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ShareScore release 0.9.0
Dataset results
57 results for “Chest X-Ray”
Next Generation Chest X-Ray Tomosynthesis for Screening of Lung Cancer
ClinicalTrials.gov study NCT06577883. IPD Sharing: NO. Countries: 1. Publications: 0.
Study to Evaluate the Effectiveness of the Device in Detection of Abnormal Findings on Chest X-ray
ClinicalTrials.gov study NCT05614232. IPD Sharing: NO. Countries: 1. Publications: 0.
Artificial Intelligence to Improve Physicians' Interpretation of Chest X-Rays in Breathless Patients
ClinicalTrials.gov study NCT05117320. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Evaluating Validity of Clinical Criteria for Requesting Chest X-Rays in Trauma Patients
ClinicalTrials.gov study NCT01134744. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Evaluation of the Efficacy of Diagnostic Support Algorithms in Chest X-rays- LuAna Trial
ClinicalTrials.gov study NCT06686251. IPD Sharing: NO. Countries: 1. Publications: 0.
The AI-CAC Model for Subclinical Atherosclerosis Detection on Chest X-ray
ClinicalTrials.gov study NCT06301009. IPD Sharing: YES. Countries: 0. Publications: 0.
Routine Chest X-ray Post Rigid Bronchoscopy for Foreign Body Extraction: is it Necessary?
ClinicalTrials.gov study NCT06106503. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Ultrasound vs Chest X-ray for NG Tube Placement in ICU
ClinicalTrials.gov study NCT07376083. IPD Sharing: NO. Countries: 0. Publications: 0.
Evaluation of Chest CT Versus Chest X-Ray for Lung Surveillance After Curative-Intent Resection of High-Risk Truncal-Extremity Soft Tissue Sarcoma
ClinicalTrials.gov study NCT06526897. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Chest Ultrasound Versus Chest X-ray with Ct As Gold Standard At Trauma Patients
ClinicalTrials.gov study NCT06699277. IPD Sharing: NO. Countries: 0. Publications: 0.
Influence of Chest X-ray vs. Chest CT Scan on the Management of ICU Patients With Respiratory Failure
ClinicalTrials.gov study NCT07256860. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Dynamic Chest X-ray With Simultaneous Spirometry
ClinicalTrials.gov study NCT06122051. IPD Sharing: NO. Countries: 0. Publications: 0.
Computer-Aided diagnostic for classifying Chest X-Ray Images Using Deep Ensemble Learning
<p>Both healthy and tuberculosis images are from "Tuberculosis (TB) Chest X-Ray Database'' collected by researchers from Qatar and Dhaka University, Doha, Qatar, and collaboration with doctors from Hamad Medical Corporation and Bangladesh. All the images are CRX in PNG format and a size 512x512. </p> <p>The COVID and Pneumonia images are also from a Kaggle dataset: "COVID-19 Radiography Database'' , which collects images from different sources. This dataset was collected by the same researchers as the "Tuberculosis (TB) Chest X-Ray Database''. All the images in this database are CRX in PNG format and a size 256X256.</p>
Chest X-ray images dataset of viral and bacterial pulmonary diseases.
Open the record for dataset details and reuse information.
Chest x-ray in the COVID-19 pandemic: Radiologists real-world reader performance.
<p>Dataset from the article Cozzi A, Schiaffino S, Arpaia F, Della Pepa G, Tritella S, Bertolotti P, Menicagli L, Monaco CG, Carbonaro LA, Spairani R, Babaei Paskeh B, Sardanelli F. Chest x-ray in the COVID-19 pandemic: Radiologists' real-world reader performance. Eur J Radiol. 2020 Nov;132:109272. doi: 10.1016/j.ejrad.2020.109272. Epub 2020 Sep 10. PMID: 32971326; PMCID: PMC7481070.</p> <p><strong>Abstract</strong></p> <p><strong>Purpose: </strong>To report real-world diagnostic performance of chest x-ray (CXR) readings during the COVID-19 pandemic.</p> <p><strong>Methods: </strong>In this retrospective observational study we enrolled all patients presenting to the emergency department of a Milan-based university hospital from February 24th to April 8th 2020 who underwent nasopharyngeal swab for reverse transcriptase-polymerase chain reaction (RT-PCR) and anteroposterior bedside CXR within 12 h. A composite reference standard combining RT-PCR results with phone-call-based anamnesis was obtained. Radiologists were grouped by CXR reading experience (Group-1, >10 years; Group-2, <10 years), diagnostic performance indexes were calculated for each radiologist and for the two groups.</p> <p><strong>Results: </strong>Group-1 read 435 CXRs (77.0 % disease prevalence): sensitivity was 89.0 %, specificity 66.0 %, accuracy 83.7 %. Group-2 read 100 CXRs (73.0 % prevalence): sensitivity was 89.0 %, specificity 40.7 %, accuracy 76.0 %. During the first half of the outbreak (195 CXRs, 66.7 % disease prevalence), overall sensitivity was 80.8 %, specificity 67.7 %, accuracy 76.4 %, Group-1 sensitivity being similar to Group-2 (80.6 % versus 81.5 %, respectively) but higher specificity (74.0 % versus 46.7 %) and accuracy (78.4 % versus 69.0 %). During the second half (340 CXRs, 81.8 % prevalence), overall sensitivity increased to 92.8 %, specificity dropped to 53.2 %, accuracy increased to 85.6 %, this pattern mirrored in both groups, with decreased specificity (Group-1, 58.0 %; Group-2, 33.3 %) but increased sensitivity (92.7 % and 93.5 %) and accuracy (86.5 % and 81.0 %, respectively).</p> <p><strong>Conclusions: </strong>Real-world CXR diagnostic performance during the COVID-19 pandemic showed overall high sensitivity with higher specificity for more experienced radiologists. The increase in accuracy over time strengthens CXR role as a first line examination in suspected COVID-19 patients.</p>
Abdominal obesity phenotype is associated with COVID-19 chest X-ray severity score better than BMI-based obesity
<p>Malavazos AE, Secchi F, Basilico S, Capitanio G, Boveri S, Milani V, Dubini C, Schiaffino S, Morricone L, Foschini C, Gobbo G, Piccinni R, Saibene A, Sardanelli F, Menicanti L, Guazzi M, Dong C, Romanelli MMC, Carruba M, Iacobellis G. Abdominal obesity phenotype is associated with COVID-19 chest X-ray severity score better than BMI-based obesity. Eat Weight Disord. 2022 Feb;27(1):345-359. doi: 10.1007/s40519-021-01173-w. Epub 2021 Apr 5. PMID: 33821453; PMCID: PMC8020829.</p> <p>Abstract</p> <p><strong>Purpose: </strong>Chest X-ray (CXR) severity score and BMI-based obesity are predictive risk factors for COVID-19 hospital admission. However, the relationship between abdominal obesity and CXR severity score has not yet been fully explored.</p> <p><strong>Methods: </strong>This retrospective cohort study analyzed the association of different adiposity indexes, including waist circumference and body mass index (BMI), with CXR severity score in 215 hospitalized patients with COVID-19.</p> <p><strong>Results: </strong>Patients with abdominal obesity showed significantly higher CXR severity scores and had higher rates of CXR severity scores ≥ 8 compared to those without abdominal obesity (P < 0.001; P = 0.001, respectively). By contrast, patients with normal weight, with overweight and those with BMI-based obesity showed no significant differences in either CXR severity scores or in the rates of CXR severity scores ≥ 8 (P = 0.104; P = 0.271, respectively). Waist circumference and waist-to-height ratio (WHtR) correlated more closely with CXR severity scores than BMI (r = 0.43, P < 0.001; r = 0.41, P < 0.001; r = 0.17, P = 0.012, respectively). The area under the curves (AUCs) for waist circumference and WHtR were significantly higher than that for BMI in identifying a high CXR severity score (≥ 8) (0.68 [0.60-0.75] and 0.67 [0.60-0.74] vs 0.58 [0.51-0.66], P = 0.001). A multivariate analysis indicated abdominal obesity (risk ratio: 1.75, 95% CI: 1.25-2.45, P < 0.001), bronchial asthma (risk ratio: 1.73, 95% CI: 1.07-2.81, P = 0.026) and oxygen saturation at admission (risk ratio: 0.96, 95% CI: 0.94-0.97, P < 0.001) as the only independent factors associated with high CXR severity scores.</p> <p><strong>Conclusion: </strong>Abdominal obesity phenotype is associated with a high CXR severity score better than BMI-based obesity in hospitalized patients with COVID-19. Therefore, when visiting the patient in a hospital setting, waist circumference should be measured, and patients with abdominal obesity should be monitored closely. Level of evidence Cross-sectional descriptive study, Level V.</p> <p> </p>
Abdominal obesity phenotype is associated with COVID-19 chest X-ray severity score better than BMI-based obesity.
<p>Dataset from Malavazos AE, Secchi F, Basilico S, Capitanio G, Boveri S, Milani V, Dubini C, Schiaffino S, Morricone L, Foschini C, Gobbo G, Piccinni R, Saibene A, Sardanelli F, Menicanti L, Guazzi M, Dong C, Romanelli MMC, Carruba M, Iacobellis G. Abdominal obesity phenotype is associated with COVID-19 chest X-ray severity score better than BMI-based obesity. Eat Weight Disord. 2021 Apr 5:1–15. doi: 10.1007/s40519-021-01173-w. Epub ahead of print. PMID: 33821453; PMCID: PMC8020829.</p> <p>Abstract</p> <p><strong>Purpose: </strong>Chest X-ray (CXR) severity score and BMI-based obesity are predictive risk factors for COVID-19 hospital admission. However, the relationship between abdominal obesity and CXR severity score has not yet been fully explored.</p> <p><strong>Methods: </strong>This retrospective cohort study analyzed the association of different adiposity indexes, including waist circumference and body mass index (BMI), with CXR severity score in 215 hospitalized patients with COVID-19.</p> <p><strong>Results: </strong>Patients with abdominal obesity showed significantly higher CXR severity scores and had higher rates of CXR severity scores ≥ 8 compared to those without abdominal obesity (P < 0.001; P = 0.001, respectively). By contrast, patients with normal weight, with overweight and those with BMI-based obesity showed no significant differences in either CXR severity scores or in the rates of CXR severity scores ≥ 8 (P = 0.104; P = 0.271, respectively). Waist circumference and waist-to-height ratio (WHtR) correlated more closely with CXR severity scores than BMI (r = 0.43, P < 0.001; r = 0.41, P < 0.001; r = 0.17, P = 0.012, respectively). The area under the curves (AUCs) for waist circumference and WHtR were significantly higher than that for BMI in identifying a high CXR severity score (≥ 8) (0.68 [0.60-0.75] and 0.67 [0.60-0.74] vs 0.58 [0.51-0.66], P = 0.001). A multivariate analysis indicated abdominal obesity (risk ratio: 1.75, 95% CI: 1.25-2.45, P < 0.001), bronchial asthma (risk ratio: 1.73, 95% CI: 1.07-2.81, P = 0.026) and oxygen saturation at admission (risk ratio: 0.96, 95% CI: 0.94-0.97, P < 0.001) as the only independent factors associated with high CXR severity scores.</p> <p><strong>Conclusion: </strong>Abdominal obesity phenotype is associated with a high CXR severity score better than BMI-based obesity in hospitalized patients with COVID-19. Therefore, when visiting the patient in a hospital setting, waist circumference should be measured, and patients with abdominal obesity should be monitored closely. Level of evidence Cross-sectional descriptive study, Level V.</p>
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Allen Brain Atlas
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OpenNeuro
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