Objective: To review the effect of patient decision aids for adults making treatment decisions regarding the management of chronic musculoskeletal pain.
Methods: We performed a systematic review of randomized controlled trials of adults using patient decision aids to make treatment decisions for chronic musculoskeletal pain in the outpatient setting.
Results: Of 477 records screened, 17 met the inclusion criteria. Chronic musculoskeletal pain conditions included osteoarthritis of the hip, knee, or trapeziometacarpal joint and back pain. Thirteen studies evaluated the use of a decision aid for deciding between surgical and nonsurgical management. The remaining four studies evaluated decision aids for nonsurgical treatment options. Outcomes included decision quality, pain, function, and surgery utilization. The effects of decision aids on decision-making outcomes were mixed. Comparing decision aids with usual care, all five studies that examined knowledge scores found improvement in patient knowledge. None of the four studies that evaluated satisfaction with the decision-making process found a difference with use of a decision aid. There was limited and inconsistent data on other decision-related outcomes. Of the eight studies that evaluated surgery utilization, seven found no difference in surgery rates with use of a decision aid. Five studies made comparisons between different types of decision aids, and there was no clearly superior format.
Conclusions: Decision aids may improve patients' knowledge about treatment options for chronic musculoskeletal pain but largely did not impact other outcomes. Future efforts should focus on improving the effectiveness of decision aids and incorporating nonpharmacologic and nonsurgical management options.
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http://dx.doi.org/10.1093/pm/pnz280 | DOI Listing |
JMIR Res Protoc
January 2025
Clinical Physiology Institute, Consiglio Nazionale delle Ricerche, Pisa, Italy.
Background: Among cardiovascular diseases, adult patients with congenital heart disease represent a population that has been continuously increasing, which is mainly due to improvement of the pathophysiological framing, including the development of surgical and reanimation techniques. However, approximately 20% of these patients will require surgery in adulthood and 40% of these cases will necessitate reintervention for residual defects or sequelae of childhood surgery. In this field, cardiac rehabilitation (CR) in the postsurgical phase has an important impact on the patient by improving psychophysical and clinical recovery in reducing fatigue and dyspnea to ultimately increase survival.
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December 2024
Cardiovascular Medicine, Hayatabad Medical Complex Peshawar, Peshawar, PAK.
Background Coronary artery bypass grafting (CABG) improves outcomes in patients with ischemic left ventricular (LV) dysfunction, but accurate patient selection remains critical. Late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) imaging aids in assessing myocardial viability, a key predictor of surgical outcomes. This study aimed to evaluate the impact of myocardial viability on postoperative outcomes in patients undergoing CABG.
View Article and Find Full Text PDFFront Artif Intell
January 2025
Department of Genetic Engineering, Computational Biology Lab, School of Bioengineering, SRM Institute of Science and Technology, SRM Nagar, Chennai, India.
Cell-penetrating peptides (CPPs) are highly effective at passing through eukaryotic membranes with various cargo molecules, like drugs, proteins, nucleic acids, and nanoparticles, without causing significant harm. Creating drug delivery systems with CPP is associated with cancer, genetic disorders, and diabetes due to their unique chemical properties. Wet lab experiments in drug discovery methodologies are time-consuming and expensive.
View Article and Find Full Text PDFClinicoecon Outcomes Res
January 2025
Public Systems Group, Indian Institute of Management Ahmedabad, Ahmedabad, Gujarat, India.
Introduction: Clinical trials are critical for drug development and patient care; however, they often need more efficient trial design and patient enrolment processes. This research explores integrating machine learning (ML) techniques to address these challenges. Specifically, the study investigates ML models for two critical aspects: (1) streamlining clinical trial design parameters (like the site of drug action, type of Interventional/Observational model, etc) and (2) optimizing patient/volunteer enrolment for trials through efficient classification techniques.
View Article and Find Full Text PDFHealth Sci Rep
January 2025
Department Health Information Technology, School of Paramedical and Rehabilitation Sciences Mashhad University of Medical Sciences Mashhad Iran.
Background And Aims: The goal of this research was to create a minimum data set (MDS) and design a web-based registry for outpatient rehabilitation, focusing on four disciplines: speech therapy, audiology, optometry, and physical therapy. The registry was intended to enhance assessment, guide optimal care, and provide value-based and evidence-based rehabilitation management for patients.
Methods: This cross-sectional study utilized the Delphi technique at Mashhad University of Medical Sciences in northeastern Iran from 2022 to 2023.
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