Swallowing Assessment using High-Resolution Cervical Auscultations and Transformer-based Neural Networks.

Swallowing assessment is a crucial task to reveal swallowing abnormalities. There are multiple modalities to analyze swallowing kinematics, such as videofluoroscopic swallow studies (VFSS), which is the gold standard method, and high-resolution cervical auscultation (HRCA), which is a noninvasive technique that uses a triaxial accelerometer attached to the patient's neck. Deep learning models play an essential role in data driven analysis of swallowing landmarks using VFSS and/or HRCA as input data.

Towards Non-Invasive Swallowing Assessment: an AI-Powered Interface for Swallowing Kinematic Analysis using High-Resolution Cervical Auscultation.

Swallowing is a pivotal physiological function for human sustenance and hydration. Dysfunctions, termed dysphagia, necessitate prompt and precise diagnosis. Videofluoroscopic swallowing studies (VFSS) remain the gold standard for swallowing assessment but pose accessibility and radiation exposure concerns.

Assessing the capture of sociodemographic information in electronic medical records to inform clinical decision making.

There is a growing need to document sociodemographic factors in electronic medical records to produce representative cohorts for medical research and to perform focused research for potentially vulnerable populations. The objective of this work was to assess the content of family physicians' electronic medical records and characterize the quality of the documentation of sociodemographic characteristics. Descriptive statistics were reported for each sociodemographic characteristic.

Electrocardiogram-based machine learning for risk stratification of patients with suspected acute coronary syndrome.

Background And Aims: The importance of risk stratification in patients with chest pain extends beyond diagnosis and immediate treatment. This study sought to evaluate the prognostic value of electrocardiogram feature-based machine learning models to risk-stratify all-cause mortality in those with chest pain.

Methods: This was a prospective observational cohort study of consecutive, non-traumatic patients with chest pain.

Machine Learning to Detect Cervical Spine Fractures Missed by Radiologists on CT: Analysis Using Seven Award-Winning Models from the RSNA 2022 Cervical Spine Fracture AI Challenge.

Available data on radiologists' missed cervical spine fractures are based primarily on studies using human reviewers to identify errors on re-evaluation; such studies do not capture the full extent of missed fractures. To use machine-learning (ML) models to identify cervical spine fractures on CT missed by interpreting radiologists, characterize the nature of these fractures, and assess their clinical significance. This retrospective study included all cervical spine CT examinations performed in adult patients in the emergency department between January 1, 2018 and December 31, 2022.

Elevating Patient Care With Deep Learning: High-Resolution Cervical Auscultation Signals for Swallowing Kinematic Analysis in Nasogastric Tube Patients.

Patients with nasogastric (NG) tubes require careful monitoring due to the potential impact of the tube on their ability to swallow safely. This study aimed to investigate the utility of high-resolution cervical auscultation (HRCA) signals in assessing swallowing functionality of patients using feeding tubes. HRCA, capturing swallowing vibratory and acoustic signals, has been explored as a surrogate for videofluoroscopy image analysis in previous research.

RSNA 2023 Abdominal Trauma AI Challenge: Review and Outcomes.

Purpose To evaluate the performance of the winning machine learning models from the 2023 RSNA Abdominal Trauma Detection AI Challenge. Materials and Methods The competition was hosted on Kaggle and took place between July 26 and October 15, 2023. The multicenter competition dataset consisted of 4274 abdominal trauma CT scans, in which solid organs (liver, spleen, and kidneys) were annotated as healthy, low-grade, or high-grade injury.

Assessing the Performance of Models from the 2022 RSNA Cervical Spine Fracture Detection Competition at a Level I Trauma Center.

Purpose To evaluate the performance of the top models from the RSNA 2022 Cervical Spine Fracture Detection challenge on a clinical test dataset of both noncontrast and contrast-enhanced CT scans acquired at a level I trauma center. Materials and Methods Seven top-performing models in the RSNA 2022 Cervical Spine Fracture Detection challenge were retrospectively evaluated on a clinical test set of 1828 CT scans (from 1829 series: 130 positive for fracture, 1699 negative for fracture; 1308 noncontrast, 521 contrast enhanced) from 1779 patients (mean age, 55.8 years ± 22.

Deep immune cell phenotyping and induced immune cell responses at admission stratified by BMI in patients hospitalized with COVID-19: An observational multicenter cohort pilot study.

Introduction: Overweight and obesity are linked to increased hospitalization and mortality in COVID-19 patients. This study aimed to characterize induced immune responses and deep immune cell profiles stratified by BMI in hospitalized COVID-19 patients.

Methods And Results: This observational multicenter cohort pilot study included 122 adult patients with PCR-confirmed COVID-19 in Denmark, stratified by BMI (normal weight, overweight, obese).

Towards a comprehensive bedside swallow screening protocol using cross-domain transformation and high-resolution cervical auscultation.

High-resolution cervical auscultation (HRCA) is an emerging noninvasive and accessible option to assess swallowing by relying upon accelerometry and sound sensors. HRCA has shown tremendous promise and accuracy in identifying and predicting swallowing physiology and biomechanics with accuracies equivalent to trained human judges. These insights have historically been available only through instrumental swallowing evaluation methods, such as videofluoroscopy and endoscopy.

Immune cell populations and induced immune responses at admission in patients hospitalized with vaccine breakthrough SARS-CoV-2 infections.

Background: Vaccine breakthrough SARS-CoV-2 infections are common and of clinical and public health concern. However, little is known about the immunological characteristics of patients hospitalized due to these infections. We aimed to investigate and compare immune cell subpopulations and induced immune responses in vaccinated and non-vaccinated patients hospitalized with severe COVID-19.

Corrigendum: Adiponectin as a predictor of mortality and readmission in patients with community-acquired pneumonia: a prospective cohort study.

[This corrects the article DOI: 10.3389/fmed.2024.

Adiponectin as a predictor of mortality and readmission in patients with community-acquired pneumonia: a prospective cohort study.

Background: Adiponectin is secreted by adipocytes and is inversely associated with obesity. Given the association between low body mass index (BMI) and higher mortality risk after community-acquired pneumonia (CAP), we hypothesized that high adiponectin levels are associated with a higher risk of adverse clinical outcomes in patients with CAP.

Methods: In a prospective cohort study of 502 patients hospitalized with CAP, adiponectin was measured in serum at admission.

Automatic Tracking of Hyoid Bone Displacement and Rotation Relative to Cervical Vertebrae in Videofluoroscopic Swallow Studies Using Deep Learning.

The hyoid bone displacement and rotation are critical kinematic events of the swallowing process in the assessment of videofluoroscopic swallow studies (VFSS). However, the quantitative analysis of such events requires frame-by-frame manual annotation, which is labor-intensive and time-consuming. Our work aims to develop a method of automatically tracking hyoid bone displacement and rotation in VFSS.

Fear of falling in community-dwelling older adults: What their gait acceleration pattern reveals.

Background: Fear of Falling (FOF) is common among community-dwelling older adults and is associated with increased fall-risk, reduced activity, and gait modifications.

Objective: In this cross-sectional study, we examined the relationships between FOF and gait quality.

Methods: Older adults (N=232; age 77±6; 65 % females) reported FOF by a single yes/no question.

Weekly minutes of moderate to vigorous physical activity is associated with movement quality in overweight and obese older adults, independent of age.

Background: Physical activity can improve function and decrease healthcare spending among overweight and obese older adults. Although unstructured physical activity has been related to cardiometabolic improvements, the relationship between unstructured activity and movement quality is unclear.

Aims: This study aimed to evaluate the association of amount of unstructured free-living moderate-vigorous physical activity (MVPA) with measures of movement quality in overweight and obese older adults.

Uneven surface and cognitive dual-task independently affect gait quality in older adults.

Background: Real-world mobility involves walking in challenging conditions. Assessing gait during simultaneous physical and cognitive challenges provides insights on cognitive health.

Research Question: How does uneven surface, cognitive task, and their combination affect gait quality and does this gait performance relate to cognitive functioning?

Methods: Community-dwelling older adults (N = 104, age=75 ± 6 years, 60 % females) performed dual-task walking paradigms (even and uneven surface; with and without alphabeting cognitive task (ABC)) to mimic real-world demands.

Correction: Bohlke et al. The Effect of a Verbal Cognitive Task on Postural Sway Does Not Persist When the Task Is Over. 2021, , 8428.

There was an error in the original publication [...

Weekly minutes of moderate to vigorous physical activity is associated with movement quality in overweight and obese older adults.

Background: Physical activity can improve function and decrease healthcare spending among overweight and obese older adults. Although unstructured physical activity has been related to cardiometabolic improvements, the relationship between unstructured activity and movement quality is unclear.

Aims: This study aimed to evaluate the association of amount of unstructured free-living moderate-vigorous physical activity (MVPA) with measures of movement quality in overweight and obese older adults.

Accelerometry applications and methods to assess standing balance in older adults and mobility-limited patient populations: a narrative review.

Accelerometers provide an opportunity to expand standing balance assessments outside of the laboratory. The purpose of this narrative review is to show that accelerometers are accurate, objective, and accessible tools for balance assessment. Accelerometry has been validated against current gold standard technology, such as optical motion capture systems and force plates.