ABSTRACT
Objective To summarize regularities in acupoint prescriptions for acupuncture treatment of stroke disorders by using data mining techniques to analyze 150 ancient acupuncture books from the Han dynasty to the end of Qing dynasty. Method A standard database and a ancient book database were established by a manual entry and proofreading method. The sentences containing stroke disorders, acupoints, meridians and needling moxibustion method in the ancient books were selected according to the key words in the standard database using a variety of data mining techniques and a regular relation to establish corresponding disease, acupoint, needling moxibustion method and meridian databases. They were classified into two types: prescriptions for stroke disorders and acupoint indications containing stroke disorders. The results from selection were reviewed manually and standardized. A multilevel analysis of regularities in acupuncture prescriptions for stroke disorders in the ancient books was performed by statistical analysis and apriori algorithm on association rules with support degree and confidence level. Result There were a total of 536 records on acupuncture point prescription for stroke disorders. Single acupoint prescriptions accounted for 34.89% of the total number of prescriptions. The single acupoint that was used most frequently was Baihui(GV20). Thedouble acupoints that were combined most frequently were Quchi(LI11) and Baihui. In three acupoint combination, Quchi and Fengshi(GB31) were separately combined most frequently with Baihui, Jianyu(LI15) and Xuanzhong(GB39). The three meridians that were used most frequently were the Du Meridian, the Large Intestine Meridian of Hand-Yangming and the Gallbladder Meridian of Foot-Shaoyang. The two meridians that were combined most frequently were the Gallbladder Meridian of Foot-Shaoyang and the Stomach Meridian of Foot-Yangming. Crossing points and Five-Shu points were selected most frequently in specific points. He-Sea points were used most frequently in Five-Shu points. Conclusion The prescriptions for stroke disorders in ancient acupuncture books focus on selecting the confluence of all yang meridians and yang meridian points. Specific points are the important composition of the prescriptions. Crossing points and He-Sea points are mainly used in specific points.
ABSTRACT
<p><b>OBJECTIVE</b>To assess the predictive value of heart rate turbulence (HRT) in patients with acute myocardial infarction.</p><p><b>METHODS</b>One hundred and twenty-five patients with acute myocardial infarction were enrolled in this study. During the period from 6 to 21 days after onset of acute myocardial infarction, they were undergone 24-hour Holter recordings to collect the mean RR interval and heart rate variability (HRV) SDNN. The Holter files were processed with software of "HRT! View V0.60-1" to obtain the value of Turbulence Onset (TO) and Turbulence Slope (TS) and the value of "heart rate variability (HRV) SDNN". LVEF and EDD were measured by Ultrasonic Cardiography. Endpoint of follow-up was cardiac death. According to the results, patients were divided into two groups (the "survivors" and the "nonsurvivors"). The predictive value for high-risk patients with acute myocardial infarction was assessed by variables between the two groups.</p><p><b>RESULTS</b>In the period of follow-up (mean 225.4 +/- 99.8 days), 14 patients died and 111 patients survived. In the univariate Cox regression analysis, "TS" was a strong univariate predictor of mortality (hazard ratio 11.46, P < 0.01); "TO" was a relatively weak predictor and the hazard ratio was 2.76 (P > 0.05). Combination of abnormal TO and abnormal TS was the strongest mortality predictor (hazard ratio 26.70, P < 0.01); in the multivariate Cox regression analysis, TS < or = 2.5 ms/RR and EDD > or = 5.6 cm were the independent predictors of mortality with hazard ratios 9.49 (P < 0.01) and 3.64 (P < 0.05), respectively.</p><p><b>CONCLUSIONS</b>The absence of the heart rate turbulence after ventricular premature beats is a very potent post-infarction risk predictor which is independent of and stronger than other known risk predictors.</p>