ABSTRACT
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.
ABSTRACT
Objective:To explore the predictive value of the recurrence risk estimator at 90-days(RRE-90) score combined with lipoprotein-associated phospholipase A2 (Lp-PLA2) and high sensitivity C-reactive protein(hs-CRP) in the recurrence risk of acute atherosclerotic cerebral infarction.Methods:Totally 400 patients with acute atherosclerotic cerebral infarction who were hospitalized for the first time in neurology department were followed up for 90 days.However, 8 cases were lost and 392 cases were included finally.According to recurrence or not, 64 cases were divided into recurrence group and 328 cases into non-recurrence group.The RRE-90 score was applied to all the participants and the levels of Lp-PLA2 was detected by enzyme-linked immunosorbent assay, the levels of hs-CRP was detected by immunoturbidimetry.The ROC curve was used to analyze the predictive value of RRE-90 score combined with Lp-PLA2 and hs-CRP for the recurrence risk of acute cerebral infarction.Results:Compared with the non-recurrence group(RRE-90: (3.07±1.01)score, Lp-PLA2: (103.53±8.11)μg/L, hs-CRP: (4.07±1.48)mg/L), the levels of (RRE-90 score: (4.11±0.78)score, Lp-PLA2: (121.52±13.95)μg/L, hs-CRP: (12.40±2.46) mg/L)in the recurrence group of cerebral infarction were significantly higher ( P<0.05, P<0.01). Compared with RRE-90 score (0.705), Lp-PLA2 (0.697), hs-CRP (0.622), RRE-90 score combined with Lp-PLA2 (0.752), RRE-90 score combined with hs-CRP (0.746), RRE-90 score combined with Lp-PLA2 and hs-CRP (0.782) had the largest area under the curve for predicting recurrence of cerebral infarction within 90 days, with statistical significance( P<0.05), sensitivity was 87.8%, specificity was 89.6%. Conclusion:RRE-90 score combined with Lp-PLA2 and hs-CRP detection can further improve the accuracy of predicting recurrence within 90 days in patients with cerebral atherosclerotic infarction, and the predictive value is high.