ABSTRACT
Objective:To screen appropriate techniques of cardiovascular diseases (CVD) prevention in primary care based on patient-centered model.Methods:The preliminary list of techniques used for CVD prevention in primary care was formed through literature study and focus group discussion. The evaluation index system of technical suitability was constructed by literature research and expert judgment. Delphi method was used to screen and evaluate the list of appropriate techniques.Results:Thirteen experts in fields of general practice and cardiovascular medicine were invited for consultation. The formed index system of appropriate techniques in primary care composed of five aspects: scientificity, effectiveness, applicability, economy and requirement, with the weight coefficients of 0.205, 0.202, 0.205, 0.196 and 0.192, respectively. Twenty-four experts in fields of general medicine, cardiovascular medicine, public health and mental health were selected for two rounds of Delphi expert consultation. The experts′ positive coefficients of the first round and second consultation were 91.67%(22/24) and 100.00%(22/22), respectively. The experts′ authoritative coefficient of two rounds was both 0.92 with the coefficient of variation all<0.3. A list of techniques was developed consisting of 25 appropriate techniques of CVD prevention in primary care. The comprehensive evaluation showed that the top three were techniques of history collection and physical examination, techniques of recognition and referral of acute patients and techniques of patient reception in general practice.Conclusion:Based on the patient-centered model, after screening and evaluation this study has developed a list of appropriate techniques for CVD prevention and management at primary care, which provides technical support to general practitioners and their teams for better care of cardiovascular diseases in their practice.
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Objective:To construct a simple, precise and personalized comprehensive nomogram for prediction the risk of multidrug-resistant tuberculosis (MDR-TB) and to evaluate its prediction value among individuals with previous tuberculosis history (PTBH).Methods:A matched case-control study (1∶2 ratios) was performed in 1 881 patients with PTBH treated in 12 designated tuberculosis hospitals in Hangzhou City between January 1, 2005 and December 31, 2019, and there were 1 719 patients in training set, and 162 in validation set. A multivariable Cox regression analysis was used to evaluate independent predictors for the incident of MDR-TB in individuals with PTBH. A comprehensive nomogram was developed based on the multivariable Cox model. The accuracy of the prediction was assessed using concordance index (C-index), calibration curve and area under the receiver operator characteristic (ROC) curve.Results:The nomogram constructed based on the multivariable Cox regression model incorporated 10 independent predictors of the risk of MDR-TB. A history of direct contact (grade 1, 0-100.0 points) ranked on the top of all risk factors, followed by duration of positive sputum culture (grade 2, 0-84.5 points), unfavorable treatment outcome (grade 3, 0-52.0 points), human immunodeficiency virus infection (grade 4, 0-48.5 points), retreated tuberculosis history (grade 5, 0-40.0 points), non-standardized treatment regimens of retreated tuberculosis (grade 6, 0-32.5 points), duration of pulmonary cavities (grade 7, 0-31.0 points), passive mode of tuberculosis case finding (grade 8, 0-25.0 points), age<60 years (grade 9, 0-17.5 points), and standard frequencies of chest X-ray examination (grade 10, 0-14.0 points). The C-indexes of this nomogram for the training and validation sets were 0.833 (95% confidence interval ( CI) 0.807-0.859) and 0.871 (95% CI 0.773-0.969), respectively, indicating that the nomogram had good fitting effect. The calibration curves for the risk of incident MDR-TB showed an optimal agreement between nomogram prediction and actual observation in the training and validation sets, respectively.The areas under ROC curve of the 1-year, 5-year, and 10-year MDR-TB risk probability of the training set were 0.904, 0.921, and 0.908, respectively, and those of the validation set were 0.954, 0.970, and 0.919, respectively. Conclusion:Through this nomogram model, clinicians could precisely predict the risk of incident MDR-TB among individuals with PTBH in the clinical practice.
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Objective:To investigate the compliance of statins and influencing factors in population with cardiovascular risks in the community.Methods:One hundred and eighty-six residents with cardiovascular disease risks in a community of Tianjin were recruited from June 2017 to October 2017. The Chinese revised version of the compliance Morisky scale was used to assess the compliance, and the influencing factors were analyzed.Results:Among all subjects 119 were prescribed with statins (64.0%,119/186) , of whom 7.6% (9/119) did not take the drug. According to the risk assessment of arteriosclerotic cardiovascular disease (ASCVD) in the next 10 years, among the 110 subjects taking the medicine, there were 18 subjects with intermediate risk and 92 with high risk. The subjects with good compliance accounted for 30.0% (33/110), and those with poor compliance accounted for 70.0% (77/110). Univariate analysis showed that education level, occupation, and drug types were significantly associated with statin compliance ( P<0.05). Multivariate logistic regression analysis showed that higher education level and fewer total drug users were correlated with better compliance ( OR=3.530 and 0.388, P<0.05) . The reasons for subjects not taking medicine were fearing of adverse reactions ( n=6, 6/9) , and thinking no symptoms and no need to have medication ( n=3, 3/9).The reasons of poor medication adherence were thinking no symptoms and no need to have medication ( n=31, 40.2%), thinking ineffectiveness of medication ( n=28, 36.4%), fearing of adverse reactions ( n=16, 20.8%), and economic pressure ( n=2, 2.6%). Conclusions:The proportion of residents with poor compliance of statins is high in the community. It is suggested that targeted interventions and standardized management for subjects with cardiovascular risks should be conducted based on the related factors found in the study.