Unknown

Dataset Information

0

Visceral adipose tissue area predicts intensive care unit admission in COVID-19 patients.


ABSTRACT: 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.

SUBMITTER: Pediconi F 

PROVIDER: S-EPMC7836243 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

altmetric image

Publications

Visceral adipose tissue area predicts intensive care unit admission in COVID-19 patients.

Pediconi Federica F   Rizzo Veronica V   Schiaffino Simone S   Cozzi Andrea A   Della Pepa Gianmarco G   Galati Francesca F   Catalano Carlo C   Sardanelli Francesco F  

Obesity research & clinical practice 20201211 1


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 com  ...[more]

Similar Datasets

| PRJNA561526 | ENA
| S-EPMC7856858 | biostudies-literature
| S-EPMC8014094 | biostudies-literature
| S-EPMC8040757 | biostudies-literature
2021-11-17 | GSE176498 | GEO
| 41218 | ecrin-mdr-crc
| S-EPMC8054497 | biostudies-literature
| S-EPMC3359892 | biostudies-literature
| S-EPMC7713054 | biostudies-literature
| S-EPMC6343884 | biostudies-literature