RESUMEN
Objective:Based on systematic idea of clustering methods, a novel approach for classifying prescriptions was explored in the light of the method of classifying analogous prescriptions.Methods:A total of 581 ancient prescriptions were selected from Treatment Record of Hundreds of Selected Ancient Prescriptions, and the standardized names of Traditional Chinese Medicines in these prescriptions were entered in Microsoft Excel 2007, then imported to SPSS 24.0 to generate dendrograms using the hierarchical clustering function. The classification of 581 selected ancient prescriptions was analyzed. Results:All 581 prescriptions could be classified into 86 categories through repeated clustering, the largest group has 29 prescriptions, the smallest group has 2 prescriptions, and the average group has about 6.75 prescriptions. In general, the later the intercepted group, the lower the similarity of its internal prescriptions.Conclusion:This method could realize the classification of prescriptions in the light of the method of classifying analogous prescriptions, which may help to break the original thinking bondage and further deepen the understanding of compatibility rules of prescriptions. However, its disadvantage lied in that the theoretical clues would be reduced when analyzing the compatibility rules of prescriptions and the issues of drug dosage, nature, taste and meridian categories were not specially considered.
RESUMEN
Objective:To investigate the value of serum microRNA-92a (miR-92a) and microRNA-146a (miR-146a) expression levels combined with lung ultrasound score (LUS) in predicting the severity and prognosis of acute respiratory distress syndrome (ARDS).Methods:116 patients with ARDS admitted to Danzhou People's Hospital from January 2017 to March 2020 were enrolled. On the day of admission, the expression levels of serum miR-92a and miR-146a were detected by real-time fluorescent quantitative reverse transcript-polymerase chain reaction (RT-PCR), and pulmonary ultrasound examination was performed in 12 lung regions, with the total score as LUS score. The difference of each index was analyzed among the ARDS patients with different 28-day prognosis (survival group and death group) and different severity [mild group: 200 mmHg < oxygenation index (OI) ≤ 300 mmHg (1 mmHg = 0.133 kPa), moderate group: 100 mmHg < OI≤200 mmHg, severe group: OI≤100 mmHg]. Multivariate Logistic regression was used to analyze the risk factors of death in patients with ARDS. Receiver operating characteristic (ROC) curve was drawn to analyze the value of miR-92a and miR-146a combined with LUS score in predicting the death of patients with ARDS.Results:116 ARDS patients were included, 39 cases in the death group, 77 cases in the survival group; 20 cases in the mild group, 38 cases in the moderate group and 58 cases in the severe group. The expression levels of serum miR-92a, miR-146a and LUS score in the death group were significantly higher than those in the survival group [miR-92a (2 -ΔΔCt): 3.75±1.64 vs. 2.10±0.78, miR-146a (2 -ΔΔCt): 1.93±0.72 vs. 0.76±0.20, LUS score: 25.80±4.75 vs. 13.40±3.60, all P < 0.01]. With the aggravation of ARDS patients, the expression levels of serum miR-92a and miR-146a and LUS score gradually increased ( F values were 8.115, 6.740 and 6.216 respectively, all P < 0.01). The expression levels of serum miR-92a, miR-146a and LUS score in severe group were significantly higher than those in the moderate group and mild group [miR-92a (2 -ΔΔCt): 3.65±1.62 vs. 2.87±1.16, 1.94±0.68; miR-146a (2 -ΔΔCt): 1.85±0.58 vs. 1.30±0.51, 0.68±0.17; LUS score: 24.15±4.65 vs. 18.60±4.20, 12.20±3.15, all P < 0.01]. Multivariate Logistic regression analysis showed that low OI [odds ratio ( OR) = 2.748, 95% confidence interval (95% CI) was 1.913-6.225, P = 0.024], high LUS score ( OR = 1.685, 95% CI was 1.183-2.758, P = 0.016), high expression levels of serum miR-92a ( OR = 2.560, 95% CI was 1.806-5.627, P < 0.001) and miR-146a ( OR = 1.984, 95% CI was 1.375-3.816, P = 0.008) were independent risk factors for the death of ARDS patients. ROC curve analysis showed that the area under ROC curve (AUC) of patients with ARDS predicted by miR-92a and miR-146a combined with LUS score was significantly higher than that predicted by the three alone (0.918 vs. 0.842, 0.825, 0.807, all P < 0.01), and the sensitivity (94.0%) and specificity (85.2%) were higher. Conclusion:The expression levels of serum miR-92a, miR-146a and LUS score are related to the severity and prognosis of the patients with ARDS, and the combination of the three indicators has better value in predicting the prognosis of the patients with ARDS.