Comparative Informativity of Computing Methods of Insulin Resistance Assessment.

Kseneva, S I; Borodulina, E V; Trifonova, O Yu; Fisenko, V P; Udut, V V

Kseneva, S I; Borodulina, E V; Trifonova, O Yu; Fisenko, V P; Udut, V V.

Afiliación

Kseneva SI; E. D. Goldberg Research Institute of Pharmacology and Regenerative Medicine, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, Russia. viksbest@mail.ru.
Borodulina EV; E. D. Goldberg Research Institute of Pharmacology and Regenerative Medicine, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, Russia.
Trifonova OY; E. D. Goldberg Research Institute of Pharmacology and Regenerative Medicine, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, Russia.
Fisenko VP; I. M. Sechenov First Moscow State Medical University, Ministry of Health of the Russian Federation (Sechenov University), Moscow, Russia.
Udut VV; E. D. Goldberg Research Institute of Pharmacology and Regenerative Medicine, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, Russia.

Bull Exp Biol Med ; 172(3): 385-389, 2022 Jan.

Article en En | MEDLINE | ID: mdl-35001303

Asunto(s)

Resistencia a la Insulina; Adulto; Glucemia; Humanos; Insulina; Reproducibilidad de los Resultados

Palabras clave

Caro; FGIR; HOMA-R; QUICKI; insulin resistance

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Resistencia a la Insulina Límite: Adult / Humans Idioma: En Revista: Bull Exp Biol Med Año: 2022 Tipo del documento: Article País de afiliación: Rusia

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