目的 探讨成都地区高尿酸血症发生的危险因素。 方法 收集2009年10月－2010年4月在四川大学华西医院体检中心进行健康体检的36 639人的临床资料，对资料进行单因素分析和多因素logistic回归分析。 结果 进行健康体检的36 639人，其中男21 175人，女15 464人。高尿酸血症患者5 233例，患病率为14.3%。年龄＞50岁、男性、饮酒、糖尿病、高血压病、甘油三酯增高、低密度脂蛋白增高和血清肌酐水平增高与高尿酸血症的发生有关。Logistic回归分析显示男性（OR=13.300，P=0.000）、饮酒（OR=4.219，P=0.009）、糖尿病（OR=3.609，P=0.024）是发生高尿酸血症独立危险因素。 结论 成都地区高尿酸血症的患病率略高于全国平均水平，临床治疗和护理高尿酸血症的患者时应积极控制与高尿酸血症发生密切相关的危险因素。
ObjectiveTo explore the selection problem of independent variables and stepwise regression method for multiple logistic regression analysis. MethodsAccording to the data of the case-control investigation for coronary heart disease, age (X1), hypertension history (X2), hypertension family history (X3), smoking (X4), hyperlipidemia history (X5), animal fat intake (X6), weight index (X7), type A personality (X8), and coronary heart disease (CHD, Y) were analyzed by SPSS 18.0 software. The multiple logistic regression analysis was done and the differences of risk factors were compared among 6 kinds stepwise regression variable selection method. ResultsThe univariate analysis showed that no difference was found between CHD group and non-CHD group in age distribution (P=0.116). But the multivariate logistic regression analysis showed that, comparing to population over 65 years old, age was a protective factor on the low age groups (OR< 45=0.100, 0.000 to 0.484, P=0.020; OR45-54=0.051, 0.003 to 0.975, P=0.048). If the age was defined as categorical variable, the risk factors for coronary heart disease were animal fat intake (X6), type A personality (X8), hypertension history (X5) and age (X1), respectively (P < 0.05). If the age was defined as a continuous variable, the effect of age (X1) was not statistically significant (P=0.053). The common risk factors were intake of animal fat (X6) and type a personality (X8) by six kinds method of stepwise variable selection. In addition, the risk factor also included hyperlipidemia history (X5) (forward-condition, forward-LR, forward-wald), hypertension family history (X3), age (X1) (backward-condition, backward-LR) and hypertension history (X2) (backward-wald). ConclusionStepwise regression method should be used to analyze all the variables, including no statistically significant independent variables in univariate analysis. If the categorical variable is regarded as continuous variables, some information may be lost, and even the risk factors may be missed. When the risk factors are not the same by several stepwise regression variable selection method, it should be combined with clinical and epidemiological significance, as well as biological mechanisms and other professional knowledge.
Objective To construct and compare logistic regression and decision tree models for predicting systemic inflammatory response syndrome (SIRS) in patients with type B aortic dissection (TBAD) after interventional surgery. Methods A retrospective analysis was conducted on clinical data of TBAD patients at Peking University Shenzhen Hospital from 2020 to 2024. The patients were divided into a SIRS group and a non SIRS group based on whether SIRS occurred within 24 hours after surgery. Multivariate logistic regression was used to analyze the influencing factors of SIRS occurrence in TBAD intervention patients, and a decision tree model was constructed using SPSS Modeler to compare the predictive performance of the two models. Results A total of 742 patients with TBAD were included, including 579 males and 163 females, aged between 27 and 97 (58.85±10.79) years. Within 24 hours after intervention, a total of 506 patients developed SIRS, with an incidence rate of 68.19%. Logistic regression analysis showed that the extensive involvement of the dissection, the surgical time≥ 2 hours, PET coated stents implanted, serum creatinine, white blood cell count, C-reactive protein, monocyte count (MONO), neutrophil count levels elevated, estimated glomerular filtration rate and decreased albumin levels were independent risk factors for SIRS (P<0.05). The decision tree model selected a total of 10 explanatory variables and 6 layers with 37 nodes, among which MONO was the most important predictor. The area under the decision tree model curve was 0.829 [95% CI (0.800, 0.856)], which was better than the logistic regression model's 0.690 [95% CI (0.655, 0.723)], and the difference was statistically significant (P<0.001). Conclusion The incidence of SIRS after TBAD intervention is high, and the decision tree model has better predictive performance than logistic regression. It can identify high-risk patients with higher accuracy and provide a practical tool for early clinical intervention.
ObjectiveTo learn the outcomes of hepatitis B virus (HBV)-related acute-on-chronic liver failure (ACLF) cases after artificial liver support system (ALSS) treatment and the relevant factors correlated with the clinical outcomes. MethodsIn the period from January 2011 to June 2014, 321 patients with HBV-ACLF were admitted to West China Hospital. The clinical data at baseline, before and after treatment were analyzed by univariate and multivariate logistic regressions to identify the independent risk factors correlated with 30-day outcomes. ResultsOf all the 321 patients, 233 survived and 88 died by the end of a 30-day observation. The univariate analysis identified that the incidences of cirrhosis, hepatorenal syndrome and peritonitis in the death group were significantly higher (P<0.05). The model for end-stage liver disease values, white blood cells (WBC), blood ammonia, creatinine and total bilirubin (TBIL) at different stages in the death group were significantly higher than those in the survival group (P<0.05). In the death group, the HBV-DNA, TBIL decrease after triple ALSS treatments, baseline prothrombin time activity (PTA) and PTA level after triple ALSS treatments were significantly lower (P<0.05). The multivariate logistic regression indicated that WBC (OR=2.337, P<0.001) and TBIL level after triple ALSS treatments (OR=4.935, P<0.001) were independent predicting factors for death within 30 days after ALSS treatment; HBV-DNA (OR=0.403, P<0.001), the decrease of TBIL after triple ALSS treatments (OR=0.447, P<0.001) and PTA level after triple ALSS treatments (OR=0.332, P<0.001) were protecting factors for the 30-day prognosis. ConclusionThese five factors including WBC, HBV-DNA, PTA, TBIL and TBIL decrease after triple ALSS treatments influence the short-term prognosis for HBV-ACLF patients, which are valuable for decision making in clinical practices.
Objective To investigate the feasibility of diagnosis of potential chronic obstructive pulmonary disease (COPD) patients who cannot finish the pulmonary function test via biphasic CT scan. Methods Sixty-seven male individuals aged 43 to 74 (57.0±5.9) years were divided into a COPD group (n=26) and a control group (n=41). All individuals underwent biphasic quantitative CT scan for calculating the proportion of emphysema, functional small airway disease, and normal component of the whole lung and each lobe. Results Based on principle component analysis, two principal components “imaging feature function 1 and imaging feature function 2” were calculated and analyzed by logistic regression, which found that imaging feature function 1 was an independent risk factor of COPD (odds ratio=8.749, P<0.001), and imaging features function 1 could be used to assist the diagnosis of COPD (area under receiver operating characteristic curve=0.843, P<0.001). Conclusion Imaging features function 1 is an independent risk factor for COPD and can assist the diagnosis of COPD.
Objective To analyze the substitution mechanism of surrogate endpoints for traditional Chinese medicine (TCM) clinical efficacy evaluation of chronic heart failure (CHF). Methods To obtain data from the occurrence of surrogate endpoints and cardiogenic death of patients with CHF in 7 hospitals. The causal relationship between surrogate endpoints and cardiogenic mortality was inferred by the Bayesian network model, and the interaction among surrogate endpoints was analyzed by non-conditional logistic regression model. Results A total of 2 961 patients with CHF were included. The results of Bayesian network causal inference showed that cardiogenic mortality had a causal relationship with the surrogate endpoints including NYHA classification (P=0.46), amino-terminal pro-B-type natriuretic peptide (NT-proBNP) (P=0.24), left ventricular ejaculation fraction (LVEF) (P=0.19), and hemoglobin (HB) (P=0.11); non-conditional logistic regression analysis showed that NYHA classification had interaction with NT-proBNP, LVEF, and HB prior to and after adjusting confounders. Conclusions The substitution capability of surrogate endpoints for TCM clinical efficacy evaluation of CHF for cardiogenic mortality are NYHA classification, NT-proBNP, LVEF, and HB in turn, and there is a multiplicative interaction between the main surrogate endpoint NYHA classification and the secondary surrogate endpoints including NT-proBNP, LVEF, and HB, suggesting that when the two surrogate endpoints with interaction exist at the same time, it can enhance the substitution capability of surrogate endpoints for cardiogenic mortality.
Early detection of vascular function plays an important role in the prevention and treatment of cardiovascular diseases (CVDs). This paper reports the main studies of the effectiveness of fingertip temperature curve in digital thermal monitoring (DTM) for predicting CVDs, as well as the relationship between parameters from DTM and pulse wave velocity (PWV) detection. A total of 112 subjects [age (42.18±12.28) years, 50% male, 37 with known CVDs] underwent DTM and PWV detection. Results showed that most of parameters related to CVDs were from the declining stage of the digital thermal signal. Binary Logistic regression models were built, and the best one was chosen by ten-fold validation to predict CVDs. Consistency was great between the detection result of PWV and that of the Logistic model of DTM parameters. Parameters from DTM also contained information for early detecting of vascular stiffness. This study indicates that the fingertip temperature curve in DTM has a potential application for predication of CVDs, and it would be used to access vascular function in the initial stage of CVDs.
Objective To investigate the status of deciduous caries and early childhood caries among 3-5 year-old children of Uyghur and Chinese in Urumqi, and to explore the correlative factors of early childhood caries. Methods According to the criteria recommended by the Third National Oral Health Investigation, and Oral Health Surveys: Basic Methods of World Health Organization, the deciduous caries of 474 Urghur and Chinese children aged from three to five in nine kindergartens were clinically examined. Data were collected by questionnaire from their parents, and the result waw analyzed using Logistic regression analysis. Results The result of logistic regression analysis showed that the variables including nationality, frequency of drinking milk, eating cookie or drinking sweet beverage before sleep, brushing teeth with help, and educational background of the mother were closely related to the incidence of infantile caries. Conclusion The nationality, frequency of drinking milk, eating cookie or drinking sweet beverage before sleep, brushing teeth with help, and educational background of the mother are correlative factors of early childhood caries. Necessary methods for prevention of deciduous caries must be taken into consideration as early as possible, and the bilingual propaganda for preventing and treating caries should be also highly emphasized.
ObjectiveTo investigate the correlative factors for the efficacy of surgical treatment for single segment degenerative lumbar spinal disorders. MethodsFrom October 2008 to November 2010, a prospective non-randomized controlled study was carried out on 179 patients who were diagnosed to have L4-5 degenerative lumbar spinal disorders and underwent surgical treatment. Ninety-seven patients were included in our study, including 64 males and 33 females, aged between 21 and 86 years old, averaging 49.0. The follow up lasted for an average of 18.9 (12-27) months. The correlative factors including age, sex, body mass index, preoperative psychological state and degree of low back pain, surgical methods, combination with adjacent segment degeneration and recurrence state were analyzed. Single and multiple-factor Logistic regression analysis was used to determine the relationship between independent factors and surgical results of lumbar degenerative disease. ResultsAt the last follow-up, Japanese Orthopaedic Association scores were improved to 22.40±3.18 with an improving rate of (68.5±15.7)% compared with the preoperative condition (7.61±3.09), and the difference was significant (t=-33.031, P<0.001). Univariate analysis showed that all factors were variables associated with the surgical results excluding sex and age (P<0.05). Multiple-factor logistic regression analysis showed that the preoperative psychological state, combination with adjacent segment degeneration and surgical methods had important impact on the surgical results (P<0.05). ConclusionSurgical treatment of lumbar degenerative disease is effective. The preoperative psychological state, combination with adjacent segment degeneration and surgical methods are important factors associated with the surgical results.