key: cord-0928373-rcgxslfp
authors: Oliveira, Eduardo A.; Mak, Robert H.; Colosimo, Enrico A.; Mendonça, Ana Carmen Q.; Vasconcelos, Mariana A.; Martelli‐Júnior, Hercílio; Silva, Ludmila R.; Oliveira, Maria Christina L.; Pinhati, Clara C.; Simões e Silva, Ana Cristina
title: Risk factors for COVID‐19‐related mortality in hospitalized children and adolescents with diabetes mellitus: An observational retrospective cohort study
date: 2022-03-27
journal: Pediatr Diabetes
DOI: 10.1111/pedi.13335
sha: 44cf924394978721478c083d33130b6236c81a37
doc_id: 928373
cord_uid: rcgxslfp

BACKGROUND: Diabetes has been recognized as a major comorbidity for COVID‐19 severity in adults. This study aimed to characterize the clinical outcomes and risk factors for COVID‐19‐related death in a large cohort of hospitalized pediatric patients with diabetes. METHODS: We performed an analysis of all pediatric patients with diabetes and COVID‐19 registered in SIVEP‐Gripe, a Brazilian nationwide surveillance database, between February 2020 and May 2021. The primary outcome was time to death, which was evaluated considering discharge as a competitive risk by using cumulative incidence function. RESULTS: Among 21,591 hospitalized pediatric patients with COVID‐19, 379 (1.8%) had diabetes. Overall, children and adolescents with diabetes had a higher prevalence of ICU admission (46.6% vs. 26%), invasive ventilation (16.9% vs. 10.3%), and death (15% vs. 7.6%) (all P < 0.0001). Children with diabetes had twice the hazard of death compared with pediatric patients without diabetes (Hazard ratio [HR] = 2.0, 95% CI, 1.58–2.66). Among children with diabetes, four covariates were independently associated with the primary outcome, living in the poorest regions of the country (Northeast, HR, 2.17, 95% CI 1.18–4.01, and North, (HR 4.0, 95% CI 1.79–8.94), oxygen saturation < 95% at admission (HR 2.97, 95% CI 1.64–5.36), presence of kidney disorders (HR 3.39, 95% CI 1.42–8.09), and presence of obesity (HR 3.77, 95% CI 1.83–7.76). CONCLUSION: Children and adolescents with diabetes had a higher risk of death compared with patients without diabetes. The higher risk of death was associated with clinical and socioeconomic factors.

comorbidities associated with COVID-19 severity and mortality among adults. [4] [5] [6] [7] [8] As most research on COVID- 19 and diabetes has been done in adults, it is unclear whether this increased risk of a more severe course of COVID-19 is also present in the pediatric population. There is a paucity of data on the risk of death related to COVID-19 in pediatric patients with diabetes. The few studies reported are from highor upper-middle income countries, often with a small sample size, which may limit the generalizability of findings. For example, in the first months of the pandemic, Cardona-Hernandez et al. 9 collected data from large pediatric diabetes centers around the world and concluded that young individuals with diabetes (<25 years) were not at increased risk of hospitalization for COVID-19. On the other hand, in 2021, Elbarbay et al. 10 conducted an international survey on the management of children with diabetes and COVID-19. In this survey, 44% of respondents reported increased episodes of diabetic ketoacidosis in newly diagnosed cases and 30% in established cases. However, there is still limited data on many aspects of how COVID-19 has affected children and adolescents with diabetes, especially in developing countries. 11 We recently described clinical outcomes and risk factors for death in children and adolescents hospitalized during the first and second waves of COVID-19 in Brazil. 12, 13 In both waves, we found an important and additive effect related to the presence of comorbidities in general. Based on data from the adult population, we hypothesized that COVID-19 in pediatric patients with diabetes would have a poorer outcome compared to COVID-19 in pediatric patients without diabetes. The aim of this study was to compare the risk of mortality in children with and without diabetes and to identify risk factors for mortality in a subsample of pediatric patients with diabetes, using the SIVEP-Gripe (Surveillance Information System for Influenza) dataset, a Brazilian nationwide registry of hospitalized COVID-19 cases.

We performed a retrospective cohort study including all hospitalized pediatric cases recorded in the SIVEP-Gripe. Detailed information regarding this database, including reporting form and data dictionary, codes, and all de-identified data, are publicly available at https:// opendatasus.saude.gov.br/dataset/srag-2020 for data from 2020, and at https://opendatasus.saude.gov.br/dataset/srag-2021-e-2022 for data from 2021-2022.

We included all consecutively registered patients, aged less than 20 years, with a positive quantitative RT-PCR (RT-qPCR) test result for SARS-CoV-2 who had been admitted to the hospital. The RT-qPCR tests for SARS-CoV-2 were completed after hospital admission. For the present study, we integrated two datasets. We downloaded the first database on January 10, 2021 and the second database on May 29, 2021. For the purpose of analysis, we merged both datasets into a unique database and the cases were divided into two groups, (1) Wave 1 (44 epidemiological weeks from February 16, 2020 to December 31, 2020) and (2) Wave 2 (19 epidemiological weeks from January 1, 2021 to May 29, 2021 ). In addition, we updated on May 29, 2021, the outcomes of interest for pediatric patients admitted at Wave 1. The rationality in separate the sample into two waves was due to the emergence of the Gamma variant identified in January 2021 in the city Manaus, Brazil. 14 This lineage became predominant in Brazil around February 2021 and was characterized by an increased transmissibility and with more severe spectrum of the disease both in adults and children. 13, 15 We identified diabetes cases in the SIVEP-Gripe database by retrieving data from specific fields for comorbidities. In the database, information about comorbidities is provided in closed fields (yes/no) without any detailed information about the underlying condition. In addition to diabetes, the dataset provides data on the following comorbidities: asthma, obesity, and cardiovascular, lung, kidney, liver, autoimmune, neurologic, and hematologic diseases. The complete information about included and excluded cases are displayed in the flowchart ( Figure 1 ).

Clinical, demographic, and epidemiological data recorded in SIVEP-Gripe are described elsewhere. 12 was categorized into three groups (none, 1, and 2 or more comorbidities).

The clinical course of the disease was reported in terms of respiratory support (none, noninvasive oxygen support, and invasive ventilation), admission to intensive care unit (ICU), hospital discharge, COVID-19-related death, and ongoing clinical situation. Severe spectrum of COVID-19 was defined by the admission to the intensive care unit (ICU), the need of mechanical ventilation, and disease-related death.

Although several variables were mandatory in the SIVEP-Gripe registration form, others had the option "Ignored." These variables presented a considerable amount of missing information. The following covariates had missing information: gender (0.08%), ethnicity (19.6%), oxygen saturation at admission (24.7%), ICU admission (8%), ventilatory support (5.5%), and primary outcome (0.8%). We use various strategies to partially overcome this problem. We describe these strategies in detail elsewhere. 13 Briefly, in the first step, patients with missing information about the primary outcome were removed from the survival analyses. For those cases with missing data on a particular symptom or comorbidity, we assumed that the clinical condition was absent. Finally, we performed a multiple imputation using all predictors plus the cumulative incidence function for the primary outcome.

Ten imputed data sets were generated using the multiple imputation chain equations (MICE) package from the R software (R Foundation for Statistical Computing, Vienna, Austria. Available on https://cran.rproject.org/web/packages/mice/index.html). We combined the results from analyses on each of the imputed values using Rubin's rules to produce estimates and confidence intervals that incorporate the uncertainty of imputed values. 17, 18 

The primary outcome was time until COVID-19-related death (in-hospital-mortality). The survival time was defined from the day of admission until the event (death or discharge). We also analyzed the need of health-care resources (ICU admission and respiratory support, defined as none, noninvasive, or invasive).

The analysis was performed in three steps. First, we compared clinical, demographic and outcomes data in children and adolescents with and without diabetes. We used medians and interquartile ranges (IQRs) or means and standard deviations (SDs) to summarize continuous variables and calculated frequencies and proportions for categorical variables. We compared means and proportions using respectively the F-test and the chi-square test. Second, to assess the impact of diabetes on the survival of pediatric patients with COVID-19, we performed a survival analysis, using the cumulative incidence function (CIF) 19 and the Fine-Gray subdistribution risk model 20 to estimate the incidence of outcomes over time in the presence of competing risks. A competing risk is an event whose occurrence precludes observation of the primary event of interest. In our study, as COVID-19-related death is the primary outcome, hospital discharge was analyzed as a concurrent event in the analysis.

We performed both univariate and multivariate analyses of competitive risk survival, including age, sex, ethnicity, geographic macroregion, signs and symptoms at admission, oxygen saturation, obesity, and other comorbidities as covariates. Finally, the third step was performed on the subsample of pediatric patients with diabetes in order to identify risk factors for mortality in this group. For this step, we also performed a competitive risk survival analysis using the same methodology described in the second step. All statistical tests were two tailed, and statistical significance was defined as P < 0.05.

We accessed data in SIVEP-Gripe, which are already deidentified and publicly available. Following ethically agreed principles on open data, this analysis did not require ethical approval in Brazil. We reported our findings following the guideline STROBE for observational cohort studies. 21 3 | RESULTS

The cohort comprised 21,591 cases, including 379 cases (1.8%) of diabetes. The demographic and clinical characteristics of the cohort T A B L E 1 Demographic, clinical characteristics, and outcomes of children and adolescents with laboratory-confirmed COVID-19 according to presence of diabetes (n = 21,591) 25 reported a meta-analysis of a total of 6452 patients from 30 studies in which adult patients with diabetes had an unfavorable outcome compared with the general population. The meta-analysis showed that diabetes was associated with a poor outcome, including disease progression (RR 3.31, 95%CI, 1.08, 10.14) and mortality (RR 2.12. 95%CI, 1.44-3.11). Another meta-analysis further demonstrated that adult patients with diabetes had more than twice the risk of ICU admission and more than triple the risk of death. 27 The population-based study by Barron et al. 28 showed that Type 1 and It is noteworthy that these findings are quite similar to those found in our study. We emphasize that we did not find cohort studies with large samples of pediatric patients hospitalized with diabetes infected with SARS-CoV-2, highlighting the novelty and relevance of the present study.

Several mechanisms have been suggested as an underlying explanation for the more severe course of COVID 19 in patients with diabetes. While diabetes itself appears to be an independent risk factor, other important factors may contribute to an increased risk of COVID-19 severity and mortality in this group of patients, including older age, hypertension, cardiovascular disease, chronic kidney disease, obesity, a pro-inflammatory and hypercoagulable state, and glucose dysregulation. 7,29 However, it is important to point out that most mechanisms responsible for the higher mortality in adult patients with diabetes clearly are absent in pediatric population. Furthermore, it is unknown whether potential changes in immune response and increased cytokine storm propensity demonstrated in adults may also occur in pediatric patients with diabetes. Thus, further clinical studies in children with diabetes are clearly needed to assess the mechanisms involved in the poor outcome in pediatric age.

In the second step of our analysis, we evaluate risk factors of COVID-related death among children and adolescents with diabetes.

After adjustment by the competing-risk survival analysis, patients from the poorest Brazilian geographic macro-regions (North and Northeast), those with low oxygen saturation at admission, and those with associated kidney diseases and obesity exhibited a higher hazard of death. The finding of an increased risk of in-hospital death in patients from the poorest Brazilian macroregions (North and Northeast) is similar to our previous studies about the entire cohort of hospitalized children and adolescents. 12, 13 In these studies, we provided evidence that the social factors were inextricably associated with clinical factors to determine the outcomes of COVID-19 in Brazil, especially for the most socioeconomically disadvantaged population. 12, 13 Brazil is a country of continental dimensions and is geopolitically cents. 12, 35, 36 In adult cohorts, chronic kidney disease has been shown to be an independent risk factor for in-hospital death related to COVID-19 in the general population 35, 36 and recent studies have shown that this association is also present in patients with diabetes. 5, 37, 38 Obesity has been widely associated with the severity and mortality of COVID-19. 36, 39, 40 Since diabetes and obesity lead to proinflammatory, hypercoagulable and immune altered conditions, it would be expected an additional effect of obesity upon COVID-19 severity in diabetes patients. However, we must emphasize again that data on the role of obesity in the prognosis of children with diabetes and COVID-19 are limited in the pediatric population. 29 In addition, unfortunately the lack of detailed information on the clinical characteristics of the cohort in the SIVEP-Gripe database prevented us from further evaluating the relationship between these comorbidities and outcomes in children with diabetes. increased COVID-19-related mortality in both types of diabetes. Furthermore, glycemic control during hospital stay is an important prognostic factor for worse outcomes in hospitalized patients with COVID-19. 26, 43 Unfortunately, the SIVEP-Gripe database did not provide information on glycated hemoglobin A levels. Finally, missing data is another inherent issue due to the nature of a registry based on point-of-care case report forms. We used various strategies to try to partially overcome this limitation. For example, to clarify the fundamental point of the relationship between diabetes and its complications with the outcome, we have analyzed separately the relationship between fundamental covariates such as obesity and kidney disorders.

Regarding, missing variables, we used the multiple imputation technique for relevant predictors.

In conclusion, in this analysis of a large nationwide database of hospitalized patients with proven COVID-19, we found that children and adolescents with diabetes had a more severe spectrum of the disease and a higher risk of death than patients without diabetes. Among pediatric patients with diabetes and COVID-19, the higher hazard of death was associated with living in the poorest geographic regions of Brazil, low oxygen saturation at admission, and presence of obesity and kidney disease. Our findings suggest that the high mortality rates in children and adolescents with diabetes and COVID-19 in Brazil may be partially related to social and economic conditions and with the lack of appropriate support for these pediatric patients. Further prospective studies with large samples of pediatric patients with diabetes are necessary to investigate COVID-19 outcome, risk factors and potential mechanisms related to disease severity.

The authors are profoundly grateful and in debt to all frontline health-care workers for their impressive efforts to tackle the COVID-19 pandemic in Brazil. All data from the SIVEP-Gripe (Influenza Epidemiological Surveillance Information System) were systematically collected in challenging circumstances by these frontline healthcare workers.

Eduardo A. Oliveira https://orcid.org/0000-0002-5642-7164

Ana Cristina Simões e Silva https://orcid.org/0000-0001-9222-

Ethnic differences in SARS-CoV-2 infection and COVID-19-related hospitalisation, intensive care unit admission, and death in 17 million adults in England: an observational cohort study using the OpenSAFELY platform

Ethnic differences in COVID-19 mortality during the first two waves of the coronavirus pandemic: a nationwide cohort study of 29 million adults in England

Risk and protective factors for COVID-19 morbidity, severity, and mortality

Sanchis-Gomar F. Diabetes mellitus association with coronavirus disease 2019 (COVID-19) severity and mortality: a pooled analysis

Phenotypic characteristics and prognosis of inpatients with COVID-19 and diabetes: the CORO-NADO study

Is diabetes mellitus associated with mortality and severity of COVID-19? A meta-analysis

COVID-19 pandemic, coronaviruses, and diabetes mellitus

Diabetes, obesity, and risk prediction of severe COVID-19

Children and youth with diabetes are not at increased risk for hospitalization due to COVID-19

The challenges of managing pediatric diabetes and other endocrine disorders during the COVID-19 pandemic: results from an international cross-sectional electronic survey

COVID-19 and children with diabetes-updates, unknowns, and next steps: first, do no extrapolation

Clinical characteristics and risk factors for death among hospitalised children and adolescents with COVID-19 in Brazil: an analysis of a nationwide database

Comparison of the first and second waves of the COVID-19 pandemic in children and adolescents in a middle-income country: clinical impact associated with SARS-CoV-2 gamma lineage

Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus

COVID-19 hospital admissions: Brazil's first and second waves compared

Ethnic and regional variations in hospital mortality from COVID-19 in Brazil: a cross-sectional observational study

Dealing with missing predictor values when applying clinical prediction models

Multiple imputation: a primer

Tutorial in biostatistics: competing risks and multi-state models

A proportional hazards model for the subdistribution of a competing risk

The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies

Age and hospitalization risk in people with type 1 diabetes and COVID-19: data from the T1D exchange surveillance study

Clinical characteristics and outcomes of patients with diabetes and COVID-19 in association with glucoselowering medication

Patterns of multimorbidity and risk of severe SARS-CoV-2 infection: an observational study in the U.K

Diabetes mellitus is associated with increased mortality and severity of disease in COVID-19 pneumoniaa systematic review, meta-analysis, and meta-regression

Association of Blood Glucose Control and Outcomes in patients with COVID-19 and pre-existing type 2 diabetes

Diabetic patients with COVID-19 infection are at higher risk of ICU admission and poor short-term outcome

Associations of type 1 and type 2 diabetes with COVID-19-related mortality in England: a wholepopulation study

COVID-19 and diabetes: understanding the interrelationship and risks for a severe course

The Brazilian health system: history, advances, and challenges

Geographical variation in demand, utilization, and outcomes of hospital services for COVID-19 in Brazil: a descriptive serial cross-sectional study

Effect of socioeconomic inequalities and vulnerabilities on health-system preparedness and response to COVID-19 in Brazil: a comprehensive analysis

Characterisation of the first 250 000 hospital admissions for COVID-19 in Brazil: a retrospective analysis of nationwide data

Pathophysiology of acute respiratory distress syndrome and COVID-19 lung injury

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

Factors associated with COVID-19-related death using OpenSAFELY

Beta-cell secretory dysfunction: a key cause of type 2 diabetes

Clinical features of patients with type 2 diabetes with and without Covid-19: a case control study (CoViDiab I)

Obesity is associated with severe forms of COVID-19

Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in new York City: prospective cohort study

COVID-19 severity is tripled in the diabetes community: a prospective analysis of the Pandemic's impact in type 1 and type 2 diabetes

Risks of and risk factors for COVID-19 disease in people with diabetes: a cohort study of the total population of Scotland

Glycemic characteristics and clinical outcomes of COVID-19 patients hospitalized in the United States

Risk factors for COVID-19-related mortality in hospitalized children and adolescents with diabetes mellitus: An observational retrospective cohort study