Selected article for: "admission predictive and logistic regression"
Author: Pediconi, Federica; Rizzo, Veronica; Schiaffino, Simone; Cozzi, Andrea; Della Pepa, Gianmarco; Galati, Francesca; Catalano, Carlo; Sardanelli, Francesco
Title: Visceral adipose tissue area predicts intensive care unit admission in COVID-19 patients
  • Cord-id: qjjvcmn3
  • Document date: 2020_12_11
    • ID: qjjvcmn3
    Snippet: We retrospectively investigated, in 62 consecutive hospitalised COVID-19 patients (aged 70 ± 14 years, 40 males), the prognostic value of CT-derived subcutaneous adipose tissue and visceral adipose tissue (VAT) metrics, testing them in four predictive models for admission to intensive care unit (ICU), with and without pre-existing comorbidities. Multivariate logistic regression identified VAT score as the best ICU admission predictor (odds ratios 4.307–12.842). A non-relevant contribution of
    Document: We retrospectively investigated, in 62 consecutive hospitalised COVID-19 patients (aged 70 ± 14 years, 40 males), the prognostic value of CT-derived subcutaneous adipose tissue and visceral adipose tissue (VAT) metrics, testing them in four predictive models for admission to intensive care unit (ICU), with and without pre-existing comorbidities. Multivariate logistic regression identified VAT score as the best ICU admission predictor (odds ratios 4.307–12.842). A non-relevant contribution of comorbidities at receiver operating characteristic analysis (area under the curve 0.821 for the CT-based model, 0.834 for the one including comorbidities) highlights the potential one-stop-shop prognostic role of CT-derived lung and adipose tissue metrics.

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