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Nevin Manimala Statistics

Prevalence of Beers Criteria Potentially Inappropriate Medication Use and Associated Factors among Three US Studies

Drugs Aging. 2026 Feb 9. doi: 10.1007/s40266-026-01280-2. Online ahead of print.

ABSTRACT

BACKGROUND: The aim of this study was to assess the prevalence of potentially inappropriate medication (PIM) use among adults ≥ 65 years, overall and for population subgroups, and factors associated with prevalent PIM use.

METHODS: Participant and medications data from the Atherosclerosis Risk in Communities (ARIC), Multi-ethnic Study of Atherosclerosis (MESA), and Action for Health in Diabetes (Look AHEAD) were used. The total number of individuals contributing to analysis was 9439 for ARIC, 5223 for MESA, and 3771 for Look AHEAD. Participants’ medication data were collected at study exams with medication inventories. Prevalence of any PIM use (yes/no), total number of PIMs used, and the major drug classes of PIMs used within a cohort were identified using Beers Criteria closest to the time of study exam (1997 onward) for all participants aged 65 years or older. Multivariable adjusted logistic regression was used to assess demographic and clinical factors associated with prevalence of any Beers Criteria PIM at the first exam after turning 65 years of age, separately for each cohort.

RESULTS: The prevalence of PIM use at the first exam at ≥ 65 years was 67% in ARIC, 51% in MESA, and 70% in Look AHEAD. The most prevalently used PIM classes across cohorts were non-aspirin pain medications, proton-pump inhibitors, and sulfonylureas. Higher body mass index and diabetes were consistently associated with greater odds of PIM use across cohorts.

CONCLUSIONS: Use of potentially inappropriate prescription and nonprescription medications was highly prevalent across three diverse cohorts and highlights the need for clinicians and pharmacists to review patient medication lists and optimize management of medications.

PMID:41661525 | DOI:10.1007/s40266-026-01280-2

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Nevin Manimala Statistics

Emerging resistance to imipenem-relebactam among enterobacterales and non-fermenting gram-negative bacilli: a systematic review and meta-analysis

Infection. 2026 Feb 9. doi: 10.1007/s15010-026-02739-5. Online ahead of print.

ABSTRACT

BACKGROUND: Multidrug-resistant Gram-negative bacteria (GNB), including carbapenem-resistant Enterobacterales and Pseudomonas aeruginosa, pose a growing global health threat with limited treatment options. Imipenem-relebactam (IMI/REL) is a promising therapy, but emerging resistance patterns remain poorly defined worldwide.

OBJECTIVES: This meta-analysis aimed to provide a comprehensive assessment of global IMI/REL resistance among Enterobacterales and non-fermenting GNB, highlighting species-specific, geographic, and temporal patterns.

METHODS: Studies were searched in Scopus, PubMed, and EMBASE (until October 23 2024), and all statistical analyses were conducted using R (ver. 4.2.1).

RESULTS: A total of 149,396 Enterobacterales and non-fermenting GNB were included. Overall, IMI/REL resistance was low at 8.8% (95% CI 7.3-10.5), with Enterobacterales showing the lowest resistance (2.9%) and Pseudomonas the highest (30.7%). Resistance was higher in carbapenemase-producing Enterobacterales and non-fermenting species, and varied by infection source and geography. Temporal analysis indicated a rising trend in resistance over recent years, while data were mostly derived from the Americas, limiting global generalizability.

CONCLUSION: IMI/REL remains largely effective against Enterobacterales, including ESBL and MDR strains, but resistance is increasing in high-risk subgroups and non-fermenting bacteria. These findings underscore the need for local susceptibility testing, cautious empiric therapy, and robust antimicrobial stewardship to preserve the efficacy of IMI/REL.

PMID:41661521 | DOI:10.1007/s15010-026-02739-5

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Nevin Manimala Statistics

Molecular Diagnostics in Hand Dermatoses: Clinical Findings and Health-Related Quality of Life in a 3-Year Follow-Up Cohort Study

Dermatol Ther (Heidelb). 2026 Feb 9. doi: 10.1007/s13555-026-01663-8. Online ahead of print.

ABSTRACT

INTRODUCTION: Hand eczema and psoriasis present overlapping clinical features, complicating diagnosis and treatment selection. Traditional diagnostic methods rely on clinical assessment, patient history, allergy testing, and histopathology. However, recent advancements in molecular diagnostics offer promising alternatives. Accurate diagnosis is crucial for optimal therapy selection, particularly in occupational dermatology, where hand eczema is a common occupational disease.This study aims to assess the effectiveness of molecular diagnostics in distinguishing hand eczema from psoriasis, analyze disease severity and chronicity, and evaluate therapeutic changes and health-related quality of life (HrQoL) over a 2-year period.

METHODS: A long-term cohort study was initiated in November 2020, enrolling 287 patients with suspected occupational skin disease. Molecular classification based on gene expression (CCL27 and NOS2) was performed on skin biopsies. Data collection included physician global assessment (PGA), Quality of Life in Hand Eczema Questionnaire (QOLHEQ), and Dermatology Life Quality Index (DLQI). Statistical analyses employed Cohen’s kappa, χ2 tests, Wilcoxon signed-rank tests, and 95% confidence intervals.

RESULTS: Of 272 patients assessed via molecular diagnostics, 38.9% had clinically unclear diagnoses, with over 95% of these clarified through molecular classification. Dermatological and molecular diagnoses showed low agreement. Disease severity and chronicity significantly decreased over 2 years. Use of systemic therapies increased, while overall corticosteroid usage declined. HrQoL improved significantly, with DLQI scores decreasing by 50%.

CONCLUSIONS: Molecular diagnostics significantly enhance diagnostic accuracy for hand dermatoses, leading to targeted treatment adjustments. The observed therapy shift correlated with improved disease outcomes and HrQoL. As specialized systemic treatments emerge, precise diagnostic tools will be essential for optimizing patient care and reducing the burden of occupational skin diseases.

PMID:41661519 | DOI:10.1007/s13555-026-01663-8

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Nevin Manimala Statistics

Safety of Early Diet After Endoscopic Full-Thickness Resection of Gastric Tumor: A Propensity Match Analysis

Dig Dis Sci. 2026 Feb 9. doi: 10.1007/s10620-026-09715-x. Online ahead of print.

ABSTRACT

BACKGROUND: Endoscopic full-thickness resection (EFTR) can effectively remove extraluminal tumors, overcoming limitations of endoscopic submucosal dissection (ESD). However, optimal post-EFTR feeding timing lacks standardized guidelines for patients with gastric tumors. This study aims to assess the safety of early feeding after EFTR.

METHODS: Retrospective analysis was conducted on patients who underwent EFTR at our hospital between January 2014 and January 2019. Based on actual fasting duration, patients were categorized: short fasting (≤ 2 days, n = 72) and long fasting (> 2 days, n = 431) group. Using 1:1 propensity score matching, postoperative complications and hospital stay were compared between balanced groups.

RESULTS: A total of 503 patients were included in this study, among which 72 were in the short fasting group and 431 were in the long fasting group. After matching, the baseline characteristics of 68 patients in the short fasting group and 68 patients in the long fasting group reached equilibrium (P > 0.05). The average age was 53.82 ± 10.98 years old. There was no significant difference in clinicopathological conditions or lesion size between the two groups. There was no statistically significant difference in the rates of postoperative bleeding, fever and abdominal distension between the two groups of patients after EFTR. However, compared with the long fasting protocol, a trend of shorter hospitalization was observed in the short fasting group.

CONCLUSIONS: Compared with the long fasting protocol, early feeding after EFTR for gastric tumors did not increase the incidence of discomfort or postoperative complications. In addition, short fasting protocol has a tendency to shorten hospital stays, which represents potential clinical benefits.

PMID:41661495 | DOI:10.1007/s10620-026-09715-x

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Prediction of metabolically healthy obesity based on dietary nutrients: a comparative analysis of six machine learning models with SHAP and LIME interpretation

Eat Weight Disord. 2026 Feb 9. doi: 10.1007/s40519-026-01821-z. Online ahead of print.

ABSTRACT

PURPOSE: The relationship between dietary nutrient intake and metabolically healthy obesity (MHO) remains poorly understood. This study aimed to construct machine learning models to predict MHO based on dietary nutrient profiles and to identify the most influential nutrients contributing to this phenotype.

METHODS: Data were derived from the U.S. National Health and Nutrition Examination Survey (NHANES) 2005-2018. Forty-five dietary nutrients, along with demographic and lifestyle variables, were included in two predictive frameworks: a dietary-only model and a complete model. Feature preprocessing involved assessing mixture effects, removing multicollinear variables, addressing class imbalance, and selecting important predictors. Six machine learning algorithms-random forest (RF), light gradient-boosting machine, k-nearest neighbor, Naive Bayes, support vector machine, and eXtreme Gradient Boosting (XGBoost)-were developed and benchmarked to compare performance. Model interpretability was examined using SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME).

RESULTS: A total of 8914 participants, including 475 classified as having MHO, were analyzed. The Random Forest model exhibited the best predictive performance in the complete model, achieving training and validation AUCs of 0.986 and 0.991, respectively. In contrast, XGBoost demonstrated superior performance in the dietary-only model, with AUCs of 0.971 and 0.988. SHAP and LIME analyses revealed that added vitamin B12, lycopene, caffeine, theobromine, and lutein/zeaxanthin were the strongest positive predictors in the complete model. When only dietary factors were considered, lycopene, lutein/zeaxanthin, magnesium, potassium, and selenium emerged as the most influential nutrients.

CONCLUSIONS: RF and XGBoost models provided the highest predictive accuracy for MHO using complete and dietary feature sets, respectively. The consistent findings from SHAP and LIME analyses emphasized lycopene and lutein/zeaxanthin as reliable and biologically relevant key predictors of metabolically healthy obesity.

LEVEL OF EVIDENCE: Level III, well-designed cohort or case-control analytic study.

PMID:41661492 | DOI:10.1007/s40519-026-01821-z

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Prevalence and Subtypes of Blastocystis in Symptomatic Children in Egypt and Anti-Blastocystis Efficacy of Artemisia alba-Loaded Silver Nanoparticles In Vitro and in Swiss Albino Mice

Acta Parasitol. 2026 Feb 9;71(1):31. doi: 10.1007/s11686-025-01189-7.

NO ABSTRACT

PMID:41661452 | DOI:10.1007/s11686-025-01189-7

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Nevin Manimala Statistics

Maternal factors associated with exclusive breastfeeding failure: a community-based cross-sectional study in the north of Iran

Wien Med Wochenschr. 2026 Feb 9. doi: 10.1007/s10354-025-01127-2. Online ahead of print.

ABSTRACT

BACKGROUND: To improve exclusive breastfeeding, we must resolve challenges for mothers and babies. This study aims to determine the maternal factors contributing to failure of exclusive breastfeeding.

METHODS: This cross-sectional study was conducted in all infants who had attended the healthcare centers for their first 6‑month vaccinations from 2019 to 2021 in Babol, Iran. Maternal factors were collected using a checklist, including demographic, social, and midwifery information. Failure of exclusive breastfeeding was defined as using anything other than breast milk, such as pacifiers, bottles, sugar water, or complementary feeding for infants during the first 6 months of life. Binary logistic analysis examined the influence of predictor variables on exclusive breastfeeding. The significance level was set at P < 0.05.

RESULT: Out of the 1400 infants, at the end of the study, 413 (29.5%) were exclusively breastfed. Multivariate regression showed education level (odds ratio [OR]: 1.42, P = 0.003) and urban residence (OR: 1.89, P < 0.001) to be associated with increased discontinuation, while term pregnancy (OR: 0.47, P = 0.008) served as a preventive factor. Breastfeeding education (OR: 6.7, P = 0.067) and breast problems (OR: 6.4, P = 0.082) had a sixfold effect on the decrease and increase of discontinuation of exclusive breastfeeding, respectively, although this relationship was not statistically significant.

CONCLUSION: This study showed that preterm delivery, higher education, and living in an urban area can increase the probability of failure of exclusive breastfeeding. These findings provide valuable insights for healthcare professionals and policymakers promoting and supporting exclusive breastfeeding.

PMID:41661450 | DOI:10.1007/s10354-025-01127-2

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Nevin Manimala Statistics

Coagulation Hemostasis Parameters in Macaque Monkeys (Macaca spp.)

Bull Exp Biol Med. 2026 Feb 9. doi: 10.1007/s10517-026-06587-z. Online ahead of print.

ABSTRACT

Coagulation hemostasis parameters were assessed in non-human primates of the genus Macaca spp. specifically Macaca mulatta and Macaca fascicularis (age 1-34 years) housed in open enclosures at the Kurchatov Complex of Medical Primatology, National Research Centre “Kurchatov Institute” under humid subtropical climatic conditions. A high degree of interspecific variability in the measured hemostatic parameters was observed among sexually mature individuals of both species. Statistically significant differences were found in the mean values of coagulation parameters between immature and mature animals. Furthermore, in the age group of 20 years and older (classified as aged animals), significant sex-dependent differences in the mean values of the studied hemostasis indicators were also detected. The quantitative reference ranges obtained in this study can serve as a baseline for interpreting hemostasiological data in laboratory studies involving these primate species.

PMID:41661431 | DOI:10.1007/s10517-026-06587-z

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Comparative analysis of freesurfer and brainsuite in thickness, surface area, and volume measurements for morphometric group comparisons

Brain Imaging Behav. 2026 Feb 9;20(1):7. doi: 10.1007/s11682-026-01092-3.

ABSTRACT

Brain analysis software uses different atlases producing different results. These variations arise mainly from differences in algorithms and region-of-interest definitions used for segmentation and parcellation. We compared the results of FreeSurfer (FS) and BrainSuite (BS), in brain segmentation and parcellation for group comparisons. Magnetic resonance images from 45 adults (23 females, 22 males) were analyzed using FS and BS. Our analysis included the volume, surface area and thickness of the total brain, right motor cortex, and right thalamus. Statistical analyses were done between software outputs and sex-based variations in brain structure. The mean volumes (cm³) of the thalamus, motor cortex, and total brain were 7.20, 28.54, and 951.9 for FS, and 6.25, 25.47, and 772.6 for BS (P = 0.001 for all). Volumes were higher with FS than BS. The mean surface areas (cm²) of the motor cortex and total brain were 59.30 and 1966.71 for FS, and 57.80 (P = 0.001 for both) and 1797.97 for BS (P = 0.001 for both). Motor cortex surface area was significantly higher in FS compared to BS, while total brain surface area was also larger in FS. The mean thickness (mm) of the motor cortex and total brain was 2.32 and 2.37 for FS, and 4.05 and 3.95 for BS (P = 0.001 for all). Thickness values were lower in FS than in BS. Sex comparison results differed for total brain surface area, but other comparisons revealed similar statistical results across sexes for both software. FS provides higher volume and surface area measurements than BS, while BS yields greater thickness measurements. Despite differences in thickness, surface area, and volume, group comparisons from FS and BS data yielded similar results.

PMID:41661408 | DOI:10.1007/s11682-026-01092-3

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The Impact of Vacations on the Transmission Dynamics of Influenza A (H1N1)

Bull Math Biol. 2026 Feb 9;88(3):37. doi: 10.1007/s11538-026-01600-y.

ABSTRACT

The 2009 influenza A (H1N1) epidemic in China provided a unique natural experiment to evaluate school closures, as it overlapped with two school vacations. Utilizing the epidemiological data from this outbreak, our study specifically assesses the impact of holidays and systematically evaluates the efficacy of school-specific prevention measures in curbing influenza transmission. By using the enhanced piecewise linear representation model and calculating the effective reproduction number Rt, we divided the entire pandemic period into six stages. We employed the Susceptible-Exposed-Infective-Removed model with quarantine compartments to align with the prevention and control policy. We quantified the effectiveness of holidays and school-specific prevention strategies using parameter estimation results. Moreover, we explored several comparative scenarios, including holiday cancellations or extensions, to further demonstrate the impact of school closure and policies. The comparison of different transmission phases revealed a 14.0% and 16.5% reduction in the mean of Rt during the summer vacation and the National Day holiday, respectively. Furthermore, the relaxation of school-specific preventive measures could potentially lead to a doubling of the accumulated case count within several months. In contrast, the extension of holiday periods demonstrated a notable mitigating impact on the epidemic curve. School-specific prevention strategies and school holidays exert a beneficial and significant influence on mitigating the spread of the influenza A (H1N1) epidemic. Our research findings and methods can provide insights for implementing school closure strategies to mitigate similar emerging infectious diseases.

PMID:41661395 | DOI:10.1007/s11538-026-01600-y