Clinical characteristics of obstructive sleep apnea in bipolar disorders

Polysomnographic features of insomnia occurring in major depressive disorder, generalized anxiety disorder and bipolar mania: Comparison with primary insomnia and association with metabolic indicators

BACKGROUND

Insomnia is very common in psychiatric disorders, but the polysomnographic (PSG) characteristics of insomnia in various psychiatric disorders are still not agreed upon. This study aimed to investigate the characteristics of PSG and its relationship with metabolic indicators in insomnia patients with affective disorders and primary insomnia (PI) patients.

METHODS

A total of 38 patients with PI, 44 major depressive disorder patients with insomnia (DI), 49 generalized anxiety disorder patients with insomnia (GI), and 19 bipolar mania patients with insomnia (BI) were included. PSG was used to detect sleep problems in subjects, and biochemical indicators were also collected.

RESULTS

The results of this study found that subjects with BI were lower on REM sleep latency (RL), awakenings number (AN), number of microarousals (NM), and apnea-hypopnea index (AHI) than those with DI and GI, and lower on RL and AN than those with PI. Subjects with PI had lower NM and AHI than those with DI and GI. Patients with DI had a higher RL than those with GI. All results passed Bonferroni correction (p < 0.00078). No differences in biochemical indices were found among the four groups of subjects. Also, AHI was found to be positively correlated with free triiodothyronine (FT3) and fasting blood glucose in subjects.

CONCLUSION

This study suggests that various psychiatric disorders may have their characteristics in terms of PSG parameters, which prompted us to focus on the PSG characteristics of these disorders when assessing them, as well as to focus on their biochemical indicators.

Effects of smoking on sleep architecture and ventilatory parameters including apneas: Results of the Tab-OSA study

Background

The interaction between smoking and sleep seems appears to be bidirectional, but few studies evaluated the impact of smoking and its cessation on objective sleep parameters. In this context, this new study aimed to assess the impact of smoking and its cessation on sleep architecture and on ventilatory sleep parameters, particularly the presence of sleep apnea syndrome (apnea-hypopnea index (AHI)≥15). Methods: Patients hospitalized for polysomnographic sleep exploration were compared according to their smoking status: active smokers (AS), former smokers (FS), non-smokers (NoNi). Psychiatric and non-psychiatric co-morbidities and treatment or substance use were taken into account in the analyses.

Results

A total of 170 participants were included (N = 37 FS, 39 AS, 86 NoNi). A significant decrease in the mean nocturnal O2 saturation was observed for FS and AS compared to NoNi. No differences were found regarding AHI. Regarding sleep architecture, we observed a significant decrease in the slow wave sleep duration for AS compared to NoNi, and interestingly not between FS and NoNi.

Conclusion

This study suggests that current smokers suffer from alterations in both sleep architecture and ventilatory parameters, the later appears to persist even after smoking cessation.

Diurnal symptoms of sleepiness and dysfunction predict future suicidal ideation in a French cohort of outpatients (FACE-DR) with treatment resistant depression: A 1-year prospective study about sleep markers

BACKGROUND

Patients suffering from treatment-resistant depression (TRD) are at risk of suicide. Sleep and circadian rhythm alterations are widely recognized as core symptoms of major depressive disorder and are associated with suicidal ideation. Thus, sleep and circadian rhythm alterations may be targeted to prevent suicide.

METHODS

Patients were recruited from a prospective cohort of the French network of TRD expert centers. Mood, sleep and circadian rhythms were assessed at baseline; suicidal risk was assessed both at baseline and during a one-year follow-up with standardized subjective questionnaires.

RESULTS

Excessive daytime sleepiness (adjusted odds ratio aOR = 1.7(1-3.3), p = 0.04) and daytime dysfunction (aOR = 1.81(1.16-2.81), p = 0.0085) increased the risk of suicidal thoughts over the one-year follow-up period in patients with TRD after adjustment on age, gender, depression, trauma, anxiety, impulsivity, current daily tobacco smoking and body mass index. Hypnotics intake is associated with a reduced risk of suicidal ideation at one-year follow-up after the same adjustments (OR = 0.73(0.56-0.95), p = 0.019). Other associations between sleep quality or circadian rhythms and suicidal ideations at either baseline or one year did not remain significant in multivariate analyses after the same adjustments.

LIMITATIONS

Sleep assessments were based on self-reported questionnaires rather than objective measures.

CONCLUSIONS

Daytime sleepiness and dysfunction are predictors of suicidal ideations, whereas hypnotics intake is associated with a reduced risk of suicidal ideations. Diurnal symptoms of sleep disturbances are therefore red flags to target for preventing suicide in depressed patients, and hypnotics seem efficient in preventing suicide for patients with TRD.

Validation of a data collection set for the psychiatric, addiction, sleep and chronobiological assessments of patients with depression: A Delphi study for the SoPsy-depression French national cohort

OBJECTIVES

Despite international efforts to identify biomarkers of depression, none has been transferred to clinical practice, neither for diagnosis, evolution, nor therapeutic response. This led us to build a French national cohort (through the clinical and research network named SoPsy within the French biological psychiatry society (AFPBN) and sleep society (SFRMS)), to better identify markers of sleep and biological rhythms and validate more homogeneous subgroups of patients, but also to specify the manifestations and pathogeneses of depressive disorders. Before inclusions, we sought to provide a predefined, standardized, and robust set of data to be collected in all centers.

METHODS

A Delphi process was performed to achieve consensus through the independent rating of invited experts, the SoPsy-depression co-investigators (n=34). The initial set open for vote included 94 questionnaires targeting adult and child psychiatry, sleep and addiction.

RESULTS

Two questionnaire rounds were completed with 94% participation in the first round and 100% participation in the second round. The results of the Delphi survey incorporated the consensus opinion of the 32 members who completed both rounds. Nineteen of the 94 questionnaires achieved consensus at the first round and seventy of 75 at the second round. The five remaining questionnaires were submitted to three experts involved in the steering committee during a dedicated meeting. At the end, 24 questionnaires were retained in the mandatory and 26 in the optional questionnaire set.

CONCLUSIONS

A validated data collection set of questionnaires is now available to assess psychiatry, addiction, sleep and chronobiology dimensions of depressive disorders.

Novel digital methods for gathering intensive time series data in mental health research: scoping review of a rapidly evolving field

Recent technological advances enable the collection of intensive longitudinal data. This scoping review aimed to provide an overview of methods for collecting intensive time series data in mental health research as well as basic principles, current applications, target constructs, and statistical methods for this type of data.In January 2021, the database MEDLINE was searched. Original articles were identified that (1) used active or passive data collection methods to gather intensive longitudinal data in daily life, (2) had a minimum sample size of N ⩾ 100 participants, and (3) included individuals with subclinical or clinical mental health problems.In total, 3799 original articles were identified, of which 174 met inclusion criteria. The most widely used methods were diary techniques (e.g. Experience Sampling Methodology), various types of sensors (e.g. accelerometer), and app usage data. Target constructs included affect, various symptom domains, cognitive processes, sleep, dysfunctional behaviour, physical activity, and social media use. There was strong evidence on feasibility of, and high compliance with, active and passive data collection methods in diverse clinical settings and groups. Study designs, sampling schedules, and measures varied considerably across studies, limiting the generalisability of findings.Gathering intensive longitudinal data has significant potential to advance mental health research. However, more methodological research is required to establish and meet critical quality standards in this rapidly evolving field. Advanced approaches such as digital phenotyping, ecological momentary interventions, and machine-learning methods will be required to efficiently use intensive longitudinal data and deliver personalised digital interventions and services for improving public mental health.

Prevalence of risk for obstructive sleep apnea in patients with bipolar disorder

AIM

To evaluate the prevalence of risk for obstructive sleep apnea (OSA) among patients with bipolar disorder (BD).

METHODOLOGY

Eighty-seven patients with BD and 50 matched controls were assessed by using the Berlin questionnaire.

RESULTS

One-fifth of the patients with BD was found to be at high risk for OSA, compared to the 6% prevalence in the control group. Patients in high risk for OSA were more often females, had significantly higher body mass index, high waist circumference, and comorbid physical illnesses. In terms of pharmacotherapy, there was association of use of antipsychotics with higher risk of OSA at the trend level (p=0.052).

CONCLUSION

The prevalence of high risk for OSA is significantly higher among patients with BD and higher prevalence is related to obesity and comorbid physical illnesses.

[Atypical depression as a risk factor for obstructive sleep apnea syndrome in young adults]

OBJECTIVES

In the literature, several studies have investigated the particular relationship between major depression and obstructive sleep apnoea syndrome (OSAS). However, most of these studies have focused primarily on middle-aged to elderly individuals (≥40 years) which means that this problem has been little studied in young adults (<30 years). Nevertheless, in young adults the prevalence of major depression (particularly its atypical subtype) is not negligible, which seems to justify carrying out additional investigations in order to allow a better understanding of the potential role played by major depression in the pathophysiology of OSAS in this particular subpopulation. The aim of this study was therefore to empirically investigate the prevalence of OSAS in young adults and to study the risk of OSAS associated with major depression in this particular subpopulation.

METHODS

Polysomnographic and demographic data from 264 young adults were collected from the Erasme Hospital Sleep Laboratory (Brussels, Belgium) database to enable our analyses. During their two-night stay (including a first night of habituation and a night of polysomnography) at the Sleep Laboratory, these individuals underwent a complete somatic assessment (including blood test, electrocardiogram, daytime electroencephalogram and urinalysis), a systematic psychiatric assessment by a unit psychiatrist and an assessment of their complaints related to sleep. These different steps made it possible to systematically diagnose all somatic pathologies, psychiatric disorders according to the diagnostic criteria of the DSM-IV-TR and sleep pathologies according to the diagnostic criteria of the AASM. This allowed the selection of young adults included in our study based on our inclusion and exclusion criteria. Polysomnographic recordings from our Sleep Laboratory were visually scored according to AASM criteria. An obstructive sleep apnoea-hypopnoea index ≥5/hour was used for the diagnosis of OSAS. At the statistical level, in order to allow our analyses, we subdivided our sample of young adults into two groups: a control group without OSAS (n=215) and a patient group with OSAS (n=49). After checking the normal distribution of our data, normally distributed data were analysed with t-tests whereas asymmetrically or dichotomously distributed data were analysed with Wilcoxon tests or Chi² tests. Univariate regression models were used to study the risk of OSAS associated with major depression (categorized: absent, typical, atypical) in young adults and potential confounding factors. In multivariate regression models, the risk of OSAS associated with major depression (categorized: absent, typical, atypical) in young adults was adjusted only for confounding factors significantly associated with OSAS during univariate analysis. These confounding factors were introduced in a hierarchical manner in the various multivariate regression models constructed.

RESULTS

The prevalence of OSAS in our population of young adults was 18.6 %. During univariate analyses, atypical depression [OR 2.51 (95% CI 1.18-5.32), p-value=0.014], male gender [OR 4.53 (95% CI 2.20-9.34), P-value <0.001], presence of snoring [OR 2.51 (95% CI 1.33-4.75), P-value=0.005], presence of at least one cardio-metabolic alteration [OR 2.26 (95% CI 1.19-4.28), P-value=0.012], body mass index>30 kg/m² [OR 4.55 (95% CI 2.07-10.03), P-value <0.001] and ferritin ≥150 μg/L [OR 3.28 (95% CI 1.69-6.36), P-value<0.001] were associated with increased risk of OSAS in our population of young adults. After adjusting for these major confounding factors associated with OSAS (gender, body mass index, cardio-metabolic alterations, ferritin level, and snoring) in the four models studied, multivariate regression analyses confirmed that unlike typical depression, atypical depression [OR 3.09 (95% CI 1.26-7.54), P-value=0.019] was a risk factor for OSAS in young adults.

CONCLUSIONS

In our study, we demonstrated that the prevalence of OSAS was 18.6 % in young adults referred to the Erasme Hospital Sleep Laboratory. In addition, we have shown that unlike typical depression, atypical depression was associated with an increased risk of OSAS in young adults, which seems to justify more systematic research of this pathology in young adults suffering from atypical depression in order to allow the establishment of adapted therapeutic strategies and avoid the negative consequences associated with the co-occurrence of these two pathologies.

Misperception of sleep in bipolar disorder: an exploratory study using questionnaire versus actigraphy

Background

The concept of misperception of sleep refers to the estimated discrepancy between subjective and objective measures of sleep. This has been assessed only in a few prior studies in individuals with Bipolar Disorder (BD) as compared to Healthy Controls (HC) and with mixed results.

Methods

We assessed a sample of 133 euthymic individuals with BD and 63 HC for retrospective subjective (Pittsburgh Sleep Quality Index) and objective (21 days of actigraphy recording) measures of total sleep time, sleep latency and sleep efficiency. We first investigated the correlations between these subjective and objective measures in the two groups. We then compared individuals with BD and HC for the absolute values of the differences between subjective and objective sleep parameters, used as a proxy of the magnitude of misperception of sleep. Finally, we undertook regression analyses to assess associations between clinical groups, core demographics, clinical factors and misperception of sleep.

Results

The correlation coefficients between subjective and objective measures of sleep did not differ between groups (total sleep time: rho = .539 in BD and rho = .584 in HC; sleep latency: rho = .190 in BD and rho = .125 in HC; sleep efficiency: rho = .166 in BD and rho = .222 in HC). Individuals with BD did not differ from HC in the magnitude of misperception of total sleep time, sleep latency nor sleep efficiency. Individuals with BD type 1 misperceived their sleep efficiency significantly more than individuals with BD type 2, with no further difference between BD type 1 and BD type 2 regarding sleep latency and sleep duration misperceptions. Three factors (age, symptoms of obstructive sleep apnea, and mild depressive symptoms), were the main contributors to the magnitude of misperception of sleep.

Conclusions

Misperception of sleep was not associated with a diagnosis of BD. In this sample, mild depressive symptoms, older age, or symptoms of obstructive sleep apnea may be related to greater sleep misperception. In that case, the reliability of subjective measures may decrease as the misperception of sleep increases. This study may help guide clinicians in selecting the best approach for assessing sleep (objective versus subjective measures) in individuals with BD.