Classifying Pituitary Adenoma Invasiveness Based on Radiological, Surgical and Histological Features: A Retrospective Assessment of 903 Cases.

Invasiveness is a major predictor of surgical outcome and long-term prognosis in patients with pituitary adenomas (PAs). We assessed PA invasiveness via radiological, surgical and histological perspectives to establish a classification scheme for predicting invasive behavior and poor prognosis. We retrospectively analyzed 903 patients who underwent transnasal-transsphenoidal surgery between January 2013 and December 2019. Radiological (hazard ratio (HR) 5.11, 95% confidence interval (CI): 3.98−6.57, p < 0.001) and surgical (HR 6.40, 95% CI: 5.09−8.06, p < 0.001) invasiveness better predicted gross-total resection (GTR) and recurrence/progression-free survival (RPFS) rates than did histological invasiveness (HR 1.44, 95% CI: 1.14−1.81, p = 0.003). Knosp grades 2 (HR 4.63, 95% CI: 2.13−10.06, p < 0.001) and 3 (HR 2.23, 95% CI: 1.39−3.59, p = 0.011) with surgical invasiveness were better predictors of prognosis than corresponding Knosp grades without surgical invasiveness. Classifications 1 and 2 were established based on radiological, surgical and histological invasiveness, and Knosp classification and surgical invasiveness, respectively. Classification 2 predicted RPFS better than Knosp classification and Classification 1. Overall, radiological and surgical invasiveness were clinically valuable as prognostic predictors. The convenience and good accuracy of Invasiveness in Classification 2 is useful for identifying invasive PAs and facilitating the development of treatment plans.

Assessment of CHA2DS2-VASc score for predicting cardiovascular and cerebrovascular outcomes in acute myocardial infarction patients.

Although established guidelines currently recommend the use of the CHA2DS2-VASc score for evaluating embolic risk in AF patients, few studies have evaluated the use of the CHA2DS2-VASc score for predicting cardiovascular outcomes in patients with acute myocardial infarction (AMI). The aim of this study was to determine whether CHA2DS2-VASc score is a predictor of a major adverse cardiocerebral vascular event (MACCE) in AMI patients.This study analyzed data in the Taiwan National Health Insurance Research Database from January 2008 to December 2012. Cardiovascular outcomes were analyzed according to the baseline characteristics, presence of AF, and CHA2DS2-VASc score.Twenty nine thousand four hundred fifty-two patients with non-fatal AMI, 1171 patients (8.3%) were with AF. The Cox regress model showed with the exception of women sex and peripheral artery disease, all the baseline characteristics considered risks in CHA2DS2-VASc scores were independently associated with the increased incidence of MACCE within 1 year after AMI. A CHA2DS2-VASc score of <5 had negative predictive values of 93.37% for recurrent MI, 98.45% for stroke, 94.86% for HF admission, 98.83% for mortality, and 87.80% for MACCE. Regardless of the presence of AF, the CHA2DS2-VASc score was correlated with 1-year MACCE.The CHA2DS2-VASc score was correlated with 1-year MACCE in AMI patients who were discharge alive. The CHA2DS2-VASc score is useful predictor for 1 year MACCE in patients with AMI.

Rainfall Threshold Assessment Corresponding to the Maximum Allowable Turbidity for Source Water.

This study aims to assess the upstream rainfall thresholds corresponding to the maximum allowable turbidity of source water, using monitoring data and artificial neural network computation. The Taipei Water Source Domain was selected as the study area, and the upstream rainfall records were collected for statistical analysis. Using analysis of variance (ANOVA), the cumulative rainfall records of one-day Ping-lin, two-day Ping-lin, two-day Tong-hou, one-day Guie-shan, and one-day Tai-ping (rainfall in the previous 24 or 48 hours at the named weather stations) were found to be the five most significant parameters for downstream turbidity development. An artificial neural network model was constructed to predict the downstream turbidity in the area investigated. The observed and model-calculated turbidity data were applied to assess the rainfall thresholds in the studied area. By setting preselected turbidity criteria, the upstream rainfall thresholds for these statistically determined rain gauge stations were calculated.

Effects of pollution sources and soil properties on distribution of polycyclic aromatic hydrocarbons and risk assessment.

In this study, the concentrations of polycyclic aromatic hydrocarbons (PAHs) in soil profiles and the soil properties were analyzed in Hunpu, a typical wastewater irrigation area, northeast of China. The total concentrations of 16 priority control PAHs ranged from 7.88 to 2,231.42 µg/kg. Among 16 PAHs, the most abundant was Phenanthrene and the 3- or 4- ring PAHs were predominant. The PAH concentrations were higher in the upland fields near the oil wells, whereas leaching of PAH into the groundwater caused low concentrations in the paddy fields. The geochemical indices and the results from the principal component analysis of all 16 PAHs indicated that PAHs were mainly from atmospheric dusts in the top soil in I-1P/I-3P/I-7P and through soil profiles in I-4U/I-5P/I-8U, whereas those in the bottom layers were mainly from petroleum production and wastewater irrigation in I-1P/I-3P/I-7P and through soil profiles in I-2U and I-6U. In the redundancy analysis, PAHs exhibited negative correlation with pH, depth, silt, and clay, but had positive correlation with sand and organic matter. Finally, total toxic equivalent in the soil profiles and the calculated health risk of PAHs in the surface soil using contaminated land exposure assessment model elucidated the cancer risk that PAHs pose on human health in the Hunpu region.

[Research on health cost of pesticide application and influence factors].

OBJECTIVE: To measure quantitatively the health costs of 380 farmer families using the pesticides and influence factors, and to provide the base for establishing the protective measures. METHODS: Based on the surveyed data of rice producers in Anhui province, a quantitative analysis of health cost of pesticide application was conducted with COI, the influence factors on farmers' pesticide application have been examined. RESULTS: The results shown that the health cost of pesticide application was as RMB 54.44 yuans per farmer a year. The influence factors of health cost were the amount and time of pesticide application, protective facilities, pesticide label illiteracy, age, gender and education level of farmers. CONCLUSION: The measures of reducing the health cost for pesticide application were to train the farmers for knowledge of pesticide application and occupational safety, to provide convenient and cheap protective equipment and instructions of pesticide application and to standardize pesticide labels.