Your browser doesn't support javascript.
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 86.523
Filtrar
1.
Medicine (Baltimore) ; 98(37): e17165, 2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-31517868

RESUMO

A thyroid cancer ultrasonography screening for all residents 18 years old or younger living in the Fukushima prefecture started in October 2011 to investigate the possible effect of the radiological contamination after the Fukushima Daiichi Nuclear Power Plant accidents as of March 12 to 15, 2011. Thyroid cancer in 184 cases was reported by February 2017. The question arises to which extent those cancer cases are a biological consequence of the radiation exposure or an artefactual result of the intense screening of a large population.Experiences with the Chernobyl accident suggest that the external dose may be considered a valid surrogate for the internal dose of the thyroid gland. We, therefore, calculated the average external effective dose-rate (µSv/h) for the 59 municipalities of the Fukushima prefecture based on published data of air and soil radiation. We further determined the municipality-specific absolute numbers of thyroid cancers found by each of the two screening rounds in the corresponding municipality-specific exposed person-time observed. A possible association between the radiation exposure and the thyroid cancer detection rate was analyzed with Poisson regression assuming Poisson distributed thyroid cancer cases in the exposed person-time observed per municipality.The target populations consisted of 367,674 and 381,286 children and adolescents for the 1st and the 2nd screening rounds, respectively. In the 1st screening, 300,476 persons participated and 270,489 in the 2nd round. From October 2011 to March 2016, a total of 184 cancer cases were found in 1,079,786 person-years counted from the onset of the exposure to the corresponding examination periods in the municipalities. A significant association between the external effective dose-rate and the thyroid cancer detection rate exists: detection rate ratio (DRR) per µSv/h 1.065 (1.013, 1.119). Restricting the analysis to the 53 municipalities that received less than 2 µSv/h, and which represent 176 of the total 184 cancer cases, the association appears to be considerably stronger: DRR per µSv/h 1.555 (1.096, 2.206).The average radiation dose-rates in the 59 municipalities of the Fukushima prefecture in June 2011 and the corresponding thyroid cancer detection rates in the period October 2011 to March 2016 show statistically significant relationships.


Assuntos
Acidente Nuclear de Fukushima , Neoplasias Induzidas por Radiação/epidemiologia , Doses de Radiação , Neoplasias da Glândula Tireoide/epidemiologia , Adolescente , Criança , Pré-Escolar , Relação Dose-Resposta à Radiação , Detecção Precoce de Câncer , Geografia Médica , Humanos , Incidência , Lactente , Recém-Nascido , Japão/epidemiologia , Modelos Estatísticos , Neoplasias Induzidas por Radiação/diagnóstico por imagem , Prevalência , Exposição à Radiação/efeitos adversos , Glândula Tireoide/diagnóstico por imagem , Glândula Tireoide/efeitos da radiação , Neoplasias da Glândula Tireoide/diagnóstico por imagem , Ultrassonografia
2.
Zhonghua Liu Xing Bing Xue Za Zhi ; 40(8): 1010-1017, 2019 Aug 10.
Artigo em Chinês | MEDLINE | ID: mdl-31484271

RESUMO

In recent years, with the improvement of various surveillance network, surveillance system has become an important data source for ecological study. Different data types, including cross-sectional data, time series data and panel data, containing abundant information involving exposure, outcome and confoundings. Gradually, some new statistical methods have been developed or improved for the special structural characteristics of surveillance data. In this paper, we summarized the principles of these models, preconditions, as well as their advantages and limitations.


Assuntos
Ecologia , Monitoramento Epidemiológico , Modelos Estatísticos , Vigilância da População , Estudos Transversais , Saúde Ambiental , Humanos , Projetos de Pesquisa
3.
Medicine (Baltimore) ; 98(32): e16687, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31393370

RESUMO

Obstructive sleep apnea (OSA) has a high prevalence in patients with obesity. Only patients with clinical symptoms of OSA are admitted to polysomnography; however, many patients with OSA are asymptomatic. We aimed to create and validate a population-based risk score that predicts the severity of OSA in patients with obesity.We here report the cross-sectional analysis at baseline of an ongoing study investigating the long-term effect of bariatric surgery on OSA. One-hundred sixty-one patients of the Obesity Center of the Catholic University Hospital in Rome, Italy were included in the study. The patients underwent overnight cardiorespiratory monitoring, blood chemistry analyses, hepatic ultrasound, and anthropometric measurements. The patients were divided into 2 groups according OSA severity assessed by the apnea-hypopnea index (AHI): AHI < 15 = no or mild and AHI ≥ 15 moderate to severe OSA. A statistical prediction model was created and validated. C statistics was used to evaluate the discrimination performance of the model.The prevalence of OSA was 96.3% with 74.5% of the subjects having moderate/severe OSA. Sex, body mass index, diabetes, and age were included in the final prediction model that had excellent discrimination ability (C statistics equals to 83%). An OSA risk chart score for clinical use was created.Patients with severe obesity are at a very high risk for moderate or severe OSA in particular if they are men, older, more obese, and/or with type 2 diabetes. The OSA risk chart can be useful for general practitioners and patients as well as for bariatric surgeons to select patients with high risk of moderate to severe OSA for further polysomnography.


Assuntos
Obesidade Mórbida/fisiopatologia , Apneia Obstrutiva do Sono/diagnóstico , Apneia Obstrutiva do Sono/epidemiologia , Adulto , Fatores Etários , Índice de Massa Corporal , Estudos Transversais , Diabetes Mellitus/epidemiologia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Modelos Estatísticos , Obesidade Mórbida/epidemiologia , Prevalência , Curva ROC , Análise de Regressão , Fatores de Risco , Sensibilidade e Especificidade , Índice de Gravidade de Doença , Fatores Sexuais
5.
An Acad Bras Cienc ; 91(3): e20180040, 2019 Aug 12.
Artigo em Inglês | MEDLINE | ID: mdl-31411253

RESUMO

We introduce a new class of continuous distributions called the generalized odd Lindley-G family. Four special models of the new family are provided. Some explicit expressions for the quantile and generating functions, ordinary and incomplete moments, order statistics and Rényi and Shannon entropies are derived. The maximum likelihood method is used for estimating the model parameters. The flexibility of the generated family is illustrated by means of two applications to real data sets.


Assuntos
Tábuas de Vida , Modelos Estatísticos , Distribuições Estatísticas , Simulação por Computador , Entropia , Funções Verossimilhança
6.
Medicine (Baltimore) ; 98(33): e16867, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31415421

RESUMO

Acute kidney injury (AKI) is a complex syndrome with a variety of possible etiologies and symptoms. It is characterized by high mortality and poor recovery of renal function. The incidence and mortality rates of patients with AKI in intensive care units are extremely high. It is generally accepted that early identification and prompt treatment of AKI are essential to improve outcomes. This study aimed to develop a model based on risk stratification to identify and diagnose early stage AKI for improved prognosis in critically ill patients.This was a single-center, retrospective, observational study. Based on relevant literature, we selected 13 risk factors (age, sex, hypertension, diabetes, coronary heart disease, chronic kidney disease, total bilirubin, emergency surgery, mechanical ventilation, sepsis, heart failure, cancer, and hypoalbuminemia) for AKI assessment using the Kidney Disease Improving Global Outcomes (KDIGO) diagnostic criteria. Univariate and multivariate analyses were used to determine risk factors for eventual entry into the predictive model. The AKI predictive model was established using binary logistic regression, and the area under the receiver operating characteristic curve (AUROC or AUC) was used to evaluate the predictive ability of the model and to determine critical values.The AKI predictive model was established using binary logistic regression. The AUROC of the predictive model was 0.81, with a sensitivity of 69.8%, specificity of 83.4%, and positive likelihood ratio of 4.2.A predictive model for AKI in critically ill patients was established using 5 related risk factors: heart failure, chronic kidney disease, emergency surgery, sepsis, and total bilirubin; however, the predictive ability requires validation.


Assuntos
Lesão Renal Aguda/epidemiologia , Lesão Renal Aguda/etiologia , Unidades de Terapia Intensiva/estatística & dados numéricos , Modelos Estatísticos , Lesão Renal Aguda/diagnóstico , Adulto , Idoso , Bilirrubina/sangue , Comorbidade , Feminino , Insuficiência Cardíaca/epidemiologia , Humanos , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Insuficiência Renal Crônica/epidemiologia , Estudos Retrospectivos , Medição de Risco , Sensibilidade e Especificidade , Sepse/epidemiologia
7.
JAMA ; 322(7): 642-650, 2019 08 20.
Artigo em Inglês | MEDLINE | ID: mdl-31429895

RESUMO

Importance: The time course of cardiovascular disease (CVD) risk after smoking cessation is unclear. Risk calculators consider former smokers to be at risk for only 5 years. Objective: To evaluate the association between years since quitting smoking and incident CVD. Design, Setting, and Participants: Retrospective analysis of prospectively collected data from Framingham Heart Study participants without baseline CVD (original cohort: attending their fourth examination in 1954-1958; offspring cohort: attending their first examination in 1971-1975) who were followed up through December 2015. Exposures: Time-updated self-reported smoking status, years since quitting, and cumulative pack-years. Main Outcomes and Measures: Incident CVD (myocardial infarction, stroke, heart failure, or cardiovascular death). Primary analyses included both cohorts (pooled) and were restricted to heavy ever smokers (≥20 pack-years). Results: The study population included 8770 individuals (original cohort: n = 3805; offspring cohort: n = 4965) with a mean age of 42.2 (SD, 11.8) years and 45% male. There were 5308 ever smokers with a median 17.2 (interquartile range, 7-30) baseline pack-years, including 2371 heavy ever smokers (406 [17%] former and 1965 [83%] current). Over 26.4 median follow-up years, 2435 first CVD events occurred (original cohort: n = 1612 [n = 665 among heavy smokers]; offspring cohort: n = 823 [n = 430 among heavy smokers]). In the pooled cohort, compared with current smoking, quitting within 5 years was associated with significantly lower rates of incident CVD (incidence rates per 1000 person-years: current smoking, 11.56 [95% CI, 10.30-12.98]; quitting within 5 years, 6.94 [95% CI, 5.61-8.59]; difference, -4.51 [95% CI, -5.90 to -2.77]) and lower risk of incident CVD (hazard ratio, 0.61; 95% CI, 0.49-0.76). Compared with never smoking, quitting smoking ceased to be significantly associated with greater CVD risk between 10 and 15 years after cessation in the pooled cohort (incidence rates per 1000 person-years: never smoking, 5.09 [95% CI, 4.52-5.74]; quitting within 10 to <15 years, 6.31 [95% CI, 4.93-8.09]; difference, 1.27 [95% CI, -0.10 to 3.05]; hazard ratio, 1.25 [95% CI, 0.98-1.60]). Conclusions and Relevance: Among heavy smokers, smoking cessation was associated with significantly lower risk of CVD within 5 years relative to current smokers. However, relative to never smokers, former smokers' CVD risk remained significantly elevated beyond 5 years after smoking cessation.


Assuntos
Doenças Cardiovasculares/epidemiologia , Fumantes , Abandono do Hábito de Fumar , Adulto , Doenças Cardiovasculares/prevenção & controle , Estudos de Coortes , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Modelos Estatísticos , Risco , Fatores de Risco
8.
Genet Sel Evol ; 51(1): 43, 2019 Aug 13.
Artigo em Inglês | MEDLINE | ID: mdl-31409294

RESUMO

BACKGROUND: Random regression models (RRM) are widely used to analyze longitudinal data in genetic evaluation systems because they can better account for time-course changes in environmental effects and additive genetic values of animals by fitting the test-day (TD) specific effects. Our objective was to implement a random regression model for the evaluation of dairy production traits in French goats. RESULTS: The data consisted of milk TD records from 30,186 and 32,256 first lactations of Saanen and Alpine goats. Milk yield, fat yield, protein yield, fat content and protein content were considered. Splines were used to model the environmental factors. The genetic and permanent environmental effects were modeled by the same Legendre polynomials. The goodness-of-fit and the genetic parameters derived from functions of the polynomials of orders 0 to 4 were tested. Results were also compared to those from a lactation model with total milk yield calculated over 250 days and to those of a multiple-trait model that considers performance in six periods throughout lactation as different traits. Genetic parameters were consistent between models. Models with fourth-order Legendre polynomials led to the best fit of the data. In order to reduce complexity, computing time, and interpretation, a rank reduction of the variance covariance matrix was performed using eigenvalue decomposition. With a reduction to rank 2, the first two principal components correctly summarized the genetic variability of milk yield level and persistency, with a correlation close to 0 between them. CONCLUSIONS: A random regression model was implemented in France to evaluate and select goats for yield traits and persistency, which are independent i.e. no genetic correlation between them, in first lactation.


Assuntos
Cabras/genética , Lactação/genética , Modelos Genéticos , Modelos Estatísticos , Animais , Indústria de Laticínios , Feminino , Cabras/fisiologia , Masculino , Leite , Análise de Regressão
9.
Genet Sel Evol ; 51(1): 45, 2019 Aug 19.
Artigo em Inglês | MEDLINE | ID: mdl-31426753

RESUMO

BACKGROUND: Crossbreeding is widely used in pig production because of the benefits of heterosis effects and breed complementarity. Commonly, sire lines are bred for traits such as feed efficiency, growth and meat content, whereas maternal lines are also bred for reproduction and longevity traits, and the resulting three-way crossbred pigs are used for production of meat. The most important genetic basis for heterosis is dominance effects, e.g. removal of inbreeding depression. The aims of this study were to (1) present a modification of a previously developed model with additive, dominance and inbreeding depression genetic effects for analysis of data from a purebred sire line and three-way crossbred pigs; (2) based on this model, present equations for additive genetic variances, additive genetic covariance, and estimated breeding values (EBV) with associated accuracies for purebred and crossbred performances; (3) use the model to analyse four production traits, i.e. ultra-sound recorded backfat thickness (BF), conformation score (CONF), average daily gain (ADG), and feed conversion ratio (FCR), recorded on Danbred Duroc and Danbred Duroc-Landrace-Yorkshire crossbred pigs reared in the same environment; and (4) obtain estimates of genetic parameters, additive genetic correlations between purebred and crossbred performances, and EBV with associated accuracies for purebred and crossbred performances for this data set. RESULTS: Additive genetic correlations (with associated standard errors) between purebred and crossbred performances were equal to 0.96 (0.07), 0.83 (0.16), 0.75 (0.17), and 0.87 (0.18) for BF, CONF, ADG, and FCR, respectively. For BF, ADG, and FCR, the additive genetic variance was smaller for purebred performance than for crossbred performance, but for CONF the reverse was observed. EBV on Duroc boars were more accurate for purebred performance than for crossbred performance for BF, CONF and FCR, but not for ADG. CONCLUSIONS: Methodological developments led to equations for genetic (co)variances and EBV with associated accuracies for purebred and crossbred performances in a three-way crossbreeding system. As illustrated by the data analysis, these equations may be useful for implementation of genomic selection in this system.


Assuntos
Cruzamento , Depressão por Endogamia , Modelos Genéticos , Modelos Estatísticos , Suínos/genética , Animais , Cruzamentos Genéticos , Feminino , Variação Genética , Hibridização Genética , Masculino
10.
Medicine (Baltimore) ; 98(26): e16186, 2019 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-31261555

RESUMO

The prevalence of chronic kidney disease (CKD) in Taiwan is 11.9%, and the incidence and prevalence of end-stage renal disease (ESRD) is ranked first in the world. The severity of CKD progression to ESRD is dependent on glomerular filtration rate and proteinuria. However, the risk factors for ESRD also include diabetes, hypertension, hyperlipidemia, age, sex, and so on, and predicting CKD progression using few variables is insufficient. Currently, there are no models with high accuracy and high explanatory power that could predict the risk of progression to dialysis in CKD patients in Taiwan. Our aim was to establish an optimal prediction model for CKD progression in patientsThis study was a retrospective cohort study, which reviewed data from the "Public health insurance Pre-ESRD preventive program and patient health education program" that was implemented by the National Health Insurance Administration, Ministry of Health and Welfare. From 2006 to 2013, data of CKD patients from the Tri-Service General Hospital in Neihu District, Taipei City was examined. The data collected in this study included demographic variables, past medical history, and blood biochemical values. After exclusion of variables with >30% missing data, the remaining variables were interpolated using multiple imputations and inputted into the prediction model for analysis. The Cox proportion hazard model was used to investigate the influence of CKD risk factors on progression to dialysis. The strengths of various models were evaluated using likelihood ratios (LR), in order to identify a model which uses the least factors but has the strongest explanatory power.The study results included 1549 CKD patients, of whom 1017 eventually had dialysis. This study found that in the prediction model with the best explanatory power, the influencing factors and hazard ratios (HR) were: age 0.95 (0.91-0.99), creatinine 1.03 (1.02-1.05), urea nitrogen 1.18 (1.14-1.23), and comorbid systemic diabetes 1.65 (1.45-1.88).A prediction model was developed in this study, which could be used to carry out predictions based on blood biochemical values from patients, in order to accurately predict the risk of CKD progression to dialysis.


Assuntos
Insuficiência Renal Crônica/diagnóstico , Idoso , Biomarcadores/sangue , Comorbidade , Creatinina/sangue , Diabetes Mellitus/epidemiologia , Progressão da Doença , Feminino , Taxa de Filtração Glomerular , Humanos , Transplante de Rim , Masculino , Pessoa de Meia-Idade , Modelos Biológicos , Modelos Estatísticos , Prognóstico , Diálise Renal , Insuficiência Renal Crônica/epidemiologia , Insuficiência Renal Crônica/terapia , Estudos Retrospectivos , Medição de Risco , Fatores de Risco , Taiwan
11.
BMC Public Health ; 19(1): 861, 2019 Jul 03.
Artigo em Inglês | MEDLINE | ID: mdl-31269940

RESUMO

BACKGROUND: Considering the lack of studies that examine built environmental factors associated with life satisfaction among old people in developing countries, particularly those focused on Brazil, the aim of this study was to estimate the prevalence of life satisfaction among old adults residents in a Brazilian urban center and to investigate its association with individual characteristics and objective measures of the built environment. METHODS: A household survey (N = 832) in Belo Horizonte, Minas Gerais, Brazil (2008-2009) and a Systematic Social Observation (SSO) was used in this study. Life satisfaction was assessed through Self-Anchoring Ladder Scale, developed by Cantril, in 1965. Participants' answers were categorized as satisfied (rungs 6-10) and dissatisfied (rungs 0-5). A Multilevel Poisson regression analysis with robust variance was performed. RESULTS: The prevalence of satisfaction with life was approximately 82%. Higher prevalence of life satisfaction was significantly associated with old people who reported higher incomes, higher religious participation, who practice physical activity and who perceive their health as good and very good. In contextual level, results showed that when the contextual features were adjusted separately by the individual characteristics they were no longer significant. The results also showed a lower prevalence of life satisfaction among those living in neighborhoods with higher physical disorder, even after adjusting for individual and other contextual characteristics. CONCLUSIONS: The present findings suggest that life satisfaction should be assessed whenever evaluating urban redevelopment programs designed to improve neighborhood characteristics, reducing physical disorder, especially among old adults.


Assuntos
Ambiente Construído/estatística & dados numéricos , Satisfação Pessoal , Características de Residência/estatística & dados numéricos , População Urbana , Idoso , Brasil , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Modelos Estatísticos , Análise Multinível , Fatores Socioeconômicos , Inquéritos e Questionários , População Urbana/estatística & dados numéricos
12.
Plant Dis ; 103(9): 2204-2211, 2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-31355735

RESUMO

One hundred and one rice genotypes were evaluated for response to sheath blight disease under greenhouse and lowland irrigated field conditions in Guyana. The level of resistance varied from highly resistant to resistant in 14 genotypes over five experimental trials. These genotypes were also observed with low area under the disease progress curve values and slow blighting reactions against artificial inoculation of the pathogen. Genotypes GR1568-31-9-1-1-2-1 and cultivar Rustic had susceptible reactions in all experiments. Additive main effect and multiplicative interaction analysis was used to study the genotype and environment interactions. The analysis revealed that 52.98% of the total sum of square was attributed to genotype effect, 7.50% was attributable to environment effect, and 39.52% was attributable to genotype by environment interaction (G × E) effects. The G × E was almost as large as the genotype effect, thus indicating significant differences of genotypes across the testing environments. This revealed that resistance was slightly influenced by the G × E. The genotypes that showed stable resistance in all environments in this study could be used for breeding the sheath blight resistance in rice.


Assuntos
Resistência à Doença , Interação Gene-Ambiente , Modelos Estatísticos , Oryza , Cruzamento , Resistência à Doença/genética , Fungos/fisiologia , Genótipo , Guiana , Oryza/genética , Oryza/microbiologia
13.
JAMA ; 322(1): 81, 2019 07 02.
Artigo em Inglês | MEDLINE | ID: mdl-31265091
14.
JAMA ; 322(1): 81, 2019 07 02.
Artigo em Inglês | MEDLINE | ID: mdl-31265092
16.
Ying Yong Sheng Tai Xue Bao ; 30(6): 2116-2128, 2019 Jun.
Artigo em Chinês | MEDLINE | ID: mdl-31257787

RESUMO

Maximum Entropy (MaxEnt) model has been widely used in recent years. However, MaxEnt is highly inclined to produce misleading results if it is not well optimized. We summarized the researches about the model optimization for sampling bias correction, model complexity tuning, presence-absence threshold selection, and model evaluation. Spatial filtering performs best for sampling bias correction, while restricted background method shows the lowest efficacy. Model complexi-ty is mainly determined by three factors: The number of environmental variables, model feature types, and regularization multiplier. Variables filtering is needed when sample size is less than the number of environment variables. The criterion of variables selection should focus on their ecological significance rather than the co-linearity between them. The choice of feature types has relatively limi-ted effects on predictive performance of the model, therefore it is advised to choose simpler models. To control overfitting, it is necessary to conduct species-specific tuning on regularization multiplier, which was usually bigger than the default setting. There are three criteria called objectivity, equality and discriminability for selecting threshold to convert continuous predication (e.g. probability of presence) into binary results. Maximizing the sum of sensitivity and specificity is a sound method for threshold selection. Model evaluation methods could be classified into two main types: Threshold-independent and threshold-dependent. Among the threshold-independent evaluations, information criteria may offer significant advantages over AUC and COR. True Skill Statistics is a better index for threshold-dependent evaluations, because it takes both omission and commission errors into account, and is robust to pseudo-absence assumption and species prevalence.


Assuntos
Monitoramento Ambiental/métodos , Modelos Estatísticos , Entropia , Especificidade da Espécie
18.
Adv Exp Med Biol ; 1156: 67-84, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31338778

RESUMO

In our chapter we are describing how to reconstruct three-dimensional anatomy from medical image data and how to build Statistical 3D Shape Models out of many such reconstructions yielding a new kind of anatomy that not only allows quantitative analysis of anatomical variation but also a visual exploration and educational visualization. Future digital anatomy atlases will not only show a static (average) anatomy but also its normal or pathological variation in three or even four dimensions, hence, illustrating growth and/or disease progression.Statistical Shape Models (SSMs) are geometric models that describe a collection of semantically similar objects in a very compact way. SSMs represent an average shape of many three-dimensional objects as well as their variation in shape. The creation of SSMs requires a correspondence mapping, which can be achieved e.g. by parameterization with a respective sampling. If a corresponding parameterization over all shapes can be established, variation between individual shape characteristics can be mathematically investigated.We will explain what Statistical Shape Models are and how they are constructed. Extensions of Statistical Shape Models will be motivated for articulated coupled structures. In addition to shape also the appearance of objects will be integrated into the concept. Appearance is a visual feature independent of shape that depends on observers or imaging techniques. Typical appearances are for instance the color and intensity of a visual surface of an object under particular lighting conditions, or measurements of material properties with computed tomography (CT) or magnetic resonance imaging (MRI). A combination of (articulated) Statistical Shape Models with statistical models of appearance lead to articulated Statistical Shape and Appearance Models (a-SSAMs).After giving various examples of SSMs for human organs, skeletal structures, faces, and bodies, we will shortly describe clinical applications where such models have been successfully employed. Statistical Shape Models are the foundation for the analysis of anatomical cohort data, where characteristic shapes are correlated to demographic or epidemiologic data. SSMs consisting of several thousands of objects offer, in combination with statistical methods or machine learning techniques, the possibility to identify characteristic clusters, thus being the foundation for advanced diagnostic disease scoring.


Assuntos
Anatomia , Imagem Tridimensional , Modelos Anatômicos , Algoritmos , Anatomia/educação , Anatomia/métodos , Diagnóstico por Imagem , Humanos , Modelos Estatísticos
19.
J Surg Oncol ; 120(4): 670-675, 2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-31301150

RESUMO

BACKGROUND: The aim of this study was to develop a prediction model for the presence and location of lymph node metastasis (LNM) in early gastric cancer. METHOD: We reviewed medical records of 4 929 patients who underwent radical gastrectomy for early gastric cancer. Variables of age, sex, lymphatic invasion, depth of invasion, location, gross type, differentiation, and tumor size were analyzed. Logistic regression analysis was used to determine independent predictors of LNM at each LN station. RESULT: Overall incidence of LNM was 9.1% (448/4 929 patients). For the presence of LNM, risk factors of age, sex, lymphatic invasion, depth of invasion, anatomical part, gross ulceration, size, and tumor differentiation were significantly associated with LNM. The area under the curve (AUC) for predicting LNM after validation was 0.834 for the test set. For the location of LNM, age, sex, lymphatic invasion, depth of invasion, anatomical part, circumferential portion, gross type, differentiation, and tumor size were significantly associated with LNM. The AUC of each LN station was favorable with the test set. CONCLUSION: Predicting the location of metastatic LNs appeared to be possible in patients with early gastric cancer.


Assuntos
Adenocarcinoma/secundário , Gastrectomia/métodos , Excisão de Linfonodo/métodos , Linfonodos/patologia , Modelos Estatísticos , Neoplasias Gástricas/patologia , Adenocarcinoma/cirurgia , Detecção Precoce de Câncer , Feminino , Seguimentos , Humanos , Linfonodos/cirurgia , Metástase Linfática , Masculino , Pessoa de Meia-Idade , Invasividade Neoplásica , Valor Preditivo dos Testes , Prognóstico , Curva ROC , Fatores de Risco , Neoplasias Gástricas/cirurgia
20.
Epidemiol Health ; 41: e2019032, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31319655

RESUMO

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 (߈=0.02), illiteracy (߈=0.04), household density per residential unit (߈=1.29), distance between the center of the county and the provincial capital (߈=0.03), and urbanization (߈=0.81). The following other risk factors for TB mortality were identified: diabetes (߈=0.02), human immunodeficiency virus infection (߈=0.04), infection with TB in the most recent 2 years (߈=0.07), injection drug use (߈=0.07), long-term corticosteroid use (߈=0.09), malignant diseases (߈=0.09), chronic kidney disease (߈=0.32), gastrectomy (߈=0.50), chronic malnutrition (߈=0.38), and a body mass index more than 10% under the ideal weight (߈=0.01). However, silicosis had no effect. CONCLUSIONS: The results of this study provide useful information on risk factors for mortality from TB.


Assuntos
Tuberculose/mortalidade , Adulto , Idoso , Estudos Transversais , Humanos , Irã (Geográfico)/epidemiologia , Pessoa de Meia-Idade , Modelos Estatísticos , Sistema de Registros , Fatores de Risco , Fatores Socioeconômicos
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA