ABSTRACT
Abstract Visceral leishmaniasis (VL) is an infectious disease predominant in countries located in the tropics. The prediction of occurrence of infectious diseases through epidemiologic modeling has revealed to be an important tool in the understanding of its occurrence dynamic. The objective of this study was to develop a forecasting model for the incidence of VL in Maranhão using the Seasonal Autoregressive Integrated Moving Average model (SARIMA). We collected monthly data regarding VL cases from the National Disease Notification System (SINAN) corresponding to the period between 2001 and 2018. The Box-Jenkins method was applied in order to adjust a SARIMA prediction model for VL general incidence and by sex (male or female) for the period between January 2019 and December 2013. For 216 months of this time series, 10,431 cases of VL were notified in Maranhão, with an average of 579 cases per year. With regard to age range, there was a higher incidence among the pediatric public (0 to 14 years of age). There was a predominance in male cases, 6437 (61.71%). The Box-Pierce test figures for overall, male and female genders supported by the results of the Ljung-Box test suggest that the autocorrelations of residual values act as white noise. Regarding monthly occurrences in general and by gender, the SARIMA models (2,0,0) (2,0,0), (0,1,1) (0,1,1) and (0,1,1) (2, 0, 0) were the ones that mostly adjusted to the data respectively. The model SARIMA has proven to be an adequate tool for predicting and analyzing the trends in VL incidence in Maranhão. The time variation determination and its prediction are decisive in providing guidance in health measure intervention.
Resumo A leishmaniose visceral (LV) é uma doença de natureza infecciosa, predominante em países de zonas tropicais. A predição de ocorrência de doenças infecciosas através da modelagem epidemiológica tem se revelado uma importante ferramenta no entendimento de sua dinâmica de ocorrência. O objetivo deste estudo foi desenvolver um modelo de previsão da incidência da LV no Maranhão usando o modelo de Média Móvel Integrada Autocorrelacionada Sazonal (SARIMA). Foram coletados os dados mensais de casos de LV através do Sistema de Informação de Agravos de Notificação (SINAN) correspondentes ao período de 2001 a 2018. O método de Box-Jenkins foi aplicado para ajustar um modelo de predição SARIMA para incidência geral e por sexo (masculino e feminino) de LV para o período de janeiro de 2019 a dezembro de 2023. Durante o período de 216 meses dessa série temporal, foram registrados 10.431 casos de LV no Maranhão, com uma média de 579 casos por ano. Em relação à faixa etária, houve maior registro no público pediátrico (0 a 14 anos). Houve predominância do sexo masculino, com 6437 casos (61,71%). Os valores do teste de Box-Pierce para incidência geral, sexo masculino e feminino reforçados pelos resultados do teste Ljung-Box sugerem que as autocorrelações de resíduos apresentam um comportamento de ruído branco. Para incidência mensal geral e por sexo masculino e feminino, os modelos SARIMA (2,0,0) (2,0,0), (0,1,1) (0,1,1) e (0,1,1) (2, 0, 0) foram os que mais se ajustaram aos dados, respectivamente. O modelo SARIMA se mostrou uma ferramenta adequada de previsão e análise da tendência de incidência da LV no Maranhão. A determinação da variação temporal e sua predição são determinantes no norteamento de medidas de intervenção em saúde.
ABSTRACT
Abstract Visceral leishmaniasis (VL) is an infectious disease predominant in countries located in the tropics. The prediction of occurrence of infectious diseases through epidemiologic modeling has revealed to be an important tool in the understanding of its occurrence dynamic. The objective of this study was to develop a forecasting model for the incidence of VL in Maranhão using the Seasonal Autoregressive Integrated Moving Average model (SARIMA). We collected monthly data regarding VL cases from the National Disease Notification System (SINAN) corresponding to the period between 2001 and 2018. The Box-Jenkins method was applied in order to adjust a SARIMA prediction model for VL general incidence and by sex (male or female) for the period between January 2019 and December 2013. For 216 months of this time series, 10,431 cases of VL were notified in Maranhão, with an average of 579 cases per year. With regard to age range, there was a higher incidence among the pediatric public (0 to 14 years of age). There was a predominance in male cases, 6437 (61.71%). The Box-Pierce test figures for overall, male and female genders supported by the results of the Ljung-Box test suggest that the autocorrelations of residual values act as white noise. Regarding monthly occurrences in general and by gender, the SARIMA models (2,0,0) (2,0,0), (0,1,1) (0,1,1) and (0,1,1) (2, 0, 0) were the ones that mostly adjusted to the data respectively. The model SARIMA has proven to be an adequate tool for predicting and analyzing the trends in VL incidence in Maranhão. The time variation determination and its prediction are decisive in providing guidance in health measure intervention.
Resumo A leishmaniose visceral (LV) é uma doença de natureza infecciosa, predominante em países de zonas tropicais. A predição de ocorrência de doenças infecciosas através da modelagem epidemiológica tem se revelado uma importante ferramenta no entendimento de sua dinâmica de ocorrência. O objetivo deste estudo foi desenvolver um modelo de previsão da incidência da LV no Maranhão usando o modelo de Média Móvel Integrada Autocorrelacionada Sazonal (SARIMA). Foram coletados os dados mensais de casos de LV através do Sistema de Informação de Agravos de Notificação (SINAN) correspondentes ao período de 2001 a 2018. O método de Box-Jenkins foi aplicado para ajustar um modelo de predição SARIMA para incidência geral e por sexo (masculino e feminino) de LV para o período de janeiro de 2019 a dezembro de 2023. Durante o período de 216 meses dessa série temporal, foram registrados 10.431 casos de LV no Maranhão, com uma média de 579 casos por ano. Em relação à faixa etária, houve maior registro no público pediátrico (0 a 14 anos). Houve predominância do sexo masculino, com 6437 casos (61,71%). Os valores do teste de Box-Pierce para incidência geral, sexo masculino e feminino reforçados pelos resultados do teste Ljung-Box sugerem que as autocorrelações de resíduos apresentam um comportamento de ruído branco. Para incidência mensal geral e por sexo masculino e feminino, os modelos SARIMA (2,0,0) (2,0,0), (0,1,1) (0,1,1) e (0,1,1) (2, 0, 0) foram os que mais se ajustaram aos dados, respectivamente. O modelo SARIMA se mostrou uma ferramenta adequada de previsão e análise da tendência de incidência da LV no Maranhão. A determinação da variação temporal e sua predição são determinantes no norteamento de medidas de intervenção em saúde.
Subject(s)
Humans , Male , Female , Infant, Newborn , Infant , Child, Preschool , Child , Adolescent , Leishmaniasis, Visceral/diagnosis , Leishmaniasis, Visceral/epidemiology , Seasons , Brazil/epidemiology , Incidence , Models, StatisticalABSTRACT
Abstract Introduction COVID-19 remains an important threat to global health and maintains the challenge of COVID-19 hospital care. To assist decision making regarding COVID-19 hospital care many instruments to predict COVID-19 progression to critical condition were developed and validated. Objective To validate eleven COVID-19 progression prediction scores for critically ill hospitalized patients in a Brazilian population. Methodology Observational study with retrospective follow-up, including 301 adults confirmed for COVID-19 sequentially. Participants were admitted to non-critical units for treatment of the disease, between January and April 2021 and between September 2021 and February 2022. Eleven prognostic scores were applied using demographic, clinical, laboratory and imaging data collected in the first 48 of the hospital admission. The outcomes of greatest interest were as originally defined for each score. The analysis plan was to apply the instruments, estimate the outcome probability reproducing the original development/validation of each score, then to estimate performance measures (discrimination and calibration) and decision thresholds for risk classification. Results The overall outcome prevalence was 41.8 % on 301 participants. There was a greater risk of the occurrence of the outcomes in older and male patients, and a linear trend with increasing comorbidities. Most of the patients studied were not immunized against COVID-19. Presence of concomitant bacterial infection and consolidation on imaging increased the risk of outcomes. College of London COVID-19 severity score and the 4C Mortality Score were the only with reasonable discrimination (ROC AUC 0.647 and 0.798 respectively) and calibration. The risk groups (low, intermediate and high) for 4C score were updated with the following thresholds: 0.239 and 0.318 (https://pedrobrasil.shinyapps.io/INDWELL/). Conclusion The 4C score showed the best discrimination and calibration performance among the tested instruments. We suggest different limits for risk groups. 4C score use could improve decision making and early therapeutic management at hospital care.
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@#[Objective] To construct a Nomogram model for the prediction of essential hypertension (EH) risks with the use of traditional Chinese medicine (TCM) syndrome elements principles in conjunction with cutting-edge biochemical detection technologies. [Methods] A case-control study was conducted, involving 301 patients with essential hypertension in the hypertensive group and 314 without in the control group. Comprehensive data, including the information on the four TCM diagnoses, general data, and blood biochemical indicators of participants in both groups, were collected separately for analysis. The differentiation principles of syndrome elements were used to discern the location and nature of hypertension. One-way analysis was carried out to screen for potential risk factors of the disease. Least absolute shrinkage and selection operator (LASSO) regression was used to identify factors that contribute significantly to the model, and eliminate possible collinearity problems. At last, multivariate logistic regression analysis was used to both screen and quantify independent risk factors essential for the prediction model. The “rms” package in the R Studio was used to construct the Nomogram model, creating line segments of varying lengths based on the contribution of each risk factor to aid in the prediction of risks of hypertension. For internal model validation, the Bootstrap program package was utilized to perform 1000 repetitions of sampling and generate calibration curves. [Results] The results of the multivariate logistic regression analysis revealed that the risk factors of EH included age, heart rate (HR), waist-to-hip ratio (WHR), uric acid (UA) levels, family medical history, sleep patterns (early awakening and light sleep), water intake, and psychological traits (depression and anger). Additionally, TCM syndrome elements such as phlegm, Yin deficiency, and Yang hyperactivity contributed to the risk of EH onset as well. TCM syndrome elements liver, spleen, and kidney were also considered the risk factors of EH. Next, the Nomogram model was constructed using the aforementioned 14 risk predictors, with an area under the curve (AUC) of 0.868 and a 95% confidence interval (CI) ranging from 0.840 to 0.895. The diagnostic sensitivity and specificity were found to be 80.7% and 85.0%, respectively. Internal validation confirmed the model’s robust predictive performance, with aconsistency index (C-index) of 0.879, underscoring the model’s strong predictive ability. [Conclusion] By integrating TCM syndrome elements, the Nomogram model has realized the objective, qualitative, and quantitative selection of early warning factors for developing EH, resulting in the creation of a more comprehensive and precise prediction model for EH risks.
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Objective:To analyze the risk factors for malnutrition among disabled stroke survivors and devise a prediction model.Methods:A total of 373 disabled stroke survivors treated in the Department of Rehabilitation Medicine, the First Affiliated Hospital of Zhengzhou University in 2021 formed a control group ( n=102) and a malnutrition group ( n=271) according to their nutritional status. Univariate correlation analysis and multivariate logistic regression were used to analyze the risk factors for malnutrition and their predictive value. Results:Age, dysphagia, pulmonary infection, disability score and feeding style were found to be related significantly to the occurrence of malnutrition. Multivariate logistic regression confirmed that age, pulmonary infection, dysphagia, low total intake and a low Barthel index were useful predictors of malnutrition in such persons. Moreover, patients who had received nasogastric tube feeding were at much higher risk of malnutrition than those with intermittent oroesophageal tube feeding. The area under the receiver operating characteristics curve of the Barthel index combined with dysphagia to predict malnutrition was 0.84. The critical value was 0.67 with a sensitivity of 88% and a specificity of 72.5%.Conclusions:Age, pulmonary infection, dysphagia, feeding method, total intake and disability score are risk factors for malnutrition in disabled stroke survivors. The Barthel index combined with dysphagia has good predictive power for the occurrence of malnutrition in such persons.
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Introduction: The prediction of potential fishing areas is considered one of the most immediate and practical approaches in fisheries and is an essential technique for decision-making in managing fishery resources. It helps fishermen reduce their fuel costs and the uncertainty of their fish catches; this technique allows to contribute to national and international food security. In this study, we build different combinations of predictive statistical models such as Generalized Linear Models and Generalized Additive Models. Objective: To predict the spatial distribution of PFZs of the dolphinfish (Coryphaena hippurus L.) in the Colombian Pacific Ocean. Methods: We built different combinations of Generalized Linear Models and Generalized Additive Models to predict the Catch Per Unit Effort of C. hippurus captured from 2002 to 2015 as a function of sea surface temperature, chlorophyll-a concentration, sea level anomaly, and bathymetry. Results: A Generalized Additive Model with Gaussian error distribution obtained the best performance for predicting PFZs for C. hipurus. Model validation was performed by calculating the Root Mean Square Error through a cross-validation approach. The R2 of this model was 50 %, which was considered suitable for the type of data used. January and March were the months with the highest Catch per Unit Effort values, while November and December showed the lower values. Conclusion: The predicted PFZs of C. hippurus with Generalized Additive Models satisfactorily with the results of previous research, suggesting that our model can be explored as a tool for the assessment, decision making, and sustainable use of this species in the Colombian Pacific Ocean.
Introducción: La predicción de zonas potenciales de pesca se considera uno de los enfoques más inmediatos y efectivos en las pesquerías, es una técnica importante para la toma de decisiones en el manejo de los recursos pesqueros. Ayuda a los pescadores a reducir su costo de combustible y también a disminuir la incertidumbre de sus capturas, esta técnica permite contribuir a la seguridad alimentaria nacional e internacional. En este estudio, se construyeron diferentes combinaciones de modelos estadísticos predictivos como modelos lineales generalizados y modelos aditivos generalizados. Objetivo: predecir la distribución espacial de las zonas potenciales de pesca del pez dorado (Coryphaena hippurus L.) en el Pacífico colombiano. Métodos: La variable de respuesta se expresó en escala de captura por unidad de esfuerzo, es decir, el número de individuos de C. hippurus capturados por un número total de anzuelos disponibles entre 2002 y 2015. Temperatura de la superficie del mar, concentración de clorofila, anomalía del nivel del mar y batimetría, se utilizaron como variables explicativas para los meses de estacionalidad de C. hippurus (noviembre - marzo). Resultados: El modelo con mejor rendimiento para la predicción de zonas potenciales de pesca fue un modelo aditivo generalizado con distribución de error gaussiana y función de enlace de registro, que se seleccionó en función del criterio de información de Akaike, el R2 y la desviación explicada. La validación del modelo se realizó calculando el error cuadrático medio a través de un enfoque de validación cruzada. El ajuste de este modelo fue del 50 %, lo que puede considerarse adecuado para el tipo de datos utilizados. Enero y marzo fueron los meses con mayor captura por unidad de esfuerzo y noviembre-diciembre los meses con menor. Conclusión: Las zonas potenciales de pesca previstas coincidieron satisfactoriamente con investigaciones anteriores, lo que sugiere que nuestro modelo es una herramienta poderosa para la evaluación, toma de decisiones y uso sostenible de los recursos pesqueros de C. hippurus en el Pacífico colombiano.
Subject(s)
Animals , Fishing Industry , Forecasting , Colombia , Geographic Information SystemsABSTRACT
Abstract Objective: To explore the diagnostic utility of 31 electrocardiogram (ECG) criteria for detecting echocardiographic (Echo) left ventricular geometry using accuracy. Methods: This cross-sectional study included consecutive adults (> 18 years) that were classified by Echo left ventricular geometry as normal (NL), concentric remodeling (CR), concentric hypertrophy (CH), and eccentric hypertrophy (EH). Thirty-one state-of-the-art ECG criteria for Echo left ventricular hypertrophy were calculated. AUC 95%CI, accuracy, sensitivity, specificity, and positive and negative predictive value for detecting Echo left ventricular geometries were compared. Multivariable linear regression models were produced using the ECG criteria as the dependent variable. Results: A total of 672 adults were included in the study. From 31 ECG criteria, Cornell (ECG21, SV3 + RaVL) and modified Cornell (ECG 31, RaVL + deepest S in all leads) criteria have the best overall AUC in differentiating NL versus CH (0.666 and 0.646), NL versus EH (0.686 and 0.656), CR versus CH (0.687 and 0.661), and CR versus EH (0.718 and 0.676). In multivariable linear regression models, CH and EH had the strongest effect on the final voltage in Cor- nell (ECG21) and modified Cornell (ECG31). Conclusions: From 31 state-of-the-art criteria, Cornell and modified Cornell criteria have the best AUC and accuracy for predicting most left ventricular geometries. CH and EH had the strongest effect on the voltage of Cornell and modified Cornell criteria compared to body mass index, age, diabetes, hypertension, and chronic heart disease. The ECG criteria poorly differentiate NL from CR and CH from EH.
Resumen Objetivo: Explorar la utilidad diagnóstica de 31 criterios de ECG para detectar la geometría ecocardiográfica del ventrículo izquierdo usando la exactitud, área bajo la curva, sensibilidad, especificidad, y valor predictivo positivo y negativo. Métodos: Este estudio transversal incluyó adultos (> 18 años) que se sometieron a ECG y ecocardiograma transtorácico. Los pacientes fueron clasificados según la geometría del ventrículo izquierdo: normal (NL), remodelado concéntrico (RC), hipertrofia concéntrica (HC) e hipertrofia excéntrica (HE). Se calcularon 31 criterios clásicos de ECG para detectar hipertrofia ventricular izquierda y se comparó el rendimiento diagnóstico en cada geometría. Creamos un modelo de regresión lineal múltiple usando los criterios de ECG como variable dependiente. Resultados: Se incluyeron 672 adultos. Los criterios de Cornell (ECG 21, SV3 + RaVL) y Cornell modificado (ECG31, RaVL + S mas profunda de las 12 derivaciones) tienen el mejor AUC para diferenciar NL versus HC (0.666 y 0.646), NL versus HE (0.686 y 0.656), RC versus HC (0.687 y 0.661) y RC versus HE (0.718 y 0.676). En el análisis multivariado la geometría del ventrículo izquierdo (HC e HE) fue la variable que mas influyó en el resultado final del criterio de Cornell y de Cornell modificado. Conclusión: De los 31 criterios clásicos explorados, los criterios de Cornell y Cornell modificado tienen el mejor AUC y exactitud para predecir la mayoría de las geometrías del ventrículo izquierdo. Los criterios del ECG no diferencian bien la geometría NL del RC ni HC de la HE.
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Resumen Introducción: la identificación de los pacientes con mayor riesgo de progresar a falla renal es fundamental para la planeación del tratamiento en la enfermedad renal crónica, pero no ha podido llevarse a cabo consistentemente. Los modelos de predicción podrían ser una herramienta útil, sin embargo, su usabilidad en la Enfermedad Renal Crónica es limitada hasta ahora y no se comprenden muy bien las barreras y limitaciones. Métodos: se desarrolló una revisión de alcance de la literatura disponible sobre modelos predictivos de falla renal o reglas de pronóstico en pacientes con Enfermedad Renal Crónica. Las búsquedas se realizaron sistemáticamente en Cochrane, Pubmed y Embase. Se realizó una revisión ciega e independiente por dos evaluadores para identificar estudios que informaran sobre el desarrollo, la validación o la evaluación del impacto de un modelo construido para predecir la progresión al estadio avanzado de la enfermedad renal crónica. Se realizó una evaluación crítica de la calidad de la evidencia proporcionada con el sistema GRADE (Grading of Recommendations Assessment, Development and Evaluation). Resultados: de 1279 artículos encontrados, fueron incluidos 19 estudios para la síntesis cualitativa final. La mayoría de los estudios eran primarios, con diseños observacionales retrospectivos y unos pocos correspondieron a revisiones sistemáticas. No se encontraron guías de práctica clínica. La síntesis cualitativa evidenció gran heterogeneidad en el desarrollo de los modelos, así como en el reporte de las medidas de desempeño global, la validez interna y la falta de validez externa en la mayoría de los estudios. La calificación de la evidencia arrojó una calidad global baja, con inconsistencia entre los estudios e importantes limitaciones metodológicas. Conclusiones: la mayoría de los modelos predictivos disponibles, no han sido adecuadamente validados y, por tanto, se consideran de uso limitado para evaluar el pronóstico individual del paciente con enfermedad renal crónica. Por lo tanto, se requieren esfuerzos adicionales para centrar el desarrollo e implementación de modelos predictivos en la validez externa y la usabilidad y disminuir la brecha entre la generación, la síntesis de evidencia y la toma de decisiones en el ámbito del cuidado del paciente.
Abstract Background: the identification of patients at higher risk of progressing to kidney failure is essential for treatment planning in chronic kidney disease, but it has not been possible to do this consistently. Predictive models could be a useful tool, however, their usability in chronic kidney disease is limited and the barriers and limitations are not well understood. Methods: a scoping review of the available literature on ESRD predictive models or prognostic rules in chronic kidney disease patients was developed. Searches were systematically executed on Cochrane, MEDLINE, and Embase. a blind and independent review was carried out by two evaluators to identify studies that reported on the development, validation, or impact assessment of a model constructed to predict the progression to an advanced stage of chronic kidney disease. A critical evaluation of the quality of the evidence provided with the GRADE system (Grading of Recommendations Assessment, Development and Evaluation) was made. Findings: of 1279 articles found, 19 studies were included for the final qualitative synthesis. Most of the studies were primary, with retrospective observational designs and a few corresponded to systematic reviews. No clinical practice guidelines were found. The qualitative synthesis showed high heterogeneity in the development of the models, as well as in the reporting of global performance measures, internal validity, and the lack of external validity in most of the studies. The evidence rating was of low overall quality, with inconsistency between studies and important methodological limitations. Conclusions: most of the available predictive models have not been adequately validated and, therefore, are of limited use to assess the individual prognosis of patients with chronic kidney disease. Therefore, additional efforts are required to focus the development and implementation of predictive models on external validity and usability and bridge the gap between generation, synthesis of evidence, and decision-making in the field of patient care.
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Introducción: Las evidencias demuestran que las ecuaciones de predicción de riesgo cardiovascular no se pueden aplicar directamente en todas las poblaciones y demandan de la evaluación de su validez en una nueva población. Objetivo: Evaluar si el índice pronóstico de morbilidad y mortalidad por enfermedad cardiovascular asociada con factores de riesgo aterogénico, es aplicable a la población general. Métodos: Se realizó un estudio de validación externa basado en una cohorte prospectiva de 10 años de seguimiento, que reclutó a 700 pacientes hipertensos libres de enfermedad cardiovascular al ingreso. Se comparó el número de eventos cardiovasculares esperados y observados en esos diez años (calibración) y se estimó la capacidad de la función de riesgo para separar los sujetos de alto y bajo riesgo (discriminación). Resultados: Se evidenciaron diferencias significativas entre los casos observados y esperados, el grupo de bajo riesgo, de 5 esperados solo alcanza el 2,5 por ciento, situación que se invierte en el grupo de alto riesgo, en el que de 50 eventos esperados, alcanza un incremento de 1,62 veces (81 enfermos). Los valores de sensibilidad superan el 80 por ciento y la especificidad se incrementó en relación directa y proporcional con el gradiente de riesgo. El área bajo la curva ROC fue de 0,78; se consideró como aceptable. Conclusiones: El índice pronóstico evaluado, calibra inadecuadamente porque sobrestima el riesgo cardiovascular, sin embargo discrimina apropiadamente a las personas clasificadas como alto riesgo para adquirir una enfermedad cardiovascular aterosclerótica(AU)
Introduction: The evidence shows that cardiovascular risk prediction equations cannot be applied directly in all populations and require the evaluation of their validity in a new population. Objective: To evaluate whether the prognostic index of morbidity and mortality due to cardiovascular disease associated with atherogenic risk factors is applicable to the general population. Methods: An external validation study was carried out based on a prospective cohort with 10 years of follow-up, which recruited 700 hypertensive patients free of cardiovascular disease on admission. The number of expected and observed cardiovascular events in those ten years was compared (calibration) and the ability of the risk function to separate high and low risk subjects (discrimination) was estimated. Results: Significant differences were evidenced between the observed and expected cases, since the low-risk group of 5 expected only reaches 2.5 percent, a situation that is reversed in the high-risk group, in which 50 expected events reach an increase 1.62 times (81 patients). Sensitivity values 203;exceed 80 percent and specificity increased in direct and proportional relationship with the hazard gradient. The area under the ROC curve was 0.78, considered acceptable. Conclusions: The evaluated prognostic index inadequately calibrates because it overestimates cardiovascular risk, however it appropriatelydiscriminates against people classified as high risk for acquiring atherosclerotic cardiovascular disease(AU)
Subject(s)
Humans , Aptitude , Cardiovascular Diseases , Indicators of Morbidity and Mortality , Social Discrimination , Aftercare , Heart Disease Risk FactorsABSTRACT
RESUMEN Introducción: La predicción de fenómenos en las ciencias médicas mediante escalas pronósticas constituye una herramienta valiosa en la actualidad y deben incluirse en el proceso de toma de decisiones. Pronosticar la mediastinitis postoperatoria permite disponer de recursos para su prevención. Objetivo: Construir una escala pronóstica para estratificar el riesgo de padecer mediastinitis postoperatoria. Método: Se realizó un estudio de casos y controles para los factores de riesgo de mediastinitis postoperatoria en el Cardiocentro Ernesto Guevara de Santa Clara, Cuba. Luego de la regresión logística se obtuvo el modelo y, a partir de este, se incluyeron y ponderaron los predictores para obtener la escala cubana pronóstica de mediastinitis postoperatoria: PREDICMED, que se validó por diversos métodos. Resultados: Esta escala se obtuvo con seis predictores y dos estratos de riesgo. Se analizó su rendimiento mediante ajuste, calibración y determinación de su poder discriminante, con buenos resultados. Se realizó validación interna por el método de división de datos y se comparó su capacidad en ambos subconjuntos (desarrollo y validación) sin diferencias. Se probó su buena validez de constructo, al no existir diferencias entre las probabilidades predichas y las observadas. También se analizó su validez de contenido mediante expertos. Por último, se determinó su validez de criterio al comparar con otra escala similar (MEDSCORE). PREDICMED presentó muy buena capacidad discriminatoria (área bajo la curva 0,962) y elevados valores de sensibilidad (84,62%) y especificidad (92,31%). Conclusiones: La escala pronóstica cubana PREDICMED, para estratificar el riesgo de mediastinitis postoperatoria, mostró buenos parámetros de validación y logró estratificar el riesgo en no alto y alto.
ABSTRACT Introduction: Phenomena prediction through prognostic scales is a valuable tool in medical sciences nowadays and it should be included in the decision-making process. Predicting postoperative mediastinitis allows to count on resources for its prevention. Objective: To build a prognostic scale to stratify the risk of suffering from postoperative mediastinitis. Method: A case-control study for the risk factors of postoperative mediastinitis was carried out at the Cardiocentro Ernesto Guevara from Santa Clara, Cuba. After the logistic regression, the model was obtained and from it, the predictors to obtain the Cuban prognostic scale of postoperative mediastinitis PREDICMED were included and weighted, which was validated through several methods. Results: This scale was obtained, counting on six predictors and two risk strata. Its performance was analyzed through adjustment, calibration and determination of its discriminating capacity, showing good results. Internal validation was carried out through the data division method and its capacity was compared in both subsets (development and validation) showing no differences. Its good construct validity was demonstrated, since there were no differences between the predicted and the observed probabilities. Its contents validity was also analyzed by experts. Finally, its criteria validity was determined when compared with another similar scale (Medscore). PREDICMED showed a very good discriminatory capacity (area under the curve 0.962) as well as high values of sensitivity (84.62%) and specificity (92.31%). Conclusions: The Cuban prognostic scale PREDICMED, to stratify the risk of postoperative mediastinitis showed good validation parameters and it was able to stratify the risk in not high and high.
Subject(s)
Thoracic Surgery , Validation Study , Forecasting , MediastinitisABSTRACT
Resumen Objetivo: actualmente, en Colombia están en uso diferentes escalas para estimar el riesgo de morbimortalidad en pacientes con pancreatitis, lo que genera incertidumbre a la hora de clasificar y manejar a estos pacientes. El objetivo de este estudio es analizar la concordancia entre las más usadas en una población atendida a 2670 metros sobre el nivel del mar (msnm). Materiales y métodos: se evaluaron 200 pacientes, entre 18 y 65 años, con diagnóstico de pancreatitis aguda y manejados en el Hospital Universitario San Ignacio de Bogotá (Colombia). Se estimaron tres escalas de riesgo y se clasificaron como pancreatitis con predicción de gravedad si los puntajes de APACHE II eran ≥8, Marshall modificada ≥2, o si tenían 3 o más criterios de Ranson positivos. Se determinó la concordancia entre los resultados usando el estadístico kappa. Resultados: según Marshall, el 45,5 % de los pacientes correspondieron a pancreatitis con predicción de gravedad, mientras que de acuerdo con APACHE II y Ranson se encontró este diagnóstico en un 39,5 % y un 38,5 %, respectivamente. El coeficiente kappa mostró una concordancia débil entre APACHE II y Ranson (kappa: 0,201; intervalo de confianza [IC], 95 %: 0,05-0,34), así como una concordancia pobre entre Ranson y Marshall (kappa: 0,18; IC, 95 %: 0,04-0,32). La concordancia entre APACHE y Marshall fue moderada (kappa: 0,42; IC, 95 %: 0,28-0,56). Conclusiones: existe un pobre acuerdo entre las diferentes escalas de clasificación de riesgo de pancreatitis usadas en Colombia, por lo que no pueden interpretarse como clínicamente equivalentes. Los datos de este estudio demuestran la necesidad de validar las distintas escalas en Colombia y en Latinoamérica. Además, sugieren que la escala de Marshall sobreestima el riesgo en ciudades por encima de los 2000 msnm.
Abstract Introduction: Different scales to estimate the risk of morbidity and mortality in patients with pancreatitis are currently in use in Colombia, which leads to uncertainty when classifying and treating these patients. Objective: This study seeks to analyze agreement between the most used scales to estimate the risk of patient morbidity and mortality in a population treated at 2,670 meters above sea level (m.a.s.l.). Materials and methods: Two hundred patients between 18 and 65 years old, diagnosed with acute pancreatitis, were evaluated and treated at the Hospital Universitario San Ignacio, Bogotá (Colombia). Three risk scales were used for the estimations. Scores ≥ 8 in the APACHE II system, ≥ 2 in the Modified Marshall Score, or 3 or more positive Ranson criteria were classified as pancreatitis with severity prognostic marker. Agreement between the results was determined using the Kappa coefficient. Results: According to the Marshall score, 45.5% of the cases were pancreatitis with predicted severity, while APACHE II and Ranson yielded scores of 39.5% and 38.5%, respectively. The Kappa coefficient showed weak agreement between APACHE II and Ranson (Kappa=0.201; 95%CI 0.05-0.34), poor agreement between Ranson and Marshall (Kappa=0.18; 95%CI 0.04-0.32), and moderate agreement between APACHE II and Marshall (Kappa=0.42; 95%CI 0.28-0.56). Conclusions: There is poor agreement between the pancreatitis severity scoring systems used in Colombia, so they cannot be interpreted as clinically equivalent. The data from this study demonstrate the need to validate the scales in Colombia and Latin America. They also suggest that the Marshall scale overestimates the risk in cities above 2,000 m.a.s.l.
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Humans , Male , Female , Adolescent , Adult , Middle Aged , Aged , Pancreatitis , Indicators of Morbidity and Mortality , Forecasting , Classification , Sea Level , MethodsABSTRACT
The COVID-19 outbreak in several countries of the world is facing a challenging task to control the virus transmission as 3.7 million people are tested positive in all over world at the time of writing. India is also suffering with the virus outbreak in different states as on January 30, 2020, India reported its first confirmed case of coronavirus deadly disease (COVID-19) in Kerala state where three students returned from the epicentre of the disease, Wuhan, China. During the first week, India experienced a slow growth in the infected cases but soon after an outbreak has been found in several states and union territories, although strict measures are being made to control the outbreak. This study presents a comprehensive analysis to explore the current status of virus transmission at state and country level, infection growth, most affected age groups, available datasets and prediction models and strict control measures. Several data sources are analysed to collect the pandemic data such as Johns Hopkins University, Ministry of Health, COVID-19 India,Worldometer and media. The analysed study will be significant for scientist, researchers and health workers of India and also for the administrative tasks to consider the different strict measure to control COVID-19
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Background: Cardiovascular diseases (CVD) are the world leading causes of death in non-communicable diseases. The aim of this study is to predict cardiovascular risk and compare two prediction models.Methods: This cross-sectional study involved 440 sample size of beverage industrial participants. The 10-year prediction was processed by World Health Organization/International Society of Hypertension (WHO/ISH) score chart and Framingham general risk score. WHO stepwise questionnaire and biomedical forms was used. Data was collected and analyzed by SPSS 16.0 version.Results: The overall CVD low risk prediction (<10%) by Framingham general risk score (FGRS) and WHO/ISH score chart was 74.5%, 95.4%, respectively while the CVD elevated risk (≥10%) was 25.5%, 4.6%, respectively. Gender CVD risk (≥10%) was 16.1% of male versus 9.3% of female by FGRS while 2.7% of male versus 1.5% of female classified by WHO/ISH. CVD risk increases in both of the models with age but very much in FGRS. 8.4% of employees versus 5.2% of spouses was classified as having the risk of 10-20% by FGRS while WHO/ISH classified 2.5% of employees and 0.9% of spouses as having the risk of 10-20%. FGRS classified 11.7% of all participant as having the risk above 20% while WHO/ISH classified only 1% as having the risk above 20%. Two model’s kappa agreement level was fair or minimal interrater reliability with 0.25 with p value <0.001 and the correlated receiver operating characteristic curve (ROC) curve of FGRS and WHO/ISH of 0.887 area under the curve (AUC), 0.847AUC all with a p value <0.001, respectively.Conclusions: FGRS predicted more risk in participants than WHO/ISH and was with minimal kappa agreement.
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Prostate cancer (PCa) risk calculators (RCs) with prostate-specific antigen (PSA) and other risk factors can greatly improve the accurate prediction of potential risk of PCa compared to PSA. The European Randomized Study of Screening for PCa Risk Calculator (ERSPC-RC) and the Prostate Cancer Prevention Trial Risk Calculator (PCPT-RC) are developed on the Western population. However, the Western RCs showed limited diagnostic efficacy in the Eastern Asian population, mainly due to racial differences between the two populations. We aimed to review the application of Western RCs and Eastern Asian RCs in Eastern Asian cohorts and to identify the characteristics and efficacy of these RCs.
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Objectives To analyze the studies about predicting COVID-19 by math models, to provide evidences and experiences to reduce the hazard of COVID-19. Methods PubMed, CNKI and other databases were searched for studies involving math models of COVID-19, and the studies were compared with each other and the real data. Results A total of 21 publications were included. SIR, SEIR and other models were used to predict the prevalence and evaluate the interventions. The results were predicted by SEIR+CAQ model were the closest to the actual situation. And the control measures have effectively restrained COVID-19. Conclusion Characteristics of COVID-19 and prevention measures should be concerned, when predicting the epidemic trend of COVID-19.
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RESUMO Os aterros sanitários (ASs) são considerados uma das soluções mais utilizadas para a disposição final de resíduos sólidos urbanos (RSUs) em países em desenvolvimento. Entretanto, um dos problemas são os valores elevados de deslocamentos verticais (recalques), pois os resíduos são muito compressíveis, sofrem degradação com o tempo e, consequentemente, podem ocasionar danos nos sistemas estruturais dos ASs. O objetivo do trabalho foi avaliar os recalques de dois ASs verificando a eficiência de alguns modelos de previsão de recalques. A avaliação foi realizada nos ASs de Minas do Leão e de São Leopoldo, comparando os recalques medidos com os previstos e ajustando os modelos utilizados com base nos dados históricos. A partir das análises realizadas, foi possível verificar que os quatro modelos analisados obtiveram boa aderência entre os valores medidos e previstos.
ABSTRACT Landfills are considered one of the best solutions for the disposal of municipal solid waste (MSW) in developing countries. However, one problem is the high values of vertical displacements (settlements), because the residues are very compressible and undergo degradation with time and consequently may cause damage to structural systems landfill. Theobjective is to evaluate the settlements of two landfills checking the efficiency of some settlements prediction models. The evaluation was performed in Minas do Leão and São Leopoldo Landfills, comparing the measured settlements with the predicted and adjusting the models used based on historical data. From the analyzes, we found that the four analyzed models showed good adhesion between the measured and predicted values.
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@#Acute kidney injury (AKI) is a complication with high morbidity and mortality after cardiac surgery. In order to predict the incidence of AKI after cardiac surgery, many risk prediction models have been established worldwide. We made a detailed introduction to the composing features, clinical application and predictive capability of 14 commonly used models. Among the 14 risk prediction models, age, congestive heart failure, hypertension, left ventricular ejection fraction, diabetes, cardiac valve surgery, coronary artery bypass grafting (CABG) combined with cardiac valve surgery, emergency surgery, preoperative creatinine, preoperative estimated glomerular filtration rate (eGFR), preoperative New York Heart Association (NYHA) score>Ⅱ, previous cardiac surgery, cadiopulmonary bypass (CPB) time and low cardiac output syndrome (LCOS) are included in many risks prediction models (>3 times). In comparison to Mehta and SRI models, Cleveland risk prediction model shows the best discrimination for the prediction of renal replacement therapy (RRT)-AKI and AKI in the European. However, in Chinese population, the predictive ability of the above three risk prediction models for RRT-AKI and AKI is poor.
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Introducción: teniendo en cuenta los diversos factores relacionados con el pronóstico adverso en pacientes con síndrome coronario agudo sin elevación del segmento ST, es importante determinarlos que se relacionan con aumento en la tasa de eventos. Objetivo: desarrollar un modelo de predicción a corto plazo en pacientes con síndrome coronario agudo sin elevación del segmento ST, con base en las escalas TIMI y GRACE, que incluya otras variables predictoras. Metodología: estudio observacional, analítico, de cohorte prospectiva, de desarrollo de un modelo de regresión logística, en pacientes mayores de 18 años con diagnóstico de síndrome coronario agudo sin elevación del segmento ST, que ingresan a dos centros con unidad de cuidados coronarios. Se construyeron modelos de predicción con las escalas de riesgo GRACE y TIMI como modelos independientes (modelo nulo), y comparados con un modelo de dos o tres variables formado por cada una de las escalas asociado a la creatinina y la fracción de eyección (Modelo completo). El desenlace evaluado fue el compuesto de muerte, reinfarto, ACV y sangrado. Resultados: se recolectaron datos de 422 pacientes que ingresaron con impresión diagnóstica de SCA sin elevación del segmento ST y tuvieron seguimiento al menos durante el primer mes posterior el evento. El promedio de edad fue de 64.36 ± 11.9 años, el 54.1% fueron hombres y la mayoría ingresaron con diagnóstico de infarto sin elevación del segmento ST (52.7%). La mayoría de los pacientes ingresaron en Killip I (90.8%) y el acceso vascular para el cateterismo fue radial en el 57.7%. La discriminación de los dos modelos es adecuada con estadístico C de 0.65 para TIMI y 0.69 para GRACE. La comparación de las dos curvas ROC no demuestra diferencias estadísticamente significativas (p=0.39). Los modelos completos demuestran mejor poder predictivo; sin embargo la diferencia no es significativa. Los dos modelos finales muestran adecuada calibración (Hosmer Lemershow p=0.96 para la escala TIMI y 0.86 para la escala GRACE). Conclusión: en pacientes con síndrome coronario agudo sin elevación del segmento ST los modelos basados en las escalas TIMI y GRACE predicen adecuadamente el riesgo de eventos a corto plazo. (Acta Med Colomb 2015; 40: 109-117).
Introduction: considering the various factors associated with adverse prognosis in patients with acute coronary syndrome without ST-segment elevation, is important to identify those factors associated with an increase in the rate of events. Objective: to develop a prediction model of short-term risk in patients with acute coronary syndrome without ST segment elevation, based on the TIMI and GRACE scales, including other predictor variables. Methodology: observational, analytical, prospective cohort study of development of a logistic regression model, in patients older than 18 years diagnosed with acute coronary syndrome without ST segment elevation, entering two coronary care unit centers. Prediction models were constructed with risk scales GRACE and TIMI as independent models (null model), and compared with a modelof 2 or 3 variables formed by each of the scales associated with creatinine and ejection fraction (full Model ) .The outcome evaluated was the composite of death, re-infarction, stroke and bleeding.Results: data from 422 patients admitted with diagnostic impression of ACS without ST-segment elevation who were followed for at least the first month after the event, were collected. The average age was 64.36 ± 11.9 years. 54.1% were men and most were admitted with diagnosis of myocardial infarction without ST segment elevation (52.7%). Most patients were admitted in Killip I (90.8%) and vascular access for catheterization was radial at 57.7%. Discrimination of the two models is adequate with C statistic of 0.65 for TIMI and 0.69 for GRACE. Comparison of the two ROC curves shows no statistically significant difference (p = 0.39). Complete models show better predictive power, but the difference is not significant. The final two models show proper calibration (p = 0.96 HosmerLemershow for the TIMI scale and 0.86 for the GRACE scale). Conclusion: in patients with acute coronary syndrome without ST-segment elevation models based on the TIMI and GRACE scales adequately predict the risk of short-term events. (Acta MedColomb 2015; 40: 109-117).
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Humans , Male , Adult , Acute Coronary Syndrome , Weights and Measures , Coronary Care Units , Vascular Access Devices , Non-ST Elevated Myocardial Infarction , ForecastingABSTRACT
Objective To compare the consistency in the measurement of percentage of body fat(PBF) by multi-frequency bioelectrical impedance analysis (MF-BIA) and dual energy X-ray absorptiometry(DXA)in overweight and obese adults in China,and provide evidence for the accurate MF-BIA application in China. Methods A total of 1 323 overweight/obese adults aged 22-55 years were recruited in this study. All the subjects received PBF measurement by both MF-BIA and DXA. The consistency in PBF measurement by MF-BIA and DXA was evaluated by using interclass correlation coefficients(ICC),then the correction prediction models was established. Results The differences in PBF measurement in male subjects and female subjects between MF-BIA and DXA were statistical significant (all P<0.01),the mean difference values were-6.5% for overweight males and -4.3% for obese males,-2.5% for overweight females and 0.5% for obese females, respectively. The difference in ICC of PBF between MF-BIA and DXA measurement were statistically significant in all subgroups (P<0.01). The ICC was 0.746 for overweight males,0.807 for obese males,0.628 for overweight females and 0.674 for obese females,respectively. The correction prediction models included:PBF(DXA)=13.425+0.719 × PBF(MF-BIA)for overweight males;PBF(DXA)=12.572+0.741×PBF(MF-BIA)for obese males;PBF(DXA)=9.785+0.802× PBF (MF-BIA) for overweight females;PBF(DXA)=20.348+0.532 × PBF(MF-BIA) for obese females. Conclusion The consistency in PBF measurement in overweight/obese adults by MF-BIA and DXA was poor in China. Correction should be conducted when MF-BIA is used in the measurement of PBF.