatment adherence and effectiveness, but participants described barriers including laboratory delays, access challenges, and health system constraints. The IP-10 POC triage test was broadly acceptable; same-day results were perceived to reduce anxiety, support adherence, and enable timely clinical decision-making. Providers and stakeholders emphasised its potential to improve monitoring efficiency by prioritising clients who require confirmatory viral load testing and adherence support. Concerns were raised regarding test accuracy and the need to maintain confirmatory viral load testing, underscoring the importance of clear communication and client education. Successful implementation would require training, workflow integration, and quality assurance. Conclusions An IP-10 POC triage test could strengthen ART monitoring by enabling same-day identification of clients requiring confirmatory viral load testing and targeted adherence support. By reducing unnecessary viral load testing for virally suppressed clients, it may contribute to more efficient monitoring and support differentiated care approaches. Careful integration into existing ART monitoring algorithms will be critical to maximise impact.

Delayed diagnosis and poor antiretroviral therapy (ART) adherence remain primary drivers of HIV-related morbidity in low-resource settings, yet real-world AI validation at scale is lacking. We conducted a retrospective validation study using two publicly available, de-identified datasets: a Quality of Care cohort of 27,288 HIV-positive patients on ART across multiple healthcare facilities, and the CEPHIA multi-country assay database comprising 165,444 specimen records from six countries. Four machine learning classifiers were evaluated using 10-fold stratified cross-validation with SMOTE applied strictly to training folds. Explicit data leakage prevention, ablation analysis, calibration assessment, and bootstrap confidence intervals were applied. Economic projections used one-way sensitivity analysis. This study adheres to TRIPOD reporting guidelines. Random Forest achieved AUC-ROC of 0.9753 (95% CI: 0.970-0.975), sensitivity 87.3% (95% CI: 86.4-88.2%), specificity 95.7% (95% CI: 95.2-96.2%), and Brier score 0.079. Ablation testing confirmed robustness (AUC 0.963 without the primary predictor). Temporal validation on held-out future patients yielded AUC 0.772 (95% CI: 0.744-0.802), confirming generalisation across time. Real-world analysis revealed median diagnosis-to-ART delay of 74 days, with 47.3% of patients exceeding 90 days and 36.7% presenting with CD4 below 200 cells per microlitre. Multi-country CEPHIA analysis identified 18.6% HIV recency within the 130-day early-intervention window. Decision curve analysis confirmed net clinical benefit across threshold probabilities 0.03-0.45. Subgroup analysis demonstrated consistent AUC across sex, age, CD4 strata, and WHO staging (max difference 0.051). Economic modelling projected base-case savings of USD 415 per patient (USD 2.07 million per 5,000-patient cohort). These findings provide large-scale empirical evidence that AI-driven informatics can predict ART adherence failure and quantify systemic care gaps, offering a scalable framework for equitable HIV care delivery in resource-limited settings. Prospective external validation is required before clinical deployment.

Background: Olfactory dysfunction (OD) in children remains underdiagnosed and poorly characterised. Despite its known impacts on nutrition, quality of life, safety awareness, and psychosocial development, no standardised diagnostic or management pathway currently exists for paediatric OD. This study aimed to characterise global practice patterns and identify diagnostic and therapeutic challenges unique to paediatric care. Methodology/Principal: A 44-item cross-sectional online survey was distributed to a verified international network of paediatric otolaryngologists across 36 countries via a closed professional platform. The survey assessed five domains: diagnostic practices, management protocols, technology and innovation, education and training, and barriers to effective care. Regional grouping was used to facilitate meaningful statistical comparisons. Categorical variables were evaluated using chi-square tests, with odds ratios and 95% confidence intervals reported for significant findings. Results: Of 351 potential participants, 167 responded (47.6% response rate). Most respondents (83%) reported seeing children with OD, yet 95% saw fewer than ten such patients annually. Psychophysical testing was never performed by 54.8% of respondents, while 88.4% routinely ordered cross-sectional imaging. Testing frequency increased significantly with patient age (Cochran's Q p<0.001). The most common barriers to objective testing were insufficient training (44.3%), time constraints (29.9%), and funding limitations (28.1%). Multidisciplinary collaboration was negligible. Significant regional variation was observed across most practice domains. Conclusions: Paediatric OD care is characterised by functional underinvestigation, fragmented multidisciplinary collaboration, and systemic educational gaps. These findings support urgent development of standardised clinical guidelines, age-appropriate validated assessment tools, and formal interdisciplinary care pathways.

Patients with primary immunodeficiency (PID) often face prolonged diagnostic delays and may increasingly turn to large language models (LLMs) to interpret their symptoms during this period. We evaluated whether an LLM could recognize PID from symptom descriptions derived from interviews with 21 PID patients. In a prior study, we showed that GPT-4o identified PID in 96% of cases when prompted with physician-written patient histories (Rider et al., JACI, 2024). Here, when prompted with symptom descriptions in patients' own words, GPT-5 identified PID in only 7 cases (33%), although it more broadly suggested immune system issues in 18 cases (81%). The gap between these findings indicates that LLMs are sensitive to the language and framing of symptom descriptions, performing substantially worse when patients describe their own symptoms in everyday language than when clinicians summarize patient histories in structured medical terms. This study underscores the need to carefully evaluate how LLMs are used in patient-facing applications.