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Nevin Manimala Statistics

Dynamics of Conventional Metabolic Indices in Relation to Endometriosis Severity: A Retrospective Analysis

Int J Gen Med. 2025 Sep 4;18:5183-5193. doi: 10.2147/IJGM.S537848. eCollection 2025.

ABSTRACT

OBJECTIVE: This study aims to investigate the association between the dynamics of routine metabolic markers and endometriosis severity.

METHODS: A retrospective analysis was conducted on patients diagnosed with endometriosis at Zhongshan Hospital, Xiamen, affiliated with Fudan University. The collected data encompassed demographic details and biochemical indicators related to lipid, hepatobiliary, renal metabolism, and electrolyte balance. Independent influencing factors were screened by univariate logistic regression and statistically significant variables were included in the model for adjustment. Restricted cubic spline (RCS) models were also plotted to analyze the nonlinear relationship between factors and endometriosis severity. The receiver operating characteristic (ROC) curve was used to validate the discriminative ability of independent influencing factors.

RESULTS: Ninety-four patients were enrolled in the study, including 32 at stage IV as classified by the American Society for Reproductive Medicine (ASRM) staging. Univariate analysis identified fasting blood glucose (FBG), total protein, direct bilirubin, total bilirubin (TBil) and glutamic-pyruvic transaminase (ALT) as significant metabolic indicators. Additionally, carbohydrate antigen 125 (CA125) and human epididymal protein 4 (HE4) emerged as significant covariates. The RCS analysis revealed a nonlinear association between most metabolic indicators and outcome measures. ROC curve analysis showed that the area under the curve (AUC) of the alanine transaminase (ALT) was above 0.6.

CONCLUSION: ALT had a negative correlation with the severity of endometriosis and was an independent influencing factor with statistical significance. This finding could offer clinicians non-invasive biomarkers for early detection and precise monitoring of disease progression.

PMID:40927773 | PMC:PMC12416391 | DOI:10.2147/IJGM.S537848

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The Comparative Effects of White Potato and White Rice Consumption on Measures of Cardiometabolic Health in Individuals with Type 2 Diabetes Mellitus and Features of Metabolic Syndrome

Curr Dev Nutr. 2025 Aug 6;9(9):107518. doi: 10.1016/j.cdnut.2025.107518. eCollection 2025 Sep.

ABSTRACT

BACKGROUND: The objective of this study was to compare the effects of daily consumption of white potatoes compared with white rice on cardiometabolic health in individuals with type-2 diabetes (T2D).

OBJECTIVE: To determine the effects of white potato consumption compared to white rice (a commonly consumed refined grain) on indices of glycemic control and cardiovascular health in individuals with overweight or obesity and T2D.

METHODS: In this randomized crossover study, comparative control trial, 24 adults with T2D [45-80 y, body mass index (kg/m2) 25-40] consumed baked white potatoes (100 g) or calorie-matched white rice (75 g) daily for 12 wk, separated by a 2-wk washout, with assessments of glycemic control, lipids, inflammation, blood pressure, endothelial function, and body composition at baseline (only 1 baseline visit included as a covariate in statistical analyses), 6 wk, and 12 wk. A linear mixed model was used to assess treatment (potato or rice), time (6 wk or 12 wk), and the treatment-by-time interaction for all outcome variables.

RESULTS: There were no significant (P ≤ 0.05) treatment-by-time interactions for any outcome. There was a main effect of treatment (i.e., independent of time) with the potato regimen resulting in lower waist circumference (P < 0.0001; 4.5 ± 1.0 cm), percent fat mass (P = 0.01; 1.7 ± 0.7%), waist-to-hip ratio (P = 0.002; 0.025 ± 0.013), heart rate (P = 0.01; 3.1 ± 1.2 bpm), as well as higher percent fat-free mass (P = 0.05; 1.4 ± 0.7%) and maximum brachial artery dilation (P = 0.05; 0.074 ± 0.037 mm) when compared to the rice regimen. There were significant timepoint effects (i.e., independent of treatment) for increased homeostatic model assessment of β-cell function (P = 0.02; 34.3 ± 14.5) and decreased high sensitivity C-reactive protein (P = 0.02; 0.08 ± 0.05 μg/mL) and flow-mediated dilation/shear (P = 0.03; 4.3 × 10-5 ± 3.79 × 10-5) during the study.

CONCLUSIONS: White potatoes did not negatively affect glycemic indices, vascular health, lipids, or blood pressure compared to white rice and modestly improved body composition and vascular measures. In both groups, over time, there were reductions in flow-mediated dilation/shear stress, β cell function, and high-sensitivity C-reactive protein. Our preliminary results support white potatoes as a substitute for white rice in T2D.

PMID:40927748 | PMC:PMC12414893 | DOI:10.1016/j.cdnut.2025.107518

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Nevin Manimala Statistics

Machine learning predicts improvement of functional outcomes in spinal cord injury patients after inpatient rehabilitation

Front Rehabil Sci. 2025 Aug 25;6:1594753. doi: 10.3389/fresc.2025.1594753. eCollection 2025.

ABSTRACT

INTRODUCTION: Spinal cord injury (SCI) presents a significant burden to patients, families, and the healthcare system. The ability to accurately predict functional outcomes for SCI patients is essential for optimizing rehabilitation strategies, guiding patient and family decision making, and improving patient care.

METHODS: We conducted a retrospective analysis of 589 SCI patients admitted to a single acute rehabilitation facility and used the dataset to train advanced machine learning algorithms to predict patients’ rehabilitation outcomes. The primary outcome was the Functional Independence Measure (FIM) score at discharge, reflecting the level of independence achieved by patients after comprehensive inpatient rehabilitation.

RESULTS: Tree-based algorithms, particularly Random Forest (RF) and XGBoost, significantly outperformed traditional statistical models and Generalized Linear Models (GLMs) in predicting discharge FIM scores. The RF model exhibited the highest predictive accuracy, with an R-squared value of 0.90 and a Mean Squared Error (MSE) of 0.29 on the training dataset, while achieving 0.52 R-squared and 1.37 MSE on the test dataset. The XGBoost model also demonstrated strong performance, with an R-squared value of 0.74 and an MSE of 0.75 on the training dataset, and 0.51 R-squared with 1.39 MSE on the test dataset. Our analysis identified key predictors of rehabilitation outcomes, including the initial FIM scores and specific demographic factors such as level of injury and prehospital living settings. The study also highlighted the superior ability of tree-based models to capture the complex, non-linear relationships between variables that impact recovery in SCI patients.

DISCUSSION: This research underscores the potential of machine learning models to enhance the accuracy of outcome predictions in SCI rehabilitation. The findings support the integration of these advanced predictive tools in clinical settings to better guide decision making for patients and families, tailor rehabilitation plans, allocate resources efficiently, and ultimately improve patient outcomes.

PMID:40927746 | PMC:PMC12414964 | DOI:10.3389/fresc.2025.1594753

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Clinical efficacy comparison of internal fixation of locking compression plate and cannulated screw in treatment of elderly femoral neck fractures-a retrospective study

Front Surg. 2025 Aug 25;12:1600331. doi: 10.3389/fsurg.2025.1600331. eCollection 2025.

ABSTRACT

OBJECTIVE: To explore the clinical efficacy of internal fixation of locking compression plate and Cannulated Screw in treatment of elderly femoral neck fractures.

METHODS: 175 patients with femoral neck fractures admitted to our hospital from January 2022 to December 2022 were enrolled in the study. 93 cases in the control group were treated with Cannulated Screw internal fixation, and 82 cases in the observation group were treated with locking plate internal fixation. The control group was treated with cannulated screw internal fixation, while the observation group was treated with locking compression plate internal fixation.

RESULTS: Compared with the control group, the observation group had a significantly shorter time for partial weight-bearing exercise, with a statistically significant difference (p < 0.05), and a significantly lower incidence of postoperative complications, with a statistically significant difference (p < 0.05). The ROM of hip extension-flexion at 1 month and 6 months after operation and the ROM of hip internal rotation-external rotation at 1 month after operation in the observation group were significantly higher than those in the control group, and the differences were statistically significant (P < 0.01). The VAS score of the observation group was significantly lower than that of the control group at 1 month after operation, and the difference was statistically significant (P < 0.01).

CONCLUSION: Both locking compression plate internal fixation and cannulated screw internal fixation are effective in the treatment of elderly femoral neck fractures. Compared with cannulated screw internal fixation, locking compression plate internal fixation helps patients to engage in early functional exercise and has a lower incidence of postoperative complications.

PMID:40927707 | PMC:PMC12414934 | DOI:10.3389/fsurg.2025.1600331

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The Role of Plasma Metabolites in Mediating the Effect of Gut Microbiota on Obstructive Sleep Apnea: A Two-Step, Two-Sample Mendelian Randomization Study

Nat Sci Sleep. 2025 Sep 3;17:2119-2130. doi: 10.2147/NSS.S527778. eCollection 2025.

ABSTRACT

BACKGROUND: Recent research has increasingly underscored a significant correlation between gut microbiota and obstructive sleep apnea (OSA). Probiotics have emerged as promising adjunctive interventions for OSA. Metabolites and their related biochemical pathways have emerged as important contributors to the development of OSA. This study aimed to estimate the causal association between gut microbiota and OSA and to quantify the mediating effects of metabolites.

METHODS: We employed two-step, two-sample Mendelian randomization techniques, utilizing single nucleotide polymorphisms as genetic instruments for exposures and mediators. Summary statistics were obtained from genome-wide association studies of gut microbiota (the Dutch Microbiome Project, n=7,738), plasma metabolites (the Canadian Longitudinal Study on Aging cohort, n=8,299), and OSA (FinnGen database, n=410,385). To ensure the robustness of our findings, sensitivity analyses and heterogeneity tests were systematically conducted.

RESULTS: In the Dutch Microbiome Project, species Parabacteroides merdae, genus Faecalibacterium, species Faecalibacterium prausnitzii and species Bifidobacterium longum demonstrated a potential protective association with OSA. We included the top 10 metabolites with potential biological significance as candidate mediators. Among them, only 2-hydroxypalmitate was associated with a reduced risk of OSA. 2-hydroxypalmitate partially mediated the association between species Parabacteroides merdae and OSA, with a mediation proportion of 20.53%.

CONCLUSION: The study highlighted the protective effect of species Parabacteroides merdae against OSA. It also revealed the mediating role of 2-hydroxypalmitate in the relationship between species Parabacteroides merdae and OSA.

PMID:40927699 | PMC:PMC12415091 | DOI:10.2147/NSS.S527778

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Changing Utilization of Primary Anatomic and Reverse Shoulder Arthroplasty in a Single High-Volume Institution: A Retrospective Cohort Study

Orthop Res Rev. 2025 Sep 3;17:421-426. doi: 10.2147/ORR.S515073. eCollection 2025.

ABSTRACT

OBJECTIVE: The incidence of total shoulder arthroplasty (TSA) in the United States continues to climb as an aging yet active population increases demand for the procedure. Due to promising clinical results out of Europe, improvement in prosthesis design, and wider acceptance of reverse total shoulder arthroplasty (rTSA), this study was designed to evaluate how rTSA and anatomical TSA (aTSA) utilization, patient selection, and length of stay have changed at a single institution.

METHODS: This was a retrospective cohort study of patients from one hospital system between 2017 and 2023. Inclusion criteria included primary TSA cases using CPT codes. Exclusion criteria included hemiarthroplasty, revision arthroplasty, non-arthroplasty procedures. Primary arthroplasty procedures were separated into reverse or anatomic cohorts for analysis. Independent sample t-tests were used to compare continuous data between the first and last year of cohort data and to compare parameters between procedure types. Chi-square analysis was used for frequency-based data comparisons. Type-I error was set at α=0.05 for all analyses.

RESULTS: From all 2774 shoulder arthroplasty cases identified, 2604 TSA cases were included in the final statistical analyses, 2114 of which were rTSA and 490 anatomic TSA. Comparison of arthroplasties in 2017 and 2023 revealed, rTSA increased from 115 surgery cases to 549, or 77.18% to 82.81% over the study period (p < 0.001). Anatomic TSA increased in total surgery cases from 29 to 111, (p = 0.655) and thus signifies an overall decrease in anatomic surgery utilization from 19.46% to 16.74%. Data showed an increase in average patient age for rTSA and decreased procedure time and length of stay for both groups.

CONCLUSION: rTSA utilization has surpassed and continues to increase relative to anatomic TSA. Peri-operative management of shoulder replacement has become more efficient with significantly decreased procedure time and decreased total hospital length of stay after primary TSA.

PMID:40927697 | PMC:PMC12415622 | DOI:10.2147/ORR.S515073

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Clinical manifestations of Oropouche virus infection: A systematic review and meta-analysis

Med Int (Lond). 2025 Aug 27;5(6):67. doi: 10.3892/mi.2025.266. eCollection 2025 Nov-Dec.

ABSTRACT

Oropouche virus (OROV) is emerging as a growing public health concern, with increasing numbers of case, an expanding global spread and the potential for severe clinical outcomes. However, despite the increasing incidence, the clinical features of OROV infections have not yet been thoroughly examined. The present systematic review and meta-analysis aimed to investigate the prevalence of clinical manifestations in OROV infections. For this purpose, a comprehensive search across PubMed, Web of Science and Embase was conducted up to April 9, 2025, to identify relevant studies. A random effects model was employed to calculate the pooled prevalence and 95% confidence intervals were calucalted. Heterogeneity was assessed using the I2 statistic. Additionally, sensitivity analyses and publication bias assessments were conducted to ensure the robustness of our findings. The present study included 28 articles and assessed 4,196 patients with OROV infection from 6 countries across the globe. The pooled prevalence of clinical manifestations of OROV included fever (97%), headache (86.5%), myalgia (72.3%), malaise or fatigue (56.4%), arthralgia (50.3%), chills (49.6%), loss of appetite (44.3%), eye pain (43.2%), back pain (31.7%), pallor (31.7%), dizziness (30.2%), photophobia (30.9%), nausea/vomiting (28.9%), sore throat (26.1%), odynophagia (22.9%), diarrhea (18.4%), skin rash (18.2%), conjunctival injection (15.4%), abdominal pain (16.3%), petechiae (2.3%), cough (12.9%), and chest pain (0.7%). High heterogeneity was detected among the included studies, which may be attributed to differences in geographic locations and diagnostic methodologies. Sensitivity analyses further supported the robustness of our findings. On the whole, the present systematic review provides a comprehensive analysis of the clinical manifestations of OROV infection, highlighting key symptoms that may aid in differential diagnosis in arbovirus-endemic regions. The findings may provide critical insight for clinicians and public health professionals and lay the groundwork for future research on the pathogenesis and epidemiology of OROV.

PMID:40927694 | PMC:PMC12416135 | DOI:10.3892/mi.2025.266

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Patterns of extreme outlier gene expression suggest an edge of chaos effect in transcriptomic networks

Genome Biol. 2025 Sep 9;26(1):272. doi: 10.1186/s13059-025-03709-0.

ABSTRACT

BACKGROUND: Most RNA-seq datasets harbor genes with extreme expression levels in some samples. Such extreme outliers are usually treated as technical errors and are removed from the data before further statistical analysis. Here we focus on the patterns of such outlier gene expression to investigate whether they provide insights into the underlying biology.

RESULTS: Our study is based on multiple datasets, including data from outbred and inbred mice, GTEx data from humans, data from different Drosophila species, and single-nuclei sequencing data from human brain tissues. All show comparable general patterns of outlier gene expression, indicating this as a generalizable biological effect. Different individuals can harbor very different numbers of outlier genes, with some individuals showing extreme numbers in only one out of several organs. Outlier gene expression occurs as part of co-regulatory modules, some of which correspond to known pathways. In a three-generation family analysis in mice, we find that most extreme over-expression is not inherited, but appears to be sporadically generated. Genes encoding prolactin and growth hormone are also among the co-regulated genes with extreme outlier expression, both in mice and humans, for which we include also a longitudinal expression analysis for protein data.

CONCLUSIONS: We show that outlier patterns of gene expression are a biological reality occurring universally across tissues and species. Most of the outlier expression is spontaneous and not inherited. We suggest that the outlier patterns reflect edge of chaos effects that are expected for systems of non-linear interactions and feedback loops, such as gene regulatory networks.

PMID:40926263 | DOI:10.1186/s13059-025-03709-0

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Identifying levels of alcohol use disorder severity in electronic health records

Subst Abuse Treat Prev Policy. 2025 Sep 8;20(1):36. doi: 10.1186/s13011-025-00670-w.

ABSTRACT

BACKGROUND: Alcohol use disorder (AUD) is conceptualized as a dimensional phenomenon in the DSM-5, but electronic health records (EHRs) rely on binary AUD definitions according to the ICD-10. The present study classifies AUD severity levels using EHR data and tests whether increasing AUD severity levels are linked with increased comorbidity.

METHODS: Billing data from two German statutory health insurance companies in Hamburg included n = 21,954 adults diagnosed with alcohol-specific conditions between 2017 and 2021. Based on ICD-10 alcohol-specific diagnoses, patients were classified into five AUD severity levels: 1 (F10.0, T51.0 or T51.9); 2 (F10.1); 3 (F10.2); 4 (F10.3/4); 5 (K70 + or one of the following diagnoses: K70.0-4, K70.9, K85.2, K85.20, K86.0, 10.5-9, E24.4, G31.2, G62.1, G72.1, I42.6, K29.2). Generalized estimating equation regression models for count data (Poisson distribution) were used to assess associations with the Elixhauser Comorbidity Score (ECS).

RESULTS: Across the study period, the annual prevalence of any AUD diagnosis varied between 2.7% and 2.9%. A dose-response relationship was observed between AUD severity and ECS, indicating that individuals with higher AUD severity experience more comorbid conditions, particularly cardiovascular and liver diseases.

CONCLUSIONS: The proposal to define AUD severity levels based on ICD-10 diagnoses allows for a more nuanced analysis of AUD in EHR data.

PMID:40926261 | DOI:10.1186/s13011-025-00670-w

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Two step approach for detecting and segmenting the second mesiobuccal canal of maxillary first molars on cone beam computed tomography (CBCT) images via artificial intelligence

BMC Oral Health. 2025 Sep 8;25(1):1404. doi: 10.1186/s12903-025-06796-4.

ABSTRACT

AIM: The purpose of this study was to assess the accuracy of a customized deep learning model based on CNN and U-Net for detecting and segmenting the second mesiobuccal canal (MB2) of maxillary first molar teeth on cone beam computed tomography (CBCT) scans.

METHODOLOGY: CBCT scans of 37 patients were imported into 3D slicer software to crop and segment the canals of the mesiobuccal (MB) root of the maxillary first molar. The annotated data were divided into two groups: 80% for training and validation and 20% for testing. The data were used to train the AI model in 2 separate steps: a classification model based on a customized CNN and a segmentation model based on U-Net. A confusion matrix and receiver-operating characteristic (ROC) analysis were used in the statistical evaluation of the results of the classification model, whereas the Dice-coefficient (DCE) was used to express the segmentation accuracy.

RESULTS: F1 score, testing accuracy, recall and precision values were 0.93, 0.87, 1.0 and 0.87 respectively, for the cropped images of MB root of maxillary 1st molar teeth in the testing group. The testing loss was 0.4, and the area under the curve (AUC) value was 0.57. The segmentation accuracy results were satisfactory, where the DCE of training was 0.85 and DCE of testing was 0.79.

CONCLUSION: MB2 in the maxillary first molar can be precisely detected and segmented via the developed AI algorithm in CBCT images.

TRIAL REGISTRATION: Current Controlled Trial Number NCT05340140. April 22, 2022.

PMID:40926256 | DOI:10.1186/s12903-025-06796-4