key: cord-0985609-e8pjpch3
authors: Prado-Galbarro, F.-J.; Sanchez-Piedra, C.; Gamiño-Arroyo, A. E.; Cruz-Cruz, C.
title: Determinants of survival following SARS-CoV-2 infection in Mexican outpatients and hospitalised patients
date: 2020-09-30
journal: Public Health
DOI: 10.1016/j.puhe.2020.09.014
sha: 996397a596610237f12f76c51d66c7ab3dac0bcf
doc_id: 985609
cord_uid: e8pjpch3

Objectives This study aimed to evaluate the association of chronic diseases and Indigenous ethnicity on the poor prognosis of coronavirus disease 2019 (COVID-19) outpatients and hospitalised patients in Mexico. Study design Observational study of consecutive COVID-19 cases that were treated in Mexican health care units and hospitals between February 27 and April 27, 2020. Methods Epidemiological, clinical and sociodemographic data were analysed from outpatients and hospitalised patients. Cox regression models were used to analyse the risk of mortality after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Results In total, 15,529 COVID-19 patients were characterised; 62.6% were aged over 40 years, 57.8% were male and 1.4% were of Indigenous ethnicity. A high proportion had a history of diabetes (18.4%), hypertension (21.9%) and obesity (20.9%). Among hospitalised patients, 11.2% received health care in the intensive care unit. Advanced age, being male, Indigenous ethnicity and having a history of chronic diseases, such as hypertension, diabetes and obesity, were significantly associated with a high risk of death following SARS-CoV-2 infection. Diabetes and obesity were the comorbidities most highly associated with death through the models used in this study. Moreover, living in Mexico City and Mexico State (where there is easy access to medical services) and walking (rather than driving or getting public transport), were negatively associated with mortality after SARS-CoV-2 infection. Conclusions Diabetes, hypertension and obesity, combined with older age, being male and Indigenous ethnicity increase the risk of death following SARS-CoV-2 infection in the Mexican population. It is recommended that the incidence of COVID-19 is monitored in Indigenous communities and access to health services is increased nationwide.

The novel coronavirus, named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified in December 2019 in Wuhan, China, and results in coronavirus disease 2019 . 1 The disease is highly contagious and each infected person could infect at least 3 other people on average. 2 On March 11, 2020, the World Health Organization declared COVID-19 to be a global pandemic. 3 At the time of writing, there have been more than 5.3 million cases of COVID-19 and 342,105 deaths, worldwide. 4 In Mexico, the first confirmed case of COVID-19 was registered on February 28, 2020; as of May 24, 2020, there have been 65,856 COVID-19 cases reported 5 and a total of 7179 COVID-19-related deaths. 5 As a result of the rapidly increasing death rates from COVID-19, the key public health priority was to determine the factors that modify the prognosis of an individual following SARS-CoV-2 infection.

Diverse risk factors associated with death from COVID-19 have been reported from national records and hospital case-series, 6, 7, 8 including advanced age and male gender. 9 Studies from hospitalised patients have shown that comorbidities, such as diabetes mellitus, hypertension, cardiovascular disease and obesity also increase the mortality risk among patients with COVID-19. 10, 11, 12 In addition, patients with chronic kidney disease (CKD) have a high risk for in-hospital death. 13 However, few studies have analysed the association between social determinants and COVID-19 death rates. A recent study from the UK analysed ethnicity and risk of COVID-19 death and found that Black individuals were at a higher risk of death than White individuals (adjusted hazard ratio [aHR] 1.71; 95% confidence interval [CI] 1.44-2.02); similar findings were found for the Asian population (aHR 1.62; 95% CI 1.43-1.82). 14, 15, 16 Given that COVID-19 is highly contagious and there are limited data about the impact on vulnerable populations, it is important to analyse the J o u r n a l P r e -p r o o f effect of health inequalities and Indigenous status on the risk of death from COVID-19 in middle-income countries. 17 In low-and middle-income countries (LMICs), such as Mexico, there is a high prevalence of risk factors for COVID-19 death. For example, in 2016, 69.4% of the Mexican population were overweight or obese, 18 10 35 All cases were confirmed using real-time reverse-transcription polymerasechain-reaction (RT-PCR). 19 Clinical data, such as recent exposure history, comorbidities and sociodemographic information, from outpatients and hospitalised patients were analysed. This study did not require the approval of an institutional ethics committee because it is an analysis of secondary data. The data are publicly available on The primary endpoint was the survival time or time to death, defined as the time from the expected day of infection to death or the last follow-up date (censorship). To study mortality was a different endpoint, as there were no variables on the follow-up of patients to know whether they had recovered from COVID-19. An average incubation period of 6 days, 21 an average of 14 days for recovery from the date of symptoms for outpatients 22 and an average of 25 days for hospitalised patients were assumed. 23 COVID-19-positive cases were analysed into two groups: outpatients and hospitalised patients. Sociodemographic variables used in this study included age as a continuous variable, sex (female vs male) and Indigenous ethnicity (a person was defined as Indigenous if an Indigenous language was spoken by a member of the household). The region was classified into four; North-western, Central, Mexico City-State of Mexico and South. Population density size was defined as <100,000 and ≥100,000 people. Clinical information included previous exposure to COVID-19positive cases and pregnancy. Comorbidities were determined based on the patient's self-report on admission, were treated as a categorical variables (yes vs no) and included cardiovascular disease, hypertension, diabetes, obesity, CKD, chronic obstructive pulmonary disease (COPD), asthma, disease associated to immunosuppression, and additional comorbidities. Smoking status was analysed as a habit and independent variable using the Kaplan-Meier estimator and the log-rank test, and the variable was not significant. In addition, smoking status was evaluated in the Cox proportional-hazards models and it was not significant and was thus not included in the final model.

Information on mobility trends, reported by Apple between January 13 and April 28, 2020, was used, which provides data on modes of transport (i.e. public transport, driving and walking). The data published by Apple is the percentage change from a baseline for each region. Taking into account the mean incubation period of COVID-19 infection to be 6 days and the mean duration from onset of symptoms to death to be 18 days, it was considered the average time from onset to death to be 24 days. 21, 23 Therefore, the date of symptoms was accordingly moved back 6 days based on that estimation of the probable date of infection, and the date was related with the daily reported mobility on that day.

Data for the two groups (outpatient vs hospitalised patient) were expressed as mean ± standard deviation (ȳ ± s) and they were compared using the independent group t-test or Fisher's test when appropriate. The count data were showed as a rate (%) and used an χ 2 test. Survival outcomes were analysed according to the Kaplan-Meier estimator. Differences between survival curves were assessed by using the log-rank test. Cox proportionalhazards models were constructed based on multivariate analysis results to evaluate the association between risk factors and survival time over the entire follow-up period, in all samples and stratified by hospitalised and nonhospitalised patients. Variables for multivariate models were chosen based on clinical relevance or a statistically significant relationship with the dependent variable. Statistical analysis was performed using Stata 14.0 (StataCorp, Stata Statistical Software, 2015). A p-value of <0.05 was considered to be statistically significant. Table 1 shows the sociodemographic, clinical and epidemiological characteristics of COVID-19 cases by type of patient care. In total, 62.6% of patients were aged over 40 years, 57.8% were male and 1.4% were of Indigenous ethnicity. Overall, 45.8% of patients with COVID-19 had come into close contact with patients who experienced symptoms of COVID-19, 1.4% of cases were pregnant and 8.9% were tobacco smokers. In the sample, the prevalence of comorbidities was high; 20.9% were obese, 18.4% had type 2 diabetes and 21.9% had hypertension. CKD and COPD were less prevalent at 2.3%, and 2.5%, respectively. Among hospitalised cases, 11 .2% received health care in the intensive care unit and 67.1% of COVID-19 cases developed pneumonia. Indigenous population showed a lower survival probability than non-Indigenous (Figure 1c ). Individuals with diabetes, hypertension or obesity had a decreased overall survival following COVID-19 infection compared with people without these comorbidities (Figure 1d, 1e, 1f ). In addition, males showed a higher mortality than women (10.92% vs 6.93%, respectively, p < 0.001). Similarly, COVID-19 patients with cardiovascular disease, CKD or COPD exhibited higher death rates than those without these conditions (see Table S1in the supplementary information). Table 2 Secondly, the results from this study found a strong association between risk of death and Indigenous ethnicity, which may suggest an increased risk of death in vulnerable groups.

The results of this study indicate that for patients who have not recovered in the average estimated time, the risk of dying is high, particularly among hospitalised patients, Indigenous individuals and patients with diabetes, hypertension and obesity. During the 32 days of follow-up, there were 1434 (9.23%) deaths from COVID-19.

Similar studies have found different rates of death. For example, a study from Wuhan, China, found that 16.5% of patients died during the 32 days of follow-up and the study of Cheng et al. also found the death rate to be 16.5%. Other studies of two hospitals in Wuhan found the rate of death to be 15.6%. Additionally, a study from China found the mortality rate to be 3.1%. 7, 11, 13, 24 Differences in these results compared with the current study could be attributed to the sample characteristics, including prevalence of risk factors in the study population and access to health treatment.

A high risk of death was found to be associated with two variables; the first was Indigenous ethnicity, which increased the likelihood of death following SARS-CoV-2 infection by approximately 47%. Previous studies have described the effect of ethnicity on the risk of COVID-19 death; for example, one study from the US documented a high death rate in Afro-American populations, as is the case of Louisiana, where 70% of COVID-19 deaths have been in the Afro-American population. Increased death rates have also been attributed to limited J o u r n a l P r e -p r o o f access to health care, high prevalence of chronic conditions and reduced social distancing in the low-wage essential services that cannot be performed remotely. 25 In Mexico, Indigenous people could be living a such situations, with limited health care as a result of the low distribution of human resources and healthcare staff in rural areas. 26 Other factors could be the high prevalence of chronic conditions among Indigenous people; the prevalence of metabolic syndrome in this population has been recorded as 50.3% and the prevalence of high blood pressure was 42.7%. 27 The reduced risk of COVID-19 deaths (50%, p < 0.001) seen in Mexico City and the State of Mexico could be attributed to the easy access to medical services and resulting treatment of the disease in this area; previous evidence from a Chinese study suggests that mortality is correlated to healthcare resource availability. 28 Chronic diseases are common factors associated with the risk of death from COVID-19. A strong positive association was found between metabolic conditions and death. Previous studies have explained the effect of comorbidities on COVID-19 patients. Patients with diabetes, often associated with obesity and hypertension, may be more susceptible to an inflammatory reaction, eventually leading to rapid progression and adverse prognosis of COVID-19. 29 In obese patients, there is an increased risk of inflammation due to adipose tissue potential. Hyper-expression of ACE2 is also found in obese patients and thromboembolism events are frequent. 30 SARS-CoV-2 infection induces an alteration of insulin secretion and may increase resistance to insulin action, which could lead to acute decompensation in patients with diabetes. 31 A high level of troponin and natriuretic peptides have been found in critically ill patients, where the main proposed mechanism is inflammation of the vascular system that can result in diffuse microangiopathy with thrombosis. Inflammation of the myocardium can induce myocarditis, heart failure, cardiac arrhythmias, acute coronary syndrome, rapid deterioration and sudden death. 32 Currently, social distancing is the only effective tool recommended to slow the spread of COVID-19. 33 In some countries, such as Italy, Spain and China, lockdown measures have been extreme; however, in Mexico, the J o u r n a l P r e -p r o o f measures were more moderate considering the vulnerability of the population. In this study, it was identified that the mobility reduction is very important in controlling and reducing the risk of death from COVID-19.

There are significant associations between mobility trends and COVID-19 death risk: driving and public transport were positively associated with the risk of death. Walking was negatively associated with the risk of death and showed that it is the most sustainable option and allows guarantees social distancing.

This study has several limitations. It is a case-series study based on the Mexican registry data; thus, the proportion of severe and critical patients and fatality rate might be different to the whole infected population.

The follow-up was a relatively short duration and some patients remained in hospital at the time of writing.

Further studies that explore the associations in a sufficiently long time frame are warranted. As with other observational studies, our findings do not provide direct inference about the causation or reverse causation of comorbidities and the poor clinical outcomes. Finally, in this work, no information on the date of recovery is available, even though we were able to find information on the time of recovery in the existing literature. 

Interactions of coronaviruses with ACE2, angiotensin II, and RAS inhibitors-lessons from available evidence and insights into COVID-19

The Estimate of the Basic Reproduction Number for Novel Coronavirus disease (COVID-19): A Systematic Review and Meta-Analysis

WHO declares COVID-19 a pandemic

European Centre for Disease Prevention and Control (ECDC)

European Centre for Disease Prevention and Control (ECDC) 2020

Covid-19 México. Subsecretaría de Prevención y Promoción la Salud

Clinical characteristics of 113 deceased patients with coronavirus disease 2019: Retrospective study

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

Prevalence of comorbidities and its effects in coronavirus disease 2019 patients: A systematic review and meta-analysis

Risk factors of critical & mortal COVID-19 cases: A systematic literature review and meta-analysis

Acute Hyperglycemic Crises with Coronavirus Disease-19: Case Reports

Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis

Angiotensin-converting enzyme inhibitors and angiotensin receptor blockers during COVID-19 pandemic

Kidney disease is associated with inhospital death of patients with COVID-19

OpenSAFELY: factors associated with COVID-19-related hospital death in the linked electronic health records of 17 million adult NHS patients. medRxiv

Combating COVID-19: health equity matters

COVID-19 ) related deaths by ethnic group

The survival of indigenous peoples is at risk

La Obesidad en México. Estado de la política pública y recomendaciones para su prevención y control. México: Salud Pública de México

Interim infection prevention and control recommendations for patients with known or patients under investigation for 2019 novel coronavirus (2019-nCoV) in a healthcare setting

Hypertension in Mexican adults: Prevalence, diagnosis and type of treatment. Ensanut MC 2016

Report of the WHO-China joint mission on Coronavirus Disease

Symptom Duration and Risk Factors for Delayed Return to Usual Health Among Outpatients with COVID-19 in a Multistate Health Care Systems Network -United States

Estimates of the severity of coronavirus disease 2019: a model-based analysis

Risk factors for severity and mortality in adult COVID-19 inpatients in Wuhan

African American COVID-19 Mortality: A Sentinel Event

Critical review of social, environmental and health risk factors in the Mexican indigenous population and their capacity to respond to the COVID-19

Metabolic syndrome in indigenous communities in Mexico: a descriptive and cross-sectional study

Potential association between COVID-19 mortality and healthavailability

Hospitalization Rates and Characteristics of Patients Hospitalized with

Comorbidities in COVID-19: Outcomes in hypertensive cohort and controversies with renin angiotensin system blockers

Are patients with hypertension and diabetes mellitus at increased risk for COVID-19 infection?

COVID-19 pandemic: do we need systematic screening of patients with cardiovascular risk factors in Low-and Middle-Income Countries (LMICs) for preventing death?

Does COVID-19 Spread Through Droplets Alone

Available from: www.datos.gob.mx [accessed 16

COVID-19, coronavirus disease

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.