[Correlation between cold pain of knee joint and subchondral bone marrow edema in patients with knee osteoarthritis].

OBJECTIVE: To investigate relationship between cold pain of knee joint and subchondral bone marrow edema (BME). METHODS: From May 2018 to August 2019, 92 patients with knee osteoarthritis (KOA) associated with cold pain of knee were admitted, all patients were underwent MRI examination. The patients were divided into observation group (47 patients with BME) and control group(45 patients without BME). In observation group, there were 6 males and 41 females aged from 36 to 87 years old with an average of (63.2±12.3) years old. In control group, there were 10 males and 35 females, aged from 48 to 84 years old with an average of (62.7±8.3) years old. All patientswere treated with drugs. The degree of joint degeneration was evaluated by Kellgren-Lawrence (K-L) grading. Degree of cold pain of knee was evaluated by knee cold pain score, and degree of BME was evaluated according to WORMS. The correlation between cold pain of knee and K-L grading and BME was analyzed. RESULTS: Score of cold pain in observation group (15.55±7.68) was higher than that of control group (9.42± 5.50), which had significant difference (t=4.383, P<0.001). There was no correlation between cold pain of knee and K-L grading(χ2=2.138, P=0.907). There was correlation between BME grading and degree of cold pain in observation group(χ2=19.709, P<0.001), and Spearman correlation coefficient was rs=0.509(P<0.001). CONCLUSION: The cold pain of KOA patients is not related to K-L grading, but corelate with BME grading. The Cold pain of knee was more pronounced in KOA patients with BME, and the severity of BME is often related to degree of cold pain. It seemed to be a tendency:the more serious BME, the heavier coldpain.

Application of TQSM polypharmacokinetics and its similarity approach to ascertain Q-marker by analyses of transitivity in vivo of five candidates in Buyanghuanwu injection.

BACKGROUND: It is well-known that the public still have been facing on a severe issue about the inconsistency of quality and therapeutic efficacy of traditional medicines. Recently, Professor Chang-Xiao Liu has created a new promising concept for identifying relevant quality-markers (Q-marker) from herbs, their formulas and manufacturing products. Therefore, building up a new approach is necessary for us to bridge over quality to efficacy of pharmaceutical products. STUDY DESIGN: In this paper, five candidate Q-markers, astragaloside IV, paeonflorin, amygdalin, tetramethylpyrazine, ferulic acid in Buyanghuanwu injection (BYHWI) had been designed to carry out in rat by using single and polypharmacokinetic models for total quanta to ascertain adequate Q-marker. METHODS: The Q-marker transitivity in vivo was studied with polypharmacokinetic model and its similarity approach, which were modeled with TQSM principle. The Q-marker was ascertained with transitive similarity and bioavailability in polypharmacokinetics. Their concentrations in plasma sample of white rat were determined by RP-HPLC. Data analyses were used by the DAS software for singles and myself-written-program with EXCEL for multiples. RESULTS: In BYHWI, five candidate Q-marker pharmacokinetic profiles were singly fixed to two compartmental models in rat using classical compartmental analysis, but there were tremendous differences among which the candidate parameters were fluctuated from nearly 3552 folds to equivalency. The theoretical value of TQSM polypharmacokinetic parameters such as AUCT, MRTT, VRTT, CLT, VT over the mixure of five drugs were 110.8 ±â€¯51.91 mg min ml-1, 176.0 ±â€¯36.5 min, 39,921 ±â€¯4311 min2, 0.3116 ±â€¯0.02347 ml min-1 kg-1, 54.83 ±â€¯7.683 ml kg-1 respectively. The TQSM polypharmacokinetic parameters in astragaloside Ⅳ ordered by AUCT, MRTT, VRTT, CLT, VT were 110.8 ±â€¯51.91 mg min ml-1, 176.0 ±â€¯36.5 min, 39,921 ±â€¯4311 min2, 0.3116 ±â€¯0.02347 ml min-1 kg-1, 54.83 ±â€¯7.683 ml kg-1, respectively, which were closed to the theoretical values. TQSM similarity versus astragaloside Ⅳ was 0.9661. CONCLUSION: The results represented that the optimum Q-marker in BYHWI is astragaloside Ⅳ, whose transitivity in vivo similarity was close to the behavior of polypharmacokinetics with maximum bioavailability to the total quanta. It is feasible for Q-marker in CMMs to screen on the comparison of single pharmacokinetic behavior and bioavailability to the total quanta.