The prediction of obstructive sleep apnea severity based on anthropometric and Mallampati indices.

Amra, Babak; Pirpiran, Mohsen; Soltaninejad, Forogh; Penzel, Thomas; Fietze, Ingo; Schoebel, Christoph

Amra, Babak; Pirpiran, Mohsen; Soltaninejad, Forogh; Penzel, Thomas; Fietze, Ingo; Schoebel, Christoph.

Afiliação

Amra B; Bamdad Respiratory and Sleep Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
Pirpiran M; Department of Internal Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
Soltaninejad F; Bamdad Respiratory and Sleep Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
Penzel T; Center of Sleep Medicine, Charité - Berlin University of Medicine, Berlin, Germany.
Fietze I; Department of Cardiology and Pulmonology, Center of Sleep Medicine, Charité - Berlin University of Medicine, Berlin, Germany.
Schoebel C; Department of Cardiology and Angiology, Center of Sleep Medicine, Charité - Berlin University of Medicine, Berlin, Germany.

J Res Med Sci ; 24: 66, 2019.

Article em En | MEDLINE | ID: mdl-31523252

Palavras-chave

Anthropometry; body mass index; decision trees; gender; obstructive sleep apnea; polysomnography

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Res Med Sci Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Irã

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