ABSTRACT

BACKGROUND:

Multimorbidity can influence intensive care unit (ICU) admissions and deaths due to coronavirus disease (COVID-19).

OBJECTIVE:

To analyze the association between multimorbidity, ICU admissions, and deaths due to COVID-19 in Brazil.

DESIGN AND SETTING:

This cross-sectional study was conducted using data from patients with severe acute respiratory syndrome (SARS) due to COVID-19 recorded in the Influenza Epidemiological Surveillance Information System (SIVEP-Gripe) in 2020.

METHODS:

Descriptive and stratified analyses of multimorbidity were performed based on sociodemographic, ventilatory support, and diagnostic variables. Poisson regression was used to estimate the prevalence ratios.

RESULTS:

We identified 671,593 cases of SARS caused by COVID-19, of which 62.4% had at least one morbidity. Multimorbidity was associated with male sex, age 60–70 and ≥ 80 years, brown and black skin color, elementary education and high school, ventilatory support, and altered radiologic exams. Moreover, all regions of the country and altered computed tomography due to COVID-19 or other diseases were associated with death; only the northeast region and higher education were associated with ICU admission.

CONCLUSION:

Our results showed an association between multimorbidity, ICU admission, and death in COVID-19 patients in Brazil.

KEY WORDS (MeSH terms):
Multimorbidity; Morbidity; COVID-19; Hospitalization; Death; Comorbidity

AUTHORS’ KEY WORDS:
Coronavirus deaths in Brazil; COVID-19 prevalence studies; Hierarchical multiple logistic models; Intensive care unit

INTRODUCTION

The coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), rapidly spread worldwide, causing approximately 185 million cases and more than 4 million deaths between December 31, 2019, and June 30, 2021.¹1 World Health Organization. WHO Coronavirus (COVID-19) Dashboard. Available from: https://covid19.who.int/. Accessed in 2022 (Jun 16).
https://covid19.who.int/...

In Brazil, COVID-19 cases that progress to severe acute respiratory syndrome (SARS), leading to hospitalizations and deaths, are monitored using clinical samples analyzed in reference laboratories. Case notification is mandatory, and records are stored in the Influenza Epidemiological Surveillance Information System (SIVEP-Gripe) from the SARS Surveillance network, initially implemented to monitor the influenza epidemic in 2000.²2 Brasil. Ministério da Saúde. Secretaria de Vigilância em Saúde. Guia de vigilância epidemiológica: emergência de saúde pública de importância nacional pela doença pelo coronavírus 2019 – covid-19/Ministério da Saúde, Secretaria de Vigilância em Saúde. Brasília: Ministério da Saúde; 2022. Available from: https://www.gov.br/saude/pt-br/coronavirus/publicacoes-tecnicas/guias-e-planos/guia-de-vigilancia-epidemiologica-covid-19/view. Accessed in 2022 (Jun 16).
https://www.gov.br/saude/pt-br/coronavir...

Since the emergence of COVID-19, scientific literature has addressed the virological characteristics of SARS-Cov-2 and clinical complications arising from its infection in different populations. Although severity is high in older individuals and males, some studies have shown a relationship between COVID-19 and pre-existing morbidities³3 Mehmood I, Ijaz M, Ahmad S, et al. SARS-CoV-2: An Update on Genomics, Risk Assessment, Potential Therapeutics and Vaccine Development. Int J Environ Res Public Health. 2021;18(4):1626. PMID: 33567746; https://doi.org/10.3390/ijerph18041626.
https://doi.org/10.3390/ijerph18041626... ,⁴4 Singh R, Kang A, Luo X, et al. COVID-19: Current knowledge in clinical features, immunological responses, and vaccine development. FASEB J. 2021;35(3):e21409. PMID: 33577115; https://doi.org/10.1096/fj.202002662R.
https://doi.org/10.1096/fj.202002662R... (e.g., cardiovascular diseases),⁵5 Madjid M, Safavi-Naeini P, Solomon SD, Vardeny O. Potential Effects of Coronaviruses on the Cardiovascular System: A Review. JAMA Cardiol. 2020;5(7):831-40. PMID: 32219363; https://doi.org/10.1001/jamacardio.2020.1286.
https://doi.org/10.1001/jamacardio.2020.... –⁷7 Zheng YY, Ma YT, Zhang JY, Xie X. COVID-19 and the cardiovascular system. Nat Rev Cardiol. 2020;17(5):259-60. PMID: 32139904; https://doi.org/10.1038/s41569-020-0360-5.
https://doi.org/10.1038/s41569-020-0360-... which are associated with increased intensive care unit (ICU) admissions and deaths.

Studies have also shown an association between morbidity and COVID-19; however, only a few have investigated multimorbidity (i.e., the co-occurrence of two or more chronic diseases for a specific period⁸8 Johnston MC, Crilly M, Black C, Prescott GJ, Mercer SW. Defining and measuring multimorbidity: a systematic review of systematic reviews. Eur J Public Health. 2019;29(1):182-9. PMID: 29878097; https://doi.org/10.1093/eurpub/cky098.
https://doi.org/10.1093/eurpub/cky098... ) as a factor predisposing patients to ICU admission and death.⁵5 Madjid M, Safavi-Naeini P, Solomon SD, Vardeny O. Potential Effects of Coronaviruses on the Cardiovascular System: A Review. JAMA Cardiol. 2020;5(7):831-40. PMID: 32219363; https://doi.org/10.1001/jamacardio.2020.1286.
https://doi.org/10.1001/jamacardio.2020.... ,⁹9 Zhou F, Yu T, Du R, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020;395(10229):1054-62. Erratum in: Lancet. 2020;395(10229):1038. Erratum in: Lancet. 2020;395(10229):1038. PMID: 32171076; https://doi.org/10.1016/S0140-6736(20)30566-3.
https://doi.org/10.1016/S0140-6736(20)30...

Brazil had the highest number of COVID-19 cases in Latin America and currently it also has a high prevalence of diabetes, hypertension, and cardiovascular diseases.⁵5 Madjid M, Safavi-Naeini P, Solomon SD, Vardeny O. Potential Effects of Coronaviruses on the Cardiovascular System: A Review. JAMA Cardiol. 2020;5(7):831-40. PMID: 32219363; https://doi.org/10.1001/jamacardio.2020.1286.
https://doi.org/10.1001/jamacardio.2020.... –⁷7 Zheng YY, Ma YT, Zhang JY, Xie X. COVID-19 and the cardiovascular system. Nat Rev Cardiol. 2020;17(5):259-60. PMID: 32139904; https://doi.org/10.1038/s41569-020-0360-5.
https://doi.org/10.1038/s41569-020-0360-... Therefore, studies on association between multimorbidity, and ICU admissions and deaths due to COVID-19, are needed to provide basic knowledge for more complex studies establishing multicausality.⁵5 Madjid M, Safavi-Naeini P, Solomon SD, Vardeny O. Potential Effects of Coronaviruses on the Cardiovascular System: A Review. JAMA Cardiol. 2020;5(7):831-40. PMID: 32219363; https://doi.org/10.1001/jamacardio.2020.1286.
https://doi.org/10.1001/jamacardio.2020.... –⁷7 Zheng YY, Ma YT, Zhang JY, Xie X. COVID-19 and the cardiovascular system. Nat Rev Cardiol. 2020;17(5):259-60. PMID: 32139904; https://doi.org/10.1038/s41569-020-0360-5.
https://doi.org/10.1038/s41569-020-0360-... Therefore, this study aimed to analyze the association between multimorbidity, ICU admission, and death due to COVID-19 in Brazil.

METHODS

Study design and data source

This cross-sectional study was conducted using data from hospitalized patients with SARS, reported in SIVEP-Gripe (base population) between February 20 and December 31, 2020. SIVEP-Gripe is a Brazilian epidemiological surveillance information system implemented in 2000 to monitor the influenza virus. However, during the H1N1 pandemic (2009), SARS surveillance was implemented in the Brazilian hospital network²2 Brasil. Ministério da Saúde. Secretaria de Vigilância em Saúde. Guia de vigilância epidemiológica: emergência de saúde pública de importância nacional pela doença pelo coronavírus 2019 – covid-19/Ministério da Saúde, Secretaria de Vigilância em Saúde. Brasília: Ministério da Saúde; 2022. Available from: https://www.gov.br/saude/pt-br/coronavirus/publicacoes-tecnicas/guias-e-planos/guia-de-vigilancia-epidemiologica-covid-19/view. Accessed in 2022 (Jun 16).
https://www.gov.br/saude/pt-br/coronavir... which became important for the notification of SARS cases during the COVID-19 pandemic.

We considered SARS in patients diagnosed with COVID-19 when they presented with flu-like syndrome followed by dyspnea, respiratory distress, persistent chest tightness, oxygen saturation < 95%, or cyanosis (i.e., bluish discoloration of lips or face).²2 Brasil. Ministério da Saúde. Secretaria de Vigilância em Saúde. Guia de vigilância epidemiológica: emergência de saúde pública de importância nacional pela doença pelo coronavírus 2019 – covid-19/Ministério da Saúde, Secretaria de Vigilância em Saúde. Brasília: Ministério da Saúde; 2022. Available from: https://www.gov.br/saude/pt-br/coronavirus/publicacoes-tecnicas/guias-e-planos/guia-de-vigilancia-epidemiologica-covid-19/view. Accessed in 2022 (Jun 16).
https://www.gov.br/saude/pt-br/coronavir... Moreover, cases should have been be reported in the SIVEP-Gripe, according to the Epidemiological Surveillance Guidance: Public Health Emergency of National Concern due to COVID-19.²2 Brasil. Ministério da Saúde. Secretaria de Vigilância em Saúde. Guia de vigilância epidemiológica: emergência de saúde pública de importância nacional pela doença pelo coronavírus 2019 – covid-19/Ministério da Saúde, Secretaria de Vigilância em Saúde. Brasília: Ministério da Saúde; 2022. Available from: https://www.gov.br/saude/pt-br/coronavirus/publicacoes-tecnicas/guias-e-planos/guia-de-vigilancia-epidemiologica-covid-19/view. Accessed in 2022 (Jun 16).
https://www.gov.br/saude/pt-br/coronavir... All patients with SARS due to COVID-19 were included (study population), except pregnant women, because pregnancy is a temporary condition that affects physiological functions independent of the disease¹⁰10 Kucirka LM, Norton A, Sheffield JS. Severity of COVID-19 in pregnancy: A review of current evidence. Am J Reprod Immunol. 2020;84(5):e13332. PMID: 32865300; https://doi.org/10.1111/aji.13332.
https://doi.org/10.1111/aji.13332... and should be studied separately. Pregnant women represented 0.97% of the patients with SARS due to COVID-19 and were identified using Question 11 of the notification form.²2 Brasil. Ministério da Saúde. Secretaria de Vigilância em Saúde. Guia de vigilância epidemiológica: emergência de saúde pública de importância nacional pela doença pelo coronavírus 2019 – covid-19/Ministério da Saúde, Secretaria de Vigilância em Saúde. Brasília: Ministério da Saúde; 2022. Available from: https://www.gov.br/saude/pt-br/coronavirus/publicacoes-tecnicas/guias-e-planos/guia-de-vigilancia-epidemiologica-covid-19/view. Accessed in 2022 (Jun 16).
https://www.gov.br/saude/pt-br/coronavir...

The database of SARS cases from 2020 was obtained from the openDataSus platform of the Brazilian Ministry of Health on May 3, 2021 (https://opendatasus.saude.gov.br/). We also obtained a dictionary of variables and SARS notification form. Unspecified SARS cases accounted for 37.3% of the total records.

Variables

Outcome variables were ICU admission (yes or no), and death due to COVID-19, which were based on the progression of cases to “yes” (death due to COVID-19) or “no” (cure or death due to other causes) answers.

The independent variable, multimorbidity, was addressed using Question 36 (“Do you have risk factor or comorbidities?”) on the SIVEP-Gripe notification form, which had 14 answer options (puerperium, Down syndrome, asthma, diabetes mellitus, obesity, immunodeficiency or immunosuppression, cardiovascular, hematological, neurological, liver, kidney, or lung disease, among others). However, the puerperium option was not evaluated. We also identified other morbidities in option “others”. After identification and grouping, the following morbidities were included in the study: cancer, diabetes mellitus, dyslipidemias, obesity, systemic arterial hypertension, hypothyroidism, immunodeficiency or immunosuppression, and cerebrovascular, cardiac, hematologic, psychiatric, neurological, respiratory, liver, and kidney diseases. Multimorbidity was defined as a case (presence of at least two morbidities) and non-case (one morbidity). The number of morbidities (from one to five or more) was also included.

Independent variables were the following:

1. Sociodemographic variables:

   • Sex (female or male);

   • Age (days, months, years). Patients were categorized into age groups (20–39, 40–59, 60–79, and ≥ 80 years) based on the age distribution according to chronic morbidities from the National Health Survey 2019.

   • Race or skin color (white or yellow, black, and brown). We excluded the indigenous category because it represented only 0.38% of the SARS cases due to COVID-19.

   • Educational level, categorized as no education, complete elementary education (1^st to 9^th year), high school (1^st to 3^rd year), or higher education

   • Brazilian regions (midwest, northeast, north, southeast, and south) were categorized based on data from the states of residence (including the Federal District) of patients.

2. Ventilatory support and diagnostic variables:

   Invasive ventilatory support (yes, no)

   • Positive radiologic examinations for COVID-19, collected in six categories (normal, infiltrated, consolidated, mixed, other, or not performed) and dichotomized into normal and altered (infiltrated, consolidated, mixed, and other).

   • Computed tomography (CT) was categorized as negative or positive for COVID-19 or other diseases. We did not assess the “not performed” category for radiologic examinations and CT.

Statistical analysis

R software 4.0.4 (R Foundation, Vienna, Austria)¹¹11 R Core Team. R: A Language and Environment for Statistical Computing [Internet]. Vienna, Austria: R Foundation for Statistical Computing; 2021. Available from: https://www.r-project.org. Accessed in 2022 (Jun 16).
https://www.r-project.org... was used to analyze the data. The absolute and relative frequencies were calculated for each morbidity and outcome.

We calculated the number of morbidities and estimated the prevalence (P%), prevalence ratio (PR), and 95% confidence interval (95% CI) for ICU admission and death due to COVID-19.

The association between multimorbidity and outcomes was investigated using raw (number of morbidities) and stratified (multimorbidity) analyses, according to sociodemographic, ventilatory support, and diagnostic variables.

Hierarchical adjusted analysis, associated multimorbidity and sociodemographic, ventilatory support, and diagnostic variables, with ICU admission and death. Three blocks were considered: country region, sociodemographic, and support and diagnostic variables.

Poisson model with robust variance was used to estimate PR and 95% CI since outcomes of interest had prevalence of > 10%.¹²12 Coutinho LM, Scazufca M, Menezes PR. Methods for estimating prevalence ratios in cross-sectional studies. Rev Saude Publica. 2008;42(6):992-8. PMID: 19009156; https://doi.org/10.1590/S0034-89102008000600003.
https://doi.org/10.1590/S0034-8910200800... We selected variables using bivariate analysis between outcomes and region, sociodemographic, ventilatory support, and diagnosis variables; P ≤ 0.20 was set as cutoff point for initial model selection. The model was adjusted to retain variables with the lowest Akaike information criterion values and theoretical criteria. We then assessed the influential point (i.e., absolute value of standardized errors > 3) and collinearity between predictor variables (i.e., positive variables with values > 10). The Hosmer-Lemeshow test determined the goodness of fit of the final model, considering a good fit when P ≥ 0.05.

Ethical aspects

This study used anonymous information from the public domain. Thus, authorization for data collection and approval by the research ethics committee were not required.

RESULTS

A total of 671,593 (59.7%) out of 1,121,601 hospitalized patients with SARS recorded in the SIVEP-Gripe in 2020 were diagnosed with COVID-19 (≥ 20 years and not pregnant). Of these, 216,055 patients were admitted to the ICU (38.1%) and 219,405 (35.7%) died. Moreover, 62.4% (419,425) of the patients with COVID-19 had at least one morbidity, and 97.0% with up to three morbidities were hospitalized due to SARS.

Table 1 shows the frequency distribution of morbidities according to ICU admission and mortality. The frequency of morbidities ranged from 34.1% (systemic arterial hypertension) to 47.1% (kidney diseases) in patients admitted to the ICU, and from 16.0% (hypothyroidism) to 62.8% (cancer) in those who died.

We observed that 29.5% (57,331) of the patients admitted to the ICU and 25.2% (57,359) of the patients who died had no morbidities. The prevalence and prevalence ratio of ICU admissions and deaths increased with an increase in number of morbidities (Table 2).

Stratified analysis indicated a higher prevalence of ICU admissions and deaths in patients with multimorbidity at all types of sociodemographic variables (Table 3).

The prevalence of ICU admission (48.6%) and death (49.0%) were high in males with multimorbidity. Moreover, patients with multimorbidity aged 60–79 years and ≥ 80 years had 48.0% and 48.5% prevalence of ICU admission, respectively. Patients aged ≥ 80 years also had a high mortality rate (64.2%).

The prevalence of ICU admission was higher in patients with multimorbidity, with higher educational levels (49.7%) than in those with lower educational levels (40.1%). However, deaths were more frequent in patients with a lower educational level (60.8%) than in those with a higher educational level (38.8%). Black and brown patients presented with ICU admissions at 45.9 and 45.1%, respectively. They also presented a high prevalence of death (black patients, 51.7%; brown patients, 49.7%). The northeast region had a prevalence of 48.3% for ICU admissions, whereas the northern region had 55.2% of deaths (Table 3).

Regarding the associations between multimorbidity and outcomes according to support and diagnostic variables, the prevalence of ventilatory support was high in patients admitted to the ICU (52.7%) and those who died (51.1%). We also found that a high prevalence according to imaging tests; altered radiologic exams were associated with ICU admission (49.3%) and death (48.6%), while CT positivity for COVID-19 or other diseases was associated with ICU admission (50.3%) and death (41.5%) (Table 4).

The hierarchical adjusted analysis (Table 5) showed an association between multimorbidity and ICU admission and death after inclusion of variables (distal to proximal). These outcomes were also associated with male sex (ICU admission: PR = 1.15, 95% CI: 1.06–1.24; death: PR = 1.34, 95% CI: 1.24–1.46), 60–79 years (ICU admission: PR = 1.42, 95% CI: 1.21–1.66; death: PR = 2.96, 95% CI: 2.47–3.53), ≥ 80 years (ICU admission: PR = 1.55, 95% CI: 1.30–1.85; death: PR = 7.02, 95% CI: 5.76–8.56), brown color (ICU admission: PR = 1.14, 95% CI: 1.04–1.24; death: PR = 1.37; 95% CI: 1.23–1.51), black skin color (ICU admission: PR = 1.20, 95% CI: 1.03–1.41; death: PR = 1.77, 95% CI: 1.50–2.08), elementary education (ICU admission: PR = 1.34, 95% CI: 1.13–1.56; death: PR = 1.31, 95% CI: 1.12–1.55), high school (ICU admission: PR = 1.69, 95% CI: 1.43–1.99; death: PR = 1.38, 95% CI: 1.16–1.64), ventilatory support (ICU admission: PR = 5.50, 95% CI: 4.85–6.23; death: PR = 4.02, 95% CI: 3.53–4.58), and altered radiologic exams (ICU admission: PR = 1.63, 95% CI: 1.38–1.93; death: PR = 1.65, 95% CI: 1.38–1.96). Positive CT for COVID-19 or other diseases had a protective effect against death (PR = 0.65, 95% CI: 0.55–0.76).

We did not find associations between the three Brazilian regions and positive CT findings for COVID-19 or other diseases and ICU admission, or between higher education and death. Collinearity was not observed between variables. The most influential point was no lower than 0.005. Furthermore, the goodness-of-fit test indicated a good fit in both ICU admission (P = 0.358) and death (P = 0.105).

DISCUSSION

We aimed to analyze the association between multimorbidity, ICU admission, and death due to COVID-19 in Brazil. We found associations between multimorbidity, male sex, black skin color, ventilatory support, and altered radiologic exams.

The high percentage of morbidities in the studied population was expected and corroborated the literature¹³13 Iaccarino G, Grassi G, Borghi C, et al. Age and Multimorbidity Predict Death Among COVID-19 Patients: Results of the SARS-RAS Study of the Italian Society of Hypertension. Hypertension. 2020;76(2):366-72. PMID: 32564693; https://doi.org/10.1161/HYPERTENSIONAHA.120.15324.
https://doi.org/10.1161/HYPERTENSIONAHA.... since individuals, with some morbidity and COVID-19, are more likely to be admitted to the ICU or they may expire.

The frequency of morbidities analyzed in this study (e.g., diabetes mellitus, systemic arterial hypertension, obesity, and cardiac diseases) was higher than those in the literature,¹³13 Iaccarino G, Grassi G, Borghi C, et al. Age and Multimorbidity Predict Death Among COVID-19 Patients: Results of the SARS-RAS Study of the Italian Society of Hypertension. Hypertension. 2020;76(2):366-72. PMID: 32564693; https://doi.org/10.1161/HYPERTENSIONAHA.120.15324.
https://doi.org/10.1161/HYPERTENSIONAHA.... ,¹⁴14 Fernández-Niño JA, Guerra-Gómez JA, Idrovo AJ. Multimorbidity patterns among COVID-19 deaths: proposal for the construction of etiological models. Rev Panam Salud Publica. 2020;44:e166. PMID: 33417654; https://doi.org/10.26633/RPSP.2020.166.
https://doi.org/10.26633/RPSP.2020.166... even compared to a study conducted in the Brazilian population.¹⁵15 Nunes BP, Souza ASS, Nogueira J, et al. Multimorbidity and population at risk for severe COVID-19 in the Brazilian Longitudinal Study of Aging. Cad Saude Publica. 2020;36(12):e00129620. PMID: 33237250; https://doi.org/10.1590/0102-311X00129620.
https://doi.org/10.1590/0102-311X0012962... We also obtained more robust results due to the size and national scope of the SIVEP-Gripe database, which is different from previous studies.¹³13 Iaccarino G, Grassi G, Borghi C, et al. Age and Multimorbidity Predict Death Among COVID-19 Patients: Results of the SARS-RAS Study of the Italian Society of Hypertension. Hypertension. 2020;76(2):366-72. PMID: 32564693; https://doi.org/10.1161/HYPERTENSIONAHA.120.15324.
https://doi.org/10.1161/HYPERTENSIONAHA.... –¹⁵15 Nunes BP, Souza ASS, Nogueira J, et al. Multimorbidity and population at risk for severe COVID-19 in the Brazilian Longitudinal Study of Aging. Cad Saude Publica. 2020;36(12):e00129620. PMID: 33237250; https://doi.org/10.1590/0102-311X00129620.
https://doi.org/10.1590/0102-311X0012962...

The simultaneous effects of morbidities explain the increase in hospitalizations and deaths due to COVID-19. Therefore, assessing multimorbidity is important because some COVID-19 patients are expected to have other morbidities. Studies associated with metabolic syndrome and COVID-19 showed worsening of patients' conditions that led to ICU admission or death when two or three additional conditions (e.g., hyperglycemia, dyslipidemia, or arterial hypertension) were considered to classify this syndrome.¹⁶16 Maddaloni E, D’Onofrio L, Alessandri F, et al. Cardiometabolic multimorbidity is associated with a worse Covid-19 prognosis than individual cardiometabolic risk factors: a multicentre retrospective study (CoViDiab II). Cardiovasc Diabetol. 2020;19(1):164. PMID: 33004045; https://doi.org/10.1186/s12933-020-01140-2.
https://doi.org/10.1186/s12933-020-01140... ,¹⁷17 McQueenie R, Foster HME, Jani BD, et al. Correction: Multimorbidity, polypharmacy, and COVID-19 infection within the UK Biobank cohort. PLoS One. 2020;15(8):e0238091. Erratum in: PLoS One. 2021;16(5):e0251613. PMID: 32817712; https://doi.org/10.1371/journal.pone.0238091.
https://doi.org/10.1371/journal.pone.023...

The P% and PR of ICU admission and death due to COVID-19 increased with increase in the number of morbidities. This result was expected;¹⁷17 McQueenie R, Foster HME, Jani BD, et al. Correction: Multimorbidity, polypharmacy, and COVID-19 infection within the UK Biobank cohort. PLoS One. 2020;15(8):e0238091. Erratum in: PLoS One. 2021;16(5):e0251613. PMID: 32817712; https://doi.org/10.1371/journal.pone.0238091.
https://doi.org/10.1371/journal.pone.023... however, the increase was significant in the presence of two or three morbidities. These data indicate a worse prognosis for patients with COVID-19 and multimorbidity, raising concerns for health services due to the high costs and increased demand of the health care personnel and technological support.

Analysis by age groups suggested that younger individuals were less affected by COVID-19 than adults and older individuals.¹⁴14 Fernández-Niño JA, Guerra-Gómez JA, Idrovo AJ. Multimorbidity patterns among COVID-19 deaths: proposal for the construction of etiological models. Rev Panam Salud Publica. 2020;44:e166. PMID: 33417654; https://doi.org/10.26633/RPSP.2020.166.
https://doi.org/10.26633/RPSP.2020.166... ,¹⁸18 Katulanda P, Dissanayake HA, Ranathunga I, et al. Prevention and management of COVID-19 among patients with diabetes: an appraisal of the literature. Diabetologia. 2020;63(8):1440-52. PMID: 32405783; https://doi.org/10.1007/s00125-020-05164-x.
https://doi.org/10.1007/s00125-020-05164... We also found associations between age group and ICU admission or death in patients with multimorbidity. Age is an essential factor to assess the time to ICU admission or death due to COVID-19.¹⁹19 Nanda S, Chacin Suarez AS, Toussaint L, et al. Body Mass Index, Multi-Morbidity, and COVID-19 Risk Factors as Predictors of Severe COVID-19 Outcomes. J Prim Care Community Health. 2021;12:21501327211018559. PMID: 34024181; https://doi.org/10.1177/21501327211018559.
https://doi.org/10.1177/2150132721101855... Also, the time to ICU admission of older individuals may have been underreported since individuals belonging to this group are more likely to die before ICU admission.

This is the first study to report an increase in the P% of patients with multimorbidity admitted to the ICU with an increase in educational level. This result may be associated with better jobs, higher income, and better social living conditions in individuals with higher educational levels, suggesting availability of better healthcare. However, decrease in P% of deaths among individuals with higher education levels with multimorbidity was an inverse result. A study analyzing the socioeconomic aspects of COVID-19 lethality in Brazil showed that patients with higher education who had a more severe disease presented a lower prevalence of death than those with less education.²⁰20 Batista A, Antunes B, Faveret G, et al. Análise socioeconômica da taxa de letalidade da COVID-19 no Brasil. Rio de Janeiro: Núcleo de Operações e Inteligência em Saúde, PUC-RIO; 2020. (Nota técnica 11). Available from: https://ponte.org/wp-content/uploads/2020/05/NT11-An%C3%A1lise-descritiva-dos-casos-de-COVID-19.pdf. Accessed in 2022 (Jun 16).
https://ponte.org/wp-content/uploads/202...

Black and brown patients with multimorbidity have a high mortality rate. Another study also demonstrated that non-white patients, especially black patients, were more likely to develop severe conditions due to COVID-19, require ventilatory support in the ICU, and/or pass away.²¹21 Apea VJ, Wan YI, Dhairyawan R, et al. Ethnicity and outcomes in patients hospitalised with COVID-19 infection in East London: an observational cohort study. BMJ Open. 2021;11(1):e042140. PMID: 33455936; https://doi.org/10.1136/bmjopen-2020-042140.
https://doi.org/10.1136/bmjopen-2020-042...

Regional disparities in socioeconomic development directly affected the number of COVID-19 cases. We observed that the northeast and north regions had the highest prevalence compared to other macro-regions of Brazil. Even considering that presence of, and access to specialized healthcare facilities for treating COVID-19 reduces the number of outcomes investigated in this study, access to health care must be considered in the most affected regions.

Complementary tests, such as radiologic and CT examinations, showed an relevant prevalence of ICU admission and death. Although these tests have good sensitivity, studies investigating complementary tests for COVID-19 have revealed low specificity compared with the reference diagnostic test (i.e., the reverse transcriptase real-time polymerase chain reaction). Nevertheless, some studies recommend using imaging tests to assess the extent of the disease and investigate possible complications,²²22 Salameh JP, Leeflang MM, Hooft L, et al. Thoracic imaging tests for the diagnosis of COVID-19. Cochrane Database Syst Rev. 2020;9:CD013639. Update in: Cochrane Database Syst Rev. 2020;11:CD013639. PMID: 32997361; https://doi.org/10.1002/14651858.CD013639.pub2.
https://doi.org/10.1002/14651858.CD01363... ,²³23 de Farias LPG, Strabelli DG, Fonseca EKUN, et al. Thoracic tomographic manifestations in symptomatic respiratory patients with COVID-19. Radiol Bras. 2020;53(4):255-61. PMID: 32904780; https://doi.org/10.1590/0100-3984.2020.0030.
https://doi.org/10.1590/0100-3984.2020.0... particularly in patients receiving ventilatory support in the ICU.²⁴24 Agricola E, Beneduce A, Esposito A, et al. Heart and Lung Multimodality Imaging in COVID-19. JACC Cardiovasc Imaging. 2020;13(8):1792-808. PMID: 32762885; https://doi.org/10.1016/j.jcmg.2020.05.017.
https://doi.org/10.1016/j.jcmg.2020.05.0...

Multivariate analysis indicated associations between male sex, age 60–70 and ≥ 80 years, black and brown skin color, elementary education, high school, ventilatory support, and radiological examinations. These findings corroborate with recent studies²⁵25 Khan MS, Dogra R, Miriyala LKV, et al. Clinical characteristics and outcomes of patients with Corona Virus Disease 2019 (COVID-19) at Mercy Health Hospitals, Toledo, Ohio. PLoS One. 2021;16(4):e0250400. PMID: 33886663; https://doi.org/10.1371/journal.pone.0250400.
https://doi.org/10.1371/journal.pone.025... –²⁷27 Tisminetzky M, Delude C, Hebert T, et al. Age, Multiple Chronic Conditions, and COVID-19: A Literature Review. Newman AB, organizador. J Gerontol A Biol Sci Med Sci. 2022;77(4):872-878. PMID: 33367606; https://doi.org/10.1093/gerona/glaa320.
https://doi.org/10.1093/gerona/glaa320... suggesting that sociodemographic factors are important predictors of ICU admission and death due to COVID-19.

This study had some limitations. Data may have been underreported, considering the lack of data regarding non-mandatory questions on the form. However, the sample size evaluated allowed us to demonstrate situations that were not revealed by other studies. Another limitation could be related to cases of SARS due to COVID-19 not detected by the Brazilian healthcare system, mainly those who did not have time to be treated in emergency care units or ambulances. Moreover, unreliable records may have influenced the results. Linking different databases may yield robust results. Finally, the SARS notification form did not inform whether deaths were caused during the disease or later due to post-disease complications. Similarly, the length of stay in the ICU may be a relevant factor in the assessment of cases.

In this study we highlight the assessment performed with the morbidities and outcomes, since it may be more expressive when considering isolated, dyad, and triad morbidities.

From the present study, we concluded that the prevalence of ICU admission and death was high in patients with morbidities, and that the increment in number of morbidities increased the prevalence and prevalence ratio of outcomes. An association between multimorbidity and ICU admissions due to COVID-19 was observed when adjusted for male sex, black and brown skin colors, age between 18 and 40 years, patients with some degree of education, use of ventilatory support, and altered radiological examinations. Regarding deaths due to COVID-19, multimorbidity was associated with male sex, black and brown skin colors, age ≥ 60 years, ventilatory support, altered radiologic exams, and CT findings indicating COVID-19 or other diseases.

Our findings may help train healthcare personnel to offer specialized care to patients with morbidities and COVID-19. Furthermore, we expect competent healthcare groups in the three spheres of the government to disseminate knowledge about multimorbidity and COVID-19 to reduce the spread of the disease and its impact on the healthcare system.

REFERENCES

Publication Dates

History