Comparing mental health and substance use disorders in patients receiving durable VADs versus transplants: A TriNetX database analysis.

Ventricular assist device (VAD) and cardiac transplant patients experience significant strain on their physical and mental wellbeing postoperatively. Mental health and substance use disorders (MHDs and SUDs) have substantial effects on the quality of life and compliance of transplant and VAD patients. In this study, we compare and characterize MHDs and SUDs between VAD and cardiac allograft patients and transplant list patients with and without VADs.

Embracing the informative missingness and silent gene in analyzing biologically diverse samples.

Bioinformatics software tools are essential to identify informative molecular features that define different phenotypic sample groups. Among the most fundamental and interrelated tasks are missing value imputation, signature gene detection, and differential pattern visualization. However, many commonly used analytics tools can be problematic when handling biologically diverse samples if either informative missingness possess high missing rates with mixed missing mechanisms, or multiple sample groups are compared and visualized in parallel.

The clinical value of ultrasound-guided sacral anesthesia in Intracavitary and/or interstitial brachytherapy for cervical Cancer.

Objective: To explore the effectiveness and safety of ultrasound-guided sacral anesthesia in intracavitary and/or interstitial brachytherapy for cervical cancer patients.

Method: A retrospective analysis was conducted on a total of 1039 intracavitary and/or interstitial brachytherapy involving 220 patients in our department from December 7, 2020 to March 21, 2024. The study assessed the satisfaction with anesthesia, changes in vital signs, onset time of anesthesia, dosage of anesthetic drugs, duration of anesthesia, and incidence of adverse reactions.

The Long-Term Survival of LVAD Patients-A TriNetX Database Analysis.

Donor shortage limits the utilization of heart transplantation, making it available for only a fraction of the patients on the transplant waiting list. Therefore, continuous-flow left ventricular assist devices (CF-LVADs) have evolved as a standard of care for end-stage heart failure. It is imperative therefore to investigate long-term survival in this population.

Mental Health and Substance Use Disorders in Transplant Waitlist, VAD, and Heart Transplant Patients: A TriNetX Database Analysis.

: Mental health and substance use disorders (MHDs and SUDs) affect cardiac allograft and VAD recipients and impact their quality of life and compliance. Limited research currently exists on MHDs and SUDs in this population. : This study compares the incidence of MHDs and SUDs in the transplant list, VAD, and post-transplant patients with that in heart failure patients.

Propensity matched post-transplant survival in durable CF-axial pump BTT patients with and without diabetes: A UNOS database analysis.

Diabetes and post-transplant survival have been linked. However, the impact on post-transplant survival of patients supported on Continuous Flow (CF) axial left ventricular assist devices (LVAD) as a bridge to transplant (BTT) with diabetes has not been widely studied. This study attempts to assess the impact of diabetes type II (DM type II) as a comorbidity influencing survival patterns in the post-cardiac transplant population supported on LVADs and to test if the presence of a pre- transplant durable LVAD acts as an independent risk factor in long-term post-transplant survival.

ABDS: a bioinformatics tool suite for analyzing biologically diverse samples.

Bioinformatics software tools are essential to identify informative molecular features that define different phenotypic sample groups. Among the most fundamental and interrelated tasks are missing value imputation, signature gene detection, and differential pattern visualization. However, many commonly used analytics tools can be problematic when handling biologically diverse samples if either informative missingness possess high missing rates with mixed missing mechanisms, or multiple sample groups are compared and visualized in parallel.

Artificial Intelligence Approaches for Predicting the Risks of Durable Mechanical Circulatory Support Therapy and Cardiac Transplantation.

The use of AI-driven technologies in probing big data to generate better risk prediction models has been an ongoing and expanding area of investigation. The AI-driven models may perform better as compared to linear models; however, more investigations are needed in this area to refine their predictability and applicability to the field of durable MCS and cardiac transplantation. A literature review was carried out using Google Scholar/PubMed from 2000 to 2023.

CAM3.0: determining cell type composition and expression from bulk tissues with fully unsupervised deconvolution.

Motivation: Complex tissues are dynamic ecosystems consisting of molecularly distinct yet interacting cell types. Computational deconvolution aims to dissect bulk tissue data into cell type compositions and cell-specific expressions. With few exceptions, most existing deconvolution tools exploit supervised approaches requiring various types of references that may be unreliable or even unavailable for specific tissue microenvironments.

Machine learning models for diagnosis and risk prediction in eating disorders, depression, and alcohol use disorder.

This study uses machine learning models to uncover diagnostic and risk prediction markers for eating disorders (EDs), major depressive disorder (MDD), and alcohol use disorder (AUD). Utilizing case-control samples (ages 18-25 years) and a longitudinal population-based sample (n=1,851), the models, incorporating diverse data domains, achieved high accuracy in classifying EDs, MDD, and AUD from healthy controls. The area under the receiver operating characteristic curves (AUC-ROC [95% CI]) reached 0.

ABDS: tool suite for analyzing biologically diverse samples.

Motivation: Analytics tools are essential to identify informative molecular features about different phenotypic groups. Among the most fundamental tasks are missing value imputation, signature gene detection, and expression pattern visualization. However, most commonly used analytics tools may be problematic for characterizing biologically diverse samples when either signature genes possess uneven missing rates across different groups yet involving complex missing mechanisms, or multiple biological groups are simultaneously compared and visualized.

Preventive Effect of Local Lidocaine Administration on the Formation of Traumatic Neuroma.

Background: Traumatic neuroma is a common sequela of peripheral nerve injury or amputation, which often leads to severe neuropathic pain. The present study investigated the effect of local lidocaine administration on preventing the formation of traumatic neuroma.

Methods: Forty-eight male Sprague-Dawley rats were randomly assigned to two groups.

Prediction of the Efficacy of Lumbar Sympathetic Block in Patients with Lower Extremity Complex Regional Pain Syndrome Type 1 Based on the Sympathetic Skin Response.

Introduction: Complex regional pain syndrome type 1 (CRPS-1) is prevalent after trauma, with intractable pain being the most prominent clinical symptom. The impact of sympathetic block on CRPS is unclear. The goal of this study was to explore the characteristics that predict successful symptom relief with lumbar sympathetic block (LSB) in patients with lower extremity CRPS-1.

Skin Cancer Risk Prediction in Heart Transplant Recipients.

Objectives: This study was undertaken to derive a risk prediction model for skin cancer utilizing the United Network for Organ Sharing database population.

Materials And Methods: Of the 24734 adults (>18 years old) heart transplant recipients (2000-2015) in the United Network for Organ Sharing database, 2625 recipients developed skin cancer. Univariate and multivariate Cox regression analyses were performed; P values, hazard ratios, and confidence intervals were derived.

Musical therapy attenuates neuroma pain by modifying leptin expression.

Background: Accumulating evidence reveals that music therapy appears to help patients with pain. However, there is a limited understanding of the underlying mechanisms. Several studies indicate that leptin level has a crucial relationship with acute and chronic pain.

Cosbin: cosine score-based iterative normalization of biologically diverse samples.

Motivation: Data normalization is essential to ensure accurate inference and comparability of gene expression measures across samples or conditions. Ideally, gene expression data should be rescaled based on consistently expressed reference genes. However, to normalize biologically diverse samples, the most commonly used reference genes exhibit striking expression variability and size-factor or distribution-based normalization methods can be problematic when the amount of asymmetry in differential expression is significant.

Risk Prediction Model for Survival of Wait-List Patients on Axial CF-LVAD: A UNOS Database Analysis.

Background: Continuous flow left ventricular assist devices (CF-LVADs) have become a viable option for patients with end-stage heart failure as a bridge to transplantation or the destination therapy.

Methods: Adult patients listed for heart transplantation (2010-2015) with an axial CF-LVAD on the wait list were obtained from the UNOS database. The multivariate Cox regression model was used to predict the probability of survival after listing.

Mechanosensitive Ion Channel TMEM63A Gangs Up with Local Macrophages to Modulate Chronic Post-amputation Pain.

Post-amputation pain causes great suffering to amputees, but still no effective drugs are available due to its elusive mechanisms. Our previous clinical studies found that surgical removal or radiofrequency treatment of the neuroma at the axotomized nerve stump effectively relieves the phantom pain afflicting patients after amputation. This indicated an essential role of the residual nerve stump in the formation of chronic post-amputation pain (CPAP).

The Tourniquet Ischemia Test Effectively Predicts the Efficacy of Lumbar Sympathetic Block in Patients with Lower Extremity Complex Regional Pain Syndrome Type 1.

Background: Neuropathic pain is the most common clinical sign of complex regional pain syndrome (CRPS). Currently, lumbar sympathetic block (LSB) is commonly utilized in lower extremity CRPS that has failed to respond to medication therapy and physical therapy, but its effectiveness is unknown. The tourniquet ischemia test (IT) can distinguish between two types of CRPS: IT-positive CRPS and IT-negative CRPS.

Ultrasound-Guided Extraforaminal Thoracic Nerve Root Block Through the Midpoint of the Inferior Articular Process and the Parietal Pleura: A Clinical Application of Thoracic Paravertebral Nerve Block.

Purpose: Thoracic nerve root (TNR) block is performed primarily under computed tomography or X-ray fluoroscopy but is associated with radiation exposure. Ultrasound requires no radiation and distinguishes vessels, nerves, pleura, and other tissues. Few reports of ultrasound-guided TNR (US-TNR) block have been described, and the puncture end point has not been clearly defined.

Control of a Mechanical Blood Pump based on a Trade-off between Aortic Valve Dynamics and Cardiac Outputs.

Left ventricular assist device (LVAD) is a therapeutic option for advanced heart failure (HF) patients. This mechanical device assists a failing heart to circulate blood in the human body by adjusting its pump speed according to cardiac output. However, to use an LVAD for bridge-to-recovery, other criteria (e.

Deep Neural Network-Based Survival Analysis for Skin Cancer Prediction in Heart Transplant Recipients.

Heart-transplant recipients are at high risk of developing skin cancer, while Squamous Cell Carcinoma (SCC) and Basal Cell Carcinoma (BCC) are commonly detected. This paper utilized the database from the United Network for Organ Sharing (UNOS) to study the incidence rate of SCC and BCC among heart transplant recipients. Cox proportional hazards model and two deep neural network-based models were studied, and their performance were compared.