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doi:10.1097/00002820-199904000-00011
Notable strengths of this study include our use of propensity matching for causal inference on real-world data, being among the first to report serial (i.e., daily) measurements of cardiovascular measures and health behaviors among GLP-1 RA users, and our use of wearable technology that has been validated against gold-standard electrocardiogram and polysomnography measures with a low degree of bias and low precision of errors (10, 11)
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