Summary Obstructive sleep apnea (OSA) is a highly prevalent sleep disorder; however, it remains underdiagnosed and undertreated. Although screening tools such as the Berlin questionnaire (BQ), ...STOP-BANG questionnaire (SBQ), STOP questionnaire (STOP), and Epworth sleepiness scale (ESS) are widely used for OSA, the findings regarding their diagnostic accuracy are controversial. Therefore, this meta-analysis investigated and compared the summary sensitivity, specificity, and diagnostic odds ratio (DOR) among the BQ, SBQ, STOP, and ESS according to the severity of OSA. Electronic databases, namely the Embase, PubMed, PsycINFO, ProQuest dissertations and theses A&I databases, and China knowledge resource integrated database, were searched from their inception to July 15, 2016. We included studies examining the sensitivity and specificity of the BQ, SBQ, STOP, and ESS against the apnea–hypopnea index (AHI) or respiratory disturbance index (RDI). The revised quality assessment of diagnostic accuracy studies was used to evaluate the methodological quality of studies. A random-effects bivariate model was used to estimate the summary sensitivity, specificity, and DOR of the tools. We identified 108 studies including a total of 47 989 participants. The summary estimates were calculated for the BQ, SBQ, STOP, and ESS in detecting mild (AHI/RDI ≥ 5 events/h), moderate (AHI/RDI ≥ 15 events/h), and severe OSA (AHI/RDI ≥ 30 events/h). The performance levels of the BQ, SBQ, STOP, and ESS in detecting OSA of various severity levels are outlined as follows: for mild OSA, the pooled sensitivity levels were 76%, 88%, 87%, and 54%; pooled specificity levels were 59%, 42%, 42%, and 65%; and pooled DORs were 4.30, 5.13, 4.85, and 2.18, respectively. For moderate OSA, the pooled sensitivity levels were 77%, 90%, 89%, and 47%; pooled specificity levels were 44%, 36%, 32%, and 621%; and pooled DORs were 2.68, 5.05, 3.71, and 1.45, respectively. For severe OSA, the pooled sensitivity levels were 84%, 93%, 90%, and 58%; pooled specificity levels were 38%, 35%, 28%, and 60%; and pooled DORs were 3.10, 6.51, 3.37, and 2.10, respectively. Therefore, for mild, moderate, and severe OSA, the pooled sensitivity and DOR of the SBQ were significantly higher than those of other screening tools ( P < .05); however, the specificity of the SBQ was lower than that of the ESS ( P < .05). Moreover, age, sex, body mass index, study sample size, study populations, presence of comorbidities, PSG or portable monitoring performance, and risk of bias in the domains of the index test and reference standard were significant moderators of sensitivity and specificity ( P < .05). Compared with the BQ, STOP, and ESS, the SBQ is a more accurate tool for detecting mild, moderate, and severe OSA. Sleep specialists should use the SBQ to conduct patient interviews for the early diagnosis of OSA in clinical settings, particularly in resource-poor countries and sleep clinics where PSG is unavailable.
The Clinical Dementia Rating (CDR) Scale comprising global score (CDR-GS) and sum of boxes scores (CDR-SB) is commonly used in staging cognitive impairment; however, its diagnostic accuracy is not ...well clarified. The meta-analysis aimed to investigate the diagnostic accuracy of the CDR for mild cognitive impairment (MCI) and dementia in older populations.
Studies examining the diagnostic accuracy of the CDR for MCI or dementia against reference standards were included from seven electronic databases. The bivariate analysis with a random-effects model was adopted to calculate the pooled sensitivity and specificity of the CDR for MCI and dementia.
Fifteen studies investigating the diagnostic accuracy of the CDR-GS (n = 13) or CDR-SB (n = 5) for MCI or dementia were included. The pooled sensitivity and specificity of the CDR-GS for MCI were 93% and 97%, respectively. With respect to dementia, the CDR-GS had superior pooled specificity compared to the CDR-SB (99% vs. 94%), while similar sensitivities were found between the CDR-GS and CDR-SB (both 87%). Significant moderators of an old age, a high educational level, a high prevalence of MCI or dementia, being in a developing country, and a lack of informants' observations may affect the estimation of the sensitivity or specificity of the CDR.
Evidence supports the CDR being useful for detecting MCI and dementia; applying the CDR for staging cognitive impairment in at risk populations should be considered. Furthermore, including objective observations from relevant informants or proxies to increase the accuracy of the CDR for dementia is suggested.
Aims
To compare the efficacy of digitally assisted interventions on the glycated haemoglobin (HbA1c) levels of patients with type 2 diabetes by performing a systematic review, network meta‐analysis ...and component network meta‐analysis.
Methods
Six databases were searched to identify eligible articles from the inception of each database until 17 March 2023. We included randomized controlled trials evaluating HbA1c levels. Data were pooled with a random‐effects model under a frequentist framework. The evidence certainty was assessed using Confidence in Network MetaAnalysis (CINeMA). The PROSPERO registration number was CRD42021283815.
Results
In total, 75 trials involving 9764 participants were included. Results from standard network meta‐analyses of 17 interventions revealed that compared with standard care, a mobile application (MA) combined with a professional education programme and peer support education (PSE; −1.98, 95% confidence interval = −2.90 to −1.06, CINeMA score: moderate to high) significantly reduced HbA1c levels. The component analysis found that PSE (−1.50, −2.36 to −0.64), SMS (−0.33, −0.56 to −0.11), MA (−0.30, −0.56 to −0.04) and telephone calls (−0.30, −0.53 to −0.06) most effectively reduced HbA1c levels among patients with type 2 diabetes.
Conclusions
SMS and MA are the optimal digitally assisted interventions for reducing HbA1c levels. Educators can integrate digitally assisted interventions complemented by educational programmes, particularly MA combined with professional education programme and PSE, into daily care to control HbA1c. The limitations of included trials include a lack of information on allocation concealment and blinding and the fact that long‐term follow‐up effects were not investigated.
Virtual reality (VR) technology constitutes a promising rehabilitation strategy, but its effect on frailty in older adults remains inconclusive. This study examined the effects of interactive VR ...training programs on lower-limb muscle strength, walking speed, balance, and fall risks in older adults with frailty.
Various electronic databases comprising PubMed, the Cumulative Index to Nursing and Allied Health Literature, the Cochrane Library, Embase, the Chinese Electronic Periodical Service, the Chinese National Knowledge Infrastructure, and gray literature were searched from their inception through December 31, 2022 for relevant studies. Randomized controlled trials that examined the effects of interactive VR training programs on lower-limb muscle strength, balance, walking speed, and fall risks as measured by validated scales or methods. in older adults aged 65 years and older with frailty were included. A random-effects model was employed to examine the overall effect size, and the trim-and-fill method was adopted to examine publication bias.
For those studies that defined frailty using fall risks, substantial evidence demonstrated that interactive VR training interventions increased lower-limb muscle strength (Hedges' g = 0.35, p = 0.015), walking speed (Hedges' g = 0.29, p = 0.003), balance (Hedges' g = 0.62, p = 0.011), and fall risks (Hedges' g = -0.61, p < 0.001). Studies that defined frailty in accordance with the Fried frailty phenotype criteria indicated that interactive VR training interventions only increased walking speed (Hedges' g = 0.28, p = 0.023) and balance (Hedges' g = 0.27, p = 0.049).
Interactive VR training programs may benefit older adults with frailty with respect to walking speed and balance. More studies with good study quality are required to validate the effects of interactive VR exercise training on these frailty-related parameters in older adults.
Non-contact sensors are gaining popularity in clinical settings to monitor the vital parameters of patients. In this study, we used a non-contact sensor device to monitor vital parameters like the ...heart rate, respiration rate, and heart rate variability of hemodialysis (HD) patients for a period of 23 weeks during their HD sessions. During these 23 weeks, a total number of 3237 HD sessions were observed. Out of 109 patients enrolled in the study, 78 patients reported clinical events such as muscle spasms, inpatient stays, emergency visits or even death during the study period. We analyzed the sensor data of these two groups of patients, namely an event and no-event group. We found a statistically significant difference in the heart rates, respiration rates, and some heart rate variability parameters among the two groups of patients when their means were compared using an independent sample t-test. We further developed a supervised machine-learning-based prediction model to predict event or no-event based on the sensor data and demographic information. A mean area under curve (ROC AUC) of 90.16% with 96.21% mean precision, and 88.47% mean recall was achieved. Our findings point towards the novel use of non-contact sensors in clinical settings to monitor the vital parameters of patients and the further development of early warning solutions using artificial intelligence (AI) for the prediction of clinical events. These models could assist healthcare professionals in taking decisions and designing better care plans for patients by early detecting changes to vital parameters.
To systematically review and meta-analyze the associations between sleep disturbances and suicidal ideation, plans, and attempts in adolescents and explore potential moderators of these associations.
...Embase, PubMed, ProQuest, and the China Knowledge Resource Integrated Database were searched from their inception dates to October 19, 2018. We selected cross-sectional, prospective, or retrospective studies without time or language restrictions.
Nine cross-sectional studies, four prospective studies, and one retrospective report that, respectively, involved 37 536, 9295, and 80 adolescents were included in the meta-analysis. Cross-sectional analyses revealed that adolescents with sleep disturbances were at higher risks of suicidal ideation, plans, and attempts (pooled odds ratios ORs = 2.35, 1.58, and 1.92) than those without sleep disturbances. Prospective reports indicated that sleep disturbances in adolescents significantly predicted the risk of suicidal ideation but not suicide attempts (pooled ORs = 1.79 and 1.98, 95% confidence intervals = 1.36-2.36 and 0.62-6.29, respectively). The retrospective study did not support the association between sleep disturbances and suicide attempts. Depression did not moderate the associations between sleep disturbances and suicidal ideation or attempts in adolescents. Adolescents with insomnia complaints had a higher risk of suicidal ideation than those with other sleep complaints. Age, the female percentage, and reliable sleep measures were significant moderators (all p < .05).
Sleep disturbances, particularly insomnia, should be considered an influencing factor when developing preventive strategies against adolescent suicidal ideation. Additional prospective studies are warranted to establish causality of sleep disturbances in youth suicide plans and attempts.
Purpose
This meta‐analysis was conducted to determine the prevalence and risk factors of fatigue in type 1 and type 2 diabetes mellitus (DM).
Methods
Observational studies reporting the prevalence ...and risk factors of fatigue in type 1 or 2 DM were systematically searched for in PubMed, Embase, CINAHL Plus, Cochrane Trial, and ProQuest Dissertation and Theses databases. Data were extracted by two independent reviewers. A random‐effect model was used for data analysis.
Findings
We included 19 studies involving 7131 patients with type 1 DM and 32 studies involving 34,994 patients with type 2 DM in the study. The pooled prevalence of fatigue in type 1 and type 2 DM was 44% and 50%, respectively. The Asia–Pacific region (e.g., Japan and Australia), South America, and Africa lacked reports regarding fatigue prevalence in type 1 DM, and North Asia and Southeast Asia lacked reports of fatigue prevalence in type 2 DM. Depression and physical activity were the only two variables significantly correlated with fatigue in both type 1 and type 2 DM (all p < 0.05).
Conclusions
Approximately half of the patients with type 1 or type 2 DM experienced fatigue, with the prevalence of 44% and 50%, respectively. Our findings regarding its risk factors can provide an evidence‐based approach for managing fatigue in DM patients.
Clinical relevance
This meta‐analysis emphasizes the importance of fatigue management in patients with type 1 and type 2 DM. Most significantly, our results on risk factors related to fatigue in diabetes can contribute to the development of evidence‐based strategies for managing fatigue in individuals with DM.
Abstract Background Insomnia is a highly prevalent health complaint in the modern societies; however, insomnia remains under-diagnosed and under-treated. Although screening tools, including the ...Insomnia Severity Index (ISI), Athens Insomnia Scale (AIS), and Pittsburg Sleep Quality Index (PSQI), are widely used for assessing the risk of insomnia, the diagnostic properties have yet to be summarized in a systematic manner. Objectives To estimate and to compare the diagnostic accuracy of the ISI, AIS, and PSQI for insomnia screening. Data sources We systematically searched EMBASE, PubMed, PsycINFO, CINAHL and Chinese Electronic Periodic Services for data from their inception to May 20, 2015. Data selection Original articles that had assessed the sensitivity and specificity of the ISI, AIS, or PSQI against a reference standard in adult participants (age > 18) were included. Results A total of 19 studies comprising 4693 participants were included. The pooled sensitivity for the ISI, AIS, and PSQI was 88% (95% confidence interval CI = 0.79 to 0.93), 91% (0.87 to 0.93), and 94
% (0.86 to 0.98), respectively. The pooled specificity was 85% (0.68 to 0.94), 87% (0.68 to 0.95), and 76% (0.64 to 0.85); and the pooled DORs was 41.93 (8.77 to 200.33), 67.7 (23.4 to 196.1), and 53 (15.5 to 186.2), respectively. The summary estimates did not differ significantly among the ISI, AIS and PSQI (all P > 0
.05). Conclusions The current evidence indicates that the ISI, AIS, and PSQI yield comparable diagnostic properties for insomnia screening.
Delirium is a critical and highly prevalent problem among critically ill patients. The Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) and the Intensive Care Delirium Screening ...Checklist (ICDSC) are the most recommended assessment tools for detecting intensive care unit (ICU) delirium.
To synthesize the current evidence and compared the diagnostic accuracy of the two tools in the detection of delirium in adults in ICUs.
Systematic review and meta-analysis.
A comprehensive search of the following electronic databases was performed using PubMed, Embase, CINAHL and ProQuest Dissertations and Theses A&I. The date range searched was from database inception to April 26, 2019.
Two researchers independently identified articles, systematically abstracted data and evaluated the sensitivity and specificity of the CAM-ICU or the ICDSC against standard references. Bivariate diagnostic statistical analysis with a random-effects model was performed to summarize the pooled sensitivity and specificity of the two tools.
In total, 29 CAM-ICU and 12 ICDSC studies were identified. The pooled sensitivity was 0.84 and 0.83 and pooled specificity was 0.95 and 0.87 for the CAM-ICU and the ICDSC, respectively. The CAM-ICU had higher summary specificity than the ICDSC did (p = 0.04). The percentage of hypoactive delirium, ICU type, use of mechanical ventilation, number of participants, and female percentage moderated the accuracy of the tools. Most of the domains of patient selection, index test, reference standards, and flow and timing were rated as having a low or unclear risk of bias.
Although both the CAM-ICU and the ICDSC are accurate assessment tools for screening delirium in critically ill patients, the CAM-ICU is superior in ruling out patients without ICU delirium and detecting delirium in patients in the medical ICU and those receiving mechanical ventilation. Further investigations are warranted to validate our findings. The study protocol is registered at PROSPERO (CRD42020133544).
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