0880 Relationships Between Multimorbidity and Disturbed Sleep Phenotypes in Chronic Spinal Cord Injury

Abstract Introduction Disturbed sleep is a modifiable risk factor for a variety of co-morbidities. Treatment of sleep disorders can provide a key target for improving cardiometabolic health and overall wellness. Despite evidence suggesting higher prevalence of disturbed sleep in Veterans with spinal cord injury (SCI) compared to the non-injured population, the intersectional effects of sleep-wake disruption remain undefined. The purpose of this study is to examine existing data from the spinal cord injury-pressure injury resource (SCI-PIR) database to assess prevalence and identify relationships among sleep disorders and cardiometabolic risk after spinal cord injury. Methods This retrospective longitudinal national database cohort study utilized the VA’s SCI-PIR database containing comprehensive clinical data for 29,000 individual Veterans with SCI with over 120,000 encounters. SCI-PIR data includes clinical characteristics of Veterans with SCI, demographics, and comorbidities identified as being relevant to sleep and cardiometabolic risk. We queried the database for ICD9 diagnosis codes related to cardiovascular, metabolic, psychologic, and sleep conditions to identify sleep disorder subgroups defined by clustering of cardiometabolic risk factors and sleep diagnoses within SCI individuals diagnosed with sleep disorders. Results In the sample of 18,894 Veterans, sleep disturbances were diagnosed in only 16.25% of the sample. Sleep apnea (6.7%) and insomnia (4.3%) were the most common sleep diagnosis. Correspondence analysis of sleep, cardiac disorders, and other co-morbidities demonstrated two clusters. The first cluster showed a robust link between sleep apnea, hypersomnia, heart failure and arrhythmias, and secondary associations with coronary artery disease, chronic kidney disease, obesity, diabetes, and hyperlipidemia. The second cluster showed a strong relationship between insomnia, anxiety, and post-traumatic stress disorder. Conclusion Sleep disturbances are common in Veterans with SCI, but underdiagnosed. Our findings support the link between medical complications and consequences of disturbed sleep and cardiometabolic risk. This will enable development of SCI validated sleep instruments and clinical decision tools that identify those at highest risk for sleep disorders lead to the development of targeted interventions and treatments to advance precision health for Veterans with SCI. Support (if any) NIH grant R25 HL105400 and VHA Office of Research, Supplement to Promote Diversity