AIMC Topic: Aged

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Association between fat-to-muscle ratio and secondary osteoporosis in rheumatoid arthritis: a cross-sectional study at a tertiary hospital in China.

BMJ open
OBJECTIVES: To investigate the correlation between fat-to-muscle ratio (FMR) or other body composition and secondary osteoporosis (OP) in patients with rheumatoid arthritis (RA) and to develop a predictive model using FMR and related clinical factors...

Enteral versus parenteral nutrition in auto-HCT: a randomized controlled trial on clinical outcomes and gut microbiome dynamics.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
Disruption of the gut microbiome is a common consequence of chemotherapy, linked with detrimental treatment outcomes (e.g. sepsis), especially in haematopoietic stem cell transplant (HCT) recipients. Preclinical data suggest that enteral nutrition (E...

Risk prediction of all-cause mortality in hospitalized patients with severe acute pancreatitis by serum urea nitrogen/albumin ratio.

PloS one
BACKGROUND: Classification of risk levels in patients with acute pancreatitis remains a difficult task. Although some biomarkers have emerged to predict the prognosis of patients with acute pancreatitis, they have not been widely used in clinical pra...

Optimized deep learning-accelerated single-breath-hold abdominal HASTE with and without fat saturation improves and accelerates abdominal imaging at 3 Tesla.

BMC medical imaging
BACKGROUND: Deep learning-accelerated single-shot turbo-spin-echo techniques (DL-HASTE) enable single-breath-hold T2-weighted abdominal imaging. However, studies evaluating the image quality of DL-HASTE with and without fat saturation (FS) remain lim...

Fusion of X-Ray Images and Clinical Data for a Multimodal Deep Learning Prediction Model of Osteoporosis: Algorithm Development and Validation Study.

JMIR medical informatics
BACKGROUND: Osteoporosis is a bone disease characterized by reduced bone mineral density and mass, which increase the risk of fragility fractures in patients. Artificial intelligence can mine imaging features specific to different bone densities, sha...

Predicting Surgical Site Infection after Lumbar Laminectomy and Discectomy: A Cutting-edge Algorithmic Approach by Incorporating Ensembled Stacking into the Current State-of-the-art for Automated Machine Learning.

Neurosurgical review
To develop an algorithmic approach for predicting surgical site infections (SSIs) in patients undergoing lumbar laminectomy and discectomy for adult degenerative spinal disease (DSD) by incorporating ensembled stacking into state-of-the-art (SOTA) au...

Development and validation of an explainable machine learning model for predicting sepsis risk following flexible ureteroscopic lithotripsy.

Urolithiasis
Sepsis is a severe complication of flexible ureteroscopic lithotripsy (fURL), a widely used treatment for kidney stones. This study aimed to develop and validate a predictive model based on machine learning (ML) for assessing the risk of sepsis follo...

Identifying determinants of readmission and death post-stroke using explainable machine learning.

PloS one
BACKGROUND: Stroke remains a global health challenge with high rates of mortality and rehospitalization placing significant demands on healthcare systems. Identifying factors that determine outcomes of post-hospitalization improves resource allocatio...

Identification and predictive machine learning model construction of gut microbiota associated with carcinoembryonic antigens in colorectal cancer.

mSphere
UNLABELLED: Carcinoembryonic antigen (CEA) is a critical colorectal cancer (CRC) biomarker, but its mechanistic link to gut microbiota remains unclear. This study characterized gut microbiota differences between high-CEA (H-CEA) and low-CEA (L-CEA) C...

Collecting and Sharing Person-Centered AI Clinical Summaries Across Frailty Services Provided by the National Health Service and Voluntary, Community, and Social Enterprise: Protocol for a Co-Design and Feasibility Study.

JMIR research protocols
BACKGROUND: Due to its association with multimorbidity, frailty gives rise to multidimensional needs for different services. Too often, patient preferences and service encounter information are not adequately shared.