Clinical utility of a cluster of tests as a diagnostic support tool for clinical lumbar instability

2020 ◽  
Vol 50 ◽  
pp. 102224
Author(s):  
Pattanasin Areeudomwong ◽  
Kitti Jirarattanaphochai ◽  
Thapakorn Ruanjai ◽  
Vitsarut Buttagat
2016 ◽  
Author(s):  
Po-Hao Chen ◽  
Emmanuel Botzolakis ◽  
Suyash Mohan ◽  
R. N. Bryan ◽  
Tessa Cook

2021 ◽  
Author(s):  
Rochelle K Rosen ◽  
Stephanie C Garbern ◽  
Monique Gainey ◽  
Ryan Lantini ◽  
Sabiha Nasrin ◽  
...  

BACKGROUND The availability of mobile clinical decision-support (CDS) tools has grown substantially with the increased prevalence of smartphone devices and applications (apps). Though healthcare providers express interest in integrating mobile health (mHealth) technologies into their clinical settings, concerns raised include perceived disagreements between information provided by mobile CDS tools and standard guidelines. Despite their potential to transform health care delivery, there remains limited literature on the provider’s perspective of the clinical utility of mobile CDS tools for improving patient outcomes, especially in low- and middle- income countries. OBJECTIVE The aim of this study is to describe providers’ perceptions about the utility of a mobile CDS tool accessed via a smartphone app for diarrhea management in Bangladesh. In addition, feedback was collected on preliminary components of the mobile CDS tool to address clinicians’ concerns and incorporate their preferences. METHODS From November to December 2020, qualitative data were gathered through eight virtual focus group discussions with physicians and nurses from three Bangladeshi hospitals. Each discussion was conducted in the local language, Bangla, and audio recorded for transcription and translation by the local research team. Transcripts and codes were entered into NVivo12 and applied thematic analysis was used to identify themes that explore the clinical utility of a mHealth app to assess dehydration severity in patients with acute diarrhea. Summaries of concepts and themes were generated from reviews of the aggregated coded data, and thematic memos were written and used for the final analysis. RESULTS Of the 27 focus group participants, 14 were nurses and 13 doctors; 15 worked at a diarrhea specialty hospital and 12 worked in government district or subdistrict hospitals. The participants’ experience in their current position ranged from 2 to 14 years, with an average of 10.3 years. Key themes from the qualitative data analysis, including: current experience with CDS, overall perception of the app utility and its potential role in clinical care, barriers and facilitators to app use, considerations of overtreatment and undertreatment, and guidelines for the app’s clinical recommendations. CONCLUSIONS Participants were positive about the mHealth app and its potential to inform diarrhea management. They provided detailed feedback, which developers used to further the design and programming. Participants felt that the tool would initially take time to use, but once learned could be useful during epidemic cholera. Some felt that clinical experience remains an important part of treatment that can be supplemented, but not replaced, by a CDS tool. Additionally, diagnostic information, including mid-upper arm circumference and blood pressure, might not be available to directly inform programming decisions. These formative qualitative data provided timely and relevant feedback to improve the utility of a CDS tool for diarrhea treatment in Bangladesh.


Author(s):  
Makenzie Pryor ◽  
Doug Ebert ◽  
Vicky Byrne ◽  
Khalaeb Richardson ◽  
Qua Jones ◽  
...  

The present study examined a diagnostic medical decision aid developed to help inexperienced operators to diagnose and treat a simulated patient. Diagnosis and treatment accuracy using the tool were assessed and compared across both physicians and non-physicians. Initial analysis revealed more accurate diagnostic and treatment choices for non-physicians, but upon further investigation, physicians were found to have recognized signs for another diagnosis and correctly diagnosed and treated based on the limited information in the patient simulation. This fit with other noted behaviors, such as non-physicians opening the diagnostic support tool within the aid more often than physicians, and frequently returning to the tool during the task. In general, non-physicians were supported in choosing the correct diagnosis and treatment by the aid, while physicians disregarded the aid’s recommendations to make decisions based on their own expertise. These results have implications for the development of future decision support aids for non-physicians performing medical procedures.


Diagnostics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 40 ◽  
Author(s):  
Darian M. Onchis ◽  
Codruta Istin ◽  
Cristina Tudoran ◽  
Mariana Tudoran ◽  
Pedro Real

In this paper, we propose an analytical rapid method to estimate the endocardial borders of the left ventricular walls on echocardiographic images for prospective clinical integration. The procedure was created as a diagnostic support tool for the clinician and it is based on the use of the anisotropic generalized Hough transform. Its application is guided by a Gabor-like filtering for the approximate delimitation of the region of interest without the need for computing further anatomical characteristics. The algorithm is applying directly a deformable template on the predetermined filtered region and therefore it is responsive and straightforward implementable. For accuracy considerations, we have employed a support vector machine classifier to determine the confidence level of the automated marking. The clinical tests were performed at the Cardiology Clinic of the County Emergency Hospital Timisoara and they improved the physicians perception in more than 50% of the cases. The report is concluded with medical discussions.


2015 ◽  
Vol 57 (1) ◽  
pp. 233-236
Author(s):  
Maria Christina Maioli ◽  
Teresa de Souza Fernandez ◽  
Mércia Mendes Campos ◽  
Hilda Rachel Diamond ◽  
Gabriel Alves Costa Veranio-Silva ◽  
...  

Diagnostics ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1892
Author(s):  
Siddharth Arora ◽  
Athanasios Tsanas

Numerous studies have reported on the high accuracy of using voice tasks for the remote detection and monitoring of Parkinson’s Disease (PD). Most of these studies, however, report findings on a small number of voice recordings, often collected under acoustically controlled conditions, and therefore cannot scale at large without specialized equipment. In this study, we aimed to evaluate the potential of using voice as a population-based PD screening tool in resource-constrained settings. Using the standard telephone network, we processed 11,942 sustained vowel /a/ phonations from a US-English cohort comprising 1078 PD and 5453 control participants. We characterized each phonation using 304 dysphonia measures to quantify a range of vocal impairments. Given that this is a highly unbalanced problem, we used the following strategy: we selected a balanced subset (n = 3000 samples) for training and testing using 10-fold cross-validation (CV), and the remaining (unbalanced held-out dataset, n = 8942) samples for further model validation. Using robust feature selection methods we selected 27 dysphonia measures to present into a radial-basis-function support vector machine and demonstrated differentiation of PD participants from controls with 67.43% sensitivity and 67.25% specificity. These findings could help pave the way forward toward the development of an inexpensive, remote, and reliable diagnostic support tool for PD using voice as a digital biomarker.


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