S
Saeid Safiri
Researcher at Tabriz University of Medical Sciences
Publications - 388
Citations - 49522
Saeid Safiri is an academic researcher from Tabriz University of Medical Sciences. The author has contributed to research in topics: Population & Mortality rate. The author has an hindex of 40, co-authored 376 publications receiving 32616 citations. Previous affiliations of Saeid Safiri include Shahid Beheshti University of Medical Sciences and Health Services & University of Tabriz.
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Prognostic Value of Primary Tumor Volume Changes on Kilovoltage Onboard Cone Beam Computed Tomography during Definitive Chemoradiotherapy for stage III Non–Small Cell Lung Cancer: Methodological Issues
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Clinical outcome and predictive factors of postoperative myasthenic crisis in 173 thymomatous myasthenia gravis patients: methodological issues.
TL;DR: This research presents a novel and scalable approach called “Smartphone Biostatistics” that automates the very labor-intensive and therefore time-heavy and expensive and expensive process of manually cataloging and quantifying the components of infectious disease in a population.
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Prevalence of and Factors Associated with Nephropathy in Diabetic Patients Attending an Outpatient Clinic in Harare, Zimbabwe: Methodological Issues.
Reza Pakzad,Saeid Safiri +1 more
TL;DR: It was concluded that higher fructosamine and retinopathy were independent predictors of nephropathy and the findings of the aforementioned study may be biased due to the “Testimation” bias.
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Neonatal cerebral lesions predict 2-year neurodevelopmental impairment in children treated with laser surgery for twin-twin transfusion syndrome: methodological issues.
TL;DR: The authors examined whether postnatally detected cerebral abnormalities were predictive of neurodevelopmental impairment (NDI) in survivors of twin–twin transfusion syndrome who underwent laser surgery and found that cerebral lesions were associated with NDI among “high-risk survivors”.
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J-shaped relationship between habitual coffee consumption and 10-year (2002-2012) cardiovascular disease incidence: methodological issues.
TL;DR: The authors used CVD as a composite endpoint in the study and included measurements at baseline in the analysis, so a degree of regression dilution bias is expected in the association between the exposure and the outcome variable.