Articles producció científicaMedicina i Cirurgia

Predictive biomarkers of COVID-19 severity in SARS-CoV-2 infected patients with obesity and metabolic syndrome

  • Identification data

    Identifier:  imarina:9178060
    Authors:  Perpinan, Carles; Bertran, Laia; Terra, Ximena; Aguilar, Carmen; Lopez-Dupla, Miguel; Alibalic, Ajla; Riesco, David; Camaron, Javier; Perrone, Francesco; Rull, Anna; Reverte, Laia; Yeregui, Elena; Marti, Anna; Vidal, Francesc; Auguet, Teresa
    Abstract:
    In SARS-CoV-2-infected patients, obesity, hypertension, and diabetes are dangerous factors that may result in death. Priority in detection and specific therapies for these patients are necessary. We wanted to investigate the impact of obesity and metabolic syndrome (MS) on the clinical course of COVID-19 and whether prognostic biomarkers described are useful to predict the evolution of COVID-19 in patients with obesity or MS. This prospective cohort study included 303 patients hospitalized for COVID-19. Participants were first classified according to the presence of obesity; then, they were classified according to the presence of MS. Clinical, radiologic, and analytical parameters were collected. We reported that patients with obesity presented moderate COVID-19 symptoms and pneumonia, bilateral pulmonary infiltrates, and needed tocilizumab more frequently. Meanwhile, patients with MS presented severe pneumonia and respiratory failure more frequently, they have a higher mortality rate, and they also showed higher creatinine and troponin levels. The main findings of this study are that IL-6 is a potential predictor of COVID-19 severity in patients with obesity, while troponin and LDH can be used as predictive biomarkers of COVID-19 severity in MS patients. Therefore, treatment for COVID-19 in patients with obesity or MS should probably be intensified and personalized.
  • Others:

    Link to the original source: https://www.mdpi.com/2075-4426/11/3/227
    APA: Perpinan, Carles; Bertran, Laia; Terra, Ximena; Aguilar, Carmen; Lopez-Dupla, Miguel; Alibalic, Ajla; Riesco, David; Camaron, Javier; Perrone, Frances (2021). Predictive biomarkers of COVID-19 severity in SARS-CoV-2 infected patients with obesity and metabolic syndrome. J Pers Med, 11(3), 227-. DOI: 10.3390/jpm11030227
    Paper original source: J Pers Med. 11 (3): 227-
    Article's DOI: 10.3390/jpm11030227
    Journal publication year: 2021-03-01
    Entity: Universitat Rovira i Virgili
    Paper version: info:eu-repo/semantics/publishedVersion
    Record's date: 2026-03-02
    URV's Author/s: Aguilar Crespillo, Carmen Isabel / Alibalic, Ajla / Auguet Quintillà, Maria Teresa / Bertran Ramos, Laia / Camarón Mallén, Javier Mariano / López Dupla, Jesús Miguel / Martí Zaragoza, Àlex / Perpiñan Auguet, Carles / RULL AIXA, ANNA / Terra Barbadora, Ximena / Vidal Marsal, Francisco / Yeregui Etxeberria, Elena
    Department: Medicina i Cirurgia
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Publication Type: Journal Publications
    Author, as appears in the article.: Perpinan, Carles; Bertran, Laia; Terra, Ximena; Aguilar, Carmen; Lopez-Dupla, Miguel; Alibalic, Ajla; Riesco, David; Camaron, Javier; Perrone, Francesco; Rull, Anna; Reverte, Laia; Yeregui, Elena; Marti, Anna; Vidal, Francesc; Auguet, Teresa
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Journal volume: 11
    e-ISSN: 2075-4426
    Thematic Areas: Science and technology studies, Medicine, general & internal, Medicine (miscellaneous), Health care sciences & services
    Author's mail: javiermariano.camaron@urv.cat, carles.perpinan@urv.cat, carles.perpinan@urv.cat, ajla.alibalic@estudiants.urv.cat, elena.yeregui@estudiants.urv.cat, alex.marti@estudiants.urv.cat, laia.bertranr@estudiants.urv.cat, laia.bertranr@estudiants.urv.cat, ximena.terra@urv.cat, carmenisabel.aguilar@urv.cat, carmenisabel.aguilar@urv.cat, mariateresa.auguet@urv.cat, francesc.vidal@urv.cat, jesusmiguel.lopez@urv.cat
  • Keywords:

    Sars-cov-2
    Prediction
    Pneumonia
    Personalized therapy
    Obesity
    Metabolic syndrome
    Good health and well-being
    Covid-19
    Health Care Sciences & Services
    Medicine (Miscellaneous)
    Medicine
    General & Internal
    Science and technology studies
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