Introduction: Despite common, serious, costly, and often fatal conditions affecting up to 50 % of older patients, delirium is often unrecognized and overlooked. We examine the accuracy of the 4AT for detecting older patients with delirium.Methods: We performed a systematic search of PubMed, Web of Science, PsycINFO, and EMBASE databases from inception to April 2020 and updated to January 2022. Four independently reviewers extracted study data and assessed the methodological quality using the revised quality assessment of diagnostic accuracy studies tool (QUADAS-2). Pooled estimates of sensitivity and specificity were generated using a bivariate random effects model. All statistical analyses were performed with STATA version 15.1 and Meta-DiSc version 1.4 software. Results: Eleven studies with 2789 participants were included. The pooled sensitivity and specificity were 0.87 (95 % CI: 0.81-0.91) and 0.87 (95 % CI: 0.79-0.92), respectively, and the positive and negative likelihood ratios were 6.66 (95 % CI: 4.12-10.74) and 0.15 (95 % CI: 0.10-0.23), respectively. Deeks' test indicated no significant publication bias (t = 0.83, P = 0.43). Univariable meta-regression showed that patient selection and flow and timing significantly influenced the pooled sensitivity (P < 0.05), settings significantly influenced the pooled specificity (P < 0.05).Conclusion: Our meta-analysis demonstrates that 4AT is a sensitive and specific screening tool for delirium in older patients. Its brevity and simplicity support its use in routine clinical practice, particularly in time-poor settings. Clinicians should come to a conclusion based largely on the 4AT findings in conjunction with clinical judgment.

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.

Sugar-sweetened beverages (SSBs), artificially sweetened beverages (ASBs), and 100% fruit juices are frequently consumed and have been documented that they could lead to serious disease burden. However, inconsistent evidence on the association between SSBs, ASBs, and 100% fruit juices consumption and mortality have been presented. PubMed, Embase, Web of Science, Cochrane Central Register of Controlled Trials, and PsycINFO were systematically searched. We conducted a random-effects meta-analysis and dose-response meta-analysis to assess the association and calculated the pooled hazard ratio with 95% confidence interval. And we evaluated the certainty of evidence using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Thirteen studies with 1,539,127 participants proved eligible. An SSB-consumption increase per 250 mL/day was associated with a 4% greater risk of all-cause mortality (5 more per 1000 persons; low certainty) and 8% greater risk of cardiovascular disease mortality (3 more per 1000 persons; low certainty). ASB-consumption increase per 250 mL/day demonstrated a 4% greater risk of all-cause mortality (5 more per 1000 persons; low certainty) and 4% greater risk of cardiovascular disease mortality (2 more per 1000 persons; low certainty). The association of SSBs and ASBs with cancer mortality was not significant, with a very low certainty of evidence. There was evidence of a linear dose-response association between SSB intake and cancer mortality, as well as between ASB intake and all-cause mortality and cancer mortality. We observed a non-linear dose-response association between ASB intake and CVD mortality and SSB intake and all-cause and CVD mortality. Low certainty of evidence demonstrated that per 250 mL/day consumption increase in SSBs and ASBs had a small impact on all-cause and cardiovascular disease mortality but not on cancer mortality. The association of 100% fruit juice consumption with all-cause and cardiovascular disease mortality was uncertain.

Background: The coronavirus disease 2019 (COVID-19) pandemic continues to grow worldwide, and systematic reviews (SRs)/meta-analyses (MAs) on COVID-19 can efficiently guide evidence-based clinical practice. However, SRs/MAs with weaknesses can mislead clinical practice and pose harm to patients, and too many useless SRs/MAs could pose confusion and waste sources. A "living" overview of SRs/MAs aims to provide an open, accessible and frequently updated resource summarizing the highest-level evidence of COVID-19, that can help evidence-users to quickly identify trusted evidence to guide the practice. This study aims to systematically give an overview SRs/MAs of COVID-19, assess their quality, and identify the best synthesis of evidence. Methods: Databases including Medline, EMBASE, Web of Science, China National Knowledge Infrastructure (CNKI), China Biology Medicine (CBM) and WanFang were systematically searched on May 1, 2020 using relevant terms for identify SRs/MAs related to COVID-19. The study selection, data extraction and quality assessment will be performed by independent reviewers, and results will be crosschecked. The authoritative tools (AMSTAR-2, PRISMA and its extensions) will be used to assess the methodological quality and reporting quality of included SRs/MAs, and potential influence factors will be explored. The consistency of conclusions will be compared among reviews and the best evidence will be summarized. In addition, we will conduct exploratory meta-analyses (MAs) of individual studies when applicable. Data will be reported as number with (or) percentage, risk ratio (RR) or odds ratio (OR), mean difference (MD) or standardized mean difference (SMD) with 95% confidence interval (CI) according to the specific results. R3.6.1 and Microsoft Excel 2016 will be used to analyze and manage data. Results: The results of this overview will be submitted to a peer-reviewed journal for publication. Conclusions: In this study, we will present for the first time, an overview of SRs/MAs, which provides a comprehensive, dynamic evidence landscape on prevalence, prevention, diagnosis, treatment, and prognosis of COVID-19.