Polysomnographic Measurement of Sleep Duration and Bodily Pain Perception in the Sleep Heart Health Study

Does poor sleep quality lead to increased low back pain the following day?

OBJECTIVES

This study explored the relationship between sleep quality and next-day pain intensity for people with low back pain and investigated whether there was any evidence that this relationship was causal.

METHODS

We conducted a secondary analysis of an observational study that investigated sleep quality in people with low back pain. People with low back pain were recruited from primary care and the community. Sleep quality was measured with subjective (self-report) and objective (polysomnography (PSG)) measures. PSG analysis classifies sleep into stages, of which slow-wave sleep (SWS) is thought to have a key role in maintaining or increasing pain intensity. We drew directed acyclic graphs to identify possible confounders of the relationship between both measures of sleep quality, and pain intensity. We constructed two linear regression models to explore the effect of subjective and objective sleep quality on next-day pain intensity before and after confounder adjustment.

RESULTS

Thirty-nine participants were included in the study. For participants with low back pain, self-reported better quality sleep β=-0.38 (95% CI -0.63 to -0.13), or spending a greater proportion of time in SWS β=-0.12 (95% CI -0.22 to -0.02) was associated with lower next day pain intensity. After confounder adjustment, the effect reduced and was no longer significant for either self-reported β=-0.18 (95% CI -0.46 to 0.10), or SWS β=-0.08 (95% CI -0.18 to 0.03).

CONCLUSIONS

Sleep quality, whether measured by self-report or proportion of time in SWS, was associated with next day pain intensity for people with low back pain. However, this relationship is likely to be confounded and therefore not likely to be causal.

Subjective Sleep Disruption and Mood Disorders are Associated with the Risk of Chronic Pain in Patients with Obstructive Sleep Apnea

OBJECTIVE

This study aimed to determine the prevalence of chronic pain and its risk factors in patients with obstructive sleep apnea (OSA).

METHODS

A total of 145 patients diagnosed with OSA were consecutively recruited from the Sleep Medicine Center in West China Hospital. All patients were divided into two groups including OSA with and without chronic pain. They were assessed the subjective sleep (Pittsburgh Sleep Quality Index, Insomnia Severity Index), objective sleep (polysomnography), mood symptoms (Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale), and pain characteristics (Short-Form McGill Pain Questionnaire). Demographic, clinical, subjective and objective sleep parameters were compared between OSA patients with and without chronic pain. Binary logistic regression models and linear regression models were used to examine the risk factors of chronic pain in OSA.

RESULTS

Fifty-five (37.9%) patients with OSA were diagnosed with chronic pain. There were more severe subjective sleep disruption and symptoms of anxiety and depression in patients with chronic pain compared to those without chronic pain. After controlling for potential confounders, poor subjective sleep quality and severe insomnia and mood disorders (all ps < 0.05), but not objective sleep fragmentation or nocturnal hypoxemia (all ps > 0.05) were associated with the increased risk of pain and pain intensity, respectively.

CONCLUSION

More than one-third of patients with OSA had chronic pain. Subjective sleep disruption and mood disorders are the risk factors of chronic pain in OSA. Our findings suggest that subjective sleep quality should be valued highly in the relationship between OSA and pain.

A classification algorithm to predict chronic pain using both regression and machine learning - A stepwise approach

This secondary data analysis study aimed to (1) investigate the use of two sense-based parameters (movement and sleep hours) as predictors of chronic pain when controlling for patient demographics and depression, and (2) identify a classification model with accuracy in predicting chronic pain. Data collected by Oregon Health & Science University between March 2018 and December 2019 under the Collaborative Aging Research Using Technology Initiative were analyzed in two stages. Data were collected by sensor technologies and questionnaires from older adults living independently or with a partner in the community. In Stage 1, regression models were employed to determine unique sensor-based behavioral predictors of pain. These sensor-based parameters were used to create a classification model to predict the weekly recalled pain intensity and interference level using a deep neural network model, a machine learning approach, in Stage 2. Daily step count was a unique predictor for both pain intensity (75% Accuracy, F1 = 0.58) and pain interference (82% Accuracy, F1 = 0.59). The developed classification model performed well in this dataset with acceptable accuracy scores. This study demonstrated that machine learning technique can be used to identify the relationship between patients' pain and the risk factors.

Association Between Sleep Quality and Pain Intensity in Mild Patients with COPD: A Community Study

Purpose

Poor sleep quality and pain were common and had been proved as an important influenced factor of quality of life for patients with COPD. The association of sleep quality with pain has been observed in other population but remains unclear in mild patients with COPD from a community setting.

Methods

A cross-sectional study was conducted to include eligible mild patients with COPD in Pudong New District of Shanghai. A structured questionnaire was used to collect general and clinical information for the patients. The Chinese version of Pittsburgh Sleep Quality Index (PSQI) and the short form of McGill Pain Questionnaire (SF-MPQ) was used to assess sleep quality and intensity of pain. Logistic regression was performed to test the association between sleeping quality and pain intensity.

Results

Two hundred and sixty-four patients with COPD, with an average age of 64 years (SD 5.78 years), were enrolled, and of 52% were women. Seventy-one (26.9%) participants reported at least one exacerbation during the past year. About 28.2% of the patients were classified as having poor sleep quality. Sleep quality was significantly associated with PRI score (adjusted odds ratio (ORad)=2.16, 95% CI: 1.16–4.00) and PPI rank (ORad=1.90, 95% CI: 1.08–3.34). People with daytime disturbance were more likely to have pain (ORad =2.03, 95% CI: 1.18–3.50).

Conclusion

Poor sleep quality was common in mild patients with COPD in community and was associated with higher pain intensity. Pain may involve an impairment of sleep quality.

Systematic decrease of slow-wave sleep after a guided imagery designed to deepen sleep in low hypnotizable subjects

Slow-wave sleep is one of the most important restorative components of sleep and central for our health and cognitive functioning. Although the amount of slow-wave sleep depends on sleep drive, age and other factors, also the pre-sleep mental state might influence sleep depth. We had shown that a pre-sleep hypnotic suggestion to sleep more deeply increased slow-wave sleep duration in hypnotizable subjects. In contrast, low-hypnotizable participants decreased sleep depth after this intervention. A possible reason might be an aversion to and active resistance against hypnosis. To overcome this potential opposition, we introduced the procedure as 'guided imagery'. We replaced the hypnotic induction by a breathing relaxation. Importantly, the suggestion 'to sleep more deeply' remained identical. We expected that these changes would make it easier for low-hypnotizable subjects to benefit from the suggestion. In contrast, young healthy low-hypnotizable participants did not show positive effects. Similar to our previous studies, they exhibited a reduced slow-wave sleep duration after the intervention. Additionally, the ratio between slow-wave activity and beta band power decreased. Subjective sleep quality remained unaffected. Our results indicate that suggestions to sleep more deeply result in decreased sleep depth in low-hypnotizable participants regardless of the mental technique (guided imagery versus hypnosis). Thus, the aversion against hypnosis per se cannot explain the detrimental effect of the intervention on slow-wave sleep in low-hypnotizable subjects. The results support the notion that our mental state before sleep can influence subsequent slow-wave sleep. However, the mechanisms of the contradictory decrease in low-hypnotizable subjects remain unknown.

Daytime and Nighttime Sleep Characteristics and Pain Among Adults With Stable Heart Failure

BACKGROUND

Pain and sleep disturbance are common among patients with heart failure (HF) and are associated with symptom burden, disability, and poor quality of life. Little is known about the associations between specific sleep characteristics and pain in people with HF.

OBJECTIVE

The aim of this study was to describe the relationships between nocturnal sleep characteristics, use of sleep medication, and daytime sleep characteristics and pain among people with HF.

METHODS

We conducted a cross-sectional study of stable participants with HF. We administered the SF36 Bodily Pain Scale, Pittsburgh Sleep Quality Index, and Sleep Habits Questionnaire and obtained 3 days of wrist actigraphy and 1 night of home unattended polysomnography. We conducted bivariate analyses and generalized linear models.

RESULTS

The sample included 173 participants (mean [SD] age, 60 [16.1] years; 65.3% [n = 113] male). Insomnia symptoms (P = .0010), sleep duration (P = .0010), poor sleep quality (P = .0153), use of sleep medications (P = .0170), napping (P = .0029), and daytime sleepiness (P = .0094) were associated with increased pain. Patients with the longest sleep duration, who also had insomnia, had more pain (P = .0004), fatigue (P = .0028), daytime sleepiness (P = .0136), and poorer sleep quality (P < .0001) and took more sleep medications (P = .0029) than did those without insomnia.

CONCLUSIONS

Pain is associated with self-reported poor sleep quality, napping, daytime sleepiness, and use of sleep medication. The relationship between pain and sleep characteristics differs based on the presence of insomnia and sleep duration. Studies are needed to evaluate the causal relationships between sleep and pain and test interventions for these cooccurring symptoms.

Might chronic opioid use impact sleep-disordered breathing and vice versa?

Orr JE, Wallace MS, Malhotra A. Might chronic opioid use impact sleep-disordered breathing and vice versa? J Clin Sleep Med . 2020;16(6):843–845.

Preoperative sleep quality affects postoperative pain and function after total joint arthroplasty: a prospective cohort study

Background

The relationship between preoperative sleep quality and postoperative clinical outcomes after total joint arthroplasty (TJA) is unclear. We performed a prospective cohort study to determine whether preoperative sleep quality was correlated with postoperative outcomes after TJA.

Methods

In this prospective cohort study, 994 patients underwent TJA. Preoperative sleep measures included scores on the Pittsburgh Sleep Quality Index (PSQI), the Epworth Sleepiness Scale (ESS), and a ten-point sleep quality scale. The primary study outcome measured was the visual analog scale (VAS) pain score to 12 weeks postoperation. The consumption of analgesic rescue drugs (oxycodone and parecoxib) and postoperative length of stay (LOS) were recorded. We also measured functional parameters, including range of motion (ROM), Knee Society Score (KSS), and Harris hip score (HHS).

Results

The mean age for total knee and hip arthroplasties was 64.28 and 54.85 years, respectively. The PSQI scores were significantly correlated with nocturnal and active pain scores and ROM and functional scores from postoperative day 1 (POD1) to POD3. In addition, significant correlation was noted between the correlation between the active pain scores and ESS scores in the TKA group at postoperative 3 months. The consumption of analgesics after joint arthroplasty was significantly correlated with the PSQI scores. Moreover, significant correlations were noted between the sleep parameters and postoperative length of hospital stay (LOS).

Conclusion

Preoperative sleep parameters were correlated with clinical outcomes (i.e., pain, ROM, function, and LOS) after TJA. Clinicians should assess the sleep quality and improve it before TJA.

Chronic exposure to insufficient sleep alters processes of pain habituation and sensitization

Chronic pain conditions are highly comorbid with insufficient sleep. While the mechanistic relationships between the 2 are not understood, chronic insufficient sleep may be 1 pathway through which central pain-modulatory circuits deteriorate, thereby contributing to chronic pain vulnerability over time. To test this hypothesis, an in-laboratory model of 3 weeks of restricted sleep with limited recovery (5 nights of 4-hour sleep per night followed by 2 nights of 8-hour sleep per night) was compared with 3 weeks of 8-hour sleep per night (control protocol). Seventeen healthy adults participated, with 14 completing both 3-week protocols. Measures of spontaneous pain, heat-pain thresholds, cold-pain tolerance (measuring habituation to cold over several weeks), and temporal summation of pain (examining the slope of pain ratings during cold water immersion) were assessed at multiple points during each protocol. Compared with the control protocol, participants in the sleep-restriction protocol experienced mild increases in spontaneous pain (P < 0.05). Heat-pain thresholds decreased after the first week of sleep restriction (P < 0.05) but normalized with longer exposure to sleep restriction. By contrast, chronic exposure to restricted sleep was associated with decreased habituation to, and increased temporal summation in response to cold pain (both P < 0.05), although only in the past 2 weeks of the sleep-restriction protocol. These changes may reflect abnormalities in central pain-modulatory processes. Limited recovery sleep did not completely resolve these alterations in pain-modulatory processes, indicating that more extensive recovery sleep is required. Results suggest that exposure to chronic insufficient sleep may increase vulnerability to chronic pain by altering processes of pain habituation and sensitization.

Sleep Patterns and Obesity: Hispanic Community Health Study/Study of Latinos Sueño Ancillar Study

BACKGROUND

The relationship of poor sleep patterns to the increased risk of obesity has been reported, but the results are variable. This study evaluated the association between objectively measured sleep patterns and obesity in a representative adult population of Hispanic/Latino subjects living in the United States.

METHODS

This cross-sectional study was an analysis of a multicenter, community-based cohort of 2,156 participants aged 18 to 64 years from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Recruitment was conducted in San Diego, California; Chicago, Illinois; Bronx, New York; and Miami, Florida. Models were controlled for age, sex, ethnic background, site, income, education, and apnea-hypopnea index. Seven days of wrist actigraphy data were collected. Obesity was defined as BMI ≥ 30 kg/m², and abdominal obesity was defined as waist circumference ≥ 88 cm in women and ≥ 102 cm in men. Napping was defined as more than one 15-min nap per week.

RESULTS

An inverse linear relationship was found between sleep duration and prevalence of obesity (P linear trend ≤ 0.01). A reduction of 1 h sleep increased obesity prevalence by 4.1% (95% CI, 1.6-6.6; P = .002) and abdominal obesity prevalence by 3.6% (95% CI, 1.1-6.1; P = .007). Daytime napping increased obesity prevalence by 10.4% (95% CI, 3.5-17.3; P = .004) and abdominal obesity prevalence by 7.1% (95% CI, 1.0-13.2; P = .02).

CONCLUSIONS

In a population of young to older adult Hispanic/Latino subjects, we found an inverse linear association between sleep duration and the prevalence of obesity. Daytime napping was strongly associated with greater adiposity. Interventional and longitudinal studies are needed to better understand how abnormal sleep patterns contribute to the obesity epidemic.

Impact of insomnia on pain in postmenopausal women

BACKGROUND

Sleep disturbances and pain are assumed to be reciprocally linked. Insomnia and pain are central symptoms of the postmenopausal period and are closely related. Insomnia affects quality of life, increases pain sensitivity, the risk of pain-related disability, and other health problems.

OBJECTIVE

To investigate whether insomnia influences aspects of pain (pain intensity and the effect of pain on daily function) in postmenopausal women, and to evaluate the objective sleep pattern of insomniacs with pain.

METHODS

Fifty-seven women completed questionnaires about insomnia, climacteric symptoms, and pain. Polysomnography data were collected as well as their medical history. Patients were allocated into three groups: control, subthreshold insomnia, and insomnia. Pain intensity, climacteric symptoms and objective sleep pattern were compared between groups.

RESULTS

Postmenopausal women with insomnia had statistically significant higher pain interference in their activities (e.g. relationships with other people, enjoyment of life and sleep) than controls, and had more severe climacteric symptoms. There were no statistically significant differences in pain intensity and objective sleep pattern between groups.

CONCLUSIONS

Insomnia status affected climacteric symptoms and pain interference, but not pain intensity in postmenopausal women. Women with insomnia had higher rates of climacteric symptoms than those without insomnia or those with subthreshold insomnia. No changes in objective sleep pattern were found.

Causal Mediation in the Development of Painful Temporomandibular Disorder

We explored causal mediation of sleep quality and perceived stress in development of painful temporomandibular disorder (TMD). Sleep quality and perceived stress were assessed at baseline and quarterly intervals thereafter in 2,737 initially TMD-free adults in the Orofacial Pain Prospective Evaluation and Risk Assessment study (OPPERA) prospective cohort study. During follow-up, incident TMD cases were classified using research diagnostic criteria. Mediation analysis was conducted using a weighted Cox proportional hazards regression model that estimated hazard ratios (HRs) and 95% confidence limits (CL) of first-onset TMD. Models determined whether: 1) poor sleep quality during follow-up mediated the effect of baseline perceived stress on first-onset TMD, and 2) perceived stress during follow-up mediated the effect of baseline poor sleep quality on first-onset TMD. In both analyses, the total effect was decomposed into natural direct and indirect effects. Poor baseline sleep quality led to heightened perceived stress that then contributed to TMD development. When the total effect of poor sleep quality (HR = 2.10, CL = 1.76, 2.50) was decomposed, 34% of its effect was mediated by perceived stress (indirect effect HR = 1.29, CL = 1.06, 1.58). The effect of perceived stress on first-onset TMD was not mediated by sleep quality. Improving sleep may avert escalation of stress, limiting effects of both factors on TMD development.

PERSPECTIVE

Causal mediation analysis highlights mechanisms by which poor sleep quality promotes development of TMD. First, poor sleep quality exerts a direct effect on pain. Second, it triggers a heightened perception of stress, which acts as an intermediate factor in the causal pathway between poor sleep quality and first-onset TMD pain.