Aleksandra Wierzbicka

Sleep and antidepressant treatment.

The aim of this review was to describe the sleep anomalies in depression, the effects of antidepressants on sleep, the usefulness of antidepressants in the treatment of primary insomnia and insomnia in other psychiatric disorders. Depression is associated with abnormalities in the sleep pattern that include disturbances of sleep continuity, diminished slow-wave sleep (SWS) and altered rapid eye movement (REM) sleep parameters. Although none of the reported changes in sleep are specific to depression, many of them, for example increased REM density and reduced amount of SWS in the first sleep cycle, are used as biological markers for research on depression and in the development of antidepressant drugs. An antidepressant should reverse abnormalities in the sleep pattern. However, many antidepressants can worsen sleep. Because of the activating effects of some drugs, for example imipramine, desipramine, fluoxetine, paroxetine, venlafaxine, reboxetine and bupropion, many patients who take them have to be co-prescribed with sleep-promoting agents to improve sleep. Even in maintenance treatment with activating antidepressants as many as 30-40% of patients may still suffer from insomnia. Antidepressants with sleep-promoting effects include sedative antidepressants, for example doxepin, mirtazapine, trazodone, trimipramine, and agomelatine which promotes sleep not through a sedative action but through resynchronization of the circadian rhythm. Sedative antidepressants are frequently used in the treatment of primary insomnia, although not many double-blind studies have been provided to support such an approach to insomnia treatment. One exception is doxepin, which has been approved for the treatment of insomnia characterized by difficulties in maintaining sleep.

Sleep as a biomarker for depression

Abstract Sleep is a complex biological process that involves cyclic changes of brain activity. The smooth transition between wakefulness and sleep and cyclic succession of sleep stages depend on the function of numerous neurotransmitters that reciprocally influence each other. For this reason sleep is a very sensitive biomarker of brain functioning. This article provides an overview of sleep changes in depression, mechanisms involved in sleep regulation and pathophysiology underlying depression, studies on sleep as a biomarker for depression, effects of antidepressants on sleep EEG, and studies in depression with the use of quantitative sleep EEG analysis. Research on sleep in depression has provided several valuable biomarkers that are related to increased risk for depression, show worsening during depressive episode, and are related to treatment outcome and relapse risk during remission phase. Among many sleep parameters, increased REM density and diminished delta sleep ratio deserve special interest. Sleep studies are also an important research tool for antidepressant drug development. However, due to sensitivity of sleep parameters to pharmacological interventions, the patients have to be investigated before the start of pharmacological treatment or after washout from the antidepressant drug, to obtain reliable data on disease-related biological processes from polysomnography.

Electroencephalogram slowing, sleepiness and treatment response in patients with schizophrenia during olanzapine treatment

Electroencephalogram (EEG) slowing is associated with clozapine side effects, e.g., sedation, and may predict treatment response during clozapine treatment. As olanzapine and clozapine share many pharmacological properties, we investigated whether EEG slowing during olanzapine treatment was related to therapy outcome and sleepiness in patients with schizophrenia. Participants were age- and gender-matched schizophrenic patients treated with olanzapine (n 54), receiving no pharmacological treatment (n 54), or cotreated with olanzapine and some other psychotropic drug (n 38). Their EEG recordings were assessed visually by the same rater blind to clinical data. The EEG scores were categorized using standardized forms. Patients with a poor treatment response did not differ significantly from those with a good response to treatment either in EEG patterns or in frequency of sleepiness. Olanzapine treatment was associated with increased rates of slow (70.4% vs. 22.3%) and sharp waves (22.2% vs. 7.4%), as well as of paroxysmal slow wave discharges (14.8% vs. 1.9%), but did not induce spike- or sharp-slow-wave complexes. Cotreatment with another antipsychotic further increased EEG abnormalities, whereas benzodiazepine administration diminished the olanzapine-induced EEG changes. The results show that olanzapine inducing both slow and sharp waves, as well as paroxysmal discharges, has a strong impact on EEG. However, as no spike- or sharp-slow-wave complexes were observed, the risk of epileptic seizure during olanzapine treatment can be regarded as low, as long as olanzapine is not combined with some other antipsychotic.

Effects of Antidepressants on Sleep

Purpose of ReviewThe aim of this review article was to summarize recent publications on effects of antidepressants on sleep and to show that these effects not only depend on the kind of antidepressant drugs but are also related to the dose, the time of drug administration, and the duration of the treatment.Recent FindingsComplaints of disrupted sleep are very common in patients suffering from depression, and they are listed among diagnostic criteria for this disorder. Moreover, midnocturnal insomnia is the most frequent residual symptom of depression. Thus, all antidepressants should normalize sleep. However, at least in short-term treatment, many antidepressants with so-called activating effects (e.g. fluoxetine, venlafaxine) may disrupt sleep, while others with sedative properties (e.g., doxepin, mirtazapine, trazodone) rapidly improve sleep, but may cause problems in long-term treatment due to oversedation.For sleep-promoting action, the best effects can frequently be achieved with a very low dose, administered early enough before bedtime and importantly, always as a part of more complex interventions based on the cognitive-behavioral protocol to treat insomnia (CBT-I).SummaryFor successful treatment of depression, it is necessary to understand the effects of antidepressants on sleep. Each physician should also be aware that some antidepressants may worsen or induce primary sleep disorders like restless legs syndrome, sleep bruxism, REM sleep behavior disorder, nightmares, and sleep apnea, which may result from an antidepressant-induced weight gain.

Patients with insomnia and subthreshold depression show marked worsening of insomnia after discontinuation of sleep promoting medication.

OBJECTIVE To investigate whether the outcome of treatment with trazodone CR in primary insomnia differs between patients with and without subthreshold depression. METHODS 14 patients (9 females, mean age 57.3 ± 13.3) with primary insomnia and increased Beck Depression Inventory (BDI) scores (>10) and 15 sex- and age-matched patients with primary insomnia and low BDI scores (≤ 10) were treated with trazodone CR 25-150 mg/d for 3 months and followed for 1 month after discontinuation of the medication. The Athens Insomnia Scale (AIS), Sheehan Disability Scale (SDS), and Clinical Global Impression scale (CGI) were completed at baseline, after each month of treatment and after the first week of run-out phase. Additional assessment tools comprised sleep diaries, the Leeds Sleep Evaluation Questionnaire (LSEQ) and actigraphic recordings. RESULTS Subjective sleep time increased by 61.5 ± 72.3 min in the group with low BDI and 60.0 ± 59.4 min in the group with increased BDI at the end of the treatment phase. The significant improvements were also observed in the AIS, CGI, LSEQ and SDS. During the run-out phase the improvement was sustained in patients with low BDI, while AIS scores, sleep latency and total sleep time deteriorated in patients with increased BDI. CONCLUSIONS Patients with subthreshold depression, even if the depressive symptoms do not fulfill the time criteria for depressive episode, show marked worsening of insomnia after discontinuation of sleep promoting medication.

Low Risk for Switch to Mania during Treatment with Sleep Promoting Antidepressants

INTRODUCTION Sleep-promoting antidepressants are of interest because they are used not only as antidepressants, but also to promote sleep. METHODS We reviewed case reports describing the switch to mania during treatment with trazodone, mirtazapine, or agomelatine. RESULTS Trazodone, mirtazapine, and agomelatine may induce manic symptoms. However, the risk of switching is related, first of all, to doses recommended for antidepressant treatment, administered without mood-stabilizer co-therapy. Low doses of these antidepressants, used for their hypnotic or sedative effects, were observed to cause mania only in patients with other risk factors for switching. There is no evidence for trazodone or mirtazapine and only sparse evidence for agomelatine, claiming that treatment with these antidepressants is related to an increased risk of switching to mania when administered in combination with a mood stabilizer. DISCUSSION These findings suggest that low doses of trazodone and mirtazapine are safe in bipolar disorder, and should still be considered important alternatives to hypnotics when long-term pharmacological treatment of insomnia is necessary. It seems that these antidepressants and agomelatine can also be used safely in antidepressant doses when combined with a mood stabilizer.

Obstructive sleep apnea in severe mental disorders.

The prevalence of obstructive sleep apnoea (OSA) is estimated to be 3-7.5% in men and 2-3% in women. In mentally ill population it is even higher, as these patients are a high risk OSA group. The aim of the paper was a review of literature about the prevalence of sleep apnoea in patients with schizophrenia, bipolar disorder and recurrent depressive disorder.The available data show that OSA is present in 15-48% of patients with schizophrenia, 21-43% of patients with bipolar disorder and 11-18% of patients with recurrent depressive disorder. The lack of diagnosis of OSA in people with mental illnesses has multiple negative consequences. The symptoms of sleep apnoea might imitate the symptoms of mental illnesses such as negative symptoms of schizophrenia and symptoms of depression, they might as well aggravate the cognitive impairment. A number of the drugs used in mental disorders may aggravate the symptoms of OSA. OSA is as well the risk factor for cardiovascular and metabolic diseases which are a serious clinical problem in mentally ill people and contribute to shortening of their expected lifespan. From the point of view of the physicians treating OSA it is important to pay attention to the fact that co-existing depression is the most common reason for resistant daytime sleepiness in OSA patients treated effectively with Continuous Positive Airway Pressure (CPAP). CPAP therapy leads to significant improvement of mood. However, in schizophrenia and bipolar patients it may rarely lead to acute worsening of mental state, exacerbation of psychotic symptoms or phase shift from depression to mania.

Electroencephalographic theta activity and cognition in schizophrenia: Preliminary results

Abstract Objectives. MATRICS Consensus Cognitive Battery (MCCB) is a contemporary standard for assessment of cognitive functions in schizophrenia. The aim of the study was to examine the association between electroencephalographic spectral power and a wide range of cognitive functions measured with MCCB. Methods. Thirty-nine patients with schizophrenia (27 male, mean age 28.2 ± 5.2 years) underwent EEG recordings and were assessed with MCCB. The EEG recordings were visually inspected and manually cleaned from artifacts and subjected to spectral analysis with EEGlab. Absolute and relative power as percentage of total spectral power were computed for frequency ranges from 0.5 to 30 Hz. To compare spectral power in patients with various cognitive functioning, patients from best and worst MCCB quartiles were selected. Results. Superior cognitive performance was associated with less power of theta waves. Six MCCB cognitive tests showed significant correlations with absolute theta power and three tests with relative theta power. The correlation coefficients between MCCB composite score and theta power were rp = −0.45 for absolute and rp = −0.36 for relative values. Increased theta power was linked especially to memory deficits. Conclusions. These preliminary results suggest that electroencephalographic resting state theta power is an indicator of cognitive deficit in patients with schizophrenia.

Sertindole: EEG Analysis, Tolerability, and Clinical Efficacy

INTRODUCTION One of the common side effects of antipsychotic drugs is excessive sedation. The treatment with antipsychotics often manifests as an increase in slow wave activity in electroencephalography (EEG). The aim of this study was to analyze EEG recordings of patients treated with a non-sedative antipsychotic drug sertindole with regard to its adverse effects and clinical efficacy. PATIENTS AND METHODS EEG recordings of 45 patients (27 females, mean age 30.1±8.7 years) with schizophrenia were analyzed. EEG recordings were categorized based on abnormalities severity. The clinical efficacy was rated on the Clinical Global Impression Scale. RESULTS Abnormalities from mild to moderate were found in 29% of the group. Clinical improvement was observed in 80% of patients. Sedation/daytime sleepiness was present in 7% of patients. Other side effects were prolongation of QTc (11%, severe 4%), insomnia (9%), extrapyramidal symptoms (7%), and heart palpitations (2%). CONCLUSIONS Patients treated with sertindole do not show side effects similar to those found during treatment with other antipsychotic drugs. Increased slow wave activity in EEG and sedation were absent in the majority of the investigated patients.

Automatic artefact detection in single-channel sleep EEG recordings.

Quantitative electroencephalogram analysis (e.g. spectral analysis) has become an important tool in sleep research and sleep medicine. However, reliable results are only obtained if artefacts are removed or excluded. Artefact detection is often performed manually during sleep stage scoring, which is time consuming and prevents application to large datasets. We aimed to test the performance of mostly simple algorithms of artefact detection in polysomnographic recordings, derive optimal parameters and test their generalization capacity. We implemented 14 different artefact detection methods, optimized parameters for derivation C3A2 using receiver operator characteristic curves of 32 recordings, and validated them on 21 recordings of healthy participants and 10 recordings of patients (different laboratory) and considered the methods as generalizable. We also compared average power density spectra with artefacts excluded based on algorithms and expert scoring. Analyses were performed retrospectively. We could reliably identify artefact contaminated epochs in sleep electroencephalogram recordings of two laboratories (healthy participants and patients) reaching good sensitivity (specificity 0.9) with most algorithms. The best performance was obtained using fixed thresholds of the electroencephalogram slope, high‐frequency power (25–90 Hz or 45–90 Hz) and residuals of adaptive autoregressive models. Artefacts in electroencephalogram data can be reliably excluded by simple algorithms with good performance, and average electroencephalogram power density spectra with artefact exclusion based on algorithms and manual scoring are very similar in the frequency range relevant for most applications in sleep research and sleep medicine, allowing application to large datasets as needed to address questions related to genetics, epidemiology or precision medicine.