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Genetic and biomarker factors also shape recovery patterns

These can make it harder to focus or do daily activities, especially at the start

Data extraction and risk of bias assessment Two researchers extracted data including the characteristics of the study population (number of patients per group, age, sex, diabetic status, liver disease status [NAFLD or NASH], and BMI per group), intervention(s) (TZD or GLP-1RA, treatment duration), control(s), outcome(s), and study results for each outcome according to a predefined Excel format

Adherence engines powered by predictive analytics can detect when a patient is likely to drop off and intervene before it happens

Cardiovascular risk factors: Managing weight helps reduce strain on the heart and lowers future disease risk

Effects of 12 weeks of endurance training on bone mineral content and bone mineral density in obese, overweight and normal weight adolescent girls