Dataset Information

Sleep and mental disorders: A meta-analysis of polysomnographic research.

ABSTRACT: Investigating sleep in mental disorders has the potential to reveal both disorder-specific and transdiagnostic psychophysiological mechanisms. This meta-analysis aimed at determining the polysomnographic (PSG) characteristics of several mental disorders. Relevant studies were searched through standard strategies. Controlled PSG studies evaluating sleep in affective, anxiety, eating, pervasive developmental, borderline and antisocial personality disorders, attention-deficit-hyperactivity disorder (ADHD), and schizophrenia were included. PSG variables of sleep continuity, depth, and architecture, as well as rapid-eye movement (REM) sleep were considered. Calculations were performed with the "Comprehensive Meta-Analysis" and "R" software. Using random effects modeling, for each disorder and each variable, a separate meta-analysis was conducted if at least 3 studies were available for calculation of effect sizes as standardized means (Hedges' g). Sources of variability, that is, sex, age, and mental disorders comorbidity, were evaluated in subgroup analyses. Sleep alterations were evidenced in all disorders, with the exception of ADHD and seasonal affective disorders. Sleep continuity problems were observed in most mental disorders. Sleep depth and REM pressure alterations were associated with affective, anxiety, autism and schizophrenia disorders. Comorbidity was associated with enhanced REM sleep pressure and more inhibition of sleep depth. No sleep parameter was exclusively altered in 1 condition; however, no 2 conditions shared the same PSG profile. Sleep continuity disturbances imply a transdiagnostic imbalance in the arousal system likely representing a basic dimension of mental health. Sleep depth and REM variables might play a key role in psychiatric comorbidity processes. Constellations of sleep alterations may define distinct disorders better than alterations in 1 single variable. (PsycINFO Database Record

SUBMITTER: Baglioni C

PROVIDER: S-EPMC5110386 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Sleep and mental disorders: A meta-analysis of polysomnographic research.

Baglioni Chiara C Nanovska Svetoslava S Regen Wolfram W Spiegelhalder Kai K Feige Bernd B Nissen Christoph C Reynolds Charles F CF Riemann Dieter D

Psychological bulletin 20160714 9

Investigating sleep in mental disorders has the potential to reveal both disorder-specific and transdiagnostic psychophysiological mechanisms. This meta-analysis aimed at determining the polysomnographic (PSG) characteristics of several mental disorders. Relevant studies were searched through standard strategies. Controlled PSG studies evaluating sleep in affective, anxiety, eating, pervasive developmental, borderline and antisocial personality disorders, attention-deficit-hyperactivity disorder ...[more]

PMID: 27416139

Similar Datasets

Project description:BACKGROUND:Sleep-wakefulness cycles are an essential diagnostic criterion for disorders of consciousness (DOC), differentiating prolonged DOC from coma. Specific sleep features, like the presence of sleep spindles, are an important marker for the prognosis of recovery from DOC. Based on increasing evidence for a link between sleep and neuronal plasticity, understanding sleep in DOC might facilitate the development of novel methods for rehabilitation. Yet, well-controlled studies of sleep in DOC are lacking. Here, we aimed to quantify, on a reliable evaluation basis, the distribution of behavioral and neurophysiological sleep patterns in DOC over a 24-h period while controlling for environmental factors (by recruiting a group of conscious tetraplegic patients who resided in the same hospital). METHODS:We evaluated the distribution of sleep and wakefulness by means of polysomnography (EEG, EOG, EMG) and video recordings in 32 DOC patients (16 unresponsive wakefulness syndrome [UWS], 16 minimally conscious state [MCS]), and 10 clinical control patients with severe tetraplegia. Three independent raters scored the patients' polysomnographic recordings. RESULTS:All but one patient (UWS) showed behavioral and electrophysiological signs of sleep. Control and MCS patients spent significantly more time in sleep during the night than during daytime, a pattern that was not evident in UWS. DOC patients (particularly UWS) exhibited less REM sleep than control patients. Forty-four percent of UWS patients and 12% of MCS patients did not have any REM sleep, while all control patients (100%) showed signs of all sleep stages and sleep spindles. Furthermore, no sleep spindles were found in 62% of UWS patients and 21% of MCS patients. In the remaining DOC patients who had spindles, their number and amplitude were significantly lower than in controls. CONCLUSIONS:The distribution of sleep signs in DOC over 24?h differs significantly from the normal sleep-wakefulness pattern. These abnormalities of sleep in DOC are independent of external factors such as severe immobility and hospital environment.

Project description:BackgroundResearch on sleep after stroke has focused mainly on sleep disordered breathing. However, the extend to which sleep physiology is altered in stroke survivors, how these alterations compare to healthy volunteers, and how sleep changes might affect recovery as well as physical and mental health has yet to be fully researched. Motivated by the view that a deeper understanding of sleep in stroke is needed to account for its role in health and well-being as well as its relevance for recovery and rehabilitation, we conducted a systematic review and meta-analysis of polysomnographic studies comparing stroke to control populations.MethodMedline and PsycInfo databases were searched using "stroke" and words capturing polysomnographic parameters as search terms. This yielded 1692 abstracts for screening, with 15 meeting the criteria for systematic review and 9 for meta-analysis. Prisma best practice guidelines were followed for the systematic review; the Comprehensive Meta-Analysis software was used for random effects modelling.ResultsThe meta-analysis revealed that patients with stroke have poorer sleep than controls. Patients had lower sleep efficiency (mean 75% vs 84%), shorter total-sleep-time (309.4 vs 340.3 min) and more wake-after-sleep-onset (97.2 vs 53.8 min). Patients also spend more time in stage 1 (13% vs 10%) and less time in stage 2 sleep (36% vs 45%) and slow-wave-sleep (10% vs 12%). No group differences were identified for REM sleep. The systematic review revealed a strong bias towards studies in the early recovery phase of stroke, with no study reporting specifically on patients in the chronic state. Moreover, participants in the control groups included community samples as well as other patients groups.ConclusionsThese results indicate poorer sleep in patients with stroke than controls. While strongly suggestive in nature, the evidence base is limited and methodologically diverse, and hands a clear mandate for further research. A particular need regards polysomnographic studies in chronic community-dwelling patients compared to age-matched individuals.

Project description:Introduction: The diagnosis of sleep bruxism is challenging due to the difficulties involved. Sleep bruxism can lead to clinical consequences, including pain in masticatory muscles, limitation of jaw mobility, headache, and the spectrum of symptoms associated with damage to the teeth and oral mucosa. Currently, only video-polysomnography can definitely diagnose sleep bruxism. Due to the risk of painful temporomandibular disorders (TMD) in sleep bruxers, early diagnosis of pain in the temporomandibular region using questionnaires is recommended. Therefore, this study aimed to assess the relationship between the intensity of sleep bruxism and the occurrence of pain related to TMD. Materials and Methods: This study was conducted on the patients of the Clinic of Prosthetic Dentistry operating at the Department of Prosthetic Dentistry at the Wroclaw Medical University. Based on a positive medical history, a thorough examination for the diagnosis of probable sleep bruxism was carried out in the enrolled patients. Eligible patients were then subjected to a video-polysomnographic study. Each patient was asked to complete the TMD Pain Screener questionnaire to assess the occurrence of pain in jaw and temple area. Results: The results of the study showed that increased bruxism episode index (BEI) was statistically significantly correlated with increase of all types of bruxism episodes-phasic, tonic, and mixed-in all the studied patients; a significant correlation was also found with respect to division of patients into studied and control groups. The study also showed that there was no statistically significant difference between BEI values and scores of TMD Pain Screener. In all the studied patients, a higher BEI was not found to be correlated with the occurrence of TMD-related pain assessed by TMD Pain Screener; similarly, no correlation was found with respect to division of patients into studied and control groups. Conclusions: The occurrence of TMD-related pain is not related to the intensity of sleep bruxism. TMD Pain Screener may be used as an auxiliary tool in the diagnosis or risk of occurrence of TMD-related pain, whereas in the case of sleep bruxism, it has only limited diagnostic value. Clinical Trial Registration: www.ClinicalTrials.gov, identifier NCT03083405.

Project description:Trazodone has been widely prescribed for off-label use as a sleep aid. Identifying how trazodone impacts the performance of polysomnographic sleep architecture in insomnia disorder will provide additional data that can be used to guide clinical application. To assess the efficacy of trazodone in altering the polysomnographic sleep architecture in insomnia disorder so that sleep can be facilitated. PubMed, EMBASE, Web of Science, PsycINFO, Cochrane Library, Chinese Biomedical Literature Database (SinoMed), China National Knowledge Infrastructure, Wanfang Database, and the China Science and Technology Journal Database were searched for articles published between inception and June 2022. RCTs in patients with insomnia disorder applying trazodone in one arm of interventions at least 1 week, and reporting PSG parameters in the outcomes were eligible. RoB 2 was used to evaluate the risk of bias. The results of quality of evidence assessed by the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. When I2 < 50%, the fixed effects model was used. When I2 ≥ 50%, the random effects model was used. The mean differences (MD) or standardized mean differences (SMD) and odds ratios (OR) with 95% confidence intervals (CIs) were estimated. Eleven randomized controlled trials were selected and participants were 466. Risk of bias was low in 5 trials (45.5%), and was moderate in 6 (54.5%). Compared with the control group, trazodone significantly increased total sleep time (TST, min) (MD = 39.88, 95% CI 14.44-65.32, P = 0.002) and non-rapid eye movement stage 3 (N3, mixed min and %) (SMD = 1.61, 95% CI 0.69-2.53, P = 0.0006); trazodone significantly decreased latency to onset of persistent sleep (LPS, min) (MD = - 19.30, 95% CI - 37.28 to - 1.32, P = 0.04), non-rapid eye movement stage 1 (N1, mixed min and %) (SMD = - 0.62, 95% CI - 1.13 to - 0.12, P = 0.02), the number of awakenings (NAs, including both arousal times and arousal index) (SMD = - 0.67, 95% CI - 0.91 to - 0.42, P < 0.00001), and waking time after persistent sleep onset (WASO, mixed min and %) (SMD = - 0.42, 95% CI - 0.81, - 0.03, P = 0.04), with no obvious effect on non-rapid eye movement stage 2 (N2, mixed min and %) (SMD = - 0.15, 95% CI - 0.41 to 0.11, P = 0.25), rapid eye movement (REM, mixed min and %) (SMD = 0.22, 95% CI - 0.26 to 0.70, P = 0.37), rapid eye movement latency (REML, min) (MD = 2.33, 95% CI - 27.56 to 32.22, P = 0.88), or apnea-hypopnea index (AHI) (MD = - 4.21, 95% CI - 14.02 to 5.59, P = 0.40). Daytime drowsiness (OR = 2.53, 95% CI 1.14-5.64, P = 0.02) and decreased appetite (OR = 2.81, 95% CI 1.14-6.92, P = 0.02) occurred with greater frequency in the trazodone group as compared to the control group, and the differences were significant. The results of quality of evidence were very low in TST, N3 and AHI, were low in LPS, WASO and REM, and were moderate in N1 and NAs. The sources of heterogeneity in TST and N3 were not found out from sensitive and subgroup analysis and there was no high quality of evidence in outcomes by GRADE Assessment. Trials with combination of other therapy could be a problem in this meta-analysis as the possibility of interactions were found from sungroup analysis. Trazodone could improve sleep by changing the sleep architecture in insomnia disorder, but it should be used with caution due to the adverse events that may occur.PROSPERO registration register name: The effect of trazodone on polysomnography sleep architecture in patients with insomnia: a systematic review and meta-analysis protocol; Registration Number CRD42020215332.

Project description:BACKGROUND:It is presumed that pharmacological and non-pharmacological treatment of prenatal common mental disorders can mitigate associated adverse effects in offspring, yet strong evidence for the prophylactic benefits of treatment is lacking. We therefore examined the effect of prenatal treatments for common mental disorders on offspring outcomes. METHODS:For this meta-analysis, articles published up to August 31, 2017, were obtained from PubMed, PsycInfo, Embase, and Cochrane databases. Included studies needed to be randomized controlled trials (RCTs) on the effect of treatment of prenatal common mental disorders comparing an intervention to a control condition, including offspring outcome(s). Random effects models were used to calculate Hedges' g in the program Comprehensive Meta-Analysis© (version 3.0). RESULTS:Sixteen randomized controlled trials among 2778 pregnant women compared offspring outcomes between prenatal interventions and control groups. There were zero pharmacological, 13 psychological, and three other interventions (homeopathy, relaxation interventions, and short psycho-education). Birth weight (mean difference 42.88 g, g?=?0.08, 95% CI -0.06 to 0.22, p?=?0.27, n?=?11), Apgar scores (g?=?0.13, 95% CI -0.28 to 0.54, p?=?0.53, n?=?4), and gestational age (g?=?0.03, 95% CI -0.06 to 0.54, p?=?0.49, n?=?10) were not significantly affected. Other offspring outcomes could not be meta-analyzed due to the inconsistent reporting of offspring outcomes and an insufficient number of studies. CONCLUSIONS:Non-pharmacological interventions had no significant effect on birth outcomes, although this outcome should be considered with caution due to the risk of biases. No randomized controlled trial examined the effects of prenatal pharmacological treatments as compared to treatment as usual for common mental disorders on offspring outcomes. Present clinical guidelines may require more research evidence on offspring outcomes, including child development, in order to warrant the current recommendation to routinely screen and subsequently treat prenatal common mental disorders. TRIAL REGISTRATION:PROSPERO CRD42016047190.

Dataset Information

Sleep and mental disorders: A meta-analysis of polysomnographic research.

Publications

Sleep and mental disorders: A meta-analysis of polysomnographic research.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets