Network pharmacology strategy to investigate the pharmacological effects of Suanzaoren Decoction on insomnia

Abstract Suanzaoren Decoction (SZRD) is an ancient prescription used in the treatment of insomnia. This study aimed to investigate the components and targets of SZRD in treating insomnia. First, the compounds of five herbs in SZRD were collected from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the putative targets for treating insomnia were obtained from DrugBank to construct the herb-compound-target- disease network. A protein-protein interaction (PPI) network was constructed in the STRING database, and then Gene Ontology functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed to predict the mechanism of action of intersection target. Finally, 30 mice were divided into five groups: control, model, and quercetin groups (100, 50, 25 mg/kg). The sleep latency and duration of pentobarbital-induced sleeping were measured. The production of interleukin-6 (IL-6) and γ-aminobutyric acid (γ-GABA) was detected by using an enzyme-linked immunosorbent assay kit (ELISA), and Gamma-aminobutyric acid type a receptor subunit alpha1 (GABRA1) was tested by Reverse Transcription-Polymerase Chain Reaction (RT-PCR). A total of 152 active ingredients, including 80 putative targets of SZRD, were obtained. The main active compounds included quercetin and kaempferol, and the key targets involved IL-6 and nitric oxide synthase 3 (NOS3). The results of pathway enrichment analysis indicated that the putative targets of SZRD mainly participated in Neuroactive ligand-receptor interaction. The experiment of P-chlorophenylalanine (PCPA)-induced insomnia model showed that quercetin obviously shortened the sleep latency and prolonged the sleep duration of the insomnia model. The production of IL-6, γ-GABA, and GABRA1 mRNA was significantly increased in mice treated with quercetin. This study predicted the active ingredients and potential targets of SZRD on insomnia on the basis of a systematic network pharmacology approach and illustrated that SZRD might exert hypnotic effects via regulating IL-6, γ-GABA, and GABRA1

Insomnia subtypes characterised by objective sleep duration and NREM spectral power and the effect of acute sleep restriction: an exploratory analysis.

Insomnia disorder (ID) is a heterogeneous disorder with proposed subtypes based on objective sleep duration. We speculated that insomnia subtyping with additional power spectral analysis and measurement of response to acute sleep restriction may be informative in overall assessment of ID. To explore alternative classifications of ID subtypes, insomnia patients (n = 99) underwent two consecutive overnight sleep studies: (i) habitual sleep opportunity (polysomnography, PSG) and, (ii) two hours less sleep opportunity (electroencephalography, EEG), with the first night compared to healthy controls (n = 25). ID subtypes were derived from data-driven classification of PSG, EEG spectral power and interhemispheric EEG asymmetry index. Three insomnia subtypes with different sleep duration and NREM spectral power were identified. One subtype (n = 26) had shorter sleep duration and lower NREM delta power than healthy controls (short-sleep delta-deficient; SSDD), the second subtype (n = 51) had normal sleep duration but lower NREM delta power than healthy controls (normal-sleep delta-deficient; NSDD) and a third subtype showed (n = 22) no difference in sleep duration or delta power from healthy controls (normal neurophysiological sleep; NNS). Acute sleep restriction improved multiple objective sleep measures across all insomnia subtypes including increased delta power in SSDD and NSDD, and improvements in subjective sleep quality for SSDD (p = 0.03), with a trend observed for NSDD (p = 0.057). These exploratory results suggest evidence of novel neurophysiological insomnia subtypes that may inform sleep state misperception in ID and with further research, may provide pathways for personalised care.

Trastornos del sueño en emergencias y desastres / Sleep disorders in emergencies and disasters

Los trastornos del sueño son frecuentes en la población y una causa importante de morbilidad. El objetivo de esta revisión es evaluar las alteraciones del sueño en periodos de emergencia y desastres. A lo largo de la historia, la esfera biopsicosocial y el sueño de las personas ha sido abrumada por múltiples eventos a gran escala, tales como desastres naturales, tragedias provocadas por el hombre, conflictos bélicos, crisis sociales y pandemias, cuya experiencia puede derivar en problemas de salud a corto, mediano y/o largo plazo. En los estudios analizados, se ha observado el impacto negativo de las emergencias y desastres en el sueño, por lo que ha cobrado gran relevancia la difusión y promoción de medidas que incentiven el buen dormir. Debido a la llegada del COVID-19 y a la situación de confinamiento por periodos prolongados en el hogar para prevenir su propagación, han surgido importantes consecuencias a nivel social. Ciertos factores ocupacionales y características de los desastres se asocian a mayor comorbilidad, un alto riesgo de experimentar agotamiento físico, trastornos psicológicos e insomnio en grupos altamente vulnerables, como lo son los profesionales de la salud, rescatistas y socorristas. El insomnio es el trastorno de sueño más frecuente en la población general y su empeoramiento en el contexto de pandemia por COVID-19 representa un nuevo problema en salud pública. Es por ello, que es indispensable promover campañas de prevención de salud física y mental orientados a la pesquisa precoz y manejo de patologías de la esfera psicosocial, dentro de las posibilidades socioeconómicas.

Sleep disorders are common in the population and are major cause of morbidity. The objective of this review is to assess sleep disturbances in times of emergency and disasters. Throughout history, the biopsychosocial field and sleep have been affected by multiple large-scale events, such as natural disasters, man-caused tragedies, armed conflicts, social crises and pandemics, the experience of which can lead to short, medium and/or long term health problems. In several studies, the negative impact of emergencies and disasters on sleep have been analyzed, emphasizing the importance of the diffusion and promotion of measures that encourage good sleep. The arrival of COVID-19 and consequent home confinement for prolonged periods caused important social consequences. Certain occupational factors and characteristics of disasters are associated with greater comorbidity: a high risk of experiencing physical exhaustion, psychological disorders and insomnia, especially in highly vulnerable groups, such as health professionals, rescuers and first aids-responders. Insomnia is the most frequent sleep disorder in the general population and its worsening in the context of the COVID-19 pandemic, represents a new public health problem. It is essential to promote physical and mental health prevention campaigns, aimed at early screening and management of pathologies in the psychosocial sphere, within socioeconomic possibilities.

Insomnia Disorders: Nosology and Classification Past, Present, and Future.

Insomnia is the most common sleep disorder in the adult population. However, the definition of insomnia disorder has varied across major classification systems and changed over time. In the present study, the investigators traced the evolution of insomnia disorder across classification systems, contemplated the empirical basis for its current definitions, and surveyed ongoing research efforts that may clarify insomnia nosology in the future. Three major classification systems for insomnia are the International Classification of Sleep Disorders, the International Classification of Diseases, and DSM. Despite their divergent origins, these classification systems have converged to nearly identical contemporary insomnia definitions. Over time, the emphasis in classification approaches has shifted from symptomatology to etiology to treatment implications. Additionally, the historical multitude of insomnia subtypes has gradually consolidated into a few core diagnoses, reflecting inadequate evidence with which to support subtyping. Current insomnia definitions include frequency and duration criteria to operationalize these diagnoses, while the diagnostic criterion of nonrestorative sleep has been eliminated (with some controversy). In ongoing research efforts, the quest for insomnia biomarkers has not thus far yielded clinically deployable breakthroughs. Data-driven insomnia subtyping suggests a promising new approach in deriving empirically based subtypes; conversely, the transdiagnostic perspective proposes the elimination of categorical distinctions in favor of finding common processes underlying all psychiatric disorders. The continual evolution of insomnia nosology highlights that much remains to be learned about these conditions; all current diagnostic classification systems are best regarded as "works in progress." Nevertheless, refinement and convergence of classification approaches is essential to standardizing insomnia research, diagnosis, and treatment.

Are symptoms of insomnia related to respiratory symptoms? Cross-sectional results from 10 European countries and Australia.

OBJECTIVES: To compare the prevalence of different insomnia subtypes among middle-aged adults from Europe and Australia and to explore the cross-sectional relationship between insomnia subtypes, respiratory symptoms and lung function. DESIGN: Cross-sectional population-based, multicentre cohort study. SETTING: 23 centres in 10 European countries and Australia. METHODS: We included 5800 participants in the third follow-up of the European Community Respiratory Health Survey III (ECRHS III) who answered three questions on insomnia symptoms: difficulties falling asleep (initial insomnia), waking up often during the night (middle insomnia) and waking up early in the morning and not being able to fall back asleep (late insomnia). They also answered questions on smoking, general health and chronic diseases and had the following lung function measurements: forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and the FEV1/FVC ratio. Changes in lung function since ECRHS I about 20 years earlier were also analysed. MAIN OUTCOME MEASURES: Prevalence of insomnia subtypes and relationship to respiratory symptoms and function. RESULTS: Overall, middle insomnia (31.2%) was the most common subtype followed by late insomnia (14.2%) and initial insomnia (11.2%). The highest reported prevalence of middle insomnia was found in Iceland (37.2%) and the lowest in Australia (22.7%), while the prevalence of initial and late insomnia was highest in Spain (16.0% and 19.7%, respectively) and lowest in Denmark (4.6% and 9.2%, respectively). All subtypes of insomnia were associated with significantly higher reported prevalence of respiratory symptoms. Only isolated initial insomnia was associated with lower FEV1, whereas no association was found between insomnia and low FEV1/FVC ratio or decline in lung function. CONCLUSION: There is considerable geographical variation in the prevalence of insomnia symptoms. Middle insomnia is most common especially in Iceland. Initial and late insomnia are most common in Spain. All insomnia subtypes are associated with respiratory symptoms, and initial insomnia is also associated with lower FEV1.

Revisiting the value of polysomnographic data in insomnia: more than meets the eye.

BACKGROUND: Polysomnography (PSG) is not recommended as a diagnostic tool in insomnia. However, this consensual approach might be tempered in the light of two ongoing transformations in sleep research: big data and artificial intelligence (AI). METHOD: We analyzed the PSG of 347 patients with chronic insomnia, including 59 with Sleep State Misperception (SSM) and 288 without (INS). 89 good sleepers (GS) were used as controls. PSGs were compared regarding: (1) macroscopic indexes derived from the hypnogram, (2) mesoscopic indexes extracted from the electroencephalographic (EEG) spectrum, (3) sleep microstructure (slow waves, spindles). We used supervised algorithms to differentiate patients from GS. RESULTS: Macroscopic features illustrate the insomnia conundrum, with SSM patients displaying similar sleep metrics as GS, whereas INS patients show a deteriorated sleep. However, both SSM and INS patients showed marked differences in EEG spectral components (meso) compared to GS, with reduced power in the delta band and increased power in the theta/alpha, sigma and beta bands. INS and SSM patients showed decreased spectral slope in NREM. INS and SSM patients also differed from GS in sleep microstructure with fewer and slower slow waves and more and faster sleep spindles. Importantly, SSM and INS patients were almost indistinguishable at the meso and micro levels. Accordingly, unsupervised classifiers can reliably categorize insomnia patients and GS (Cohen's κ = 0.87) but fail to tease apart SSM and INS patients when restricting classifiers to micro and meso features (κ=0.004). CONCLUSION: AI analyses of PSG recordings can help moving insomnia diagnosis beyond subjective complaints and shed light on the physiological substrate of insomnia.

Parental Separation and Parental Mental Health in Childhood and Risk of Insomnia in Adulthood among Patients with Tinnitus.

BACKGROUND: Many patients seeking help for tinnitus also suffer from insomnia. Adverse childhood experiences may affect the likelihood of insomnia in later life for such patients. PURPOSE: To explore whether parental separation and parental mental health during childhood are related to the severity of insomnia among patients with tinnitus and/or hyperacusis seen in an Audiology clinic. RESEARCH DESIGN: This was a retrospective cross-sectional study. STUDY SAMPLE: One hundred seventy-four consecutive patients who attended a tinnitus/hyperacusis clinic in the United Kingdom were included. DATA COLLECTION: Data were based on responses to questionnaires for people seeking help for tinnitus. RESULTS: Sixteen percent of patients (27/174) reported that during the first 18 years of life, their parents were separated or divorced and 41% (72/174) reported that their parent(s) suffered from a mental illness. The mean score for the insomnia severity index (ISI) was not significantly affected by parental separation or divorce. However, the mean ISI score was significantly worse for patients whose parents had a mental illness. A multinomial logistic regression model, adjusted for the presence of hyperacusis, hearing loss, age, and gender, indicated that for individuals experiencing tinnitus, a history of parental mental illness during their childhood increased the chance of severe insomnia by a factor of 3.4 (95% confidence interval: 1.1 to 10.8, p = 0.04). The risk of having severe insomnia was 3.8 times greater for patients with hyperacusis than for those without. CONCLUSIONS: Among patients seeking help for tinnitus/hyperacusis, poor parental mental health was associated with severe insomnia.

Multiple sleep dimensions and type 2 diabetes risk among women in the Sister Study: differences by race/ethnicity.

Objective: Poor sleep has been associated with type 2 diabetes. Since racial/ethnic minorities experience a disproportionately high prevalence of poor sleep and type 2 diabetes, we sought to determine the relationships between multiple sleep dimensions and incident type 2 diabetes and to investigate if these relationships vary by race/ethnicity. Research design and methods: Prospective data were analyzed from the Sister Study, which enrolled 50 884 women from 2003 to 2009. Participants self-reported sleep duration, sleep latency, night awakenings, and napping at baseline, and a physician's diagnosis of type 2 diabetes at follow-up. Multivariable-adjusted HRs and 95% CIs were estimated using Cox proportional hazards models. Results: Among the 39 071 eligible participants, 87% self-identified as white, 8% black and 5% Hispanic/Latina. The mean follow-up period was 8.5±2.1 years and 1785 type 2 diabetes cases were reported. The incidence rate per 1000 person-years was 5.4 for whites, 13.3 for blacks and 11.6 for Hispanics/Latinas. There was a positive but non-significant increased risk of type 2 diabetes among women who reported short sleep, latency >30 min and frequent night awakenings. In fully-adjusted models, frequent napping was associated with a 19% (HR 1.19, 95% CI 1.04 to 1.37) higher type 2 diabetes risk in the overall sample. Poor sleep among racial/ethnic minorities ranged from a 1.4-fold to a 3.2-fold higher type 2 diabetes risk than whites with recommended sleep. Conclusions: Frequent napping was associated with higher type 2 diabetes risk. Racial/ethnic minorities with poor sleep had a higher type 2 diabetes risk than whites with recommended sleep.

Effects of individual characteristics on insomnia severity trajectory among nurses: A prospective longitudinal study.

AIMS: To examine the longitudinal effects of individual characteristics on the change pattern of insomnia and the association of occupational stress with insomnia over time in newly graduated nurses. BACKGROUND: The association between individual factors and insomnia in nurses is inconclusive. Longitudinal research on insomnia in newly graduated nurses is limited. METHODS: This prospective longitudinal study included 200 participants generating 800 observations of insomnia severity during their first year of nursing. We employed growth mixture modelling for data analyses. Both time-varying covariate (occupational stress) and time-invariant covariates (nurses' characteristics) were entered into the model simultaneously. RESULTS: Nurses had a homogeneous insomnia trajectory during the whole year of survey. The educational level significantly predicted the growth rate of insomnia severity among nurses. Occupational stress at each time point was significantly associated with worse insomnia across time points (all p < .001). CONCLUSIONS: Nurses with a baccalaureate degree were more resilient to the development of severe insomnia. Additional studies have an opportunity to investigate the reason for the effects of the educational level on the pattern of insomnia. IMPLICATIONS FOR NURSING MANAGEMENT: Considering nurses' occupational stress and educational level would lead more effective management of stress and insomnia in newly graduated nurses.

Managing insomnia in older adults.

NPs frequently care for patients with complaints of insomnia in the hospital and community settings. Because older adults with insomnia present unique challenges for successful management, NPs should understand the latest assessment and treatment options.

Insomnia theory and assessment.

BACKGROUND: Insomnia is a common condition affecting individuals of various ages. It is diagnosed on the basis of a self-reported complaint of poor sleep quality concomitant with daytime disturbances. If left untreated, insomnia is associated with a number of adverse health outcomes. OBJECTIVE: The aim of this article is to review key diagnostic criteria, theories and assessment of insomnia. DISCUSSION: Insomnia may be precipitated by stressful events. Unhelpful strategies employed by the individual to remedy sleep can perpetuate insomnia symptoms even after the stressful event subsides. Insomnia is often undiagnosed and undertreated, which is concerning given that untreated insomnia associated with a number of negative health outcomes. Diagnosis and treatment planning can be facilitated using self-report measures.

Trastorno de insomnio. Consideraciones actuales / Insomnia disorder. Current considerations

RESUMEN El insomnio es el trastorno del sueño más frecuente en la población, se acompaña de un nivel significativo de malestar o deterioro de áreas importantes del funcionamiento humano. Es importante realizar un diagnóstico correcto de este desorden con el objetivo de instaurar un tratamiento adecuado que permita mejorar la calidad de vida de los pacientes que lo padecen. El objetivo de este artículo es ofrecer una revisión actualizada que contribuya al incremento y actualización de la información sobre este tema. Se realizó una revisión en artículos, principalmente de los últimos cinco años y se sistematizan los resultados para de esta forma contribuir a la superación de los profesionales.

ABSTRACT Insomnia is the most frequently sleep disorder in the population. It is linked to a significant discomfort and an impairment of important areas of the human functioning. The correct diagnosis of this disorder is important with the objective of prescribing an adequate treatment for improving the life quality of the patients suffering it. The aim of this article is offering an up-dated review contributing to increase and update the information on this topic. The authors carried out a review of articles published mainly during the last five years, and the results were systematized for contributing to the professionals´ upgrading.

Trastorno de insomnio. Consideraciones actuales / Insomnia disorder. Current considerations

RESUMEN El insomnio es el trastorno del sueño más frecuente en la población, se acompaña de un nivel significativo de malestar o deterioro de áreas importantes del funcionamiento humano. Es importante realizar un diagnóstico correcto de este desorden con el objetivo de instaurar un tratamiento adecuado que permita mejorar la calidad de vida de los pacientes que lo padecen. El objetivo de este artículo es ofrecer una revisión actualizada que contribuya al incremento y actualización de la información sobre este tema. Se realizó una revisión en artículos, principalmente de los últimos cinco años y se sistematizan los resultados para de esta forma contribuir a la superación de los profesionales (AU).

ABSTRACT Insomnia is the most frequently sleep disorder in the population. It is linked to a significant discomfort and an impairment of important areas of the human functioning. The correct diagnosis of this disorder is important with the objective of prescribing an adequate treatment for improving the life quality of the patients suffering it. The aim of this article is offering an up-dated review contributing to increase and update the information on this topic. The authors carried out a review of articles published mainly during the last five years, and the results were systematized for contributing to the professionals upgrading (AU).

A Simultaneous Cluster Analysis of Cognitive, Emotional, and Personality Factors and Insomnia and Sleep Quality Among Earthquake Victims.

OBJECTIVE: The current study compares the measures of sleep quality and intensity of insomnia based on the clustering analysis of variables including dysfunctional beliefs and attitudes about sleep, experiential avoidance, personality traits of neuroticism, and complications with emotion regulation among the individuals struck by an earthquake in Kermanshah Province. METHODS: This study is a cross-sectional study that was carried out among earthquake victims of Kermanshah Province (western Iran) in 2017. Data were gathered starting 10 days after the earthquake and lasted for 2 weeks; of 1,200 standard questionnaires distributed, 1,001 responses were received, and the analysis was performed using 999 participants. The data analysis was carried out using a cluster analysis (K-mean method). RESULTS: Two clusters were identified, and there is a significant difference between these two clusters in regard to all of the variables. The cluster with higher mean values for the selected variables shows a higher intensity of insomnia and a lower sleep quality. CONCLUSIONS: Considering the current results, it can be concluded that variables of dysfunctional attitudes and beliefs about sleep, experiential avoidance, the personality traits of neuroticism, and complications with emotion regulation are able to identify the clusters where there is a significant difference in regard to sleep quality and the intensity of insomnia. (Disaster Med Public Health Preparedness. 2019;13:745-752).

The paradox of paradoxical insomnia: A theoretical review towards a unifying evidence-based definition.

Paradoxical insomnia is one of the most intriguing yet challenging subtypes of insomnia. Despite being recognized for a long time by the international community, it is still unclear whether this entity really exists, which are its features and boundaries. Much of the debate is fuelled by the lack of a consensus on its precise definition. To help filling some of the existing gaps, a systematic review of the literature was conducted, through which 19 different quantitative definitions were obtained. These definitions were then applied to two distinct datasets. The first consisted of 200 chronic primary insomnia patients, diagnosed according to the DSM-IV-TR criteria. The second consisted of 200 age- and sex-matched healthy persons without insomnia. For each dataset, available data from the objective sleep parameters and their subjective estimation were imported and analysed in MATLAB. Depending on the definition used, the prevalence of paradoxical insomnia ranged from 8 to 66%, while agreement between different definitions ranged from -0.19 to 0.9 (using Cohen's kappa coefficient). Based on the results garnered, necessary features for a quantitative definition of paradoxical insomnia were identified. Several open questions remain, such as whether there is a minimum number of hours a patient should sleep to fulfill the criteria for a diagnosis of paradoxical insomnia, and whether sleep latency can be used in the definition along with total sleep time. We conclude by advocating continued study of paradoxical insomnia and sleep state misperception and by providing specific directions for future research. STATEMENT OF SIGNIFICANCE: The current understanding of paradoxical insomnia and, more broadly, of sleep state misperception, is greatly hampered by the lack of agreement on a quantitative and evidence-base measure of the discrepancy between subjective and objective sleep evaluation. The current study provides a critical analysis about the strength and the limitations of the available definitions, using both a data-driven and a theory-driven approach. The overarching goal is to motivate a rigorous discussion involving the main experts of the field, to build a consensus, and develop an evidence-based measure of sleep state misperception and/or of paradoxical insomnia.

Insomnia disorder subtypes derived from life history and traits of affect and personality.

BACKGROUND: Insomnia disorder is the second most prevalent mental disorder, and it is a primary risk factor for depression. Inconsistent clinical and biomarker findings in patients with insomnia disorder suggest that heterogeneity exists and that subtypes of this disease remain unrecognised. Previous top-down proposed subtypes in nosologies have had insufficient validity. In this large-scale study, we aimed to reveal robust subtypes of insomnia disorder by use of data-driven analyses on a multidimensional set of biologically based traits. METHODS: In this series of studies, we recruited participants from the Netherlands Sleep Registry, a database of volunteers aged 18 years or older, who we followed up online to survey traits, sleep, life events, and health history with 34 selected questionnaires of which participants completed at least one. We identified insomnia disorder subtypes by use of latent class analyses. We evaluated the value of our identified subtypes of insomnia disorder by use of a second, non-overlapping cohort who were recruited through a newsletter that was emailed to a new sample of Netherlands Sleep Registry participants, and by assessment of within-subject stability over several years of follow-up. We extensively tested the clinical validity of these subtypes for the development of sleep complaints, comorbidities (including depression), and response to benzodiazepines; in two subtypes of insomnia disorder, we also assessed the clinical relevance of these subtypes by use of an electroencephalogram biomarker and the effectiveness of cognitive behavioural therapy. To facilitate implementation, we subsequently constructed a concise subtype questionnaire and we validated this questionnaire in the second, non-overlapping cohort. FINDINGS: 4322 Netherlands Sleep Registry participants completed at least one of the selected questionnaires, a demographic questionnaire, and an assessment of their Insomnia Severity Index (ISI) between March 2, 2010, and Oct 28, 2016. 2224 (51%) participants had probable insomnia disorder, defined as an ISI score of at least 10, and 2098 (49%) participants with a lower ISI score served as a control group. With a latent class analysis of the questionnaire responses of 2224 participants, we identified five novel insomnia disorder subtypes: highly distressed, moderately distressed but reward sensitive (ie, with intact responses to pleasurable emotions), moderately distressed and reward insensitive, slightly distressed with high reactivity (to their environment and life events), and slightly distressed with low reactivity. In a second, non-overlapping replication sample of 251 new participants who were assessed between June 12, 2017, and Nov 26, 2017, five subtypes were also identified to be optimal. In both the development sample and replication sample, each participant was classified as having only one subtype with high posterior probability (0·91-1·00). In 215 of the original sample of 2224 participants with insomnia who were reassessed 4·8 (SD 1·6) years later (between April 13, 2017, and June 21, 2017), the probability of maintaining their original subtype was 0·87, indicating a high stability of the classification. We found differences between the identified subtypes in developmental trajectories, response to treatment, the presence of an electroencephalogram biomarker, and the risk of depression that was up to five times different between groups, which indicated a clinical relevance of these subtypes. INTERPRETATION: High-dimensional data-driven subtyping of people with insomnia has addressed an unmet need to reduce the heterogeneity of insomnia disorder. Subtyping facilitates identification of the underlying causes of insomnia, development of personalised treatments, and selection of patients with the highest risk of depression for inclusion in trials regarding prevention of depression. FUNDING: European Research Council and Netherlands Organization for Scientific Research.

The relationship between sleep disturbance and health status in patients with COPD.

Introduction: The detection of insomnia in patients with COPD is assumed to be significantly lower than the actual prevalence. In this study, we investigated the prevalence of insomnia and the relationship between insomnia and health status in patients with COPD using two fairly simple and straightforward questionnaires: COPD assessment test (CAT) and insomnia severity index (ISI). Patients and methods: A cross-sectional study was conducted using data from patients undergoing treatment for COPD at St Paul's Hospital, The Catholic University of Korea, between December 2015 and August 2016. Patients were classified into three groups according to the ISI score: a "clinical insomnia" group (ISI≥15), a "subthreshold insomnia" group (ISI 8-15), and a "non-insomnia" group (ISI<8). Clinical parameters including past medical history, pulmonary function tests, and questionnaire data were collected and analyzed. Results: A total of 192 patients were recruited, of which 25.0% were found to have clinical insomnia (ISI≥8). Insomnia severity was related to all CAT component items except for cough, and patients with higher CAT scores generally had more severe insomnia. Logistic regression analysis revealed that CAT score was significantly associated with insomnia in these patients (odds ratio, 1.23; 95% CI, 1.13-1.34; p<0.0001). CAT score was also a significant predictor of insomnia (area under receiver operating characteristic curve, 0.779; p<0.001). The optimal predictive cutoff value was a CAT score >14, giving a sensitivity and specificity of 66.7% and 71.5%, respectively. Conclusion: CAT score was closely related to insomnia severity in patients with COPD. The use of CAT scores to assess for the presence and severity of insomnia in these patients may allow for better detection and management and improve clinical practice.

Development of an Algorithm to Identify Patients with Physician-Documented Insomnia.

We developed an insomnia classification algorithm by interrogating an electronic medical records (EMR) database of 314,292 patients. The patients received care at Massachusetts General Hospital (MGH), Brigham and Women's Hospital (BWH), or both, between 1992 and 2010. Our algorithm combined structured variables (such as International Classification of Diseases 9th Revision [ICD-9] codes, prescriptions, laboratory observations) and unstructured variables (such as text mentions of sleep and psychiatric disorders in clinical narrative notes). The highest classification performance of our algorithm was achieved when it included a combination of structured variables (billing codes for insomnia, common psychiatric conditions, and joint disorders) and unstructured variables (sleep disorders and psychiatric disorders). Our algorithm had superior performance in identifying insomnia patients compared to billing codes alone (area under the receiver operating characteristic curve [AUROC] = 0.83 vs. 0.55 with 95% confidence intervals [CI] of 0.76-0.90 and 0.51-0.58, respectively). When applied to the 314,292-patient population, our algorithm classified 36,810 of the patients with insomnia, of which less than 17% had a billing code for insomnia. In conclusion, an insomnia classification algorithm that incorporates clinical notes is superior to one based solely on billing codes. Compared to traditional methods, our study demonstrates that a classification algorithm that incorporates physician notes can more accurately, comprehensively, and quickly identify large cohorts of insomnia patients.

Clinically Oriented Subtyping of Chronic Insomnia of Childhood.

OBJECTIVES: To identify different profiles of pediatric insomnia, based on the most frequent clinical presentations (nocturnal awakenings, difficulty in falling asleep, nocturnal restlessness, early morning awakenings). STUDY DESIGN: A structured parent interview was conducted in 338 children (mean age 21.29 months, SD 10.56) referred by pediatricians because of insomnia resistant to behavioral approaches and common drug treatments. The aim was to assess the characteristics of insomnia in children, together with family sleep-related history. A latent class analysis was run to identify profiles of insomnia. ANOVA and the χ2 test were used to examine differences between profiles. RESULTS: A 3-class model was built by latent class analysis: 17% (n = 58) of children constituted the first class, characterized by difficulties in falling asleep, with restlessness, nocturnal restlessness, and awakenings during the night; the second class, characterized by early morning awakenings, comprised 21% (n = 71) of children; 62% (n = 209) of children fell within the third class because of their high frequency of nocturnal awakenings and difficulties in falling asleep. The first class reported longer sleep latency and the presence of restless legs syndrome and anemia in the family history; depression and/or mood disorders were more frequent in class 2 and allergies and/or food intolerance were more frequent in class 3. CONCLUSIONS: Our study suggests the existence of 3 different phenotypes of insomnia in children, based on clinical, personal, and familial data. The identification of these different phenotypes might help to optimize the assessment and treatment of insomnia in young children.

Identifying the best sleep measure to screen clinical insomnia in a psychiatric population.

BACKGROUND: Insomnia symptoms are highly prevalent among patients with psychiatric disorders, and this mandates the need to identify the best self-administered sleep measure to screen for clinical insomnia among them. METHODS: A total of 400 psychiatric outpatients completed the Pittsburgh Sleep Quality Index, Insomnia Severity Index (ISI), Epworth Sleepiness Scale, Flinders Fatigue Scale, Functional Outcomes of Sleep Questionnaire, and Dysfunctional Beliefs and Attitudes about Sleep Scale in a cross-sectional study. The sensitivity, specificity, positive, and negative predictive values of these six sleep scales were assessed and compared in relation to both ICD-10 and DSM-5 insomnia disorder status established using the interviewer-administered Brief Insomnia Questionnaire. RESULTS: Receiver operator characteristic curves with the area under the curve (AUC) revealed the ISI to be the most accurate measure to discriminate cases and non-cases on both ICD-10 (AUC = 0.88, 95% CI = 0.84-0.92) and DSM-5 (AUC = 0.82, 95% CI = 0.78-0.86) criteria with "good" accuracy. The cut-off scores of ≥14 and ≥ 11 for the ISI provided optimal sensitivity and specificity for the detection of ICD-10 and DSM-5 insomnia, respectively. DISCUSSION: With the new calling from DSM-5 to treat sleep symptoms in the presence of a co-existing mental condition, early detection of psychiatric patients with clinically significantly insomnia using a simple but accurate self-report sleep measure becomes important. Our study suggests that the ISI could be used as a potential screening tool for comorbid insomnia disorder in patients with mental disorders.