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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Association Between Behavioral Responses and Burn Pain Intensity
TL;DR: The behavioral responses including moving away from painful stimuli, moaning, crying, grimacing, restlessness, protesting, and being silent were found to be significantly associated with burn pain intensity at the dressing change time (P < 0.05).
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Clinical characteristics and survival of pulmonary arterial hypertension associated with three major connective tissue diseases: Methodological issues.
Erfan Ayubi,Saeid Safiri +1 more
TL;DR: The authors tried to assess the effect of baseline clinical characteristics on survival rates of patients with pulmonary arterial hypertension associated with three major connective tissue diseases (CTDs) by developing a forward stepwise model.
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Detection of blaSPM-1 Metallo-β-Lactamase Gene in Imipenem-Resistant Pseudomonas aeruginosa Strains Isolated From Hospitalized Patients in Isfahan Hospitals
TL;DR: The rate of imipenem resistance due to MBL has increased dramatically and early detection and infection-control practices are the best antimicrobial strategy for this organism.
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Validity and reliability of the Greek version of the xerostomia questionnaire in head and neck cancer patients: methodological issues to avoid misinterpretation.
Saeid Safiri,Erfan Ayubi +1 more
TL;DR: The authors tried to assess the reliability and validity of the Greek version of the self-reported eight-item xerostomia questionnaire (XQ) in patients treated with radiotherapy for head and neck (H&N) cancer and concluded that the XQ is a valid tool.
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Platelet count: A predictor of sepsis and mortality in severe burns; Methodological issues.
TL;DR: A take-home message is that the longitudinal data can be analyzed through the advanced and modern statistical methods to provide less biased results and the differences between AUROCs can be statistically examined.