Prediction of visceral leishmaniasis incidence using the Seasonal Autoregressive Integrated Moving Average model (SARIMA) in the state of Maranhão, Brazil / Previsão da incidência da leishmaniose visceral usando o modelo de média móvel integrado autorregressivo sazonal (SARIMA) no Maranhão, Brasil

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.

Comparison of methods for controlling acquiescence bias in balanced and unbalanced scales / Comparação de métodos para o controle do viés da aquiescência em escalas balanceadas e desbalanceadas / Comparación de métodos para controlar el sesgo de aquiescencia en escalas balanceadas y no balanceadas

Controlling acquiescence bias typically involves the application of positive and negative keyed items. However, little is known about the effect of balancing positive and negative items on bias control. The aim of this study was to compare three Confirmatory Factor Analysis models (without control, MIMIC, and Random Intercept) to recover the factor structure of unbalanced and balanced instruments, using simulated and real data (from an instrument that assesses Personality). By controlling for acquiescence, the results indicated that the performance of balanced scales was better than that of unbalanced scales, as well as in the absence of control for response bias, when considering balanced and unbalanced scales. Thus, this research suggests the possibility of controlling acquiescence through balanced instruments associated with the use of statistical methods in modeling.(AU)

O controle do viés de aquiescência normalmente envolve a aplicação de itens positivos e negativos. Contudo, pouco se sabe sobre o efeito do balanceamento entre itens positivos e negativos sobre o controle do viés. O objetivo deste estudo foi comparar três modelos de Análise Fatorial Confirmatória (sem controle, MIMIC e Intercepto Randômico) para recuperar a estrutura fatorial de instrumentos desbalanceados e balanceados, a partir de dados simulados e reais (procedentes de um instrumento que avalia Personalidade). Mediante o controle da aquiescência, os resultados indicaram que a performance de escalas balanceadas foi melhor do que de escalas desbalanceadas, bem como na ausência de controle desse viés de resposta, ao considerar as escalas balanceadas e desbalanceadas. Dessa maneira, esta pesquisa aponta para a possibilidade de controle de aquiescência por meio de instrumentos balanceados associada ao uso dos métodos estatísticos na modelagem.(AU)

El control del sesgo de aquiescencia involucra la aplicación de ítems positivos y negativos. Sin embargo, el efecto del equilibrio entre ítems positivos y negativos en el control del sesgo sigue siendo una pregunta abierta. En este sentido, el objetivo de este estudio fue comparar tres modelos de Análisis Factorial Confirmatorio (sin control, MIMIC e Intercepto Aleatorio) para recuperar la estructura factorial de instrumentos balanceados y desbalanceados, a partir de datos simulados y reales (a partir de un instrumento que evalúa personalidad). El control de este sesgo de respuesta indicó que el desempeño de escalas balanceadas fue mejor que el de escalas desbalanceadas, así como en la ausencia del control de la aquiescencia, al considerar escalas balanceadas y desbalanceadas. Por lo tanto, esta investigación sugiere la posibilidad de controlar este sesgo de respuesta por medio de instrumentos balanceados asociados con el uso de métodos estadísticos modelado.(AU)

Nonparametric item response models: a comparison on recovering true scores / Modelos de resposta ao item não-paramétricos: comparando a recuperação de escores verdadeiros / Modelos de respuesta al item no-paramétricos: comparando la recuperación de puntuaciones verdaderas

Nonparametric procedures are used to add flexibility to models. Three nonparametric item response models have been proposed, but not directly compared: the Kernel smoothing (KS-IRT); the Davidian-Curve (DC-IRT); and the Bayesian semiparametric Rasch model (SP-Rasch). The main aim of the present study is to compare the performance of these procedures in recovering simulated true scores, using sum scores as benchmarks. The secondary aim is to compare their performances in terms of practical equivalence with real data. Overall, the results show that, apart from the DC-IRT, which is the model that performs the worse, all the other models give results quite similar to those when sum scores are used. These results are followed by a discussion with practical implications and recommendations for future studies.(AU)

Procedimentos não paramétricos são usados para adicionar flexibilidade aos modelos. Três modelos não paramétricos de resposta ao item foram propostos, mas não comparados diretamente: o Kernel smoothing (KS-IRT); a Curva Davidiana (DC-IRT); e o modelo semiparamétrico Rasch Bayesiano (SP-Rasch). O objetivo principal do presente estudo é comparar o desempenho desses procedimentos na recuperação de escores verdadeiros simulados, utilizando escores de soma como benchmarks. O objetivo secundário é comparar seus desempenhos em termos de equivalência prática com dados reais. De forma geral, os resultados mostram que, além do DC-IRT, que é o modelo que apresenta o pior desempenho, todos os outros modelos apresentam resultados bastante semelhantes aos de quando se usam somatórios. Esses resultados são seguidos de uma discussão com implicações práticas e recomendações para estudos futuros.(AU)

Se utilizan procedimientos no paramétricos para agregar flexibilidad a los modelos. Se propusieron tres modelos de respuesta al ítem no paramétricos, pero no se compararon directamente: Kernel smoothing (KS-IRT); la curva davidiana (DC-IRT); y el modelo bayesiano de Rasch semiparamétrico (SP-Rasch). El objetivo principal del presente estudio es comparar el desempeño de estos procedimientos en la recuperación de puntajes verdaderos simulados, utilizando puntajes de suma como puntos de referencia. El objetivo secundario es comparar su desempeño en términos de equivalencia práctica con datos reales. En general, los resultados muestran que, a excepción de DC-IRT, que es el modelo con peor desempeño, todos los otros modelos presentan resultados bastante similares a los obtenidos cuando se utilizan sumatorios. Estos resultados son seguidos por una discusión con implicaciones prácticas y recomendaciones para estudios futuros.(AU)

Análisis de la heterogeneidad en revisiones sistemáticas de cardiología publicadas entre 2000-2005 y 2011-2016 / Analysis of heterogeneity in cardiology systematic reviews published be-tween 2000-2005 and 2011-2016 / Análise da heterogeneidade em revisões sistemáticas de cardiologia publicadas entre 2000-2005 e 2011-2016

Introducción: la cardiología es una de las especialidades médicas que cuenta con más revisiones sistemáticas y metanálisis. Estudiar la metodología de las revisiones y anali­zar su heterogeneidad estadística es fundamental para garantizar su validez científica. Objetivo: describir la comparación de medidas de asociación, modelos estadísticos y grado de heterogeneidad en metanálisis de revisiones sistemáticas de intervenciones farmacológicas en cardiología, publicadas entre 2000-2005 y 2011-2016. Metodología: estudio analítico basado en la descripción y comparación de métodos estadísticos de revisiones sistemáticas de intervenciones farmacológicas en cardiología, publicadas en la biblioteca Cochrane. Para las variables cualitativas se estimaron frecuen­cias absolutas y relativas, mientras que para las cuantitativas se determinaron medias y desviaciones estándar, o medianas y rangos intercuartílicos, según su distribución. Para establecer la diferencia de medias se realizó la prueba t de Student y para la diferencia de proporciones el Chi cuadrado. Resultados: se incluyeron 54 revisiones sistemáticas, con un total de 1053 metanálisis, 6 revisiones con 240 metanálisis entre 2000-2005 y 48 revisiones con 813 metanálisis entre 2011-2016. La mayoría de metanálisis utilizaron el tratamiento estándar como grupo de comparación (56.6%), midieron desenlaces cualitativos nominales (86.3%), determinaron riesgos relativos (63.3%) y aplicaron modelos de efectos fijos (57.8%). En 2011-2016 se encontró una media del Índice de Higgins 17.5 menor que en 2000-2005 (p<0.05). Conclusión: se evidenció una disminución de la heterogeneidad estadística y un aumento en la implementación de modelos de efectos aleatorios, lo que da cuenta de una mayor rigurosidad a la hora de demostrar resultados verdaderamente significativos.

Introduction: cardiology is one of the medical specialties with the most systematic reviews and meta-analyses. Studying the methodology of the reviews and analyzing their statistical heterogeneity is essential to guarantee their scientific validity. Objective: to describe the comparison of association measures, statistical models and degree of heterogeneity in meta-analyses of systematic reviews of pharmacological interventions in cardiology, published between 2000-2005 and 2011-2016. Methodology: analytical study based on the description and comparison of statistical methods of systematic reviews of pharmacological interventions in cardiology, published in the Cochrane library. For the qualitative variables, absolute and relative frequencies were estimated, while for the quantitative ones, means and standard deviations, or medians and interquartile ranges, were determined, depending on their distribution. The Student's t test was used to establish the difference in means and the Chi square for the difference in proportions. Results: 54 systematic reviews were included, with a total of 1.053 meta-analyses, 6 reviews with 240 meta-analyses between 2000-2005, and 48 reviews with 813 meta-analyses between 2011-2016. Most meta-analyses used standard treatment as the comparison group (56.6%), measured nominal qualitative outcomes (86.3%), determined relative risks (63.3%), and applied fixed-effect models (57.8%). In the 2011-2016 period, an average of the Higgins Index was found to be 17.5 lower than in the 2000-2005 (p<0.05). Conclusion: there was evidence of a decrease in statistical heterogeneity and an increase in the implementation of random effects models, which accounts for greater rigor when it comes to demonstrating truly significant results.

Introdução: a cardiologia é uma das especialidades médicas com mais revisões sistemáticas e metanálises. Estudar a metodologia das revisões e analisar sua heterogeneidade estatística é essencial para garantir sua validade científica. Objetivo: descrever a comparação de medidas de associação, modelos estatísticos e grau de heterogeneidade em metanálises de revisões sistemáticas de intervenções farmacológicas em cardiologia, publicadas entre 2000-2005 e 2011-2016. Metodologia: estudo analítico baseado na descrição e comparação de métodos estatísticos de revisões sistemáticas de intervenções farmacológicas em cardiologia, publicadas na biblioteca Cochrane. Para as variáveis qualitativas foram estimadas frequências absolutas e relativas, enquanto para as quantitativas foram determinadas médias e desvios padrão, ou medianas e intervalos interquartis, dependendo de sua distribuição. O teste t de Student foi utilizado para estabelecer a diferença de médias e o qui-quadrado para a diferença de proporções. Resultados: foram incluídas 54 revisões sistemáticas, com um total de 1053 meta-análises, 6 revisões com 240 meta-análises entre 2000-2005 e 48 revisões com 813 meta-análises entre 2011-2016. A maioria das metanálises usou tratamento padrão como grupo de comparação (56.6%), mediu resultados qualitativos nominais (86.3%), determinou riscos relativos (63.3%) e aplicou modelos de efeito fixo (57.8%). Em 2011-2016, a média do Índice de Higgins foi 17.5 menor do que em 2000-2005 (p<0.05). Conclusão: evidenciou-se uma diminuição da heterogeneidade estatística e um aumento da implementação de modelos de efeitos aleatórios, o que confere maior rigor na demonstração de resultados verdadeiramente significativos.

ARIMA model in predicting of COVID-19 epidemic for the Southern Africa region

Background: Coronavirus pandemic, a serious global public health threat, affects the Southern African countries more than any other country on the continent. The region has become the epicenter of the coronavirus with South Africa accounting for the most cases. To cap the deadly effect caused by the pandemic, we apply a statistical modelling approach to investigate and predict COVID-19 incidence. Methods: Using secondary data on the daily confirmed COVID-19 cases per million for Southern Africa Development Community (SADC) member states from March 5, 2020, to July 15, 2021, we model and forecast the spread of coronavirus in the region. We select the best ARIMA model based on the log-likelihood, AIC, and BIC of the fitted models. Results: The ARIMA (11,1,11) model for the complete data set was finally selected among ARIMA models based upon the parameter test and the Box­Ljung test. The ARIMA (11,1,9) was the best candidate for the training set. A 15-day forecast was also made from the model, which shows a perfect fit with the testing set. Conclusion: The number of new COVID-19 cases per million for the SADC shows a downward trend, but the trend is characterized by peaks from time to time. Tightening up of the preventive measures continuously needs to be adapted in order to eradicate the coronavirus epidemic from the population.

Establishment and validation of clinical prediction model for steroid-resistant nephrotic syndrome in children / 中华儿科杂志

Objective: To identify the clinically relevant factors of steroid-resistant nephrotic syndrome (SSNS) in children and establish a predictive model followed by verifying its feasibility. Methods: A retrospective analysis was performed in a total of 111 children with nephrotic syndrome admitted to Children's Hospital of ShanXi from January 2016 to December 2021. The clinical data of general conditions, manifestations, laboratory tests, treatment, and prognosis were collected. According to the steroid response, patients were divided into SSNS and steroid resistant nephrotic syndrome (SRNS) group. Single factor Logistic regression analysis was used for comparison between the 2 groups, and variables with statistically significant differences were included in multivariate Logistic regression analysis. The multivariate Logistic regression analysis was used to identify the related variables of children with SRNS. The area under the receiver operating characteristic curve (ROC), the calibration curve and the clinical decision curve were used to evaluate its effectiveness of the variables. Results: Totally 111 children with nephrotic syndrome was composed of 66 boys and 45 girls, aged 3.2 (2.0, 6.6) years. There were 65 patients in the SSNS group and 46 in the SRNS group.Univariate Logistic regression analysis showed that the 6 variables, including erythrocyte sedimentation rate, 25-hydroxyvitamin D, suppressor T cells, D-dimer, fibrin degradation products, β2-microglobulin, had statistically significant differences between SSNS and SRNS groups (85 (52, 104) vs. 105 (85, 120) mm/1 h, 18 (12, 39) vs. 16 (12, 25) nmol/L, 0.23 (0.19, 0.27) vs. 0.25 (0.20, 0.31), 0.7 (0.6, 1.1) vs. 1.1 (0.9, 1.7) g/L, 3.1 (2.3, 4.1) vs. 3.3 (2.7, 5.8) g/L, 2.3 (1.9,2.8) vs. 3.0 (2.5, 3.7) g/L, χ2=3.73, -2.42, 2.24, 3.38, 2.24,3.93,all P<0.05), were included in the multivariate Logistic regression analysis. Finally, we found that 4 variables including erythrocyte sedimentation rate, suppressor T cells, D-dimer and β2-microglobulin (OR=1.02, 1.12, 25.61, 3.38, 95%CI 1.00-1.04, 1.03-1.22, 1.92-341.04, 1.65-6.94, all P<0.05) had significant correlation with SRNS. The optimal prediction model was selected. The ROC curve cut-off=0.38, with the sensitivity of 0.83, the specificity of 0.77 and area under curve of 0.87. The calibration curve showed that the predicted probability of SRNS group occurrence was in good agreement with the actual occurrence probability, χ2=9.12, P=0.426. The clinical decision curve showed good clinical applicability. The net benefit is up to 0.2. Make the nomogram. Conclusions: The prediction model based on the 4 identified risk factors including erythrocyte sedimentation rate, suppressor T cells, D-dimer and β2-microglobulin was suitable for the early diagnosis and prediction of SRNS in children. The prediction effect was promising in clinical application.

Building of a Clinical Prediction Model for Hemodynamic Depression after Carotid Artery Stenting / 中国医学科学院学报

Objective To analyze the risk factors and build a clinical prediction model for hemodynamic depression (HD) after carotid artery stenting (CAS). Methods A total of 116 patients who received CAS in the Department of Vascular Surgery,Drum Tower Clinical College of Nanjing Medical University and the Department of Vascular Surgery,the Affiliated Suqian First People's Hospital of Nanjing Medical University from January 1,2016 to January 1,2022 were included in this study.The patients were assigned into a HD group and a non-HD group.The clinical baseline data and vascular disease characteristics of each group were collected,and multivariate Logistic regression was employed to identify the independent predictors of HD after CAS and build a clinical prediction model.The receiver operating characteristic (ROC) curve was drawn,and the area under the ROC curve (AUC) was calculated to evaluate the predictive performance of the model. Results The HD group had lower proportions of diabetes (P=0.014) and smoking (P=0.037) and higher proportions of hypertension (P=0.031),bilateral CAS (P=0.018),calcified plaque (P=0.001),eccentric plaque (P=0.003),and the distance<1 cm from the minimum lumen level to the carotid bifurcation (P=0.009) than the non-HD group.The age,sex,coronary heart disease,symptomatic carotid artery stenosis,degree of stenosis,and length of lesions had no statistically significant differences between the HD group and the non-HD group (all P>0.05).Based on the above predictive factors,a clinical prediction model was established,which showed the AUC of 0.807 and the 95% CI of 0.730-0.885 (P<0.001).The model demonstrated the sensitivity of 62.7% and the specificity of 87.7% when the best cut-off value of the model score reached 12.5 points. Conclusions Diabetes,smoking,calcified plaque,eccentric plaque,and the distance<1 cm from the minimum lumen level to the carotid bifurcation are independent predictors of HD after CAS.The clinical prediction model built based on the above factors has good performance in predicting the occurrence of HD after CAS.

Preliminary exploration of clinical prediction model of severe swallowing disorder after acute ischemic stroke based on nomogram model / 中华危重病急救医学

OBJECTIVE@#To establish a predictive model for severe swallowing disorder after acute ischemic stroke based on nomogram model, and evaluate its effectiveness.@*METHODS@#A prospective study was conducted. The patients with acute ischemic stroke admitted to Mianyang Central Hospital from October 2018 to October 2021 were enrolled. Patients were divided into severe swallowing disorder group and non-severe swallowing disorder group according to whether severe swallowing disorder occurred within 72 hours after admission. The differences in general information, personal history, past medical history, and clinical characteristics of patients between the two groups were compared. The risk factors of severe swallowing disorder were analyzed by multivariate Logistic regression analysis, and the relevant nomogram model was established. The bootstrap method was used to perform self-sampling internal validation on the model, and consistency index, calibration curve, receiver operator characteristic curve (ROC curve), and decision curve were used to evaluate the predictive performance of the model.@*RESULTS@#A total of 264 patients with acute ischemic stroke were enrolled, and the incidence of severe swallowing disorder within 72 hours after admission was 19.3% (51/264). Compared with the non-severe swallowing disorder group, the severe swallowing disorder group had a higher proportion of patients aged of ≥ 60 years old, with severe neurological deficits [National Institutes of Health stroke scale (NIHSS) score ≥ 7], severe functional impairments [Barthel index, an activity of daily living functional status assessment index, < 40], brainstem infarction and lesions ≥ 40 mm (78.43% vs. 56.81%, 52.94% vs. 28.64%, 39.22% vs. 12.21%, 31.37% vs. 13.62%, 54.90% vs. 24.41%), and the differences were statistically significant (all P < 0.01). Multivariate Logistic regression analysis showed that age ≥ 60 years old [odds ratio (OR) = 3.542, 95% confidence interval (95%CI) was 1.527-8.215], NIHSS score ≥ 7 (OR = 2.741, 95%CI was 1.337-5.619), Barthel index < 40 (OR = 4.517, 95%CI was 2.013-10.136), brain stem infarction (OR = 2.498, 95%CI was 1.078-5.790) and lesion ≥ 40 mm (OR = 2.283, 95%CI was 1.485-3.508) were independent risk factors for severe swallowing disorder after acute ischemic stroke (all P < 0.05). The results of model validation showed that the consistency index was 0.805, and the trend of the calibration curve was basically consistent with the ideal curve, indicating that the model had good prediction accuracy. ROC curve analysis showed that the area under the ROC curve (AUC) predicted by nomogram model for severe swallowing disorder after acute ischemic stroke was 0.817 (95%CI was 0.788-0.852), indicating that the model had good discrimination. The decision curve showed that within the range of 5% to 90%, the nomogram model had a higher net benefit value for predicting the risk of severe swallowing disorder after acute ischemic stroke, indicating that the model had good clinical predictive performance.@*CONCLUSIONS@#The independent risk factors of severe swallowing disorder after acute ischemic stroke include age ≥ 60 years old, NIHSS score ≥ 7, Barthel index < 40, brainstem infarction and lesion size ≥ 40 mm. The nomogram model established based on these factors can effectively predict the occurrence of severe swallowing disorder after acute ischemic stroke.

Analysis of Clinical Data and Construction of A Diagnostic Prediction Model for Metabolic Syndrome after Single-Center Hematopoietic Stem Cell Transplantation / 中国实验血液学杂志

UNLABELLED@#AbstractObjective: To analysis the clinical data of patients after single-center hematopoietic stem cell transplantation (HSCT) and construct a predictive model for metabolic syndrome (MS) diagnosis.@*METHODS@#Ninety-three hematology patients who underwent HSCT at the First Hospital of Lanzhou University from July 2015 to September 2022 were selected to collect basic data, transplantation status and postoperative data, the clinical characteristics of patients with and without MS after transplantation were compared and analyzed. Logistic regression model was used to analyze the influence fators of MS after transplantation, and a predictive model of HSCT-MS diagnosis was constructed under the influence of independent influence factors. The model was evaluated using the ceceiver operating characteristic curve (ROC curve).@*RESULTS@#Metabolic syndrome occurred in 36 of 93 HSCT patients and did not occur in 57. Compared with non-HSCT-MS group, HSCT-MS had significantly higher fasting blood glucose (FBG) levels before transplantation, shorter course before transplantation, and higher bilirubin levels after transplantation (P<0.05). The statistically significant clinical indicators were subjected to multi-factor logistic regression analysis, and the results showed that pre-transplant high FBG, pre-transplant short disease course and post-transplant high bilirubin were independent influence factors for HSCT-MS. The standard error of predicting the occurrence of HSCT-MS based on the clinical model was 0.048, the area under the curve AUC=0.776, 95% CI :0.683-0.869, the optimal threshold was 0.58 based on the Jorden index at maximum, the sensitivity was 0.694, and the specificity was 0.772, which has certain accuracy.@*CONCLUSION@#A clinical prediction model for HSCT-MS based on logistic regression analysis is constructed through the analysis of clinical data, which has certain clinical value.

Hidatidosis pulmonar: comparación de los resultados de la cirugía con y sin capitonaje mediante Propensity Score Matching / Pulmonary hydatidosis: comparison results of surgery with capitonnage versus surgery without capitonnage using Propensity Score Matching

Resumen Introducción: El tratamiento de elección del Quiste Hidatídico Pulmonar (QHP) es la resección quirúrgica. Actualmente, existe controversia sobre la superioridad de la cirugía con capitonaje (CC) versus la cirugía sin capitonaje (SC). Objetivo: Comparar los resultados de la cirugía conservadora CC y SC mediante Propensity Score Matching (PSM). Materiales y Método: Se realizó un estudio analítico retrospectivo de los pacientes con QHP tratados quirúrgicamente en el Hospital Guillermo Grant Benavente, Concepción, Chile; entre enero-1995 y diciembre-2018. Se realizó un PSM con una relación 1:1 entre los pacientes operados con la técnica CC y SC. Posterior al PSM se balancearon las características basales. Resultados: Total 205 episodios de QHP en el período. Se realizó cirugía conservadora en 165 casos, 101 CC y 64 SC. Posterior al emparejamiento se obtuvieron 53 pacientes operados CC y 53 SC. No se observaron diferencias significativas en la presencia de fuga aérea persistente (CC = 9,4%; SC = 11,3%, p 0,75), empiema (CC = 3,8%; SC = 0%, p 0,49), días con pleurotomía (CC = 9,1 ± 8,9; SC 10,1 ± 10,7, p 0,39, mediana 6 versus 6 días, respectivamente), ni días de estadía posoperatoria (CC = 10,4 ± 9,0; SC = 11,7 ± 11,9, p 0,22, mediana 7 versus 7 días, respectivamente). Conclusiones: La cirugía SC demostró resultados comparables a la técnica CC en el tratamiento quirúrgico conservador del QHP.

Background: The treatment of choice for Pulmonary Hydatid Cys (PHC) is surgical resection. There is currently controversy about the superiority of surgery with capitonage (SC) versus surgery without it (SWC). Aim: To compare the results of conservative surgery with capitonnage and versus surgery without capitonnage using Propensity Score Matching (PSM). Materials and Method: A retrospective analytical study was carried out with patients with PHC treated surgically at the Guillermo Grant Benavente Hospital, Concepción, Chile, between January-1995 and December-2018. A PSM was performed with a 1:1 ratio. Results: Conservative surgery was done in 165 cases, 101 SC and 64 SWC. After matching, 53 SC and 53 SWC operated patients were obtained. No significant differences were observed in the presence of persistent air leak (9.4% vs11.3%, SC vs SWC respectively, p 0.75), empyema (3.8% vs 0%, p 0.49), days with pleurotomy (9.1 ± 8.9 vs 10.1 ± 10.7, p 0.39), nor days of postoperative stay (10.4 ± 9.0 vs 11.7 ± 11.9, p 0.22). Conclusión: The SWC demonstrated comparable results to the SC technique in the conservative surgical treatment of PHC.

El Enfoque Bayesiano en las Ciencias de la Salud / The Bayesian Approach in the Health Sciences

En estadística existen dos enfoques básicos, la estadística frecuentista que es la corriente principal y la estadística bayesiana. La mayoría de los principales métodos estadísticos son frecuentistas siendo el enfoque bayesiano más desconocido entre los investigadores. En el presente artículo se exponen los fundamentos lógicos del enfoque bayesiano y su uso mediante un ejemplo de aplicación. En este contexto, más que presentar un debate entre la lógica clásica y la bayesiana, se pretende mostrar de manera introductoria las enormes posibilidades que el enfoque bayesiano puede aportar a la investigación en las Ciencias de la Salud.

In the stadistic field there are two basic approaches, the Frequentist Statistics which is the primary one, and the Bayesian Statistics. The most used statistical methods are the Frequentist methods, being the Bayesian approach the most popular among researchers. In this article, the logical basis of the Bayendian approach and its use are exposed through an application example. In this context, rather than presenting a debate between the classic and the Bayensian logic, it is intended to demonstrate in an introductory method the considerable possibilities how Bayesian approach can contribute to Health and Sciences research.

Emprego do modelo matemático SEIHDR para auxiliar gestores na estimativa de ocupação de leitos de UTI em uma pandemia: simulação para pacientes com COVID-19 no município de Porto Alegre / Use of the SEIHDR mathematical model to assist health managers in estimating ICU bed occupancy in a pandemic: simulation for patients with COVID-19 in the city of Porto Alegre, Brazil

Introdução: A pandemia de COVID-19, no Brasil, constituiu uma ameaça ao sistema de saúde pelo risco de esgotamento dos leitos de Unidade de Terapia Intensiva (UTI). O objetivo do estudo foi projetar a ocupação de leitos de UTI com casos de COVID-19 no pico em Porto Alegre. Para isso, resolvemos utilizar uma ferramenta matemática com parâmetros da pandemia desta cidade.Métodos:Utilizamos o modelo matemático SEIHDR. Analisamos os casos de hospitalização por COVID-19 em Porto Alegre e RS até 3 de agosto de 2020 a fim de extrair os parâmetros locais para construir uma curva epidemiológica do total de casos prevalentes hospitalizados em UTI. Também analisamos as taxas de reprodução básica (R0) e reprodução efetiva (Re).Resultados: O modelo matemático projetou um pico de 344 casos prevalentes, em UTI, para o dia 22 de agosto de 2020. Calculamos 1,56 para o R0 e 1,08 no dia 3 de agosto para o Re.Conclusão: O modelo matemático simulou uma primeira onda de casos ocupando leitos de UTI muito próxima dos dados reais. Também indicou corretamente uma queda no número de casos nos dois meses subsequentes. Apesar das limitações, as estimativas do modelo matemático forneceram informações sobre as dimensões temporal e numérica de uma pandemia que poderiam ser usadas como auxílio aos gestores de saúde na tomada de decisões para a alocação de recursos frente a calamidades de saúde como o surto de COVID-19 no Brasil.

Introduction: The COVID-19 pandemic in Brazil has been a threat to health services due to the risk of bed shortage in the intensive care unit (ICU). This study aimed to estimate the bed occupancy at the ICU with patients with COVID-19 during the peak of the pandemic in Porto Alegre, capital of Rio Grande do Sul (RS), the southernmost state of Brazil. To this end, we used a mathematical model with pandemic parameters from the city.Methods: We used the SEIHDR mathematical model. We analyzed hospitalizations for COVID-19 in Porto Alegre and RS until August 3, 2020, to extract local parameters to create an epidemiological curve of the total number of prevalent cases in the ICU. We also analyzed the basic reproduction rate (R0) and effective reproduction rate (Re). Results: The mathematical model estimated a peak of 344 prevalent cases in the ICU on August 22, 2020. The model calculated an R0 of 1.56 and Re of 1.08 on August 3, 2020.Conclusion: The mathematical model accurately estimated the first peak of cases in the ICU. Also, it correctly indicated a drop in the number of cases in the following two months. Despite the limitations, the mathematical model estimates provided information on the temporal and numerical dimensions of a pandemic that could be used to assist health managers in making decisions on the allocation of resources in a state of public calamity such as the COVID-19 outbreak in Brazil.

Statistical modeling for analyzing grain yield of durum wheat under rainfed conditions in Azad Jammu Kashmir, Pakistan / Modelagem estatística para analisar o rendimento de grãos de trigo durum sob condições de chuva em Azad Jammu Kashmir, Paquistão

One of the most important traits that plant breeders aim to improve is grain yield which is a highly quantitative trait controlled by various agro-morphological traits. Twelve morphological traits such as Germination Percentage, Days to Spike Emergence, Plant Height, Spike Length, Awn Length, Tillers/Plant, Leaf Angle, Seeds/Spike, Plant Thickness, 1000-Grain Weight, Harvest Index and Days to Maturity have been considered as independent factors. Correlation ,regression, and principal component analysis (PCA) are used to identify the different durum wheat traits, which significantly contribute to the yield. The necessary assumptions required for applying regression modeling have been tested and all the assumptions are satisfied by the observed data. The outliers are detected in the observations of fixed traits and Grain Yield. Some observations are detected as outliers but the outlying observations did not show any influence on the regression fit. For selecting a parsimonious regression model for durum wheat, best subset regression, and stepwise regression techniques have been applied. The best subset regression analysis revealed that Germination Percentage, Tillers/Plant, and Seeds/Spike have a marked increasing effect whereas Plant thickness has a negative effect on durum wheat yield. While stepwise regression analysis identified that the traits, Germination Percentage, Tillers/Plant, and Seeds/Spike significantly contribute to increasing the durum wheat yield. The simple correlation coefficient specified the significant positive correlation of Grain Yield with Germination Percentage, Number of Tillers/Plant, Seeds/Spike, and Harvest Index. These results of correlation analysis directed the importance of morphological characters and their significant positive impact on Grain Yield. [...].

Uma das características mais importantes que os produtores de plantas visam melhorar é o rendimento de grãos, que é uma particularidade altamente quantitativa e controlada por várias características agromorfológicas. Foram considerados 12 traços morfológicos como fatores independentes, como Porcentagem de Germinação, Dias para Emergência da Espiga, Altura da Planta, Comprimento da Espiga, Comprimento da Aresta, Perfilhos /Planta, Ângulo da Folha, Sementes /Espiga, Espessura da Planta, Peso de 1000 Grãos, Índice de Colheita e Dias até a Maturidade. A correlação, regressão e análise de componentes principais (em inglês Principal Component Analysis (PCA)) são usadas para identificar as diferentes características do trigo duro, que contribuem significativamente para o rendimento. As suposições necessárias exigidas para a aplicação da modelagem de regressão foram testadas e todas as suposições são adequadas de acordo com os dados observados. Os outliers são detectados nas observações de características fixas e rendimento de grãos. Algumas observações são detectadas como outliers, mas as observações outliers não mostraram qualquer influência no ajuste da regressão. Para selecionar um modelo de regressão parcimonioso para o trigo duro, foram aplicadas tanto a melhor regressão de subconjunto quanto as técnicas de regressão stepwise. A melhor análise de regressão de subconjunto revelou que a porcentagem de germinação, perfilhos /planta e sementes /espiga tem um efeito de aumento acentuado, enquanto a espessura da planta tem um efeito negativo sobre o rendimento do trigo duro. Enquanto a análise de regressão passo a passo identificou que as características, porcentagem de germinação, perfilhos/planta e sementes /espiga contribuem significativamente para aumentar a produtividade do trigo duro. O coeficiente de correlação simples especificou a correlação positiva significativa do [...].

Progress in research on redistribution methods for garbage codes in causes of death data / 中华流行病学杂志

The existence of garbage codes in death cause surveillance data sets could influence the accuracy of the death cause statistics, and subsequently affect the precision and effectiveness of public health policy making. International and domestic researchers have studied the characteristics of garbage codes in various death cause data sets from different countries or regions in the world. They proposed several approaches for redistributing garbage codes, such as expert consultancy, fixed proportional reassignment, using the information about death cause chain, building statistical models, and so on. This paper summarizes and compares the principles, applications and limitation of application scenarios of currently common methods for garbage code redistribution in order to provide some references for improving the accuracy and usefulness of the death cause data in China.

A comparative study of multiple parallel mediation analysis methods / 中华流行病学杂志

Objective: To introduce and compare four analysis methods of multiple parallel mediation model, including pure regression method, method based on inverse probability weighting, extended natural effect model method and weight-based imputation strategies. Methods: For the multiple parallel mediation model, the simulation experiments of three scenarios were carried out to compare the performance of different methods in estimating direct and indirect effects in different situations. Dataset from UK Biobank was then analyzed by using the four methods. Results: The estimation biases of the regression method and the inverse probability weighting method were relatively small, followed by the extended natural effect model method, and the estimation results of the weight-based imputation strategies were quite different from the other three methods. Conclusions: Different multiple parallel mediation analysis methods have different application situations and their own advantages and disadvantages. The regression method is more suitable for continuous mediator, and the inverse probability weighting method is more suitable for binary mediator. The extended natural effect model method has better performances when the residuals of two parallel mediators are positively correlated and the correlation degree is small. The weight-based imputation strategies might not be appropriate for parallel mediation analysis. Therefore, appropriate methods should be selected according to the specific situation in practice.

Introduction of reduced rank regression and development of a user-written Stata package / 中华流行病学杂志

Reduced rank regression is an extended multivariate linear regression model with the function of dimension reduction. It has been more and more widely used in nutritional epidemiology research to understand people's dietary patterns in recent years. However, there has been no existing Stata package or command to implement reduced rank regression independently. Therefore, we developed a new user-written package named "rrr" for its implementation in Stata. This paper summarizes the methodology of reduced rank regression, the development and functions of the Stata rrr package and its application in the China Kadoorie Biobank dataset, with the aim of facilitating the future wide use of this statistical method in epidemiology and public health research.

A review of global and domestic HIV epidemic estimation / 中华流行病学杂志

Due to the latent characteristics of HIV infection, exceptionality of HIV high-risk population, social discrimination and insufficient awareness of AIDS prevention, timely testing and diagnosis of HIV infection is still a challenge worldwide. Until recently, it is difficult to exactly understand the overall HIV epidemic only using routine surveillance data. Therefore, epidemiological and statistical modeling is widely used to address this issue. Almost at the same time when AIDS was firstly discovered firstly, scientists also began to study the methods for the estimation and prediction of HIV infection epidemic. This article summarizes the development of global and domestic HIV epidemic estimation for the further understanding of its current performance and methods applied to provide reference for the future work.

Risk Factors for the Incidence of Dental Caries in Low, Very Low, and Extremely Low Birth Weight Children: A Cohort Study

Abstract Objective: To assess the incidence of caries in a two-year period among low birth weight (LBW), very low birth weight (VLBW), and extremely low birth weight (ELBW) children considering socioeconomic indicators, dietary factors and oral hygiene. Material and Methods: A convenience sample was formed of 42 low birth weight children aged two to five years at baseline. Two examiners diagnosed caries using the World Health Organization criteria. Birth weight, socioeconomic indicators and diet were collected from medical records and questionnaires. Binomial models were used to estimate unadjusted and adjusted rate ratios (RR) and respective 95% confidence intervals for the factors evaluated. Results: Thirty-six children were re-examined after two years. The incidence of dental caries was 36.7%. The dmft index was 0.44 (±1.25) at baseline and increased to 1.36 (±3.85) at follow-up. VLBW children (1,000 to 1,500 g) (RR=0.23; 95%CI: 0.08-0.72) and LBW children (1,500 to 2,500 g) (RR=0.06; 0.01-0.55) had fewer carious lesions compared to ELBW children (<1,000 g). Carious lesions were more frequent among children with a lower income (RR=6.05; 1.05-34.84) and less frequent among those who did not consume sweetened juice, tea or yogurt (RR: 0.21; 0.07-0.62). Conclusion: An inverse dose-response relation was found between birth weight and the incidence of caries. A lower income and the consumption of sweetened beverages were risk factors for the development of caries (AU).

Pronóstico de la tendencia de COVID-19 para 2021 en el noroeste de Argentina / COVID-19 prediction of tendency for 2021 in northwestern Argentina

RESUMEN Usando un modelo de regresión polinomial con retraso, que empleó datos de COVID-19 de 2020 con ausencia de vacunas, se realizó la predicción de COVID-19 en un escenario con administración de vacunas para Tucumán en 2021. La modelación incluyó la identificación de un punto de quiebre de contagios entre ambas series con la mejor correlación. Previamente, se indicó por medio de correlación cruzada el lag que sirvió para obtener el menor error entre los valores esperados y los observados. La validación del modelo fue realizada con datos reales. En 21 días fueron predichos 18.640 casos de COVID-19 de 20.400 casos informados. El pico máximo de COVID-19 fue estimado 21 días antes con la intensidad esperada.

ABSTRACT: Using a lagged polynomial regression model, which used COVID-19 data from 2020 with no vaccines, the prediction of COVID-19 was performed in a scenario with vaccine administration for Tucumán in 2021. The modeling included the identification of a contagion breaking point between both series with the best correlation. Previously, the lag that served to obtain the smallest error between the expected and observed values was indicated by means of cross correlation. The validation of the model was carried out with real data. In 21 days, 18,640 COVID-19 cases out of 20,400 reported cases were predicted. The maximum peak of COVID-19 was estimated 21 days in advance with the expected intensity.