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PREDICTORS OF DEATHS ASSOCIATED WITH COVID-19 IN PATIENTS ADMITTED TO TWO HOSPITALS IN THE STATE OF SANTA CATARINA, BRAZIL

PREDICTORES DE MUERTES ASOCIADAS AL COVID-19 EN PACIENTES INGRESADOS EN DOS HOSPITALES DEL ESTADO DE SANTA CATARINA, BRASIL

ABSTRACT

Objective:

To investigate predictors of deaths associated with COVID-19 in patients admitted to two hospitals in the state of Santa Catarina, Brazil.

Method:

This is a retrospective cross-sectional study with 799 patients admitted to hospital for COVID-19 in 2020. The study took place in two reference hospitals for COVID-19 located in Greater Florianópolis, Santa Catarina, Brazil. Data collection took place from November 2020 to January 2021. Electronic medical records were used to collect data and were recorded in the Survey Monkey® application. The database was published in the Figshare Dataset Springer Nature© repository. Multivariate and bivariate analyzes were performed.

Results:

There was a predominance of male patients (57.9%), white patients (93.4%), senior patients (41.5%). The mean age was 61.5 years (±15.8). There was a higher occurrence of Diabetes Mellitus (54.2%) and hypertension (34.2%). Thus, 222 patients (27.8%) were admitted to the Intensive Care Unit. The outcome of death was observed in 157 patients (19.6%). There was a correlation between death and some sociodemographic and clinical variables.

Conclusion:

The study showed a higher prevalence of previous diseases such as hypertension, Diabetes Mellitus, obesity and chronic obstructive pulmonary disease. Age proved to be an independent risk factor for death. Occurrence of death in the age group over 80 years was 13 times higher compared to the younger population.

DESCRIPTORS:
COVID-19; Coronavirus Infections; Mortality; Risk Factors; Coronavirus

RESUMEN

Objetivo:

Investigar los predictores de muertes asociadas a COVID-19 en pacientes ingresados ​​en dos hospitales del estado de Santa Catarina, Brasil.

Método:

Estudio transversal retrospectivo con 799 pacientes hospitalizados por COVID-19 en 2020. El estudio se desarrolló en dos hospitales de referencia para COVID-19 ubicados en la Gran Florianópolis, Santa Catarina, Brasil. La recolección se realizó de noviembre de 2020 a enero de 2021. Para la recolección de datos se utilizaron historias clínicas electrónicas y se registraron en la aplicación Survey Monkey®. La base de datos se publicó en el repositorio Figshare Dataset Springer Nature©. Se realizaron análisis multivariados y bivariados.

Resultados:

Hubo predominio de pacientes masculinos (57,9%), pacientes blancos (93,4%), pacientes ancianos (41,5%). La edad media fue de 61,5 años (±15,8). Hubo mayor aparición de Diabetes Mellitus (54,2%) e hipertensión arterial sistémica (34,2%). Ingresaron en la Unidad de Cuidados Intensivos 222 pacientes (27,8%). El desenlace de muerte se observó en 157 pacientes (19,6%). Hubo correlación entre la muerte y algunas variables sociodemográficas y clínicas.

Conclusión:

El estudio mostró una mayor prevalencia de enfermedades previas como hipertensión, Diabetes Mellitus, obesidad y enfermedad pulmonar obstructiva crónica. La edad demostró ser un factor de riesgo independiente de muerte. La ocurrencia de muertes en el grupo de edad mayor de 80 años fue 13 veces mayor en comparación con la población más joven.

DESCRIPTORES:
COVID-19; Infecciones por Coronavirus; Mortalidad; Factores de Riesgo; Coronavirus

RESUMO

Objetivo:

Investigar os fatores preditores de óbitos associados à Covid-19 em pacientes internados em dois hospitais do estado de Santa Catarina, Brasil.

Método:

Estudo transversal retrospectivo com 799 pacientes internados por Covid-19 em 2020. O estudo ocorreu em dois Hospitais referência para Covid-19 situados na Grande Florianópolis, Santa Catarina, Brasil. A coleta ocorreu de novembro de 2020 a janeiro de 2021. Para a coleta de dados, foram utilizados prontuários eletrônicos, sendo registrados no aplicativo Survey Monkey®. O banco de dados foi publicado no repositório Figshare Dataset Springer Nature©. Análises multivariadas e bivariadas foram realizadas. Resultados: Predominaram pacientes do sexo masculino (57,9%), brancos (93,4%), idosos (41,5%). A média de idade foi de 61,5 anos (±15,8). Houve maior ocorrência de Diabetes Mellitus (54,2%) e Hipertensão Arterial Sistêmica (34,2%). 222 pacientes (27,8%) foram internados na Unidade de Terapia Intensiva. O desfecho óbito foi observado em 157 pacientes (19,6%). Houve correlação do óbito entre algumas variáveis sociodemográficas e clínicas.

Conclusão:

O estudo evidenciou maior prevalência de doenças prévias como a hipertensão, diabetes mellitus, obesidade e doença pulmonar obstrutiva crônica. A idade mostrou-se um fator de risco independente para óbito. A ocorrência de óbito na faixa etária acima de 80 anos foi 13 vezes maior em relação à população mais jovem.

DESCRITORES:
Covid-19; Infecções por coronavírus; Mortalidade; Fatores de risco; Coronavírus

INTRODUCTION

Currently, many uncertainties persist about the situation and, particularly, about the future of the COVID-19 pandemic. Looking to the year 2023, the most important uncertainties are related to the future of this infection and this disease11. Martín Sánchez FJ, Martínez-Sellés M, Molero García JM, Moreno Guillén S, Rodríguez-Artalejo FJ, Ruiz-Galiana J, et al. Insights for COVID-19 in 2023. Rev Esp Quimioter [Internet]. 2023 [cited 2021 Oct 20];36(2):114-24. Available from: https://doi.org/10.37201/req/122.2022
https://doi.org/10.37201/req/122.2022...
.

In December 2019, the world went into a state of alert with the emergence of SARS-CoV-2, responsible for affecting the respiratory tract, causing everything from asymptomatic infections to serious infections, such as acute respiratory syndrome, which can lead to death11. Martín Sánchez FJ, Martínez-Sellés M, Molero García JM, Moreno Guillén S, Rodríguez-Artalejo FJ, Ruiz-Galiana J, et al. Insights for COVID-19 in 2023. Rev Esp Quimioter [Internet]. 2023 [cited 2021 Oct 20];36(2):114-24. Available from: https://doi.org/10.37201/req/122.2022
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-22. Brito SBP, Braga IO, Cunha CC, Palácio MAV, Takenami l. Pandemia da COVID-19: O maior desafio do século XXI, Vigil Sanit Debate [Internet]. 2020 [cited 2021 Jun 10];8(2):54-63. Available from: https://doi.org/10.22239/2317-269X.01531
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. In Brazil, epidemiological surveillance authorities implemented the Public Health Emergency Operations Center for Human Infection by the New Coronavirus33. Ministério da Saúde (BR). Coronavírus: o que você precisa saber e como prevenir o contágio. Brasília: Ministério da Saúde; 2020 [cited 2023 Sep 10]. Available from: https://saude.gov.br/saude-de-a-z/coronavírus
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-44. Kalal N, Sharma SK, Rana N, Kumar A. Impact of COVID-19 on lifestyles related etiquette among nursing staff in India: A cross sectional descriptive e-survey. Invest Educ Enferm [Internet]. 2023 [cited 2021 Oct 10];41(1):e6. Available from:Available from:https://pubmed.ncbi.nlm.nih.gov/37071861/
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and declared a Public Health Emergency of National Concern. In a few epidemiological weeks of 2020, isolation and social distancing were established to implement actions to tackle COVID-19, such as expanding available beds and strategies to minimize the growing number of cases55. Bitencourt JV de OV, Meschial WC, Frizon G, Biffi P, Souza JB de, Maestri E. Nurse's protagonism in structuring and managing a specific unit for covid-19. Texto Contexto Enferm [Internet]. 2020 [cited 2021 Jun 10];29:e20200213. Available from: https://doi.org/10.1590/1980-265X-TCE-2020-0213
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-66. Marques LC, Lucca DC, Alves EO, Fernandes GCM, Nascimento KC do. COVID-19: Nursing care for safety in the mobile pre-hospital service. Texto Contexto Enferm [Internet]. 2020 [cited 2021 Jun 20];29:e20200119. Available from: https://doi.org/10.1590/1980-265X-TCE-2020-0119
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In the state of Santa Catarina, the first cases of COVID-19 were confirmed on March 12, 2020. The spread of the disease to some cities in the state led the government to institute Decree 515 of March 17, 2020, which determined the closure of non-essential services. The population was advised to stay at home, establish social isolation and avoid crowds66. Marques LC, Lucca DC, Alves EO, Fernandes GCM, Nascimento KC do. COVID-19: Nursing care for safety in the mobile pre-hospital service. Texto Contexto Enferm [Internet]. 2020 [cited 2021 Jun 20];29:e20200119. Available from: https://doi.org/10.1590/1980-265X-TCE-2020-0119
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.

Knowledge about the social dynamics of the disease in developing countries and regions with fewer resources required deepening, and around 5% of patients present severe conditions and require hospital admission in Intensive Care Units77. Ramalho Neto JM, Viana RAPP, Franco AS, Prado PR do, Gonçalves FAF, Nóbrega MML da. Nursing diagnosis/outcomes and interventions for critically ill patients affected by covid-19 and sepsis. Texto Contexto Enferm [Internet]. 2020 [cited 2021 Jul 01];29:e20200160. Available from: https://doi.org/10.1590/1980-265X-TCE-2020-0160
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. Studies have also shown that COVID-19 has a mortality rate of around 2% in cases where there is massive alveolar damage and progressive respiratory failure88. Xu Z, Shi L, Wang Y, Zhang J, Huang L, Zhang C, et al. Pathological findings of COVID-19 associated with acute respiratory distress syndrome. Rev Lancet Respir Med [Internet]. 2020 [cited 2021 Jul 01];8(4):420-2. Available from: https://doi.org/10.1016/S2213-2600(20)30076-X
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-99. Wu F, Zhao S, Yu B, Chen YM, Wang W, Zhi-Gang C, et al. A new coronavirus associated with human respiratory disease in China. Nature [Internet]. 2020 [cited 2021 Jun 07];579(7798):265-9. Available from: https://doi.org/10.1038/s41586-020-2008-3
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.

COVID-19 displays a wide clinical spectrum, ranging from asymptomatic or mild cases to more severe situations. International research has identified some variables that predict mortality from COVID-19, such as being male, aged between 49 and 75 years or older, reporting smoking, having high blood pressure, diabetes, heart and respiratory system diseases as well as symptoms such as difficulty breathing, chest pain, cough, diarrhea, nausea, blood expectoration and fatigue1010. Souza ÍVS de, Holanda ER de, Barros MBSC. Factors associated with covid-19 deaths in the city of Recife, Pernambuco, Brazil, 2020: A cross-sectional study with “Notifique Aqui” system data. Epidemiol Serv Saúde [Internet]. 2023 [cited 2021 Oct 11];32(2):e2022701. Available from: https://doi.org/10.1590/S2237-96222023000200014
https://doi.org/10.1590/S2237-9622202300...
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In this regard, the epidemiology, clinical course, pathogenesis and risk factors related to complications as well as registration of COVID-19 are not yet fully understood. This study contributes in this sense, since all of its analysis is based on data prior to the existence of vaccines. As far as we know, it is the only study that included all patients admitted due to COVID-19 in two hospitals in the state of Santa Catarina, Brazil. Thus, we sought to answer the following research questions: How are sociodemographic and clinical factors characterized in patients admitted to hospital with COVID-19? What factors are predictors of death in patients admitted to hospital with COVID-19?

Therefore, this study aimed to investigate predictors of deaths associated with COVID-19 in patients admitted to two hospitals in the state of Santa Catarina, Brazil.

METHOD

This is a retrospective cross-sectional study of 799 patients admitted with a medical diagnosis of COVID-19 to two reference hospitals due to COVID-19 in the state of Santa Catarina, Brazil. As a way of ensuring the rigor and transparency of this study, the criteria indicated by the STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) initiative were adopted1111. Elm EV, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. J Clin Epidemiol [Internet]. 2007 [cited 2021 May 10];61(4):344-9. Available from: https://doi.org/10.1016/j.jclinepi.2007.11.008
https://doi.org/10.1016/j.jclinepi.2007....
.

The population of this study consists of all patients diagnosed with COVID-19, admitted to both institutions, between April 1 and December 31, 2020. A review of electronic medical records was carried out.

All patients aged 18 or over admitted to the hospital with a diagnosis of COVID-19 were included. No criteria were applied to exclude patients.

Data collection was carried out using questionnaires that were stored on the Survey Monkey® platform, which contained questions about sociodemographic data, health conditions, clinical, therapeutic and outcome data. The variables considered for this study were sociodemographic (gender, age, age group, race, marital status, years of study), health conditions (pulmonary involvement, ventilation pattern, high concentration O22. Brito SBP, Braga IO, Cunha CC, Palácio MAV, Takenami l. Pandemia da COVID-19: O maior desafio do século XXI, Vigil Sanit Debate [Internet]. 2020 [cited 2021 Jun 10];8(2):54-63. Available from: https://doi.org/10.22239/2317-269X.01531
https://doi.org/10.22239/2317-269X.01531...
mask, evolution of patients’ condition and previous illnesses), clinical and therapeutic data (number of hospital admissions, hospital admission sector, number of days of hospital admission, risk classification, diagnostic test for COVID-19, type of diagnostic test for COVID-19 and outcome (deaths and non-deaths). The type of diagnostic test for COVID-19 variable considered the performance of a reverse transcription laboratory test followed by polymerase chain reaction (RT-PCR), collected using a nasopharyngeal or oropharyngeal swab, rapid test and serology.

The complete study database is published in Springer Nature’s Figshare Dataset repository, a specific public access repository (https://doi.org/10.6084/m9.figshare.16746073.v3)1212. Jesus ER, Boell JEW, Reckziegel JCL, Malkiewiez MM, Weissenberg VCC, Piccolin MM, et al. COVID-19 Hospital Admissions Database .xlsx. figshare. Dataset [Internet]. 2021 [cited 2021 Dec 10]. Available from: https://doi.org/10.6084/m9.figshare.16746073.v3
https://doi.org/10.6084/m9.figshare.1674...
.

Descriptive and analytical analyzes were carried out using the Statistical Package for the Social Sciences version 25.0 computational tool. A p-value≤ 0.05 was considered significant. The binary logistic regression technique was used to observe the independent variables’ predictive/explanatory capacity (sociodemographic and clinical profile) on the death outcome. The independent variables listed to compose the initial model were those that presented a significant result in comparison with the outcome. The selection of representative variables occurred using the conditional backward method. To check the goodness of fit of the final logistic regression model, Nagelkerk and Hosmer-Lemeshow R22. Brito SBP, Braga IO, Cunha CC, Palácio MAV, Takenami l. Pandemia da COVID-19: O maior desafio do século XXI, Vigil Sanit Debate [Internet]. 2020 [cited 2021 Jun 10];8(2):54-63. Available from: https://doi.org/10.22239/2317-269X.01531
https://doi.org/10.22239/2317-269X.01531...
estimators were considered. The probability of gradual entry of variables into the model was 0.05, and for removal, 0.10.

The results were presented using descriptive statistics using absolute and relative distributions (n - %) as well as measures of central tendency (mean and median) and variability (standard deviation and interquartile range), with a study of the symmetry of distributions of continuous variables analyzed by the Kolmogorov-Smirnov test.

The comparison of continuous variables with the outcome was death vs. no death, and occurred using Student’s t-test (independent groups) and Mann-Whitney U (asymmetric distributions) test. Considering the comparison of categorical variables and the outcome (death vs. non-death), Pearson’s chi-square test (X2) and Yates’ continuity correction were used.

P-value was estimated using the F test. In the adjusted analysis, the variables that presented a p-value <0.200 in the unadjusted analysis were included in the model, and the variables that reached a p-value <0.05 and/or adjusted the analysis remained in the model.

To carry out this study, all ethical precepts determined by Resolution n.º 580/18 of the Brazilian National Health Council. The study was submitted to the Research Ethics Committee of the Universidade Federal de Santa Catarina.

RESULTS

Most participants were male (57.9%), white (93.4%), older adults (41.5%), married or in a stable union (60.8%), with an education level of elementary education (60.2%). The mean age was 61.5 years (SD=15.8 years). The most prevalent comorbidities were hypertension (34.2%) and Diabetes Mellitus (DM) (54.2%). A total of 222 patients (27.8%) were transferred to an Intensive Care Unit (ICU).

The outcome of death was observed in 157 patients (19.6%). Figure 1 describes the number of cases that died observing a certain characteristic, divided by the total number of cases in each age group.

Figure 1 -
Proportions of deaths by age group, Santa Catarina, Brazil, 2021.

In the bivariate and multivariate analysis, it was observed that the risk of death increases according to the days of hospital admission. In the first hospital admission, for each additional day of hospital admission, there is a 2.8% greater chance of a patient dying [OR: 1.028; 95%CI: 1.015 - 1.041]. In the second hospital admission, it was observed that, with each additional day of hospital admission, there is a 3.8% greater chance of a patient dying [OR: 1.038; 95%CI: 1.031 - 1.087]. ICU admission (27.8%) and death (48.6%) showed a significant association with mortality (X2 (g.l.=5) =11.388; p<0.001).

Patients with lung involvement greater than 75% were 2.668 [95%CI: 1.255 - 5.671] times more likely to die, when compared to those with involvement less than 50%. With lung involvement between 50 and 75%, the risk was 1.891 [95%CI: 1.069 - 3.344]. The presence of sepsis resulted in a 7.841 [95%CI: 5.176 - 11.877] times greater chance of a patient dying. For cases requiring dialysis, the risk of death was significantly higher when compared to the group of cases without the need for dialysis [OR: 43.348; 95%CI: 21.666 - 86.726] x [OR: 6.709; 95%CI: 3.786 - 11.887].

Considering the risk estimates on previous diseases, it was found that the presence of chronic obstructive pulmonary disease (COPD) [OR: 1.943; 95%CI: 1.213 - 4.522], chronic kidney failure [OR: 2.949; 95%CI: 1.142 - 2.985] and stroke [OR: 2.447; 95%CI: 1.266 - 5.941] implies a higher risk of death, as shown in Table 1.

Table 1-
Demographic and clinical characterization according to the outcome and risk estimate (Odds Ratio) for occurrence of death, Florianópolis, SC, Brazil, 2021 (n=799).

In Table 2, in the final regression model, age group was observed as a greater risk factor for death in the 60 to 69 years old [OR: 7.299] and 80 years and older [OR: 13.564] groups, when compared to age range up to 49 years.

Regarding the hospital admission sector, patients who were admitted to the ICU were 3.742 times more likely to die when compared to those who were admitted to the clinic/ward sector.

In relation to ventilation pattern, patients with exertional dyspnea were 9.061 times more likely to die. For acute renal failure, the need for dialysis was 25.421 times more likely to die, and, in cases without dialysis, the risk was 7.351 times, as shown in Table 2.

Table 2 -
Initial and final binary logistic regression models to predict the outcome of death through independent sociodemographic and clinical variables with a significant association with the outcome of death. Florianópolis, SC, Brazil, 2021 (n=799).

The binary logistic regression model aimed to investigate the impact of chronic diseases on death, controlling for possible confounding factors. In this study, the age group presented this characteristic. Previous illnesses with a representative number of cases (n ≥ 50) were considered for the regression models. In the new analyses, controlled exclusively by age group, COPD lost its explanatory power [OR: 1.390; 95%CI: 0.817 - 2.366; p=0.224], being the only disease initially proven to be representative [OR: 1.943; 95%CI: 1.213 - 4.522], i.e., age group stands out as a potential predictor of death in this population and with the variables analyzed. Other previous illnesses were also analyzed as a predictive factor for death, considering control by age group and diabetes as well as age group, DM and hypertension. However, the results remained non-significant, as shown in Table 3.

Table 3 -
Binary logistic regression models for each of the diseases (n ≥ 50) as independent variables to predict the outcome of death, with control for age group, diabetes and hypertension. Florianópolis, SC, Brazil, 2021 (n=799).

Regarding age group, the evolution of some disease burdens was compared, and there is evidence that patients aged 65 or over are associated with cardiac dysfunction (p=0.013) (16.8%) (n=18), acute renal failure (p=0.007) (55.0%) (n=61), and pulmonary sepsis (p=0.008) (51.4%) (n=56).

Regarding the analysis that compares different age groups with disease incidence, the age group of 65 years and over presents a significant association with DM (p=0.005), corresponding to 46.4% (n=52), hypertension (p<0.001), corresponding to 71.4% (n=80), COPD (p<0.001), corresponding to 24.1% (n=27), and congestive heart failure (p=0.008), corresponding to 15.2% (n=17). Furthermore, it was observed that patients aged up to 64 years are significantly associated with the presence of obesity (p=0.008), reaching 21.8% (n=24).

DISCUSSION

Our findings highlighted the clinical characteristics with the highest prevalence of previous diseases, with the most prevalent being hypertension, DM, obesity and COPD, corroborating other studies1313. Jordan RE, Chen KK. COVID-19: Risk factors for severe disease and death. BMJ [Internet]. 2020 [cited 2021 Jun 11];368:m1198. Available from: https://doi.org/10.1136/bmj.m1198
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-1515. Zangrillo A, Beretta L, Scandroglio AM, Monti G, Fominskiy E, Colombo S, et al. Characteristics, treatment, outcomes and cause of death of invasively ventilated patients with COVID-19 ARDS in Milan, Italy. Crit Care Resusc [Internet]. 2020 [cited 2021 Jul 10];22(3):200-11. Available from: https://pubmed.ncbi.nlm.nih.gov/32900326/
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. The results also showed that most patients were male and over 60 years of age, corroborating data from other studies1414. Jackson BR, Gold JAW, Natarajan P, Rossow J, Fanfair RN, Silva J da, et al. Predictors at admission of mechanical ventilation and death in an observational cohort of adults hospitalized with Coronavirus Disease 2019. Clin Infect Dis [Internet]. 2020 [cited 2021 May 10];73(11):e4141-51. Available from: https://doi.org/10.1093/cid/ciaa1459
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-1616. Yadaw AS, Miphil YC, Bose S, Iyengar R, Bunyavanich S, Pandey G. Clinical predictors of COVID-19 mortality. Lancet Digit Health [Internet]. 2020 [cited 2021 Jun 11];2(10):516-25. Available from: https://doi.org/10.1016/S2589-7500(20)30217-X
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. In a study by Zangrillo et al.1515. Zangrillo A, Beretta L, Scandroglio AM, Monti G, Fominskiy E, Colombo S, et al. Characteristics, treatment, outcomes and cause of death of invasively ventilated patients with COVID-19 ARDS in Milan, Italy. Crit Care Resusc [Internet]. 2020 [cited 2021 Jul 10];22(3):200-11. Available from: https://pubmed.ncbi.nlm.nih.gov/32900326/
https://pubmed.ncbi.nlm.nih.gov/32900326...
, most male patients were found with a mean age of 73.4 years (±12.7). Males had a more frequent occurrence of death than females, as observed in other studies1616. Yadaw AS, Miphil YC, Bose S, Iyengar R, Bunyavanich S, Pandey G. Clinical predictors of COVID-19 mortality. Lancet Digit Health [Internet]. 2020 [cited 2021 Jun 11];2(10):516-25. Available from: https://doi.org/10.1016/S2589-7500(20)30217-X
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-1717. Escobar AL, Rodrigues TD, Monteiro JC. Letalidade e características dos óbitos por COVID-19 em Rondônia: estudo observacional. Epidemiol Serv Saúde [Internet]. 2021 [cited 2021 Aug 20];30(1):e2020763. Available from: https://doi.org/10.1590/S1679-49742021000100019
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. In contrast with our finding, the study1818. Romano PH, Hillesheim D, Hallal ALC, Menegon FA, Menegon L da S. Covid-19 in health workers: An ecological study from SINAN data, 2020-2021. Texto Contexto Enferm [Internet]. 2023 [cited 2021 Oct 20];32:e20220325. Available from:Available from:https://doi.org/10.1590/1980-265X-TCE-2022-0325en
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that assessed health professionals observed higher rates in females, non-white individuals, younger age groups and states in northern Brazil.

Considering age, the proportion of deaths increased significantly in the age groups of 60 to 69 years, 70 to 79 years and 80 years or more, when compared to younger age groups. Older individuals have a higher mortality rate in relation to COVID-19, especially those with chronic diseases, which may be influenced by increased vulnerability of this population1919. Kabarriti R, Brodin P, Maron M, Guha C, Kalnicki S, Garg MK, et al. Association of race and ethnicity with comorbidities and survival among patients with COVID-19 at an Urban Medical Center in New York. JAMA Netw Open [Internet]. 2020 [cited 2021 May 10];3(9):e2019795. Available from: https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2770960
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-2020. Hammerschmidt KS de A, Bonatelli LCS, Carvalho AA de. The path of hope in relationships involving older adults: the perspective from the complexity of the covid-19 pandemic. Texto Contexto Enferm [Internet]. 2020 [cited 2021 Jul 11];29:e20200132. Available from: https://doi.org/10.1590/1980-265X-TCE-2020-0132
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.

Regarding the mean age related to deaths, the findings showed that the patients who died had a mean age of 70 years (±13.3), similar to a study2121. Menezes HF de, Lima FR, Camacho ACLF, Dantas J da C, Ferreira LB, Silva RAR da. Specialized nursing terminology for the clinical practice Directed at covid-19. Texto Contexto Enferm [Internet]. 2020 [cited 2021 Jun 30];29:e20200171. Available from: https://doi.org/10.1590/1980-265X-TCE-2020-0171
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in which deaths were related to a mean age of 68 years. In another study2222. Pan F, Yang L, Li Y, Liang B, Li L, Ye T, et al. Factors associated with death outcome in patients with severe coronavirus disease-19 (COVID-19): A case-control study. Int J Med Sci [Internet]. 2020 [cited 2021 May 20];17(9):1281-92. Available from: https://doi.org/10.7150/ijms.46614
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, patients with a mean age of 63.6 years (±16.2) died. Another study2323. Ioannou GN, Locke E, Grenn P, Berry K, O’Hare AN, Shah JA, et al. Risk factors for hospitalization, mechanical ventilation, or death among 10 131 US Veterans with SARS-CoV-2 Infection. JAMA Netw Open [Internet]. 2020 [cited 2021 May 21];3(9):e2022310. Available from: https://doi.org/10.1001/jamanetworkopen.2020.22310
https://doi.org/10.1001/jamanetworkopen....
used a multivariate regression model and showed that age was associated with mortality and that the risk of death increased with each additional year of life. Corroborating this finding, a study2424. Ferrando C, Artigas MR, Gea A, Arruti E, Aldecoa C, Bordell A, et al. Características, evolución clínica y factores asociados a la mortalidad en UCI de los pacientes críticos infectados por SARS-CoV-2 en España: Estudio prospectivo, de cohorte y multicéntrico. Rev Esp Anestesiol Reanim [Internet]. 2020 [cited 2021 Aug 10];67(8):425-37. Available from: https://doi.org/10.1016/j.redar.2020.07.003
https://doi.org/10.1016/j.redar.2020.07....
indicated that concomitant mortality risk analyzes were less significant; however, the risk rate increased proportionately with age for those aged 75 and older.

In relation to the hospital admission unit, patients admitted to the ICU presented an outcome with a greater chance of death, which was also frequently found in other studies2525. Petrilli CM, Jones SA, Yang J, Rajagopalan H, O’Donnel L, Chernyak Y, et al. Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: Prospective cohort study. BMJ [Internet]. 2020 [cited 2021 Jul 11];369:m1966. Available from: https://doi.org/10.1136/bmj.m1966
https://doi.org/10.1136/bmj.m1966...
. It is worth noting that the higher number of deaths in the ICU may be related to the high demand and insufficient supply of beds in these locations, associated with the severity of these patients’ clinical conditions and uncertainty regarding what criteria to establish for occupying available beds2626. Pereira JFS, Carvalho RHSBF, Pinho JRO, Thomaz EBAF, Lamy ZC, Soares RD, et al. Challenges at the front: experiences of professionals in admitting patients to the intensive care unit during the covid-19 pandemic. Texto Contexto Enferm [Internet]. 2022 [cited 2023 Jan 21];31:e20220196. Available from: https://doi.org/10.1590/1980-265X-TCE-2022-0196en
https://doi.org/10.1590/1980-265X-TCE-20...
.

The prevalence of smoking also drew attention. The highest incidence of deaths with statistically significant differences were identified in people with COPD, chronic kidney disease and stroke. However, the results obtained did not contribute to the other variables present in the model in a representative way. In the new analyses, controlling exclusively by age group, COPD was the only disease that was initially representative, but lost its explanatory power, i.e., the age group stood out as a predictor of death.

Other previous illnesses were also analyzed to verify whether they could have been responsible for the deaths, considering control by age group and DM as well as age group, DM and hypertension. However, the results did not show statistically significant differences. These findings differ, in part, from another study2525. Petrilli CM, Jones SA, Yang J, Rajagopalan H, O’Donnel L, Chernyak Y, et al. Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: Prospective cohort study. BMJ [Internet]. 2020 [cited 2021 Jul 11];369:m1966. Available from: https://doi.org/10.1136/bmj.m1966
https://doi.org/10.1136/bmj.m1966...
, which associated the presence of heart disease, diabetes, hypertension and kidney disease with deaths from COVID-19, and autoimmune diseases were the only significant predictor of death after adjusting for age and sex.

In a study2727. Almirall A, Kostov B, Heredia MM, Rotllan SV, Ayamar ES, Corrales MS, et al. Prognostic factors in Spanish COVID-19 patients: A case series from Barcelona. PLoS One [Internet]. 2020 [cited 2021 Jul 12];15(8):e0237960. Available from: https://doi.org/10.1371/journal.pone.0237960
https://doi.org/10.1371/journal.pone.023...
that carried out a multivariate analysis of independent factors related to death, a prevalence of neurological diseases and neoplasms was found. Cerebrovascular disease and cancer2828. Jimenéz E, Vela MF, Valencia J, Jimenez IF, Alonso EAA, Garcia EI, et al. Characteristics, complications and outcomes among 1549 patients hospitalised with COVID-19 in a secondary hospital in Madrid, Spain: A retrospective case series study. BMJ Open [Internet]. 2020 [cited 2021 May 09];10(11):e042398. Available from: https://doi.org/10.1136/bmjopen-2020-042398
https://doi.org/10.1136/bmjopen-2020-042...
were also identified as factors most strongly associated with severe COVID-19 infection.

The presence of hypertension, DM, COPD and coronary disease is consistently associated with a higher risk of complications and death as well as advanced age2929. Sole FD, Farcomeni A, Loffredo L, Carnevale R, Menichelli D, Vicario T, et al. Features of severe COVID-19: A systematic review and meta-analysis. Eur J Clin Invest [Internet]. 2020 [cited 2021 Jul 13];50(10):e13378. Available from: https://doi.org/10.1111/eci.13378
https://doi.org/10.1111/eci.13378...
. In addition to the diseases mentioned, obesity was also highlighted as the most prevalent complication3030. Huang C, Wang Y, Xingwand L, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Rev Lancet [Internet]. 2020 [cited 2021 Jun 11];15(10223):497-506. Available from: https://doi.org/10.1016/S0140-6736(20)30183-5
https://doi.org/10.1016/S0140-6736(20)30...
. Studies indicate3131. Pouw N, Maat JV, Veerman K, Oever JT, Janssen N, Abbink E, et al. Clinical characteristics and outcomes of 952 hospitalized COVID-19 patients in The Netherlands: A retrospective cohort study. PLoS One [Internet]. 2020 [cited 2021 Jul 22];16(3):e0248713. Available from: https://doi.org/10.1371/journal.pone.0248713
https://doi.org/10.1371/journal.pone.024...
-3232. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort study. Lancet [Internet]. 2020 [cited 2021 Jul 19];395(10229):1054-62. Available from: https://doi.org/10.1016/S0140-6736(20)30566-3
https://doi.org/10.1016/S0140-6736(20)30...
DM, chronic kidney disease, chronic respiratory disease and cardiovascular diseases as the most frequent comorbidities in people who died due to COVID-19.

Regarding ventilation pattern, the presence of dyspnea and respiratory compromise was frequent in relation to the tomographic pattern, highlighting cases of 50% - 75% of the lung being affected. The main tomographic findings observed in patients with COVID-19 were: ground-glass opacities; ground-glass opacities associated with thickening of the interlobular septa, characterizing a mosaic paving pattern; and ground-glass opacities associated with consolidations3333. Guan WJ, Ni Z, Hu Y, Liang WH, Ou CQ, He JX, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med [Internet]. 2020 [cited 2021 Aug 11];382:1708-20. Available from: https://doi.org/10.1056/NEJMoa2002032
https://doi.org/10.1056/NEJMoa2002032 ...
. The literature shows that the typical findings on chest computed tomography (bilateral ground-glass image of the lung parenchyma, consolidative pulmonary opacities) are compatible with pulmonary edema, which leads to worsening of clinical picture, admission to ICU and frequent death3434. Virot E, Mathien C, Pointurier V, Poidevin A, Labro G, Pinto L, et al. Caracterização do comprometimento pulmonar associado à COVID-19 em pacientes com necessidade de ventilação mecânica. Rev Bras Ter Intensiva [Internet]. 2021 [cited 2021 May 19];33(1):75-81. Available from: https://doi.org/10.5935/0103-507X.20210007
https://doi.org/10.5935/0103-507X.202100...
.

Ground glass opacities, which appear in both lungs and in multiple lobes, are the most frequently observed results in CT scans of COVID-19 cases, generally associated with acute respiratory distress syndrome3535. Chen T, Wu D, Chen H, Yan W, Yang D, Chen G, et al. Clinical characteristics of 113 deceased patients with coronavirus disease 2019: Retrospective study. BMJ [Internet]. 2020 [cited 2021 May 30];368:m1091. Available from: https://doi.org/10.1136/bmj.m1091
https://doi.org/10.1136/bmj.m1091...
. A previous study3636. Berlin DA, Gulick RM, Martinez FJ. Severe Covid-19. N Engl J Med [Internet]. 2020 [cited 2021 May 19];383(25):2451-60. Available from: https://doi.org/10.1056/NEJMcp2009575
https://doi.org/10.1056/NEJMcp2009575...
established a link between the degree of lung impairment and patients’ need for ventilatory support. Furthermore, another study3737. Vences MA, Pareja-Ramos JJ, Otero P, Veramendi-Espinoza LE, Vega-Villafana M, Mogollón-Lavi J, et al. Factors associated with mortality in patients hospitalized with COVID-19: A prospective cohort in a Peruvian national referral hospital. Medwave [Internet]. 2021 [cited 2021 Nov 20];21(6):e8231. Available from: https://doi.org/10.5867/medwave.2021.06.8231
https://doi.org/10.5867/medwave.2021.06....
indicated that the mean percentage of lung involvement on tomography was 55.4% among patients, and a greater extent of lung involvement was associated with a higher mortality rate, which was also observed in this study, in which patients with greater pulmonary involvement had a higher risk of death compared to those with less involvement.

As limitations of this study, the lack of data in medical records relating to certain variables is highlighted, making collection difficult. However, regarding missing information characterization, there was a random pattern (Missing completely at random, MCAR), i.e., there were missing data that did not impact the observed effects. The database is available for reuse3838. Jesus ER, Boell JEW, Reckziegel JCL, Vaz RS, Goulart MA, Peluso FM, et al. Sociodemographic and clinical characteristics of hospital admissions for COVID-19: A retrospective cohort of patients in two hospitals in the south of Brazil [version 1; peer review: 1 approved with reservations]. F1000Research [Internet]. 2023 [cited 2021 Sep 20];12:627. Available from: https://doi.org/10.12688/f1000research.130532.1
https://doi.org/10.12688/f1000research.1...
. Other issues that may have caused bias are that patients admitted to a clinical unit and patients admitted to an ICU were analyzed. Data from tools used to predict mortality such as SAPS and SOFA and laboratory markers did not comprise this analysis.

CONCLUSION

The study was carried out and completed during 2020, before vaccines were available. Clinical, sociodemographic characteristics and predictors of death were analyzed in patients admitted to hospital with COVID-19 in two hospitals in southern Brazil. A higher prevalence of previous diseases was evidenced, particularly hypertension, DM, obesity and COPD. Advanced age was an important risk factor for hospital admission and death. Older patients were highly vulnerable. In the age group of 60 to 69 years, there was a seven times greater chance of death, and among individuals aged 80 and older, this chance increased to 13 times when compared to the age group up to 49 years.

Studies involving different populations can help build a clinical and sociodemographic portrait and understand the variables involved in occurrence of death in patients admitted to hospital with COVID-19. Furthermore, such studies can support actions by health teams, which promote the implementation of care for patients with COVID-19. We recommend that future studies can be conducted to elucidate the interrelationship of variables and predictors of death in patients with COVID-19, considering the emergence of new variants of the virus and the current availability of vaccines.

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NOTES

  • ORIGIN OF THE ARTICLE

    Article extracted from the dissertation - “Análise de internações hospitalares por Covid-19 em dois hospitais de Santa Catarina: Estudo de Coorte”, presented to the Graduate Nursing Program in Nursing, Universidade Federal de Santa Catarina, in 2021.
  • FUNDING INFORMATION

    Santa Catarina Research Support Foundation (FAPESC - Fundação de Amparo à Pesquisa e Inovação do Estado de Santa Catarina). Grant/award number: (2021TR1530)
  • APPROVAL OF ETHICS COMMITTEE IN RESEARCH

    Approved by the Ethics Committee in Research of the Universidade Federal de Santa Catarina, Opinion n.º 4.361.273/2020, Certificate of Presentation for Ethical Consideration (Certificado de Apresentação para Apreciação Ética) 38674120.1.1001.0121
  • TRANSLATED BY

    Letícia Belasco

Edited by

EDITORS

Associated Editors: Glilciane Morceli, Maria Lígia Bellaguarda Editor-in-chief: Elisiane Lorenzini

Publication Dates

  • Publication in this collection
    19 Jan 2024
  • Date of issue
    2023

History

  • Received
    05 June 2023
  • Accepted
    03 Oct 2023
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