# The Effect of Sleep Disorder Diagnosis on Mortality in End-Stage Renal Disease Patients
## 4 Discussion  
There is a high prevalence of sleep disorders in patients with ESRD [8; 9; 22], and specific sleep disorders, such as OSA lead to progression of CKD and increased complications [14; 15]. The relationship between sleep disorders and mortality has not been studied in ESRD patients. This study was a retrospective analysis of the USRDS database to examine the relationship between the diagnosis of the disorders of hypersomnolence, insomnia, RLS, or OSA/CSA and mortality in ESRD patients while controlling for various demographic variabilities and overall health (as assessed by the CCI). This study highlights clinical characteristics of patients diagnosed with sleep disorders and ESRD. Our data show that amongst patients with ESRD, 0.5% were diagnosed with hypersomnolence, 6.9% were diagnosed with insomnia, 2.8% were diagnosed with RLS, and 12.6% were diagnosed with OSA/CSA. This is similar to the prevalence of these conditions in the general population except for OSA/CSA, which exhibited an increased prevalence in patients with ESRD compared to what has been found in studies of the general population [23]. This contrasts with several studies that showed patients with CKD have higher rates of all sleep disorders than the general population [8; 24; 25]. Unfortunately, despite their high prevalence, many sleep disorders often go undiagnosed, and less than 20% of patients with insomnia are properly diagnosed and treated [23]. This number is even smaller for hypersomnolence and RLS [23]. Studies have also shown a high prevalence of sleep disorders amongst minorities [26; 27; 28]. To investigate this disparity, a  
Figure 2: Forest plot showing the relative risk of mortality associated with various demographic parameters, CCI, and each sleep disorder diagnosis. Error bars indicate the 95% confidence interval. future prospective study could objectively measure sleep in this population to determine whether there are disparities in diagnosing sleep disorders in minority ESRD patients. Our study suggests that certain sleep disorders may be underdiagnosed in this population, especially amongst minorities. Previous studies also showed an association between sleep disorders and increased overall mortality in patients with CKD [29; 30]. However, there have been other studies that produced conflicting results, especially in patients with ESRD on hemodialysis. [PERSON] et al. [31], found that despite the presence of a strong association between sleep apnea and mortality in the general population, a similar association could not be demonstrated in ESRD patients with a high prevalence of this condition. Their study found that a high probability of sleep apnea at baseline did not predict total or cardiovascular mortality [31]. These results are of interest to our study since despite the multifactorial mechanisms that could produce an association between sleep disorders and increased mortality in patients with ESRD, our final CPH model showed that a diagnosis of hyper-somnolence, insomnia, RLS, or OSA/CSA was associated with a decreased risk of death after controlling for sex, age, race, ethnicity, access type, dialysis modality, and CCI. The odds ratios in these cases take into account the person years at risk. In Figure 1, patients with sleep disorders show improved survival early in their disease history, although both those with and those without a diagnosis of sleep disorders eventually die. Therefore, when results are corrected for the length of time that the patient has lived with a certain diagnosis, sleep disorders become protective. Catheter access type, increasing age, graft access type, and hemodialysis were associated with increased risk of mortality. Black race, other race, and Hispanic ethnicity, were correlated with decreased risk of mortality, and female sex and increasing CCI with a slightly decreased risk, in the final model. With large datasets, such as the USRDS, occasionally there are values, particularly for continuous variables, that are statistically significant but not biologically relevant.