Special thrombocytopenic purpura belongs to "blood sign and spots" in TCM.Starting from TCM,combining with concerned documents over recent 10 years,it sums up its causa morbi,mechanism,differentiation of signs and types and treatment,and discusses the state quo and main application of the combination of TCM and WM in the said disease,therefore puts forwards the advantages of combination of TCM and WM,as well as the characteristic of TCM treating the disease,finally makes analysis and prospect on the shortcomings.

OBJECTIVES: To explore the application of random forest algorithm in screening the risk factors and predictive values for postpartum depression. METHODS: We recruited the participants from a tertiary hospital between June 2017 and June 2018 in Changsha City, and followed up from pregnancy up to 4-6 weeks postpartum.Demographic economics, psychosocial, biological, obstetric, and other factors were assessed at first trimesters with self-designed obstetric information questionnaire and the Chinese version of Edinburgh Postnatal Depression Scale (EPDS). During 4-6 weeks after delivery, the Chinese version of EPDS was used to score depression and self-designed questionnaire to collect data of delivery and postpartum. The data of subjects were randomly divided into the training data set and the verification data set according to the ratio of 3꞉1. The training data set was used to establish the random forest model of postpartum depression, and the verification data set was used to verify the predictive effects via the accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and AUC index. RESULTS: A total of 406 participants were in final analysis. Among them, 150 of whom had EPDS score ≥9, and the incidence of postpartum depression was 36.9%. The predictive effects of random forest model in the verification data set were at accuracy of 80.10%, sensitivity of 61.40%, specificity of 89.10%, positive predictive value of 73.00%, negative predictive value of 82.80%, and AUC index of 0.833. The top 10 predictive influential factors that screening by the variable importance measure in random forest model was antenatal depression, economic worries after delivery, work worries after delivery, free triiodothyronine in first trimesters, high-density lipoprotein in third trimester, venting temper to infants, total serum cholesterol and serum triglyceride in first trimester, hematocrit and serum triglyceride in third trimester. CONCLUSIONS Random forest has a great advantage in risk prediction for postpartum depression. Through comprehensive evaluation mechanism, it can identify the important influential factors for postpartum depression from complex multi-factors and conduct quantitative analysis, which is of great significance to identify the key factors for postpartum depression and carry out timely and effective intervention.
Depression, Postpartum/epidemiology* ; Female ; Humans ; Postpartum Period ; Pregnancy ; Pregnancy Trimester, Third ; Psychiatric Status Rating Scales ; Risk Factors ; Sensitivity and Specificity

OBJECTIVETo study the accuracy of pulse contour cardiac output (PCCO) during blood volume change.

METHODSHemorrhagic shock model was made in twenty dogs followed by volume resuscitation. Two PiCCO catheters were placed into each model to monitor the cardiac output (CO). One of catheters was used to calibrate CO by transpulmonary thermodilution technique (COTP) (calibration group), and the other one was used to calibrate PCCO (none-calibration group). In the hemorrhage phase, calibration was carried out each time when the blood volume dropped by 5 percents in the calibration group until the hemorrhage volume reached to 40 percent of the basic blood volume. Continuous monitor was done in the none-calibration group.Volume resuscitation phase started after re-calibration in the two groups. Calibration was carried out each time when the blood equivalent rose by 5 percents in calibration group until the percentage of blood equivalent volume returned back to 100. Continuous monitor was done in none-calibration group. COTP, PCCO, mean arterial pressure (MAP), systemic circulation resistance (SVR), global enddiastolic volume (GEDV) were recorded respectively in each time point.

RESULTS(1) At the baseline, COTP in calibration group showed no statistic difference compared with PCCO in none-calibration group (P >0.05). (2) In the hemorrhage phase, COTP and GEDV in calibration group decreased gradually, and reached to the minimum value (1.06 ± 0.57) L/min, (238 ± 93) ml respectively at TH8. SVR in calibration group increased gradually, and reached to the maximum value (5 074 ± 2 342) dyn · s · cm⁻⁵ at TH6. However, PCCO and SVR in none-calibration group decreased in a fluctuating manner, and reached to the minimum value (2.42 ± 1.37) L/min, (2 285 ± 1 033) dyn · s · cm⁻⁵ respectively at TH8. COTP in the calibration group showed a significant statistic difference compared with PCCO in the none-calibration group at each time point (At TH1-8, t values were respectively -5.218, -5.495, -4.639, -6.588, -6.029, -5.510, -5.763 and -5.755, all P < 0.01). From TH1 to TH8, the difference in percentage increased gradually. There were statistic differences in SVR at each time point between the two groups (At TH1 and TH4, t values were respectively 2.866 and 2.429, both P < 0.05, at TH2 - TH3 and TH5 - TH8, t values were respectively 3.073, 3.590, 6.847, 8.425, 6.910 and 8.799, all P < 0.01). There was no statistic difference in MAP between the two groups (P > 0.05). (3) In the volume resuscitation phase, COTP and GEDV in the calibration group increased gradually. GEDV reached to the maximum value ((394±133) ml) at TR7, and COTP reached to the maximum value (3.15 ± 1.42) L/min at TR8. SVR in the calibration group decreased gradually, and reached to the minimum value (3 284 ± 1 271) dyn · s · cm⁻⁵ at TR8. However, PCCO and SVR in the none-calibration group increased in a fluctuating manner. SVR reached to the maximum value (8 589 ± 4 771) dyn · s · cm⁻⁵ at TR7, and PCCO reached to the maximum value (1.35 ± 0.70) L/min at TR8. COTP in the calibration group showed a significant statistic difference compared with PCCO in the none-calibration group at each time point (At TR1-8, t values were respectively 8.195, 8.703, 7.903, 8.266, 9.600, 8.340, 8.938, 8.332, all P < 0.01). From TR1 to TR8, the difference in percentage increased gradually. There were statistic differences in SVR at each time point between the two groups (At TR1, t value was -2.810, P < 0.05, at TR2-8, t values were respectively -6.026, -6.026, -5.375, -6.008, -5.406, -5.613 and -5.609, all P < 0.05). There was no statistic difference in MAP between the two groups (P > 0.05).

CONCLUSIONPCCO could not reflect the real CO in case of rapid blood volume change, which resulting in the misjudgment of patient's condition. In clinical practice, more frequent calibrations should be done to maintain the accuracy of PCCO in rapid blood volume change cases.

Animals ; Blood Volume ; Calibration ; Cardiac Output ; Disease Models, Animal ; Dogs ; Humans ; Monitoring, Physiologic ; Shock, Hemorrhagic ; diagnosis ; Thermodilution