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Measurement, Classification and Evaluation of Sleep Disturbance in Psoriasis: A Systematic Review.

ABSTRACT: BACKGROUND:Psoriasis is a long-term immune-mediated inflammatory disorder mainly, but not only, affecting skin, and is associated with significant medical and psychological morbidity. Evidence suggests that sleep is disrupted in psoriasis, however high quality empirical evidence is lacking. Given the importance of sleep for health, characterisation of sleep disruption in psoriasis is an important goal. We therefore conducted a systematic review of the sleep-psoriasis literature. METHODS:Searches were conducted in Pubmed, SCOPUS and Web of Science from inception to May 2016. Studies were compared against inclusion/exclusion criteria and underwent a quality evaluation. Given the heterogeneity of studies, we conducted a narrative synthesis of the findings. RESULTS:Searches revealed 32 studies which met our predetermined inclusion/exclusion criteria. Whilst 93.7% of studies reported sleep disruption in this population, ranging from 0.05% to 85.4%, many had important methodological shortcomings. Over half of all quantitative studies (54.8%; 17/31) relied on non-validated measures, contributing to heterogeneity in study findings. In those that employed valid measures, assessing sleep was often not the primary objective. We frequently found the absence of adequate sample size calculations and poor statistical reporting. CONCLUSION:This review showed that in psoriasis, reported sleep rates of sleep disturbance varied substantially. Most studies lacked a hypothesis driven research question and/or failed to use validated measures of sleep. We were unable to draw firm conclusions about the precise prevalence and nature of sleep disturbance within the psoriasis population. We offer suggestions to help advance understanding of sleep disturbance in psoriasis.

SUBMITTER: Henry AL

PROVIDER: S-EPMC4915697 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Measurement, Classification and Evaluation of Sleep Disturbance in Psoriasis: A Systematic Review.

Henry Alasdair L AL Kyle Simon D SD Bhandari Sahil S Chisholm Anna A Griffiths Christopher E M CE Bundy Christine C

PloS one 20160621 6

<h4>Background</h4>Psoriasis is a long-term immune-mediated inflammatory disorder mainly, but not only, affecting skin, and is associated with significant medical and psychological morbidity. Evidence suggests that sleep is disrupted in psoriasis, however high quality empirical evidence is lacking. Given the importance of sleep for health, characterisation of sleep disruption in psoriasis is an important goal. We therefore conducted a systematic review of the sleep-psoriasis literature.<h4>Metho ...[more]

PMID: 27327082

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Project description:RationaleSleep disturbance during intensive care unit (ICU) admission is common and severe. Sleep disturbance has been observed in survivors of critical illness even after transfer out of the ICU. Not only is sleep important to overall health and well being, but patients after critical illness are also in a physiologically vulnerable state. Understanding how sleep disturbance impacts recovery from critical illness after hospital discharge is therefore clinically meaningful.ObjectivesThis Systematic Review aimed to summarize studies that identify the prevalence of and risk factors for sleep disturbance after hospital discharge for critical illness survivors.Data sourcesPubMed (January 4, 2017), MEDLINE (January 4, 2017), and EMBASE (February 1, 2017).Data extractionDatabases were searched for studies of critically ill adult patients after hospital discharge, with sleep disturbance measured as a primary outcome by standardized questionnaire or objective measurement tools. From each relevant study, we extracted prevalence and severity of sleep disturbance at each time point, objective sleep parameters (such as total sleep time, sleep efficiency, and arousal index), and risk factors for sleep disturbance.SynthesisA total of 22 studies were identified, with assessment tools including subjective questionnaires, polysomnography, and actigraphy. Subjective questionnaire studies reveal a 50-66.7% (within 1 mo), 34-64.3% (>1-3 mo), 22-57% (>3-6 mo), and 10-61% (>6 mo) prevalence of abnormal sleep after hospital discharge after critical illness. Of the studies assessing multiple time points, four of five questionnaire studies and five of five polysomnography studies show improved aspects of sleep over time. Risk factors for poor sleep varied, but prehospital factors (chronic comorbidity, pre-existing sleep abnormality) and in-hospital factors (severity of acute illness, in-hospital sleep disturbance, pain medication use, and ICU acute stress symptoms) may play a role. Sleep disturbance was frequently associated with postdischarge psychological comorbidities and impaired quality of life.ConclusionsSleep disturbance is common in critically ill patients up to 12 months after hospital discharge. Both subjective and objective studies, however, suggest that sleep disturbance improves over time. More research is needed to understand and optimize sleep in recovery from critical illness.

Project description:BackgroundMobile health (mHealth) apps offer a scalable option for treating sleep disturbances at a population level. However, there is a lack of clarity about the development and evaluation of evidence-based mHealth apps.ObjectiveThe aim of this systematic review was to provide evidence for the design engineering and clinical implementation and evaluation of mHealth apps for sleep disturbance.MethodsA systematic search of studies published from the inception of databases through February 2020 was conducted using 5 databases (MEDLINE, Embase, Cochrane Library, PsycINFO, and CINAHL).ResultsA total of 6015 papers were identified using the search strategy. After screening, 15 papers were identified that examined the design engineering and clinical implementation and evaluation of 8 different mHealth apps for sleep disturbance. Most of these apps delivered cognitive behavioral therapy for insomnia (CBT-I, n=4) or modified CBT-I (n=2). Half of the apps (n=4) identified adopting user-centered design or multidisciplinary teams in their design approach. Only 3 papers described user and data privacy. End-user acceptability and engagement were the most frequently assessed implementation metrics. Only 1 app had available evidence assessing all 4 implementation metrics (ie, acceptability, engagement, usability, and adherence). Most apps were prototype versions (n=5), with few matured apps. A total of 6 apps had supporting papers that provided a quantitative evaluation of clinical outcomes, but only 1 app had a supporting, adequately powered randomized controlled trial.ConclusionsThis is the first systematic review to synthesize and examine evidence for the design engineering and clinical implementation and evaluation of mHealth apps for sleep disturbance. The minimal number of apps with published evidence for design engineering and clinical implementation and evaluation contrasts starkly with the number of commercial sleep apps available. Moreover, there appears to be no standardization and consistency in the use of best practice design approaches and implementation assessments, along with very few rigorous efficacy evaluations. To facilitate the development of successful and evidence-based apps for sleep disturbance, we developed a high-level framework to guide researchers and app developers in the end-to-end process of app development and evaluation.

Project description:BackgroundStudies have investigated the relationship between sleep disturbance and postoperative delirium (PD) but have controversial results. A systematic review and meta-analysis have a high level of evidence to comprehensively evaluate the effect of sleep disturbance on PD. Our study aims to provide available evidence regarding the effect of sleep disturbance on PD.MethodsPubMed, Embase, Cochrane Library, and Web of Science databases were searched for relevant studies from database inception to April 28, 2021. The eligible studies were identified according to the "PICOS" principles. Odds ratio (OR) was used to indicate the effect index, and 95% confidence interval (CI) was applied to express the effect size. The heterogeneity was tested. Subgroup analyses, meta-regression, and sensitivity analysis were also applied. Begg's test was used to test potential publication bias. The modified Newcastle-Ottawa Scale (NOS) was used to evaluate the literature quality.ResultsTotally, 18 articles including 2,714 patients were enrolled, with most of the included literature being of moderate to high quality. The results of systematic and meta-analysis suggested that sleep disturbance was associated with an increased risk of PD (OR: 3.731; 95% CI: 2.338 to 5.956). Subgroup analysis results demonstrated that sleep disturbance in patients aged <65 years (OR: 6.072; 95% CI: 3.054 to 12.071), aged ≥65 years (OR: 2.904; 95% CI: 1.487 to 5.671), and undergoing cardiac (OR: 3.390; 95% CI: 1.359 to 8.453), orthopedic (OR: 3.943; 95% CI: 2.219 to 7.008), or other surgeries (OR: 4.963; 95% CI: 2.156 to 11.420) increased the risk of PD (all P<0.005). Moreover, increased risk of PD was found for both preoperative (OR: 2.804; 95% CI: 1.517 to 5.184) and postoperative (OR: 6.302; 95% CI: 3.794 to 10.467) sleep disturbance (all P<0.005). No associations between obstructive sleep apnea (OSA; OR: 2.008; 95% CI: 0.753 to 5.354; P=0.164), insomnia (OR: 4.005; 95% CI: 0.636 to 25.203; P=0.139) and risk of PD were observed.ConclusionsOur study indicated the relationship between sleep disturbance and the risk of PD. Patients undergoing surgical treatments should pay attention to their sleep quality. However, more research is needed to confirm its relationship.

Project description:OBJECTIVES:Basic science and clinical studies suggest that sleep disturbance may be a modifiable risk factor for postoperative delirium. We aimed to assess the association between preoperative sleep disturbance and postoperative delirium. DATA SOURCES:We searched PubMed, Embase, CINAHL, Web of Science, and Cochrane from inception until May 31, 2017. STUDY SELECTION:We performed a systematic search of the literature for all studies that reported on sleep disruption and postoperative delirium excluding cross-sectional studies, case reports, and studies not reported in English language. DATA EXTRACTION:Two authors independently performed study selection and data extraction. We calculated pooled effects estimates with a random-effects model constructed in Stata and evaluated the risk of bias by formal testing (Stata Corp V.14, College Station, TX), DATA SYNTHESIS:: We included 12 studies, from 1,238 citations that met our inclusion criteria. The pooled odds ratio for the association between sleep disturbance and postoperative delirium was 5.24 (95% CI, 3.61-7.60; p < 0.001 and I = 0.0%; p = 0.76). The pooled risk ratio for the association between sleep disturbance and postoperative delirium in prospective studies (n = 6) was 2.90 (95% CI, 2.28-3.69; p < 0.001 and I = 0.0%; p = 0.89). The odds ratio associated with obstructive sleep apnea and unspecified types of sleep disorder were 4.75 (95% CI, 2.65-8.54; p < 0.001 and I = 0.0%; p = 0.85) and 5.60 (95% CI, 3.46-9.07; p < 0.001 and I = 0.0%; p = 0.41), respectively. We performed Begg's and Egger's tests for publication bias and confirmed a null result for publication bias (p = 0.371 and 0.103, respectively). CONCLUSIONS:Preexisting sleep disturbances are likely associated with postoperative delirium. Whether system-level initiatives targeting patients with preoperative sleep disturbance may help reduce the prevalence, morbidity, and healthcare costs associated with postoperative delirium remains to be determined.

Dataset Information

Measurement, Classification and Evaluation of Sleep Disturbance in Psoriasis: A Systematic Review.

Publications

Measurement, Classification and Evaluation of Sleep Disturbance in Psoriasis: A Systematic Review.

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