Results of high frequency drugs and drug-phrase matrix
Through the extraction of drug names from the bibliographic information, 83 PCA related drugs were obtained, including 19 drugs with frequency of 1. According to Pao’s effective word frequency formula, 39 high-frequency drugs with a lowest frequency 7 were determined, and the cumulative word frequency contribution rate was 93.10%. Morphine, Dexmedetomidine and Fentanyl were the top three drugs (Table 1).
The drug-phrase matrix of 39 high-frequency drugs was constructed by Bicomb software, and 593 articles with co-occurrence relationship were obtained. Part of the matrix was shown in Table 2.
Results of system clustering
The clustering process was to integrate 39 drugs from small clusters to larger ones according to the distance, and the similarity within the cluster decreases gradually. The drugs in the smallest cluster can often be combined with drugs directly. In addition, we can make valuable discoveries by analyzing the nature or type of different clusters of drugs. The results of clustering are shown in Figure 1. According to the distance at the red line, the 39 drugs were generally divided into two big clusters.
The first cluster contains 26 drugs, with Propofol appearing 78 times at the highest frequency and Celecoxib appearing 7 times at the lowest frequency. Ketorolactic is the most widely used combination drug, which was related to eight drugs, and Litonavir, Methadone and Pregabalin are the least, which were related with only one drug.
The second cluster contains 13 drugs, with Morphine appearing 759 times at the highest frequency and Meperidine appearing 57 times at the lowest frequency. Morphine was the most abundant combination drug, which is related with 26 drugs, and Meperidine was related with 6 drugs at least.
Results of frequent itemsets and association rules
Apriori algorithm involves three important parameters, Support, Confidence and Lift. Support measures the universality of the application of association rules, and the higher the degree of Support, the more common the rule is adopted; Confidence reflects the accuracy of association rules, and the higher the degree of Confidence, the greater the opportunity of the latter item under the condition of the existence of the preceding item of the rule; Lift reflects the practicability of the association rules, only the Lift with a degree greater than 1 are useful. In order to obtain a certain number of association analysis results, we set the Support to 0.05 and the Confidence to 0.7.
After operation, we get 22 frequent itemsets. Among them, there are 12 frequent 1-item sets and 10 frequent 2-item sets. As shown in Figure 2, the larger the circle, the greater the Support. Each item points to the Support through a directed arrow, indicating that the relevant items constitute an itemset. In this case, the Support is 0.052–0.53. The maximum frequent 1-item set is {Morphine} with Support of 0.53; the maximum frequent 2-item set is {Morphine, Ropivacaine}, with support of 0.15.
In the analysis of association rules, we obtained six valuable association rules with Lift greater than 1. As shown in Figure 3, the larger the circle, the greater the Support, the darker the color of the circle, the greater the lift. Among them, {Ketamine} = > {Morphine} has the greatest Support, with the Support of 0.14; the greatest Lift is {Neostigmine} = > {Bupivacaine}, with the Lift of 5.12.