Obesity portends an increased risk of thromboembolic events in severely injured geriatric trauma, a retrospective study.

Background: Obesity is a known risk factor for thromboembolic complications in trauma patients. The aim of our study is to evaluate the prevalence of thrombotic complications in obese geriatric patients.

Methods: We performed a retrospective analysis of TQIP (2017-2019).

Geriatric falls: an enormous economic burden compared to firearms.

Background: This study aimed to assess the medical costs, and the combined costs of fatal firearm injury and fatal falls during a 5 year period. While fatal firearm injury represents a significant public health concern, the healthcare community is faced with the significant challenge of fatal falls, particularly in light of the elderly population growth.

Methods: Data were exported from the Web-based Injury Statistics Query and Reporting System database for fatal firearm and falls in patients aged between 15-85 years-old.

Message-Passing Monte Carlo: Generating low-discrepancy point sets via graph neural networks.

Discrepancy is a well-known measure for the irregularity of the distribution of a point set. Point sets with small discrepancy are called low discrepancy and are known to efficiently fill the space in a uniform manner. Low-discrepancy points play a central role in many problems in science and engineering, including numerical integration, computer vision, machine perception, computer graphics, machine learning, and simulation.

Identifying psychological predictors of SARS-CoV-2 vaccination: A machine learning study.

Background: Major barriers to addressing SARS-CoV-2 vaccine hesitancy include limited knowledge of what causes delay/refusal of SARS-CoV-2 vaccination and limited ability to predict who will remain unvaccinated over significant time periods despite vaccine availability. The present study begins to address these barriers by developing a machine learning model that prospectively predicts who will persist in not vaccinating against SARS-CoV-2.

Method: Unvaccinated individuals (n = 325) who completed a baseline survey were followed over the six-month period when vaccines against SARS-CoV-2 were first widely available (April-October 2021).

The differential burden of 3 health care-associated infections on hospital costs and lengths of stay: A quasi-experimental case-control observation.

In patients with a health care-associated infection (HAI), lengths of stay and costs increased >150% from 2019 to 2023, and were 2 to 6 times greater compared to concurrent non-HAI patients with the same diagnoses. Unlike surgical HAI, no device-associated HAI occurred before hospital day 12. These findings highlight the possibly under-recognized influence of delayed discharges on device-associated HAIs.

Step-by-step roadmap to building a robotic acute care surgery program (RACSP) in a level I trauma center: outcomes and lessons learned after 1-year implementation.

Minimally invasive surgical techniques have demonstrated superior outcomes across various elective procedures. Laparoscopic surgery (LS) is established in general surgery with laparoscopic operations for acute appendicitis and cholecystitis being the standard of care. Robotic surgery (RS) has been associated with equivalent or improved postoperative outcomes compared with LS.

Graph Kernel Neural Networks.

The convolution operator at the core of many modern neural architectures can effectively be seen as performing a dot product between an input matrix and a filter. While this is readily applicable to data such as images, which can be represented as regular grids in the Euclidean space, extending the convolution operator to work on graphs proves more challenging, due to their irregular structure. In this article, we propose to use graph kernels, i.

Shock Index is a Stronger Predictor of Outcomes in Older Compared to Younger Patients.

Introduction: The shock index (SI) is a known predictor of unfavorable outcomes in trauma. This study seeks to examine and compare the SI values between geriatric patients and younger adults.

Methods: We conducted a retrospective study of the Trauma Quality Improvement Program database from 2017 to 2019.

Trajectories and predictors of response to social cognition training in people with schizophrenia: A proof-of-concept machine learning study.

Background: Social cognition training (SCT) can improve social cognition deficits in schizophrenia. However, little is known about patterns of response to SCT or individual characteristics that predict response.

Methods: 76 adults with schizophrenia randomized to receive 8-12 weeks of remotely-delivered SCT were included in this analysis.

Combinatorial prediction of therapeutic perturbations using causally-inspired neural networks.

As an alternative to target-driven drug discovery, phenotype-driven approaches identify compounds that counteract the overall disease effects by analyzing phenotypic signatures. Our study introduces a novel approach to this field, aiming to expand the search space for new therapeutic agents. We introduce PDGrapher, a causally-inspired graph neural network (GNN) designed to predict combinatorial perturbagens - sets of therapeutic targets - capable of reversing disease effects.

A new age in protein design empowered by deep learning.

The rapid progress in the field of deep learning has had a significant impact on protein design. Deep learning methods have recently produced a breakthrough in protein structure prediction, leading to the availability of high-quality models for millions of proteins. Along with novel architectures for generative modeling and sequence analysis, they have revolutionized the protein design field in the past few years remarkably by improving the accuracy and ability to identify novel protein sequences and structures.

RECOVER identifies synergistic drug combinations in vitro through sequential model optimization.

For large libraries of small molecules, exhaustive combinatorial chemical screens become infeasible to perform when considering a range of disease models, assay conditions, and dose ranges. Deep learning models have achieved state-of-the-art results in silico for the prediction of synergy scores. However, databases of drug combinations are biased toward synergistic agents and results do not generalize out of distribution.

Genomic-driven nutritional interventions for radiotherapy-resistant rectal cancer patient.

Radiotherapy response of rectal cancer patients is dependent on a myriad of molecular mechanisms including response to stress, cell death, and cell metabolism. Modulation of lipid metabolism emerges as a unique strategy to improve radiotherapy outcomes due to its accessibility by bioactive molecules within foods. Even though a few radioresponse modulators have been identified using experimental techniques, trying to experimentally identify all potential modulators is intractable.

Diagnosis and management of prolactin-secreting pituitary adenomas: a Pituitary Society international Consensus Statement.

This Consensus Statement from an international, multidisciplinary workshop sponsored by the Pituitary Society offers evidence-based graded consensus recommendations and key summary points for clinical practice on the diagnosis and management of prolactinomas. Epidemiology and pathogenesis, clinical presentation of disordered pituitary hormone secretion, assessment of hyperprolactinaemia and biochemical evaluation, optimal use of imaging strategies and disease-related complications are addressed. In-depth discussions present the latest evidence on treatment of prolactinoma, including efficacy, adverse effects and options for withdrawal of dopamine agonist therapy, as well as indications for surgery, preoperative medical therapy and radiation therapy.

Intraoperative Nerve Stimulation as an Approach for the Surgical Treatment of Genitofemoral Neuralgia.

BACKGROUND Genitofemoral neuralgia is a pain syndrome that involves injury to the genitofemoral nerve and is frequently iatrogenic. We report intraoperative nerve localization using ultrasound, nerve stimulation, and the cremasteric reflex in the surgical treatment of genitofemoral neuralgia. CASE REPORT A 49-year-old man with a history of extracorporeal membrane oxygenation with cannulation sites in bilateral inguinal regions presented with right groin numbness and pain following decannulation.

Social interpretation inflexibility moderates emotional reactions to social situations in children and adolescents.

Interpretation biases and inflexibility (i.e., difficulties revising interpretations) have been linked to increased internalizing symptoms.

Using machine learning to decode animal communication.

New methods promise transformative insights and conservation benefits.

Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications.

Graphs are a powerful tool for representing and analyzing unstructured, non-Euclidean data ubiquitous in the healthcare domain. Two prominent examples are molecule property prediction and brain connectome analysis. Importantly, recent works have shown that considering relationships between input data samples has a positive regularizing effect on the downstream task in healthcare applications.