Diabetes is associated with increased risk of death in COVID‐19 hospitalizations in Mexico 2020: A retrospective cohort study

Abstract Background and Aim The COVID‐19 disease course can be thought of as a function of prior risk factors consisting of comorbidities and outcomes. Survival analysis data for diabetic patients with COVID‐19 from an up to date and representative sample can increase efficiency in resource allocation. The study aimed to quantify mortality in Mexico for individuals with diabetes in the setting of COVID‐19 hospitalization. Methods This retrospective cohort study utilized publicly available data from the Mexican Federal Government, covering the period from April 14, 2020, to December 20, 2020 (last accessed). Survival analysis techniques were applied, including Kaplan–Meier curves to estimate survival probabilities, log‐rank tests to compare survival between groups, Cox proportional hazard models to assess the association between diabetes and mortality risk, and restricted mean survival time (RMST) analyses to measure the average survival time. Results A total of 402,388 adults age greater than 18 with COVID‐19 were used in the analysis. Mean age = 16.16 (SD = 15.55), 214,161 males (53%). Twenty‐day Kaplan–Meier estimates of mortality were 32% for COVID‐19 patients with diabetes and 10.2% for those without diabetes with log‐rank p < 0.01. Univariable analysis showed increased mortality in diabetic patients (hazard ratio [HR]: 3.61, 95% confidence interval [CI]: 3.54–3.67, p < 0.01) showing a 254% increase in death. After controlling for confounding variables, multivariate analysis continued to show increased mortality in diabetics (HR: 1.37, 95% CI: 1.29–1.44, p < 0.01) indicating a 37% increase in death. Multivariable RMST at Day 20 showed in Mexico, hospitalized COVID‐19 patients were associated with less mean survival time by 2.01 days (p < 0.01) and a 10% increased mortality (p < 0.01). Conclusions In the present analysis, COVID‐19 patients with diabetes in Mexico had shorter survival times. Further interventions aimed at improving comorbidities in the population, particularly in individuals with diabetes, may contribute to better outcomes in COVID‐19 patients.


COVID-19 is caused by SARS-CoV-2 virus first identified in Wuhan,
China around December 2019 and spread globally. 1,2 The virus spread through internationally and reached Mexico February 28, 2020. 2,3 Since then, over 7 million confirmed cases of COVID-19 and over 300,000 have occurred in Mexico. 4,5 A total of 200,000,000 doses have been administered, which roughly approximates to threequarters of the population receiving a dose. 6,7 Even so, Latin America continues to have a disproportionate burden of disease. 8,9 Mexico has increased comorbidities and age. These comorbidities are associated with increased risk of death and worse outcomes. 10,11 Mexico has the highest overweight and obesity rates with a prevalence of diabetes of over 10% roughly equating to 13 million Mexicans. 12 This number has increased since 2006 by 7% and continues to grow. 13 Diabetes plays a role in increasing risk of contraction and the outcome of many upper respiratory infections including the common cold and influenza. 14,15 The proposed mechanism is in disrupting the body's ability to mount a response and immune dysregulation. Increased inflammation increases the assault to the alveoli. 16 Diabetes also does not exist in isolation but is comorbid with a lot of other risk factors that are not independently associated such as hypertension and death.
Numerous reports from China, Italy, and other countries have consistently demonstrated that patients with diabetes are more susceptible to severe forms of COVID-19. 17,18 Studies have shown that individuals with diabetes and COVID-19 pneumonia are more likely to require intensive care, experience organ failure, and exhibit hypercoagulability. [18][19][20][21][22] The mortality rates among COVID-19 patients with diabetes have been alarmingly high, ranging from 11% to 33% in different populations. 23 A retrospective study conducted in China revealed that patients with pre-existing type 2 diabetes required more medical interventions and presented with multiple organ failure compared to nondiabetic individuals. 24 These findings were supported by observations from the French COVID CORO-NADO cohort, where diabetic patients had a higher risk of death within 28 days after hospitalization. 17 26 Additionally, there is a lack of research that explores the impact of interventions targeting comorbidities, particularly in individuals with diabetes, on the outcomes of COVID-19 patients.
To address these gaps and limitations, the present study focuses on the Mexican population and seeks to investigate the relationship between diabetes and COVID-19 mortality. Patients that contract COVID-19 have a range of symptoms ranging from asymptomatic to death. 27

| METHODS
This study was a retrospective study that used data from the Mexican

| Determination of COVID-19
COVID-19 diagnosis was determined by testing for the presence of the SARS-CoV-2 antigen using nasal swabs. The test was conducted at various monitoring and medical units by the Mexican Government, and results were available in a timely manner.
A positive COVID-19 status was defined as the presence of the SARS-CoV-2 antigen, while a negative status was defined as the absence of the antigen.

| Variables
This study aims to investigate the impact of diabetes on the prognosis of COVID-19 in Mexican patients on the probability of death in the hospital among diabetic patients. This is a large, national, retrospective cohort study that will provide valuable insights into the relationship between diabetes and COVID-19 outcomes, which can inform the development of effective mitigation strategies and improve patient triaging. Information regarding individuals' sex, age, country of origin, existing health conditions (such as hypertension, diabetes, and obesity), smoking habits, and pregnancy status were documented for each person. The COVID-19 status includes recorded data on antigen test outcomes and whether an antigen sample was collected. Throughout their stay at medical facilities, no details concerning the patients' progress were made accessible to the public.

| Statistical analysis
The demographic and diabetes-related characteristics of patients with a positive SARS-CoV-2 antigen were analyzed using descriptive statistics. T-tests and χ 2 tests were used to compare the patients in relation to relevant covariates. The primary endpoint of the study was survival, which was defined as the time from symptom onset to death and censored at the last enrollment date for adult hospitalized COVID-19 patients. Kaplan-Meier curves were plotted to estimate the survival curve, and a log-rank test was used to determine the statistical significance of the survival times between adult hospitalized patients with and without diabetes. A Cox proportional hazards model was used to calculate the hazard ratio and 95% confidence interval (CI) for the treatment effect. All statistical tests were twosided and a p-value of less than 0.05 was considered statistically significant. In addition to overall survival, the restricted means survival time (RMST) was also calculated for diabetic and nondiabetic hospitalized COVID-19 adult patients after propensity matching to control for confounders. This method fitted a parametric survival model to the data to estimate the mean survival time for the two groups. 30 3 | RESULTS Table 1    The results demonstrate demographic numbers that are consistent with rates reported in other studies such as the 21.6% prevalence among hospitalized patients with COVID-19 in Wuhan. 32 The data is also representative of the greater than 10% prevalence in Mexico for the general population. 13 Studies have suggested that individuals with diabetes may be at an increased risk for poor outcomes in COVID-19. 19 The rate of death in hospitalized patients in the present study (32%) is similar to mortality rates reported in other countries such as Italy (25.2%) and Belgium (29.9%). 20,21 Research has indicated that people with diabetes may be more likely to experience severe illness and complications from COVID-19. 22 Diabetes and high blood sugar alone has been found to result in poorer HUANG and HUANG | 5 of 8 outcomes. 33 Many descriptive studies have found high rates of COVID-19 and diabetes concurrently. 34,35 The results of the present survival analysis is consistent with other survival studies find survival analysis studies. According to a study enrolling patients for a 3-month period in 2020 at Dr. Soetomo General Hospital in Indonesia there was a decrease in probability of survival in patients with a metric that included a decrease in white cell count, diabetes, older age. 36  The proposed mechanism of diabetes stems beyond just that of COVID-19, but also includes worsening outcomes and increased contraction of upper respiratory infections (URIs). 14,15 Diabetes impairs the body's ability to amount an immune response from constant and chronic inflammation and damage to blood vessels. [40][41][42] Diabetes also disrupts the bodies immune regulation. 43,44 Diabetes occurs alongside other comorbidities that each also individually contribute to worser outcomes. Tailored interventions, such as targeted education on diabetes management, close monitoring of glycemic control, and early identification of complications, could potentially mitigate the increased mortality risk in this vulnerable population.
One of the major advantages of the present study was the use of a large sample size, which enabled us to detect significant differences between groups with greater precision. There are a few points to keep in mind when interpreting the findings of the present study. As an observational and retrospective study, it is not possible to determine a cause-and-effect relationship between the variables being examined. 45 Additionally, the lack of temporal data on diabetes makes it challenging to understand the impact of COVID-19 on the diabetic status of patients over time.
While the sample size of the study is large, the data were collected from the population of Mexico, and the results may not be applicable to other populations, particularly those outside of Mexico. As a study that is reliant on reported data from individuals, there could be reporting bias. It is important to consider these limitations when interpreting the results of the study.

CONFLICT OF INTEREST STATEMENT
The authors declare no conflict of interest.

DATA AVAILABILITY STATEMENT
The data from this cohort can be found on COVID-19 database on the Mexican Federal Government website. Data described in the manuscript is publicly and freely available without restriction at https://datos.gob.mx/

ETHICAL APPROVAL
The methods behind acquisition and analysis of the data are described by the Epidemiological Surveillance System for Viral Respiratory Diseases of the Mexican Ministry of Health.

TRANSPARENCY STATEMENT
The lead author Samuel Y. Huang affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.