Polysomnography reveals unexpectedly high rates of organic sleep disorders in patients with prediagnosed primary insomnia

Study Objectives: To determine the prevalence of occult sleep disordered breathing (SDB) and describe the relationship between classic SDB symptoms (e.g., loud snoring) and occult SDB in older veterans with insomnia. Methods: We analyzed baseline survey and in-home sleep study data for 435 veterans (mean age = 72.0 years [SD 8.0]) who had no known history of SDB, met International Classifi cation of Sleep Disorders 2 nd Edition criteria for insomnia, and were enrolled in a behavioral intervention trial for insomnia. Variables of interest included apnea-hypopnea index (AHI) ≥ 15, age, race/ethnicity, marital status, body mass index (BMI), insomnia subtype (i.e., onset, maintenance, or terminal), self-reported excessive daytime sleepiness, snoring, and witnessed breathing pause items from the Berlin Questionnaire. We computed the frequency of AHI ≥ 15 and assessed whether each classic SDB symptom was associated with an AHI ≥ 15 in 4 separate multivariate logistic regression models.Results: Prevalence of AHI ≥ 15 was 46.7%. Excessive daytime sleepiness (adjusted odds ratio 1.63, 95% CI 1.02, 2.60, p = 0.04), but not snoring loudness, snoring frequency, or witnessed breathing pauses was associated with occult SDB (AHI ≥ 15). Insomnia subtypes were not signifi cantly associated with occult SDB (p > 0.38). Conclusions: In our sample of older veterans with insomnia, nearly half had occult SDB, which was characterized by reported excessive daytime sleepiness, but not loud or frequent snoring or witnessed breathing pauses. Insomnia subtype was unrelated to the presence of occult SDB.

Section: S C I E N T I F I C I N V E S T I G a T I O N Smentioning

confidence: 90%

Prevalence and Symptoms of Occult Sleep Disordered Breathing among Older Veterans with Insomnia

Fung

Martin

Dzierzewski³

et al. 2013

“…Overall, our data suggest that polysomnography is useful to assess comorbid sleep disorders and OSA in particular in PD patients. 35 However, PSG cannot explain subjective symptoms of sleepiness and insomnia specific to PD. The MSLTs did not reflect subjective daytime sleepiness as measured by the ESS.…”

Section: Discussionmentioning

confidence: 99%

Insomnia and Sleepiness in Parkinson Disease: Associations with Symptoms and Comorbidities

Chung

Bohnen

Albin

et al. 2013

Study Objectives: Insomnia and daytime sleepiness are common complaints in Parkinson disease (PD), but the main causes remain unclear. We examined the potential impact of both motor and non-motor symptoms of PD on sleep problems. Methods: Patients with PD (n = 128) were assessed using the Insomnia Severity Index, Epworth Sleepiness Scale, Unifi ed Parkinson Disease Rating Scale, Beck Depression Inventory, Fatigue Severity Scale, Survey of Autonomic Symptoms, and the 39-item Parkinson Disease Questionnaire. A subset of subjects (n = 38, 30%) also completed nocturnal polysomnography and a multiple sleep latency test (MSLT) S C I E N T I F I C I N V E S T I G A T I O N SS leep-related disturbances, including insomnia and excessive daytime sleepiness, are some of the most common complaints of patients with Parkinson disease (PD). As many as 60% to 76% of PD patients experience insomnia.1,2 Nocturnal hypokinesia, nocturnal and early morning dystonia, and impaired bed mobility are thought to be common causes.2,3 In practice, attention often focuses on motor symptoms of PD, and these are probably considered fi rst as possible causes of sleep disturbance. Although non-motor symptoms, such as depressed mood, anxiety, pain, or frequent nocturia tend to receive less clinical consideration, such symptoms could have substantial impact on sleep. 4 In particular, depression is the most common psychiatric problem in PD, with an estimated prevalence of 17% to 50%, 5,6 depending on the rating scales or structured clinical diagnosis used to identify the problem. Several studies have examined the relationship between depressed mood and sleep disturbance in PD patients. 7 The relative contributions, however, of motor and non-motor features to sleep disturbance remains unclear, despite the important impact that sleep disturbance can have on quality of life in patients with PD. Furthermore, the potential value of objective sleep laboratory data, in understanding sleep-related complaints in PD, remains unclear. The main objective of this study was to examine associations of both motor and non-motor PD symptoms with reported sleep problems. We hypothesized that non-motor and motor symptoms of PD patients would each show independent association with subjective insomnia or daytime sleepiness. In a subset of patients, we also assessed the extent to which polysomnography and the multiple sleep latency test (MSLT) may help to understand sleep complaints in PD. BRIEF SUMMARYCurrent Knowledge/Study Rationale: Sleep disturbance and daytime somnolence are common complaints in patients with Parkinson disease (PD), but the main causes remain unclear. This study was done to explore associations between sleep-related complaints and potential contributors, including both motor and non-motor PD symptoms. Study Impact: Non-motor features of PD, such as mild depressive symptoms, fatigue, and autonomic symptoms, are associated with subjective insomnia, whereas fatigue and dopaminergic medication dose are associated with subjective daytime sleepiness. I...

“…65 Cronlein and colleagues found that occult OSA was most likely to be found on PSG in older and overweight individuals with insomnia, alluding to the possible necessity for PSG in these patients. 66 Men with insomnia who frequently reported dry mouths were likely to have occult sleep apnea even after been screened for possible OSA. 67 Our findings complement these studies by highlighting the risks of occult OSA in insomnia patients, and this might be particularly prominent in those with the MI symptom profile.…”

Section: "Mild Insomnia" Symptom Cluster Profilementioning

confidence: 99%

Characterization of Patients Who Present With Insomnia: Is There Room for a Symptom Cluster-Based Approach?

Crawford

Chirinos

Iurcotta

et al. 2017

Study Objectives: This study examined empirically derived symptom cluster profiles among patients who present with insomnia using clinical data and polysomnography. Methods: Latent profile analysis was used to identify symptom cluster profiles of 175 individuals (63% female) with insomnia disorder based on total scores on validated self-report instruments of daytime and nighttime symptoms (Insomnia Severity Index, Glasgow Sleep Effort Scale, Fatigue Severity Scale, Beliefs and Attitudes about Sleep, Epworth Sleepiness Scale, Pre-Sleep Arousal Scale), mean values from a 7-day sleep diary (sleep onset latency, wake after sleep onset, and sleep efficiency), and total sleep time derived from an in-laboratory PSG. Results:The best-fitting model had three symptom cluster profiles: "High Subjective Wakefulness" (HSW), "Mild Insomnia" (MI) and "Insomnia-Related Distress" (IRD). The HSW symptom cluster profile (26.3% of the sample) reported high wake after sleep onset, high sleep onset latency, and low sleep efficiency. Despite relatively comparable PSG-derived total sleep time, they reported greater levels of daytime sleepiness. The MI symptom cluster profile (45.1%) reported the least disturbance in the sleep diary and questionnaires and had the highest sleep efficiency. The IRD symptom cluster profile (28.6%) reported the highest mean scores on the insomnia-related distress measures (eg, sleep effort and arousal) and waking correlates (fatigue). Covariates associated with symptom cluster membership were older age for the HSW profile, greater obstructive sleep apnea severity for the MI profile, and, when adjusting for obstructive sleep apnea severity, being overweight/obese for the IRD profile. Conclusions:The heterogeneous nature of insomnia disorder is captured by this data-driven approach to identify symptom cluster profiles. The adaptation of a symptom cluster-based approach could guide tailored patient-centered management of patients presenting with insomnia, and enhance patient care. Keywords: insomnia disorder, latent profile analysis, symptom profile, symptom clusters Citation: Crawford MR, Chirinos DA, Iurcotta T, Edinger JD, Wyatt JK, Manber R, Ong JC. Characterization of patients who present with insomnia: is there room for a symptom cluster-based approach? J Clin Sleep Med. 2017;13(7):911-921. I NTRO DUCTI O NInsomnia is the experience of the difficulty falling asleep, difficulty staying asleep, or early morning awakenings. About one-third to one-half of adults complains of these symptoms. Frequently, other complaints, such as sleepiness, fatigue, and hyperarousal, will occur with nocturnal sleep disturbance. An insomnia disorder is defined in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) 2 as the combination of the nocturnal sleep disturbance with one of these waking complaints at least 3 nights a week for at least 3 months. Approximately 8% to 10% of the adult population meets these criteria. 3,4Insomnia disorder is a heterogeneous condition.5 This can pose a chall...