Interobserver and Intraobserver Variability in the CT Assessment of COVID-19 Based on RSNA Consensus Classification Categories.

PURPOSE: To assess the interobserver and intraobserver agreement of fellowship trained chest radiologists, nonchest fellowship-trained radiologists, and fifth-year radiology residents for COVID-19-related imaging findings based on the consensus statement released by the Radiological Society of North America (RSNA). METHODS: A survey of 70 chest CTs of polymerase chain reaction (PCR)-confirmed COVID-19 positive and COVID-19 negative patients was distributed to three groups of participating radiologists: five fellowship-trained chest radiologists, five nonchest fellowship-trained radiologists, and five fifth-year radiology residents. The survey asked participants to broadly classify the findings of each chest CT into one of the four RSNA COVID-19 imaging categories, then select which imaging features led to their categorization. A 1-week washout period followed by a second survey comprised of randomly selected exams from the initial survey was given to the participating radiologists. RESULTS: There was moderate overall interobserver agreement in each group (κ coefficient range 0.45-0.52 ± 0.02). There was substantial overall intraobserver agreement across the chest and nonchest groups (κ coefficient range 0.61-0.67 ± 0.06) and moderate overall intraobserver agreement within the resident group (κ coefficient 0.58 ± 0.06). For the image features that led to categorization, there were varied levels of agreement in the interobserver and intraobserver components that ranged from fair to perfect kappa values. When assessing agreement with PCR-confirmed COVID status as the key, we observed moderate overall agreement within each group. CONCLUSION: Our results support the reliability of the RSNA consensus classification system for COVID-19-related image findings.

Antiplatelet therapy and the risk of ischemic and hemorrhagic complications associated with Pipeline embolization of cerebral aneurysms: a systematic review and pooled analysis.

BACKGROUND: Pipeline embolization devices (PEDs) are increasingly used in the treatment of cerebral aneurysms. Yet, major ischemic or hemorrhagic complications after PED treatment associated with antiplatelet regimens are not well-established. OBJECTIVE: To investigate the risk of ischemic and hemorrhagic complications associated with common antiplatelet regimens following PED treatment, and to examine whether platelet function testing (PFT) is associated with a lower risk of these complications. METHODS: We searched Medline, Embase, and Cochrane from 2009 to 2017. Twenty-nine studies were included that had reported a uniform antiplatelet regimen protocol and had provided data on major ischemic and hemorrhagic complications following PED treatment. Random-effect meta-analysis was used to pool overall ischemic and hemorrhagic event rates across studies. The rate of these complications with respect to the antithrombotic regimen and PFT was assessed by χ2 proportional tests. RESULTS: Overall, 2002 patients (age 55.9 years, 76% female) were included. A low-dose acetylsalicylic acid (ASA) regimen before and after PED treatment was associated with a higher rate of late ischemic complications than with high-dose ASA therapy (2.62 (95% CI 1.46 to 4.69) and 2.56 (1.41 to 4.64), respectively). Duration of post-procedure clopidogrel therapy <6 months was associated with greater rates of ischemic complications (1.56, 95% CI 1.11 to 2.20) than a clopidogrel regimen of ≥6 months. Performing PFT before PED treatment was not associated with the risk of ischemic complications (1.27, 95% CI 0.77 to 2.10). CONCLUSION: High-dose ASA therapy and clopidogrel treatment for at least 6 months were associated with a reduced incidence of ischemic events, without affecting the risk of hemorrhagic events.

Precision annotation of digital samples in NCBI's gene expression omnibus.

The Gene Expression Omnibus (GEO) contains more than two million digital samples from functional genomics experiments amassed over almost two decades. However, individual sample meta-data remains poorly described by unstructured free text attributes preventing its largescale reanalysis. We introduce the Search Tag Analyze Resource for GEO as a web application (http://STARGEO.org) to curate better annotations of sample phenotypes uniformly across different studies, and to use these sample annotations to define robust genomic signatures of disease pathology by meta-analysis. In this paper, we target a small group of biomedical graduate students to show rapid crowd-curation of precise sample annotations across all phenotypes, and we demonstrate the biological validity of these crowd-curated annotations for breast cancer. STARGEO.org makes GEO data findable, accessible, interoperable and reusable (i.e., FAIR) to ultimately facilitate knowledge discovery. Our work demonstrates the utility of crowd-curation and interpretation of open 'big data' under FAIR principles as a first step towards realizing an ideal paradigm of precision medicine.