Predicting Mortality Due to SARS-CoV-2: A Mechanistic Score Relating Obesity and Diabetes to COVID-19 Outcomes in Mexico

J Clin Endocrinol Metab. 2020 Aug 1;105(8):dgaa346. doi: 10.1210/clinem/dgaa346.

Abstract

Background: The SARS-CoV-2 outbreak poses a challenge to health care systems due to its high complication rates in patients with cardiometabolic diseases. Here, we identify risk factors and propose a clinical score to predict COVID-19 lethality, including specific factors for diabetes and obesity, and its role in improving risk prediction.

Methods: We obtained data of confirmed and negative COVID-19 cases and their demographic and health characteristics from the General Directorate of Epidemiology of the Mexican Ministry of Health. We investigated specific risk factors associated to COVID-19 positivity and mortality and explored the impact of diabetes and obesity on modifying COVID-19-related lethality. Finally, we built a clinical score to predict COVID-19 lethality.

Results: Among the 177 133 subjects at the time of writing this report (May 18, 2020), we observed 51 633 subjects with SARS-CoV-2 and 5,332 deaths. Risk factors for lethality in COVID-19 include early-onset diabetes, obesity, chronic obstructive pulmonary disease, advanced age, hypertension, immunosuppression, and chronic kidney disease (CKD); we observed that obesity mediates 49.5% of the effect of diabetes on COVID-19 lethality. Early-onset diabetes conferred an increased risk of hospitalization and obesity conferred an increased risk for intensive care unit admission and intubation. Our predictive score for COVID-19 lethality included age ≥ 65 years, diabetes, early-onset diabetes, obesity, age < 40 years, CKD, hypertension, and immunosuppression and significantly discriminates lethal from non-lethal COVID-19 cases (C-statistic = 0.823).

Conclusions: Here, we propose a mechanistic approach to evaluate the risk for complications and lethality attributable to COVID-19, considering the effect of obesity and diabetes in Mexico. Our score offers a clinical tool for quick determination of high-risk susceptibility patients in a first-contact scenario.

Keywords: COVID-19; Mexico; SARS-CoV-2; diabetes; lethality; obesity.

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Betacoronavirus*
  • COVID-19
  • Comorbidity
  • Coronavirus Infections / immunology
  • Coronavirus Infections / mortality*
  • Databases, Factual
  • Diabetes Mellitus / mortality*
  • Disease Susceptibility
  • Female
  • Hospitalization / statistics & numerical data
  • Humans
  • Immunocompromised Host
  • Male
  • Mexico / epidemiology
  • Middle Aged
  • Obesity / mortality*
  • Pandemics
  • Pneumonia, Viral / immunology
  • Pneumonia, Viral / mortality*
  • Prognosis
  • Proportional Hazards Models
  • Pulmonary Disease, Chronic Obstructive / mortality
  • Renal Insufficiency, Chronic / mortality
  • Risk Assessment / methods
  • Risk Factors
  • SARS-CoV-2
  • Sex Factors