Objective: To perform a COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN)-based systematic literature review of measurement properties of the Polymyalgia Rheumatica Activity Score (PMR-AS).
Methods: PubMed, EMBASE, and CINAHL were broadly searched. English full-text articles, with (quantitative) data on ≥ 5 patients with PMR using the PMR-AS were selected. Seven hypotheses for construct validity and 3 for responsiveness, concerning associations with erythrocyte sedimentation rate, physical function, quality of life, clinical disease states, ultrasound, and treatment response, were formulated. We assessed the structural validity, internal consistency, reliability, and measurement error, or the hypotheses on construct validity or responsiveness of the PMR-AS based on COSMIN criteria.
Results: Out of the identified 26 articles that used the PMR-AS, we were able to use 12 articles. Structural validity, internal consistency, construct validity, and responsiveness were assessed in 1, 2, 8, and 3 articles, respectively. Insufficient evidence was found to confirm structural validity and internal consistency. No data were found on reliability or measurement error. Although 60% and 67% of hypotheses tested for construct validity and responsiveness, respectively, were confirmed, there was insufficient evidence to meet criteria for good measurement properties.
Conclusion: While there is some promising evidence for construct validity and responsiveness of the PMR-AS, it is lacking for other properties and, overall, falls short of criteria for good measurement properties. Therefore, further research is needed to assess its role in clinical research and care.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.3899/jrheum.211292 | DOI Listing |
JACS Au
December 2024
Key Laboratory of Molecular Enzymology and Engineering of Ministry of Education, School of Life Sciences, Jilin University, Changchun 130023, P. R. China.
In this study, we developed a machine-learning-aided protein design strategy for engineering hemoglobin (VHb) as carbene transferase. A Natural Language Processing (NLP) model was used for the first time to construct an algorithm (EESP, enzyme enantioselectivity score predictor) and predict the enantioselectivity of VHb. We identified critical amino acid residue sites by molecular docking and established a simplified mutation library by site-saturated mutagenesis.
View Article and Find Full Text PDFJ Inflamm Res
December 2024
Beijing Institute of Heart, Lung and Blood Vessel Diseases, The Key Laboratory of Remodeling Cardiovascular Diseases, Ministry of Education, Collaborative Innovation Center for Cardiovascular Disorders, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.
Aim: To investigate the regulatory mechanism of CXCL16 molecule-related ( extract-induced antigen presentation in a mouse asthma model based on the long non-coding RNA (lncRNA) and mRNA expression profile.
Methods: knockout mice and wild-type mice were administered with . extract by intratracheal instillations to induce asthma airway inflammation.
J Inflamm Res
December 2024
Department of Gynecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China.
Background: Surgery is the best approach to treat endometrial cancer (EC); however, there is currently a deficiency in effective scoring systems for predicting EC recurrence post-surgical resection. This study aims to develop a clinicopathological-inflammatory parameters-based nomogram to accurately predict the postoperative recurrence-free survival (RFS) rate of EC patients.
Methods: A training set containing 1068 patients and an independent validation set consisting of 537 patients were employed in this retrospective study.
Front Cardiovasc Med
December 2024
Department of Cardiovascular Medicine, Tacheng People's Hospital, Tacheng, China.
Objective: To analyze the risk factors for coronary heart disease (CHD) in patients hospitalized in general hospitals in the Tacheng Prefecture, Xinjiang, and to construct and verify the nomogram prediction model for the risk of CHD.
Methods: From June 2022 to June 2023, 489 CHD patients (CHD group) and 520 non-CHD individuals (control group) in Tacheng, Xinjiang, were retrospectively selected. Using a 7:3 ratio, patients were divided into a training group (706 cases) and a validation group (303 cases).
Front Physiol
December 2024
Department of Oral & Maxillofacial Surgery, Shenzhen Stomatology Hospital, Affiliated to Shenzhen University, Shenzhen, Guangdong Province, China.
Introduction: This study aimed to develop a deep learning-based method for interpreting magnetic resonance imaging (MRI) scans of temporomandibular joint (TMJ) anterior disc displacement (ADD) and to formulate an automated diagnostic system for clinical practice.
Methods: The deep learning models were utilized to identify regions of interest (ROI), segment TMJ structures including the articular disc, condyle, glenoid fossa, and articular tubercle, and classify TMJ ADD. The models employed Grad-CAM heatmaps and segmentation annotation diagrams for visual diagnostic predictions and were deployed for clinical application.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!