T
Thomas McGinn
Researcher at Hofstra University
Publications - 128
Citations - 12974
Thomas McGinn is an academic researcher from Hofstra University. The author has contributed to research in topics: Population & Health care. The author has an hindex of 35, co-authored 123 publications receiving 10091 citations. Previous affiliations of Thomas McGinn include Mount Sinai Hospital & Icahn School of Medicine at Mount Sinai.
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The use of weighted and scored risk assessment models for venous thromboembolism.
TL;DR: The basic concepts in the derivation of recent scored and weighted VTE RAMs in hospitalised surgical and medical patients and cancer outpatients are discussed, the mechanisms for accurate external validation of the models, and implications for their use in clinical practice are discussed.
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Validation of a Model to Predict Perioperative Mortality from Lung Cancer Resection in the Elderly
TL;DR: A prediction rule can identify those patients at higher risk for fatal complications from surgery among elderly patients with lung cancer, and further studies should evaluate whether use of the model can lead to improvements in treatment decision making.
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Validation of a hepatitis C screening tool in primary care.
TL;DR: A prediction tool can be used to accurately identify patients at high risk of HCV who may benefit from serologic screening and future studies should assess whether wider use of this tool may lead to improved outcomes.
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The utility of B-type natriuretic peptide in the diagnosis of heart failure in the emergency department: a systematic review
Deborah Korenstein,Juan P. Wisnivesky,Peter C. Wyer,Rhodes S. Adler,Diego Ponieman,Thomas McGinn +5 more
TL;DR: It is suggested that BNP has moderate accuracy in detecting HF in the ED, and many studies were of marginal quality, and all included patients with varying degrees of diagnostic uncertainty, which will clarify the real-world utility of BNP in the emergency management of dyspnea.
Validity of clinical prediction rules for isolating inpatients with suspected tuberculosis : A systematic review
Juan P. Wisnivesky,Denise Serebrisky,Carlton Moore,Henry S. Sacks,Michael C. Lannuzzi,Thomas McGinn +5 more
TL;DR: It is suggested that clinicians can use prediction rules to identify patients with very low risk of infection among those suspected for TB on admission to the hospital, and thus reduce isolation of patients without TB.