Publications by authors named "Lutfi Ali S Kurban"
Background: Developing a reliable predictive tool of disease severity in COVID-19 infection is important to help triage patients and ensure the appropriate utilization of health-care resources.
Objective: To develop, validate, and compare three CT scoring systems (CTSS) to predict severe disease on initial diagnosis of COVID-19 infection.
Methods: One hundred and twenty and 80 symptomatic adults with confirmed COVID-19 infection who presented to emergency department were evaluated retrospectively in the primary and validation groups, respectively.
Rationale: This study was conducted to develop, validate, and compare prediction models for severe disease and critical illness among symptomatic patients with confirmed COVID-19.
Methods: For development cohort, 433 symptomatic patients diagnosed with COVID-19 between April 15th 2020 and June 30th, 2020 presented to Tawam Public Hospital, Abu Dhabi, United Arab Emirates were included in this study. Our cohort included both severe and non-severe patients as all cases were admitted for purpose of isolation as per hospital policy.
The purpose of this article was to evaluate MRI features of uterine leiomyomas that predict volumetric response after uterine artery embolization (UAE). This retrospective study included 75 patients with 212 uterine leiomyomas who were successfully treated between August 2013 and December 2018. To predict uterine volumetric response, age, number of lesions, and baseline uterine volume were assessed.
View Article and Find Full Text PDFIntroduction: We examined the relationship between the size and nature of renal masses in term of malignant potential, histological grading, pathological staging and presence of necrosis and sarcomatoid changes.
Materials And Methods: Retrospectively, we reviewed 323 consecutive nephrectomies between 2000 and 2010. Final pathology was correlated with tumour size.