Tag: pubmed

J Med Internet Res. 2025 Feb 10;27:e58434. doi: 10.2196/58434.

ABSTRACT

BACKGROUND: Obesity and mental health issues present interconnected public health challenges that impair physical, social, and mental well-being. Digital technologies offer potential for enhancing health care communication between health professionals (HPs) and individuals living with obesity and mental health issues, but their effectiveness is not fully understood.

OBJECTIVE: This scoping review aims to identify and understand the different types of technologies used by HPs in supporting obesity and mental health communication.

METHODS: A comprehensive scoping review, which followed a validated methodology, analyzed studies published between 2013 and 2023 across 8 databases. The data extraction focused on HPs’ use of communication technologies, intervention types, biopsychosocial considerations, and perceptions of technology use. The review was guided by the following research question: “What are the uses, benefits, and limitations of digital technologies in supporting communication between HPs and persons living with obesity and mental health issues?”

RESULTS: In total, 8 studies-featuring web-based platforms, social media, synchronous video calls, telephone calls, automated SMS text messaging, and email-met the inclusion criteria. Technologies such as virtual learning collaborative dashboards and videoconferencing, supported by automated SMS text messaging and social media (Facebook and WhatsApp groups), were commonly used. Psychologists, dietitians, social workers, and health coaches used digital tools to facilitate virtual appointments, diet and mental health monitoring, and motivational and educational support through group therapy, 1-on-1 sessions, and hybrid models. Benefits included enhanced access to care and engagement, personalized digital cognitive behavioral therapy, perceived stigma reduction, privacy, and improved physical health outcomes in weight reduction. However, improvements in mental health outcomes were not statistically significant in studies reporting P values (P≥.05). The limitations included engagement difficulties due to conflicting personal family and work commitments; variable communication mode preferences, with some preferring in-person sessions; and misinterpretations of SMS text messaging prompts. Conflicts arose from cultural and individual differences, weight stigma, and confusion over HP roles in obesity and mental health care.

CONCLUSIONS: Digital technologies have diversified the approaches HPs can take in delivering education, counseling, and motivation to individuals with obesity and mental health issues, facilitating private, stigma-reduced environments for personalized care. While the interventions were effective in obesity management, the review revealed a shortfall in addressing mental health needs. This highlights an urgent need for digital tools to serve as media for a deeper engagement with individuals’ complex biopsychosocial needs. The integration of data science and technological advancements offers promising avenues for tailored digital solutions. The findings advocate the importance of continued innovation and adaptation in digital health care communication strategies, with clearer HP roles and an interdisciplinary, empathetic approach focused on individual needs.

PMID:39928923 | DOI:10.2196/58434

J Med Internet Res. 2025 Feb 10;27:e60630. doi: 10.2196/60630.

ABSTRACT

BACKGROUND: The ubiquitous use of mobile phones among medical students has been linked to potential health consequences, including poor sleep quality.

OBJECTIVE: This study investigates the prevalence of mobile phone addiction and its association with sleep quality among medical students across 6 Latin American countries.

METHODS: A descriptive, cross-sectional, multicenter study was conducted between December 2023 and March 2024 using a self-administered online survey. The survey incorporated the Mobile Phone Addiction Scale and the Pittsburgh Sleep Quality Index to evaluate mobile phone addiction and sleep quality among 1677 medical students. A multiple regression model was applied to analyze the relationship between mobile phone addiction and poor sleep quality, adjusting for sex, age, and educational level to ensure robust results.

RESULTS: Mobile phone addiction was identified in 32.5% (545/1677) of participants, with significant differences across countries. The overall mean Pittsburgh Sleep Quality Index score was 7.26, indicating poor sleep quality. Multiple regression analysis revealed a strong association between mobile phone addiction and poor sleep, controlled for demographic variables (β=1.4, 95% CI 1.05-1.74).

CONCLUSIONS: This study underscores a significant prevalence of mobile phone addiction among medical students and its detrimental association with sleep quality in Latin America. The findings advocate for the need to address mobile phone usage to mitigate its negative implications on student health and academic performance. Strategies to enhance digital literacy and promote healthier usage habits could benefit medical education and student well-being.

PMID:39928921 | DOI:10.2196/60630

Neurology. 2025 Mar 11;104(5):e213352. doi: 10.1212/WNL.0000000000213352. Epub 2025 Feb 10.

ABSTRACT

BACKGROUND AND OBJECTIVES: Idiopathic normal pressure hydrocephalus (iNPH) is characterized by gait disturbance, cognitive decline, and urinary incontinence and may include parkinsonism. The underlying mechanism of parkinsonism in iNPH-whether neurodegenerative or mechanical-remains unclear. This study aimed to assess nigrostriatal integrity in iNPH patients with parkinsonism using dopaminergic transporter imaging (DAT-SPECT) and nigrosome MRI.

METHODS: This prospective study was conducted at the Movement Disorders Clinic, Santa Chiara Hospital, Pisa University, from 2021 to 2023. Inclusion criteria for the iNPH group included the following: (1) clinical diagnosis of probable iNPH per the 2021 Japanese Society Guidelines and (2) parkinsonism per United Kingdom Parkinson’s Disease Society Brain Bank criteria. An equal number of patients with Parkinson disease (PD), matched for age and sex, served as a comparison group. All participants underwent DAT-SPECT and 3T MRI within 1 month. Statistical analyses included the Student t test or Fisher-Pitman permutation tests for continuous variables and χ² tests for categorical variables. Multiple linear regression (adjusted for age and sex) compared DAT binding between groups. Pearson correlation assessed relationships between striatal DAT binding and parkinsonism in patients with iNPH evaluated using the Movement Disorder Society Unified Parkinson’s Disease Rating Scale Part III.

RESULTS: A total of 20 patients with iNPH (mean age 75.4 ± 5.1 years, 65% female) and 20 patients with PD (mean age 74 ± 3.7 years, 55% female) were included. Reduced striatal DAT binding was observed in 45% of patients with iNPH, with none exhibiting nigrosome loss. Conversely, all patients with PD showed both reduced DAT binding and nigrosome loss (p < 0.001). After adjusting for age and sex, patients with iNPH exhibited significantly higher putaminal and caudate DAT binding than patients with PD (right putamen: β = -0.644, p < 0.001; left putamen: β = -0.659, p < 0.001; right caudate: β = -0.429, p = 0.006; left caudate: β = -0.391, p = 0.016), with an elevated putaminal/caudate ratio (p = 0.012). In patients with iNPH, striatal DAT binding negatively correlated with motor severity (left: r = -0.626, p = 0.004; right: r = -0.425, p = 0.07).

DISCUSSION: Findings suggest that parkinsonism in iNPH may stem from mechanical disruption of the nigrostriatal pathway rather than neurodegeneration, as indicated by preserved nigrosome integrity despite reduced DAT binding. Limitations include the small sample size and lack of postsurgical follow-up data.

PMID:39928907 | DOI:10.1212/WNL.0000000000213352

Int J Oral Maxillofac Implants. 2025 Feb 7;40(1):13-20. doi: 10.11607/jomi.10940.

ABSTRACT

Principal component analysis (PCA) is a statistical tool that condenses the information contained in a large group of independent variables to a more manageable number of variables. This is useful when performing an analysis on data sets with a large number of variables. PCA restructures the original independent variables into new variables called principal components that maximize the information present in the data. The principal components then act as a substitute for the independent variables in an analysis. The purpose of this article is to present PCA in an understandable way for researchers without advanced statistical and mathematical backgrounds. To solidify the comprehension of the process and provide a template for researchers, we present an extended step-by-step example of PCA in use on a fictitious peri-implantitis data set.

PMID:39928897 | DOI:10.11607/jomi.10940

Pancreas. 2025 Feb 1;54(2):e130-e135. doi: 10.1097/MPA.0000000000002409. Epub 2024 Nov 13.

ABSTRACT

OBJECTIVES: This study aimed to identify the risk profile for postpancreatitis diabetes mellitus (PPDM) in children after a single acute pancreatitis (AP) episode and to investigate the association between episode severity and complications, length of stay (LOS), and intensive care unit (ICU) needs.

METHODS: This cross-sectional study used the Pediatric Health Information System database for patients ≤19 years old with index AP admissions (2011-2020). A query (2012-2021) was performed for diabetes mellitus (DM). Patients with prior DM or pancreatic surgery before AP or DM diagnoses were excluded.

RESULTS: Out of 12,822 patients with index AP admissions (median age, 13.4 years; 54% female), 686 (5.4%) developed PPDM, with 320 (2.5%) during and 366 (2.9%) at a later admission. The median time to PPDM was 1.9 months (interquartile range: 0-20.8 months). Patients with PPDM experienced extended LOS, heightened ICU needs, and increased complications such as sepsis, pancreatic necrosis, and cyst formation, along with higher rates of organ dysfunction and comorbidities.

CONCLUSIONS: Children face DM risks during or after AP episodes. Enhanced DM screening and close outpatient follow-up within 3 to 6 months post-discharge are recommended.

PMID:39928890 | DOI:10.1097/MPA.0000000000002409

Pancreas. 2025 Feb 1;54(2):e97-e100. doi: 10.1097/MPA.0000000000002399. Epub 2024 Aug 12.

ABSTRACT

BACKGROUND: Retrospective studies and large databases, such as the OneFlorida Clinical Research Consortium, rely on International Classification of Diseases, Tenth Revision (ICD-10) diagnosis codes to identify patients with specificity. This study aimed to determine if ICD-10 codes for CP are overutilized.

MATERIALS AND METHODS: Retrospective analysis was conducted for patients with ICD-10 codes K86.0 (alcohol-induced CP) and K86.1 (other CP) from February 2018 to February 2020. Data were extracted from the integrated electronic data repository. This study was approved by the institutional review board. The diagnosis of CP was defined as either being made by a gastroenterologist, proven by biopsy, or having characteristic findings on cross-sectional imaging with appropriate symptoms.

RESULTS: Five hundred four (37%) out of the 1360 patients had no evidence of CP. When broken down by diagnosis code, 41 of 176 charts (23.3%) with K86.0 and 461 of 1184 charts (38.6%) with K86.1 had no evidence of CP. Two hundred ninety-nine of these patients had either a single episode of acute pancreatitis, recurrent acute pancreatitis, or episode of acute necrotizing pancreatitis. Of note, 81 patients had no identifiable abdominal pathology.

CONCLUSIONS: Although the OneFlorida database makes multicenter research more accessible, it does not replace labor-intensive chart review given the propensity for overdiagnosis.

PMID:39928887 | DOI:10.1097/MPA.0000000000002399

Pancreas. 2025 Feb 1;54(2):e82-e88. doi: 10.1097/MPA.0000000000002397. Epub 2024 Aug 12.

ABSTRACT

BACKGROUND: This systematic review assessed the volume and methodological quality of randomized controlled trials (RCTs) in relation to management of acute pancreatitis (AP).

MATERIALS AND METHODS: The PubMed, MEDLINE, and CENTRAL databases were systematically searched for RCTs published across 3 time periods: <1996 (P1), 1996-2008 (P2), and >2008 (P3). RCT quality was assessed using the Cochrane Risk of Bias (RoB) 2 tool and sample size recalculation, and for spin (interpretation of nonstatistically significant results as relevant, making the study appear to be positive).

RESULTS: Overall, 263 RCTs with 23,232 patients with AP were included. The average number of RCTs per year increased from 1.4, 6.0, to 10.6 in P1, P2, and P3, respectively. The RoB assessment showed low, some, and high concerns in overall RoB in 21%, 56%, and 24% of all RCTs. Selective reporting bias improved over time. Sample size calculation reporting significantly increased through the 3 time periods (17%, 38%, and 47%; P < 0.001). Spin was identified in 68 RCTs (26% of all RCTs).

CONCLUSION: The quantity and quality of published RCTs relating AP management has increased over time, however significant shortcomings of methodological quality persist. Significant improvements in the conduct and reporting of randomized trials in AP are required to improve the evidence base in this field.

PMID:39928886 | DOI:10.1097/MPA.0000000000002397

Proc Natl Acad Sci U S A. 2025 Feb 18;122(7):e2423915122. doi: 10.1073/pnas.2423915122. Epub 2025 Feb 10.

NO ABSTRACT

PMID:39928877 | DOI:10.1073/pnas.2423915122

J Proteome Res. 2025 Feb 10. doi: 10.1021/acs.jproteome.4c00556. Online ahead of print.

ABSTRACT

ProteoArk is a web-based tool that offers a range of computational pipelines for comprehensive analysis and visualization of mass spectrometry-based proteomics data. The application comprises four primary sections designed to address various aspects of mass spectrometry data analysis in a single platform, including label-free and labeled samples (SILAC/iTRAQ/TMT), differential expression analysis, and data visualization. ProteoArk supports postprocessing of Proteome Discoverer, MaxQuant, and MSFragger search results. The tool also includes functional enrichment analyses such as gene ontology, protein-protein interactions, pathway analysis, and differential expression analysis, which incorporate various statistical tests. By streamlining workflows and developing user-friendly interfaces, we created a robust and accessible solution for users with basic bioinformatics skills in proteomic data analysis. Users can easily create manuscript-ready figures with a single click, including principal component analysis, heatmaps (K-means and hierarchical), MA plots, volcano plots, and circular bar plots. ProteoArk is developed using the Django framework and is freely available for users [https://ciods.in/proteoark/]. Users can also download and run the standalone version of ProteoArk using Docker as described in the instructions [https://ciods.in/proteoark/dockerpage]. The application code, input data, and documentation are available online at https://github.com/ArokiaRex/proteoark. A tutorial video is available on YouTube: https://www.youtube.com/watch?v=WFMKAZ9Slq4&ab_channel=RexD.A.B.

PMID:39928856 | DOI:10.1021/acs.jproteome.4c00556

Invest Ophthalmol Vis Sci. 2025 Feb 3;66(2):26. doi: 10.1167/iovs.66.2.26.

ABSTRACT

PURPOSE: Both genetic and environmental factors contribute to the development of Fuchs’ endothelial corneal dystrophy (FECD), the most common indication for corneal transplantation in the United States. Prior studies have suggested an association of height, weight, or body mass index (BMI) with FECD. We examined the association between anthropometric measures and incident FECD in the Women’s Health Initiative Observational Study (WHI-OS) of postmenopausal women (n = 22,983).

METHODS: Medicare Part B claims data from the WHI-OS baseline visit (1993-1998) to 2019 were used to identify incident cases of FECD. At baseline and follow-up year 3, weight, height, waist circumference (WC), and hip circumference were measured. At baseline, women were asked to recall their historic weight at ages 18, 35, and 50 years. At follow-up years 1 and 4 to 8, the women were asked to self-report their weight. Height and weight were used to calculate BMI at each time point. Adjusted hazard ratios (HRs), 95% confidence intervals (CI), and p for trend for incident FECD were estimated by measures of historic BMI, baseline anthropometrics measures, and anthropometric measures that incorporated more than one baseline visit (time-varying). Anthropometric measures were parameterized as continuous and categorical in analyses.

RESULTS: There were 1399 incident FECD cases with an annualized incidence rate of 5.06 per 1000 person-years (95% CI = 4.80-5.33) over 276,443 person-years of follow-up. No statistically significant associations were observed between baseline height and risk of FECD. Women with baseline BMIs ≥35 (obesity II) compared to <25 kg/m2 (normal weight or underweight) had lower risk of incident FECD (HR = 0.68, 95% CI = 0.53-0.88) with a P value = 0.0373 for an ordinal trend analysis across BMI categories. Significant inverse associations were observed for continuous measures of WC (HR = 0.97, 95% CI = 0.95-0.99 per 5 cm increase) and waist-to-hip ratio (WHR; HR = 0.92, 95% CI = 0.86-0.99 per 0.1 unit increase). No statistically significant associations were observed for time-varying BMI, but time-varying WC and WHR has statistically significant inverse associations with risk for FECD (data not shown).

CONCLUSIONS: In this cohort of postmenopausal women, BMI, WC, and WHR were inversely associated with incident FECD. These findings generally support the potential role of anthropometric measures, particularly those indicative of abdominal obesity in FECD susceptibility in women.

PMID:39928313 | DOI:10.1167/iovs.66.2.26