scholarly journals Modeling agreement on bounded scales

2017 ◽  
Vol 27 (11) ◽  
pp. 3460-3477 ◽  
Author(s):  
Sophie Vanbelle ◽  
Emmanuel Lesaffre
Keyword(s):  
Normal Distribution ◽  
Correlation Coefficient ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Concordance Correlation Coefficient ◽  
Concordance Correlation ◽  
Behavioral Sciences ◽  
Score Distribution ◽  
Outcome Scores ◽  
The Impact

Agreement is an important concept in medical and behavioral sciences, in particular in clinical decision making where disagreements possibly imply a different patient management. The concordance correlation coefficient is an appropriate measure to quantify agreement between two scorers on a quantitative scale. However, this measure is based on the first two moments, which could poorly summarize the shape of the score distribution on bounded scales. Bounded outcome scores are common in medical and behavioral sciences. Typical examples are scores obtained on visual analog scales and scores derived as the number of positive items on a questionnaire. These kinds of scores often show a non-standard distribution, like a J- or U-shape, questioning the usefulness of the concordance correlation coefficient as agreement measure. The logit-normal distribution has shown to be successful in modeling bounded outcome scores of two types: (1) when the bounded score is a coarsened version of a latent score with a logit-normal distribution on the [0,1] interval and (2) when the bounded score is a proportion with the true probability having a logit-normal distribution. In the present work, a model-based approach, based on a bivariate generalization of the logit-normal distribution, is developed in a Bayesian framework to assess the agreement on bounded scales. This method permits to directly study the impact of predictors on the concordance correlation coefficient and can be simply implemented in standard Bayesian softwares, like JAGS and WinBUGS. The performances of the new method are compared to the classical approach using simulations. Finally, the methodology is used in two different medical domains: cardiology and rheumatology.

Religion and Medicine

2020 ◽  
Author(s):  
Jeff Levin ◽  
Stephen G. Post
Keyword(s):  
Clinical Decision Making ◽  
Well Being ◽  
Clinical Decision ◽  
Religion And Medicine ◽  
Physical And Mental Health ◽  
Faith Based ◽  
Baylor University ◽  
Wide Range ◽  
History Of ◽  
The Impact

In Religion and Medicine, Dr. Jeff Levin, distinguished Baylor University epidemiologist, outlines the longstanding history of multifaceted interconnections between the institutions of religion and medicine. He traces the history of the encounter between these two institutions from antiquity through to the present day, highlighting a myriad of contemporary alliances between the faith-based and medical sectors. Religion and Medicine tells the story of: religious healers and religiously branded hospitals and healthcare institutions; pastoral professionals involved in medical missions, healthcare chaplaincy, and psychological counseling; congregational health promotion and disease prevention programs and global health initiatives; research studies on the impact of religious and spiritual beliefs and practices on physical and mental health, well-being, and healing; programs and centers for medical research and education within major universities and academic institutions; religiously informed bioethics and clinical decision-making; and faith-based health policy initiatives and advocacy for healthcare reform. Religion and Medicine is the first book to cover the full breadth of this subject. It documents religion-medicine alliances across religious traditions, throughout the world, and over the course of history. It summarizes a wide range of material of relevance to historians, medical professionals, pastors and theologians, bioethicists, scientists, public health educators, and policymakers. The product of decades of rigorous and focused research, Dr. Levin has produced the most comprehensive history of these developments and the finest introduction to this emerging field of scholarship.

scholarly journals Structured Reporting of Rectal Cancer Staging and Restaging: A Consensus Proposal

Cancers ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 2135
Author(s):  
Vincenza Granata ◽  
Damiano Caruso ◽  
Roberto Grassi ◽  
Salvatore Cappabianca ◽  
Alfonso Reginelli ◽  
...  
Keyword(s):  
Rectal Cancer ◽  
Correlation Coefficient ◽  
Clinical Decision Making ◽  
Intraclass Correlation ◽  
Clinical Decision ◽  
Cancer Staging ◽  
Structured Reporting ◽  
Quality Analysis ◽  
Promising Tool ◽  
Structured Reports

Background: Structured reporting (SR) in oncologic imaging is becoming necessary and has recently been recognized by major scientific societies. The aim of this study was to build MRI-based structured reports for rectal cancer (RC) staging and restaging in order to provide clinicians all critical tumor information. Materials and Methods: A panel of radiologist experts in abdominal imaging, called the members of the Italian Society of Medical and Interventional Radiology, was established. The modified Delphi process was used to build the SR and to assess the level of agreement in all sections. The Cronbach’s alpha (Cα) correlation coefficient was used to assess the internal consistency of each section and to measure the quality analysis according to the average inter-item correlation. The intraclass correlation coefficient (ICC) was also evaluated. Results: After the second Delphi round of the SR RC staging, the panelists’ single scores and sum of scores were 3.8 (range 2–4) and 169, and the SR RC restaging panelists’ single scores and sum of scores were 3.7 (range 2–4) and 148, respectively. The Cα correlation coefficient was 0.79 for SR staging and 0.81 for SR restaging. The ICCs for the SR RC staging and restaging were 0.78 (p < 0.01) and 0.82 (p < 0.01), respectively. The final SR version was built and included 53 items for RC staging and 50 items for RC restaging. Conclusions: The final version of the structured reports of MRI-based RC staging and restaging should be a helpful and promising tool for clinicians in managing cancer patients properly. Structured reports collect all Patient Clinical Data, Clinical Evaluations and relevant key findings of Rectal Cancer, both in staging and restaging, and can facilitate clinical decision-making.

Clinical Conundrums When Integrating the QbTest into a Standard ADHD Assessment of Children and Young People

2021 ◽  
Author(s):  
Carsten Vogt
Keyword(s):  
Clinical Practice ◽  
Clinical Decision Making ◽  
Ecological Validity ◽  
Neuropsychological Test ◽  
Real Life ◽  
Clinical Decision ◽  
Hyperactivity Disorder ◽  
Standard Clinical Practice ◽  
Novel Method ◽  
The Impact

AbstractThe uptake of the QbTest in clinical practice is increasing and has recently been supported by research evidence proposing its effectiveness in relation to clinical decision-making. However, the exact underlying process leading to this clinical benefit is currently not well established and requires further clarification. For the clinician, certain challenges arise when adding the QbTest as a novel method to standard clinical practice, such as having the skills required to interpret neuropsychological test information and assess for diagnostically relevant neurocognitive domains that are related to attention-deficit hyperactivity disorder (ADHD), or how neurocognitive domains express themselves within the behavioral classifications of ADHD and how the quantitative measurement of activity in a laboratory setting compares with real-life (ecological validity) situations as well as the impact of comorbidity on test results. This article aims to address these clinical conundrums in aid of developing a consistent approach and future guidelines in clinical practice.

A repeated measures concordance correlation coefficient

2007 ◽  
Vol 26 (16) ◽  
pp. 3095-3113 ◽  
Author(s):  
Tonya S. King ◽  
Vernon M. Chinchilli ◽  
Josep L. Carrasco
Keyword(s):  
Correlation Coefficient ◽  
Repeated Measures ◽  
Concordance Correlation Coefficient ◽  
Concordance Correlation

scholarly journals MRI texture feature repeatability and image acquisition factor robustness, a phantom study and in silico study

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Joshua Shur ◽  
Matthew Blackledge ◽  
James D’Arcy ◽  
David J. Collins ◽  
Maria Bali ◽  
...  
Keyword(s):  
Correlation Coefficient ◽  
Coefficient Of Variation ◽  
In Silico ◽  
Image Acquisition ◽  
Texture Feature ◽  
Texture Features ◽  
Concordance Correlation Coefficient ◽  
Concordance Correlation ◽  
Simulation Data ◽  
Mri Features

Abstract Purpose To evaluate robustness and repeatability of magnetic resonance imaging (MRI) texture features in water and tissue phantom test-retest study. Materials and methods Separate water and tissue phantoms were imaged twice with the same protocol in a test-retest experiment using a 1.5-T scanner. Protocols were acquired to favour signal-to-noise ratio and resolution. Forty-six features including first order statistics and second-order texture features were extracted, and repeatability was assessed by calculating the concordance correlation coefficient. Separately, base image noise and resolution were manipulated in an in silico experiment, and robustness of features was calculated by assessing percentage coefficient of variation and linear correlation of features with noise and resolution. These simulation data were compared with the acquired data. Features were classified by their degree (high, intermediate, or low) of robustness and repeatability. Results Eighty percent of the MRI features were repeatable (concordance correlation coefficient > 0.9) in the phantom test-retest experiment. The majority (approximately 90%) demonstrated a strong or intermediate correlation with image acquisition parameter, and 19/46 (41%) and 13/46 (28%) of features were highly robust to noise and resolution, respectively (coefficient of variation < 5%). Agreement between the acquired and simulation data varied, with the range of agreement within feature classes between 11 and 92%. Conclusion Most MRI features were repeatable in a phantom test-retest study. This phantom data may serve as a lower limit of feature MRI repeatability. Robustness of features varies with acquisition parameter, and appropriate features can be selected for clinical validation studies.

scholarly journals AB0798 IS THERE A REPRODUCIBILITY OF THE HISTOGRAM AND GRAY SCALE IN ECOEXTRUCTURAL DAMAGES IN RHEUMATOTOLOGICAL DISEASES?

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1423.2-1424
Author(s):  
J. A. Mendonça ◽  
I. Siste de Almeida Aoki ◽  
C. C. Cavuto ◽  
V. A. Leandro-Merhi ◽  
J. L. B. D. Aquino
Keyword(s):  
Correlation Coefficient ◽  
Intraclass Correlation Coefficient ◽  
Rheumatic Diseases ◽  
Femoral Condyle ◽  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Concordance Correlation Coefficient ◽  
Image Method ◽  
Concordance Correlation ◽  
Gray Scale

Background:The gray scale (GS) in high resolution ultrasound is already well validated for use in rheumatological diseases, but the color map or the histogram, can be considered a new proposal, to better define and complement the echotextural damages detection1.Objectives:To calculate the lesions area measures reproducibility index in arthropathies, between 3 blind evaluators and correlate these measures using the GS and the histogram.Methods:Observational and retrospective study approved by the ethics committee of the Pontifical Catholic University of Campinas, with the opinion number: 1.526.307. A total of 29 patients have been assessed (31% males and 69% females) on period 2014 to 2019 in Rheumatology service. A MyLab 50 -Esaote equipment was used with frequency transducer that ranged between 6.0 and 18.0 MHz, 10 different area measures were performed from each recorded images previously, by the GS and the histogram. Statistical analysis: Spearman’s correlation coefficients, Lin’s concordance coefficient (CCC) and the intraclass correlation coefficient (ICC) and their respective 95% confidence intervals, with the SPSS software package for Windows v. 17.0 (SPSS Inc., Chicago, IL, USA).Results:Average age 43.5 ± 21.5 years of age; with disease duration that varied between ≤ 1 month (48.3%) and ≥36 months (24.1%); with the following diseases: juvenile idiopathic arthritis (17.24%); osteoarthritis (13.79%); psoriatic arthritis (13.79%); undifferentiated spondyloarthritis (3.44%); gout (20.68%); rheumatoid arthritis (27.58%) and reactive arthritis (3.44%). A total of 840 measures of exudative (27.58%), proliferative (27.58%) and snowstorm appearance (6.89%) synovitis were performed; femoral-condyle cartilage (3.44%); synovial cyst (3.44%); paratendinitis (6.89%); calcification (3.44%); nail enthesitis (3.44%); tenosynovitis (6.89%) and tophi (10.34%) (Figure 1). The concordance correlation coefficient showed values closer to 1; p <0.001, the intraclass correlation coefficients with excellent reproducibility (ICC ≥ 0.75); p <0.001, always in relation to the three evaluators (Table 1) and the Spearman correlation between the GS and the histogram ranged from rs = 0.665 to rs = 1,000; p <0.001.Conclusion:The histogram can be considered an image method to better identify echotextural damages.References:[1]Mendonça J, Provenza J, Guissa V, et al AB1059 2D Histogram Ultrasound and 3D Ultrasound Correlation in Rheumatic Diseases Annals of the Rheumatic Diseases 2015; 74:1253-1254.Table 1.Concordance Correlation Coefficient (CCC) and Intraclass Correlation Coefficient (ICC):EvaluatorsGS - CCC(IC 95%)p-valorHistogram (IC 95%)p-valor1 e 20,998(0,994-0,999)<0,0010,999(0,995-1,000)<0,0011 e 30,998(0,995-0,999)<0,0010,999(0,995-1,000)<0,0012 e 30,992(0,980-0,997)<0,010,996(0,979-0,999)<0,01Standard by US 2DICCp-valorGS0,997(0,992-0,999)<0,001Histogram0,998(0,992-0,999)<0,001Legends: Gray Scale (GS).Figure 1.Patient with gout: A and B: Tophi area measures (star) in right metatarsos and efusion (arrow) by GS (45 mm2) and histogram (39 mm2), respectively.Disclosure of Interests:José Alexandre Mendonça Speakers bureau: Novartis, Janssen, Bristol, UCB, Isabella Siste de Almeida Aoki: None declared, Caique Chagas Cavuto: None declared, Vânia Aparecida Leandro-Merhi: None declared, José Luis Braga de Aquino: None declared

A Bayesian Framework for Estimating the Concordance Correlation Coefficient Using Skew-elliptical Distributions

2018 ◽  
Vol 14 (1) ◽  
Author(s):  
Dai Feng ◽  
Richard Baumgartner ◽  
Vladimir Svetnik
Keyword(s):  
Clinical Study ◽  
Missing Data ◽  
Correlation Coefficient ◽  
Real Life ◽  
Bayesian Framework ◽  
Concordance Correlation Coefficient ◽  
Elliptical Distributions ◽  
Concordance Correlation ◽  
Heavy Tailed ◽  
Biomarker Data

Abstract The concordance correlation coefficient (CCC) is a widely used scaled index in the study of agreement. In this article, we propose estimating the CCC by a unified Bayesian framework that can (1) accommodate symmetric or asymmetric and light- or heavy-tailed data; (2) select model from several candidates; and (3) address other issues frequently encountered in practice such as confounding covariates and missing data. The performance of the proposal was studied and demonstrated using simulated as well as real-life biomarker data from a clinical study of an insomnia drug. The implementation of the proposal is accessible through a package in the Comprehensive R Archive Network.

AAC Assessment and Clinical-Decision Making: The Impact of Experience

2012 ◽  
Vol 28 (3) ◽  
pp. 148-159 ◽  
Author(s):  
Aimee Dietz ◽  
Wendy Quach ◽  
Shelley K. Lund ◽  
Miechelle McKelvey
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
The Impact

Standardized Synoptic Cancer Pathology Reports — So What and Who Cares?: A Population-Based Satisfaction Survey of 970 Pathologists, Surgeons, and Oncologists

2013 ◽  
Vol 137 (11) ◽  
pp. 1599-1602 ◽  
Author(s):  
Sara Lankshear ◽  
John Srigley ◽  
Thomas McGowan ◽  
Marta Yurcan ◽  
Carol Sawka
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Physician Satisfaction ◽  
Cross Sectional ◽  
Cancer Pathology ◽  
Report Turnaround Time ◽  
Significant Difference ◽  
Pathology Reporting ◽  
The Impact

Context.—Cancer Care Ontario implemented synoptic pathology reporting across Ontario, impacting the practice of pathologists, surgeons, and medical and radiation oncologists. The benefits of standardized synoptic pathology reporting include enhanced completeness and improved consistency in comparison with narrative reports, with reported challenges including increased workload and report turnaround time. Objective.—To determine the impact of synoptic pathology reporting on physician satisfaction specific to practice and process. Design.—A descriptive, cross-sectional design was utilized involving 970 clinicians across 27 hospitals. An 11-item survey was developed to obtain information regarding timeliness, completeness, clarity, and usability. Open-ended questions were also employed to obtain qualitative comments. Results.—A 51% response rate was obtained, with descriptive statistics reporting that physicians perceive synoptic reports as significantly better than narrative reports. Correlation analysis revealed a moderately strong, positive relationship between respondents' perceptions of overall satisfaction with the level of information provided and perceptions of completeness for clinical decision making (r = 0.750, P &lt; .001) and ease of finding information for clinical decision making (r = 0.663, P &lt; .001). Dependent t tests showed a statistically significant difference in the satisfaction scores of pathologists and oncologists (t169 = 3.044, P = .003). Qualitative comments revealed technology-related issues as the most frequently cited factor impacting timeliness of report completion. Conclusion.—This study provides evidence of strong physician satisfaction with synoptic cancer pathology reporting as a clinical decision support tool in the diagnosis, prognosis, and treatment of cancer patients.

scholarly journals Clinicians’ experiences of using and implementing a medical mobile phone app (QUiPP V2) designed to predict the risk of preterm birth and aid clinical decision making

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
N. Carlisle ◽  
H. A. Watson ◽  
J. Carter ◽  
K. Kuhrt ◽  
P. T. Seed ◽  
...  
Keyword(s):  
Decision Making ◽  
Preterm Birth ◽  
Cultural Context ◽  
Clinical Decision Making ◽  
Qualitative Interviews ◽  
Scale Up ◽  
Clinical Decision ◽  
Clinical Trial Registry ◽  
Support Tool ◽  
The Impact

Abstract Background As the vast majority of women who present in threatened preterm labour (TPTL) will not deliver early, clinicians need to balance the risks of over-medicalising the majority of women, against the potential risk of preterm delivery for those discharged home. The QUiPP app is a free, validated app which can support clinical decision-making as it produces individualised risks of delivery within relevant timeframes. Recent evidence has highlighted that clinicians would welcome a decision-support tool that accurately predicts preterm birth. Methods Qualitative interviews were undertaken as part of the EQUIPTT study (The Evaluation of the QUiPP app for Triage and Transfer) (REC: 17/LO/1802) which aimed to evaluate the impact of the QUiPP app on management of TPTL. Individual semi-structured telephone interviews were used to explore clinicians’ (obstetricians’ and midwives’) experiences of using the QUiPP app and how it was implemented at their hospital sites. Thematic analysis was chosen to explore the meaning of the data, through a framework approach. Results Nineteen participants from 10 hospital sites in England took part. Data analysis revealed three overarching themes which were: ‘experience of using the app’, ‘how QUiPP risk changes practice’ and ‘successfully adopting QUiPP: context is everything’. With these final themes we appeared to have achieved our aim of exploring the clinicians’ experiences of using and implementing the QUiPP app. Conclusion This study explored different clinician’s experiences of implementing the app. The organizational and cultural context at different sites appeared to have a large impact on how well the QUiPP app was implemented. Future work needs to be undertaken to understand how best to embed the intervention within different settings. This will inform scale up of QUiPP app use across the UK and ensure that clinicians have access to this free, easy-to-use tool which can positively aid clinical decision making when caring for women in TPTL. Clinical trial registry and registration number ISRCTN 17846337, registered 08th January 2018, https://doi.org/10.1186/ISRCTN17846337.

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