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1.
Rev. argent. salud publica ; 12(Suplemento Covid-19): 1-7, 23 de Julio 2020.
Article in Spanish | LILACS (Americas), BINACIS, ARGMSAL | ID: biblio-1104047

ABSTRACT

La modelización matemática se utiliza desde hace más de 100 años para evaluar el impacto de las estrategias de intervención de salud pública y sugerir el curso de acción óptimo en la lucha contra las enfermedades infecciosas emergentes. La aparición del nuevo virus SARS-CoV-2 plantea un gran desafío para los planificadores y decisores en salud, que deben movilizar recursos finitos, reorganizar los sistemas de atención y tomar decisiones en un contexto de gran incertidumbre. Para afrontar la pandemia por COVID-19, muchos sistemas de salud incorporan información provista por modelos predictivos. Esto insta a revisar la evolución de los distintos tipos de modelos existentes, sus características, limitaciones y vinculación con la toma de decisiones en Argentina y otros países. Con ese objetivo, se realizó una búsqueda bibliográfica sobre los modelos publicados acerca de la evolución de la pandemia. Se analizó el número de proyectos conexos presentados a becas del Ministerio de Ciencia, Tecnología e Innovación. Se identificaron, clasificaron y describieron distintos tipos de modelos, como determinísticos y estocásticos, distintos modelos compartimentados, y se describió la teoría del umbral y características principales de los modelos, como el número reproductivo básico (R0). Se analizó la importancia de los supuestos de cada modelo y el abordaje de la incertidumbre. Se discutieron sus principales limitaciones y su vinculación con la toma de decisiones en provincias y regiones.


Subject(s)
Models, Statistical , Coronavirus Infections , Models, Theoretical
2.
Caracas; Observatorio Nacional de Ciencia, Tecnología e Innovación; 22 may. 2020. 15-23 p. tab, ilus.(Observador del Conocimiento. Revista Especializada en Gestión Social del Conocimiento, 5, 1).
Monography in Spanish | LILACS (Americas), LIVECS | ID: biblio-1119072

ABSTRACT

El presente trabajo plantea un modelo matemático capaz de reproducir la dinámica de transmisión del nuevo coronavirus (Covid-19) en grupos humanos a partir de un sistema de ecuaciones diferenciales. Para ello se dividió a la población en tres clases diferentes dependiendo de los estadios de la enfermedad: aquellos que son susceptibles de contraer el virus, los infectados y los recuperados. Los parámetros fueron determinados por mínimos cuadrados a partir de los registros diarios del Covid-19 realizados por la Universidad Johns Hopkins, y se validó en cuatro países seleccionados al azar: China, Estados Unidos, Brasil y Venezuela. Simultáneamente, se exploró la calidad de los datos para detectar cualquier manipulación o alteración de las cifras de contagios en estos cuatro países, a partir de dos metodologías computacionales empleadas en análisis forense de información digital. Así, será posible predecir grosso modo el número de contagios en el tiempo: a modo de ejemplo, se estimó que pudieran darse 597 casos de contagios en la República Bolivariana de Venezuela hasta el 22 de junio del presente año en función de la información analizada hasta el 20 de abril, fuertemente influenciada por los brotes detectados(AU)


The present work proposes a Mathematical model capable of reproducing the transmission dynamics of the new coronavirus (Covid-19) in human groups, from a system of differential equations. The total population was divided into three different types: susceptible, infected, and recovered. Parameters were developed using the least squared method, based on Johns Hopkins' Covid-19 data, and were validated in four countries: China, the United States, Brazil and Venezuela. Simultaneously, the quality of the data was explored to detect any manipulation or alteration of the numbers of infections in these four countries, based on two computational methodologies used in forensic analysis of digital information. Finally, it will be possible to estimate that 597 cases of infection could occur in the Bolivarian Republic of Venezuela, until June 22 of this year, based on the information analyzed up to April 20, heavily influenced by the detected break out(AU)


Subject(s)
Humans , Models, Statistical , Coronavirus Infections , Pandemics/prevention & control
3.
J. health med. sci. (Print) ; 6(1): 45-50, ene.-mar. 2020. tab, ilus
Article in Spanish | LILACS (Americas) | ID: biblio-1096716

ABSTRACT

Los métodos de clasificación permiten explorar y analizar grandes conjuntos de datos visualmente, lo cual es de gran utilidad para tomar decisiones rápidas. El objetivo fue comparar dos métodos de análisis de clúster para big data en variables demográficas de las provincias del Ecuador. Se hizo uso de un estudio observacional de tipo comparativo mediante la representación simultanea del HJ-Biplot y el método Two Step (clúster bietápico), a través del software MultBiplot y SPSS. Los datos corresponden a variables demográficas de interés sociosanitarias tasa de mortalidad general, tasa de mortalidad infantil, tasa de natalidad, densidad poblacional, porcentaje urbano y esperanza de vida, medidas en las provincias del Ecuador. Se utilizaron datos provenientes del Instituto de Estadísticas y Censos INEC. Se analizó la asociación entre variables y se identificaron clústeres de las provincias del Ecuador según estas variables demográficas. Según la representación simultánea del HJ-Biplot se identificaron 3 clústeres, el clúster 1 son provincias con mayor densidad poblacional y tasas de mortalidad general, pero valores bajos de tasas de natalidad, el clúster 2 agrupa provincias con mayor esperanza de vida y tasas de mortalidad infantil pero bajos valores de tasa de natalidad y el clúster 3 están las provincias con valores altos de tasas de natalidad y valores bajos de densidad poblacional, esperanza de vida, tasas de mortalidad general y mortalidad infantil, distintos resultados se obtuvieron con el método Two Step. Se pudo concluir que estos métodos son de utilidad para explorar las similitudes entre las provincias según variables demográficas.


The classification methods allow to explore and analyze big data sets visually, which is very useful for making quick decisions. This work aimed to compare of two methods of cluster analysis for big data in demographic variables of the provinces of Ecuador. An observational study of comparative type was carried out through the simultaneous representation of the HJ/Biplot and the Two Step method (two-stage cluster), through the MultBiplot and SPSS software. The data correspond to demographic variables of socio-health interest, general mortality rate, infant mortality rate, birth rate, population density, urban percentage and life expectancy, measured in the provinces of Ecuador. Data from Statistics and Census Institute were used. The association between variables was analyzed and clusters of the provinces of Ecuador were identified according to these demographic variables. According to the simultaneous representation of the HJBiplot, 3 clusters were identified, cluster 1 are provinces with higher population density and general mortality rates, but low birth rates values, cluster 2 are provinces with higher life expectancy and mortality rates infantile but low birth rate values and cluster 3 are the provinces with high birth rates values and low population density, life expectancy, general mortality and infant mortality rates, different results were obtained with the Two Step method. It was concluded that these methods are useful for exploring the similarities between provinces according to demographic variables.


Subject(s)
Humans , Cluster Analysis , Demography , Models, Statistical , Vital Statistics , Ecuador/epidemiology
4.
Electron. j. biotechnol ; 43: 8-15, Jan. 2020. tab
Article in English | LILACS (Americas) | ID: biblio-1087467

ABSTRACT

Background: Plant tissue cultures have the potential to reprogram the development of microspores from normal gametophytic to sporophytic pathway resulting in the formation of androgenic embryos. The efficiency of this process depends on the genotype, media composition and external conditions. However, this process frequently results in the regeneration of albino instead of green plants. Successful regeneration of green plants is affected by the concentration of copper sulfate (CuSO4) and silver nitrate (AgNO3) and the length of induction step. In this study, we aimed at concurrent optimization of these three factors in barley (Hordeum vulgare L.), wheat (Triticum aestivum L.), and triticale (x Triticosecale spp. Wittmack ex A. Camus 1927) using the Taguchi method. We evaluated uniform donor plants under varying experimental conditions of in vitro anther culture using the Taguchi approach, and verified the optimized conditions. Results: Optimization of the regeneration conditions resulted in an increase in the number of green regenerants compared with the control. Statistic Taguchi method for optimization of the in vitro tissue culture plant regeneration via anther cultures allowed reduction of the number of experimental designs from 27 needed if full factorial analysis is used to 9. With the increase in the number of green regenerants, the number of spontaneous doubled haploids decreased. Moreover, in barley and triticale, the number of albino regenerants was reduced. Conclusion: The statistic Taguchi approach could be successfully used for various factors (here components of induction media, time of incubation on induction media) at a one time, that may impact on cereals anther cultures to improve the regeneration efficiency


Subject(s)
Agricultural Cultivation , Edible Grain/growth & development , Models, Statistical , Pigments, Biological , Plant Growth Regulators , Pollen , Silver Nitrate , Color , Copper Sulfate , Androgens
5.
Article in Korean | WPRIM (Western Pacific) | ID: wprim-820816

ABSTRACT

OBJECTIVES: The decayed-missing-filled (DMFT) index is a representative oral health indicator. Prediction of DMFT index is an important basis for the development of public oral health care projects and strategies for caries prevention. In this study, we used data from the 2015 Korean children's oral health survey to predict DMFT index and caries risk groups using statistical techniques and four different machine-learning algorithms.METHODS: DMFT prediction models were constructed using multiple linear regression and four different machine-learning algorithms: decision tree regressor, decision tree classifier (DTC), random forest regressor, and random forest classifier (RFC). Thereafter, their accuracies were compared.RESULTS: For the DMFT predictive model, the prediction accuracy of multiple linear regression and RFC were 15.24% and 43.27%, respectively. The accuracy of DTC prediction was 2.84 times that of multiple linear regression. The important feature of the machine-learning model, which predicts DMFT index and the caries risk group, was the number of teeth with sealants.CONCLUSIONS: Using data from the 2015 Korean children's oral health survey, which is considered big data in the field of oral health survey in Korea, this study confirmed that machine-learning models are more useful than statistical models for predicting DMFT index and caries risk in 12-year-old children. Therefore, it is expected that the machine-learning model can be used to predict the DMFT score.


Subject(s)
Child , Decision Trees , Dental Caries , Forests , Humans , Korea , Linear Models , Machine Learning , Models, Statistical , Oral Health , Tooth
6.
Rev. saúde pública (Online) ; 54: 43, 2020. graf
Article in English | LILACS (Americas) | ID: biblio-1094422

ABSTRACT

ABSTRACT The rapid increase in clinical cases of the new coronavirus disease, COVID-19, suggests high transmissibility. However, the estimates of the basic reproductive number reported in the literature vary widely. Considering this, we drew the function of contact-rate reduction required to control the transmission from both detectable and undetectable sources. Based on this, we offer a set of recommendations for symptomatic and asymptomatic populations during the current pandemic. Understanding the dynamics of transmission is essential to support government decisions and improve the community's adherence to preventive measures.


Subject(s)
Humans , Pneumonia, Viral/prevention & control , Pneumonia, Viral/epidemiology , Coronavirus Infections/prevention & control , Coronavirus Infections/epidemiology , Pandemics/prevention & control , Betacoronavirus/growth & development , Pneumonia, Viral/transmission , Brazil , Quarantine/statistics & numerical data , Feasibility Studies , Models, Statistical , Contact Tracing , Coronavirus Infections/transmission , Basic Reproduction Number
7.
Prensa méd. argent ; 105(9 especial): 644-651, oct 2019. fig
Article in English | LILACS (Americas), BINACIS | ID: biblio-1046879

ABSTRACT

The article introduces the findings of the analysis of the existing approaches to the development of mathematical models of acoustic heart phenomena. The analysis of mathematical methods that can be used to model heart sounds has been performed with the use of reference signals from the 3M Open Library (Littmann Library) and a set of signals obtained by the authors during their previous scientific efforts. The analysis findings have allowed revealing the approaches and methods that are most suitable for developing the mathematical models of human phonocardiograms (normal and pathological) for further research efforts meant to develop methods to single out heart beats against the high level of interference and creating intervalograms to characterize the heart rate at the current moments of time. In addition to the generation of model phonocardiograms, the article reviews the methods to analyze model and real-life phonocardiograms with the assessment of an input from random and deterministic components.


Subject(s)
Humans , Phonocardiography/instrumentation , Spectrum Analysis , Acoustics , Models, Statistical , Heart Rate Determination/methods , Heart/physiology
8.
Psico USF ; 24(2): 233-244, 2019. tab
Article in Portuguese | LILACS (Americas) | ID: biblio-1012783

ABSTRACT

Esta pesquisa teve como objetivos a adaptação transcultural e avaliação das propriedades psicométricas da versão brasileira do Reno Inventory of Self-Perspective - RISP, instrumento que avalia a habilidade de tomada de perspectiva, compreensão de si mesmo enquanto construção contextual, por meio dos fatores enredado, centrado e transcendente. A amostra foi composta por 344 universitários (idade 21,1 ± 4,8; 64,2% mulheres). A estrutura interna foi estimada por meio do Exploratory Structural Equation Modeling (ESEM). Também se avaliou a invariância do modelo fatorial entre participantes do sexo masculino e feminino, indicadores de precisão e associação com variáveis externas: satisfação com a vida, fusão cognitiva, ansiedade, estresse e depressão. Os resultados revelaram a estrutura composta por três fatores, conforme hipótese teórica, com indicadores desejáveis de precisão. Foi demonstrado equivalência do modelo de medida ao avaliar participantes dos diferentes sexos, e associações correspondentes as perspectivas teóricas com as variáveis externas estudadas. Os resultados sugerem adequação da versão brasileira RISP. (AU)


This research aimed to adapt and assess the psychometric properties of the Brazilian version of the Reno Inventory of Self-Perspective (RISP), which aims to measure fusion with self-content, the ability to take a centered self-perspective, and verbal awareness of the transcendent nature of that perspective, using three factors: Entangled, Centered and Transcendent. The sample consisted of 344 Brazilian undergraduate students (age 21.1±4.8; 64.2% women). The dimensionality of the inventory was estimated by the Exploratory Structural Equation Modeling (ESEM). The invariance of the factorial model between men and women, scale reliability and association with other variables: life satisfaction, cognitive fusion, anxiety, stress and depression were estimated as well. The results showed a three-factor structure, confirming the theoretical hypothesis with desirable precision indices. It was also observed the measurement model equivalence to assess participants of both sexes. The results suggest adequacy of the Brazilian version of the RISP. (AU)


Esta investigación tuvo como principal objetivo la adaptación transcultural y la evaluación de las propiedades psicométricas de la versión brasileña del Reno Inventory of Self-Perspective RISP, un instrumento que evalúa la medición de habilidad de capacidad de toma de perspectiva, comprensión de sí mismo como construcción contextual, a través de los factores Enredado, Centrado y Trascendente. La muestra fue compuesta por 344 universitarios (edad 21,1 ± 4,8; 64,2% mujeres). La estructura interna del instrumento fue estimada por la Exploratory Structural Equation Modeling (ESEM). También se evaluó la invariancia del modelo factorial entre participantes de sexo masculino y femenino, indicadores de precisión y asociación con variables externas: satisfacción con la vida, fusión cognitiva, ansiedad, estrés y depresión. Los resultados revelaron la estructura compuesta por tres factores, según hipótesis teórica, con indicadores deseables de precisión. También se demostró la equivalencia del modelo de medida al evaluar participantes de diferente sexo, así como asociaciones correspondientes a perspectivas teóricas con las variables externas estudiadas. Los resultados sugieren adecuación de la versión brasileña RISP. (AU)


Subject(s)
Humans , Male , Adolescent , Adult , Middle Aged , Cognitive Behavioral Therapy , Cross-Cultural Comparison , Sex Distribution , Reproducibility of Results , Models, Statistical
9.
Yonsei Medical Journal ; : 525-534, 2019.
Article in English | WPRIM (Western Pacific) | ID: wprim-762083

ABSTRACT

PURPOSE: Standard treatment for cases of non-small cell lung cancer (NSCLC) exhibiting acquired drug resistance includes tumor rebiopsy, epidermal growth factor receptor (EGFR) mutation testing (e.g., for T790M mutations), and the subsequent administration of third-generation EGFR-tyrosine kinase inhibitors (EGFR-TKIs). However, rebiopsies are typically invasive, costly, and occasionally not feasible. Therefore, the present study aimed to assess rebiopsy procedures by analyzing real-world data collected by the ASTRIS study of patients with resistant NSCLC. MATERIALS AND METHODS: The present study used statistical models to evaluate data collected by the ASTRIS trial (NCT02474355) conducted at Yonsei Cancer Center, including the rebiopsy success rate, incidence of T790M mutations in collected tissue and plasma samples, and association of administered osimertinib treatment efficacy. RESULTS: In a total of 188 screened patients, 112 underwent rebiopsy. An adequate tumor specimen was obtained in 95 of these patients, the greatest majority of whom (43.8%) were subjected to bronchoscopy. T790M mutations were detected in 53.3% of successfully EGFR-tested rebiopsy samples. A total of 88 patients received osimertinib treatment, and the objective response rate and median progression-free survival time was 44.3% and 32.7 weeks, respectively, among the treated patients overall, but 57.8% and 45.0 weeks, and 35.2% and 20.4 weeks among patients who exhibited T790M-positive tissue (n=45) and plasma (n=54) samples, respectively. CONCLUSION: Approximately 60% of patients in the analyzed real-world cohort were eligible for tissue rebiopsy upon NSCLC progression. Osimertinib activity was higher in patients in whom T790M mutations were detected in tissues rather than in plasma samples.


Subject(s)
Bronchoscopy , Carcinoma, Non-Small-Cell Lung , Cohort Studies , Disease-Free Survival , Drug Resistance , Humans , Incidence , Models, Statistical , Phosphotransferases , Plasma , ErbB Receptors , Treatment Outcome
10.
Clin. biomed. res ; 39(4): 356-363, 2019.
Article in Portuguese | LILACS (Americas) | ID: biblio-1087969

ABSTRACT

Dando continuidade aos artigos da série "Perguntas que você sempre quis fazer, mas nunca teve coragem", que tem como objetivo responder e sugerir referências para o melhor entendimento das principais dúvidas dos pesquisadores do Hospital de Clínicas de Porto Alegre sobre estatística, este quarto artigo se propõe a responder às principais dúvidas levantadas sobre modelagem estatística. São discutidas questões referentes à classificação de variáveis em independentes e dependentes, diferenças entre correlação, associação e regressão, os principais tipos de regressão e quais etapas são necessárias na construção de modelos. Os conceitos são abordados numa linguagem acessível ao público leigo e diversas referências são sugeridas para os curiosos em relação ao tema. (AU)


Continuing the series of articles "Questions you have always wanted to ask but never had the courage to," which aims to answer the most common questions of researchers at Hospital de Clínicas de Porto Alegre regarding statistics and to suggest references for a better understanding, this forth article addresses the topic of statistical modeling. Questions about classification of variables as dependent or independent, differences between correlation, association and regression, types of regression and steps for statistical modeling are discussed. The concepts are explained in plain language for lay readers and several references are suggested for those curious about the topic. (AU)


Subject(s)
Humans , Regression Analysis , Models, Statistical , Correlation of Data
11.
Article in English | WPRIM (Western Pacific) | ID: wprim-766121

ABSTRACT

OBJECTIVES:: Investigating the survival of patients with cancer is vitally necessary for controlling the disease and for assessing treatment methods. This study aimed to compare various statistical models of survival and to determine the survival rate and its related factors among patients suffering from lung cancer. METHODS:: In this retrospective cohort, the cumulative survival rate, median survival time, and factors associated with the survival of lung cancer patients were estimated using Cox, Weibull, exponential, and Gompertz regression models. Kaplan-Meier tables and the log-rank test were also used to analyze the survival of patients in different subgroups. RESULTS:: Of 102 patients with lung cancer, 74.5% were male. During the follow-up period, 80.4% died. The incidence rate of death among patients was estimated as 3.9 (95% confidence [CI], 3.1 to 4.8) per 100 person-months. The 5-year survival rate for all patients, males, females, patients with non-small cell lung carcinoma (NSCLC), and patients with small cell lung carcinoma (SCLC) was 17%, 13%, 29%, 21%, and 0%, respectively. The median survival time for all patients, males, females, those with NSCLC, and those with SCLC was 12.7 months, 12.0 months, 16.0 months, 16.0 months, and 6.0 months, respectively. Multivariate analyses indicated that the hazard ratios (95% CIs) for male sex, age, and SCLC were 0.56 (0.33 to 0.93), 1.03 (1.01 to 1.05), and 2.91 (1.71 to 4.95), respectively. CONCLUSIONS:: Our results showed that the exponential model was the most precise. This model identified age, sex, and type of cancer as factors that predicted survival in patients with lung cancer.


Subject(s)
Cohort Studies , Female , Follow-Up Studies , Humans , Incidence , Iran , Lung Neoplasms , Lung , Male , Models, Statistical , Multivariate Analysis , Retrospective Studies , Small Cell Lung Carcinoma , Survival Rate
12.
Article in English | WPRIM (Western Pacific) | ID: wprim-758971

ABSTRACT

BACKGROUND: Unlike patterns observed in the general population, obesity is associated with better survival among hemodialysis patients, which could be explained by reverse causation or illness-related weight loss. However, the time-varying effect of body mass index (BMI) on hemodialysis survival has not been investigated. Therefore, this study investigated the time-varying effect of BMI on mortality after starting hemodialysis. METHODS: In the present study, we examined Korean Society of Nephrology data from 16,069 adult patients who started hemodialysis during or after the year 2000. Complete survival data were obtained from Statistics Korea. Survival analysis was performed using Cox regression and a non-proportional hazard fractional polynomial model. RESULTS: During the median follow-up of 8.6 years, 9,272 patients (57.7%) died. Compared to individuals with normal BMI (18.5–24.9 kg/m²), the underweight group (< 18.5 kg/m²) had a higer mortality hazard ratio (HR, 1.292; 95% confidence interval [CI], 1.203–1.387; P < 0.001) and the overweight group (25.0–29.9 kg/m²) had a lower mortality HR (0.904; 95% CI, 0.829–0.985; P = 0.022). The underweight group had increasing HRs during the first 3 to 7 years after starting hemodialysis, which varied according to age group. The young obese group (< 40 years old) had a U-shaped temporal trend in their mortality HRs, which reflected increased mortality after 7 years. CONCLUSION: The obese hemodialysis group had better survival during the early post-dialysis period, although the beneficial effect of obesity disappeared 7 years after starting hemodialysis. The young obese group also had an increased mortality HR after 7 years.


Subject(s)
Adult , Body Mass Index , Follow-Up Studies , Humans , Korea , Models, Statistical , Mortality , Nephrology , Obesity , Overweight , Renal Dialysis , Thinness , Weight Loss
13.
Article in English | WPRIM (Western Pacific) | ID: wprim-763797

ABSTRACT

Understanding the role of the microbiome in human health and how it can be modulated is becoming increasingly relevant for preventive medicine and for the medical management of chronic diseases. The development of high-throughput sequencing technologies has boosted microbiome research through the study of microbial genomes and allowing a more precise quantification of microbiome abundances and function. Microbiome data analysis is challenging because it involves high-dimensional structured multivariate sparse data and because of its compositional nature. In this review we outline some of the procedures that are most commonly used for microbiome analysis and that are implemented in R packages. We place particular emphasis on the compositional structure of microbiome data. We describe the principles of compositional data analysis and distinguish between standard methods and those that fit into compositional data analysis.


Subject(s)
Biomarkers , Chronic Disease , Genome, Microbial , Humans , Metagenome , Metagenomics , Microbiota , Models, Statistical , Preventive Medicine , Sequence Analysis, DNA , Statistics as Topic
14.
Experimental Neurobiology ; : 376-389, 2019.
Article in English | WPRIM (Western Pacific) | ID: wprim-763767

ABSTRACT

Despite significant advances in neuroscience research over the past several decades, the exact cause of AD has not yet fully understood. The metabolic hypothesis as well as the amyloid and tau hypotheses have been proposed to be associated with AD pathogenesis. In order to identify metabolome signatures from the postmortem brains of sporadic AD patients and control subjects, we performed ultra performance liquid chromatography coupled with linear ion trap-Orbitrap mass spectrometer (UPLC-LTQ–Orbitrap-MS). Not only our study identified new metabolome signatures but also verified previously known metabolome profiles in the brain. Statistical modeling of the analytical data and validation of the structural assignments discovered metabolic biomarkers associated with the AD pathogenesis. Interestingly, hypotaurin, myo-inositol and oxo-proline levels were markedly elevated in AD while lutamate and N-acetyl-aspartate were decreased in the postmortem brain tissue of AD patients. In addition, neurosteroid level such as cortisol was significantly increased in AD. Together, our data indicate that impaired amino acid metabolism is associated with AD pathogenesis and the altered amino acid signatures can be useful diagnostic biomarkers of AD. Thus, modulation of amino acid metabolism may be a possible therapeutic approach to treat AD.


Subject(s)
Alzheimer Disease , Amyloid , Biomarkers , Brain , Chromatography, Liquid , Humans , Hydrocortisone , Metabolism , Metabolome , Metabolomics , Models, Statistical , Neurosciences
15.
Epidemiology and Health ; : e2019032-2019.
Article in English | WPRIM (Western Pacific) | ID: wprim-763731

ABSTRACT

OBJECTIVES: Tuberculosis (TB) is a global public health problem that causes morbidity and mortality in millions of people per year. The purpose of this study was to examine the relationship of potential risk factors with TB mortality in Iran. METHODS: This cross-sectional study was performed on 9,151 patients with TB from March 2017 to March 2018 in Iran. Data were gathered from all 429 counties of Iran by the Ministry of Health and Medical Education and Statistical Center of Iran. In this study, a generalized estimating equation-based zero-inflated negative binomial model was used to determine the effect of related factors on TB mortality at the community level. For data analysis, R version 3.4.2 was used with the relevant packages. RESULTS: The risk of mortality from TB was found to increase with the unemployment rate (β


Subject(s)
Body Mass Index , Cross-Sectional Studies , Education, Medical , Family Characteristics , Gastrectomy , HIV , Humans , Iran , Literacy , Malnutrition , Models, Statistical , Mortality , Public Health , Renal Insufficiency, Chronic , Risk Factors , Silicosis , Statistics as Topic , Tuberculosis , Unemployment , Urbanization
16.
Article in English | WPRIM (Western Pacific) | ID: wprim-763386

ABSTRACT

BACKGROUND/AIMS: In recent years, greater assessment accuracy after transjugular intrahepatic portosystemic shunt (TIPS) to ascertain prognosis has become important in decompensated cirrhosis due to portal hypertension. The aim of this study was to assess the ratio of the portal pressure gradient (PPG) pre-TIPS (pre-PPG) to albumin (PPA), which influence ascites formation in cirrhotic patients in the 6-months after TIPS placement, and is a metric introduced in our study. METHODS: This was a retrospective cohort study of 58 patients with decompensated cirrhosis admitted to an academic hospital for the purpose of TIPS placement. We collected the following data: demographics, laboratory measures, and PPG during the TIPS procedure. Then we analyzed the association between the above data and ascites formation post-TIPS in cirrhosis patients. RESULTS: Twenty-two patients with ascites and 28 without ascites were evaluated. Univariate and binary logistic regression analysis were adjusted for the following variables: to determine prognosis; Child-Pugh scores, lymphocyte count, platelet count, hemoglobin level, albumin level and pre-PPG or PPA. The outcome showed that PPA was better than pre-PPG and albumin for predicting ascites according to area under receiver operating characteristic curves and a statistical model that also showed PPA’s influence 6-months post-TIPS. CONCLUSIONS: The combined measurement of pre-PPG and albumin, defined as PPA, may provide a better way to predict post-TIPS ascites in decompensated cirrhosis, which underlines the need for a large clinical trial in the future.


Subject(s)
Ascites , Cohort Studies , Demography , Fibrosis , Humans , Hypertension, Portal , Logistic Models , Lymphocyte Count , Models, Statistical , Platelet Count , Portal Pressure , Portasystemic Shunt, Surgical , Prognosis , Retrospective Studies , ROC Curve , Serum Albumin
17.
Epidemiology and Health ; : 2019032-2019.
Article in English | WPRIM (Western Pacific) | ID: wprim-785755

ABSTRACT

OBJECTIVES: Tuberculosis (TB) is a global public health problem that causes morbidity and mortality in millions of people per year. The purpose of this study was to examine the relationship of potential risk factors with TB mortality in Iran.METHODS: This cross-sectional study was performed on 9,151 patients with TB from March 2017 to March 2018 in Iran. Data were gathered from all 429 counties of Iran by the Ministry of Health and Medical Education and Statistical Center of Iran. In this study, a generalized estimating equation-based zero-inflated negative binomial model was used to determine the effect of related factors on TB mortality at the community level. For data analysis, R version 3.4.2 was used with the relevant packages.RESULTS: The risk of mortality from TB was found to increase with the unemployment rate (β


Subject(s)
Body Mass Index , Cross-Sectional Studies , Education, Medical , Family Characteristics , Gastrectomy , HIV , Humans , Iran , Literacy , Malnutrition , Models, Statistical , Mortality , Public Health , Renal Insufficiency, Chronic , Risk Factors , Silicosis , Statistics as Topic , Tuberculosis , Unemployment , Urbanization
19.
Ultrasonography ; : 50-57, 2019.
Article in English | WPRIM (Western Pacific) | ID: wprim-731041

ABSTRACT

PURPOSE: Existing ultrasound-based fetal weight estimation models have been shown to have high errors when used in the Indian population. Therefore, the primary objective of this study was to develop Indian population-based models for fetal weight estimation, and the secondary objective was to compare their performance against established models. METHODS: Retrospectively collected data from 173 cases were used in this study. The inclusion criteria were a live singleton pregnancy and an interval from the ultrasound scan to delivery of ≤7 days. Multiple stepwise regression (MSR) and lasso regression methods were used to derive fetal weight estimation models using a randomly selected training group (n=137) with cross-products of abdominal circumference (AC), biparietal diameter (BPD), head circumference (HC), and femur length (FL) as independent variables. In the validation group (n=36), the bootstrap method was used to compare the performance of the new models against 12 existing models. RESULTS: The equations for the best-fit models obtained using the MSR and lasso methods were as follows: log₁₀(EFW)=2.7843700+0.0004197(HC×AC)+0.0008545(AC×FL) and log₁₀(EFW)=2.38 70211110+0.0074323216(HC)+0.0186555940(AC)+0.0013463735(BPD×FL)+0.0004519715 (HC×FL), respectively. In the training group, both models had very low systematic errors of 0.01% (±7.74%) and −0.03% (±7.70%), respectively. In the validation group, the performance of these models was found to be significantly better than that of the existing models. CONCLUSION: The models presented in this study were found to be superior to existing models of ultrasound-based fetal weight estimation in the Indian population. We recommend a thorough evaluation of these models in independent studies.


Subject(s)
Femur , Fetal Weight , Head , India , Methods , Models, Statistical , Pregnancy , Regression Analysis , Retrospective Studies , Ultrasonography , Ultrasonography, Prenatal
20.
Braz. j. biol ; 78(2): 328-336, May-Aug. 2018. tab, graf
Article in English | LILACS (Americas) | ID: biblio-888874

ABSTRACT

Abstract The practice of capture-recapture to estimate the diversity is well known to many animal groups, however this practice in the larval phase of anuran amphibians is incipient. We aimed at evaluating the Lincoln estimator, Venn diagram and Bayes theorem in the inference of population size of a larval phase anurocenose from lotic environment. The adherence of results was evaluated using the Kolmogorov-Smirnov test. The marking of tadpoles for later recapture and methods measurement was made with eosin methylene blue. When comparing the results of Lincoln-Petersen estimator corresponding to the Venn diagram and Bayes theorem, we detected percentage differences per sampling, i.e., the proportion of sampled anuran genera is kept among the three methods, although the values are numerically different. By submitting these results to the Kolmogorov-Smirnov test we have found no significant differences. Therefore, no matter the estimator, the measured value is adherent and estimates the total population. Together with the marking methodology, which did not change the behavior of tadpoles, the present study helps to fill the need of more studies on larval phase of amphibians in Brazil, especially in semi-arid northeast.


Resumo A prática de captura-recaptura para a estimação da diversidade é bem conhecida para diversos grupos animais, porém na fase larvar de anfíbios anuros essa prática é incipiente. Objetivamos avaliar os métodos do estimador de Lincoln, diagrama de Venn e o teorema de Bayes na inferência do tamanho populacional de uma anurocenose em fase larvar de ambiente lótico. A aderência dos resultados foi avaliada através do teste de Kolmogorov-Smirnov. A marcação dos girinos para posterior recaptura e aferição dos métodos foi feita com eosina de azul de metileno. Ao compararmos os resultados do estimador de Lincoln que corresponde com o do diagrama de Venn e com o teorema de Bayes detectamos diferenças percentuais por amostragem, isto é, a manutenção da proporção dos gêneros de anuros amostrados é mantida entre os três métodos, embora com valores numericamente diferentes. Ao submetermos esses resultados ao teste Kolmogorov-Smirnov não encontramos diferenças significativas. Logo, qualquer que seja o estimador o valor aferido é aderente e estima a população total. Aliado à metodologia de marcação que não alterou o comportamento dos girinos, o presente estudo ajuda a preencher a necessidade de mais estudos na fase larvar dos anfíbios no Brasil, em especial no semiárido nordestino.


Subject(s)
Animals , Ponds , Models, Statistical , Larva/physiology , Environmental Monitoring , Bayes Theorem , Population Density
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