Application of multilevel models for predicting pain following root canal treatment.

OBJECTIVES: This study developed predictive models for one-week acute and six-month persistent pain following root canal treatment (RCT). An additional aim was to study the gain in predictive efficacy of models containing clinical factors only, over models containing sociodemographic characteristics. METHODS: A secondary data analysis of 708 patients who received RCTs was conducted. Three sets of predictors were used: (1) combined set, containing all predictors in the data set; (2) clinical set and (3) sociodemographic set. Missing data were handled by multiple imputation using the missing indicator method. The multilevel least absolute selection and shrinkage operator (LASSO) regression was used to select predictors into the final multilevel logistic models. Three measures, the area under the receiver operating characteristic curve (AUROC) and precision-recall curve (AUPRC) and calibration curves, were used to assess the predictive performance of the models. RESULTS: The selected-in factors in the final models, using LASSO regression, are related to pre- and intra-treatment clinical symptoms and pain experience. Predictive performance of the models remained the same with the inclusion (exclusion) of the socio-demographic factors. For predicting one-week outcome, the model built with combined set of predictors yielded the highest AUROC and AUPRC of 0.85 and 0.72, followed by the models built with clinical factors (AUROC = 0.82, AUPRC = 0.66). The lowest predictive ability was found in models with only sociodemographic characteristics (AUROC = 0.68, AUPRC = 0.40). Similar patterns were observed in predicting six-month outcome, where the AUROC for models with combined, clinical and sociodemographic sets of predictors were 0.85, 0.89 and 0.66, respectively, and the AUPRC were 0.48, 0.53 and 0.22, respectively. CONCLUSIONS: Clinical factors such as the severity and experience of pre-operative and intra-operative pain were discovered important to the subsequent development of pain following RCTs. Adding sociodemographic characteristics to the models with clinical factors did not change the models' predictive performance or the proportion of explained variance.

A Nomogram model involving preoperative inflammatory markers for predicting postoperative overall survival in patients with stage Ⅰ-Ⅲ gastric cancer / 中华普通外科杂志

Objective:To establish a nomogram to predict overall survival of patients with stage Ⅰ-Ⅲ gastric cancer (GC) based on preoperative inflammatory markers.Methods:Clinicopathological and follow-up data of 1 035 patients with stage Ⅰ-Ⅲ gastric cancer operated at He'nan Cancer Hospital between May 2015 and Oct 2016 were retrospectively collected. A nomogram was established based on prognostic factors. Harrell's concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA) were used to verify the performance of the model according to differentiation, calibration and clinical utility.Results:A total of 1 035 patients were enrolled . The median follow-up time was 41.9 months; According to the optimal cutoff value, 170 were with elevated neutrophil-to-lymphocyte ratio (NLR) and 865 with a reduced　ratio; 562 in elevated platelet-to-lymphocyte ratio (PLR) vs. 473 in the reduced group; fibrinogen/albumin ratio (FAR) elevated in 108 group vs. 972 in the reduced group; 180 in the prognostic nutritional index score (PNI) elevated group and 855 in the reduced group. Two hundred and sixty-seven patients were categorized at stage Ⅰ, 334 at stage Ⅱ ,434 at stage Ⅲ. Multivariate regression analysis showed tumor location, vascular tumor thrombus, pTNM stage, FAR, PNI and NLR were independent prognostic factors (all P<0.05). The C-index of the nomogram was 0.723 (95% CI: 0.710 -0.736) and had better clinical utility than the American Joint Committee on Cancer (AJCC) 8th TNM staging system 0.693 (95% CI, 0.681 -0.705). The calibration curve of the nomogram showed that the predicted survival rate was consistent with the actual survival rate in GC patients. Compared to AJCC 8th pTNM staging system, the DCA curve indicate that the nomogram has a higher net income. Conclusion:The nomogram predicting overall survival of patients with stage Ⅰ-Ⅲ gastric cancer is established and verified , which provides better individual prediction than TNM staging system.

How to Decide on Modeling Details: Risk and Benefit Assessment.

Mathematical models based on thermodynamic, kinetic, heat, and mass transfer analysis are central to this chapter. Microbial growth, death, enzyme inactivation models, and the modeling of material properties, including those pertinent to conduction and convection heating, mass transfer, such as diffusion and convective mass transfer, and thermodynamic properties, such as specific heat, enthalpy, and Gibbs free energy of formation and specific chemical exergy are also needed in this task. The origins, simplifying assumptions, and uses of model equations are discussed in this chapter, together with their benefits. The simplified forms of these models are sometimes referred to as "laws," such as "the first law of thermodynamics" or "Fick's second law." Starting to modeling a study with such "laws" without considering the conditions under which they are valid runs the risk of ending up with erronous conclusions. On the other hand, models started with fundamental concepts and simplified with appropriate considerations may offer explanations for the phenomena which may not be obtained just with measurements or unprocessed experimental data. The discussion presented here is strengthened with case studies and references to the literature.

Homicídios em homens jovens: tendência e projeção em Mato Grosso-Brasil, 1996-2022 / Homicides in young men: trend and projection in Mato Grosso-Brazil, 1996-2022

Objetivo: Analisar a tendência de 1996 a 2017 e projetar de 2018 a 2022 a taxa de homicídios em homens jovens, segundo faixa etária, no estado de Mato Grosso. Métodos: Trata-se de Estudo ecológico, exploratório, de tendência temporal. Para modelagem da série e predição da taxa de homicídios para o período de 2018-2022, utilizou-se o método ARIMA (autoregressive integrated moving average). Resultados: Verificou-se a tendência temporal crescente de homicídios em homens jovens (15 a 29 anos), com manutenção de taxas altas para a população masculina de 15 a 19 anos. A previsão para o quinquênio 2018-2022 indicou elevação das taxas de homicídios entre homens jovens, revelando crescimento maior em adolescentes, mesmo com menores taxas ao longo dos anos. Conclusão: Este estudo indicou tendência crescente de homicídios em homens jovens em Mato Grosso, sobretudo em adolescentes. Visto que o homicídio possui variadas facetas fomentadoras admite-se que número substancial de homicídios deste estrato social poderia ser evitado seguindo estratégias eficazes de prevenção por meio de políticas públicas.

Objective: To analyze the trend from 1996 to 2017 and project from 2018 to 2022 homicide rates in young men, age group, in the state of Mato Grosso. Methods: This is an ecological, exploratory, time series study. To model the series and predict the homicide rate for the period 2018-2022, the ARIMA (autoregressive integrated moving average) method was used. Results: There was an increasing temporal trend of homicides in young men (15 to 29 years), with high rates for the male population aged 15 to 19 years. The forecast for the 2018-2022 five-year period indicates an increase in homicide rates among young men, revealing greater growth in adolescents, even with lower rates over the years. Conclusion: This study indicated an increasing trend of homicides in young men in Mato Grosso, especially in adolescents. Since homicide has several fomenting facets, it is admitted that a substantial number of homicides from this social stratum could be avoided by following useful prevention through public policies

Initial investigation on predicting factors for gastrointestinal failure and the impaction to prognosis of patients with severe cases / 中国基层医药

Objective To evaluate the association of gastrointestinal failure(GIF)with ICU hospital days,mechanical ventilation days and mortality,to identify its risk factors.Methods A retrospective analysis of patients (n=1836)admired to ICU and EICU during the years from 2003 to 2007 was performed to evaluate the association between GIF and their length of stay,mechanical ventilation days and mortality.The ability of APACHE Ⅱ,SOFA and age in predicting the incidence rate of GIF was identified.Results GIF was significantly related to higher mortality,as well as prolonged length of ICU stay and mechanical ventilation respectively.Age,APACHE Ⅱ and SOFA scores at admission were identified as the risk factors for the development of GIF.Condusion GIF should be considered a relevant clinical predictor of mcreased mortality and prolonged ICU stay and mechanical ventilation.Age,APACHE Ⅱ and SOFA scores are sensitive risk factors for the development of GIF.