Survival of patients with diabetes mellitus hospitalized for acute respiratory syndrome due to COVID-19

ABSTRACT

Given the magnitude of COVID-19 and the increase in hospitalization cases for severe acute respiratory syndrome (SARS), especially among patients with diabetes mellitus, it is essential to understand the epidemiological aspects inherent to the disease and the worsening of cases. Thus, this study aimed to analyze the survival of patients with diabetes mellitus hospitalized for SARS due to COVID-19 in different regions of Brazil. This is a longitudinal study, carried out based on data reported in the Influenza Epidemiological Surveillance Information System during the year 2020. The number of patients with diabetes mellitus among the hospitalized cases of SARS due to COVID-19 in the different regions of Brazil and the lethality rate among them were identified. A comparison of patient profiles of those who survived or did not survive and the Cox regression analysis were performed to evaluate the factors associated with shorter survival of patients. It was found that 51.4% of patients hospitalized with SARS due to COVID-19 had diabetes, and the case lethality rate among them was 45.0%. The Northeastern and Northern regions presented a higher proportion of patients with diabetes mellitus (56.5% and 54.3%, respectively) and a higher lethality rate (53.8% and 59.9%, respectively). The mean survival time of cases with diabetes mellitus hospitalized for SARS due to COVID-19 was estimated to be 35.7 days (0.5 days). A lower survival rate was observed among residents of the Northeastern and Northern regions with skin color reported as non-white, who required admission to Intensive Care Units and invasive mechanical ventilation, and presented respiratory symptoms such as dyspnea, respiratory distress and an oxygen saturation lower than 95%. It is concluded that diabetes mellitus was responsible for the high occurrence and lethality, mainly in the Northeastern and Northern regions, among non-white patients and those with greater clinical severity, which reinforces the importance of taking measures aimed at supporting this population.

Diabetes mellitus; COVID-19; Severe acute respiratory syndrome; Survival analysis; Pandemics

INTRODUCTION

The novel coronavirus, identified in China in 2019 as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been responsible for the morbidity and mortality of thousands of people due to the disease named COVID-19¹. This disease can be manifested in an asymptomatic form or with mild symptoms, mimicking a case of Influenza-Like Illness (ILI) – especially when affects young people and children – as well as in a severe form, causing pneumonia, severe acute respiratory syndrome (SARS) and organ failure, particularly in the elderly (> 60 years old) and people with heart, lung, or endocrine comorbidities, such as diabetes mellitus²,³.

Studies have shown that the presence of comorbidities such as diabetes mellitus is strongly associated with increased complications and hospitalizations for SARS due to COVID-19⁴,⁵. In China, a study performed in a hospital considered a benchmark for COVID-19 treatment showed that patients with diabetes and affected by the novel coronavirus disease had an increased risk of severe pneumonia, excessive inflammatory responses, and hypercoagulability when compared to those who were not diagnosed with diabetes⁶. A meta-analysis including 33 studies concluded that diabetes mellitus is associated with a worse prognosis in patients with COVID-19, having a twofold increase in the risk of dying compared to patients who do not present this comorbidity⁷.

In Brazil, a study conducted up until the 21^st epidemiological week of 2020 showed that diabetes mellitus was more frequent in individuals hospitalized with SARS due to COVID-19 when compared to the country’s general population⁸. Other studies conducted with patients hospitalized for SARS showed an association between mortality and diabetes mellitus, corroborating the results of many international studies⁵,⁷,⁹,¹⁰.

In March 2020, when the community transmission of COVID-19 was declared, the Health Surveillance Department of the Brazilian Ministry of Health (SVS/MS) carried out the adaptation of the Acute Respiratory Syndrome Surveillance System, aiming to guide the National Health Surveillance System for the simultaneous flow of SARS-CoV-2, influenza and other respiratory viruses, in order to assist the efforts of healthcare professionals¹¹.

In this scenario, regarding the health surveillance measures, the mandatory notification and monitoring of hospitalized cases and deaths by SARS in the Influenza Epidemiological Surveillance Information System (SIVEP-Gripe) – developed to provide updated information in order to support the decision-making by managers and healthcare providers for the prevention and management of this disease – are highlighted¹²,¹³. However, for the SIVEP-Gripe to fulfill its purpose and for the health surveillance measures to be effective, it is necessary to have qualified personnel assigned to it, to provide this information promptly and for this measure not to be regarded as a mere bureaucratic task but as the initial step for planning measures aiming to reduce the impacts of COVID-19, especially among the most vulnerable people¹⁴.

Given the magnitude of COVID-19 and the increase in SARS hospitalizations, especially among patients with diabetes mellitus, it is necessary to produce comprehensive studies to specifically evaluate the behavior of this disease in the different regions of Brazil.

Therefore, this study aims to analyze the survival of patients with diabetes mellitus hospitalized for SARS due to COVID-19 in different regions of Brazil.

MATERIALS AND METHODS

This is an observational, longitudinal study related to the epidemiological surveillance of cases of patients with diabetes mellitus hospitalized for SARS nationwide due to COVID-19 in 2020. The study population consisted of all cases of patients with diabetes mellitus hospitalized for SARS registered in SIVEP-Gripe between the 1^st and the 63^thepidemiological weeks of 2020.

COVID-19 infection was assumed when patients tested positive on the RT-PCR or the SARS-CoV-2 infection tests. People with SARS who required admission to the Intensive Care Unit (ICU) or needed invasive or non-invasive ventilatory support were classified as SARS-critical. The source of information used was the secondary, anonymous, unidentified database of individuals from the SIVEP-Gripe for the year 2020, which was updated on April 26^th, 2021¹⁵.

The variables of interest were as follows: epidemiological week of the onset of first symptoms; evolution (death and recovery); evolution date; Brazilian region of residence and hospitalization; sex (male, female); age (years); skin color (non-white, white); signs and symptoms; ICU admission; ventilatory support (invasive and non-invasive).

The data were analyzed using the Statistical Package for the Social Sciences (SPSS) statistical software (version 23.0, IBM, Armonk, NY, USA). Descriptive and inferential analyses were performed. The Kolmogorov–Smirnov’s test was used to assess the variables’ normality. For the descriptive analysis, absolute and relative frequency distributions, central tendency measures, and variability measures were used, according to the result of the normality test.

The number of patients with diabetes mellitus among the cases of SARS hospitalized for COVID-19 in the different regions of Brazil and the case lethality rate among them were identified. A comparison of the characteristics of patients who survived and those who did not was carried out in order to identify the differences between them. Categorical variables were compared using the Pearson’s Chi-squared test. For the numerical variables, the Mann–Whitney’s test was used, due to the absence of normality in the data distribution. Values of p < 0.05 were considered as statistically significant differences.

To evaluate the factors associated with the survival of critical COVID-19 patients, a survival analysis was performed, considering the observation time as the dependent variable, indicating the end of observation time (censoring). The Kaplan–Meier’s estimator was used to estimate the probability of survival of critical COVID-19 patients.

To identify the statistical significance between survival curves the Log-rank test was applied, adopting as a significant difference the variables that presented p < 0.05. The variables with statistical significance were included in the multivariate analysis using the Cox regression. The Hazard Ratio (HR) and their respective 95% Confidence Intervals (95% CI) were estimated. Since this was a study that only included secondary data from the public domain, of free and open access, without identifying the research participants, the approval by the Research Ethics Committee for Research with Human Beings was not required. Consent was not obtained due to the data being anonymous and in the public domain.

RESULTS

During the 1^st and the 63^th epidemiological weeks of 2020, a total of 563,051 SARS-hospitalized cases were reported, of which 429,010 were due to COVID-19. Of these, 222,111 (51.8%) provided information regarding the presence or absence of diabetes mellitus. A total of 114,144 (51.4%) cases of diabetes mellitus were identified.

Regarding the geographical distribution of cases, it was found that the Northeastern and Northern regions showed a higher proportion of patients with diabetes mellitus among the SARS-hospitalized cases due to COVID-19, with 56.5% and 54.3%, respectively, according to Table 1.

Table 1
Geographic distribution of patients with diabetes mellitus hospitalized for SARS due to COVID-19 in 2020, Brazil.

Region	Patients with diabetes mellitus (n = 114,144)	p-value*
Northern Region	4,957 (54.3%)	Ref.
Northeastern Region	18,607 (56.5%)	<0.001
Central-western Region	9,698 (46.2%)	<0.001
Southeastern Region	62,003 (52.7%)	<0.003
Southern Region	18,879 (45.6%)	<0.001

• *Pearson’s Chi-squared test, statistically significant (p < 0.05); Ref.= Reference used.

The case lethality rate of SARS due to COVID-19 among patients with diabetes mellitus was 45.0%, corresponding to 51,378 deaths in Brazil nationwide in 2020.

Regarding the profile of patients with diabetes mellitus hospitalized for SARS who survived or those who did not, a prevalence of deaths was observed among patients living in the Northern (59.9%) and Northeastern (53.8%) regions, with higher median age (70 vs. 63 years), male (54.3%), who required admission to the Intensive Care Unit (67.4%), required IMV (51.0%), and presented symptoms of dyspnea (86.1%), respiratory distress (77.5%) and SpO₂ < 95% (82.9%), as shown in Table 2.

Table 2
The profile of patients with diabetes mellitus hospitalized for SARS due to COVID-19 who survived or those who did not in 2020, Brazil (n = 114,144).

Variables	Survived (n = 81,704)	Did not survive (n = -65,977)	p-value*
Region of residence (n = 114,144)			<0.001a
Northern Region	1,990 (40.1)	2,967 (59.9)	Ref.
Northeastern Region	8,593 (46.2)	10,014 (53.8)	<0.001a
Central-western Region	5,584 (57.6)	4,114 (42.4)	<0.001a
Southeastern Region	35,568 (57.4)	26,435 (42.6)	<0.001a
Southern Region	11,031 (58.4)	7,848 (41.6)	<0.001a
Age in years (n = 114,144) median (Q1-Q3)	63.0 (54.0–72.0)	70 (62.0-79.0)	<0.001b
Sex (n = 114,130)			<0.001a
Female	30,423 (48.5)	23,496 (45.7)
Male	32,334 (51.5)	27,877 (54.3)
Skin color (n = 90,355)			<0.001a
Non-white	21,323 (43.9)	20,340 (48.7)
White	27,241 (56.1)	21,451 (51.3)
ICU admission (n = 106,129)			<0.001a
No	41,141 (70.2)	15,506 (32.6)
Yes	17,456 (29.8)	32,026 (67.4)
Required IMV (n = 102,986)			<0.001a
No	52,431 (91.9)	22,506 (49.0)
Yes	4,620 (8.1)	23,429 (51.0)
Signs and symptoms
Fever (n = 100,221)	37,877 (67.9)	29,539 (66.5)	<0.001a
Coughing (n = 103,091)	46,240 (80.3)	34,609 (76.1)	<0.001a
Odynophagia (n = 85,409)	10,265 (21.5)	7,167 (19.1)	<0.001a
Dyspnea (n = 104,268)	44,019 (77.2)	40,704 (86.1)	<0.001a
Respiratory distress (n = 96,947)	33,794 (64.1)	34,301 (77.5)	<0.001a
SpO2 < 95% (n = 100,162)	38,489 (70.5)	37,752 (82.9)	<0.001a
Diarrhea (n = 85,415)	9,615 (20.0)	6,040 (16.1)	<0.001a
Vomit (n = 83,772)	5,501 (11.7)	3,852 (10.5)	<0.001a
Abdominal pain (n = 50,434)	23,149 (7.4)	1,451 (6.8)	<0.001a
Fatigue (n = 52,461)	9,373 (31.0)	6,491 (29.2)	<0.001a
Anosmia (n = 50,656)	4,544 (15.5)	2,113 (9.9)	<0.001a
Ageusia (n = 50,551)	4,609 (15.7)	2,098 (9.9)	<0.001a

• Values refer to the total of valid answers; missing data were not considered; Ref. = Reference used (the region with the highest proportion of deaths among patients with diabetes mellitus); ICU = intensive care unit; IMV = invasive mechanical ventilation; SpO₂ = oxygen saturation; ^*Statistically significant (p < 0.05); ^aPearson’s Chi-squared test; ^bMann–Whitney’s test.

The mean survival time of patients with diabetes mellitus hospitalized for SARS due to COVID-19 was estimated to be 35.7 days (mean standard error of 0.5 days). Table 3 shows the univariate analysis results of the variables associated with patient survival based on the Kaplan–Meier estimate.

Table 3
Results of Log-rank test analysis for factors associated with the survival of patients with diabetes mellitus hospitalized for SARS due to COVID-19 in 2020, Brazil (n = 114,144).

Variable	Estimate survival (days) mean (error)	Log-rank (p-value) *
Region of residence		<0.001
Northern Region	25.8 (0.6)
Northeastern Region	29.4 (0.6)
Central-western Region	33.7 (0.9)
Southeastern Region	40.2 (0.9)
Southern Region	34.8 (0.8)
Age (Age group)		0.866
0 to 19 years old	42.3 (7.3)
20 to 59 years old	29.0 (3.5)
≥ 60 years old	19.8 (2.1)
Sex		0.020
Female	36.5 (0.7)
Male	34.8 (0.7)
Skin color		<0.001
Non-white	32.8 (0.7)
White	34.9 (0.8)
ICU admission		<0.001
No	48.8 (1.5)
Yes	30.2 (0.5)
Required IMV		<0.001
No	50.4 (1.3)
Yes	22.0 (0.3)
Signs and symptoms
Fever		<0.001
No	35.3 (0.8)
Yes	36.5 (0.7)
Coughing		<0.001
No	34.2 (0.9)
Yes	36.8 (0.7)
Odynophagia		0.013
No	36.1 (0.7)
Yes	37.3 (1.1)
Signs and symptoms
Dyspnea		<0.001
No	48.5 (2.0)
Yes	32.9 (0.5)
Respiratory distress		<0.001
No	45.9 (1.6)
Yes	31.5 (0.5)
SpO 2 < 95%		<0.001
No	43.4 (1.5)
Yes	32.8 (0.5)
Diarrhea		<0.001
No	36.0 (0.7)
Yes	38.2 (1.5)
Vomit		0.001
No	36.0 (0.7)
Yes	37.5 (1.4)
Abdominal pain		0.804
No	37.7 (0.9)
Yes	34.2 (1.5)
Fatigue		0.912
No	38.2 (1.0)
Yes	33.7 (0.9)
Anosmia		<0.001
No	37.2 (0.9)
Yes	38.3 (1.9)
Ageusia		<0.001
No	37.0 (0.9)
Yes	40.1 (2.1)

• ICU = intensive care unit; IMV = invasive mechanical ventilation; SpO₂ = oxygen saturation; ^*Statistically significant (p < 0.05).

In the multivariate analysis, using Cox regression, it was found that cases residing in the Northern and Northeastern regions had a lower survival rate when compared to those residing in the Central-western region. Conversely, cases residing in the Southern region had a higher survival rate than patients from the Central-western region.

Regarding socio-demographic and clinical profiles, an association was found between shorter survival and patients whose skin color was declared as non-white, patients who required ICU admission, who required IMV, and who presented respiratory symptoms such as dyspnea, respiratory distress and SpO₂ < 95%. The presence of fever, coughing, odynophagia, diarrhea and aging were associated with longer patient survival, as shown in Table 4.

Table 4
Results of the final multivariate Cox regression model for factors associated with death in patients with diabetes mellitus hospitalized for SARS due to COVID-19 in 2020, Brazil (n = 114,144).

Variable	HR	95% CI	p-value*
Central-western Region	-	-	<0.001
Northern Region	1.136	1.065–1.212	<0.001
Northeastern Region	1.084	1.024–1.147	0.006
Southern Region	0.813	0.768–0.854	<0.001
Southeastern Region	0.993	0.945–1.043	0.766
Non-white skin color	1.044	1.013–1.077	0.006
ICU admission	1.045	1.009–1.083	0.014
Required IMV	1.814	1.755–1.875	<0.001
Fever	0.929	0.904–0.956	<0.001
Coughing	0.906	0.879–0.934	<0.001
Odynophagia	0.954	0.918–0.991	0.016
Dyspnea	1.184	1.140–1.230	<0.001
Respiratory distress	1.168	1.130–1.207	<0.001
SpO2 < 95%	1.152	1.1123–1.194	<0.001
Diarrhea	0.942	0.906–0.981	0.003
Ageusia	0.889	0.847–0.933	<0.001

• *Statistically significant (p < 0.05).

DISCUSSION

Diabetes mellitus was considered a comorbidity of high occurrence among patients hospitalized for SARS nationwide, with a higher proportion of cases being patients living in the Northeastern and Northern regions. Lower survival was also found among residents of the Northeastern and Northern regions, who self-declared as non-white, who required ICU admission, required IMV, and who presented symptoms such as dyspnea, respiratory distress and/or SpO₂ < 95%.

Diabetes mellitus is a comorbidity of public health importance. In the Brazilian population, it is estimated that the prevalence of diabetes mellitus is 9.2%, with a higher occurrence in the Southeastern region (12.8%), followed by the Northeastern region (12.2%). The prevalence in the Central-western (7.6%), Southern (7.2%) and Northern (6.3%) regions is lower, which demonstrates regional disparities¹⁶.

Data from the Epidemiological Bulletin of the Ministry of Health indicated that 65.7% of SARS deaths due to COVID-19, notified between the 8^th and the 53^th epidemiological weeks of 2020, had at least one comorbidity or risk factor for the disease, with heart disease and diabetes mellitus being the most frequent conditions¹⁷. Studies suggest that patients with diabetes are at a higher risk of developing severe forms of COVID-19 such as pneumonia and SARS, leading to a worse prognosis and, consequently, a lower survival rate¹⁸,¹⁹.

Results found regarding the survival of patients with diabetes and with SARS due to COVID-19 in different regions may be associated with the socioeconomic disparities and access to health services that exist among Brazilian regions, as the availability and access to resources for disease management and control of complications directly impact survival rates⁸.

The Northern and Northeastern regions presented the highest proportion of diabetes patients hospitalized for SARS due to COVID-19 in 2020, as well as the highest in-hospital lethality. In contrast, the lowest proportion of cases and lowest lethality were found in the Southern region. The heterogeneity presented by Brazil in relation to the evolution of the pandemic and social determinants may justify the differences found among its regions, given that the differences in population distribution patterns, transportation conditions, income, and education inequalities are determining factors for the transmission, severity, and lethality of COVID-19²⁰.

Furthermore, a study based on data available at the Information Technology Department of the Unified Health System (Datasus) showed inequality in the distribution of ICU beds for patients with COVID-19 among the Brazilian regions. In relation to public beds, the Southeastern region concentrates 43.2% of the ICU beds, while the Northern region has 6.9%; in the case of private hospital beds, the Southeastern region concentrates 51.7% of the ICU beds, while the Northern region has 5.8%, contradicting the principle of equity²¹. There is heterogeneity in the distribution of beds per inhabitant among the different regions of Brazil. In the Southeastern and Southern regions, the proportion of public ICU beds is 1.8 beds/10,000 inhabitants. In the Central-western region, the proportion is 1.2 beds/10,000 inhabitants. In the Northeastern and Northern regions, the proportion is even smaller, with 1.0 and 0.9 beds/10,000 inhabitants, respectively²².

In this study, lower survival rates were found among patients who self-declared as non-white, corroborating data found in the United States, where the infection and mortality rates found were higher in the black population compared to the white population; in addition, higher risks of hospitalization, ICU admission, and death were identified in black, brown, and yellow people²³.

A study conducted in Brazil also demonstrated that having black or brown skin color is the second most important risk factor for the outcome of mortality, second only to the factor ‘age’, thus reinforcing the relevance of social determinants²⁴. There is an important relationship between social determinants, multimorbidity and COVID-19, where individuals with the worst socioeconomic conditions are the most affected²⁴. Lower-income and educational level, along with poor living conditions and difficult access to health services, can contribute to the transmission of COVID-19 and the development of its complications in the population self-declared as non-white²⁵. In this context, the importance of social determinants of health are emphasized, especially in pandemics²⁵.

Moreover, studies conducted in the United States and China corroborate the findings of this study by identifying that patients with diabetes mellitus hospitalized due to COVID-19 have a greater need for ICU admission, intubation and IMV use, in addition to higher risks for complications involving respiratory failure, multiple organ damage, and sepsis. These variables can be considered severity indicators of the clinical case presented by patients, and it is known that the greater the severity presented by these patients, the more it will negatively impact their survival time⁶,¹⁶,²⁶-²⁸.

It is worth mentioning that the time of diagnosis of diabetes mellitus, as well as the adherence to its treatment, can also influence the health status of patients, as poorly managed diabetes mellitus is a risk factor for several infectious diseases²⁹. Type II diabetes mellitus, which affects elderly patients the most, has a silent onset. Most patients only receive the diagnosis when they have a complication resulting from high blood glucose levels, which contributes to the greater severity of the clinical condition³⁰.

In Scotland, the risks of complications due to COVID-19 or a greater need for ICU admission were extremely high in the population with diabetes, unlike the population without this comorbidity, which reinforces the greater susceptibility to complications of this population³¹. A meta-analysis conducted in China showed that patients with diabetes presented higher serum levels of inflammatory biomarkers, such as C-reactive protein, IL-6, serum ferritin, and coagulation index, making them more susceptible to an inflammatory storm and consequent worsening of COVID-19. Thus, justifying the greater need for ICU admissions as well as IMV use by these patients, which may contribute to lower survival rates⁶.

A meta-analysis that studied specific symptoms and comorbidities that predict severe COVID-19 and ICU admission demonstrated that the novel coronavirus can generate asymptomatic cases, especially in young patients without comorbidities, as SARS with high rates of morbidity and mortality in patients who are in older age groups and/or with comorbidities. According to the study, dyspnea stands out as the most relevant symptom in predicting worse outcomes, and when present, the probability of ICU admission increases 6.6 times compared to those cases where it is absent³².

In addition, the presence of signs of severity identified in this study, such as dyspnea, respiratory distress, and SpO₂ < 95% define SARS, which when not managed and controlled quickly and accurately can lead to unfavorable outcomes and decreased chances of survival.

Among the limitations of the study, the inherent limitations of using secondary data are highlighted, such as the possibility of filling errors and missing information in the SIVEP-Gripe records, the under-reporting of cases and deaths by SARS, and also the under-reporting of comorbidities. Furthermore, it was not possible to manage duplicate cases in these records, as no case identification variables exist.

Studying the survival of patients affected by SARS due to COVID-19 is vital for the development of preventive and countermeasures against the pandemic in Brazil, especially among patients with diabetes mellitus, as this is a significantly affected population.

CONCLUSION

It was concluded that diabetes mellitus presented high occurrence and lethality, especially in the Northeastern and Northern regions, in patients who were non-white and with greater clinical severity. It was verified that 51.4% of the hospitalized cases had diabetes mellitus and the lethality rate among them was 45.0%. The results presented show the need to meet the demands of the Brazilian diabetic population, especially in these regions, considering the specificities of each one. Moreover, understanding how the social determinants of health contribute to the incidence, prevalence, treatment, and mortality associated with COVID-19 may favor the development of more effective interventions to address the pandemic.

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• FUNDING: This work was supported by Fundacao de Amparo a Pesquisa do Estado de Minas Gerais – FAPEMIG, public notice Nº 001/2021 – Demanda Universal, Process Nº APQ-02360-21.

Publication Dates

• Publication in this collection
  14 Nov 2022
• Date of issue
  2022

History

• Received
  8 July 2022
• Accepted
  3 Oct 2022