Tag: nevin manimala

Am J Trop Med Hyg. 2026 Feb 24:tpmd250662. doi: 10.4269/ajtmh.25-0662. Online ahead of print.

ABSTRACT

Rheumatic manifestations are the third most common clinical features of Hansen’s disease (HD), after cutaneous and neurological involvement. However, few studies have systematically characterized these manifestations, and most lack appropriate controls and standardized assessments. To address this gap, the present cross-sectional study was conducted to evaluate the rheumatic manifestations associated with HD. The study included 23 patients with HD and 23 age- and sex-matched non-HD controls from Puerto Rico. All participants underwent a standardized evaluation and examination for rheumatic features. Demographic data, clinical manifestations, comorbidities, and pharmacologic treatments were documented. Statistical analyses were performed using bivariate methods. The mean (SD) age of HD patients was 51.3 (15.7) years, and 60.8% were female. Regarding treatment status, 8.7% had received <1 year of multidrug therapy (MDT), 8.7% had received at least 1 year of MDT, and 82.6% had completed therapy. Overall, 87% of HD patients presented with rheumatic manifestations, most commonly arthralgia (73.9%) and arthritis (69.6%). Compared with controls, HD patients exhibited a significantly higher proportion of arthritis, particularly involving the small joints of the hands, as well as tendinopathy, dactylitis, and swollen hand and foot syndrome. These manifestations were significantly associated with leprosy reactions and multibacillary disease. In conclusion, rheumatic manifestations were present in 87% of HD patients, with several being significantly more frequent than in controls. Moreover, a substantial proportion of patients continued to experience persistent rheumatic manifestations despite receiving or completing MDT. Given their potential to substantially impair functional status, these manifestations should be recognized early to ensure timely and appropriate management.

PMID:41734397 | DOI:10.4269/ajtmh.25-0662

Am J Trop Med Hyg. 2026 Feb 24:tpmd250558. doi: 10.4269/ajtmh.25-0558. Online ahead of print.

ABSTRACT

Urinary tract infections (UTIs) are a global health concern exacerbated by rising antimicrobial resistance (AMR), especially in developing countries where empirical therapy is common. Untreated UTIs can progress to sepsis with a poor prognosis. Understanding local AMR profiles of uropathogens is crucial for effective UTI treatment. This study aimed to identify the predominant uropathogens and determine their AMR profiles against a range of commonly used antimicrobials. This study was a 5-year retrospective cross-sectional surveillance study conducted on urine cultures processed from January 1, 2020 to December 31, 2024 at the University Teaching Hospital of Kigali. In total, 2,921 positive urine cultures and their antimicrobial susceptibility testing results were recorded and analyzed by pathogen and across care settings. Descriptive statistics were used to summarize the data. Associations were evaluated at a 5% significance level. This study found that among 2,921 isolates, Escherichia coli (64%) and Klebsiella pneumoniae (22.9%) were the predominant uropathogens. High resistance rates were observed against commonly used antibiotics, such as amoxicillin-clavulanic acid (>88%), third-generation cephalosporins (51-75%), and fluoroquinolones (∼55%) in both species, with K. pneumoniae showing a more extensive resistance profile. Conversely, the isolates were less resistant to carbapenems (imipenem and meropenem) and amikacin (<20%) across care settings. The findings reveal a significant burden of multidrug-resistant gram-negative pathogens at the University Teaching Hospital of Kigali, underscoring the urgent need for enhanced antimicrobial stewardship and sustained surveillance. Such measures are essential to preserve the efficacy of critical antibiotics, particularly carbapenems and aminoglycosides, and to guide effective clinical management.

PMID:41734396 | DOI:10.4269/ajtmh.25-0558

J Clin Psychiatry. 2026 Feb 18;87(1):25m16125. doi: 10.4088/JCP.25m16125.

ABSTRACT

Objective: This study describes recent trends in benzodiazepine prescribing to US adults and characterizes patients who receive benzodiazepines and other central nervous system (CNS) depressants.

Method: This repeated cross-sectional study analyzed benzodiazepine use by adults (ages ≥18 years) in the 2018-2022 Medical Expenditure Panel Surveys, which are nationally representative surveys of the civilian noninstitutionalized population. We examined sex-adjusted annual trends (2018-2022) in benzodiazepine use by age group (ages 18-35, 36-55, and ≥56 years) and pooled marginal differences by age group in any benzodiazepine use and in benzodiazepine use and other CNS-depressant medications, stratified by sociodemographic and clinical characteristics.

Results: The analysis involved 104,231 participants. Between 2018 and 2022, annual benzodiazepine use by US adults decreased from 4.7% to 3.4%. This included a greater decrease for adults ages ≥56 years (7.2% to 4.7%) than for those ages 36-55 years (4.4% to 3.4%) or 18-35 years (2.1% to 1.8%). Approximately 41.6% adults treated with benzodiazepines also received other CNS-depressant medications in the same year including a higher percentage aged 36-55 years (44.6%) or ≥56 years (42.9%) than 18-35 years (30.0%). Most benzodiazepine-treated adults with fair or poor general health (72.0%) or with serious psychological distress (62.9%) also received other CNS-depressant medications.

Conclusions: Benzodiazepine treatment decreased among US adults between 2018 and 2022, with a greater decline among adults ≥56 years than those 36-55 or 18-35 years. Prescription of benzodiazepines to adults who also received other CNS depressants was common, especially among adults in fair or poor general health or with serious psychological distress.

PMID:41734365 | DOI:10.4088/JCP.25m16125

JMIR Form Res. 2026 Feb 24;10:e79978. doi: 10.2196/79978.

ABSTRACT

BACKGROUND: Rare genetic diseases pose significant diagnostic and therapeutic challenges, often leading to delayed diagnoses, misinformation, and patient isolation. Social media platforms have emerged as prominent spaces for health information dissemination and community building among patients with rare diseases.

OBJECTIVE: This study aimed to evaluate the role of TikTok videos in patient education, community engagement, and information quality related to 5 rare genetic conditions: Ehlers-Danlos syndrome, Marfan syndrome, cystic fibrosis, Wilson disease, and Gaucher disease.

METHODS: A cross-sectional analysis was conducted on 184 TikTok videos identified via disease-specific hashtags. Included videos were 15 seconds to 4 minutes long and directly discussed the target diseases. Advertisements, promotional content, and product marketing were excluded. Videos were categorized by creator type: physicians, medical professionals, patients, influencers, nonprofit organizations, and others. Content quality was assessed using the Global Quality Scale (GQS) and a modified DISCERN tool (mDISCERN). Engagement metrics (views, likes, and shares) were recorded. Kruskal-Wallis and chi-square tests evaluated differences across creator categories.

RESULTS: Of the 184 TikTok videos, 88 (47.8%) were created by patients or family members; 31 (16.8%) by influencers, 24 (13.0%) by physicians, 17 (9.2%) by nonprofit organizations, 15 (8.2%) by general users, and 9 (4.9%) by others. Collectively, the videos amassed more than 123 million views. Influencer-generated content accounted for the highest cumulative view count, totaling approximately 60.9 million views. Content produced by medical professionals and physicians demonstrated higher information quality, with mean GQS scores of 3.89 (SD 0.66) and 3.62 (SD 0.71) and mDISCERN scores of 3.11 (SD 0.58) and 3.21 (SD 0.65), respectively. In contrast, videos by influencers and patients exhibited lower quality scores (influencers: GQS mean 1.48, SD 0.60; mDISCERN mean 1.42, SD 0.55; patients: GQS mean 1.57, SD 0.58; mDISCERN mean 1.38, SD 0.52). For Ehlers-Danlos syndrome (n=40 videos, 21.7%), Wilson disease (n=40 videos, 21.7%), and cystic fibrosis (n=34 videos, 18.5%), significant differences in quality scores among creator types were observed (P<.001, P<.001, and P≤.04, respectively). For Marfan syndrome (n=40 videos, 21.7%) and Gaucher disease (n=30 videos, 16.3%), no significant differences were observed (P=.43 and P=.07, respectively). Chi-square analysis indicated no association between creator type and inclusion of peer-reviewed references (χ25=10.6; P=.07). Overall, only 7 (3.8%) videos cited scientific literature.

CONCLUSIONS: TikTok serves as a key platform for rare disease awareness and community engagement, although the quality and accuracy of health information vary widely. Although medical professionals produced higher-quality content, it tended to receive less visibility. Increasing the presence of health care professionals and improving visibility of evidence-based content could enhance patient education and safer health information sharing.

PMID:41734363 | DOI:10.2196/79978

J Clin Oncol. 2026 Feb 24:JCO2501796. doi: 10.1200/JCO-25-01796. Online ahead of print.

ABSTRACT

PURPOSE: Transarterial chemoembolization (TACE) alone has shown limited efficacy in improving survival among patients with unresectable hepatocellular carcinoma (HCC). This phase II trial compared TACE combined with camrelizumab (anti-PD-1 antibody) and rivoceranib (vascular endothelial growth factor receptor 2 inhibitor) versus TACE in unresectable HCC.

METHODS: Patients with unresectable HCC (Barcelona Clinic Liver Cancer stage A to C without extrahepatic metastases) and Child-Pugh class A liver function were randomly assigned (1:1), stratified by macrovascular invasion, previous tyrosine kinase inhibitor treatment, and number of previous TACE procedures, to receive TACE combined with camrelizumab (200 mg once every 3 weeks) and rivoceranib (250 mg once daily; TACE-C-R) or TACE alone. The primary end point was progression-free survival (PFS) per composite criteria (progression per Response Evaluation Criteria in Cancer of the Liver version 5, transient deterioration to Child-Pugh class C, or TACE failure or refractoriness) in the intention-to-treat population.

RESULTS: Between December 28, 2020, and October 29, 2023, 200 patients were randomly assigned (100 in each group). Median PFS per composite criteria was significantly longer with TACE-C-R than with TACE (10.8 months [95% CI, 8.8 to 13.7] v 3.2 months [95% CI, 2.4 to 4.2]; hazard ratio, 0.34 [95% CI, 0.24 to 0.50], P < .001). Grade ≥3 treatment-related adverse events occurred in 74.5% (70 of 94) of patients with TACE-C-R and 22.3% (23 of 103) of patients with TACE, with the most common being increased AST (29 [30.9%] and 13 [12.6%]) and increased ALT (23 [24.5%] and 14 [13.6%]).

CONCLUSION: The addition of camrelizumab and rivoceranib to TACE showed statistically significant improvement in PFS for patients with unresectable HCC, with a manageable safety profile. Follow-up for further overall survival analysis is ongoing.

PMID:41734362 | DOI:10.1200/JCO-25-01796

JMIR Cardio. 2026 Feb 24;10:e82042. doi: 10.2196/82042.

ABSTRACT

BACKGROUND: Mortality prediction in intensive care unit (ICU) patients with ischemic stroke complicated by intracranial artery stenosis or occlusion remains difficult. Conventional scoring systems often lack discriminatory power and fail to provide individualized risk estimates. Machine learning approaches have been increasingly explored to integrate diverse clinical features for prognostic modeling.

OBJECTIVE: This study aims to develop and evaluate machine learning models for individualized mortality prediction in ICU patients with ischemic stroke associated with intracranial artery stenosis or occlusion.

METHODS: Using the Medical Information Mart for Intensive Care IV (MIMIC-IV) database, we conducted a retrospective cohort study including 5280 adult ICU patients identified through International Classification of Diseases, Ninth and Tenth Revision (ICD-9/10) codes. Mortality status was determined based on the presence of a recorded date of death (dod) in the MIMIC-IV database. Patients with a documented dod were classified as deceased, whereas those without a recorded dod were classified as nondeceased. The primary outcome was all-cause mortality as recorded in the MIMIC-IV database, defined by the presence of a documented dod. Patients were randomly split into training (n=3696, 70%) and testing (n=1584, 30%) cohorts. Missing value imputation, correlation reduction, and multistep supervised feature selection (gradient boosting, BorutaShap, recursive feature elimination with cross-validation, LassoCV, and chi-square analysis) were performed exclusively within the training set and subsequently applied to the test set, resulting in 35 retained predictive features. Eight machine learning models-including light gradient boosting machine (LightGBM), Bagging (bootstrap aggregating), random forest, logistic regression, support vector machine, gradient boosting, adaptive boosting, and k-nearest neighbors-were trained with hyperparameter optimization using RandomizedSearchCV. Model performance was evaluated using area under the curve, accuracy, recall, precision, F1-score, and calibration curves. Shapley additive explanations were used for global and individual-level interpretability.

RESULTS: LightGBM, Bagging, and logistic regression demonstrated comparable discrimination, achieving an area under the curve of approximately 0.82-0.83 and accuracy above 73% on the independent test set. LightGBM demonstrated balanced performance (recall 0.70; precision 0.72) and good calibration. Shapley additive explanations analysis identified acute physiology score III, suspected infection, Charlson comorbidity index, age, weight on admission, and red cell distribution width as the most influential predictors. Overall, higher physiological severity, greater comorbidity burden, and older age were consistently associated with increased observed mortality risk.

CONCLUSIONS: Machine learning models-including LightGBM and Bagging-provide interpretable predictions of all-cause mortality in ICU patients with ischemic stroke and intracranial arterial disease. These models highlight key prognostic features and may support mortality risk stratification. External validation and evaluation of workflow integration are warranted before clinical implementation.

PMID:41734354 | DOI:10.2196/82042

JMIR Public Health Surveill. 2026 Feb 24;12:e69133. doi: 10.2196/69133.

ABSTRACT

BACKGROUND: Social determinants of health continue to drive persistent disparities in perioperative care. Our team has previously demonstrated racial and socioeconomic disparities in perioperative processes, notably in the administration of antiemetic prophylaxis, in several large perioperative registries. Given how neighborhoods are socially segregated in the United States, we examined geospatial clustering of perioperative antiemetic disparities.

OBJECTIVE: The study aimed to determine whether disparities in perioperative antiemetic prophylaxis exhibit geographic clustering based on neighborhood-level disadvantage and whether patients from disadvantaged communities are more likely to be undertreated after adjusting for individual postoperative nausea and vomiting risk.

METHODS: We conducted a retrospective cohort study of anesthetic records from the University of Utah Hospital involving 19,477 patients who met the inclusion criteria. We geocoded patient home addresses and combined them with the census block group-level neighborhood disadvantage, a composite index from the National Neighborhood Data Archive. We stratified our patients by antiemetic risk score and calculated the number of antiemetic interventions. We used Poisson spatial scan statistics, implemented in SaTScan (Information Management Services, Inc), to detect geographic clusters of undertreatment.

RESULTS: We identified 1 significant cluster (P<.001) of undertreated perioperative antiemetic prophylaxis cases. The relative risk of the whole cluster was 1.44, implying that patients within the cluster were 1.44 times more likely to receive fewer antiemetics after controlling for antiemetic risk. Patients from more disadvantaged neighborhoods were more likely to receive below-median antiemetic prophylaxis after controlling for risk.

CONCLUSIONS: To our knowledge, this is the first geospatial cluster analysis of perioperative process disparities; we leveraged innovative geostatistical methods and identified a spatially defined, geographic cluster of patients whose home address census-tract level neighborhood deprivation index predicted disparities in risk-adjusted antiemetic prophylaxis.

PMID:41734334 | DOI:10.2196/69133

Med Ultrason. 2026 Feb 12. doi: 10.11152/mu-4589. Online ahead of print.

ABSTRACT

AIMS: The aim of this study was to investigate the differences in clinical and ultrasound findings between alveolar rhabdomyosarcoma (ARMS) and non-ARMS in order to improve the accuracy of preoperative diagnosis of ARMS in children.

MATERIAL AND METHODS: A retrospective study of 33 children with pathologically confirmed RMS (ARMS and non-ARMS groups) was realized. Clinical features and ultrasound parameters were compared between ARMS and non-ARMS using Fisher ‘s exact test analysis. Receiver operating characteristic (ROC) curves and area under the curve (AUC) were used to represent diagnostic performance.

RESULTS: Among the clinical features, there were statistically significant differences between ARMS and non-ARMS groups in site (p=0.020), TNM stage (p=0.007), IRS stage (p=0.009), risk grade (p=0.011), and distant metastasis (p=0.020). There were statistical differences in necrosis (p= p0.039) and central hyperechoic fiber bundles (p<0.001) between the two groups. The combination of ultrasound and clinical characteristics demonstrated excellent predictive ability (AUC was 0.964).

CONCLUSIONS: Children with ARMS more often present with poor prognosis, and combined clinical and ultrasound features are helpful for preoperative identification of ARMS and providing imaging evidence for accurate clinical diagnosis and treatment.

PMID:41734302 | DOI:10.11152/mu-4589

Br J Radiol. 2026 Feb 24:tqag044. doi: 10.1093/bjr/tqag044. Online ahead of print.

ABSTRACT

OBJECTIVES: To evaluate the influence of fat on the assessment of liver fibrosis in chronic liver disease using two-point Dixon water-only Look-Locker T1 mapping by comparing water-only derived sequence (W-Dixon) with in-phase (IP) and opposed-phase (OP)-based sequences.

METHODS: 2.89-T MRI included 2D two-point Dixon Look-Locker T1 mapping and proton density fat fraction (PDFF) mapping. The correlations between liver T1 values and PDFF were assessed using Spearman correlation coefficient. T1 values on each T1 map were compared among three FIB-4 index range groups (FIB-4 < 1.3, 1.3-2.67, > 2.67) in patients with and without hepatic steatosis using one-way analysis of variance and Kruskal-Wallis test.

RESULTS: 204 patients with chronic liver disease were retrospectively evaluated. T1 values on IP or OP images were significantly correlated with PDFF (r = -0.373, 0.220), while no significant correlation was found between T1 values on W-Dixon images and PDFF (r = -0.071). In patients without hepatic steatosis, T1 values on each T1 map in FIB-4 > 2.67 group were significantly higher than in FIB-4 1.3-2.67 group (p < 0.01). Conversely, in patients with hepatic steatosis, only W-Dixon sequence statistically differentiated FIB-4 > 2.67 group from FIB-4 1.3-2.67 group based on T1 values (p < 0.05).

CONCLUSIONS: The assessment of liver fibrosis based on T1 values obtained by Dixon water-only T1 mapping was less influenced by the presence of fat.

ADVANCES IN KNOWLEDGE: Two-point Dixon water-only Look-Locker T1 mapping minimizes the confounding effect of fat, enabling proper assessment of liver fibrosis in steatotic chronic liver disease.

PMID:41734280 | DOI:10.1093/bjr/tqag044

Pain. 2025 Nov 19. doi: 10.1097/j.pain.0000000000003869. Online ahead of print.

ABSTRACT

An estimated 50% to 75% of patients with mild traumatic brain injury (mTBI) report chronic pain. Symptomatology evolution, subtypes, and risk factors remain poorly understood. We evaluated patient-reported pain intensity and interference with daily function in a longitudinal U.S. mTBI cohort. The Transforming Research and Clinical Knowledge in Traumatic Brain Injury Study prospectively enrolled patients with TBI across 18 trauma centers who received head computed tomography (CT) within 24 hours post-injury. Subjects aged ≥17 years with arrival Glasgow Coma Scale = 13 to 15, Marshall CT Score = 1 to 2, and PROMIS-Pain Intensity and Interference assessments at 2 weeks, 3 months, 6 months, and 12 months post-injury were included. Subjects with cranial surgery, major extracranial injury, or pre-injury musculoskeletal pain were excluded. Healthy controls (HCs) completed assessments at all timepoints. Pain assessment T-scores were compared using mixed-effect linear regressions. Adjusted mean differences (aMDs; [95% confidence intervals]) were reported. In 906 subjects (mTBI = 710, HC = 196), mean age was 39.6 ± 16.7-years, 64% were male, and 75% were White/Caucasian. In subjects with mTBI, 35% were CT positive, ≥80% reported pain intensity or interference symptoms at 2 weeks post-injury, and <20% received TBI care postdischarge. Compared with HCs, CT-negative subjects had statistically elevated pain intensity (aMD; 2 weeks: +12.8 [10.9-14.6], 3 months: +4.6 [2.7-6.6], 6 months: +3.4 [1.4-5.4], 12 months: +2.7 [0.7-4.7]) and interference (aMD; 2 weeks: +12.3 [10.7-13.9], 3 months: +4.6 [3.0-6.2], 6 months: +3.1 [1.4-4.8], 12 months: +2.1 [0.4-3.8]). Similarly vs HCs, CT-positive subjects had statistically elevated pain intensity (aMD; 2 weeks: +12.5 [10.4-14.6], 3 months: +3.8 [1.7-5.9], 6 months: +2.8 [0.6-5.0], 12 months: +2.4 [0.2-4.6]) and interference (aMD; 2 weeks: +11.7 [9.9-13.5], 3 months: +4.0, [2.2-5.8], 6 months: +2.9 [1.1-4.7], and 12 months: +2.2 [0.3-4.0]). Pain intensity and daily interference symptoms remained longitudinally elevated in patients with mTBI. The majority did not receive follow-up care for TBI, underscoring opportunities for preventative and therapeutic interventions.

PMID:41734261 | DOI:10.1097/j.pain.0000000000003869