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Made available in DSpace on 2022-04-29T08:31:56Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-09-01 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Objectives: The majority of available scores to assess mortality risk of coronavirus disease 2019 (COVID-19) patients in the emergency department have high risk of bias. Therefore, this cohort aimed to develop and validate a score at hospital admission for predicting in-hospital mortality in COVID-19 patients and to compare this score with other existing ones. Methods: Consecutive patients (≥ 18 years) with confirmed COVID-19 admitted to the participating hospitals were included. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients admitted between March–July, 2020. The model was validated in the 1054 patients admitted during August–September, as well as in an external cohort of 474 Spanish patients. Results: Median (25–75th percentile) age of the model-derivation cohort was 60 (48–72) years, and in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. Seven significant variables were included in the risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein, SpO2/FiO2 ratio, platelet count, and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829–0.859), which was confirmed in the Brazilian (0.859 [95% CI 0.833–0.885]) and Spanish (0.894 [95% CI 0.870–0.919]) validation cohorts, and displayed better discrimination ability than other existing scores. It is implemented in a freely available online risk calculator (https://abc2sph.com/). Conclusions: An easy-to-use rapid scoring system based on characteristics of COVID-19 patients commonly available at hospital presentation was designed and validated for early stratification of in-hospital mortality risk of patients with COVID-19. Department of Internal Medicine Medical School Universidade Federal de Minas Gerais Telehealth Center University Hospital Universidade Federal de Minas Gerais Institute for Health Technology Assessment IATS/ CNPq)., Rua Ramiro Barcelos, 2359. Prédio 21 | Sala 507 Department of Statistics Universidade Federal de Minas Gerais Center for Research and Graduate Studies in Business Administration Universidade Federal de Minas Gerais Universidade Federal de São João del-Rei Infectious Diseases Department Vall d'Hebron University Hospita Universitat Autònoma de Barcelona Hospital Nossa Senhora da Conceição and Hospital Cristo Redentor Grupo Hospitalar Conceição Pontifícia Universidade Católica do Rio Grande do Sul RGS) Hospital São Lucas PUCRS Rede Mater Dei de Saúde Hospital Márcio Cunha Universidade do Sul de Santa Catarina UNISUL Dissertare Scientific Advice SOS Cardio Hospital Internal Medicine Department University Hospital Universidade Federal de Minas Gerais Faculdade de Medicina de Botucatu Universidade Estadual Paulista Júlio de Mesquita Filho Hospital das Clínicas da Faculdade de Medicina de Botucatu Universidade Federal do Rio Grande do Sul Hospital Bruno Born Research Center of Vale do Taquari. Hospital Mãe de Deus Hospital Universitário de Canoas Mucuri Medical School FAMMUC Universidade Federal dos Vales do Jequitinhonha e Mucuri – UFVJM Hospital Santa Rosalia Hospital Metropolitano Doutor Célio de Castro Hospital Moinhos de Vento Hospital Unimed BH Hospital Risoleta Tolentino Neves Post-graduation Center Medical School Universidade Federal de Minas Gerais Hospital Metropolitano Odilon Behrens Hospital Eduardo de Menezes Universidade FUMEC Hospital Julia Kubitschek Hospital Universitário de Santa Maria Departamento de Medicina Interna Universidade Federal de Santa Maria Hospital São João de Deus Hospital Regional Antônio Dias Faculdade Ciências Médicas de Minas Gerais Hospital de Clínicas de Porto Alegre Universidade Federal do Rio Grande do Sul Faculdade de Ciências Humanas de Curvelo Hospital João XXIII Av. Professor Alfredo Balena Hospital Santo Antônio Hospital Universitário Ciências Médicas Vall d'Hebron University Hospital PROSICS Barcelona Instituto René Rachou-FIOCRUZ Minas. Universidade Federal da Fronteira Sul Hospital Regional do Oeste Pontifícia Universidade Católica de Minas Gerais Hospital Tacchini Centro Universitário de Patos de Minas. RPatos de Minas Hospital Semper Hospital Santa Cruz Universidade de Santa Cruz Fundação Hospitalar do Estado de Minas Gerais – FHEMIG. Universidade Federal de Ouro Preto Hospital das Clínicas da Universidade Federal de Pernambuco Universidade Federal de Pernambuco Centro de Ciências Médicas Centro Universitário de Belo Horizonte UniBH) Erasmus MC University Medical Center Rotterdam Department of Cardiology Faculdade de Medicina de Botucatu Universidade Estadual Paulista Júlio de Mesquita Filho Hospital das Clínicas da Faculdade de Medicina de Botucatu

The COVID-19 pandemic caused unprecedented pressure over health care systems worldwide. Hospital-level data that may influence the prognosis in COVID-19 patients still needs to be better investigated. Therefore, this study analyzed regional socioeconomic, hospital, and intensive care units (ICU) characteristics associated with in-hospital mortality in COVID-19 patients admitted to Brazilian institutions. This multicenter retrospective cohort study is part of the Brazilian COVID-19 Registry. We enrolled patients ≥ 18 years old with laboratory-confirmed COVID-19 admitted to the participating hospitals from March to September 2020. Patients' data were obtained through hospital records. Hospitals' data were collected through forms filled in loco and through open national databases. Generalized linear mixed models with logit link function were used for pooling mortality and to assess the association between hospital characteristics and mortality estimates. We built two models, one tested general hospital characteristics while the other tested ICU characteristics. All analyses were adjusted for the proportion of high-risk patients at admission. Thirty-one hospitals were included. The mean number of beds was 320.4 ± 186.6. These hospitals had eligible 6556 COVID-19 admissions during the study period. Estimated in-hospital mortality ranged from 9.0 to 48.0%. The first model included all 31 hospitals and showed that a private source of funding (β = - 0.37; 95% CI - 0.71 to - 0.04; p = 0.029) and location in areas with a high gross domestic product (GDP) per capita (β = - 0.40; 95% CI - 0.72 to - 0.08; p = 0.014) were independently associated with a lower mortality. The second model included 23 hospitals and showed that hospitals with an ICU work shift composed of more than 50% of intensivists (β = - 0.59; 95% CI - 0.98 to - 0.20; p = 0.003) had lower mortality while hospitals with a higher proportion of less experienced medical professionals had higher mortality (β = 0.40; 95% CI 0.11-0.68; p = 0.006). The impact of those association increased according to the proportion of high-risk patients at admission. In-hospital mortality varied significantly among Brazilian hospitals. Private-funded hospitals and those located in municipalities with a high GDP had a lower mortality. When analyzing ICU-specific characteristics, hospitals with more experienced ICU teams had a reduced mortality.

Background: Assessing predictors of critical outcomes in COVID-19 may advise timely treatments and better prepare facilities to overcome extra adversities during pregnancy. However, many clinical parameters of existent scores are deeply modified by physiologic adaptations. Our aim was to assess the feasibility of a prognosis score developed for general hospitalized adults with COVID-19 in Brazil to predict clinical adverse outcomes in pregnant women upon hospital admission.Methods: This is a multicenter retrospective substudy of the Brazilian COVID-19 Registry, a multicenter cohort analysis in Brazilian hospitals, which provided an accurate score to predict in-hospital death. The present analysis assessed the performance of this model, ABC2-SPH, based on data of 3978 patients, to assess poor clinical outcomes in data from 85 pregnant women admitted due to COVID-19 from March 1, 2020, to May 5, 2021, in 19 Brazilian hospitals. The primary outcomes were death and the composite mechanical ventilation or death, and secondary were pregnancy outcomes and severe/critical Covid-19. The overall discrimination of the model was presented as the area under the receiver operating characteristic curve (AUROC).Results: Thirty-one (36.5%) pregnant women had critical or severe COVID-19. Most of them had no previous comorbidities (64.7%). The median gestational age was 31.0 (26.0, 36.2) weeks; 38 (44.7%) women gave birth during hospitalization by Covid-19, most of them by C-section (76.3%). The need for mechanical ventilation or death occurred in 14 (17.3%) pregnant women. Severe and critical COVID-19 in pregnant women was associated with diabetes, inflammatory markers, and abnormal vital signals observed at admission. The model was not able to identify adverse clinical outcomes. The AUROC of predicting severe/critical Covid-19 illness was 0.595 (95% CI: 0.424-0.754); AUROC of the inpatient death discrimination was 0.683 (95% CI: 0.293-0.945), as the AUROC of mechanical ventilation or death discrimination was 0.591 (95% CI: 0.434-0.75).Conclusions: The model ABC2-SPH developed in Brazilian general patients was not able to identify adverse clinical outcomes in pregnant women with COVID-19. We warn against the use of general inpatients COVID-19 prognosis in pregnant women. A more useful model for clinical prognosis is necessary concerning the specificities of pregnancy affected by COVID-19.

BackgroundIt is not clear whether previous thyroid diseases influence the course and outcomes of COVID-19. The study aims to compare clinical characteristics and outcomes of COVID-19 patients with and without hypothyroidism.MethodsThe study is a part of a multicentric cohort of patients with confirmed COVID-19 diagnosis, including data collected from 37 hospitals. Matching for age, sex, number of comorbidities and hospital was performed to select the patients without hypothyroidism for the paired analysis.ResultsFrom 7,762 COVID-19 patients, 526 had previously diagnosed hypothyroidism (50%) and 526 were selected as matched controls. The median age was 70 (interquartile range 59.0-80.0) years-old and 68.3% were females. The prevalence of underlying comorbidities were similar between groups, except for coronary and chronic kidney diseases, that had a higher prevalence in the hypothyroidism group (9.7% vs. 5.7%, p=0.015 and 9.9% vs. 4.8%, p=0.001, respectively). At hospital presentation, patients with hypothyroidism had a lower frequency of respiratory rate > 24 breaths per minute (36.1% vs 42.0%; p=0.050) and need of mechanical ventilation (4.0% vs 7.4%; p=0.016). D-dimer levels were slightly lower in hypothyroid patients (2.3 times higher than the reference value vs 2.9 times higher; p=0.037). In-hospital management was similar between groups, but hospital length-of-stay (8 vs 9 days; p=0.029) and mechanical ventilation requirement (25.4% vs. 33.1%; p=0.006) were lower for patients with hypothyroidism. There was a trend of lower in-hospital mortality in patients with hypothyroidism (22.1% vs. 27.0%; p=0.062).ConclusionIn this large Brazilian COVID-19 Registry, patients with hypothyroidism had a lower requirement of mechanical ventilation, and showed a trend of lower in-hospital mortality. Therefore, hypothyroidism does not seem to be associated with a worse prognosis, and should not be considered among the comorbidities that indicate a risk factor for COVID-19 severity.

IntroductionChildren and adolescents with Covid-19 have been shown lower mortality less intense symptoms when compared to adults, but studies in Brazil have been based on the compulsory notifying system only.ObjectiveTo analyse clinical, laboratory, radiological characteristics and outcomes of hospitalized patients under 20 years with Covid-19.MethodsCases series of hospitalized patients with confirmed Covid-19 under 20 years, obtained from a cohort study in 37 hospitals from five states of Brazil.ResultsFrom 36 patients, 20 (55.5%) were adolescentes, 20 (55.5%) were male, 18 (50.0%) had comorbidities, 2 were pregnant and in 7 (19.4%), initial symptoms occurred during hospitalization for other causes, of whom 3 were possibly infected in the hospital. Fever (61.1%), dyspnea (33.3%) and neurological symptoms (33.0%) were the most common complaints. C-reactive protein was higher than 50mg/L in 16.7% and D-dimer was above the reference limit in 22.2%. Chest X-rays were performed in 20 (55.5%) patients, 9 had abnormalities, and chest tomography in 5. Hospital length of stay ranged from 1-40 days (median 5 [interquartile range 3-10]), 16 (44.4%) needed intensive therapy, 6 (16.7%) required mechanical ventilation and one patient (2.8%) died.ConclusionIn case series patients under 20 years from hospitals from 5 states of Brazil, comorbidities were frequent, and most common symptoms were fever, dyspnea and neurological symptoms. Forty-four percent required intensive therapy, showing that the disease was not as mild as it was expected, and one patient died.

**Background:** The economic impact associated with the treatment strategies of coronavirus disease-2019 (COVID-19) patients by hospitals and health-care systems in Brazil is unknown and difficult to estimate. This research describes the investments made to absorb the demand for treatment and the changes in occupation rates and billing in Brazilian hospitals. **Methods:** This research covers the initial findings of “COVID-19 hospital costs and the proposition of a bundled reimbursement strategy for the health-care system,” which includes 10 hospitals. The chief financial officer, the chief medical officer, and hospital executives of each participating hospital provided information regarding investments attributed to COVID-19 patient treatment. The analysis included variations in occupation rates and billing from 2019 to 2020 observed in each institution, and the investments for medical equipment, individual protection materials and building construction per patient treated. **Results:** The majority of hospitals registered a decrease in hospitalization rates and revenue from 2019 to 2020. For intensive care units (ICUs), the mean occupancy rate ranged from 88% to 83%, and for wards, it ranged from 85% to 73%. Monthly average revenue decreased by 10%. The mean hospital investment per COVID-19 inpatient was I$6800 (standard deviation 7664), with the purchase of ventilators as the most common investment. For this item, the mean, highest and lowest acquisition cost per ventilator were, respectively, I$31 468, I$48 881 and I$17 777. **Conclusion:** There was significant variability in acquisition costs and investments by institution for responding to the COVID-19 pandemic. These findings highlight the importance of continuing microeconomic studies for a comprehensive assessment of hospital costs. Only with more detailed analyses, will it be possible to define and drive sustainable strategies to manage and reimburse COVID-19 treatment in health-care systems.

ObjectiveTo develop and validate a rapid scoring system at hospital admission for predicting in-hospital mortality in patients hospitalized with coronavirus disease 19 (COVID-19), and to compare this score with other existing ones.DesignCohort studySettingThe Brazilian COVID-19 Registry has been conducted in 36 Brazilian hospitals in 17 cities. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients that were admitted between March-July, 2020. The model was then validated in the 1054 patients admitted during August-September, as well as in an external cohort of 474 Spanish patients.ParticipantsConsecutive symptomatic patients (≥18 years old) with laboratory confirmed COVID-19 admitted to participating hospitals. Patients who were transferred between hospitals and in whom admission data from the first hospital or the last hospital were not available were excluded, as well those who were admitted for other reasons and developed COVID-19 symptoms during their stay.Main outcome measuresIn-hospital mortalityResultsMedian (25th-75th percentile) age of the model-derivation cohort was 60 (48-72) years, 53.8% were men, in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. From 20 potential predictors, seven significant variables were included in the in-hospital mortality risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein, SpO2/FiO2ratio, platelet count and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829 to 0.859), which was confirmed in the Brazilian (0.859) and Spanish (0.899) validation cohorts. Our ABC2-SPH score showed good calibration in both Brazilian cohorts, but, in the Spanish cohort, mortality was somewhat underestimated in patients with very high (>25%) risk. The ABC2-SPH score is implemented in a freely available online risk calculator (https://abc2sph.com/).ConclusionsWe designed and validated an easy-to-use rapid scoring system based on characteristics of COVID-19 patients commonly available at hospital presentation, for early stratification for in-hospital mortality risk of patients with COVID-19.Summary boxesWhat is already known on this topic?Rapid scoring systems may be very useful for fast and effective assessment of COVID-19 patients in the emergency department.The majority of available scores have high risk of bias and lack benefit to clinical decision making.Derivation and validation studies in low- and middle-income countries, including Latin America, are scarce.What this study addsABC2-SPH employs seven well defined variables, routinely assessed upon hospital presentation: age, number of comorbidities, blood urea nitrogen, C reactive protein, Spo2/FiO2 ratio, platelets and heart rate.This easy-to-use risk score identified four categories at increasing risk of death with a high level of accuracy, and displayed better discrimination ability than other existing scores.A free web-based calculator is available and may help healthcare practitioners to estimate the expected risk of mortality for patients at hospital presentation.

FUNDAMENTO: A ocorrencia de hiper-homocisteinemia parece ser frequente apos o transplante renal. Nenhum estudo ate o momento avaliou o papel da homocisteina (Hcy) associada a dislipidemia no Brasil. OBJETIVO: Determinar a prevalencia de hiper-homocisteinemia (Hcy serica >15 mmol/l) em pacientes estaveis submetidos a transplante renal e avaliar o papel dos lipidios sericos e da funcao do enxerto nos niveis de Hcy serica. METODOS: Cento e cinco pacientes estaveis submetidos a transplante renal foram avaliados, levando-se em consideracao idade, tempo pos-transplante, niveis sericos de colesterol, funcao do enxerto, proteinuria e uso de ciclosporina (analisados por regressao linear multipla). A prevalencia de hiper-homocisteinemia foi de 74,3%. Os pacientes foram divididos em dois grupos: hipercolesterolemicos (colesterol total > 200 mg/dl, colesterol LDL > 130 mg/dl) e normocolesterolemicos. RESULTADOS: Os pacientes hipercolesterolemicos eram mais velhos, tinham menor tempo pos-transplante, menor depuracao de creatinina endogena, maior proteinuria e niveis sericos mais elevados de Hcy. Os pacientes com hiper-homocisteinemia tinham niveis sericos de triglicerides significativamente mais elevados e funcao do enxerto significativamente pior; alem disso, seus niveis de colesterol LDL apresentaram tendencia a ser mais elevados. Houve uma correlacao positiva entre os niveis sericos de creatinina e de Hcy (r = 0,32; p = 0,01). A analise de regressao linear multipla revelou que tanto a dislipidemia quanto a funcao renal afetam de forma independente os valores de Hcy. CONCLUSAO: Observamos uma alta prevalencia de hiper-homocisteinemia em pacientes submetidos a transplante renal, especialmente em hipercolesterolemicos, sugerindo que uma pior funcao do enxerto pode influenciar negativamente os niveis sericos de Hcy e colesterol. Estudos futuros deverao investigar se esse perfil metabolico adverso esta associado com maior mortalidade cardiovascular no longo prazo.

Hyperhomocysteinemia seems to be frequent after renal transplantation. No study so far has assessed the role of homocysteine (Hcy) associated with dyslipidemia in Brazil.To determine the prevalence of hyperhomocysteinemia (serum Hcy15 mmol/l) in stable renal transplant recipients and to evaluate the role of serum lipids and graft function in serum Hcy levels.One hundred and five stable renal transplant recipients were evaluated, considering age, post-transplant time, cholesterol levels, graft function, proteinuria, and cyclosporine (analyzed using multiple linear regression). The prevalence of hyperhomocysteinemia was 74.3%. Patients were further divided into two groups, hyper (total cholesterol200 mg/dl, LDL-cholesterol130 mg/dl) and normocholesterolemic.Hypercholesterolemic recipients were older, had shorter post-transplant time, lower endogenous creatinine clearance, and higher proteinuria and Hcy serum levels. Patients with hyperhomocysteinemia had statistically significantly higher serum triglycerides and poorer graft function, and their LDL-cholesterol also tended to be higher. A positive correlation was found between serum creatinine and Hcy levels (r = 0.32, P = 0.01). Multiple regression analysis revealed that both dyslipidemia and renal function independently affect Hcy values.We observed a high prevalence of hyperhomocysteinemia in renal transplant recipients, especially in hypercholesterolemic, suggesting that worse graft function may influence serum Hcy and cholesterol levels negatively. Further studies should investigate if this adverse metabolic profile is associated with higher cardiovascular mortality in the long term.