Objective To determine whether B-type natriuretic peptide （BNP） levels combined with Spontaneous breathing trial (SBT) could improve the weaning outcome. Methods Eighty-three patients who were ready to undergo a 90-minute weaning trial （low-pressure support level） were enrolled .Weaning was considered to be successful if the patient passed the trial and sustained spontaneous breathing for more than 48 h after extubation. Plasma BNP was measured just before and at the end of the trial. All patients were divided into a weaning success group and a weaning failure group according to the outcomes of weaning. Categorical variables，expressed as percentages，were analyzed with a chi-square test or a Fisher’s exact test. Continuous variables were expressed as median （25th-75th percentile） and were compared using the Wilcoxon paired test （for related samples） or the Kolgomorov-Smirnov test （for independent samples）. A two-tailed p value of less than 0.05 was taken to indicate statistical significance. Receiver operating characteristic （ROC） curve analysis was performed to assess plasma BNP’s ability to discriminate the subjects who weaned succesfully or failed. Results Overall，13 patients （16.7%） failed the weaning process （6 patients passed the trial but failed extubation）. At the end of SBT，the BNP levels of the weaning failure group were significantly higher than the weaning success group. The BNP levels of the weaning failure group were significantly higher than the weaning success group （Plt;0.001）. The area under cure （AUC） of the ROC curve of BNP to predict the failure of weaning was 0.94±0.03 （Plt;0.001）.At a cut-off level of 123 pg/mL,BNP had a predictive efficiency in weaning outcome as Yourdon’s index of 0.837，sensitivity of 92.3%，and specificity of 91.4%. Conclusion Monitoring the change of BNP during a SBT may improve weaning outcome.
【摘要】 目的 应用受试者工作特征曲线（receiver operating characteristic curve，ROC曲线）探讨α-L-岩藻糖苷酶（AFU）对恶性腹水和非结核良性腹水的诊断价值。 方法 2004年7月—2008年1月对213例诊断明确的良、恶性腹水（其中良性腹水117例、恶性腹水96例）AFU活性进行检测。采用ROC曲线评价AFU的诊断灵敏度、特异度、准确性、阳性预测值、阴性预测值、阳性似然比、阴性似然比及Youden指数，评价其诊断效率。 结果 恶性腹水组AFU水平（164.96±87.72） μmol/（L•h），良性腹水组（104.02±62.07） μmol/（L•h），两者比较差异有统计学意义（Plt;0.01）。AFU诊断恶性腹水的ROC 曲线下面积为0.754±0.034，最佳分界值101.95 μmol/（L•h）。以AFU≥101.95 μmol/（L•h）来预测恶性腹水，其诊断的灵敏度为82.3%，特异度为63.2%，准确性为72.8%、阳性预测值为65.3%、阴性预测值为83.1%、阳性似然比为2.23、阴性似然比为0.28及Youden指数为0.455。 结论 腹水AFU活性检测有助于恶性腹水和非结核良性腹水的鉴别诊断，是一个比较理想的实用指标，适合于基层医院的临床应用。【Abstract】 Objective To assess the value of α-L-fucosidase (AFU) levels with receiver operating characteristic curve (ROC curve) in the diagnosis of malignant and non-tuberculous benign ascites. Methods Ascitic AFU activity was measured in 213 patients (117 with benign ascites and 96 with malignant ascites) diagnosed with benign or malignant ascites. The diagnostic sensitivity (SEN), specificity (SPE), accuracy, positive predictive value (PV+), negative predictive value (PV-), positive likelihood ratio (LR+), negative likelihood ratio (LR-) and Youden index (YI) of AFU were assessed with receiver operating characteristic curve, and the diagnostic effectiveness of AFU was evaluated. Results The average level of AFU in the malignant group [(164.96±87.72) μmol/(L•h)] was significantly higher than that in the benign group [(104.02±62.07) μmol/(L•h)] (Plt;0.01). The area under the curve (AUC) of the ROC curve of AFU was 0.754±0.034 for malignant ascites diagnosis, and the optimal cut-off value was 101.95 μmol/(L•h). When an AFU level equal to or higher than 101.95 μmol/(L•h) was used to predict malignant ascites, the diagnostic sensitivity was 82.3%, specificity was 63.2%, accuracy was 72.8%, PV+ was 65.3%, PV- was 83.1%, LR+ was 2.23, LR- was 0.28 and YI was 0.455. Conclusion Detection of AFU activity in ascites is helpful to differentiate the diagnose between malignant and non-tuberculous benign ascites, which is a relatively ideal index to fit for clinical application of local hospitals.
ObjectiveTo investigate the feasibility of quantitative detection of WBC count and bacteria count with UF-1000i urinary sediment analyzer in rapid screening for urinary tract infection by receiver operator characteristic (ROC) curve. MethodsFrom August to December 2013, we used quantitative bacterial culture and UF-1000i automatic urine sediment analyzer respectively to examine asepsis urine specimens of 218 patients with suspected urinary tract infection. Among them, there were 95 males and 123 females, with an average age of 54.7 years old. ResultsAmong the 218 urinary samples, 65 were culture positive specimens. With positive urine culture as the gold standard for making ROC curve, the area under ROC curve for WBC count and bacterial numbers by UF-1000i urine sediment analyzer were respectively 0.839 and 0.894. The cut-off values of Youden index for optimal WBC cell count and bacterial count were ≥31.0/μL and 38.8/μL, respectively. When the above numbers were used as cut-off values, the WBC count sensitivity and specificity were 78.3% and 80.4%, the positive likelihood ratio was 3.99, and the negative likelihood ratio was 1.11. And the bacterial count sensitivity and specificity were 84.3% and 80.6%, the positive likelihood ratio was 4.30, and the negative likelihood ratio was 0.80. ConclusionUsing white blood cell count ≥31/μL and bacterial count ≥38.8/μL detected by UF-1000i urine sediment analyzer as the cut off values of noninvasive screening indexes has a very important value in screening for urinary tract infection in the early stage, determining whether there is a need for urine culture, and guiding clinical rational application of antibiotics
Objective To explore the diagnostic value of a disintegrin-like and metalloproteinase with thrombospondin type 1 motifs (ADAMTS)-9 in acute aortic dissection (AAD). Methods A total of 328 patients with acute onset of chest pain within 24 hours were enrolled in West China Hospital from January 2015 to June 2016 and according to the results of computed tomography angiography they were divided into an AAD group (n=172, 107 males, 65 females, mean age of 50.4±13.1 years) and a control group (n=156, 89 males, 67 females, mean age of 54.9±14.7 years). The enzyme-linked immunosorbent assay (ELISA) test was used to measure the level of ADAMTS-9. Results Patients in two groups had no significant difference in age, gender, smoke history, hypertension history, total cholesterol, triacylglyceride and hemoglobin (P>0.05). But systolic and diastolic blood pressures were significantly higher in the AAD group than those in the control group (P<0.05, respectively). The level of ADAMTS-9 was significantly higher in the AAD group than that in the control group (249.4±186.8 ng/mlvs. 78.2±48.6 ng/ml,t=11.107, P<0.001). Receiver operating characteristic curve analysis showed that ADAMTS-9 (156.7 ng/ml) was predictive in the diagnosis of AAD with sensitivity of 0.942 and specificity of 0.628. Conclusion ADAMTS-9 might be an effective and important biomarker in diagnosis of AAD.
Objective To screen the key genes in childhood therapy-resistant asthma by bioinformatic method, and to verify its expression and diagnostic value in peripheral blood of children with therapy-resistant asthma. Methods The transcriptome dataset GSE27011 of peripheral blood mononuclear cells from healthy children (healthy control group), mild asthma (MA) children (MA group) and severe asthma (SA) children (SA group) was downloaded from the Gene Expression Omnibus of the National Center for Biotechnology Information of the United States. Key genes were obtained by using R software for gene differential expression analysis, weighted gene co-expression network analysis (WGCNA) and clinical phenotypic correlation analysis. The differential expression levels of key genes were verified in children with asthma and immune cell transcriptome datasets. Seventy-eight children with asthma and 30 healthy children who were diagnosed in the Department of Pediatrics of Tangshan People’s Hospital between September 2020 and September 2021 were selected and divided into control group, MA group and SA group. Peripheral blood samples from children with asthma and healthy children who underwent physical examination were collected to detect the expression levels of key genes and inflammatory factors interleukin (IL)-4 and IL-17 in peripheral blood of children. Receiver operating characteristic curve was used to evaluate the sensitivity, specificity and accuracy of key genes in predicting childhood therapy-resistant asthma. Results The key gene GNA15 was obtained by bioinformatic analysis. Analysis of asthma validation dataset showed that GNA15 was up-regulated in asthma groups, and was specifically expressed in eosinophils. Clinical results showed that the expression levels of IL-4, IL-17 and GNA15 among the three groups were significantly different (P<0.05). The expression levels of IL-4 and IL-17 in the MA group and the SA group were higher than those in the control group (P<0.05). Compared with the control group and the MA group, the expression level of GNA15 in the SA group was up-regulated (P<0.05). Neither the difference in the expression level of IL-4 or IL-17 between the MA group and the SA group, nor the difference in the expression level of GNA15 between the control group and the MA group was statistically significant (P>0.05). The specificity, sensitivity and accuracy of GNA15 in predicting SA were 92.90%, 80.00% and 86.10%, respectively. Conclusion GNA15 has a significant clinical value in predicting the childhood therapy-resistant asthma, and may become a potential diagnostic marker for predicting the severity of asthma in children.
To investigate the γ pass rate limit of plan verification equipment for volumetric modulated arc therapy (VMAT) plan verification and its sensitivity on the opening and closing errors of multi-leaf collimator (MLC), 50 cases of nasopharyngeal carcinoma VMAT plan with clockwise and counterclockwise full arcs were randomly selected. Eight kinds of MLC opening and closing errors were introduced in 10 cases of them, and 80 plans with errors were generated. Firstly, the plan verification was conducted in the form of field-by-field measurement and true composite measurement. The γ analysis with the criteria of 3% dose difference, distance to agreement of 2 mm, 10% dose threshold, and absolute dose global normalized conditions were performed for these fields. Then gradient analysis was used to investigate the sensitivity of field-by-field measurement and true composite measurement on MLC opening and closing errors, and the receiver operating characteristic curve (ROC) was used to investigate the optimal threshold of γ pass rate for identifying errors. Tolerance limits and action limits for γ pass rates were calculated using statistical process control (SPC) method for another 40 cases. The error identification ability using the tolerance limit calculated by SPC method and the universal tolerance limit (95%) were compared with using the optimal threshold of ROC. The results show that for the true composite measurement, the clockwise arc and the counterclockwise arc, the descent gradients of the γ passing rate with per millimeter MLC opening error are 10.61%, 7.62% and 6.66%, respectively, and the descent gradients with per millimeter MLC closing error are 9.75%, 7.36% and 6.37%, respectively. The optimal thresholds obtained by the ROC method are 99.35%, 97.95% and 98.25%, respectively, and the tolerance limits obtained by the SPC method are 98.98%, 97.74% and 98.62%, respectively. The tolerance limit calculated by SPC method is close to the optimal threshold of ROC, both of which could identify all errors of ±2 mm, while the universal tolerance limit can only partially identify them, indicating that the universal tolerance limit is not sensitive on some large errors. Therefore, considering the factors such as ease of use and accuracy, it is suggested to use the true composite measurement in clinical practice, and to formulate tolerance limits and action limits suitable for the actual process of the institution based on the SPC method. In conclusion, it is expected that the results of this study can provide some references for institutions to optimize the radiotherapy plan verification process, set appropriate pass rate limit, and promote the standardization of plan verification.