scholarly journals Radiologic Classification of Black Lung: Time for a New Gold Standard?

2022 ◽  
Author(s):  
David A. Lynch ◽  
Jonathan H Chung ◽  
Jeffrey P Kanne ◽  
Cristopher A Meyer
Keyword(s):  
Gold Standard

scholarly journals Validity of classification of distal radial fractures in the Swedish fracture register

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Malena Bergvall ◽  
Carl Bergdahl ◽  
Carl Ekholm ◽  
David Wennergren
Keyword(s):  
Gold Standard ◽  
Reference Group ◽  
Observer Agreement ◽  
Distal Radial Fractures ◽  
Young Males ◽  
Small Peak ◽  
National Quality ◽  
Fracture Register ◽  
Standard Classification

Abstract Background Distal radial fractures (DRF) are one of the most common fractures with a small peak in incidence among young males and an increasing incidence with age among women. The reliable classification of fractures is important, as classification provides a framework for communicating effectively on clinical cases. Fracture classification is also a prerequisite for data collection in national quality registers and for clinical research. Since its inception in 2011, the Swedish Fracture Register (SFR) has collected data on more than 490,000 fractures. The attending physician classifies the fracture according to the AO/OTA classification upon registration in the SFR. Previous studies regarding the classification of distal radial fractures (DRF) have shown difficulties in inter- and intra-observer agreement. This study aims to assess the accuracy of the registration of DRF in adults in the SFR as it is carried out in clinical practice. Methods A reference group of three experienced orthopaedic trauma surgeons classified 128 DRFs, randomly retrieved from the SFR, at two classification sessions 6 weeks apart. The classification the reference group agreed on was regarded as the gold standard classification for each fracture. The accuracy of the classification in the SFR was defined as the agreement between the gold standard classification and the classification in the SFR. Inter- and intra-observer agreement was evaluated and the degree of agreement was calculated as Cohen’s kappa. Results The accuracy of the classification of DRF in the SFR was kappa = 0.41 (0.31–0.51) for the AO/OTA subgroup/group and kappa = 0.48 (0.36–0.61) for the AO/OTA type. This corresponds to moderate agreement. Inter-observer agreement ranged from kappa 0.22–0.48 for the AO/OTA subgroup/group and kappa 0.48–0.76 for the AO/OTA type. Intra-observer agreement ranged from kappa 0.52–0.70 for the AO/OTA subgroup/group and kappa 0.71–0.76 for the AO/OTA type. Conclusions The study shows moderate accuracy in the classification of DRF in the SFR. Although the degree of accuracy for DRF appears to be lower than for other fracture locations, the accuracy shown in the current study is similar to that in previous studies of DRF.

scholarly journals Towards a better understanding of the low recall of insertion variants with short-read based variant callers

2020 ◽  
Author(s):  
Wesley Delage ◽  
Julien Thevenon ◽  
Claire Lemaitre
Keyword(s):  
Gold Standard ◽  
Insertion Site ◽  
Structural Variants ◽  
Genomic Context ◽  
Breakpoint Junction ◽  
Short Read ◽  
Depth Analysis ◽  
Long Read ◽  
The Impact

AbstractSince 2009, numerous tools have been developed to detect structural variants (SVs) using short read technologies. Insertions >50 bp are one of the hardest type to discover and are drastically underrepresented in gold standard variant callsets. The advent of long read technologies has completely changed the situation. In 2019, two independent cross technologies studies have published the most complete variant callsets with sequence resolved insertions in human individuals. Among the reported insertions, only 17 to 37% could be discovered with short-read based tools. In this work, we performed an in-depth analysis of these unprecedented insertion callsets in order to investigate the causes of such failures. We have first established a precise classification of insertion variants according to four layers of characterization: the nature and size of the inserted sequence, the genomic context of the insertion site and the breakpoint junction complexity. Because these levels are intertwined, we then used simulations to characterize the impact of each complexity factor on the recall of several SV callers. Simulations showed that the most impacting factor was the insertion type rather than the genomic context, with various difficulties being handled differently among the tested SV callers, and they highlighted the lack of sequence resolution for most insertion calls. Our results explain the low recall by pointing out several difficulty factors among the observed insertion features and provide avenues for improving SV caller algorithms and their [email protected]

PV Modeling of Medical Imaging Systems

Benford's Law ◽  
2015 ◽  
Author(s):  
John Chiverton ◽  
Kevin Wells
Keyword(s):  
Medical Imaging ◽  
Gold Standard ◽  
Ground Truth ◽  
Imaging Data ◽  
Nuclear Medicine Imaging ◽  
Phantom Imaging ◽  
Positron Emission ◽  
Pet Ct ◽  
Many Sources

This chapter applies a Bayesian formulation of the Partial Volume (PV) effect, based on the Benford distribution, to the statistical classification of nuclear medicine imaging data: specifically Positron Emission Tomography (PET) acquired as part of a PET-CT phantom imaging procedure. The Benford distribution is a discrete probability distribution of great interest for medical imaging, because it describes the probabilities of occurrence of single digits in many sources of data. The chapter thus describes the PET-CT imaging and post-processing process to derive a gold standard. Moreover, this chapter uses it as a ground truth for the assessment of a Benford classifier formulation. The use of this gold standard shows that the classification of both the simulated and real phantom imaging data is well described by the Benford distribution.

scholarly journals Impact of ICD10 and secular changes on electronic medical record rheumatoid arthritis algorithms

Rheumatology ◽  
2020 ◽  
Vol 59 (12) ◽  
pp. 3759-3766 ◽  
Author(s):  
Sicong Huang ◽  
Jie Huang ◽  
Tianrun Cai ◽  
Kumar P Dahal ◽  
Andrew Cagan ◽  
...  
Keyword(s):  
Language Processing ◽  
Gold Standard ◽  
International Classification Of Diseases ◽  
Data Mart ◽  
Classification Of Diseases ◽  
Icd Codes ◽  
Rule Based Approach ◽  
Citrullinated Peptide ◽  
Better Than

Abstract Objective The objective of this study was to compare the performance of an RA algorithm developed and trained in 2010 utilizing natural language processing and machine learning, using updated data containing ICD10, new RA treatments, and a new electronic medical records (EMR) system. Methods We extracted data from subjects with ≥1 RA International Classification of Diseases (ICD) codes from the EMR of two large academic centres to create a data mart. Gold standard RA cases were identified from reviewing a random 200 subjects from the data mart, and a random 100 subjects who only have RA ICD10 codes. We compared the performance of the following algorithms using the original 2010 data with updated data: (i) a published 2010 RA algorithm; (ii) updated algorithm, incorporating ICD10 RA codes and new DMARDs; and (iii) published algorithm using ICD codes only, ICD RA code ≥3. Results The gold standard RA cases had mean age 65.5 years, 78.7% female, 74.1% RF or antibodies to cyclic citrullinated peptide (anti-CCP) positive. The positive predictive value (PPV) for ≥3 RA ICD was 54%, compared with 56% in 2010. At a specificity of 95%, the PPV of the 2010 algorithm and the updated version were both 91%, compared with 94% (95% CI: 91, 96%) in 2010. In subjects with ICD10 data only, the PPV for the updated 2010 RA algorithm was 93%. Conclusion The 2010 RA algorithm validated with the updated data with similar performance characteristics as the 2010 data. While the 2010 algorithm continued to perform better than the rule-based approach, the PPV of the latter also remained stable over time.

scholarly journals Role of Combined Pleural Fluid Cholesterol and Total Protein in Differentiation of Exudates and Transudates

2020 ◽  
Vol 3 (1) ◽  
pp. 282-285
Author(s):  
Anupam Bista ◽  
Suman Thapa ◽  
Prasant Subedi ◽  
Kiran Manandhar
Keyword(s):  
Pleural Fluid ◽  
Standard Method ◽  
Total Protein ◽  
Gold Standard ◽  
Pleural Effusions

Introduction: Light's criteria had been the standard method for distinguishing exudative and transudative pleural effusions which misidentify 15-20% of transudates as exudates. This study aims to find out the role of combined pleural fluid cholesterol and total protein in distinguishing exudative from transudative pleural effusions and its applicability in Nepalese populations. Materials and Methods: Patients with pleural effusions were enrolled for the study. The combined pleural fluid cholesterol and total protein were compared with Light’s criteria and also compared with the diagnosis on discharge to find out their usefulness in categorizing the pleural effusions. Results: A total of 81 patients enrolled in the study, 42 (51.9%) were male. Based on Light’s criteria, 88.8% pleural effusions were found to be exudates and 11.1% were found to be transudates. Within the criteria, Light’s criteria categorized more pleural fluids as exudates than the diagnosis on discharge. Based on pleural fluid cholesterol >60mg/dL and protein >3g/dL for the classification of exudative and transudative pleural fluid, 62.9% out of 81 samples felled under the exudates and 37.03% pleural effusions under transudates with the sensitivity 87.9% and specificity 100%. Conclusions: Though Light’s criteria remain the gold standard to differentiate transudates and exudates, combined pleural fluid cholesterol and total protein give nearly comparable results without the need for simultaneous blood investigations.

Questionnaire-based diagnosis of benign paroxysmal positional vertigo

Neurology ◽  
2019 ◽  
Vol 94 (9) ◽  
pp. e942-e949 ◽  
Author(s):  
Hyo-Jung Kim ◽  
Jeong-Mi Song ◽  
Liqun Zhong ◽  
Xu Yang ◽  
Ji-Soo Kim
Keyword(s):  
Confidence Interval ◽  
Gold Standard ◽  
Benign Paroxysmal Positional Vertigo ◽  
Class Iii ◽  
Positional Vertigo ◽  
National University ◽  
Seoul National University ◽  
Sensitivity Specificity ◽  
Paroxysmal Positional Vertigo

ObjectivesTo develop a simple questionnaire for self-diagnosis of benign paroxysmal positional vertigo (BPPV).MethodsWe developed a questionnaire that consisted of 6 questions, the first 3 to diagnose BPPV and the next 3 to determine the involved canal and type of BPPV. From 2016 to 2017, 578 patients with dizziness completed the questionnaire before the positional tests, a gold standard for diagnosis of BPPV, at the Dizziness Clinic of Seoul National University Bundang Hospital.ResultsOf the 578 patients, 200 were screened to have BPPV and 378 were screened to have dizziness/vertigo due to disorders other than BPPV. Of the 200 patients with a questionnaire-based diagnosis of BPPV, 160 (80%) were confirmed to have BPPV with positional tests. Of the 378 patients with a questionnaire-based diagnosis of non-BPPV, 24 (6.3%) were found to have BPPV with positional tests. Thus, the sensitivity, specificity, and precision of the questionnaires for the diagnosis of BPPV were 87.0%, 89.8%, and 80.0% (121 of 161, 95% confidence interval 74.5%–85.5%). Of the 200 patients with a questionnaire-based diagnosis of BPPV, 30 failed to respond to the questions 4 through 6 to determine the involved canal and type of BPPV. The questionnaire and positional tests showed the same results for the subtype and affected side of BPPV in 121 patients (121 of 170, 71.2%).ConclusionThe accuracy of questionnaire-based diagnosis of BPPV is acceptable.Classification of evidenceThis study provides Class III evidence that, in patients with dizziness, a questionnaire can diagnose BPPV with a sensitivity of 87.0% and a specificity of 89.8%.

Clinical Diagnostic Accuracy of Early/Advanced Parkinson Disease: Updated Clinicopathologic Study

2020 ◽  
pp. 10.1212/CPJ.0000000000001016
Author(s):  
Charles H. Adler ◽  
Thomas G. Beach ◽  
Nan Zhang ◽  
Holly A. Shill ◽  
Erika Driver-Dunckley ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Clinical Diagnosis ◽  
Gold Standard ◽  
Disease Duration ◽  
Clinical Signs ◽  
Confidence Levels ◽  
Clinicopathologic Study ◽  
Clinical Diagnostic ◽  
Neuropathological Diagnosis

AbstractObjectives:Update data for diagnostic accuracy of a clinical diagnosis of Parkinson’s disease (PD) using neuropathological diagnosis as the gold standard.Methods:Data from the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND) was used to determine the predictive value of a clinical PD diagnosis. Two clinical diagnostic confidence levels were used, Possible PD (PossPD, never treated or not responsive) and Probable PD (ProbPD, 2/3 cardinal clinical signs + responsive to dopaminergic medications). Neuropathological diagnosis was the gold standard.Results:Based on first visit to AZSAND, 15/54 (27.8%) PossPD cases and 138/163 (84.7%) ProbPD had confirmed PD. PD was confirmed in 24/34 (70.6%) ProbPD with <5 yrs and 114/128 (89.1%) with >5 yrs disease duration. Using the consensus final clinical diagnosis following death, 161/187 (86.1%) ProbPD had neuropathologically confirmed PD. Diagnostic accuracy for ProbPD improved if included motor fluctuations, dyskinesias, and hyposmia, and hyposmia for PossPD.Conclusions:This updated study confirmed lower clinical diagnostic accuracy for elderly, untreated or poorly responsive PossPD participants and for ProbPD with <5 yr disease duration, even when medication responsive. Caution continues to be needed when interpreting clinical studies of PD, especially studies of early disease, that do not have autopsy confirmation.Classification of Evidence:This study provides Class II evidence that a clinical diagnosis of probable PD at first visit identifies patients who will have pathologically confirmed PD with a sensitivity of 82.6% and specificity of 86.0%.

scholarly journals The Gold Standard of Thyroid Nodule Examination? Prospective Validation of the ACR TI-RADS in a Secondary Referral Center

2020 ◽  
pp. S329-S337
Author(s):  
T. GRIMMICHOVÁ ◽  
P. PAČESOVÁ ◽  
L. SRBOVÁ ◽  
J. VRBÍKOVÁ ◽  
T. HAVRDOVÁ ◽  
...  
Keyword(s):  
Gold Standard ◽  
Thyroid Nodules ◽  
Fine Needle Aspiration Biopsy ◽  
Needle Aspiration ◽  
American Thyroid Association ◽  
Referral Center ◽  
Proper Group ◽  
Pattern Group ◽  
Selection Of

The aim of this prospective study was the validation of the risk stratification of thyroid nodules using ultrasonography with the American College of Radiology Thyroid Imaging, Reporting and Data System (ACR TI-RADS) and partly in comparison to American Thyroid Association (ATA) guidelines in a secondary referral center. Fine needle aspiration biopsy (FNA) (n=605) and histological examinations (n=63) were the reference standards for the statistical analysis. ACR TI-RADS cut-off value: TR4 with sensitivity 85.7 %, specificity 54.1 %, PPV 58.5 %, accuracy 67.7 % (AUC 0.738; p<0.001). ATA cut-off value: “high suspicion” with sensitivity 80 %, specificity 83.3 %, PPV 80 %, accuracy 81.8 % (AUC 0.800; p=0.0025). 18.4 % nodules (3 malignant) could not be assigned to a proper ATA US pattern group (p<0.0001). Both ACR TI-RADS and ATA have allowed fair selection of nodules requiring FNA with superiority of ACR TI-RADS according to classification of all thyroid nodules to the proper group. According to ACR TI-RADS almost one third of the patients were incorrectly classified with 17.9 % missed thyroid carcinomas, exclusively micropapillary carcinomas, even though, the amount of FNA would be reduced to 48 %.

A Thorough Presentation of Autism Diagnostic Observation Schedule (ADOS-2)

2022 ◽  
pp. 21-38
Author(s):  
Elpis Papaefstathiou
Keyword(s):  
Psychometric Properties ◽  
Direct Observation ◽  
Diagnostic Tool ◽  
Gold Standard ◽  
Autism Diagnostic Observation Schedule ◽  
Autism Diagnostic Observation

ADOS-2 is considered the gold standard observational instrument for use in the diagnosis and/or classification of autism and ASD. In this chapter, the process of assessment will be described, which involves direct observation and engagement of children and adults for whom an ASD is suspected. Specifically, an emphasis will be put on ADOS structure, namely the five different modules for the assessment. Then, the advantages of ADOS-2 will be elaborated as a diagnostic tool and a brief review of studies concerning its psychometric properties will be reported.

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