The Association Between the CALLY Index and All-Cause Mortality in Patients with COPD: Results from the Cohort Study of NHANES 2007-2010.

Purpose: The C-reactive protein (CRP)-albumin-lymphocyte (CALLY) index is a newly developed biomarker that combines measurements of CRP, serum albumin, and lymphocyte count. This index provides a thorough assessment of a patient's inflammation level, nutritional condition, and immunological function. The objective of this study is to examine the correlation between the CALLY index and all-cause mortality in COPD patients.

The Diagnostic Value of Plasma NETs Levels and iCEB in Silent Myocardial Ischemia in Maintenance Hemodialysis Patients.

Objective: This study evaluated the diagnostic value of plasma Neutrophil extracellular traps (NETs) levels and the index of cardiac electrophysiological balance (iCEB) in identifying silent myocardial ischemia (SMI) in maintenance hemodialysis (MHD) patients.

Methods: This cross-sectional observational study involved patients receiving MHD treatment. Data were collected on coronary angiography performed in our hospital from February 2023 to February 2024.

Comprehensive Sepsis Risk Prediction in Leukemia Using a Random Forest Model and Restricted Cubic Spline Analysis.

Background: Sepsis is a severe complication in leukemia patients, contributing to high mortality rates. Identifying early predictors of sepsis is crucial for timely intervention. This study aimed to develop and validate a predictive model for sepsis risk in leukemia patients using machine learning techniques.

Diagnostic accuracy of Bellavere's score in cardiac autonomic neuropathy among chronic kidney disease patients: a study of prevalence and dialysis impact.

Background: Cardiac autonomic neuropathy (CAN) is a significant complication in chronic kidney disease (CKD), leading to increased morbidity and mortality. Early detection is essential for managing CKD patients effectively, especially those on hemodialysis. This study evaluated the prevalence CAN in CKD and diagnostic accuracy of Bellavere's Score in predicting CAN in CKD patients, including those undergoing hemodialysis.

The Relationship of Fatty Liver with Body Composition Indices in Individuals with Metabolic Disorders - A Cross-Sectional Study.

Objective: In this study, it was aimed to screen fatty liver in individuals with metabolic disorders, and to investigate the use of some anthropometric calculations and body composition indices in demonstrating fatty liver disease.

Methods: The cross-sectional study included 224 participants with metabolic diseases. Anthropometric measurements of the participants were measured.

Relationship between pregnant women's combined exposure to heavy metals and their offspring's congenital heart defects in Lanzhou, China.

Background: Previous research has demonstrated that exposure to individual heavy metals elevates the incidence rate of congenital heart defects (CHDs). However, there is a paucity of data concerning the relationship between combined exposure to multiple heavy metals and the occurrence of CHDs. This study seeks to investigate the association between combined heavy metal exposure in pregnant women and the incidence of CHDs in their offspring in Lanzhou, China.

Qualitative and Quantitative Evaluation of the Image Quality of MDCT Multiphasic Liver Scans in HCC Patients.

The quality of CT images obtained from hepatocellular carcinoma (HCC) patients is complex, affecting diagnostic accuracy, precision, and radiation dose assessment due to increased exposure risks. The study evaluated image quality qualitatively and quantitatively by comparing quality levels with an effective radiation dose to ensure acceptable quality accuracy. This study retrospectively reviewed 100 known HCC patients (Li-RADS-5) who underwent multidetector computed tomography (MDCT) multiphasic scans for follow-up of their health condition between January and October 2023.

The value of a metabolic and immune-related gene signature and adjuvant therapeutic response in pancreatic cancer.

Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy characterized by a dismal prognosis. Treatment outcomes exhibit substantial variability across patients, underscoring the urgent need for robust predictive models to effectively estimate survival probabilities and therapeutic responses in PDAC.

Methods: Metabolic and immune-related genes exhibiting differential expression were identified using the TCGA-PDAC and GTEx datasets.

Predicting risk of maternal critical care admission in Scotland: Development of a risk prediction model.

Background: Identifying women at highest or lowest risk of perinatal intensive care unit (ICU) admission may enable clinicians to risk stratify women antenatally so that enhanced care or elective admission to ICU may be considered or excluded in birthing plans. We aimed to develop a statistical model to predict the risk of maternal ICU admission.

Methods: We studied 762,918 pregnancies between 2005 and 2018.

The independent predictive value of admission serum ferritin concentration for prognosis in elderly patients with community-acquired pneumonia in the emergency department.

Background: Community-acquired pneumonia (CAP) poses a significant health threat to the elderly population, leading to high morbidity and mortality rates. Serum ferritin, a critical indicator of iron metabolism, plays a pivotal role in inflammation and immune regulation. Nevertheless, its specific prognostic relevance in elderly patients with CAP remains unclear.

A New Risk Score Based on Lipid Indicators for Patients with Advanced Hepatocellular Carcinoma.

Background: The prognosis is extremely troubling in advanced hepatocellular carcinoma (HCC). Prognostic scores have been developed. Yet, the positive predictive values might appear inadequate.

A Machine Learning Model for Predicting Prognosis in HCC Patients With Diabetes After TACE.

Purpose: Type II diabetes mellitus (T2DM) has been found to increase the mortality of patients with hepatocellular carcinoma (HCC). Therefore, this study aimed to establish and validate a machine learning-based explainable prediction model of prognosis in patients with HCC and T2DM undergoing transarterial chemoembolization (TACE).

Patients And Methods: The prediction model was developed using data from the derivation cohort comprising patients from three medical centers, followed by external validation utilizing patient data extracted from another center.

Post-Implant Global Longitudinal Strain as a Predictor of Pacing-Induced Cardiomyopathy in Patients with Preserved Ejection Fraction Undergoing Pacemaker Placement.

Background: Right ventricular (RV) pacing exacerbates heart failure and increases cardiac mortality in patients with reduced ejection fraction (EF). However, its impact on left ventricular dysfunction in patients with preserved EF remains inconclusive. This study investigates the relationship between RV pacing, global longitudinal strain (GLS), and EF in patients with preserved EF.

Construction and Validation of a Major Depression Risk Predictive Model for Patients with Coronary Heart Disease: Insights from NHANES 2005-2018.

Background: This study aimed to develop and validate a predictive model for major depression risk in adult patients with coronary heart disease (CHD), offering evidence for targeted prevention and intervention.

Methods: Using data from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018, 1098 adults with CHD were included. A weighted logistic regression model was applied to construct and validate a nomogram-based prediction tool for major depression in this population.

Risk Estimation of Severe Primary Graft Dysfunction in Heart Transplant Recipients Using a Smartphone.

Background: Currently, there are no standardized guidelines for graft allocation in heart transplants (HTxs), particularly when considering organs from marginal donors and donors after cardiocirculatory arrest. This complexity highlights the need for an effective risk analysis tool for primary graft dysfunction (PGD), a severe complication in HTx. Existing score systems for predicting PGD lack superior predictive capability and are often too complex for routine clinical use.

Analysis of Metabolic Risk Factors for Microcirculation Disorders Post-Percutaneous Coronary Intervention and Predictive Model Construction: A Study on Patients with Unstable Angina.

Background: This study aimed to analyze the metabolic risk factors for microcirculation disorders in patients with unstable angina (UA) after percutaneous coronary intervention (PCI), evaluating their predictive value for developing microcirculation disorders.

Methods: A single-center retrospective study design was used, which included 553 patients with UA who underwent PCI. The angiographic microcirculatory resistance (AMR) index was calculated based on coronary angiography data.

Association of Serum Gamma-Glutamyltransferase with In-hospital Heart Failure in Patients with ST-segment Elevation Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention.

Background: To explore the association between gamma-glutamyltransferase (GGT) and in-hospital heart failure (HF) in patients with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PCI).

Methods: A total of 412 patients diagnosed with STEMI and treated with primary PCI were included in our study. Univariate and multivariate logistic regression models were used to evaluate the association between GGT and the risk of in-hospital HF in STEMI patients.

Correlation between weight-adjusted waist index and coronary heart disease: NHANES 1999-2020.

Background: The weight adjusted waist index (WWI) represents a novel indicator for assessing central obesity. The objective of this study is to investigate the association between WWI and coronary heart disease (CHD).

Method: The data of 44,528 participants in total were gathered from NHANES database from 1999 to 2020.

Improving Patient Outcomes in mTBI: The Role of Integrated Nursing Interventions in the Emergency Department.

Background: Traumatic brain injury (TBI) is a major cause of morbidity and mortality, often requiring emergency department (ED) management. Integrated Nursing Interventions play a critical role in the care of TBI patients, but limited research has evaluated their efficacy in this setting. This study aims to assess the impact of Integrated Nursing Interventions on patient outcomes and complications in the ED.

Nutritional risk and HbA1c as critical risk factors and predictors of opportunistic infections in HIV-DM comorbid patients: a retrospective cross-sectional study.

Background: The clinical characteristics and risk factors for opportunistic infections in HIV patients with concomitant diabetes mellitus are unclear and worth studying. Explore the risk factors and construct a predictive model for opportunistic infections in HIV-DM patients.

Methods: Clinical data were retrospectively collected from 1,669 HIV-DM admitted to the Public Health Clinical Center of Chengdu from December 2018 to November 2023.

A multivariable model of ultrasound and biochemical parameters for predicting high-volume lymph node metastases of papillary thyroid carcinoma with Hashimoto's thyroiditis.

Objectives: This study aims to develop a nomogram to predict high-volume (> 5) lymph node metastases (HVLNM) in papillary thyroid carcinoma concomitant with Hashimoto's thyroiditis by combining ultrasound with clinicopathologic data.

Materials And Methods: The study reviewed 187 patients diagnosed with papillary thyroid cancer (PTC) concomitant with Hashimoto's thyroiditis from the First People's Hospital of Kunshan between March 2018 and December 2022. These patients underwent preoperative ultrasound and postoperative examinations.

A nomogram for predicting bladder dysfunction in patients with type 2 diabetes mellitus: a retrospective study.

Background: Diabetic bladder dysfunction (DBD) is a common urinary complication in diabetic patients, significantly affecting their overall well-being and quality of life, and placing a considerable burden on healthcare resources. Early prevention is crucial; however, the absence of a simple and effective tool to predict DBD onset remains a significant challenge. This study aims to identify risk factors for DBD in patients with type 2 diabetes mellitus (T2DM) and to develop a predictive nomogram for clinical application.

Correlation Between the Ratio of Uric Acid to High-Density Lipoprotein Cholesterol (UHR) and Diabetic Retinopathy in Patients with Type 2 Diabetes Mellitus:A Cross-Sectional Study.

Background/objective: Considering the uncertain relationship between high-density lipoprotein cholesterol (HDL-C) and uric acid (UA) with diabetic retinopathy (DR),this study investigates the link between Uric Acid to High-Density Lipoprotein Cholesterol (UHR) and DR in T2DM patients, evaluating its potential for DR diagnosis and early prediction.

Study Design And Data Collection: This retrospective study analyzed 1450 type 2 diabetes patients, divided into NDR and DR groups by retinal exams. We gathered demographic and clinical data, calculated UHR, and explored its correlation with DR development.

Elucidating genetic intersections: Co-differentially expressed genes in myasthenia gravis and idiopathic inflammatory myopathies and their role in comorbid pathogenesis.

Background: Myasthenia gravis (MG) and idiopathic inflammatory myopathies (IIM) are autoimmune disorders that can co-occur, complicating diagnosis and treatment. The molecular mechanisms underlying this comorbidity are not well understood.

Objective: This study aims to identify common differentially expressed genes (co-DEGs) between MG and IIM to elucidate shared pathogenic pathways and potential therapeutic targets.

Risk factors analysis and risk prediction model for failed back surgery syndrome: A prospective cohort study.

Introduction: With the growing number of posterior open surgery, the incidence of failed back surgery syndrome (FBSS) increases gradually. Currently, there is a lack of predictive systems and scientific evaluation in clinical practice. This study aimed to risk factors analysis of FBSS and develop a risk prediction model.