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Nevin Manimala Statistics

Impact of Mobile Phone Usage on Sleep Quality Among Medical Students Across Latin America: Multicenter Cross-Sectional Study

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

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Nevin Manimala Statistics

Involvement of the Nigrostriatal Pathway in Patients With Idiopathic Normal Pressure Hydrocephalus and Parkinsonism

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

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Nevin Manimala Statistics

Principal Component Analysis in Dental Research

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

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Nevin Manimala Statistics

From Acute Pancreatitis to Diabetes: Risk Factors and Timeline Analysis in a Pediatric Population Study

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

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International Classification of Diseases, Tenth Revision Diagnosis Codes Are Overutilized in the Diagnosis of Chronic Pancreatitis

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

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Nevin Manimala Statistics

Systematic Review of Volume and Methodological Quality of Randomized Trials in Acute Pancreatitis

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

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Nevin Manimala Statistics

Photostationary state assumption seriously underestimates NOx emissions near large point sources at 10 to 60 m pixel resolution

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

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Nevin Manimala Statistics

ProteoArk: A One-Pot Proteomics Data Analysis and Visualization Tool for Biologists

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

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Nevin Manimala Statistics

Anthropometric Measures and Fuchs’ Endothelial Corneal Dystrophy: The Women’s Health Initiative Observational Study

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

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Nevin Manimala Statistics

Evaluation of a Clinical Decision Support System for Imaging Requests: A Cluster Randomized Clinical Trial

JAMA. 2025 Feb 10. doi: 10.1001/jama.2024.27853. Online ahead of print.

ABSTRACT

IMPORTANCE: Given the widespread use of medical imaging, evaluating the effectiveness of interventions to improve appropriateness is crucial for optimizing health care resources and patient outcomes.

OBJECTIVE: To assess the effects of implementing a clinical decision support system (CDSS), the European Society of Radiology iGuide, on the appropriateness of the medical imaging ordering behavior of physicians.

DESIGN AND SETTING: A cluster randomized clinical trial with 26 departments at 3 German university hospitals acting as clusters, incorporating a before and after discontinued design. All imaging requests originating from physicians in the participating departments over a 2.5-year period were included (between December 2021 and June 2024).

INTERVENTIONS: All departments started without a CDSS and required structured clinical indication data entry and tracking of requested imaging. After randomization, 13 clusters (departments at hospitals) received the CDSS intervention (intervention clusters) and 13 clusters did not (control clusters). The CDSS intervention provided ordering physicians with information as to whether their imaging requests were appropriate, appropriate under certain conditions, or inappropriate; in addition, alternative diagnostic tests, including the corresponding appropriateness score, were suggested by the CDSS, after which physicians could choose to modify their imaging requests.

MAIN OUTCOMES AND MEASURES: The primary outcome measure was the proportion of inappropriate imaging requests made per department. A difference-in-differences analysis was used to investigate changes in the proportion of inappropriate imaging requests between departments with vs those without the CDSS.

RESULTS: A total of 65 764 imaging requests were scored using the CDSS; 50.1% of imaging requests were for female patients and the mean patient age was 64 years (SD, 17.1 years). Prior to implementation of the CDSS, there were 21 625 imaging requests from the control clusters, 1367 (6.3%) of which were categorized as inappropriate; and there were 13 338 imaging requests from the intervention clusters, 1007 (7.6%) of which were categorized as inappropriate. After implementation of the CDSS, there were 10 055 imaging requests from the control clusters, 518 (5.2%) of which were categorized as inappropriate; and there were 7206 imaging requests from the intervention clusters, 461 (6.4%) of which were categorized as inappropriate. The intervention clusters showed a similar reduction (mean difference, -0.5% [99% CI, -2.4% to 0.4%]) in inappropriate imaging requests compared with the control clusters (mean difference, -1.8% [99% CI, -4.3% to -0.4%]) and there was a difference-in-differences value of 1.3 percentage points (99% CI, -2.0 to 1.8 percentage points; P = .69), which was not statistically significant.

CONCLUSIONS AND RELEVANCE: The CDSS did not reduce the number of inappropriate imaging requests ordered by physicians in academic hospital settings.

TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05490290.

PMID:39928308 | DOI:10.1001/jama.2024.27853