Diabetes and prediabetes prevail among obstructive sleep apnea (OSA) patients. OSA and short sleep both detrimentally affect glycemic control regardless of obesity. With 1 in 10 adults having diabetes, 1 in 10 with prediabetes, and an estimated 600,000 affected by OSA in Sweden, attaining glycemic control is crucial. Though continuous positive airway pressure (CPAP) is the most effective treatment for OSA, its application lacks personalization, ignoring factors like comorbidities and sleep duration. Key unanswered questions regarding CPAP's impact on glycemic control include: 1) Does high CPAP adherence optimize glycemic control? 2) Should short sleep be addressed alongside OSA treatment for glycemic control? 3) Does long-term diabetes hinder CPAP's glycemic control efficacy? The purpose of this project is to enable precision health in CPAP treatment and producing a personalized treatment model for achieving glycemic control in patients with OSA, treated with CPAP. Taking advantage of a large unique patient cohort (600 patients followed over 18 months) with extensive and objective measures on CPAP adherence, OSA reduction, sleep duration, as well as information on comorbidities, anthropometric, lifestyle data, and a wide range of biomarkers related to glycemic control. This comprehensive approach and in-depth analysis will address these questions and generate a personalized treatment strategy for glycemic control in CPAP-treated OSA patients.