Insomnia in hospitalized psychiatric patients: prevalence and associated factors

The effect of locomotive syndrome on the trajectory of sleep disturbance in geriatric oncology inpatients

Objective

To explore the developmental trajectory of sleep disturbance in geriatric oncology inpatients and assess the impact of locomotive syndrome (LS) on this trajectory.

Methods

This longitudinal study enrolled 284 geriatric oncology inpatients through convenience sampling from August 2023 to February 2024 at the Oncology Center of the Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu Province, China. Sleep quality was monitored for seven days following admission (T0-T6) using a wrist motion analyzer. The developmental trajectory of sleep disturbance was analyzed using the latent category growth model (LCGM). Patients were categorized into the LS group (n=177) and the non-LS group (n=107) based on the 25-question Geriatric Locomotive Function Scale (GLFS-25). Comparisons were made between the two groups regarding the distribution of sleep disturbance trajectories.

Results

Three potential categories for the development trajectory of sleep disturbance in inpatients were identified: non-sleep disturbance, sleep disturbance improvement, and sleep disturbance persistence. The lowest sleep quality was observed on the second day after admission (T2). In the non-LS group, 40 cases (37.4%) experienced no sleep disturbance, 45 cases (42.1%) showed improvement, and 22 cases (20.6%) showed persistence of sleep disturbance. In the LS group, 32 cases (18.1%) experienced no sleep disturbance, 50 cases (28.2%) showed improvement, and 95 cases (53.7%) exhibited persistent sleep disturbance. Significant differences were found in the trajectory distribution of sleep disturbance between the two groups (P<0.001).

Conclusions

Sleep disturbance is prevalent in geriatric oncology inpatients, with an incidence of 74.6% (212/284), and is most severe on the third day after admission. Patients with LS exhibit lower overall sleep quality and a higher likelihood of persistent sleep disturbances.

Developing a Sleep Algxorithm to Support a Digital Medicine System: Noninterventional, Observational Sleep Study

Background

Sleep-wake patterns are important behavioral biomarkers for patients with serious mental illness (SMI), providing insight into their well-being. The gold standard for monitoring sleep is polysomnography (PSG), which requires a sleep lab facility; however, advances in wearable sensor technology allow for real-world sleep-wake monitoring.

Objective

The goal of this study was to develop a PSG-validated sleep algorithm using accelerometer (ACC) and electrocardiogram (ECG) data from a wearable patch to accurately quantify sleep in a real-world setting.

Methods

In this noninterventional, nonsignificant-risk, abbreviated investigational device exemption, single-site study, participants wore the reusable wearable sensor version 2 (RW2) patch. The RW2 patch is part of a digital medicine system (aripiprazole with sensor) designed to provide objective records of medication ingestion for patients with schizophrenia, bipolar I disorder, and major depressive disorder. This study developed a sleep algorithm from patch data and did not contain any study-related or digitized medication. Patch-acquired ACC and ECG data were compared against PSG data to build machine learning classification models to distinguish periods of wake from sleep. The PSG data provided sleep stage classifications at 30-second intervals, which were combined into 5-minute windows and labeled as sleep or wake based on the majority of sleep stages within the window. ACC and ECG features were derived for each 5-minute window. The algorithm that most accurately predicted sleep parameters against PSG data was compared to commercially available wearable devices to further benchmark model performance.

Results

Of 80 participants enrolled, 60 had at least 1 night of analyzable ACC and ECG data (25 healthy volunteers and 35 participants with diagnosed SMI). Overall, 10,574 valid 5-minute windows were identified (5854 from participants with SMI), and 84% (n=8830) were classified as greater than half sleep. Of the 3 models tested, the conditional random field algorithm provided the most robust sleep-wake classification. Performance was comparable to the middle 50% of commercial devices evaluated in a recent publication, providing a sleep detection performance of 0.93 (sensitivity) and wake detection performance of 0.60 (specificity) at a prediction probability threshold of 0.75. The conditional random field algorithm retained this performance for individual sleep parameters, including total sleep time, sleep efficiency, and wake after sleep onset (within the middle 50% to top 25% of the assessed devices). The only parameter where the model performance was lower was sleep onset latency (within the bottom 25% of all comparator devices).

Conclusions

Using industry-best practices, we developed a sleep algorithm for use with the RW2 patch that can accurately detect sleep and wake windows compared to PSG-labeled sleep data. This algorithm may be used for a more complete understanding of well-being for patients with SMI in a real-world setting, without the need for PSG and a sleep lab.

Sleep quality in secure psychiatric healthcare: Inpatient & staff perspectives

The lived experiences of psychiatric inpatients are not well represented in the literature, especially when these experiences pertain to health. Reports regarding sleep health are particularly sparse, despite the increasing prevalence of sleep disorders in this population. The current study aimed to explore inpatient and staff perspectives of inpatient sleep quality to aid the future development of a sleep quality intervention. Fourteen inpatients (average age 43 years, 36 % female) were recruited for individual interviews and eleven staff members were recruited for three focus groups, from a secure psychiatric hospital (England). A semi-structured interview guide facilitated discussions regarding the prevalence and type of inpatient sleep problems, existing support for inpatient sleep problems including medication, and the bidirectional relationships between nighttime sleep and daytime behaviours, such as napping and physical activity. Using reflexive thematic analysis, four themes were developed: Irregular Sleep Schedules, Nighttime Disruptions, The Patient's Bedroom, and Keeping a Routine & Staying Physically Active. Study results can be utilised when developing inpatient sleep interventions, which were identified within the study as being sorely needed. Such interventions could focus on managing daytime sleeping, sedentary behaviour, and physical activity, in order to support good sleep hygiene, foster regular sleep/wake cycles, and improve overall health.

Prevalence and clinical correlates of restless legs syndrome in psychiatric patients: A cross-sectional study from North India

Background

Restless legs syndrome (RLS) is a neuro-sensorimotor disorder which is scarcely researched and is commonly missed in routine psychiatry practice.

Aim

To evaluate the prevalence of RLS and its correlates in patients with anxiety, depression, and somatoform disorders.

Methods

A cross-sectional single-center study was undertaken in patients aged 18-65 years suffering from ICD-10 (International Statistical Classification of Diseases-10th edition) diagnosis of anxiety, depressive, and somatoform disorders. RLS was evaluated by using diagnostic criteria of International Restless Legs Syndrome Study Group (IRLSSG) and severity measured on IRLSSG scale. Depression and anxiety were rated on Hamilton Depression and Anxiety Rating Scales respectively, insomnia severity measured by Insomnia Severity Index (ISI), and quality of life measured by WHO Quality of Life-Brief version (WHO-QOL BREF) scale. Serum ferritin levels were measured for evaluating iron deficiency.

Results

The rate of RLS was 66.7%, 50%, and 48% in patients with depressive, anxiety, and somatoform disorders, respectively, with no significant inter-group difference. Nearly one-third of patients suffered from severe to very severe symptoms of RLS, and quality of life was poorest in those with depressive disorders. RLS was significantly higher in females (P = 0.019), who were married (P = 0.040), diagnosed with severe depression (P = 0.029), and abused benzodiazepines (P = 0.045). On binary logistic regression, female gender and presence of clinical insomnia predicted occurrence of RLS.

Conclusion

The prevalence of RLS is very high in patients with common psychiatric disorders which is often missed. Clinical enquiry and examination for reversible causes such as iron deficiency may assist in its diagnosis and improve clinical outcome.

Effects of quetiapine on sleep: A systematic review and meta-analysis of clinical trials

Quetiapine is a common off-label antipsychotic drug for treating insomnia. Its effects in different disease conditions and dosages remain unclear. We conducted a systematic review and meta-analysis in clinical trials examining the efficacy of low-dose quetiapine in sleep. We obtained 21 clinical trials. Mean difference (MD), standard mean difference (SMD), and odds ratio (OR) were used to estimate the effect sizes using a random-effects model. The pooled results showed that quetiapine improved sleep quality compared with placebo (SMD: -0.57 [95%CI: -0.75, -0.4]). The SMD of sleep quality was correlated with age (coefficient: -0.0174) and sex (coefficient: -0.012). The significant effects were observed in the general anxiety disorder (SMD: -0.59 [95%CI: -0.92, -0.27]), major depressive disorder (SMD: -0.47 [95%CI: -0.66, -0.28]), and healthy (SMD: -1.33, [95%CI [-2.12, -0.54]) subgroups, at the dosage of 50 mg (SMD: -0.36 [95%CI: -0.36, -0.11]), 150 mg (SMD: -0.4 [95%CI: -0.52, -0.29]), and 300 mg (SMD: -0.17 [95%CI: -0.31,-0.04]). Quetiapine increased total sleep time compared with placebo (MD: 47.91 [95%CI: 28.06, 67.76]) but not when compared with other psychiatric drugs (MD: -4.19 [95%CI: -19.43, 11.05]). Adverse events (AEs) and discontinuation due to AEs were common among the quetiapine users. Quetiapine is effective as a sleep-helping drug. Precaution is suggested when interpreting the results on the elderly due to the high heterogeneity caused by incorporating patients over 66 years in the meta-analyses. We recommend an initial dosage of 50-150 mg/day with priority consideration for the elderly with GAD or MDD while monitoring its potential AEs.

Risk of current suicidal ideations associated with lifelong anhedonia and recent change of anhedonia in individuals with insomnia: A cross-sectional study

BACKGROUND

Individuals with insomnia are a subpopulation at high-risk of suicide. However, despite the elements in favour of an implication of anhedonia in the occurrence of current suicidal ideations (SI), no study has investigated the role played by this affective symptom in the occurrence of current SI in individuals with insomnia. The aim of this study was to investigate the risk of current SI associated with lifelong anhedonia and recent change of anhedonia in individuals with insomnia.

METHOD

Demographic and polysomnographic data from 493 individuals with insomnia selected retrospectively from the clinical database of the Erasme Hospital Sleep Laboratory were analysed. Current SI were considered present if the score in item 9 of the Beck Depression Inventory (BDI-II) was ≥1 and/or if they were highlighted during the systematic psychiatric assessment conducted on admission to the Sleep Laboratory. Logistic regression analyses were used to determine the risk of current SI associated with anhedonia in individuals with insomnia.

RESULTS

The prevalence of current SI was 21.5% in our sample of individuals with insomnia. After adjusting for major confounding factors, multivariate logistic regression analyses demonstrated that unlike lifelong anhedonia, only recent change of anhedonia was a risk factor for current SI in individuals with insomnia.

CONCLUSION

In this study, we demonstrated that in individuals with insomnia, recent change of anhedonia is a risk factor for current SI, which seems to justify more systematic research and adequate therapeutic management of this condition to allow better prevention in this particular subpopulation at high-risk of suicide.

Sleep monitoring challenges in patients with neurocognitive disorders: A cross-sectional analysis of missing data from activity trackers

Background and Aims

Activity monitors, such as Fitbits®, are being used increasingly for research purposes and data have been validated in healthy community-dwelling older adults. Given the lack of research in older adults with neurocognitive disorders, we investigated the consistency of sleep data recorded from a wrist-worn activity monitor in this population.

Methods

Fitbit® activity monitors were worn by hospitalized older adults as part of a parent study investigating sleep and step count in patients recovering from hip fracture surgery in a tertiary care academic hospital in Hamilton, Canada between March 2018 and June 2019. In this secondary analysis, we compared the proportion of missing sleep data between participants with and without a neurocognitive disorder and used a multivariable model to assess the association between neurocognitive disorder and missing sleep data.

Results

Of 67 participants included in the analysis, 22 had a neurocognitive disorder (median age: 86.5 years). Sleep data were missing for 47% of the neurocognitive disorder group and 23% of the non-neurocognitive disorder group. The presence of a neurocognitive disorder was associated with an increased likelihood of missing sleep data using the Fitbit® activity monitors (adjusted odds ratio: 3.41; 95% confidence interval: 1.06-11.73, p = 0.04).

Conclusion

The inconsistent nature of sleep data tracking in hospitalized older adults with neurocognitive disorders highlights the challenges of using interventions in patient populations who are often excluded from validation studies. As opportunities expand for activity monitoring in persons with neurocognitive disorders, novel technologies not previously studied in this group should be used with caution.

Restless Legs Syndrome Prevalence and Clinical Correlates Among Psychiatric Inpatients: A Multicenter Study

Background

There are only limited reports on the prevalence of restless legs syndrome (RLS) in patients with psychiatric disorders. The present study aimed to evaluate the prevalence and clinical correlates in psychiatric inpatients in Germany and Switzerland.

Methods

This is a multicenter cross-sectional study of psychiatric inpatients with an age above 18 years that were diagnosed and evaluated face-to-face using the International RLS Study Group criteria (IRLSSG) and the International RLS severity scale (IRLS). In addition to sociodemographic and biometric data, sleep quality and mood were assessed using the Pittsburgh Sleep Quality Index (PSQI), the Insomnia Severity Index (ISI), the Epworth Sleepiness Scale (ESS), and the Patient Health Questionnaire (PHQ-9). In addition to univariate statistics used to describe and statistically analyze differences in variables of interest between patients with and without RLS, a logistic model was employed to identify predictors for the occurrence of RLS.

Results

The prevalence of RLS in a sample of 317 psychiatric inpatients was 16.4%, and 76.9% of these were diagnosed with RLS for the first time. RLS severity was moderate to severe (IRLS ± SD: 20.3 ± 8.4). The prevalences in women (p = 0.0036) and in first-degree relatives with RLS (p = 0.0108) as well as the body mass index (BMI, p = 0.0161) were significantly higher among patients with RLS, while alcohol consumption was significantly lower in the RLS group. With the exception of atypical antipsychotics, treatment with psychotropic drugs was not associated with RLS symptoms. Regarding subjective sleep quality and mood, scores of the PSQI (p = 0.0007), ISI (p = 0.0003), and ESS (p = 0.0005) were higher in patients with RLS, while PHQ-9 scores were not different. A logistic regression analysis identified gender (OR 2.67; 95% CI [1.25; 5.72]), first-degree relatives with RLS (OR 3.29; 95% CI [1.11; 9.73], ESS score (OR 1.09; 95% CI [1.01; 1.17]), and rare alcohol consumption (OR 0.45; 95% CI [0.22; 0.94] as predictors for RLS.

Conclusions

Clinically significant RLS had a high prevalence in psychiatric patients. RLS was associated with higher BMI, impaired sleep quality, and lower alcohol consumption. A systematic assessment of restless legs symptoms might contribute to improve the treatment of psychiatric patients.

Incidence of and Factors Associated with New-Onset Insomnia Among Lebanese Hospitalised Patients: A single-centre study

Objectives

This study aimed to determine the incidence and post-discharge resolution of new-onset insomnia in hospitalised patients with no previous history of insomnia, as well as to define major correlates of in-hospital insomnia.

Methods

This prospective observational study was conducted between November 2019 and January 2020 at a tertiary care centre in Lebanon. All hospitalised patients >18 years of age with no history of insomnia were screened for new-onset insomnia using the Insomnia Severity Index (ISI) scale. Subsequently, patients were re-assessed two weeks after discharge to determine insomnia resolution.

Results

A total of 75 patients were included in the study. Of these, nine (12%) had no insomnia, 34 (45.3%) had subthreshold insomnia, 22 (29.3%) had moderate insomnia and 10 (13.3%) had severe insomnia. The mean ISI score was 14.95 ± 6.05, with 88% of patients having ISI scores of >7 (95% confidence interval: 0.822–0.965). The frequency of new-onset insomnia was significantly higher among patients who shared a room compared to those in single-bed rooms (95.7% versus 75%; P = 0.011). Other factors were not found to be associated with new-onset insomnia, including the administration of medications known to cause insomnia, in-hospital sedative use, overnight oxygen, cardiac monitoring and self-reported nocturnal toilet use. Overall, insomnia resolution occurred in 78.7% of patients two weeks after discharge.

Conclusion

There was a high incidence of acute new-onset insomnia among hospitalised patients at a tertiary centre in Lebanon. Additional research is recommended to further examine inhospital sleep disturbance factors and to seek convenient solutions to limit insomnia.

The three syndromes and six Chinese patent medicine study during the recovery phase of COVID-19

The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), first broke out in Wuhan, China, in 2019. SARS-CoV-2 develops many types of mutations (such as B.1.1.7), making diagnosis and treatment challenging. Although we now have a preliminary understanding of COVID-19, including pathological changes, clinical manifestations, and treatment measures, we also face new difficulties. The biggest problem is that most COVID-19 patients might face sequelae (e.g., fatigue, sleep disturbance, pulmonary fibrosis) during the recovery phase. We aimed to test six Chinese patent medicines to treat three major abnormal symptoms in COVID-19 patients during the recovery phase, including cardiopulmonary function, sleep disturbance, and digestive function. We launched the "three syndromes and six Chinese patent medicines" randomized, double-blind, placebo-controlled, multicenter clinical trial on April 10, 2020. The results showed that Jinshuibao tablets and Shengmaiyin oral liquid significantly improved the cardiopulmonary function of recovering COVID-19 patients. Shumian capsules, but not Xiaoyao capsules, significantly improved patients' sleep disorders. This might be because the indication of Xiaoyao capsules is liver qi stagnation rather than psychological or emotional problems. Xiangsha Liujun pills and Ludangshen oral liquid significantly improved digestive function. Our research provides a guideline for treating COVID-19 sequelae in patients during the recovery period based on high-quality evidence.

The Smarter Sleep educational interventions: an initiative to reduce hypnotic prescribing in in-patient psychiatric care

AIMS AND METHOD

In-patients on mental health wards are commonly prescribed hypnotics for the long-term management of disturbed sleep. Specific sleep disorders remain underdiagnosed and effective behavioural interventions are underused. We developed a suite of three educational interventions (a video, poster and handbook) about sleep, sleep disorders, the safe prescribing of hypnotics and use of psychological strategies (sleep hygiene and cognitive-behavioural therapy for insomnia, CBTi) using co-design and multiprofessional stakeholder involvement. This controlled before-and-after study evaluated the effectiveness of these interventions across seven in-patient psychiatric wards, examining their impact on hypnotic prescribing rates and staff confidence scores (data collected by retrospective drug chart analysis and survey respectively).

RESULTS

A marked reduction was seen in the percentage of patients prescribed hypnotics on in-patient prescription charts (-24%), with a 41% reduction in the number of hypnotics administered per patient (mean reduction -1.142 administrations/patient).

CLINICAL IMPLICATIONS

These simple educational strategies about the causes and treatment of insomnia can reduce hypnotic prescribing rates and increase staff confidence in both the medical and psychological management of insomnia.

Assessment of sleep quality and its predictors among newly diagnosed psychiatric patients

OBJECTIVES

Poor sleep is a vital symptom observed in many psychiatric conditions and is the most neglected and underdiagnosed. The current study aims at assessment of sleep quality among psychiatric patients using the Pittsburgh Sleep Quality Index (PSQI) scale and to identify the predictors of sleep quality.

METHODS

A hospital-based cross-sectional observational study conducted in the Psychiatry department with a sample size of 256 patients for six months. PSQI scale was used to assess sleep quality and multiple logistic regression was used (to identify) the predictors for poor sleep quality.

RESULTS

The mean age of the study population was 37.95 ± 14.11 years, with 148 (58%) male study participants. 192 (75%) of the study population had poor sleep quality with respect to PSQI scale with a mean score of 9.05 ± 4.65 that was well above the expected range (0-5) suggestive of compromised quality of sleep (p=0.001). Poor sleep satisfaction, waking up after the sleep onset, anorexia, day time drowsiness and at least one completely sleepless night in the past one week of admission were identified as good predictors for poor sleep quality.

CONCLUSIONS

Our study addresses the importance of assessing sleep quality regardless of the psychiatric conditions. We recommend screening patients if they have Poor sleep satisfaction, waking up after the sleep onset, anorexia, day time drowsiness or at least one completely sleepless night in the past one week of admission predictors for comorbid sleep disorders.

Sleepless in the hospital: A systematic review of non-pharmacological sleep interventions

OBJECTIVE

Poor sleep is highly prevalent in inpatient medical settings and has been associated with attenuated healing and worsened outcomes following hospitalization. Although nonpharmacological interventions are preferred, little is known about the best way to intervene in hospital settings.

METHOD

A systematic review of published literature examining nonpharmacological sleep interventions among inpatients in Embase, PsycINFO and PubMed in accordance with PRISMA guidelines.

RESULTS

Forty-three of the 1529 originally identified manuscripts met inclusion criteria, encompassing 2713 hospitalized participants from 18 countries comprised of psychiatric and older adult patients living in hospital settings. Main outcomes were subjective and objective measures of sleep duration, quality, and insomnia.

CONCLUSIONS

Overall, the review was unable to recommend any specific intervention due to the current state of the literature. The majority of included research was limited in quality due to lack of controls, lack of blinding, and reliance on self-reported outcomes. However, the literature suggests melatonin and CBT-I likely have the most promise to improve sleep in inpatient medical settings. Additionally, environmental modifications, including designated quiet time and ear plugs/eye masks, could be easily adopted in the care environment and may support sleep improvement. More rigorous research in nonpharmacological sleep interventions for hospitalized individuals is required to inform clinical recommendations.

Sleep problems as a risk factor for suicide: Are certain specific sleep domains associated with increased suicide risk?

OBJECTIVES

The purpose of this study was to examine the relationship between sleep problems and suicidal ideation in depressive patients.

BACKGROUND AND AIMS

Evidence from diverse settings and populations indicates that sleep problems are associated with suicidal ideation. However, relationships between them are not well defined. This study was conducted in order to explore whether poor sleep was associated with suicidal ideation above and beyond depression and whether specific domains of sleep were related to suicidal ideation. We also determined whether the association between sleep problems and suicidal ideation was mediated by depression.

MATERIALS AND METHODS

Patients aged 18-65 years from an outpatient clinic at Seoul St. Mary's Hospital were recruited for this study. From September 2010 to November 2017, a total of 909 participants were included in the final sample. The Beck Depression Inventory (BDI) and Pittsburgh Sleep Quality Index (PSQI) were used to assess psychiatric symptoms. Independent samples t-test, chi-square test, Pearson correlation analyses, hierarchical multiple regression analyses, and mediation analyses were performed using SPSS PROCESS macro.

RESULTS

The majority of participants with suicidal ideation also had sleep problems (94.9%). After controlling for age, marital status, and depressive symptoms, total sleep problems estimated by the PSQI global score were also significant associated with suicidal ideation. Among seven sleep components derived from the PSQI, several components including cough or snore loudly, have bad dreams, and use sleep medication were associated with increased suicide risk. Also, the relationship between sleep problems and suicidal ideation was mediated by depressive symptoms indirectly. There was no convincing direct relationship between sleep problems and suicidal ideation.

CONCLUSIONS

Investigating the pathways which connect sleep problems and suicidality is fundamental to the development of suicide prevention. While it might be premature to suggest specific interventions, it would be important for clinicians to consider evaluating and managing sleep problems in the context of suicidality.