Dorrie Rizzo

A diagnostic symptom profile for sleep disorder in primary care patients

OBJECTIVE The aim of the present study was (1) to evaluate the extent and nature of sleep disorder-related symptoms in the older primary care patient population and (2) to differentiate a pattern of self-reported symptoms that identify patients who should be referred to the sleep clinic for further evaluation. METHOD One hundred ninety-six older adults recruited from family practice centers were administered a brief symptom survey measure. All were invited to participate in an extensive self-report evaluation, consultation with a sleep medicine specialist, and an overnight polysomnographic study. RESULTS A substantial number of older primary care patients report symptoms related directly or indirectly to physiological sleep disorder. Over 30% of total reported some insomnia, 40% daytime sleepiness, and 10% apnea. Those participants who agreed to pursue further aspects of the study protocol endorsed a higher number and greater severity of primary sleep disorder symptoms than those who declined to continue beyond the first phases. Participants who chose to pursue polysomnography (13% of total) had a very high rate (88.5) of diagnosed sleep disorder. CONCLUSION This study suggests that an older patient, male or female, who both endorses medically unexplained daytime sleepiness, fatigue, or other sleep disorder related symptoms and agrees to further evaluation, including overnight polysomnography, is at substantial risk for physiologically based sleep disorder. In the future, a brief, validated measure, such as the Sleep Symptom Checklist used in this study, would be an important part of the diagnostic process.

Impaired Sleep in Chronic Fatigue Syndrome How Is It Best Measured

The goal was to examine comparative efficacy of polysomnography, actigraphy, and self-report in evaluating the sleep/wake experience of individuals with chronic fatigue syndrome (CFS). Sleep parameters were evaluated by the three measurement modalities for the same night in 49 participants with CFS. Psychological and daytime functioning were measured by self-report. Results indicate that: (a) objectively measured nocturnal sleep time effectively approximated subjective experience although nocturnal wakefulness did not; (b) total sleep time and sleep efficiency differentiated individuals with and without insomnia complaints; (c) daytime sleepiness, fatigue, and non-refreshing sleep were not reflected by the objective sleep-related measures (polysomnography and actigraphy).

Sleep disorder symptoms are common and unspoken in Canadian general practice

OBJECTIVE Primary care patients were surveyed for what sleep disorder symptoms they discussed with their physicians. Their responses were compared with those of new Sleep clinic patients. The goal was to discover what symptom presentation leads to a successful referral to a sleep clinic. METHODS We recruited two samples: 191 older Primary care patients and 138 Sleep clinic patients. Participants completed the Sleep Symptom Checklist (SSC). This consists of 21 symptoms in four domains: insomnia, sleep disorder, daytime symptoms and psychological distress. All respondents indicated which symptoms had been discussed with their physician in the past year. Primary care subjects were designated as Decliners (completed SSC, refused further evaluation), Dropouts [completed some evaluation steps, but not polysomnography (PSG)] and Completers (completed PSG). RESULTS Primary care participants frequently had symptoms but relatively few had discussed them with their doctor. Sleep clinic participants discussed significantly more symptoms with their referring physician than did Primary care Dropouts or Decliners in all categories except psychological distress. Primary care Completers, 88.5% of whom were ultimately diagnosed with sleep apnoea/hypopnoea syndrome and/or periodic limb movement disorder, also discussed their sleep disorder symptoms less frequently than did Sleep clinic patients but tended to give more prominence to symptoms of insomnia and impaired daytime function. CONCLUSIONS The findings suggest that Primary care patients often have symptoms they do not discuss, even when a primary sleep disorder exists. The brief SSC checklist, developed in our laboratory, has potential to improve the referral rates of older primary care patients who have sleep disorder.

Sleep Apnea and Psychological Functioning in Chronic Fatigue Syndrome

Objectives were to explore: (1) whether sleep apnea/hypopnea syndrome (SAHS) should be considered a chronic fatigue syndrome (CFS) comorbidity, rather than a diagnostic exclusion criterion; and (2) to compare sleep/wake/ psychopathology in individuals with CFS, controls and another illness. Participants (CFS, SAHS, controls) completed questionnaires and were evaluated for SAHS; 68 percent were subsequently diagnosed with SAHS. CFS participants with and without SAHS did not differ. Both clinical groups were less well adjusted than controls. We conclude that SAHS should not be an exclusion criterion for CFS and that psychological problems in CFS seem a consequence of coping with illness.

Fatigue: The forgotten symptom of sleep apnea.

OBJECTIVE The present investigation was designed to explore the role and implications of both daytime sleepiness and fatigue in obstructive sleep apnea syndrome with respect to sleep, perceived health quality, and psychological functioning. METHODS Our participants consisted of two groups: 124 older community volunteers who completed a polysomnographic sleep study and were diagnosed with sleep apnea, and 19 healthy controls. All participants completed self-report measures of sleepiness, fatigue, sleep quality, health quality, and psychological functioning. RESULTS The apnea sample was divided according to clinically relevant cut-offs on sleepiness and fatigue. When those with mid-range scores were ruled out, the following groups remained: low sleepiness/low fatigue (LL, n=23), high sleepiness/high fatigue (HH, n=28), high sleepiness/low fatigue (HS, n=10) and low sleepiness/high fatigue (HF, n=13). The respiratory disturbance index did not differ significantly among these groups and only the two highly fatigued groups (HH and HF) experienced significantly lower average oxygen saturation than the control group. Analyses revealed that the HH group was significantly worse than the LL and control groups on most sleep, health quality, and psychological measures. On these same measures, the groups for whom fatigue was low (LL and HS), regardless of sleepiness, were similar to controls. CONCLUSION When patients with sleep apnea are classified into different sleepiness/fatigue categories, the results show that high fatigue is associated with more severe dysfunction than high sleepiness. The current debate on whether to treat apnea patients with low sleepiness needs to consider the impact of fatigue.

Refreshing Sleep and Sleep Continuity Determine Perceived Sleep Quality

Sleep quality is a construct often measured, employed as an outcome criterion for therapeutic success, but never defined. In two studies we examined appraised good and poor sleep quality in three groups: a control group, individuals with obstructive sleep apnea, and those with insomnia disorder. In Study 1 we used qualitative methodology to examine good and poor sleep quality in 121 individuals. In Study 2 we examined sleep quality in 171 individuals who had not participated in Study 1 and evaluated correlates and predictors of sleep quality. Across all six samples and both qualitative and quantitative methodologies, the daytime experience of feeling refreshed (nonrefreshed) in the morning and the nighttime experience of good (impaired) sleep continuity characterized perceived good and poor sleep. Our results clarify sleep quality as a construct and identify refreshing sleep and sleep continuity as potential clinical and research outcome measures.

Manifestations of Insomnia in Sleep Apnea: Implications for Screening and Treatment.

The aims of this study were to examine the presence, type, and severity of insomnia complaints in obstructive sleep apnea (OSA) patients and to assess the utility of the Sleep Symptom Checklist (SSC) for case identification in primary care. Participants were 88 OSA patients, 57 cognitive-behavioral therapy for insomnia (CBT-I) patients, and 14 healthy controls (Ctrl). Each completed a sleep questionnaire as well as the SSC, which includes insomnia, daytime functioning, psychological, and sleep disorder subscales. Results showed that OSA patients could be grouped according to 3 insomnia patterns: no insomnia (OSA), n = 21; insomnia (OSA-I), n = 30, with a subjective complaint and disrupted sleep; and noncomplaining poor sleepers (OSA-I-NC), n = 37. Comparisons among the OSA, CBT-I, and Ctrl groups demonstrate distinct profiles on the SSC subscales, indicating its potential utility for both case identification and treatment planning.

Sleep, chronic pain, and opioid risk for apnea

&NA; Pain is an unwelcome sleep partner. Pain tends to erode sleep quality and alter the sleep restorative process in vulnerable patients. It can contribute to next‐day sleepiness and fatigue, affecting cognitive function. Chronic pain and the use of opioid medications can also complicate the management of sleep disorders such as insomnia (difficulty falling and/or staying asleep) and sleep‐disordered breathing (sleep apnea). Sleep problems can be related to various types of pain, including sleep headache (hypnic headache, cluster headache, migraine) and morning headache (transient tension type secondary to sleep apnea or to sleep bruxism or tooth grinding) as well as periodic limb movements (leg and arm dysesthesia with pain). Pain and sleep management strategies should be personalized to reflect the patients history and ongoing complaints. Understanding the pain–sleep interaction requires assessments of: i) sleep quality, ii) potential contributions to fatigue, mood, and/or wake time functioning; iii) potential concomitant sleep‐disordered breathing (SDB); and more importantly; iv) opioid use, as central apnea may occur in at‐risk patients. Treatments include sleep hygiene advice, cognitive behavioral therapy, physical therapy, breathing devices (continuous positive airway pressure – CPAP, or oral appliance) and medications (sleep facilitators, e.g., zolpidem; or antidepressants, e.g., trazodone, duloxetine, or neuroleptics, e.g., pregabalin). In the presence of opioid‐exacerbated SDB, if the dose cannot be reduced and normal breathing restored, servo‐ventilation is a promising avenue that nevertheless requires close medical supervision. HighlightsPain can exacerbate complaints of poor sleep, and poor sleep quality alters pain perception and reduces coping skills.A comprehensive assessment of the role of mood in sleep disorders is essential to decipher the role of pain in sleep.A comprehensive assessment of poor sleep with insomnia and sleep apnea is essential for defining the role of pain in sleep.The effects of opioid use must be balanced with the risk of worsened SDB, especially for central sleep apnea and addiction.Pain care plans include sleep hygiene, cognitive behavioral therapy, medication, CPAP, oral devices and servo‐ventilation.

Determinants of policy decisions for non-commercial drivers with OSA: An integrative review

Excessive daytime sleepiness and reduced cognitive functioning secondary to obstructive sleep apnea (OSA) have been identified as an important health-related risk in commercial transportation with, possibly, an increased chance of road accidents. This has resulted in a variety of policies and restrictions imposed on commercial drivers. Here we review current knowledge to assess whether available data are sufficient to guide policy decisions concerning restrictions for non-commercial drivers. The review shows that there is a lack of uniformity among different consensus conferences and guidelines as to how to deal with drivers with OSA. Clear guidelines are limited and few are evidence based. It is unclear which aspect of OSA is the most valid measure of severity (e.g., apnea-hypopnea index vs oxygen desaturation index). Traditionally, sleepiness has been invoked as a major risk factor for impaired driving. Recently, there also has been an awareness that daytime fatigue, as distinct from sleepiness, has an impact on driving behavior. However, the precise effect of fatigue on driving, as well as its role in the formulation of guidelines, remain to be evaluated. We conclude that there are at least two major difficulties for the driving recommendation process: a) there is no accurate metric quantifying severity of driving risk associated with OSA, and b) there are substantial individual differences among those with OSA, both experiential and behavioral. We present implications from this review for future research and policy formulation.

CPAP Treatment Adherence in Women with Obstructive Sleep Apnea

Untreated obstructive sleep apnea (OSA) has numerous negative health-related consequences. Continuous positive airway pressure (CPAP) is generally considered the treatment of choice for OSA, but rates of nonadherence are high. It is believed that OSA is more prevalent among men; therefore understanding how OSA presents among women is limited and treatment adherence has received little research attention. For this study, 29 women were recruited from primary care offices. They completed a questionnaire battery and underwent a night of nocturnal polysomnography (PSG) followed by a visit with a sleep specialist. Women diagnosed with OSA were prescribed CPAP; 2 years later CPAP adherence was evaluated. Results show that approximately half the sample was adherent. There were no significant differences between adherent and nonadherent women on OSA severity; however CPAP adherent women had worse nocturnal and daytime functioning scores at the time of diagnosis. Moreover, when the seven nocturnal and daytime variables were used as predictors in a discriminant analysis, they could predict 87% of adherent and 93% of the nonadherent women. The single most important predictor was nonrefreshing sleep. We discuss the implications of the findings for identifying women in primary care with potential OSA and offer suggestions for enhancing treatment adherence.