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ObjectiveTo construct a quantitative differentiation model of traditional Chinese medicine （TCM） syndromes by taking primary osteoporosis （POP） with kidney yang deficiency syndrome as an example， and to provide methodological reference for the standardization of syndrome differentiation. MethodsHigh-frequency clinical features of POP were screened by descriptive statistical analysis， and strong association features of POP were obtained by association rule algorithm. On this basis， a latent structure （latent tree） model was established through latent structure analysis， and the implicit and explicit variables （features） related to POP with kidney yang deficiency syndrome were comprehensively clustered， and the clustering results were interpreted by the indexes of mutual information and cumulative information coverage， to explore the primary and secondary symptoms， and to deduce the categories of POP with kidney yang deficiency syndrome based on the probability of the features appearing in the various latent categories. Based on the categories， the clinical feature scores and identification thresholds were calculated， and the syndrome differentiation model of POP with kidney yang deficiency was initially constructed by combining the comprehensive judgment rules. Finally， the results of TCM professionals' judgment were used as the gold standard to further evaluate the effectiveness of the model in assisting the syndrome differentiation. ResultsThe 32 features strongly associated with POP were obtained， and the Bayes information critedon score of the further constructed latent tree model was -15291.93. Based on the mutual information and the cumulative information coverage， the main symptoms of POP with kidney yang deficiency syndrome were bone weakness， fatigue， pale tongue， clear urine， frequent nocturnal urination， cold limbs， thin pulse， white coating， and secondary symptoms were weakness， loss of libido， loose stool， frequent urination， lumbar and knee weakness， and fear of cold. From the probability of the occurrence of each clinical feature in different latent categories of POP with kidney yang deficiency syndrome， the state was introduced as S0 category （none/mild kidney yang syndrome）/ S1 category （moderate kidney yang syndrome）/ S2 category （severe kidney yang syndrome）. Optimizing the preliminary rules of state identification and refining the state of S1 category， the results showed that among 970 patients with POP， there were 520 patients having no/mild kidney yang deficiency syndrome， 224 patients with moderate to mild kidney yang deficiency syndrome， 81 patients with moderate to severe kidney yang deficiency syndrome， and 145 patients with severe kidney yang deficiency syndrome. During the evaluation and validation process， the correct rate of the model assessment index was 0.8835， while the sensitivity was 0.7181， and the specificity was 0.9437. ConclusionCombined with the latent structure analysis of the association rule， the syndrome differentiation model for POP with kidney yang deficiency could be constructed， and the model shows a good quantitative identification effect， which can provide methodological supports for clinicians to improve the efficiency and accuracy of TCM diagnosis.
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ObjectiveTo investigate the identification of kidney Yang deficiency syndrome of patients with osteoporosis（OP）， and to form the clinical syndrome identification rules of traditional Chinese medicine（TCM）. MethodBasic information， etiology， clinical symptoms and other characteristics of 982 OP patients were included， and statistical tests were used to screen the variables associated with kidney Yang deficiency syndrome. Taking the decision tree as the base model， bootstrap aggregation algorithm（Bagging algorithm） was utilized to establish the classification model of kidney Yang deficiency syndrome in OP， generating numerous rules and removing redundancy. Combining least absolute shrinkage and selection operator（LASSO） regression to screen key rules and integrate them to construct an identification model， achieving the identification of kidney Yang deficiency syndrome in OP patients. ResultEighteen key identification rules were screened out， and of these， where 11 rules with regression coefficients>0 correlated positively with the kidney Yang deficiency syndrome， the rule with the highest coefficient was chilliness（present）&feverish sensation over the palm and sole（absent）. The other 7 rules with regression coefficients<0 correlated negatively with the syndrome， the rule with the lowest coefficient was reddish tongue（present）&diarrhea（absent）&deficiency of endowment（absent）. According to the regression coefficients of each key rule， variables with importance>0.2 were ranked as chilliness， reddish tongue， feverish sensation over the palm and sole， cold limbs， clear urine， diarrhea， deficiency of endowment， prolonged illness. The results of the partial dependence analysis of the identification model showed that compared to OP patients without chilliness， those with chilliness（present） had a 0.266 8 higher probability of being identified as having kidney Yang deficiency syndrome， indicating that this variable had the highest impact on identification of the syndrome. Similarly， compared to OP patients without reddish tongue， those with reddish tongue had a 0.141 9 lower probability of being identified as having kidney Yang deficiency syndrome， indicating that this variable had the highest impact on identifying non-kidney Yang deficiency syndrome. The accuracy， sensitivity， specificity and area under receiver operating characteristic curve（AUC） of the established kidney Yang deficiency syndrome identification model in the test set were 0.865 9， 0.853 7， 0.872 0 and 0.931 5， respectively. ConclusionA precise identification model of OP kidney Yang deficiency syndrome is conducted basing on the rule ensemble method of Bagging combining LASSO regression， and the screened key rules can explain the identification process of kidney Yang deficiency syndrome. In this research， according to the regression coefficients of rules， the importance and partial dependence of variables， combined with the thinking of TCM， the influence of patient characteristics on the identification of syndromes is described， so as to reveal the primary and secondary syndromes of identification and assist the clinical identification of kidney Yang deficiency syndrome.
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Objective To investigate hemorrhagic transformation (HT) and outcomes in acute ischemic stroke.Methods The demographics,vascular risk factors,imaging and other clinical data in patients with acute ischemic acute were collected retrospectively and compared.Using the susceptibility weighted imaging (SWI) to diagnose HT,and the patients were divided into either a HT group or a non-HT group.The modified Rankin scale was used to evaluate the clinical outcomes.Multivariate logistic regression analysis was used to determine the independent risk factors for HT and poor outcome in HT patients.Results A total of 96 patients with acute ischemic stroke were enrolled and 34 of them had HT (35.4％).The age (66.21 ± 7.04 years vs.61.21 ±13.42 years; t =2.020,P=0.046) and infarct volume (3.88 ±2.20 cm3 vs.1.96 ± 1.37 cm3; t =5.67,P=0.001) in the HT group were significantly older or larger than those in the non-HT group.The proportions of hypertension (58.8％ vs.30.6％;x2 =7.228,P=0.007),diabetes (29.4％ vs.6.5％;x2 =9.293,P=0.002),atrial fibrillation (35.3％ vs.3.2％;x2=18.128,P=0.000),and cardiogenic cerebral embolism (35.3％ vs.3.2％ ; P =0.000) were significantly higher than those in the non-HT group,while the proportion of small arterial occlusive stroke was significantly lower than that in the non-HT group (38.2％ vs.62.9％ ;P =0.032).Multivariate logistic regression analysis showed that age (odds ratio [OR] 1.168,95％ confidence interval [CI] 1.059-3.412; P =0.021),infarct volume (OR 3.461,95 ％ CI 1.317-6.270; P =0.044) and atrial fibrillation (OR 1.284,95％ CI 1.117-2.903; P =0.015) were the independent risk factors for HT.In the HT patients,age (69.46 ±7.17 years vs.64.19 ±6.31 years; t =2.248,P =0.032) in the poor outcome group was significantly older than that in the good outcome group.The proportions of hypertension (84.6％ vs.42.9％ ;x2 =781,P =0.016),diabetes (50.0％ vs.14.3％ ;x2 =6.053,P =0.014),cardiogenic cerebral embolism (61.5％ vs.19.0％ ; P =0.025) and hematoma HT (76.9％ vs.19.0％ ;x2 =11.104,P =0.001) were significantly higher than those in the good outcome group.Multivariate logistic regression analysis showed that the diabetes (OR 2.151,95％ CI 1.179-3.218; P =0.023),atrial fibrillation (OR 4.136,95％ CI1.010 to 8.413; P =0.046) and hernatoma HT (OR 2.134,95％ CI 1.219-4.452; P =0.039) were the independent risk factors for the poor outcomes of HT patients at 3 months after symptom onset.Conelusions The incidence of HT in patients with acute ischemic stroke was 35.4％.Age,infarct volume and atrial fibrillation were the independent risk factors for HT,and diabetes,atrial fibrillation and hematoma HT were the independent risk factors for the poor outcomes in HT patients at 3 months after symptom onset.
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Aim To explore the modulaory effect of tetramethylpyrazine(TMP) on the responses mediated by P2X receptors.Methods Whole-cell patch-clamp technique was used to study the effects of TMP on P2X receptor agonists-activated currents in freshly isolated rat dorsal root ganglion(DRG) neurons.Results Extracellular application of ATP of 1 to 1000 ?mol?L~(-1) activated currents in DRG neurons(n=102).The ATP-activated currents showed rapid desensitization or slow desensitization.Preapplication of TMP(0.1～10 mmol?L~(-1))markedly inhibited ATP(100 ?mol?L~(1))-activated currents in the majority of the neurons examined(89.2%,91/102).TMP(1 mmol?L~(-1)) reduced ?,?-meATP(10 ?mol?L~(-1))-activated currents.TMP(1 mmol? L~(-1)) shifted the concentration-response curve of I_(ATP) downward markedly.TMP(1 mmol?L~(-1)) did not alter the reversal potential(0 mV) of ATP-activated currents.TMP(1 mmol?L~(-1)) significantly inhibited ATP(100 ?mol?L~(-1))-activated currents potentiated by PGE_2(100 ?mol?L~(-1))or SP(0.1 ?mol?L~(-1)).Intracellular application of 10 ?mol?L~(-1) H89(which is an inhibitor of PKA) reduced the inhibitory effect of TMP on ATP(100 ?mol?L~(-1))-activated currents.Conclusion The mechanism of TMP action may be the allosteric regulation via acting on PKA system and the large extracellular region of ATP receptor-ion channel complex(P2X receptors) to affect P2X receptor agonists-activated currents in rat DRG neurons.