Dataset Information

Global uncertainty in the diagnosis of neurological complications of SARS-CoV-2 infection by both neurologists and non-neurologists: An international inter-observer variability study.

ABSTRACT:

Introduction

Uniform case definitions are required to ensure harmonised reporting of neurological syndromes associated with SARS-CoV-2. Moreover, it is unclear how clinicians perceive the relative importance of SARS-CoV-2 in neurological syndromes, which risks under- or over-reporting.

Methods

We invited clinicians through global networks, including the World Federation of Neurology, to assess ten anonymised vignettes of SARS-CoV-2 neurological syndromes. Using standardised case definitions, clinicians assigned a diagnosis and ranked association with SARS-CoV-2. We compared diagnostic accuracy and assigned association ranks between different settings and specialties and calculated inter-rater agreement for case definitions as "poor" (κ ≤ 0.4), "moderate" or "good" (κ > 0.6).

Results

1265 diagnoses were assigned by 146 participants from 45 countries on six continents. The highest correct proportion were cerebral venous sinus thrombosis (CVST, 95.8%), Guillain-Barré syndrome (GBS, 92.4%) and headache (91.6%) and the lowest encephalitis (72.8%), psychosis (53.8%) and encephalopathy (43.2%). Diagnostic accuracy was similar between neurologists and non-neurologists (median score 8 vs. 7/10, p = 0.1). Good inter-rater agreement was observed for five diagnoses: cranial neuropathy, headache, myelitis, CVST, and GBS and poor agreement for encephalopathy. In 13% of vignettes, clinicians incorrectly assigned lowest association ranks, regardless of setting and specialty.

Conclusion

The case definitions can help with reporting of neurological complications of SARS-CoV-2, also in settings with few neurologists. However, encephalopathy, encephalitis, and psychosis were often misdiagnosed, and clinicians underestimated the association with SARS-CoV-2. Future work should refine the case definitions and provide training if global reporting of neurological syndromes associated with SARS-CoV-2 is to be robust.

SUBMITTER: Tamborska AA

PROVIDER: S-EPMC10085971 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Global uncertainty in the diagnosis of neurological complications of SARS-CoV-2 infection by both neurologists and non-neurologists: An international inter-observer variability study.

Tamborska A A AA Wood G K GK Westenberg E E Garcia-Azorin D D Webb G G Schiess N N Netravathi M M Baykan B B Dervaj R R Helbok R R Lant S S Özge A A Padovani A A Saylor D D Schmutzhard E E Easton A A Lilleker J B JB Jackson T T Beghi E E Ellul M A MA Frontera J A JA Pollak T T Nicholson T R TR Wood N N Thakur K T KT Solomon T T Stark R J RJ Winkler A S AS Michael B D BD

Journal of the neurological sciences 20230411

<h4>Introduction</h4>Uniform case definitions are required to ensure harmonised reporting of neurological syndromes associated with SARS-CoV-2. Moreover, it is unclear how clinicians perceive the relative importance of SARS-CoV-2 in neurological syndromes, which risks under- or over-reporting.<h4>Methods</h4>We invited clinicians through global networks, including the World Federation of Neurology, to assess ten anonymised vignettes of SARS-CoV-2 neurological syndromes. Using standardised case d ...[more]

PMID: 37100018

Similar Datasets

Project description:ObjectivesEstablishing the reproducibility of expert-derived measurements on CTA exams of aortic dissection is clinically important and paramount for ground-truth determination for machine learning.MethodsFour independent observers retrospectively evaluated CTA exams of 72 patients with uncomplicated Stanford type B aortic dissection and assessed the reproducibility of a recently proposed combination of four morphologic risk predictors (maximum aortic diameter, false lumen circumferential angle, false lumen outflow, and intercostal arteries). For the first inter-observer variability assessment, 47 CTA scans from one aortic center were evaluated by expert-observer 1 in an unconstrained clinical assessment without a standardized workflow and compared to a composite of three expert-observers (observers 2-4) using a standardized workflow. A second inter-observer variability assessment on 30 out of the 47 CTA scans compared observers 3 and 4 with a constrained, standardized workflow. A third inter-observer variability assessment was done after specialized training and tested between observers 3 and 4 in an external population of 25 CTA scans. Inter-observer agreement was assessed with intraclass correlation coefficients (ICCs) and Bland-Altman plots.ResultsPre-training ICCs of the four morphologic features ranged from 0.04 (-0.05 to 0.13) to 0.68 (0.49-0.81) between observer 1 and observers 2-4 and from 0.50 (0.32-0.69) to 0.89 (0.78-0.95) between observers 3 and 4. ICCs improved after training ranging from 0.69 (0.52-0.87) to 0.97 (0.94-0.99), and Bland-Altman analysis showed decreased bias and limits of agreement.ConclusionsManual morphologic feature measurements on CTA images can be optimized resulting in improved inter-observer reliability. This is essential for robust ground-truth determination for machine learning models.Key points• Clinical fashion manual measurements of aortic CTA imaging features showed poor inter-observer reproducibility. • A standardized workflow with standardized training resulted in substantial improvements with excellent inter-observer reproducibility. • Robust ground truth labels obtained manually with excellent inter-observer reproducibility are key to develop reliable machine learning models.

Project description:BackgroundPET-based tumor delineation is an error prone and labor intensive part of image analysis. Especially for patients with advanced disease showing bulky tumor FDG load, segmentations are challenging. Reducing the amount of user-interaction in the segmentation might help to facilitate segmentation tasks especially when labeling bulky and complex tumors. Therefore, this study reports on segmentation workflows/strategies that may reduce the inter-observer variability for large tumors with complex shapes with different levels of user-interaction.MethodsTwenty PET images of bulky tumors were delineated independently by six observers using four strategies: (I) manual, (II) interactive threshold-based, (III) interactive threshold-based segmentation with the additional presentation of the PET-gradient image and (IV) the selection of the most reasonable result out of four established semi-automatic segmentation algorithms (Select-the-best approach). The segmentations were compared using Jaccard coefficients (JC) and percentage volume differences. To obtain a reference standard, a majority vote (MV) segmentation was calculated including all segmentations of experienced observers. Performed and MV segmentations were compared regarding positive predictive value (PPV), sensitivity (SE), and percentage volume differences.ResultsThe results show that with decreasing user-interaction the inter-observer variability decreases. JC values and percentage volume differences of Select-the-best and a workflow including gradient information were significantly better than the measurements of the other segmentation strategies (p-value<0.01). Interactive threshold-based and manual segmentations also result in significant lower and more variable PPV/SE values when compared with the MV segmentation.ConclusionsFDG PET segmentations of bulky tumors using strategies with lower user-interaction showed less inter-observer variability. None of the methods led to good results in all cases, but use of either the gradient or the Select-the-best workflow did outperform the other strategies tested and may be a good candidate for fast and reliable labeling of bulky and heterogeneous tumors.

Dataset Information

Global uncertainty in the diagnosis of neurological complications of SARS-CoV-2 infection by both neurologists and non-neurologists: An international inter-observer variability study.

Introduction

Methods

Results

Conclusion

Publications

Global uncertainty in the diagnosis of neurological complications of SARS-CoV-2 infection by both neurologists and non-neurologists: An international inter-observer variability study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets