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INTRODUCTION: The aim of this study was to assess the impact of aortic angulation (AA) on periprocedural and in-hospital complications as well as mortality of patients undergoing Evolut™ R valve implantation. METHODS: A retrospective study was conducted on 264 patients who underwent transfemoral-approach transcatheter aortic valve replacement with self-expandable valve at our hospital between August 2015 and August 2022. These patients underwent multislice computer tomography scans to evaluate AA. Transcatheter aortic valve replacement endpoints, device success, and clinical events were assessed according to the definitions provided by the Valve Academic Research Consortium-3. Cumulative events included paravalvular leak, permanent pacemaker implantation, new-onset stroke, and in-hospital mortality. Patients were divided into two groups, AA ≤ 48° and AA > 48°, based on the mean AA measurement (48.3±8.8) on multislice computer tomography. RESULTS: Multivariable logistic regression analysis was performed to identify predictors of cumulative events, utilizing variables with a P-value < 0.2 obtained from univariable logistic regression analysis, including AA, age, hypertension, chronic renal failure, and heart failure. AA (odds ratio [OR]: 1.73, 95% confidence interval [CI]: 0.89-3.38, P=0.104), age (OR: 1.04, 95% CI: 0.99-1.10, P=0.099), hypertension (OR: 1.66, 95% CI: 0.82-3.33, P=0.155), chronic renal failure (OR: 1.82, 95% CI: 0.92-3.61, P=0.084), and heart failure (OR: 0.57, 95% CI: 0.27-1.21, P=0.145) were not found to be significantly associated with cumulative events in the multivariable logistic regression analysis. CONCLUSION: This study demonstrated that increased AA does not have a significant impact on intraprocedural and periprocedural complications of patients with new generation self-expandable valves implanted.

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ABSTRACT Objective To identify factors associated with hospitalization in the intensive care unit in children and adolescents with COVID-19. Methods This was a retrospective cohort study using secondary data of hospitalized children and adolescents (zero to 18 years old) with COVID-19 reported in Paraíba from April 2020 to July 2021, totaling 486 records. Descriptive analysis, logistic regression and multilevel regression were performed, utilizing a significance level of 5%. Results According to logistic regression without hierarchical levels, there was an increased chance of admission to the intensive care unit for male patients (OR = 1.98; 95%CI 1.18 - 3.32), patients with respiratory distress (OR = 2.43; 95%CI 1.29 - 4.56), patients with dyspnea (OR = 3.57; 95%CI 1.77 - 7.18) and patients living in large cities (OR = 2.70; 95%CI 1.07 - 6.77). The likelihood of requiring intensive care was observed to decrease with increasing age (OR = 0.94; 95%CI = 0.90 - 0.97), the presence of cough (OR = 0.32; 95%CI 0.18 - 0.59) or fever (OR = 0.42; 95%CI 0.23 - 0.74) and increasing Gini index (OR = 0.003; 95%CI 0.000 - 0.243). According to the multilevel analysis, the odds of admission to the intensive care unit increased in male patients (OR = 1.70; 95%CI = 1.68-1.71) and with increasing population size of the municipality per 100,000 inhabitants (OR = 1.01; 95%CI 1.01-1.03); additionally, the odds of admission to the intensive care unit decreased for mixed-race versus non-brown-skinned patients (OR = 0.981; 95%CI 0.97 - 0.99) and increasing Gini index (OR = 0.02; 95%CI 0.02 - 0.02). Conclusion The effects of patient characteristics and social context on the need for intensive care in children and adolescents with SARS-CoV-2 infection were better estimated with the inclusion of a multilevel regression model.

RESUMO Objetivo Identificar fatores associados ao internamento na unidade de terapia intensiva de crianças e adolescentes com COVID-19. Método Estudo de coorte retrospectiva, com dados secundários, de crianças e adolescentes hospitalizados (zero a 18 anos), notificados com COVID-19 na Paraíba, de abril de 2020 a julho de 2021, totalizando 486 registros. Foram realizadas análise descritiva, regressão logística e regressão multinível, considerando o nível de significância de 5%. Resultados Na regressão logística sem níveis hierárquicos, ocorreu aumento da chance de internamento na unidade de terapia intensiva em pacientes do sexo masculino (RC = 1,98; IC95% 1,18 - 3,32), com desconforto respiratório (RC = 2,43; IC95% 1,29 - 4,56), dispneia (RC = 3,57; IC95% 1,77 - 7,18) e residentes em cidades com grande porte populacional (RC = 2,70; IC95% 1,07 - 6,77). Foi observada diminuição da chance de cuidados intensivos com aumento da idade em anos (RC = 0,94; IC95%=0,90 - 0,97), presença de tosse (RC = 0,32; IC95% 0,18 - 0,59), febre (RC = 0,42; IC95% 0,23 - 0,74) e aumento no Índice de Gini (RC = 0,003; IC95% 0,000 - 0,243). Na análise multinível, a chance de internamento na unidade de terapia intensiva aumentou no sexo masculino (RC = 1,70; IC95%=1,68-1,71) e por conta do aumento no porte populacional do município a cada 100 mil habitantes (RC = 1,01; IC95% 1,01 - 1,03); a chance de internamento na unidade de terapia intensiva diminuiu em pacientes pardos versus não pardos (RC = 0,981; IC95% 0,97 - 0,99) e por conta do aumento a cada pontuação do Índice de Gini (RC = 0,02; IC95% 0,02 - 0,02). Conclusão Os efeitos das condições próprias do paciente e do contexto social na necessidade de cuidados intensivos em crianças e adolescentes com infecção pelo SARS-CoV-2 são mais bem estimados com a inclusão de um modelo de regressão multinível nas análises.

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ABSTRACT Introduction: The aim of this study was to assess the impact of aortic angulation (AA) on periprocedural and in-hospital complications as well as mortality of patients undergoing Evolut™ R valve implantation. Methods: A retrospective study was conducted on 264 patients who underwent transfemoral-approach transcatheter aortic valve replacement with self-expandable valve at our hospital between August 2015 and August 2022. These patients underwent multislice computer tomography scans to evaluate AA. Transcatheter aortic valve replacement endpoints, device success, and clinical events were assessed according to the definitions provided by the Valve Academic Research Consortium-3. Cumulative events included paravalvular leak, permanent pacemaker implantation, new-onset stroke, and in-hospital mortality. Patients were divided into two groups, AA ≤ 48° and AA > 48°, based on the mean AA measurement (48.3±8.8) on multislice computer tomography. Results: Multivariable logistic regression analysis was performed to identify predictors of cumulative events, utilizing variables with a P-value < 0.2 obtained from univariable logistic regression analysis, including AA, age, hypertension, chronic renal failure, and heart failure. AA (odds ratio [OR]: 1.73, 95% confidence interval [CI]: 0.89-3.38, P=0.104), age (OR: 1.04, 95% CI: 0.99-1.10, P=0.099), hypertension (OR: 1.66, 95% CI: 0.82-3.33, P=0.155), chronic renal failure (OR: 1.82, 95% CI: 0.92-3.61, P=0.084), and heart failure (OR: 0.57, 95% CI: 0.27-1.21, P=0.145) were not found to be significantly associated with cumulative events in the multivariable logistic regression analysis. Conclusion: This study demonstrated that increased AA does not have a significant impact on intraprocedural and periprocedural complications of patients with new generation self-expandable valves implanted.

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BACKGROUND: Cross-sectional studies are useful for the estimation of prevalence of a particular event with concerns in specific populations, as in the case of diseases or other public health interests. Most of these studies have been carried out with binary binomial logistic regression model which estimates OR values that could be overestimated due to the adjustment of the model. Thus, the selection of the best multivariate model for cross-sectional studies is a priority to control the overestimation of the associations. METHODS: We compared the precision of the estimates of the prevalence ratio (PR) of the negative Log-binomial model (NLB) with Mantel-Haenszel (MH) and the regression models Cox, Log-Poisson, Log-binomial, and the OR of the binary logistic regression in population-based cross-sectional studies. The prevalence from a previous cross-sectional study carried out in Colombia about the association of mental health disorders with the consumption of psychoactive substances (e.g., cocaine, marijuana, cigarette, alcohol and risk of consumption of psychoactive substances) were used. The precision of the point estimates of the PR was evaluated for the NLB model with robust variance estimates, controlled with confounding variables, and confidence interval of 95%. RESULTS: The NLB model adjusted with robust variance showed accuracy in the measurements of crude PRs, standard errors of estimate and its corresponding confidence intervals (95%CI) as well as a high precision of the PR estimate and standard errors of estimate after the adjustment of the model by grouped age compared with the MH PR estimate. Obtained PRs and 95%CI entre NLB y MH were: cocaine consumption (2.931,IC95%: 0.723-11.889 vs. 2.913, IC95%: 0.786-12.845), marijuana consumption (3.444, IC95%: 1.856-6.391 vs. 3.407, IC95%: 1.848, 6.281), cigarette smoking (2.175,IC95%: 1.493, 3.167 vs. 2.209, IC95%: 1.518-3.214), alcohol consumption (1.243,IC95%: 1.158-1.334 vs. 1.241, IC95%: 1.157-1.332), and risk of consumption of psychoactive substances (1.086, IC95%: 1.047-1.127 vs. 1.086, IC95%: 1.047, 1.126). The NLB model adjusted with robust variance showed mayor precision when increasing the prevalence, then the other models with robust variance with respect to MH. CONCLUSIONS: The NLB model with robust variance was shown as a powerful strategy for the estimation of PRs for cross-sectional population-based studies, as high precision levels were identified for point estimators, standard errors of estimate and its corresponding confidence intervals, after the adjustment of confounding variables. In addition, it does not represent convergence issues for high prevalence cases (as it occur with the Log-binomial model) and could be considered in cases of overdispersion and with greater precision and goodness of fit than the other models with robust variance, as it was shown with the data set of the cross-sectional study used in here.

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Response surface methodology (RSM) consists of mathematical and statistical techniques to develop models which help to understand the influence of various factors on a dependent variable of interest. The feasibility of RSM use to detect cases of periodontitis and its correlated factors has not yet been evaluated. This study developed mathematical models for periodontitis diagnosis independent of periodontal probing using the RSM. Demographic, socioeconomic, behavioral, systemic, local factors, and periodontitis were assessed in 176 volunteers. Periodontitis case was defined according to three different definitions: 1) ≥3 sites with clinical attachment level (CAL) ≥4 mm; 2) at least one site with CAL ≥4 mm and bleeding on probing; 3) ≥2 proximal sites with CAL ≥3 mm and ≥2 proximal sites with probing depth (PD) ≥4 mm (not on the same tooth) OR 1 site with PD ≥5 mm. 4th-degree polynomial equations showed high coefficients of determination (R²= 1) and were used to represent the mathematical models of periodontitis cases. According to definition 1, the diagnosis of periodontitis was accurate by including in the model: age, sex, education level, plaque index (PI), number of missing teeth, previous hygiene instructions, and body mass index (BMI). According to definition 2, the diagnosis of periodontitis was accurate by including in the model: age, sex, education level, income, PI, previous oral hygiene instructions, frequency of brushing and type of toothbrush, and use of mouthwash in the model. For an accurate diagnosis of periodontitis according to definition 3, the model included: age, education level, IP, number of missing teeth, previous oral hygiene instruction, BMI, and diabetes. The multifactorial mathematical models were able to diagnosis periodontitis according to different periodontitis case definitions using only variables of easy evaluation and non-invasive. (AU)

A metodologia de superfície de resposta (MSR) consiste em técnicas matemáticas e estatísticas para desenvolver modelos que ajudam a entender a influência de vários fatores em uma variável dependente de interesse. A viabilidade do uso da MSR para detectar casos de periodontite e seus fatores correlacionados ainda não foi avaliada. Este estudo desenvolveu modelos matemáticos para diagnóstico de periodontite independente da sondagem periodontal usando a MSR. Fatores demográficos, socioeconômicos, comportamentais, sistêmicos, locais e periodontite foram avaliados em 176 voluntários. O caso de periodontite foi definido de acordo com três definições diferentes: 1) ≥3 locais com nível de inserção clínica (NIC) ≥4 mm; 2) Um local com NIC ≥4 mm e sangramento à sondagem; 3) ≥2 locais proximais com NIC ≥3 mm e ≥2 locais proximais com profundidade de sondagem (PS) ≥4 mm (não no mesmo dente) OU 1 local com PS ≥5 mm. Equações polinomiais de 4º grau apresentaram altos coeficientes de determinação (R²= 1) e foram utilizadas para representar os modelos matemáticos dos casos de periodontite. De acordo com a definição 1, o diagnóstico de periodontite foi preciso ao incluir no modelo: idade, sexo, escolaridade, índice de placa (IP), número de dentes perdidos, instruções de higiene anteriores e índice de massa corporal (IMC). De acordo com a definição 2, o diagnóstico de periodontite foi preciso ao incluir no modelo: idade, sexo, escolaridade, renda, IP, instruções prévias de higiene bucal, frequência de escovação e tipo de escova dental e uso de enxaguatório bucal no modelo. Para um diagnóstico preciso de periodontite de acordo com a definição 3, o modelo incluiu: idade, escolaridade, IP, número de dentes perdidos, instrução prévia de higiene oral, IMC e diabetes. Os modelos matemáticos multifatoriais foram capazes de diagnosticar a periodontite de acordo com diferentes definições de casos de periodontite usando apenas variáveis de fácil avaliação e não invasivas. (AU)

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Estimar a prevalência de diabetes mellitus e os fatores associados em adultos. Trata-se de um inquérito realizado com 1.637 indivíduos nas zonas urbana e rural do município de Rio Branco, Acre. Diabetes foi definido pela presença de glicemia no plasma em jejum ≥ 126 mg/dl ou utilização de hipoglicemiante oral ou insulina. Medidas de associação foram estimadas por regressão logística hierarquizada. A prevalência de diabetes foi de 6,5% (n = 202). Após análise, a chance de ser diabético esteve independente e positivamente associada a idade ≥ 60 anos (OR: 6,67; IC95%: 1,83-24,30); história familiar de diabetes mellitus (OR: 2,88; IC95%: 1,43-5,81); circunferência da cintura aumentada (OR: 1,83; IC95%:1,01-3,33); dislipidemia (OR: 2,95; IC95%: 1,34-6,49); anemia (OR: 3,15; IC95%: 1,30-7,60); e doença renal crônica (DRC) (OR: 4,00; IC95%: 1,70-9,33). Foi detectada uma prevalência de 6,5%, estando o diabetes associado com idade, história familiar, anemia e DRC. Indica-se a necessidade do adequado rastreio de comorbidades nesses pacientes.

To estimate the prevalence of diabetes mellitus and associated factors in adults.Survey carried out with 1,637 individuals in urban and rural areas of the municipality of Rio Branco, state of Acre. Diabetes was defined by the presence of fasting plasma glucose ≥ 126 mg/dl or the use of oral hypoglycemic agents or insulin. Association measures were estimated by hierarchical logistic regression.The prevalence of diabetes was 6.5% (n = 202). After analysis, the chance of being diabetic was independently and positively associated with age ≥ 60 years (OR: 6.67; 95%CI: 1.83-24.30); family history of diabetes mellitus (OR: 2.88; 95%CI: 1.43-5.81); increased waist circumference (OR: 1.83; 95%CI: 1.01-3.33); dyslipidemia (OR: 2.95; 95%CI: 1.34-6.49); anemia (OR: 3.15; 95%CI: 1.30-7.60); and chronic kidney disease (CKD) (OR: 4.00; 95%CI: 1.70-9.33). A prevalence of 6.5% was detected, with diabetes associated with age, family history, anemia, and CKD. The need for adequate screening of comorbidities in these patients is indicated.

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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.

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ABSTRACT Objective: To analyze the factors associated with loss to follow-up in tuberculosis cases among adults in Brazil in 2020 and 2021. Method: Retrospective cohort with secondary data from the Brazilian Notifiable Diseases Information System. A total of 24,344 people diagnosed with tuberculosis whose information was complete in the database were included. Adjusted odds ratios and confidence intervals were estimated by binary logistic regression. Results: Higher odds of loss to follow-up were observed for males, non-white ethnicity/color, with lower education level, homeless or deprived of liberty, who used drugs, alcohol and/or tobacco, with admission due to recurrence or re-entry after abandonment, and with unknown or positive serology for HIV. On the other hand, older age, extrapulmonary tuberculosis, deprivation of libertyand supervised treatment were associated with lower odds of loss to follow-up. Conclusion: Demographic, socioeconomic and clinical-epidemiological factors were associated with the loss to follow-up in tuberculosis cases, which reiterates the various vulnerabilities intertwined with the illness and treatment of this disease. Therefore, there is a need to promote strategies aimed at adherence and linkage to the care for groups most vulnerable to loss to follow-up in tuberculosis treatment in Brazil.

RESUMEN Objetivo: Analizar los factores asociados a la pérdida de seguimiento de los casos de tuberculosis entre adultos en Brasil en 2020 y 2021. Método: Cohorte retrospectiva con datos secundarios del Sistema de Información de Enfermedades de Declaración Obligatoria de Brasil. Se incluyeron un total de 24.344 personas diagnosticadas con tuberculosis cuya información estaba completa en la base de datos. Las razones de probabilidad ajustadas y los intervalos de confianza se estimaron mediante regresión logística binaria. Resultados: Se observaron mayores posibilidades de perder el seguimiento para el sexo masculino, de etnia/color no blanco, con baja escolaridad, sin hogar, que usaban drogas, alcohol y/o tabaco, con ingreso por recidiva o reingreso tras abandono, y con serología desconocida o positiva para VIH. Por otro lado, la edad avanzada, la forma extrapulmonar de tuberculosis, la privación de libertad y el tratamiento supervisado se asociaron con menores probabilidades. Conclusión: Factores demográficos, socioeconómicos y clínico-epidemiológicos se asociaron a la pérdida del seguimiento de los casos de tuberculosis, lo que reitera las diversas vulnerabilidades entrelazadas con la enfermedad y el tratamiento de esta enfermedad. Por lo tanto, existe la necesidad de promover estrategias dirigidas a la adherencia y la vinculación a la atención de los grupos más vulnerables a la pérdida del tratamiento de seguimiento de la tuberculosis en Brasil.

RESUMO Objetivo: Analisar os fatores associados à perda de seguimento dos casos de tuberculose entre adultos no Brasil em 2020 e 2021. Método: Coorte retrospectiva com dados secundários provenientes do Sistema de Informação de Agravos de Notificação do Brasil. Foram incluídas 24.344 pessoas diagnosticadas com tuberculose cujas informações estavam completas no banco de dados. Razões de chances ajustadas eintervalos de confiança foram estimados por regressão logística binária. Resultados: Observaram-se maiores chances de perda de seguimento para pessoas do sexo masculino, deetnia/cor não branca, combaixa escolaridade, em situação de rua, que faziamuso de drogas, álcool e/outabaco, com entrada porrecorrênciaou reingressoapós abandono, e com sorologia desconhecida oupositiva para HIV. Por outro lado, a idade mais avançada, a forma extrapulmonar da tuberculose, a privação de liberdade eo tratamento supervisionado associaram-se a menores chances. Conclusão: Fatores demográficos, socioeconômicos e clínico-epidemiológicos estiveram associadosà perda de seguimento dos casos de tuberculose, o que reitera as diversas vulnerabilidades imbricadas ao adoecimento e ao tratamento dessa doença. Portanto, constata-se a necessidade depromoção de estratégias que visem à adesão e à vinculação ao cuidado dos grupos mais vulneráveis à perda de seguimento do tratamento para tuberculoseno Brasil.

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Introducción: La malaria es una de las enfermedades infecciosas más importantes y para tratarla además de medicamentos, la población emplea plantas medicinales. El objetivo fue establecer los factores asociados a malaria y las plantas empleadas para su tratamiento en habitantes de Corozal. Método: Se aplicó una encuesta con preguntas sociodemográficas, de la vivienda, de conocimiento y de actitudes y las plantas medicinales empleadas para tratarla. Resultados: El 48% emplean plantas medicinales solas o con medicamentos, siendo el Gliricidia sepium (matarratón) y el Acmella oppositifolia (yuyo) las plantas más empleadas. En el 48% de las casas ha habido malaria. Por regresión logística se estableció que la malaria se asoció con conocer cómo se adquiere, consultar al médico tradicional y tener más de 15 años en Corozal. Conclusiones: Las plantas que la población de este estudio reportan no muestran evidencia científica como antimalaricos. Es importante una mayor presencia de las autoridades de salud y su trabajo conjunto con el médico tradicional para lograr estrategias más efectivas(AU)

Introduction: Malaria is one of the most important infectious disease and to treat it in addition to medicines the population uses medicinal plants. The objective was to establish the factors associated with malaria and the plants used for its treatment in inhabitants of Corozal. Method: A survey was applied with sociodemographic questions about housing, knowledge and attitudes, in addition to the medicinal plants used to treat it. Results: 48% use medicinal plants alone or with medicines, Gliricidia sepium (rat poisson) and Acmella oppositifolia (Opposite-leaf Spotflower) are the most used. In 48% of the homes there has been malaria. By logistic regression it was established that malaria was associated with knowing how it is acquired, consulting the traditional doctor and living in Corozal for more than 15 years. Conclusions: The plants that the population of this study report usimg do not show scientific evidence antimalarials. A greater presence of health authorities and their joint work with the traditional doctor for more effective strategies is important(AU)

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BACKGROUND: In 2016, a Peace Agreement, explicitly addressing the right to food, was signed, marking the end of more than 50 years of armed conflict and the longest war in the Americas. The expectation was that the years to follow would be marked by rapid social and political change, with the potential to improve food security. OBJECTIVES: (i) Ascertain changes in the prevalence of food insecurity in Colombia between 2016 and 2019; (ii) examine which population subgroups (eg, urban women, rural women, urban men, and rural men) were most vulnerable; and (iii) determine significant individual-level factors predicting food insecurity in these 2 years. METHODS: This study used the Gallup World Poll 2016 and 2019 nationally representative samples of Colombian adults aged 15 and older for the analyses (n ≈ 1000 per year). Food insecurity was measured using the Food Insecurity Experience Scale. Descriptive statistics and logistic regression analyses were conducted using IBM SPSS Complex Samples (version 26). RESULTS: Food insecurity in Colombia increased by 7 percentage points between 2016 and 2019 (from 33% to 40%); women living in rural areas in 2019 reported the highest prevalence (50%). Results from logistic analysis confirm low income, unemployment, and lack of social support were significant predictors of food insecurity in both years. In 2019, gender, low education, and lack of autonomy were also significant predictors. Further research on the determinants of food insecurity is necessary to inform Colombian policies and programs that address food insecurity. The urgency to act is more apparent than ever, given the country's worsening food security profile.

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