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2.
Rev. salud pública ; 22(1): e185989, ene.-feb. 2020. tab, graf
Artículo en Español | LILACS (Américas) | ID: covidwho-864697

RESUMEN

RESUMEN Objetivo Este estudio tiene como primer objetivo: realizar predicciones del curso de la infección en el horizonte temporal desde marzo 18 a abril 18 del 2020, según diferentes medidas de aislamiento aplicadas. Las predicciones incluyen, población total contagiada, mortalidad y necesidad de recursos hospitalarios. Segundo objetivo: modelar la mortalidad y la necesidad de recursos hospitalarios, estratificando por edad el escenario de contagio del 70% de la población. Métodos Para el primer objetivo, nos basamos en el número de casos confirmados en el país hasta marzo 18, 2020 (n=93). Como suposiciones para el modelo, incluimos un índice de contagio R0=2,5 y el índice de casos reales por cada caso confirmado. Para la proporción de pacientes que necesitarían cuidados intensivos u otros cuidados intrahospitalarios, nos basamos en datos aportados por el Imperial College of London. Para el segundo objetivo usamos como tasa de mortalidad por edad, datos aportados por el Instituto Superiore di Sanità en Italia. Resultados Basándonos en los 93 casos reportados al 18 de marzo, si no se aplicase ninguna medida de mitigación, para el 18 de abril el país tendría un total de 613 037 casos. Medidas de mitigación que reduzcan el R0 en un 10%, generan una reducción del 50% del número de casos. Sin embargo, a pesar de reducirse los casos a la mitad, todavía habría un déficit en el número de camas requeridas y sólo uno de cada dos pacientes tendría acceso a dicho recurso. Conclusión En nuestro modelo encontramos que las medidas de mitigación que han sido implementadas hasta la fecha por el gobierno colombiano, se fundamentan en evidencia suficiente para pensar que es posible reducir significativamente el número de casos contagiados y con esto, el número de pacientes que requerirán manejo hospitalario.(AU)


ABSTRACT Introduction First case of COVID-19 in Colombia was diagnosed on March 6th. Two weeks later, cases have rapidly increased, leading the government to establish some mitigation measures. Objectives The first objective is to estimate and model the number of cases, use of hospital resources and mortality by using different R0 scenarios in a 1-month scenario (from March 18 to April 18, 2020), based on the different isolation measures applied. This work also aims to model, without establishing a time horizon, the same outcomes given the assumption that eventually 70% of the population will be infected. Materials and Methods Data on the number of confirmed cases in the country as of March 18, 2020 (n=93) were taken as the basis for the achievement of the first objective. An initial transmission rate of R0= 2.5 and a factor of 27 for undetected infections per each confirmed case were taken as assumptions for the model. The proportion of patients who may need intensive care or other in-hospital care was based on data from the Imperial College of London. On the other hand, an age-specific mortality rate provided by the Instituto Superiore di Sanità in Italy was used for the second objective. Results Based on the 93 cases reported as of March 18, if no mitigation measures were applied, by April 18, the country would have 613 037 cases. Mitigation measures that reduce R0 by 10% generate a 50% reduction in the number of cases. However, despite halving the number of cases, there would still be a shortfall in the number of beds required and only one in two patients would have access to this resource. Conclusion This model found that the mitigation measures implemented to date by the Colombian government and analyzed in this article are based on sufficient evidence and will help to slow the spread of SARS-CoV-2 in Colombia. Although a time horizon of one month was used for this model, it is plausible to believe that, if the current measures are sustained, the mitigation effect will also be sustained over time.(AU)


Asunto(s)
Humanos , Cuarentena/organización & administración , Infecciones por Coronavirus/mortalidad , Infecciones por Coronavirus/epidemiología , Prevención y Mitigación , Hospitales/provisión & distribución , Colombia/epidemiología
4.
Diabetes Care ; 43(10): 2339-2344, 2020 10.
Artículo en Inglés | MEDLINE | ID: covidwho-842772

RESUMEN

OBJECTIVE: To examine whether HbA1c, outpatient diabetes treatment regimen, demographics, and clinical characteristics are associated with mortality in hospitalized patients with diabetes and coronavirus disease 2019 (COVID-19). RESEARCH DESIGN AND METHODS: This was a retrospective cohort analysis of patients with diabetes hospitalized with confirmed COVID-19 infection from 11 March to 7 May 2020 at a large academic medical center in New York City. Multivariate modeling was used to assess the independent association of HbA1c levels and outpatient diabetes treatment regimen with mortality, in addition to independent effects of demographic and clinical characteristics. RESULTS: We included 1,126 hospitalized patients with diabetes and COVID-19 for analysis, among whom mean age was 68 years, 50% were male, 75% were Black, mean BMI was 30 kg/m2, 98% had type 2 diabetes, mean HbA1c was 7.5%, and 33.1% died. HbA1c levels were not associated with mortality in unadjusted or adjusted analyses, but an outpatient regimen with any insulin treatment was strongly predictive. Additionally, age, sex, and BMI interacted such that in all age categories, mortality was higher with increasing BMI in males compared with females. CONCLUSIONS: In this large U.S. cohort of hospitalized patients with diabetes and COVID-19, insulin treatment, as a possible proxy for diabetes duration, and obesity rather than long-term glycemic control were predictive of mortality. Further investigation of underlying mechanisms of mortality and inpatient glycemic control is needed.


Asunto(s)
Betacoronavirus , Infecciones por Coronavirus/mortalidad , Diabetes Mellitus Tipo 2/complicaciones , Neumonía Viral/mortalidad , Anciano , Anciano de 80 o más Años , Glucemia , Comorbilidad , Infecciones por Coronavirus/complicaciones , Femenino , Humanos , Pacientes Internos , Masculino , Obesidad/complicaciones , Pandemias , Neumonía Viral/complicaciones , Estudios Retrospectivos , Factores de Riesgo
5.
Biomed Res Int ; 2020: 2138387, 2020.
Artículo en Inglés | MEDLINE | ID: covidwho-841100

RESUMEN

Coronavirus disease 2019 (COVID-19) has caused considerable morbidity and mortality worldwide since December 2019. This retrospective study determined the characteristics and prognostic factors of COVID-19 patients, focusing on inpatients who died or were discharged between 30 December 2019 and 29 February 2020 at Renmin Hospital of Wuhan University. Patients' medical histories, comorbidities, symptoms, signs, laboratory findings, computed tomography (CT) findings, and clinical management were recorded. All 293 patients were divided into the nonsurviving (n = 116) and surviving (n = 177) groups. The median age was older in the nonsurviving group than in the surviving group; most patients were older than 65 years in the nonsurviving group. The incidence rates of lymphopenia, neutrophilia, and leukocytosis were significantly higher in the nonsurviving group than in the surviving group. More patients in the nonsurviving group had increased levels of nonspecific infection markers, abnormal liver and kidney function, cardiac injury, and blood coagulation abnormalities on admission. Immune and inflammatory responses were more severely disturbed in the nonsurviving group than in the surviving group. The incidence rates of complications during hospitalization were higher in the nonsurviving group than in the surviving group. Cox regression results also showed that older age, symptoms of dyspnea, comorbidities, and complications were all predictors of death. Close monitoring and timely treatment are needed for high-risk COVID-19 patients.


Asunto(s)
Infecciones por Coronavirus/etiología , Neumonía Viral/etiología , Adulto , Anciano , Anciano de 80 o más Años , Betacoronavirus , China/epidemiología , Técnicas de Laboratorio Clínico , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/tratamiento farmacológico , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/mortalidad , Femenino , Mortalidad Hospitalaria , Humanos , Pacientes Internos , Masculino , Persona de Mediana Edad , Pandemias , Alta del Paciente , Neumonía Viral/epidemiología , Neumonía Viral/mortalidad , Pronóstico , Estudios Retrospectivos
6.
BMC Infect Dis ; 20(1): 744, 2020 Oct 09.
Artículo en Inglés | MEDLINE | ID: covidwho-840886

RESUMEN

BACKGROUND: The triple burden of COVID-19, tuberculosis and human immunodeficiency virus is one of the major global health challenges of the twenty-first century. In high burden HIV/TB countries, the spread of COVID-19 among people living with HIV is a well-founded concern. A thorough understanding of HIV/TB and COVID-19 pandemics is important as the three diseases interact. This may clarify HIV/TB/COVID-19 as a newly related field. However, several gaps remain in the knowledge of the burden of COVID-19 on patients with TB and HIV. This study was conducted to review different studies on SARS-CoV, MERS-CoV or COVID-19 associated with HIV/TB co-infection or only TB, to understand the interactions between HIV, TB and COVID-19 and its implications on the burden of the COVID-19 among HIV/TB co-infected or TB patients, screening algorithm and clinical management. METHODS: We conducted an electronic search of potentially eligible studies published in English in the Cochrane Controlled Register of Trials, PubMed, Medrxiv, Google scholar and Clinical Trials Registry databases. We included case studies, case series and observational studies published between January, 2002 and July, 2020 in which SARS-CoV, MERS-CoV and COVID-19 co-infected to HIV/TB or TB in adults. We screened titles, abstracts and full articles for eligibility. Descriptive and meta-analysis were done and results have been presented in graphs and tables. RESULTS: After removing 95 duplicates, 58 out of 437 articles were assessed for eligibility, of which 14 studies were included for descriptive analysis and seven studies were included in the meta-analysis. Compared to the descriptive analysis, the meta-analysis showed strong evidence that current TB exposure was high-risk COVID-19 group (OR 1.67, 95% CI 1.06-2.65, P = 0.03). The pooled of COVID-19/TB severity rate increased from OR 4.50 (95% CI 1.12-18.10, P = 0.03), the recovery rate was high among COVID-19 compared to COVID-19/TB irrespective of HIV status (OR 2.23, 95% CI 1.83-2.74, P < 0.001) and the mortality was reduced among non-TB group (P < 0.001). CONCLUSION: In summary, TB was a risk factor for COVID-19 both in terms of severity and mortality irrespective of HIV status. Structured diagnostic algorithms and clinical management are suggested to improve COVID-19/HIV/TB or COVID-19/TB co-infections outcomes.


Asunto(s)
Coinfección/epidemiología , Infecciones por Coronavirus/epidemiología , Salud Global/estadística & datos numéricos , Infecciones por VIH/epidemiología , Neumonía Viral/epidemiología , Tuberculosis/epidemiología , Betacoronavirus , Infecciones por Coronavirus/mortalidad , Humanos , Pandemias , Neumonía Viral/mortalidad , Prevalencia , Sistema de Registros , Factores de Riesgo
7.
J Clin Invest ; 130(9): 4791-4797, 2020 09 01.
Artículo en Inglés | MEDLINE | ID: covidwho-840726

RESUMEN

BACKGROUNDConvalescent plasma is the only antibody-based therapy currently available for patients with coronavirus disease 2019 (COVID-19). It has robust historical precedence and sound biological plausibility. Although promising, convalescent plasma has not yet been shown to be safe as a treatment for COVID-19.METHODSThus, we analyzed key safety metrics after transfusion of ABO-compatible human COVID-19 convalescent plasma in 5000 hospitalized adults with severe or life-threatening COVID-19, with 66% in the intensive care unit, as part of the US FDA expanded access program for COVID-19 convalescent plasma.RESULTSThe incidence of all serious adverse events (SAEs), including mortality rate (0.3%), in the first 4 hours after transfusion was <1%. Of the 36 reported SAEs, there were 25 reported incidences of related SAEs, including mortality (n = 4), transfusion-associated circulatory overload (n = 7), transfusion-related acute lung injury (n = 11), and severe allergic transfusion reactions (n = 3). However, only 2 of 36 SAEs were judged as definitely related to the convalescent plasma transfusion by the treating physician. The 7-day mortality rate was 14.9%.CONCLUSIONGiven the deadly nature of COVID-19 and the large population of critically ill patients included in these analyses, the mortality rate does not appear excessive. These early indicators suggest that transfusion of convalescent plasma is safe in hospitalized patients with COVID-19.TRIAL REGISTRATIONClinicalTrials.gov NCT04338360.FUNDINGMayo Clinic, Biomedical Advanced Research and Development Authority (75A50120C00096), National Center for Advancing Translational Sciences (UL1TR002377), National Heart, Lung, and Blood Institute (5R35HL139854 and R01 HL059842), National Institute of Diabetes and Digestive and Kidney Diseases (5T32DK07352), Natural Sciences and Engineering Research Council of Canada (PDF-532926-2019), National Institute of Allergy and Infectious Disease (R21 AI145356, R21 AI152318, and AI152078), Schwab Charitable Fund, United Health Group, National Basketball Association, Millennium Pharmaceuticals, and Octapharma USA Inc.


Asunto(s)
Betacoronavirus , Infecciones por Coronavirus/terapia , Neumonía Viral/terapia , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Ensayos de Uso Compasivo , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/mortalidad , Femenino , Humanos , Inmunización Pasiva/efectos adversos , Inmunización Pasiva/mortalidad , Masculino , Persona de Mediana Edad , Pandemias , Neumonía Viral/epidemiología , Seguridad , Reacción a la Transfusión/epidemiología , Reacción a la Transfusión/etiología , Lesión Pulmonar Aguda Postransfusional/epidemiología , Lesión Pulmonar Aguda Postransfusional/etiología , Estados Unidos/epidemiología , United States Food and Drug Administration , Adulto Joven
8.
Rev. salud pública ; 22(1): e185989, ene.-feb. 2020. tab, graf
Artículo en Español | LILACS (Américas) | ID: covidwho-825606

RESUMEN

RESUMEN Objetivo Este estudio tiene como primer objetivo: realizar predicciones del curso de la infección en el horizonte temporal desde marzo 18 a abril 18 del 2020, según diferentes medidas de aislamiento aplicadas. Las predicciones incluyen, población total contagiada, mortalidad y necesidad de recursos hospitalarios. Segundo objetivo: modelar la mortalidad y la necesidad de recursos hospitalarios, estratificando por edad el escenario de contagio del 70% de la población. Métodos Para el primer objetivo, nos basamos en el número de casos confirmados en el país hasta marzo 18, 2020 (n=93). Como suposiciones para el modelo, incluimos un índice de contagio R0=2,5 y el índice de casos reales por cada caso confirmado. Para la proporción de pacientes que necesitarían cuidados intensivos u otros cuidados intrahospitalarios, nos basamos en datos aportados por el Imperial College of London. Para el segundo objetivo usamos como tasa de mortalidad por edad, datos aportados por el Instituto Superiore di Sanità en Italia. Resultados Basándonos en los 93 casos reportados al 18 de marzo, si no se aplicase ninguna medida de mitigación, para el 18 de abril el país tendría un total de 613 037 casos. Medidas de mitigación que reduzcan el R0 en un 10%, generan una reducción del 50% del número de casos. Sin embargo, a pesar de reducirse los casos a la mitad, todavía habría un déficit en el número de camas requeridas y sólo uno de cada dos pacientes tendría acceso a dicho recurso. Conclusión En nuestro modelo encontramos que las medidas de mitigación que han sido implementadas hasta la fecha por el gobierno colombiano, se fundamentan en evidencia suficiente para pensar que es posible reducir significativamente el número de casos contagiados y con esto, el número de pacientes que requerirán manejo hospitalario.(AU)


ABSTRACT Introduction First case of COVID-19 in Colombia was diagnosed on March 6th. Two weeks later, cases have rapidly increased, leading the government to establish some mitigation measures. Objectives The first objective is to estimate and model the number of cases, use of hospital resources and mortality by using different R0 scenarios in a 1-month scenario (from March 18 to April 18, 2020), based on the different isolation measures applied. This work also aims to model, without establishing a time horizon, the same outcomes given the assumption that eventually 70% of the population will be infected. Materials and Methods Data on the number of confirmed cases in the country as of March 18, 2020 (n=93) were taken as the basis for the achievement of the first objective. An initial transmission rate of R0= 2.5 and a factor of 27 for undetected infections per each confirmed case were taken as assumptions for the model. The proportion of patients who may need intensive care or other in-hospital care was based on data from the Imperial College of London. On the other hand, an age-specific mortality rate provided by the Instituto Superiore di Sanità in Italy was used for the second objective. Results Based on the 93 cases reported as of March 18, if no mitigation measures were applied, by April 18, the country would have 613 037 cases. Mitigation measures that reduce R0 by 10% generate a 50% reduction in the number of cases. However, despite halving the number of cases, there would still be a shortfall in the number of beds required and only one in two patients would have access to this resource. Conclusion This model found that the mitigation measures implemented to date by the Colombian government and analyzed in this article are based on sufficient evidence and will help to slow the spread of SARS-CoV-2 in Colombia. Although a time horizon of one month was used for this model, it is plausible to believe that, if the current measures are sustained, the mitigation effect will also be sustained over time.(AU)


Asunto(s)
Humanos , Cuarentena/organización & administración , Infecciones por Coronavirus/mortalidad , Infecciones por Coronavirus/epidemiología , Prevención y Mitigación , Hospitales/provisión & distribución , Colombia/epidemiología
9.
Rev Bras Epidemiol ; 23: e200095, 2020.
Artículo en Portugués, Inglés | MEDLINE | ID: covidwho-836012

RESUMEN

OBJECTIVE: To assess, through space-time analyses, whether the income inequality of the Federative Units (FUs) in Brazil can be associated with the risk of infection and death by COVID-19. METHODS: This was an ecological study, based on secondary data on incidence and mortality rates for COVID-19. Data were analyzed at the state level, having the Gini coefficient as the main independent variable. Records of twelve days were used, spaced one week each, between April 21th and June 7th, 2020. The weekly variation in the rates was calculated through Prais-Winsten regression, aiming at measuring the evolution of the pandemic in each FU. Spearman's correlation test was used to assess correlation between the rates and their weekly evolution and the independent variables. Lastly, a spatial dependence diagnosis was conducted, and a Spatial Regression lag model was used when applicable. RESULTS: Incidence and mortality rates of COVID-19 increased in all Brazilian FUs, being more pronounced among those with greater economic inequality. Association between Gini coefficient and COVID-19 incidence and mortality rates remained even when demographic and spatial aspects were taken into account. CONCLUSION: Income inequality can play an important role in the impact of COVID-19 on the Brazilian territory, through absolute and contextual effects. Structural policies to reduce inequality are essential to face this and future health crises in Brazil.


Asunto(s)
Infecciones por Coronavirus/epidemiología , Disparidades en el Estado de Salud , Pandemias , Neumonía Viral/epidemiología , Brasil/epidemiología , Infecciones por Coronavirus/mortalidad , Humanos , Neumonía Viral/mortalidad , Medición de Riesgo , Factores Socioeconómicos
10.
BMC Infect Dis ; 20(1): 735, 2020 Oct 07.
Artículo en Inglés | MEDLINE | ID: covidwho-835820

RESUMEN

BACKGROUND: The pandemic of COVID-19 has occurred close on the heels of a global resurgence of measles. In 2019, an unprecedented epidemic of measles affected Samoa, requiring a state of emergency to be declared. Measles causes an immune amnesia which can persist for over 2 years after acute infection and increases the risk of a range of other infections. METHODS: We modelled the potential impact of measles-induced immune amnesia on a COVID-19 epidemic in Samoa using data on measles incidence in 2018-2019, population data and a hypothetical COVID-19 epidemic. RESULTS: The young population structure and contact matrix in Samoa results in the most transmission occurring in young people < 20 years old. The highest rate of death is the 60+ years old, but a smaller peak in death may occur in younger people, with more than 15% of total deaths in the age group under 20 years old. Measles induced immune amnesia could increase the total number of cases by 8% and deaths by more than 2%. CONCLUSIONS: Samoa, which had large measles epidemics in 2019-2020 should focus on rapidly achieving high rates of measles vaccination and enhanced surveillance for COVID-19, as the impact may be more severe due to measles-induced immune paresis. This applies to other severely measles-affected countries in the Pacific, Europe and elsewhere.


Asunto(s)
Betacoronavirus , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/mortalidad , Sarampión/epidemiología , Sarampión/mortalidad , Neumonía Viral/epidemiología , Neumonía Viral/mortalidad , Adolescente , Adulto , Distribución por Edad , Anciano , Niño , Preescolar , Comorbilidad , Infecciones por Coronavirus/virología , Femenino , Humanos , Incidencia , Lactante , Recién Nacido , Masculino , Sarampión/inmunología , Sarampión/prevención & control , Persona de Mediana Edad , Modelos Estadísticos , Pandemias , Neumonía Viral/virología , Samoa/epidemiología , Vacunación , Adulto Joven
11.
Medicine (Baltimore) ; 99(40): e22439, 2020 Oct 02.
Artículo en Inglés | MEDLINE | ID: covidwho-835216

RESUMEN

BACKGROUND: The mortality rate associated with Covid-19 varies considerably among studies and determinants of this variability are not well characterized. METHODS: A systematic review of peer-reviewed literature published through March 31, 2020 was performed to estimate the mortality rate among hospitalized patients in China with a confirmed diagnosis of Covid-19. Hospital mortality rates were estimated using an inverse variance-weighted random-effects meta-analysis model. Funnel plot symmetry was evaluated for small-study effects, a one-study removed sensitivity analysis assessed the influence of individual studies on the pooled mortality rate, and metaregression assessed the association of potential confounding variables with mortality rates. RESULTS: The review included 16 observational studies involving 1832 hospitalized patients with a diagnosis of Covid-19. The surveillance period among studies ranged from December 16, 2019 to February 23, 2020. The median patient age was 53 years and 53% were males. A total of 38.5% of patients presented with at least 1 comorbidity, most commonly hypertension (24.0%), cardiac disease (15.1%), and diabetes mellitus (14.4%). Fever and cough, reported in 84.8% and 61.7% of patients respectively, were the most common patient symptoms. The pooled mortality rate was 9.9% (95% confidence interval 6.1% to 14.5%). Funnel plot asymmetry was not observed and the meta-analysis results were not substantially influenced by any single study since the pooled mortality rate ranged from 8.9% to 11.1% following iterative removal of one study at a time. Substantial heterogeneity in the mortality rate was identified among studies (I = 87%; P < .001). In a metaregression that included demographics, patient risk factors, and presenting symptoms, only a higher prevalence of diabetes mellitus was associated with a higher mortality rate (P = .03). CONCLUSIONS: In a meta-analysis of hospitalized patients in China with a diagnosis of Covid-19, the mortality rate was 9.9% and a higher diabetes mellitus prevalence was independently associated with a worse prognosis. The independent influence of diabetes mellitus with Covid-19 mortality should be viewed as hypothesis-generating and warrants further study.


Asunto(s)
Betacoronavirus , Infecciones por Coronavirus/mortalidad , Complicaciones de la Diabetes/mortalidad , Diabetes Mellitus/mortalidad , Mortalidad Hospitalaria , Neumonía Viral/mortalidad , Adulto , Anciano , Infecciones por Coronavirus/complicaciones , Infecciones por Coronavirus/virología , Complicaciones de la Diabetes/virología , Diabetes Mellitus/virología , Femenino , Humanos , Masculino , Persona de Mediana Edad , Pandemias , Neumonía Viral/complicaciones , Neumonía Viral/virología , Prevalencia , Factores de Riesgo
12.
Nat Commun ; 11(1): 5033, 2020 10 06.
Artículo en Inglés | MEDLINE | ID: covidwho-834869

RESUMEN

Soaring cases of coronavirus disease (COVID-19) are pummeling the global health system. Overwhelmed health facilities have endeavored to mitigate the pandemic, but mortality of COVID-19 continues to increase. Here, we present a mortality risk prediction model for COVID-19 (MRPMC) that uses patients' clinical data on admission to stratify patients by mortality risk, which enables prediction of physiological deterioration and death up to 20 days in advance. This ensemble model is built using four machine learning methods including Logistic Regression, Support Vector Machine, Gradient Boosted Decision Tree, and Neural Network. We validate MRPMC in an internal validation cohort and two external validation cohorts, where it achieves an AUC of 0.9621 (95% CI: 0.9464-0.9778), 0.9760 (0.9613-0.9906), and 0.9246 (0.8763-0.9729), respectively. This model enables expeditious and accurate mortality risk stratification of patients with COVID-19, and potentially facilitates more responsive health systems that are conducive to high risk COVID-19 patients.


Asunto(s)
Infecciones por Coronavirus/mortalidad , Aprendizaje Automático , Pandemias , Neumonía Viral/mortalidad , Anciano , Betacoronavirus , China/epidemiología , Femenino , Humanos , Modelos Logísticos , Masculino , Persona de Mediana Edad , Redes Neurales de la Computación , Medición de Riesgo , Máquina de Vectores de Soporte
13.
Acta Med Indones ; 52(3): 246-254, 2020 Jul.
Artículo en Inglés | MEDLINE | ID: covidwho-833767

RESUMEN

BACKGROUND: Coronavirus Disease 2019 is an emerging respiratory disease that is now a pandemic. Indonesia is experiencing a rapid surge of cases but the local data are scarce. METHODS: this is an analysis using data from the ongoing recapitulation of Epidemiological Surveillance (ES) by the Provincial Health Office of Jakarta from March 2nd to April 27th 2020. We evaluated demographic and clinical characteristics of all confirmed cases in association with death. RESULTS: of the 4,052 patients, 381 (9.4%) patients were deceased. Multivariable analysis showed that death was associated with older age (odds ratio [OR] 1.03; 95% confidence interval [CI] 1.02, 1.05, per year increase; p<0.001), dyspnea (OR 4.83; 95% CI 3.20, 7.29; p<0.001), pneumonia (OR 2.46; 95%CI 1.56, 3.88; p<0.001), and pre-existing hypertension (OR 1.86; 95% CI 1.24, 2.78; p=0.003). Death was highest in the week of April 6th 2020 and declined in the subsequent weeks, after a large-scale social restriction commenced. CONCLUSION: older age, dyspnea, pneumonia, and pre-existing hypertension were associated with death. Mortality was high, but may be reduced by lockdown.


Asunto(s)
Betacoronavirus , Infecciones por Coronavirus/mortalidad , Pandemias , Neumonía Viral/mortalidad , Medición de Riesgo/métodos , Adolescente , Adulto , Distribución por Edad , Anciano , Niño , Estudios Epidemiológicos , Femenino , Estudios de Seguimiento , Humanos , Incidencia , Indonesia/epidemiología , Masculino , Persona de Mediana Edad , Estudios Retrospectivos , Factores de Riesgo , Distribución por Sexo , Tasa de Supervivencia/tendencias , Adulto Joven
16.
Int J Med Sci ; 17(16): 2468-2476, 2020.
Artículo en Inglés | MEDLINE | ID: covidwho-827890

RESUMEN

Rationale: Coronavirus disease 2019 (COVID-19) was first announced in Wuhan, and has rapidly evolved into a pandemic. However, the risk factors associated with the severity and mortality of COVID-19 are yet to be described in detail. Methods: We retrospectively reviewed the information of 1525 cases from the Leishenshan Hospital in Wuhan. Univariate and multivariate Cox regression analyses were generated to explore the relationship between procalcitonin (PCT) level and the progression and prognosis of COVID-19. Univariate and multivariate logistic regression analyses were performed to explore the relationship between disease severity in hospitalized patients and their PCT levels. Survival curves and the cumulative hazard function for COVID-19 progression were conducted in the two groups. To further detect the relationship between the computed tomography score and survival days, curve-fitting analyses were performed. Results: Patients in the elevated PCT group had a higher incidence of severe and critical severity conditions (P < 0.001), death, and higher computed tomography (CT) scores. There was an association between elevated PCT levels and mortality in the univariate ((hazard ratio [1], 3.377; 95% confidence interval [2], 1.012-10.344; P = 0.033) and multivariate Cox regression analysis (HR, 4.933; 95% CI, 1.170-20.788; P = 0.030). Similarly, patients with elevated PCT were more likely to have critically severe disease conditions in the univariate (odds ratio [2], 7.247; 95% CI, 3.559-14.757; P < 0.001) and multivariate logistic regression analysis (OR, 10.679; 95% CI, 4.562-25.000; P < 0.001). Kaplan-Meier curves showed poorer prognosis for patients with elevated PCT (P = 0.024). The CT score 1 for patients with elevated PCT peaked at day 40 following the onset of symptoms then decreased gradually, while their total CT score was relatively stable. Conclusion: PCT level was shown as an independent risk factor of in-hospital mortality among COVID-19 patients. Compared with inpatients with normal PCT levels, inpatients with elevated PCT levels had a higher risk for overall mortality and critically severe disease. These findings may provide guidance for improving the prognosis of patients with critically severe COVID-19.


Asunto(s)
Betacoronavirus , Infecciones por Coronavirus/etiología , Infecciones por Coronavirus/mortalidad , Neumonía Viral/etiología , Neumonía Viral/mortalidad , Polipéptido alfa Relacionado con Calcitonina/sangre , Anciano , Antibacterianos/uso terapéutico , Antivirales/uso terapéutico , Betacoronavirus/efectos de los fármacos , China/epidemiología , Comorbilidad , Infecciones por Coronavirus/diagnóstico por imagen , Infecciones por Coronavirus/tratamiento farmacológico , Progresión de la Enfermedad , Femenino , Hospitalización , Humanos , Estimación de Kaplan-Meier , Masculino , Persona de Mediana Edad , Pandemias , Neumonía Viral/diagnóstico por imagen , Pronóstico , Estudios Retrospectivos , Tomografía Computarizada por Rayos X
18.
Clin Infect Dis ; 70(9): 1837-1844, 2020 04 15.
Artículo en Inglés | MEDLINE | ID: covidwho-822200

RESUMEN

BACKGROUND: The objective of this study was to evaluate the effect of ribavirin and recombinant interferon (RBV/rIFN) therapy on the outcomes of critically ill patients with Middle East respiratory syndrome (MERS), accounting for time-varying confounders. METHODS: This is a retrospective cohort study of critically ill patients with laboratory-confirmed MERS from 14 hospitals in Saudi Arabia diagnosed between September 2012 and January 2018. We evaluated the association of RBV/rIFN with 90-day mortality and MERS coronavirus (MERS-CoV) RNA clearance using marginal structural modeling to account for baseline and time-varying confounders. RESULTS: Of 349 MERS patients, 144 (41.3%) patients received RBV/rIFN (RBV and/or rIFN-α2a, rIFN-α2b, or rIFN-ß1a; none received rIFN-ß1b). RBV/rIFN was initiated at a median of 2 days (Q1, Q3: 1, 3 days) from intensive care unit admission. Crude 90-day mortality was higher in patients with RBV/rIFN compared to no RBV/rIFN (106/144 [73.6%] vs 126/205 [61.5%]; P = .02]. After adjusting for baseline and time-varying confounders using a marginal structural model, RBV/rIFN was not associated with changes in 90-day mortality (adjusted odds ratio, 1.03 [95% confidence interval {CI}, .73-1.44]; P = .87) or with more rapid MERS-CoV RNA clearance (adjusted hazard ratio, 0.65 [95% CI, .30-1.44]; P = .29). CONCLUSIONS: In this observational study, RBV/rIFN (RBV and/or rIFN-α2a, rIFN-α2b, or rIFN-ß1a) therapy was commonly used in critically ill MERS patients but was not associated with reduction in 90-day mortality or in faster MERS-CoV RNA clearance.


Asunto(s)
Antivirales/uso terapéutico , Infecciones por Coronavirus/mortalidad , Infecciones por Coronavirus/terapia , Interferón alfa-2/uso terapéutico , Ribavirina/uso terapéutico , Anciano , Enfermedad Crítica , Femenino , Humanos , Unidades de Cuidados Intensivos , Masculino , Persona de Mediana Edad , Coronavirus del Síndrome Respiratorio de Oriente Medio , Neumonía Viral/tratamiento farmacológico , ARN Viral/sangre , Estudios Retrospectivos , Arabia Saudita , Resultado del Tratamiento
19.
Arterioscler Thromb Vasc Biol ; 40(10): 2404-2407, 2020 10.
Artículo en Inglés | MEDLINE | ID: covidwho-817877

RESUMEN

OBJECTIVE: Alveolar-capillary endothelial cells can be activated by severe acute respiratory syndrome coronavirus 2 infection leading to cytokine release. This could trigger endothelial dysfunction, pyroptosis, and thrombosis, which are the vascular changes, commonly referred to as coronavirus disease 2019 (COVID-19) endotheliopathy. Thus, this study aimed to identify tissue biomarkers associated with endothelial activation/dysfunction and the pyroptosis pathway in the lung samples of patients with COVID-19 and to compare them to pandemic influenza A virus H1N1 subtype 2009 and control cases. Approach and Results: Postmortem lung samples (COVID-19 group =6 cases; H1N1 group =10 cases, and control group =11 cases) were analyzed using immunohistochemistry and the following monoclonal primary antibodies: anti-IL (interleukin)-6, anti-TNF (tumor necrosis factor)-α, anti-ICAM-1 (intercellular adhesion molecule 1), and anticaspase-1. From the result, IL-6, TNF-α, ICAM-1, and caspase-1 showed higher tissue expression in the COVID-19 group than in the H1N1 and control groups. CONCLUSIONS: Our results demonstrated endothelial dysfunction and suggested the participation of the pyroptosis pathway in the pulmonary samples. These conditions might lead to systemic thrombotic events that could impair the clinical staff's efforts to avoid fatal outcomes. One of the health professionals' goals should be to identify the high risk of thrombosis patients early to block endotheliopathy and its consequences.


Asunto(s)
Infecciones por Coronavirus/patología , Células Endoteliales/citología , Endotelio Vascular/patología , Neumonía Viral/patología , Trombosis/patología , Enfermedades Vasculares/patología , Autopsia , Biopsia con Aguja , Causas de Muerte , Infecciones por Coronavirus/mortalidad , Células Endoteliales/patología , Endotelio Vascular/fisiopatología , Femenino , Humanos , Inmunohistoquímica , Masculino , Pandemias , Neumonía Viral/mortalidad , Medición de Riesgo , Trombosis/etiología , Trombosis/mortalidad , Enfermedades Vasculares/mortalidad , Enfermedades Vasculares/fisiopatología
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