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Nevin Manimala Statistics

Epidemiology of Neuralgic Amyotrophy-A Retrospective Analysis of Data From a Large German Health Insurance Company

Muscle Nerve. 2025 Nov 14. doi: 10.1002/mus.70059. Online ahead of print.

ABSTRACT

INTRODUCTION/AIMS: Neuralgic amyotrophy (NA, Parsonage-Turner syndrome) is a common, multifocal, autoimmune inflammatory disease that predominantly affects proximal nerve segments of the shoulder girdle. Despite the high incidence of 100/100,000, epidemiologic data based on larger cohorts are still lacking. This study aims to address this issue.

METHODS: A retrospective evaluation of billing data from an average of approximately 26,000,000 insured persons of a large German health insurance company was performed from 2013 to 2022. In addition to descriptive statistical methods, regression analyses were carried out.

RESULTS: The incidence and prevalence of NA were 7.7-12.8 and 19.7-21.6 per 100,000 people, respectively. During the study period, a steady decline in incidence and, to a lesser extent, prevalence was observed. The diagnosis was made significantly more frequently in the first quarter of the year than in any other quarter. The prevalence of a simultaneously coded diaphragmatic paresis (indicating the involvement of the phrenic nerve) was 0.45%.

DISCUSSION: Compared with prospectively collected data, the data in this study revealed an approximately 90% lower incidence of NA. It is likely that the majority of cases are not correctly diagnosed and are therefore not captured in the billing data. The involvement of the phrenic nerve in patients with NA also appears not to be recognized in most cases. According to the current pathophysiological model of NA, an immunological trigger is necessary to initiate the disease process. Our data support the accuracy of this model.

PMID:41235535 | DOI:10.1002/mus.70059

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Nevin Manimala Statistics

Lymphopenia in glioblastoma and its association with brain vessel irradiation: pilot retrospective evaluation of dose-volume parameters

Neoplasma. 2025 Oct;72(5):371-378. doi: 10.4149/neo_2025_250730N330.

ABSTRACT

Radiotherapy (RT) plays a central role in the management of glioblastoma, often in combination with other treatment modalities. While RT can enhance both local and systemic tumor control, especially when used alongside immunotherapy, it is also associated with lymphopenia – a reduction in lymphocyte count – which has been linked to poorer treatment outcomes and reduced survival. This retrospective study aimed to examine the relationship between radiation dose delivered to brain vessels and the severity of lymphopenia in patients with newly diagnosed glioblastoma treated at a tertiary cancer center in 2021. Brain vessels were manually contoured using MRI data, and dose-volume analysis was conducted. Lymphopenia severity was graded according to CTCAE v5.0, and statistical analyses were performed to identify any correlations. Among the 28 patients analyzed, 32% developed grade 1-3 lymphopenia. No significant correlation was found between the radiation dose to brain vessels and the degree of lymphopenia. The median volume of irradiated vessels did not differ significantly between patients with and without lymphopenia. In glioblastoma patients, multiple factors contribute to decreased lymphocyte count – e.g., chemotherapy and corticosteroid use. Although no definitive link was identified, the study underscores the importance of preserving lymphocyte counts during glioblastoma treatment and supports the need for further prospective research to explore strategies like lymphocyte-sparing RT and to better understand the mechanisms behind treatment-related lymphopenia.

PMID:41235529 | DOI:10.4149/neo_2025_250730N330

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Nevin Manimala Statistics

The effect of AntiAGE-Biom probiotic on metabolic features in individuals with type 2 diabetes

Ter Arkh. 2025 Nov 11;97(10):859-866. doi: 10.26442/00403660.2025.10.203462.

ABSTRACT

BACKGROUND: Despite the variety of antidiabetic therapies, many patients with type 2 diabetes (T2D) do not achieve optimal glycemic control. Therefore, there is a need to develop additional methods for managing T2D, including ones that regulate the gut microbiome.

AIM: To assess the effect of AntiAGE-Biom probiotic on metabolic parameters in T2D patients during 3 months of therapy.

MATERIALS AND METHODS: A randomized, double-blind, placebo-controlled, single-center study included patients with T2D with glycated hemoglobin – HbA1c<7,5% on stable antidiabetic therapy. Patients were randomized into groups receiving AntiAGE-Biom and placebo. The primary endpoint was the change in HbA1c from baseline, secondary endpoints included the dynamics in biochemical and anthropometric parameters, body composition, as well as HOMA-IR index.

RESULTS: The study included 40 patients with T2D (n=20 in each group). There was a trend towards a decrease in HbA1c in AntiAGE-Biom group, that did not reach statistical significance. The use of the probiotic improved the body composition after 3 months: reduced the percentage of fat in men and a subgroup of patients with an initial HbA1c≥ 6.5%; also increased skeletal muscle mass and lean mass in the trunk segment in men (р<0,05).

CONCLUSION: AntiAGE-Biom probiotic helps to maintain metabolic control and significantly improve body composition in T2D patients with initial HbA1c<7.5%.

PMID:41235517 | DOI:10.26442/00403660.2025.10.203462

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Nevin Manimala Statistics

Contemporary capabilities of CT texture analysis in the diagnosis of pheochromocytoma: associations with clinical, laboratory, and pathomorphological findings

Ter Arkh. 2025 Nov 11;97(10):844-858. doi: 10.26442/00403660.2025.10.203371.

ABSTRACT

AIM: To investigate the presence of statistically significant correlations between clinical and laboratory characteristics and features of contrast-enhanced computed tomography (CT) images, as well as to assess the possibility of predicting group classification according to the PASS scale based on clinical, laboratory, and contrast-enhanced CT imaging data.

MATERIALS AND METHODS: A retrospective analysis was performed on preoperative four-phase contrast-enhanced CT images of 230 patients with a pathomorphologically verified diagnosis of pheochromocytoma/paraganglioma. Clinical manifestations such as the presence and duration of arterial hypertension, carbohydrate metabolism disorders, and dyslipidemia were assessed. In the first stage, comparative and correlation analyses were conducted between hormonal parameters and contrast-enhanced CT data. In the second stage, based on morphological characteristics, patients were divided into two groups: with PASS scores <4 (n=155) and PASS scores ≥4 (n=56). Logistic regression analysis was conducted to evaluate the possibility of predicting group classification based on clinical, laboratory, and contrast-enhanced CT imaging data.

RESULTS: Pheochromocytomas/paragangliomas with isolated normetanephrine secretion type accumulate significantly more contrast agent in the arterial and venous phases of the study (p<0.001) compared to other secretion types. Correlation analysis revealed statistically significant moderate positive correlations between blood normetanephrine levels and the volume of functioning tumor tissue without necrotic areas, as well as a moderate negative correlation between blood metanephrine levels and the maximum density in the venous phase, the percentage of venous contrast enhancement, and the 90th percentile of X-ray density of the functioning tumor tissue in the venous CT phase. A statistically significant association was also found between the presence/absence of necrosis and tumor size (p<0.001), as well as between structure and tumor size (p=0.004). No statistically significant correlations were identified between laboratory parameters, imaging data, and clinical manifestations (arterial hypertension, carbohydrate metabolism disorders, dyslipidemia, and carotid artery atherosclerosis). CT image characteristics allow for prediction of group classification according to the PASS scale with an AUC of 0.647 (95% confidence interval 0.471-0.797), sensitivity of 0.923 (0.727-1.000), specificity of 0.400 (0.250-0.548), PPV of 0.333 (0.176-0.500), and NPV of 0.941 (0.800-1.000).

CONCLUSION: Pheochromocytomas/paragangliomas are heterogeneous pathologies with diverse clinical, hormonal, and radiological characteristics that are associated with pathomorphological findings (PASS scale).

PMID:41235516 | DOI:10.26442/00403660.2025.10.203371

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Nevin Manimala Statistics

Visceral obesity as a risk factor for breast cancer

Ter Arkh. 2025 Nov 11;97(10):830-835. doi: 10.26442/00403660.2025.10.203363.

ABSTRACT

BACKGROUND: Obesity is associated with some types of cancer including breast cancer (BC). But still there are not so much studies on the relationship between the adipose tissue distribution, visceral obesity (VO), and insulin resistance with the development of BC. This study is devoted to the effect of VO and insulin resistance on the development of BC.

AIM: To assess the frequency of VO and insulin resistance in patients with newly diagnosed BC in an outpatient setting.

MATERIALS AND METHODS: An observational retrospective study was conducted, including 160 electronic medical records of women with suspected cancer. The control group (n=103) consisted of women with negative histological results. The study group consisted of patients in whom BC was confirmed histologically. Anthropometric data, glycemia, and lipid profile were studied. Statistical processing of the results was performed using the method of descriptive statistics and calculation of the Spearman correlation coefficient with reliability assessment by the Student’s t-test.

RESULTS: The maximum frequency of BC is observed in women over 60 years old (80%). The average age in the group of participants with confirmed BC was 64.51±10.30, in the control group 55.81±12.20 (p<0.0004%). The average Body Mass Index in patients in the group with BC was 30.50±4.98, in the control group – 25.76±5.70 (p<0.05). The average Body Mass Index in the BC group was 30.50, in the control group – 25.76 (p<0.05). A high level of VO was found in 82% of patients with BC. We have found that in the group of patients with BC the frequency of occurrence of high Total Cholesterol values is 72%, Triglycerides – 61%, Low-Density Lipoprotein – 68%, while in the group of patients with unconfirmed BC 10, 33, 24% respectively. When assessing indirect signs of insulin resistance in patients with BC high values of the indicators were recorded, which indicates the presence of insulin resistance. In the control group, Visceral Adiposity Index was detected in 22% of cases above normal values, the Triglycerides to High-Density Lipoprotein Cholesterol index was detected above normal values in 12% of cases, Metabolic Index – 1%, Lipid Accumulation Product – 14%.

CONCLUSION: The results of the study emphasize the importance of VO and insulin resistance in the pathogenesis of breast cancer, which is important for early diagnosis and prevention of the disease.

PMID:41235514 | DOI:10.26442/00403660.2025.10.203363

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Nevin Manimala Statistics

Measuring the care needs of young people with intellectual difficulties: Construct validity of the learning disability vulnerability assessment scale and utility in establish the care needs of young people

J Intellect Disabil. 2025 Nov 14:17446295251392108. doi: 10.1177/17446295251392108. Online ahead of print.

ABSTRACT

The concept of ‘vulnerability’ in children is critical to needs-related planning and risk management. Despite proliferation of measures there is limited evidence-base to support the validity of existing, relevant clinical assessments. The FACE CARAS young person’s risk assessment toolkit includes a measure of vulnerability-the Learning Disability Vulnerability Assessment Scale (LD-VAS). Good inter-rater reliability has been reported but construct validity has not previously been demonstrated. The aims of this study were to assess the construct-validity of the tool by: (i) evaluating the dimensionality of the ratings produced, and (ii) modelling the ability of the scores to quantify the care needs of young people. LD-VAS ratings were available for 143 young people, the dimensionality of the scale ratings was assessed using a parallel analysis and confirmatory factor analysis (CFA). The ability of scores to predict care-level was modelled using discriminant function analysis and multinomial logistic regression. A single factor CFA model showed a good fit to the data. The discriminant function analysis suggested several scoring profiles exist, relating to care-level. On multinomial logistic regression the scores could statistically significantly differentiate between those in the lowest and higher intensity care categories. The LD-VAS appears to have construct validity and is potentially useful in supporting rational decision-making regarding care-provision for children affected by learning disability.

PMID:41235502 | DOI:10.1177/17446295251392108

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Nevin Manimala Statistics

Evaluating Nurse Practitioner Students’ Engagement with Isabel: Enhancing Diagnostic Confidence Through AI Integration in Education

Stud Health Technol Inform. 2025 Nov 12;333:88-89. doi: 10.3233/SHTI251582.

ABSTRACT

This study assessed nurse practitioner students’ engagement with Isabel, an AI-based differential diagnosis tool, during training. A survey of 26 students revealed mixed usage, with 44% using it regularly to confirm diagnoses. The tool scored an average of 2.16 for usability. While Isabel boosted diagnostic confidence and accuracy for many, inadequate training limited effectiveness for some. The findings highlight the necessity of structured, hands-on training to successfully integrate AI tools into nursing curricula and enhance digital competency in healthcare education.

PMID:41235498 | DOI:10.3233/SHTI251582

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Nevin Manimala Statistics

Demand Prediction for Better Hospital Capacity Management

Stud Health Technol Inform. 2025 Nov 12;333:70-75. doi: 10.3233/SHTI251578.

ABSTRACT

Accurate hospital bed demand forecasting is critical for ensuring effective patient care and efficient resource allocation. This study evaluates various statistical and machine learning methods to predict daily and hourly inpatient admissions, separations, and emergency department (ED) presentations up to one year in advance. The Advanced Demand Prediction Tool (ADePT) is introduced, which leverages the SARIMAX time series model to capture trends, seasonal patterns, and public holiday effects. Its performance is evaluated using data from a large provider of tertiary health services in Melbourne, Australia against five other statistical and machine learning forecasting models, including rolling window, six-week rolling average, negative binomial regression, an ensemble approach, and random forest regression. The results demonstrated that ADePT generally outperformed other methods when predicting inpatient admissions and separations for multiple forecast horizons. For ED presentations, differences in accuracy were not statistically significant. Importantly, ADePT also showed high accuracy when applied to smaller patient subgroups, including emergency and elective inpatient admissions. By providing reliable short-term and long-term forecasts, ADePT could support more effective daily bed management as well as improved long-term capacity planning.

PMID:41235495 | DOI:10.3233/SHTI251578

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Nevin Manimala Statistics

Extreme Heat and Emergency Department Presentations for Circulatory and Respiratory Conditions: A 5-Year Study in Two Large Hospitals in Australia

Stud Health Technol Inform. 2025 Nov 12;333:64-69. doi: 10.3233/SHTI251577.

ABSTRACT

In Australia, heatwaves result in more fatalities than any other natural disaster, underscoring their significant public health impact. Heatwaves have been associated with heightened ambulance demand, and this study examines their relationship with emergency department (ED) presentations for circulatory and respiratory diseases. The analysis, focusing on the peak heatwave months of December and January over five years, revealed a positive correlation between maximum temperatures and ED presentations. Specifically, ED presentations increased by approximately 4.2% during heatwave periods and 3.9% during non-heatwave periods for every one-degree Celsius rise in maximum temperature. These findings suggest that, alongside well-recognised factors such as population growth and an ageing population, climate change poses an additional and significant challenge to the healthcare system. As maximum temperatures rise, the increased demand for emergency healthcare services could hinder the timely delivery of critical care, necessitating proactive planning and adaptation to ensure resilience in the face of a warming climate.

PMID:41235494 | DOI:10.3233/SHTI251577

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Nevin Manimala Statistics

Health Information Systems Challenges: A Perspective from Rural Indonesia

Stud Health Technol Inform. 2025 Nov 12;333:40-45. doi: 10.3233/SHTI251573.

ABSTRACT

This study investigates the persistent underperformance of health information systems (HISs) in rural Indonesian mental healthcare, despite national digital health initiatives. Utilising a socio-technical systems theoretical lens, an eight-month exploratory qualitative study was conducted, involving focus groups, in-depth interviews with healthcare providers, community health workers, and residents, alongside a literature review. Thematic analysis identified three critical socio-technical misalignments hindering HIS effectiveness: severe data integration issues due to fragmented tools and lack of interoperability; significant resource constraints (technical, human, and budgetary), and pervasive cultural and social stigma, which impede help-seeking, data accuracy and holistic care delivery. The study concludes that these are not technological failures but systemic design breakdowns, and calls for a situated, multi-stakeholder approach to co-design context-sensitive, user-centred HISs that integrate informal work systems, thereby laying foundations for equitable mental healthcare in resource-limited environments.

PMID:41235490 | DOI:10.3233/SHTI251573