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Effectiveness of eHealth for Medication Adherence in Renal Transplant Recipients: Systematic Review and Meta-Analysis

Effectiveness of eHealth for Medication Adherence in Renal Transplant Recipients: Systematic Review and Meta-Analysis

M-H: Mantel-Haenszel; IV: inverse variance. Of the 12 studies, 8 (67%) [11,34,36-38,40,42,43] reported medication adherence measured via electronic monitoring devices, with 3 (25%) [36,38,42] providing dichotomous data (I2=53%; P=.09), for which a random-effects model was applied. The e Health intervention demonstrated statistically significant improvements in adherence (RR=1.46, 95% CI 1.11-1.90; z score=2.75; P=.01; Figure 3 A) [36,38,42].

Lili Zhou, Ke Cheng, Linbin Chen, Xinyi Hou, Jingjing Wan

J Med Internet Res 2025;27:e73520

Machine Learning Clinical Decision Support for Interdisciplinary Multimodal Chronic Musculoskeletal Pain Treatment: Prospective Pilot Study of Patient Assessment and Prognostic Profile Validation

Machine Learning Clinical Decision Support for Interdisciplinary Multimodal Chronic Musculoskeletal Pain Treatment: Prospective Pilot Study of Patient Assessment and Prognostic Profile Validation

Profile accuracy: H=high, M=medium, L=low. AUC: area under the curve; M: mixed; N: negative; P: positive; TPR: true-positive rate; TNR: true-negative rate. The above summary (Figure 2) presents results for all pilot study patients to show performance and overall results. However, the individual prognostic patient profile as used in IMPT clinical assessment provides clearly presented summary results for each patient.

Fredrick Zmudzki, Rob J E M Smeets, Jan S Groenewegen, Erik van der Graaff

JMIR Rehabil Assist Technol 2025;12:e65890