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ObjectiveTo investigate the influencing factors associated with delayed time in pre-hospital emergency medical care in patients with hypertensive emergency in the main urban area of Chongqing. MethodsA total of 1 246 patients with hypertension in the main urban area of Chongqing from March 2018 to August 2021 were included in this study. The delayed time in the pre-hospital emergency medical care was determined. A multivariate linear regression model was used to analyze the influencing factors. ResultsThe delayed time in the pre-hospital emergency medical care for the patients with hypertensive emergency was concentrated in 0‒12 h， with the average of （5.89±1.96） h. The delayed time differed significantly by gender， age， history of atrial fibrillation， diabetes， educational level， time of onset， mode of transportation， awareness of hypertensive emergency， blood pressure at the onset， and presence of persons at the onset of emergency （P<0.05）. Multivariate linear regression analysis showed that educational level， time of onset， blood pressure at the onset， awareness of hypertensive emergency， presence of persons at the onset were linearly correlated with delayed time in the pre-hospital medical care for hypertensive emergencies （P<0.05）. ConclusionDelay in pre-hospital medical care is prevalent for patients with hypertensive emergency in the main urban area of Chongqing. The delayed time is associated with multiple factors， such as educational level， time of onset， blood pressure at onset， awareness of hypertensive emergency， and presence of persons at onset. It warrants further improvement in the interventions to reduce the delay in the pre-hospital medical care.
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OBJECTIVE@#To study the difference in age estimation based on quantitative analysis of DNA methylation by MassARRAY and pyrosequencing techniques.@*METHODS@#The methylation levels of 9 CpG sites from two independent whole blood sample sets (containing 65 and 62 samples) were detected using MassARRAY and pyrosequencing techniques. Z-score transformation was used to remove the batch effects of different techniques, and a linear regression model was used for age prediction.@*RESULTS@#For age prediction using the MassARRAY system, the 65 samples showed a mean absolute difference (MAD) of 2.49 years before Z-score transformation of the data and 2.44 years after the transformation, similar to the results in the 62 samples (MAD of 3.36 years before and 3.42 years after Z-score transformation). For data typed from pyrosequencing, the 65 samples showed a MAD of 4.20 years before and 2.76 years after data Z-score transformation, also similar to the results in the 62 samples (MAD of 3.92 years before and 3.63 years after data transformation).@*CONCLUSIONS@#Z-score transformation can effectively reduce the system batch effect between MassARRAY and pyrosequencing. Data from the MassARRAY system allows direct age estimation without further data processing, while the pyrosequencing data may increase the error in age estimation, which can be corrected by Z-score transformation of the data.
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Ilhas de CpG/genética , Metilação de DNA , Sequenciamento de Nucleotídeos em Larga Escala , Modelos Lineares , Análise de Sequência de DNARESUMO
OBJECTIVE: To monitor and investigate the influencing factors of 6-methylmercaptopurine ribonucleotides (6-MMPR) in human red blood cell (RBC) in Chinese kidney transplant recipients treated with azathiopurine (AZA), and to provide references for clinical personalized medicine. METHODS: In 100 Chinese kidney transplant recipients, the concentration of 6-MMPR in RBC was detected by validated HPLC-UV method. Correlation analysis was performed to analyze the effects of various factors, including patient age, gender, weight, AZA dose and thiopurine S-methyltransferase (TPMT) activity, on the 6-MMPR concentration, and multivariate linear regression analysis was performed using SPSS20.0 software to investigate the influencing factors of 6-MMPR concentration. RESULTS: The concentration of 6-MMPR in 100 Chinese kidney transplant recipients was not normally distributed (P0.05), however, there was a significant positive correlation between TPMT activity and 6-MMPR concentration in RBC (P<0.001). CONCLUSION: TPMT activity in RBC is an independent factor affecting 6-MMPR concentration, which in turn affects the clinical efficacy and toxicity of the drug.
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Objective:To obtain the volume of thoracolumbar vertebral(T12-L5)in elderly people by CT post processing software, and establish the calculation formula of lumbar vertebral body volume from L1 to L4.Methods: Collect the elderly lumbar CT examination cases, 60 normal elderly people without lumbar lesions were included in this study. The volume of each vertebral body from T12 to L5 was obtained by processing software after a lumbar CT scan. The volume values of vertebral body from L1 to L4 were regarded as dependent variables and the volumes of upper and lower vertebral body was considered as independent variables. All the data were analyzed with multiple linear regression method.Results: There was a correlation between the volume of each lumbar vertebral from L1 to L4 and volumes of adjacent vertebral bodies, and the multivariate linear regression equation between them was obtained successfully.Conclusion: The volume of vertebral body can be accurately measured by CT processing software, and the calculation formula can be used to predict the normal vertebral volume value before fracture. The ratio of bone cement quantity to vertebral volume value can be earned and used to guide the operation of bone cement implantation for the further study.
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Objective To explore health-related quality of life (HRQOL) in patients with chronic Keshan disease in China and the influence factors.Methods According to the Diagnosis of Keshan Disease (WS/T 210-2011),146 patients with chronic Keshan disease were selected from the follow-up chronic Keshan disease patients with standard treatment in Shandong.The HRQOL was assessed in those patients by use of the Chinese version of SF-36.Correlation analysis and multiple linear regression were used to analyse the influence factors of HRQOL.Results All dimension scores were significantly lower than those of general population (t =-5.12--13.13,all P ＜ 0.01).There were significant differences in Role-Physical dimensions (RP,F =47.09,P ＜ 0.01) and Physiological Function dimension (PF,F =31.49,P ＜ 0.01) between patient groups with different severity of left ventricular ejectio,n fraction (LVEF),RP dimension (F =8.47,P ＜ 0.01) and Vitality dimension (VT,F =11.29,P ＜ 0.01) in patients varies with left ventricular end-diastolic dimension (LVEDD).The scores of some dimensions were correlated with age,family income,course of disease,LVEF and LVEDD,heart function grading,labor ability (r =-0.49-0.36,P ＜ 0.05 or ＜ 0.01).The multivariate linear regression analysis indicated that the influencing factors of physiological status were NYHA cardiac function classification,course of disease,family income and body mass index (BMI).The influencing factor of mental health states was NYHA cardiac function classification.The influencing factors of the total HRQOL score were NYHA cardiac function classification,course of disease and family income.Conclusions The HRQOL of patients with chronic Keshan disease is significantly declined as compared with the general population and the lowest is RP.NYHA functional class,course of disease and family income are relative dominant predictor of patients HRQOL among all variables.
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Objective To analyze main influencing factors of hospitalization expenses by support vector machine modeling,and explore effective influence factors analysis methods of medical expenses. Methods Random selection of six hospitals in Zhejiang province.Using hospital electronic medical record system of the hospitals and selecting three kinds of typical diseases of internal medicine and surgery,to build the support vector machine model,BP neural network model,and multiple linear regression model for comparison of analysis results.The SVM model is used to analyze three various diseases.Results The support vector machine model based on radial basis kernel function scored the highest prediction accuracy on the hospitalization expenses,up to 96.07%.In a mixed analysis of different diseases,analysis results of all three models pointed the main influence factors of hospitalization expense as days of stay,disease types,and hospital coding for the surgery.In the analysis by diseases individually,the influencing factors, though varying with diseases, key factors remain the same. Conclusion The support vector machine in the influence factor analysis is feasible in hospitalization expenses.According to the analysis results,the single disease payment system can be made rationally, which can effectively control excessive growth of medical expenses.
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Through analyzing the representative indicators reflecting the real success of the New Rural Cooperative Medical System (NRCMS): including the participation rate and the degree of protection, to study its influencing factors and to reveal the effectiveness and connotation of NRCMS. The result shows that NRCMS processes wider coverage and stronger protection, highlights the effects of health care subsidies for poor farmers in the mid and west. But the government also should uphold the principle of prudence in measuring and choosing different performance targets, and focus on the issue of fairness among poor farmers.