Trazodone has been widely prescribed for off-label use as a sleep aid. Identifying how trazodone impacts the performance of polysomnographic sleep architecture in insomnia disorder will provide additional data that can be used to guide clinical application. To assess the efficacy of trazodone in altering the polysomnographic sleep architecture in insomnia disorder so that sleep can be facilitated. PubMed, EMBASE, Web of Science, PsycINFO, Cochrane Library, Chinese Biomedical Literature Database (SinoMed), China National Knowledge Infrastructure, Wanfang Database, and the China Science and Technology Journal Database were searched for articles published between inception and June 2022. RCTs in patients with insomnia disorder applying trazodone in one arm of interventions at least 1 week, and reporting PSG parameters in the outcomes were eligible. RoB 2 was used to evaluate the risk of bias. The results of quality of evidence assessed by the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. When I2 < 50%, the fixed effects model was used. When I2 ≥ 50%, the random effects model was used. The mean differences (MD) or standardized mean differences (SMD) and odds ratios (OR) with 95% confidence intervals (CIs) were estimated. Eleven randomized controlled trials were selected and participants were 466. Risk of bias was low in 5 trials (45.5%), and was moderate in 6 (54.5%). Compared with the control group, trazodone significantly increased total sleep time (TST, min) (MD = 39.88, 95% CI 14.44–65.32, P = 0.002) and non-rapid eye movement stage 3 (N3, mixed min and %) (SMD = 1.61, 95% CI 0.69–2.53, P = 0.0006); trazodone significantly decreased latency to onset of persistent sleep (LPS, min) (MD = − 19.30, 95% CI − 37.28 to − 1.32, P = 0.04), non-rapid eye movement stage 1 (N1, mixed min and %) (SMD = − 0.62, 95% CI − 1.13 to − 0.12, P = 0.02), the number of awakenings (NAs, including both arousal times and arousal index) (SMD = − 0.67, 95% CI − 0.91 to − 0.42, P < 0.00001), and waking time after persistent sleep onset (WASO, mixed min and %) (SMD = − 0.42, 95% CI − 0.81, − 0.03, P = 0.04), with no obvious effect on non-rapid eye movement stage 2 (N2, mixed min and %) (SMD = − 0.15, 95% CI − 0.41 to 0.11, P = 0.25), rapid eye movement (REM, mixed min and %) (SMD = 0.22, 95% CI − 0.26 to 0.70, P = 0.37), rapid eye movement latency (REML, min) (MD = 2.33, 95% CI − 27.56 to 32.22, P = 0.88), or apnea–hypopnea index (AHI) (MD = − 4.21, 95% CI − 14.02 to 5.59, P = 0.40). Daytime drowsiness (OR = 2.53, 95% CI 1.14–5.64, P = 0.02) and decreased appetite (OR = 2.81, 95% CI 1.14–6.92, P = 0.02) occurred with greater frequency in the trazodone group as compared to the control group, and the differences were significant. The results of quality of evidence were very low in TST, N3 and AHI, were low in LPS, WASO and REM, and were moderate in N1 and NAs. The sources of heterogeneity in TST and N3 were not found out from sensitive and subgroup analysis and there was no high quality of evidence in outcomes by GRADE Assessment. Trials with combination of other therapy could be a problem in this meta-analysis as the possibility of interactions were found from sungroup analysis. Trazodone could improve sleep by changing the sleep architecture in insomnia disorder, but it should be used with caution due to the adverse events that may occur.PROSPERO registration register name: The effect of trazodone on polysomnography sleep architecture in patients with insomnia: a systematic review and meta-analysis protocol; Registration Number CRD42020215332.
OBJECTIVE: To investigate the effects of digital rehabilitation for improving adherence to therapeutic exercise in people with musculoskeletal conditions. DESIGN: Intervention systematic review with meta-analysis. LITERATURE SEARCH: Five databases were searched from their inception to March 2022. STUDY SELECTION CRITERIA: We included randomized controlled trials evaluating digital rehabilitation programs to improve adherence to therapeutic exercise for people with musculoskeletal conditions. DATA SYNTHESIS: We calculated standardized mean differences (SMDs) or mean differences (MDs) and 95% confidence intervals (CIs). Certainty of evidence was rated using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. Bias was assessed using the Cochrane risk of bias tool. RESULTS: Eleven trials were included in the meta-analysis (n = 1144 participants). At short-term follow-up, digital rehabilitation was no better than nondigital rehabilitation (3 trials, adherence rate of prescribed exercise test SMD 0.50, 95% CI: −0.13, 1.13; 2 trials, self-reported exercise adherence test MD 1.07, 95% CI: 0.58, 1.56; 2 trials, assessor-reported exercise adherence test SMD −0.10, 95% CI: −0.56, 0.36). At intermediate-term follow-up, digital rehabilitation improved exercise adherence compared with nondigital rehabilitation (6 trials, adherence rate of prescribed exercise test SMD 0.53, 95% CI: 0.35, 0.70; 2 trials, self-reported exercise adherence test MD 1.50, 95% CI: 0.76, 2.25; 2 trials, Exercise Adherence Rating Scale test MD 5.86, 95% CI: 0.08, 11.65). At long-term follow-up, there was no clinically important difference between digital and nondigital rehabilitation (2 trials, adherence rate of prescribed exercise test SMD 0.28, 95% CI: −0.14, 0.70; 1 trial, self-reported exercise adherence test MD 0.20, 95% CI: −0.91, 1.31). CONCLUSION: Digital rehabilitation was effective at improving therapeutic exercise adherence in musculoskeletal conditions at mid-term follow-up, but not at short- and long-term follow-up. J Orthop Sports Phys Ther 2022;52(11):726–739. Epub: 12 August 2022. doi:10.2519/jospt.2022.11384
Spontaneous spinal epidural haematoma (SSEH) is a rare disease that requires emergency decompression or haematoma evacuation to prevent permanent neurological deficits. Hemiparesis is an extremely rare presentation of SSEH, commonly misdiagnosed as stroke. With the help of case studies and references, this paper comprehensively discusses the effective methods to distinguish SSEH from stroke and provides theoretical support and ideas for rapid and accurate identification of SSEH. Herein, we report on the case of a 51-year-old man with SSEH who presented with acute hemiparesis and posterior neck pain. Cervical computed tomography (CT) revealed cervical degeneration. A carotid CT angiogram revealed a high-density mass in the C2-C5 right posterolateral epidural region. Cervical spine magnetic resonance imaging showed SSEH. The patient was conservatively treated and discharged following a full recovery. Rapid identification of SSEH continues to present a great challenge for neurologists. A soft tissue CT scan can be used to quickly and accurately identify SSEH; however, in the absence of cranial signs, Brown-Sequard syndrome, Lhermitte's sign and Horner syndrome should be used to differentiate SSEH from stroke.
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