Background And Objective: The Modified Rankin Scale (mRS) is a widely adopted scale for assessing stroke recovery. Despite limitations, the mRS has been adopted as primary outcome in most recent clinical acute stroke trials. Designed to be used by multidisciplinary clinical staff, the congruency of this scale is not consistent, which may lead to mistakes in clinical or research application. We aimed to develop and validate an interactive and automated digital tool for assessing the mRS-the iRankin.
Methods: A panel of five board-certified and mRS-trained vascular neurologists developed an automated flowchart based on current mRS literature. Two international experts were consulted on content and provided feedback on the prototype platform. The platform contained five vignettes and five real video cases, representing mRS grades 0-5. For validation, we invited neurological staff from six comprehensive stroke centers to complete an online assessment. Participants were randomized into two equal groups usual practice versus iRankin. The participants were randomly allocated in pairs for the congruency analysis. Weighted kappa (kw) and proportions were used to describe agreement.
Results: A total of 59 professionals completed the assessment. The kw was dramatically improved among nurses, 0.76 (95% confidence interval (CI) = 0.55-0.97) × 0.30 (0.07-0.67), and among vascular neurologists, 0.87 (0.72-1) × 0.82 (0.66-0.98). In the accuracy analysis, after the standard mRS values for the vignettes and videos were determined by a panel of experts, and considering each correct answer as equivalent to 1 point on a scale of 0-15, it revealed a higher mean of 10.6 (±2.2) in the iRankin group and 8.2 (±2.3) points in the control group (p = 0.02). In an adjusted analysis, the iRankin adoption was independently associated with the score of congruencies between reported and standard scores (beta coefficient = 2.22, 95% CI = 0.64-3.81, p = 0.007).
Conclusion: The iRankin adoption led to a substantial or near-perfect agreement in all analyzed professional categories. More trials are needed to generalize our findings. Our user-friendly and free platform is available at https://www.irankinscale.com/.
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http://dx.doi.org/10.1177/17474930241246157 | DOI Listing |
PLOS Digit Health
December 2024
Department of Family Medicine, McMaster University, Ontario, Canada.
The Community Paramedicine at Clinic (CP@clinic) program is a community program that utilizes community paramedics to support older adults in assessing their risk factors, managing their chronic conditions, and linking them to community resources. The aim of this project is to design a low-cost, portable, secure, user-friendly database for CP@clinic sessions and pilot test the database with paramedics and older adult volunteers. The CP@clinic program database using the Microsoft Access software was first developed through consultation with the CP@clinic research team.
View Article and Find Full Text PDFPharmacy (Basel)
December 2024
Department of Medical Affairs, Becton Dickinson and Company, Franklin Lakes, NJ 07417, USA.
This study explored controlled substance (CS) diversion surveillance practices within hospital pharmacies across the United States. A survey with questions based on published CS diversion risk points was conducted in May 2024. A total of 66 participants from 31 states responded, with 54.
View Article and Find Full Text PDFHum Reprod
December 2024
Department of Medical BioSciences, Radboudumc, Nijmegen, The Netherlands.
Study Question: How can we best achieve tissue segmentation and cell counting of multichannel-stained endometriosis sections to understand tissue composition?
Summary Answer: A combination of a machine learning-based tissue analysis software for tissue segmentation and a deep learning-based algorithm for segmentation-independent cell identification shows strong performance on the automated histological analysis of endometriosis sections.
What Is Known Already: Endometriosis is characterized by the complex interplay of various cell types and exhibits great variation between patients and endometriosis subtypes.
Study Design, Size, Duration: Endometriosis tissue samples of eight patients of different subtypes were obtained during surgery.
Study Objectives: To evaluate the capability and accuracy of magnetocardiography (MCG) to identify patients with ischemic chest pain from those with non-ischemic pain and to verify normalcy in the MCG in healthy subjects.
Design: We studied 133 patients (mean age 59 ± 14 years, 69 % male) with chronic or acute chest pain syndrome and 63 healthy subjects (mean age 41.7 ± 12.
Respir Res
December 2024
Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Background: The composite physiologic index (CPI) was developed to estimate the extent of interstitial lung disease (ILD) in idiopathic pulmonary fibrosis (IPF) patients based on pulmonary function tests (PFTs). The CALIPER-revised version of the CPI (CALIPER-CPI) was also developed to estimate the volume fraction of ILD measured by CALIPER, an automated quantitative CT postprocessing software. Recently, artificial intelligence-based quantitative CT image analysis software (AIQCT), which can be used to quantify the bronchial volume separately from the ILD volume, was developed and validated in IPF.
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