Purpose To evaluate the screening efficacy of a self-designed questionnaire for chronic obstructive pulmonary disease (COPD) and the potential gender disparity in its efficacy. Patients and Methods A screening questionnaire, the COPD Screening Questionnaire-Minhang (COPD-MH), was designed with reference to the self-scored COPD population screener (COPD-PS) and the COPD screening questionnaire (COPD-SQ), incorporating characteristics of the local population in Shanghai, China. The revised questionnaire included only five questions. Each question scored 0–4, with a highest total score of 20. The COPD-PS and COPD-SQ comprised 5 and 7 questions, respectively. Their scoring criteria were not consecutive integers and, thus, not easily counted. The COPD-MH focused on symptoms, and each item was set the same answers for convenience. Screening for COPD was conducted among residents over 40 years old in a community in Shanghai using the three aforementioned questionnaires. Each participant also received spirometry tests. A receiver operator characteristic (ROC) curve was drawn, and the area under the curve (AUC) was calculated to assess the validity of each questionnaire. Results A total of 1197 community residents in Minhang District completed the screening. A total of 1023 participants were finally included in analysis with a detected prevalence of 12.4% for COPD. The best cut-off values for the COPD-PS, COPD-SQ, and COPD-MH were 4, 16, and 7 points, respectively. The AUCs for these three questionnaires were >0.5, but the sensitivity of the COPD-MH was higher than those of the COPD-PS and COPD-SQ. The sensitivity of COPD-MH was 80.77% for males and 77.5% for females. The COPD-MH had higher diagnostic efficiency and higher sensitivity with gender-specific cut-off values. Conclusion The COPD-MH is comparable to and less time-consuming than the existing screening methods for COPD. Gender-related factors affect the optimal cut-off values of the COPD screening questionnaire, and rectifying this can improve the practical screening efficacy.
BackgroundTo compare whether the general population, especially those without characteristic symptoms, need spirometry screening for chronic obstructive pulmonary disease (COPD).MethodsResidents aged > 40 years old in Minhang, Shanghai, China, filled out screening questionnaires and underwent spirometry. The structured questionnaire integrating COPD population screening and COPD screening questionnaire was designed to obtain data on demographic characteristics, risk factors of COPD, respiratory symptoms, lifestyle habits, and comorbidities. We assessed the correlations between variables and COPD and the impact factors of FEV1% predicted.ResultsA total of 1,147 residents were included with a newly diagnosed mild to moderate COPD prevalence of 9.4% (108/1,147); half of the patients (54/108) were asymptomatic. Multivariate analysis did not reveal any significant differences in symptoms or lifestyle factors between newly diagnosed COPD patients and non-COPD participants. However, according to the generalized linear model, older age (β = −0.062, p < 0.001), male sex (β = −0.031, p = 0.047), and respiratory symptoms (β = −0.025, p = 0.013) were associated with more severe airflow limitation.ConclusionNewly diagnosed COPD patients had few differences compared with the general population, which suggests that a targeted case finding strategy other than general screening was currently preferred. More attention should be paid to respiratory symptoms when making a diagnosis and exploring new therapies and interventions for COPD in the early stage.
BackgroundThe aim of this study was to derive and validate a decision tree model to predict disease-specific survival after curative resection for primary cholangiocarcinoma (CCA).MethodTwenty-one clinical characteristics were collected from 482 patients after curative resection for primary CCA. A total of 289 patients were randomly allocated into a training cohort and 193 were randomly allocated into a validation cohort. We built three decision tree models based on 5, 12, and 21 variables, respectively. Area under curve (AUC), sensitivity, and specificity were used for comparison of the 0.5-, 1-, and 3-year decision tree models and regression models. AUC and decision curve analysis (DCA) were used to determine the predictive performances of the 0.5-, 1-, and 3-year decision tree models and AJCC TNM stage models.ResultsAccording to the fitting degree and the computational cost, the decision tree model derived from 12 variables displayed superior predictive efficacy to the other two models, with an accuracy of 0.938 in the training cohort and 0.751 in the validation cohort. Maximum tumor size, resection margin, lymph node status, histological differentiation, TB level, ALBI, AKP, AAPR, ALT, γ-GT, CA19-9, and Child-Pugh grade were involved in the model. The performances of 0.5-, 1-, and 3-year decision tree models were better than those of conventional models and AJCC TNM stage models.ConclusionWe developed a decision tree model to predict outcomes for CCA undergoing curative resection. The present decision tree model outperformed other clinical models, facilitating individual decision-making of adjuvant therapy after curative resection.
Objective Estimated maximum oxygen consumption (eVO2max) is superior to six-minute walk distance (6MWD) in predicting functional capacity. The hypothesis that eVO2max is a better predictor of postoperative pulmonary complications (PPCs) than 6MWD in patients undergoing major upper abdominal surgery is evaluated. Method Patients scheduled for elective major upper abdominal surgery from July 2018 to May 2021 were included. The six-minute walk test was carried out on all patients before surgery. eVO2max was calculated using the Burr equation incorporated with 6MWD, age, gender, weight, and resting heart rate. The patients were divided into the PPC and the non-PPC group according to the occurrence of clinically significant PPCs. The sensitivity, specificity, and optimum cutoff point of 6MWD and eVO2 max were analyzed in the prediction of PPCs. The area under the receiver operating characteristic curve (AUC) of 6MWD vs. eVO2max was compared by Z test. Results A total of 308 patients were included in this study; 71/308 developed clinically significant PPCs. Compared to the non-PPCs group, the value of 6MWD (P < 0.001) and eVO2max (P < 0.001) were significantly lower in the PPC group. The optimum cutoff point for 6MWD in predicting PPCs was 372. 5m with a sensitivity of 63.4% and specificity of 79.3%. The optimum cutoff point for eVO2max was 8.8 MET with a sensitivity of 91.6% and specificity of 79.3%. A significantly increased AUC was observed in eVO2max compared to 6MWD (P < 0.001, Z = 4.713). Conclusion eVO2max has a better validity than 6MWD for predicting PPCs in patients undergoing major upper abdominal surgery. The results suggested that eVO2max has the potential to be a valid tool to screen patients with a high risk of PPCs.
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