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Anthropometric analysis of body habitus and outcomes in critically ill COVID-19 patients.
Poros, Balázs; Becker-Pennrich, Andrea Sabine; Sabel, Bastian; Stemmler, Hans Joachim; Wassilowsky, Dietmar; Weig, Thomas; Hinske, Ludwig Christian; Zwissler, Bernhard; Ricke, Jens; Hoechter, Dominik J.
  • Poros B; Department of Anesthesiology, LMU Klinikum, University Hospital, Ludwig-Maximilians-University, Munich, Marchioninistr. 15, 81377, Munich, Germany.
  • Becker-Pennrich AS; Department of Anesthesiology and Intensive Care Medicine, RoMed Klinikum Rosenheim, Pettenkoferstr. 10, 83022, Rosenheim, Germany.
  • Sabel B; Department of Anesthesiology, LMU Klinikum, University Hospital, Ludwig-Maximilians-University, Munich, Marchioninistr. 15, 81377, Munich, Germany.
  • Stemmler HJ; The Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), LMU Klinikum, University Hospital, Ludwig-Maximilians-University, Munich, Marchioninistr. 15, 81377, Munich, Germany.
  • Wassilowsky D; Department of Radiology, LMU Klinikum, University Hospital, Ludwig-Maximilians-University, Munich, Marchioninistr. 15, 81377, Munich, Germany.
  • Weig T; Department of Medicine III, LMU Klinikum, University Hospital, Ludwig-Maximilians-University, Munich, Marchioninistr. 15, 81377, Munich, Germany.
  • Hinske LC; Department of Anesthesiology, LMU Klinikum, University Hospital, Ludwig-Maximilians-University, Munich, Marchioninistr. 15, 81377, Munich, Germany.
  • Zwissler B; Department of Anesthesiology, LMU Klinikum, University Hospital, Ludwig-Maximilians-University, Munich, Marchioninistr. 15, 81377, Munich, Germany.
  • Ricke J; Department of Anesthesiology, LMU Klinikum, University Hospital, Ludwig-Maximilians-University, Munich, Marchioninistr. 15, 81377, Munich, Germany.
  • Hoechter DJ; The Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), LMU Klinikum, University Hospital, Ludwig-Maximilians-University, Munich, Marchioninistr. 15, 81377, Munich, Germany.
Obes Med ; 25: 100358, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1294094
ABSTRACT

AIMS:

This study aimed to determine whether anthropometric markers of thoracic skeletal muscle and abdominal visceral fat tissue correlate with outcome parameters in critically ill COVID-19 patients.

METHODS:

We retrospectively analysed thoracic CT-scans of 67 patients in four ICUs at a university hospital. Thoracic skeletal muscle (total cross-sectional area (CSA); pectoralis muscle area (PMA)) and abdominal visceral fat tissue (VAT) were quantified using a semi-automated method. Point-biserial-correlation-coefficient, Spearman-correlation-coefficient, Wilcoxon rank-sum test and logistic regression were used to assess the correlation and test for differences between anthropometric parameters and death, ventilator- and ICU-free days and initial inflammatory laboratory values.

RESULTS:

Deceased patients had lower CSA and PMA values, but higher VAT values (p < 0.001). Male patients with higher CSA values had more ventilator-free days (p = 0.047) and ICU-free days (p = 0.017). Higher VAT/CSA and VAT/PMA values were associated with higher mortality (p < 0.001), but were negatively correlated with ICU length of stay in female patients only (p < 0.016). There was no association between anthropometric parameters and initial inflammatory biomarker levels. Logistic regression revealed no significant independent predictor for death.

CONCLUSION:

Our study suggests that pathologic body composition assessed by planimetric measurements using thoracic CT-scans is associated with worse outcome in critically ill COVID-19 patients.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study / Randomized controlled trials Language: English Journal: Obes Med Year: 2021 Document Type: Article Affiliation country: J.obmed.2021.100358

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study / Randomized controlled trials Language: English Journal: Obes Med Year: 2021 Document Type: Article Affiliation country: J.obmed.2021.100358