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Nevin Manimala Statistics

perfDSA: Automatic Perfusion Imaging in Cerebral Digital Subtraction Angiography

Int J Comput Assist Radiol Surg. 2025 Apr 24. doi: 10.1007/s11548-025-03359-4. Online ahead of print.

ABSTRACT

PURPOSE: Cerebral digital subtraction angiography (DSA) is a standard imaging technique in image-guided interventions for visualizing cerebral blood flow and therapeutic guidance thanks to its high spatio-temporal resolution. To date, cerebral perfusion characteristics in DSA are primarily assessed visually by interventionists, which is time-consuming, error-prone, and subjective. To facilitate fast and reproducible assessment of cerebral perfusion, this work aims to develop and validate a fully automatic and quantitative framework for perfusion DSA.

METHODS: We put forward a framework, perfDSA, that automatically generates deconvolution-based perfusion parametric images from cerebral DSA. It automatically extracts the arterial input function from the supraclinoid internal carotid artery (ICA) and computes deconvolution-based perfusion parametric images including cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time (MTT), and Tmax.

RESULTS: On a DSA dataset with 1006 patients from the multicenter MR CLEAN registry, the proposed perfDSA achieves a Dice of 0.73(±0.21) in segmenting the supraclinoid ICA, resulting in high accuracy of arterial input function (AIF) curves similar to manual extraction. Moreover, some extracted perfusion images show statistically significant associations (P=2.62e 5) with favorable functional outcomes in stroke patients.

CONCLUSION: The proposed perfDSA framework promises to aid therapeutic decision-making in cerebrovascular interventions and facilitate discoveries of novel quantitative biomarkers in clinical practice. The code is available at https://github.com/RuishengSu/perfDSA .

PMID:40272658 | DOI:10.1007/s11548-025-03359-4

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Nevin Manimala Statistics

Mendelian randomization analysis reveals potential causal relationships between serum lipid metabolites and prostate cancer risk

Discov Oncol. 2025 Apr 24;16(1):602. doi: 10.1007/s12672-025-02388-4.

ABSTRACT

BACKGROUND: Prostate cancer is a common malignancy in men, with its pathogenesis not yet fully elucidated. Recent years have seen increased attention on the relationship between lipid metabolism abnormalities and prostate cancer risk. This study aims to explore the potential causal relationships between serum lipid metabolites and prostate cancer risk using Mendelian randomization methods.

METHODS: This study employed Mendelian randomization methods to analyze the relationship between various serum lipid metabolites (including phosphatidylcholines, phosphatidylethanolamines, phosphatidylinositols, etc.) and prostate cancer risk using GWAS datasets from the UK Biobank. The research analyzed data from 182,625 participants of European descent, including 9132 prostate cancer cases and 173,493 controls. Multiple statistical methods were used for analysis, including inverse variance weighted method, MR Egger regression method, and weighted median approach. Results were presented through forest plots, funnel plots, and scatter plots.

RESULTS: The study found that most serum lipid metabolites likely do not have strong causal relationships with prostate cancer risk. However, some metabolites showed weak associations: phosphatidylethanolamine (16:0_20:4) levels demonstrated a weak negative correlation with prostate cancer risk, while phosphatidylinositol (18:0_20:4) levels showed a weak positive correlation. The consistency of results across most analytical methods enhanced the reliability of these findings.

CONCLUSION: This study provides important insights into the complex relationship between serum lipid metabolites and prostate cancer risk. Although most lipid metabolites may not be strong determinants of prostate cancer risk, certain specific metabolites may have weak associations.

PMID:40272633 | DOI:10.1007/s12672-025-02388-4

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Nevin Manimala Statistics

Impact of the COVID-19 Pandemic on Prostate Cancer: Perturbations in Screening and Diagnostic Patterns

Int J Urol. 2025 Apr 24. doi: 10.1111/iju.70085. Online ahead of print.

ABSTRACT

OBJECTIVES: This study aimed to evaluate the impact of the COVID-19 pandemic on prostate cancer screening, patient characteristics, and clinical outcomes by comparing data before and after the pandemic at a Japanese institution.

METHODS: A retrospective cohort study was conducted at Toho University Sakura Medical Center, including 955 patients who underwent prostate biopsy between March 2018 and May 2022. The study period was divided into pre-pandemic (March 2018 to March 2020) and post-pandemic (April 2020 to May 2022) phases. Data on demographic characteristics, referral patterns, clinical presentation, and biopsy results were collected. Statistical analyses were performed to evaluate differences in key clinical parameters before and after the onset of the pandemic.

RESULTS: The median age of patients undergoing prostate biopsy increased significantly during the post-pandemic period (71.0 years before vs. 73.0 years after, p < 0.01). Referrals from PSA screening decreased significantly (13.5% before vs. 9.0% after, p = 0.03), whereas referrals from office urologists increased (29.8% before vs. 38.0% after, p < 0.01). The overall detection rate of prostate cancer remained stable (62.0% before vs. 67.0% after, p = 0.10). However, the proportion of higher Gleason grade groups (4 and 5) increased significantly after the pandemic (46.8% before vs. 68.1% after, p < 0.01).

CONCLUSIONS: The COVID-19 pandemic led to notable changes in prostate cancer screening practices and an increase in higher-grade cancer diagnoses. These findings highlight the importance of maintaining robust cancer screening programs and ensuring timely diagnosis during public health crises to mitigate adverse clinical outcomes.

PMID:40270432 | DOI:10.1111/iju.70085

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Nevin Manimala Statistics

Evolution of the COVID-19 Pandemic and Its Impact on Potential Sick Leave in the Federal State of Tyrol

Stud Health Technol Inform. 2025 Apr 24;324:264-269. doi: 10.3233/SHTI250199.

ABSTRACT

BACKGROUND: The COVID-19 pandemic strained healthcare systems, with Tyrol, Austria, as an early hotspot due to Alpine tourism. Variants like Alpha, Delta, and Omicron influenced infection and hospitalization trends.

OBJECTIVES: To assess how different variants affected hospital occupancy, sick leave, and infection rates in Tyrol.

METHODS: Daily data on infections, hospital occupancy, and variants from 2020-2022 were analyzed using statistical trend assessments.

RESULTS: Sick leave peaked at 38,542 days in early 2022 during the Omicron wave. Hospital occupancy rose significantly during Alpha and Omicron surges, despite milder disease severity for Omicron. Preventive measures temporarily reduced absenteeism.

CONCLUSION: Highly transmissible variants caused significant healthcare strain despite lower severity. Adaptable crisis management strategies are essential for mitigating future pandemic impacts.

PMID:40270423 | DOI:10.3233/SHTI250199

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Nevin Manimala Statistics

Extracting LOINC Codes from a Laboratory Information System’s Index: Addressing Semantic Interoperability with Web Scraping

Stud Health Technol Inform. 2025 Apr 24;324:234-239. doi: 10.3233/SHTI250194.

ABSTRACT

BACKGROUND: Standardizing laboratory data is essential for interoperability and secondary use in clinical research and healthcare. However, many laboratory information systems (LIS) still rely on internal codes rather than internationally recognized terminologies, hindering data exchange, queryability, and integration into health data infrastructures.

OBJECTIVES: This study aimed to automate the extraction and mapping of internal lab codes to LOINC to improve structured data integration by utilizing web scraping and terminology mapping, we sought to create a FHIR-compliant ConceptMap.

METHODS: Guided by key requirements for structured data integration, we developed a Python-based workflow to extract and process laboratory data from an internal lab index. Using Selenium, BeautifulSoup, and Pandas, the extracted data was mapped to LOINC codes and transformed into a FHIR-compliant ConceptMap.

RESULTS: The workflow extracted 2,870 analytes, mapping 768 (27%) to LOINC. The automated process demonstrated feasibility and scalability.

CONCLUSION: The approach enables structured laboratory data integration but highlights the need for direct LIS integration and expanded LOINC coverage for legacy data.

PMID:40270418 | DOI:10.3233/SHTI250194

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Nevin Manimala Statistics

Telemedicine for Ketogenic Dietary Treatment in Epilepsy and Inherited Metabolic Diseases: Survey of Health Care Professionals

Stud Health Technol Inform. 2025 Apr 24;324:176-177. doi: 10.3233/SHTI250182.

ABSTRACT

In refractory epilepsy and inherited metabolic disorders, Ketogenic Dietary Therapies (KDT) are established non-pharmacological treatments. Telemedicine might contribute to tackle various challenges related to KDT complexity and the respective target diseases. A questionnaire on the current use and future requirements was provided for health care professionals working in neuropediatrics, inherited metabolic diseases and nutrition within the region of German speaking countries. Distribution was facilitated via an established network. Response rate was 83% (24/29). Respondents were physicians (63%) and experts from the field of nutrition (37%). Telemedicine use in any way was reported by 71%. For future telemedicine aids, provision of digital patient information and aspects regarding ketone body, seizure and growth monitoring were ranked highest, while visualization of blood sugar and sensor integration were rated less relevant. Caution regarding legal aspects (liability), reimbursement and technical integration within the current hospital information system was addressed proactively by participants.

PMID:40270406 | DOI:10.3233/SHTI250182

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Nevin Manimala Statistics

Assessment of Factors and Deterrents Influencing Medical Students in Pursuing a Career in Surgical Disciplines: Gender-Based Perceptions From a Teaching Hospital in India

Am Surg. 2025 Apr 24:31348251337153. doi: 10.1177/00031348251337153. Online ahead of print.

ABSTRACT

IntroductionGender disparity within the health care profession, specifically in surgical fields, continues to be a subject of discussion. Understanding these gender-specific determinants is key to fostering inclusivity in surgery. This study investigates gender-related perspectives on pursuing a career in surgical disciplines and assessess the perceived challenges among medical students in India.MethodsA cross-sectional survey was conducted at a teaching hospital. Third through fifth-year medical students were invited to fill a semi-structured questionnaire investigating career preferences and the influencing factors. The data was collected through a survey and analyzed. Likert-scale type responses and open-ended questions were analyzed separately. Appropriate statistical tests were used to compare the gender-based responses.Results231 complete responses were analyzed. Of these, 61.5% were females. Interest in pursuing surgery was found to be similar in both genders (P = .61). Both male and female students cited concerns about work-life balance as the major factor (41.6%) influencing their interest in pursuing surgery, followed by personal interest in anatomy and surgical techniques (39%), and exposure to surgical procedures (36.4%). Female students perceived limited opportunities in surgical training (M = 7.8%, F = 21.1%, P = .007) and gender bias in surgical disciplines (M = 34.8%, F = 50%, P = .02) as a significant challenge as compared to their male counterparts. Approximately 1/3rd females reported a lack of female surgical role models.ConclusionThis comprehensive analysis illuminates the evolving gender dynamics in a developing nation, reflecting a burgeoning interest in surgical specialties among female students. Creating targeted training opportunities and gender-conducive environments for female students can catalyze this positive shift.

PMID:40270365 | DOI:10.1177/00031348251337153

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Nevin Manimala Statistics

Multimorbidity patterns of mental disorders and physical diseases of adults in northeast China: a cross-sectional network analysis

Epidemiol Psychiatr Sci. 2025 Apr 24;34:e27. doi: 10.1017/S2045796025000204.

ABSTRACT

AIMS: Multimorbidity, especially physical-mental multimorbidity, is an emerging global health challenge. However, the characteristics and patterns of physical-mental multimorbidity based on the diagnosis of mental disorders in Chinese adults remain unclear.

METHODS: A cross-sectional study was conducted from November 2004 to April 2005 among 13,358 adults (ages 18-65years) residing in Liaoning Province, China, to evaluate the occurrence of physical-mental multimorbidity. Mental disorders were assessed using the Composite International Diagnostic Interview (version 1.0) with reference to the Diagnostic and Statistical Manual of Mental Disorders (3rd Edition Revised), while physical diseases were self-reported. Physical-mental multimorbidity was assessed based on a list of 16 physical and mental morbidities with prevalence ≥1% and was defined as the presence of one mental disorder and one physical disease. The chi-square test was used to calculate differences in the prevalence and comorbidity of different diseases between the sexes. A matrix heat map was generated of the absolute number of comorbidities for each disease. To identify complex associations and potential disease clustering patterns, a network analysis was performed, constructing a network to explore the relationships within and between various mental disorders and physical diseases.

RESULTS: Physical-mental multimorbidity was confirmed in 3.7% (498) of the participants, with a higher prevalence among women (4.2%, 282) than men (3.3%, 216). The top three diseases with the highest comorbidity rate and average number of comorbidities were dysphoric mood (86.3%; 2.86), social anxiety disorder (77.8%; 2.78) and major depressive disorder (77.1%; 2.53). A physical-mental multimorbidity network was visually divided into mental and physical domains. Additionally, four distinct multimorbidity patterns were identified: ‘Affective-addiction’, ‘Anxiety’, ‘Cardiometabolic’ and ‘Gastro-musculoskeletal-respiratory’, with the digestive-respiratory-musculoskeletal pattern being the most common among the total sample. The affective-addiction pattern was more prevalent in men and rural populations. The cardiometabolic pattern was more common in urban populations.

CONCLUSIONS: The physical-mental multimorbidity network structure and the four patterns identified in this study align with previous research, though we observed notable differences in the proportion of these patterns. These variations highlight the importance of tailored interventions that address specific multimorbidity patterns while maintaining broader applicability to diverse populations.

PMID:40270350 | DOI:10.1017/S2045796025000204

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Nevin Manimala Statistics

Heavy DIY Activities as a Potential Preventative for Stress Urinary Incontinence

Am J Mens Health. 2025 Mar-Apr;19(2):15579883251336056. doi: 10.1177/15579883251336056. Epub 2025 Apr 24.

ABSTRACT

Physical activity is associated with stress urinary incontinence (SUI). The genetic causality of this association remains unclear. This study used the Mendelian randomization (MR) method to explore the potential causal relationship between physical activity and SUI risk using heavy do-it-yourself (DIY), light DIY, strenuous sports, walking for pleasure, and other exercises as proxies. We selected single nucleotide polymorphisms associated with physical activity from published genome-wide association studies (GWAS). Statistics of SUI come from the GWAS database. MR estimation was performed using the inverse variance weighting method, the MR-Egger method, and the weighted median method. Sensitivity analyses were performed using Cochran’s Q test, MR-Egger intercept, MR-pleiotropy residuals, outlier methods, leave-one-out analysis, and funnel plots. The results showed that there was a causal relationship between heavy DIY and SUI (OR = 0.9712, 95% confidence interval [0.951, 0.9918], p = .006), while no significant causal relationship was found between other physical activities and SUI. These findings were robust across multiple sensitivity analyses. This MR study demonstrates the causal relationship between heavy DIY and SUI, helping doctors and researchers better recommend preventive and treatment measures to patients, while also providing specific directions for improving their lifestyle in men and women suffering from SUI.

PMID:40270342 | DOI:10.1177/15579883251336056

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Nevin Manimala Statistics

Endothelial Activation and Stress Index Predicts All-Cause and Cardiovascular Mortality in Hypertensive Individuals: A Nationwide Study

J Clin Hypertens (Greenwich). 2025 Apr;27(4):e70057. doi: 10.1111/jch.70057.

ABSTRACT

Emerging evidence links the Endothelial Activation and Stress Index (EASIX) and mortality risk in coronary artery disease, but its relevance in hypertensive patients remains unclear. This study examines the association between EASIX and all-cause and cardiovascular mortality in hypertensive individuals. The analysis included 6138 hypertensive patients from seven National Health and Nutrition Examination Survey (NHNES) cycles (2003-2016), with mortality data obtained from the National Death Index (NDI). Over a median follow-up of 98 months, 1435 (23.4%) participants died, including 400 (6.5%) from cardiovascular causes. Restricted cubic spline analysis revealed a positive association between EASIX and both all-cause and cardiovascular mortality. Weighted multivariable Cox regression indicated that each 1-unit increase in EASIX corresponding to a 25% and 23% rise in mortality risk, respectively. Based on the optimal cutoff value determined using the maximally selected rank statistics method, participants were stratified into higher (>0.79) and lower (≤0.79) EASIX groups. Higher EASIX was significantly associated with increased all-cause mortality risk (HR 1.46, 95% CI 1.23-1.73, p < 0.0001). Higher EASIX scores were associated with increased cardiovascular mortality, especially in former/current smokers and those with diabetes/prediabetes. Time-dependent receiver operating characteristic analysis assessed the predictive accuracy of EASIX, yielding area under the curve (AUC) for 1-, 3-, 5-, and 10-year survival of 0.71, 0.67, 0.67, and 0.67 for all-cause mortality and 0.79, 0.73, 0.73, and 0.71 for cardiovascular mortality. In conclusion, elevated EASIX is independently associated with increased all-cause and cardiovascular mortality in hypertensive patients, suggesting its potential as a predictive biomarker in clinical practice.

PMID:40270299 | DOI:10.1111/jch.70057