A Commentary on Acupoints for Headache with Blood Stasis Syndrome: A Literature Study Based on Data Mining Technology [Letter]

Dear editor

The research by Shi et al titled “Acupoints for Headache with Blood Stasis Syndrome: A Data Mining-Based Literature Review”¹ has been an engaging read. Their innovative application of data mining techniques to analyze acupoint selection for blood stasis-type headache marks a notable methodological progress in Traditional Chinese Medicine (TCM) research. The comprehensive dataset assembly and preliminary statistical analysis indeed lay a valuable groundwork for subsequent clinical and mechanistic explorations. Nevertheless, several adjustments could be made to enhance the study’s scientific precision and interpretability.

First, a discrepancy in numerical reporting is observed in the “Utilization of Acupuncture Points” section. While the text states “7 acupoints with frequency >40” and “16 acupoints with frequency >10”, Figure 2 and Table 2 respectively list only 6 and 15 acupoints in these categories. Such inconsistencies may confuse readers when interpreting the prioritization of acupoints based on their usage frequency.

Second, regarding the classification of acupoints in the “Correlation Between Meridians and Acupuncture Points” section, the article divides acupoints into meridian acupoints and extraordinary acupoints. However, this classification framework omits Ashi points, which are explicitly recognized as a distinct category in authoritative TCM texts such as Meridian and Collaterals, Acupoints.² Given their clinical relevance in pain management, clarifying the exclusion of Ashi points from the analysis would help avoid potential misunderstandings about the scope of the study.

Third, Table 4 exhibits inconsistent rounding practices. The reported value of 40.2% for head and neck acupoints requires adjustment. Based on the formula 31/(31 + 21 + 12 + 5 + 8) = 40.26%, the rounded result should align with the table’s convention, preferably presented as 40.3% to maintain consistency with other numerical values.

Lastly, an error in proportional calculation occurs in the meridian-acupoint correlation analysis within the same section. The paper states 17.2% (97 out of 564) for Yin meridian acupoints and 82.8% (467 out of 564) for Yang meridian acupoints. However, recalculating from the data in Table 3, the total number of acupoints is actually 675. This yields a corrected proportion of 24.1% for Yin meridians (summing SP 56, HT 10, LU 10, PC 6, KI 4, LR 45, CV 17, totaling 148) and 75.9% for Yang meridians (summing GB 171, GV 76, ST 55, TE 53, LI 53, BL 49, SI 10, totaling 467). This miscalculation may affect the accurate interpretation of meridians’ roles in treating blood stasis-type headaches.

It is hoped that these proposed refinements will strengthen the article’s accuracy and facilitate broader acceptance of data-driven approaches in TCM research. Thank you for considering these comments.