An Adapted Neural-Fuzzy Inference System Model Using Preprocessed Balance Data to Improve the Predictive Accuracy of Warfarin Maintenance Dosing in Patients After Heart Valve Replacement.

BACKGROUND: Tailoring warfarin use poses a challenge for physicians and pharmacists due to its narrow therapeutic window and substantial inter-individual variability. This study aimed to create an adapted neural-fuzzy inference system (ANFIS) model using preprocessed balance data to improve the predictive accuracy of warfarin maintenance dosing in Chinese patients undergoing heart valve replacement (HVR). METHODS: This retrospective study enrolled patients who underwent HVR between June 1, 2012, and June 1, 2016, from 35 centers in China. The primary outcomes were the mean difference between predicted warfarin dose by ANFIS models and actual dose and the models' predictive accuracy, including the ideal predicted percentage, the mean absolute error (MAE), and the mean squared error (MSE). The eligible cases were divided into training, internal validation, and external validation groups. We explored input variables by univariate analysis of a general linear model and created two ANFIS models using imbalanced and balanced training sets. We finally compared the primary outcomes between the imbalanced and balanced ANFIS models in both internal and external validation sets. Stratified analyses were conducted across warfarin doses (low, medium, and high doses). RESULTS: A total of 15,108 patients were included and grouped as follows: 12,086 in the imbalanced training set; 2820 in the balanced training set; 1511 in the internal validation set; and 1511 in the external validation set. Eight variables were explored as predictors related to warfarin maintenance doses, and imbalanced and balanced ANFIS models with multi-fuzzy rules were developed. The results showed a low mean difference between predicted and actual doses (< 0.3 mg/d for each model) and an accurate prediction property in both the imbalanced model (ideal prediction percentage, 74.39-78.16%; MAE, 0.37 mg/daily; MSE, 0.39 mg/daily) and the balanced model (ideal prediction percentage, 73.46-75.31%; MAE, 0.42 mg/daily; MSE, 0.43 mg/daily). Compared to the imbalanced model, the balanced model had a significantly higher prediction accuracy in the low-dose (14.46% vs. 3.01%; P < 0.001) and the high-dose warfarin groups (34.71% vs. 23.14%; P = 0.047). The results from the external validation cohort confirmed this finding. CONCLUSIONS: The ANFIS model can accurately predict the warfarin maintenance dose in patients after HVR. Through data preprocessing, the balanced model contributed to improved prediction ability in the low- and high-dose warfarin groups.

The Preventive Value of Acupoint Sensitization for Patients with Stable Angina Pectoris: A Randomized, Double-Blind, Positive-Controlled, Multicentre Trial.

BACKGROUND: Acupoint sensitization is considered an important factor in the efficacy of acupoint therapy. This study aimed to evaluate the efficacy of acupressure in the prevention of stable angina pectoris using acupoints with different pressure-pain sensitivities. METHODS: A total of 202 patients were enrolled and randomly assigned to a high-sensitivity group (HSG) (n = 109) in which patients received acupressure at the five acupoints with the highest sensitivity to pain and a low-sensitivity group (LSG) (n = 93) in which patients received acupressure at the five acupoints with the lowest sensitivity to pain. The duration of acupressure treatment was 4 weeks, and the patients were evaluated at baseline, week 4, and week 8. The primary outcome was a change in the frequency of angina attacks from baseline. The secondary outcomes included nitroglycerin consumption, the Canadian Cardiovascular Society classification, and the Seattle Angina Questionnaire score. Adverse events such as bleeding and subcutaneous haemorrhage were recorded in both groups. RESULTS: The effect of acupressure compared with baseline on the prevention of angina pectoris in HSG was better than that in LSG at week 4 (incidence rate ratio (IRR): 0.691 and 95% confidence interval (CI): [0.569, 0.839]) and week 8 (IRR: 0.692 and 95% CI: [0.569, 0.839]). No significant difference between groups was found in the frequency of nitroglycerin consumption at week 4 (odds ratio (OR) = 0.863 and 95% CI: [0.147, 5.077]) or week 8 (OR = 1.426 and 95% CI: [0.211, 9.661]). Two themes in the questionnaire showed significantly different changes from baseline between the two groups. Scores on the angina frequency (AF) subscale had changed more from the baseline in the HSG at week 8 than in the LSG (mean difference (MD) = 3.807 and 95% CI: [0.673, 6.942]). Scores on the treatment satisfaction (TS) subscale had also changed more in the HSG than in the LSG at week 4 (MD = 3.651 and 95% CI: [0.327, 7.327]) and week 8 (MD = 4.220 and 95% CI: [0.347, 7.346]). One patient in the LSG reported bruising at the acupoint. No unexpected safety problems arose. CONCLUSIONS: This study showed that acupressure at acupoints with high sensitivity to pain may effectively reduce the frequency of stable angina pectoris episodes. This trial is registered with NCT03975140.