Importance Large language models (LLMs) may facilitate the labor-intensive process of systematic reviews. However, the exact methods and reliability remain uncertain. Objective To explore the feasibility and reliability of using LLMs to assess risk of bias (ROB) in randomized clinical trials (RCTs). Design, Setting, and Participants A survey study was conducted between August 10, 2023, and October 30, 2023. Thirty RCTs were selected from published systematic reviews. Main Outcomes and Measures A structured prompt was developed to guide ChatGPT (LLM 1) and Claude (LLM 2) in assessing the ROB in these RCTs using a modified version of the Cochrane ROB tool developed by the CLARITY group at McMaster University. Each RCT was assessed twice by both models, and the results were documented. The results were compared with an assessment by 3 experts, which was considered a criterion standard. Correct assessment rates, sensitivity, specificity, and F1 scores were calculated to reflect accuracy, both overall and for each domain of the Cochrane ROB tool; consistent assessment rates and Cohen kappa were calculated to gauge consistency; and assessment time was calculated to measure efficiency. Performance between the 2 models was compared using risk differences. Results Both models demonstrated high correct assessment rates. LLM 1 reached a mean correct assessment rate of 84.5% (95% CI, 81.5%-87.3%), and LLM 2 reached a significantly higher rate of 89.5% (95% CI, 87.0%-91.8%). The risk difference between the 2 models was 0.05 (95% CI, 0.01-0.09). In most domains, domain-specific correct rates were around 80% to 90%; however, sensitivity below 0.80 was observed in domains 1 (random sequence generation), 2 (allocation concealment), and 6 (other concerns). Domains 4 (missing outcome data), 5 (selective outcome reporting), and 6 had F1 scores below 0.50. The consistent rates between the 2 assessments were 84.0% for LLM 1 and 87.3% for LLM 2. LLM 1's kappa exceeded 0.80 in 7 and LLM 2's in 8 domains. The mean (SD) time needed for assessment was 77 (16) seconds for LLM 1 and 53 (12) seconds for LLM 2. Conclusions In this survey study of applying LLMs for ROB assessment, LLM 1 and LLM 2 demonstrated substantial accuracy and consistency in evaluating RCTs, suggesting their potential as supportive tools in systematic review processes.

BackgroundPharmacological treatment is common in practice and widely used for the management of insomnia. However, evidence comparing the relative effectiveness, safety, and certainty of evidence among drug classes and individual drugs for insomnia are still lacking. This study aimed to determine the relative effectiveness, safety, and tolerability of drugs for insomnia.MethodsIn this systematic review and network meta-analysis we systematically searched PubMed, Embase, Cochrane Central Register of Controlled Trials, PsycINFO, and ClinicalTrials.gov, from inception to January 10, 2022 to identify randomized controlled trials that compared insomnia drugs with placebo or an active comparator in adults with insomnia. We conducted random-effects frequentist network meta-analyses to summarize the evidence, and used the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach to assess the certainty, categorize interventionsand present the findings.ResultsA total of 148 articles met our eligibility criteria; these included 153 trials which enrolled 46,412 participants and assessed 36 individual drugs from eight drug classes. Compared with placebo, both subjectively and objectively measured total sleep time were significantly improved with non-benzodiazepine (subjective: mean difference [MD] 25.07, 95% confidence interval [CI] 15.49-34.64, low certainty; objective: MD 22.34, 95% CI 7.64-37.05, high certainty), antidepressants (subjective: MD 54.40, 95% CI 34.96-75.83, low certainty; objective: MD 35.64, 95% CI 13.05-58.24, high certainty), and orexin receptor antagonists (subjective: MD 21.62, 95% CI 0.84-42.40, high certainty; objective: MD 31.81, 95% CI 2.66-60.95, high certainty); of which doxepin, almorexant, suvorexant, and lemborexant were among the relatively effective drugs with relatively good tolerability and lower risks of any adverse events (AEs). Both subjectively and objectively measured sleep onset latency were significantly shortened with non-benzodiazepines (subjective: MD - 10.12, 95% CI - 13.84 to - 6.40, moderate certainty; objective: MD - 12.11, 95% CI - 19.31 to - 4.90, moderate certainty) and melatonin receptor agonists (subjective: MD - 7.73, 95% CI - 15.21 to - 0.26, high certainty; objective: MD - 7.04, 95% CI - 12.12 to - 1.95, moderate certainty); in particular, zopiclone was among the most effective drugs with a lower risk of any AEs but worse tolerability. Non-benzodiazepines could significantly decrease both subjective and objective measured wake time after sleep onset (subjective: MD - 16.67, 95% CI - 21.79 to - 11.56, moderate certainty; objective: MD - 13.92, 95% CI - 22.71 to - 5.14, moderate certainty).ConclusionsNon-benzodiazepines probably improve total sleep time, sleep onset latency, and wake time after sleep onset. Other insomnia drug classes and individual drugs also showed potential benefits in improving insomnia symptoms. However, the choice of insomnia drugs should be based on the phenotype of insomnia presented, as well as each drug's safety and tolerability.Protocol registration PROSPERO (CRD42019138790).

Objective: The aim of this study was to examine the most effective delivery format of cognitive behavioral therapy for insomnia (CBT-I) on insomnia in cancer patients. Methods: We searched five databases up to February 2021 for randomized clinical trials that compared CBT-I with inactive or active controls for insomnia in cancer patients. Outcomes were insomnia severity, sleep efficiency, sleep onset latency (SOL), wake after sleep onset (WASO), and total sleep time (TST). Pairwise meta-analyses and frequentist network meta-analyses with the random-effects model were applied for data analyses. Results: Sixteen unique trials including 1523 participants met inclusion criteria. Compared with inactive control, CBT-I could significantly reduce insomnia severity (mean differences [MD] = -4.98 points, 95% confidence interval [CI]: -5.82 to -4.14), SOL (MD = -12.29 min, 95%CI: -16.48 to -8.09), and WASO (MD = -16.58 min, 95%CI: -22.00 to -11.15), while increasing sleep efficiency (MD = 7.62%, 95%CI: 5.82% to 9.41%) at postintervention. Compared with active control, CBT-I could significantly reduce insomnia severity (MD = -2.75 points, 95%CI: -4.28 to -1.21), SOL (MD = -13.56 min, 95%CI: -18.93 to -8.18), and WASO (MD = -6.99 min, 95%CI: -11.65 to -2.32) at postintervention. These effects diminished in short-term follow-up and almost disappeared in long-term follow-up. Most of the results were rated as "moderate" to "low" certainty of evidence. Network meta-analysis showed that group CBT-I had an increase in sleep efficiency of 10.61%, an increase in TST of 21.98 min, a reduction in SOL of 14.65 min, and a reduction in WASO of 24.30 min, compared with inactive control at postintervention, with effects sustained at short-term follow-up. Conclusions: CBT-I is effective for the management of insomnia in cancer patients postintervention, with diminished effects in short-term follow-up. Group CBT-I is the preferred choice based on postintervention and short-term effects. The low quality of evidence and limited sample size demonstrate the need for robust evidence from high-quality, large-scale trials providing long-term follow-up data.

This review compared the efficacy and acceptability of different delivery formats for cognitive behavioral therapy for insomnia (CBT-I) in insomnia. We searched five databases for randomized clinical trials that compared one CBT-I delivery format against another format or control conditions for insomnia in adults. We used pairwise meta-analyses and frequentist network meta-analyses with the random-effects model to synthesize data. A total of 61 unique trials including 11,571 participants compared six CBT-I delivery formats with four control conditions. At post-intervention, with low to high certainty evidence, individual, group, guided self-help, digital assisted, and unguided self-help CBT-I could significantly increase sleep efficiency and total sleep time (TST) and reduce sleep onset latency (SOL), wake after sleep onset (WASO), and insomnia severity compared with treatment as usual (MD range for sleep efficiency: 7.81%-12.45%; MD range for TST: 16.14-33.96 min; MD range for SOL:-22.42 to-13.81 min; MD range for WASO:-40.84 to-19.48 min; MD range for insomnia severity:-6.40 to-3.93) and waitlist (MD range for sleep efficiency: 7.68%-12.32%; MD range for TST: 12.67-30.49 min; MD range for SOL:-19.07 to-10.46 min; MD range for WASO:-47.10 to-19.15 min; MD range for insomnia severity:-7.59 to-5.07). The effects of different CBT-I formats per-sisted at short-term follow-up (4 wk-6 mo). Individual, group, and digital assisted CBT-I delivery formats would be the more appropriate choices for insomnia in adults, based on post-intervention and short-term effects. Further trials are needed to investigate the long-term effects of different CBT-I formats. (c) 2022 Elsevier Ltd. All rights reserved.

Background: Acupuncture has been widely practiced for primary insomnia (PI). However, the relative benefit and harm among acupuncture therapies remain uncertain.Objectives: To compare and evaluate the effect differences of multiple acupuncture therapies for patients with PI.Methods: Systematic literature search for randomized controlled trials (RCTs). Pairs of reviewers independently conducted literature screening, data extraction, and risk of bias assessment. Meta-analysis was conducted using R and Stata software. The Grading of Recommendations Assessment, Development, and Evaluation system (GRADE) was used to assess certainty of evidence and interpret results.Results: Fifty-seven RCTs with 4678 patients were included. Compared with usual treatment, multiple acupuncture therapies showed a better effect for Pittsburgh sleep quality index score. And acupoints catgut embedding (ACE) was proved to be the most effective with a moderate certainty of evidence; auricular acupressure or auricular acupuncture plus manual acupuncture (AP + MA), electroacupuncture plus acupoint application (EA + APA), and intradermal needle (IN) might be also the most effective with low certainty of evidence. ACE, ACE + MA, AP + MA, EA, EA + APA, HPN, MA and PBN + MA showed significantly improvement in effective rate when compared with usual treatment. Insufficient evidence reported on Epworth Sleepiness Scale, Athens Insomnia Scale, and recurrence rate. The most common slight adverse events mainly included hematoma, pain, headache, and bleeding.Conclusions: With moderate to low certainty of evidence, multiple acupuncture therapies showed impressive insomnia improvement, especially ACE, AP + MA, and EA + APA. Differences between therapies were small or insignificant and based-on low or very low certainty of evidence.(c) 2022 Elsevier B.V. All rights reserved.

Background: Sjogren's syndrome (SS) is a chronic autoimmune rheumatic disease with an incidence of 0.03 to 0.3%. In recent years, there are an increasing number of randomized controlled trials of traditional Chinese medicine (TCM) for SS. However, there are generally some problems in these published clinical trials: lack of reporting primary or long-term outcomes and the heterogeneous in different clinical trials' outcome. Our study aims to determine the priority outcomes and standard TCM syndromes for all stakeholders and reach agreement on the COS and syndromes to be measured and reported in all future TCM trials in patients with SS. Methods and analysis: A phase-wise refinement approach will be used, consisting of three phases, yet complementary, sub-work phases, whereby each phase will inform the next coming phases. The following are the three phases: (I-a) identifying of a long initial list of outcomes through systematic literature review and semi-structured qualitative interviews and (I-b) identifying an initial list of TCM syndromes through (1) systematic literature review, (2) referencing ancient Chinese medical books, and (3) retrospective studies of medical records; (II) prioritization of outcomes using Delphi survey with different stakeholders, such as health professionals and patients; and (III) through consensus meetings with patients and professionals to agree on the final COS and TCM syndromes. Discussion: We summarized the actions of COS into three points: direct action, indirect action, and final action. After the final COSs is completed, we will publish this research in a journal to promote communication.

Background Traditional Chinese medicine (TCM) has been widely accepted and applied worldwide, and many publications related to Angelica sinensis (Oliv.) Diels (AS, Chinese name is "Danggui") have been published. However, to date, there has not been a scientometric study to systematically analyze the intellectual landscape and emerging research trends regarding AS. Therefore, we performed a scientometric study to address this gap. Methods Publications related to AS published from 2009 to 2018 were identified and selected from the Web of Science (WoS) Core Collection on May 30, 2019 using relevant keywords. HistCite, CiteSpace, and Excel 2016 software tools were used to conduct this scientometric study. Results Seven hundred and sixty-seven articles (including 717 primary articles and 60 review articles) and their cited references were included and analyzed. The majority of publications (N = 565, 73.7%) were published in mainland China, with Nanjing University of Chinese Medicine contributing the most publications (N = 42, 5.5%). The first core journal was Journal of Ethnopharmacology (N = 58, 7.6%; impact factor = 3.414). The identification and assessment of active components (like ferulic acid) of AS and their pharmacological actions (such as immunomodulatory effects) are the current research foci for AS research. Conclusion The present scientometric study provides an overview of the development of AS research over the previous decade using quantitative and qualitative methods, and this overview can provide references for researchers focusing on AS.

EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE

Electronic waste (e-waste) has been widely studied by scholars all over the world, but the research topics and development trends in this field are still unclear. This study aimed to explore the status quo, hot topics, and future prospects in the field of e-waste. Data of publications were downloaded from the Web of Science Core Collection. We used CiteSpace V, Histcite, and VOSviewer to analyze literature information. A total of 2800 papers in e-waste research were identified, and the number of publications increased rapidly after 2004. Six thousand five hundred seventy-three authors participated in the e-waste research, but 70.01% of the authors published only 1 article. The most productive country in this field was China (1146 publications), and the most productive institution was the Chinese Academy of Sciences (370 publications). The Waste Management (225 publications) was the most productive journal, and Environment Science & Technology (9704 co-citations) was the most co-cited journal. The main hot topics in e-waste field were management and recycling of e-waste in developing countries, health risk assessment after exposure to organic pollutants, degradation and recovery of waste metal materials, and impact of heavy metals on children's health. The frontier topic was degradation.