With the successive release of the CONSORT extensions for acupuncture, moxibustion, cupping, and Tuina/massage, this review aims to assess the reporting characteristics and quality of randomized controlled trials (RCTs) based on these specific guidelines. A comprehensive review was conducted by searching multiple databases, including Embase, Ovid MEDLINE(R), All EBM Reviews, AMED, CNKI, VIP Chinese Medical Journal Database, and Wanfang Data, for publications from January 1 to December 31, 2022. Two reviewers independently evaluated the eligibility of the records, extracted predetermined information, and assessed the reporting based on the STRICTA, STRICTOM, STRICTOC, and STRICTOTM checklists. Among the included 387 studies (acupuncture, 213; Tuina/massage, 85; moxibustion, 73; cupping, 16), the overall reporting compliance averaged 56.0%, with acupuncture leading at 62.6%, followed by cupping (60.2%), moxibustion (53.1%), and Tuina/massage (47.9%). About half of the evaluated items showed poor reporting (compliance rate < 65%). Notably, international journals demonstrated significantly higher reporting quality than Chinese journals (P < 0.05). Although acupuncture trials had relatively higher compliance rates, deficiencies persist in reporting non-pharmacological therapies of Chinese medicine, particularly in areas like treatment environment details and provider background information.

UNASSIGNED: The American Academy of Orthopaedic Surgeons (AAOS) has developed a clinical practice guideline (CPG) for management of anterior cruciate ligament (ACL) injuries. Primary studies such as randomized controlled trials (RCTs) are cited as evidence for the guidelines. Given the influence that these trials have on patient care, adherence to standardized protocols for conducting and reporting RCTs is essential.
UNASSIGNED: To evaluate the CONSORT (Consolidated Standards of Reporting Trials) Extension for Harms-related reporting of RCTs cited as supporting evidence for the AAOS CPG on the management of ACL tears.
UNASSIGNED: Cross-sectional study.
UNASSIGNED: The reference section of the AAOS guideline for ACL tears was first screened for RCTs cited in the CPG. Next, each RCT was evaluated for adherence to the CONSORT Extension for Harms checklist. Both identification of RCTs and assessment of adherence were performed in a masked and duplicate process. Descriptive statistics were used to summarize adherence to CONSORT Extension for Harms items. A Pearson correlation test was conducted to assess the relationship between the year of publication and adherence to CONSORT harms reporting.
UNASSIGNED: The sample included 113 RCTs, of which 16 (14.2%) were published before the CONSORT Extension for Harms was implemented in 2004. Sample sizes ranged from 24 to 4564 participants, with a mean of 228. None of the included RCTs included all 18 items in the CONSORT Extension for Harms checklist. The mean number of checklist items reported was 4 (of 18; 22.2%). A moderate, positive, and statistically significant correlation was found between the RCT publication year and the adherence with reporting of the CONSORT Extension for Harms (t111 = 3.54; P < .001) (r = 0.32; 95% CI, 0.14-0.47).
UNASSIGNED: Harms were infrequently reported in RCTs cited as supporting evidence in the AAOS CPG for the management of ACL tears. One encouraging finding was the positive correlation between the year when RCTs were published and how well they adhered to reporting harms. Efforts to improve adverse event reporting are warranted, as RCTs are commonly used to make clinical decisions in orthopaedic surgery.

OBJECTIVE: In the context of ophthalmologic practice, there has been a rapid increase in the amount of data collected using electronic health records (EHR). Artificial intelligence (AI) offers a promising means of centralizing data collection and analysis, but to date, most AI algorithms have only been applied to analyzing image data in ophthalmologic practice. In this review we aimed to characterize the use of AI in the analysis of EHR, and to critically appraise the adherence of each included study to the CONSORT-AI reporting guideline.
METHODS: A comprehensive search of three relevant databases (MEDLINE, EMBASE, and Cochrane Library) from January 2010 to February 2023 was conducted. The included studies were evaluated for reporting quality based on the AI-specific items from the CONSORT-AI reporting guideline.
RESULTS: Of the 4,968 articles identified by our search, 89 studies met all inclusion criteria and were included in this review. Most of the studies utilized AI for ocular disease prediction (n = 41, 46.1%), and diabetic retinopathy was the most studied ocular pathology (n = 19, 21.3%). The overall mean CONSORT-AI score across the 14 measured items was 12.1 (range 8-14, median 12). Categories with the lowest adherence rates were: describing handling of poor quality data (48.3%), specifying participant inclusion and exclusion criteria (56.2%), and detailing access to the AI intervention or its code, including any restrictions (62.9%).
CONCLUSIONS: In conclusion, we have identified that AI is prominently being used for disease prediction in ophthalmology clinics, however these algorithms are limited by their lack of generalizability and cross-center reproducibility. A standardized framework for AI reporting should be developed, to improve AI applications in the management of ocular disease and ophthalmology decision making.

UNASSIGNED: To develop text classification models for determining whether the checklist items in the CONSORT reporting guidelines are reported in randomized controlled trial publications.
UNASSIGNED: Using a corpus annotated at the sentence level with 37 fine-grained CONSORT items, we trained several sentence classification models (PubMedBERT fine-tuning, BioGPT fine-tuning, and in-context learning with GPT-4) and compared their performance. To address the problem of small training dataset, we used several data augmentation methods (EDA, UMLS-EDA, text generation and rephrasing with GPT-4) and assessed their impact on the fine-tuned PubMedBERT model. We also fine-tuned PubMedBERT models limited to checklist items associated with specific sections (e.g., Methods) to evaluate whether such models could improve performance compared to the single full model. We performed 5-fold cross-validation and report precision, recall, F1 score, and area under curve (AUC).
UNASSIGNED: Fine-tuned PubMedBERT model that takes as input the sentence and the surrounding sentence representations and uses section headers yielded the best overall performance (0.71 micro-F1, 0.64 macro-F1). Data augmentation had limited positive effect, UMLS-EDA yielding slightly better results than data augmentation using GPT-4. BioGPT fine-tuning and GPT-4 in-context learning exhibited suboptimal results. Methods-specific model yielded higher performance for methodology items, other section-specific models did not have significant impact.
UNASSIGNED: Most CONSORT checklist items can be recognized reasonably well with the fine-tuned PubMedBERT model but there is room for improvement. Improved models can underpin the journal editorial workflows and CONSORT adherence checks and can help authors in improving the reporting quality and completeness of their manuscripts.

This chapter provides a succinct overview of several recommendations for the design and analysis of treatments for AUD with a specific focus on increasing rigor and generalizability of treatment studies in order to increase the reach of AUD treatment. We recommend that researchers always register their trials in a clinical trial registry and make the protocol accessible so that the trial can be replicated in future work, follow CONSORT reporting guidelines when reporting the results of the trial, carefully describe all inclusion and exclusion criteria as well as the randomization scheme, and always use an intent to treat design with attention to analysis of missing data. In addition, we recommend that researchers pay closer attention to recruitment and engagement strategies that increase enrollment and retention of historically marginalized and understudied populations, and we end with a plea for more consideration of implementation science approaches to increase the dissemination and implementation of AUD treatment in real-world settings.

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BACKGROUND: Despite the critical importance of clinical trials to provide evidence about the effects of intervention for children and youth, a paucity of published high-quality pediatric clinical trials persists. Sub-optimal reporting of key trial elements necessary to critically appraise and synthesize findings is prevalent. To harmonize and provide guidance for reporting in pediatric controlled clinical trial protocols and reports, reporting guideline extensions to the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) and Consolidated Standards of Reporting Trials (CONSORT) guidelines specific to pediatrics are being developed: SPIRIT-Children (SPIRIT-C) and CONSORT-Children (CONSORT-C).
METHODS: The development of SPIRIT-C/CONSORT-C will be informed by the Enhancing the Quality and Transparency of Health Research Quality (EQUATOR) method for reporting guideline development in the following stages: (1) generation of a preliminary list of candidate items, informed by (a) items developed during initial development efforts and child relevant items from recent published SPIRIT and CONSORT extensions; (b) two systematic reviews and environmental scan of the literature; (c) workshops with young people; (2) an international Delphi study, where a wide range of panelists will vote on the inclusion or exclusion of candidate items on a nine-point Likert scale; (3) a consensus meeting to discuss items that have not reached consensus in the Delphi study and to \"lock\" the checklist items; (4) pilot testing of items and definitions to ensure that they are understandable, useful, and applicable; and (5) a final project meeting to discuss each item in the context of pilot test results. Key partners, including young people (ages 12-24 years) and family caregivers (e.g., parents) with lived experiences with pediatric clinical trials, and individuals with expertise and involvement in pediatric trials will be involved throughout the project. SPIRIT-C/CONSORT-C will be disseminated through publications, academic conferences, and endorsement by pediatric journals and relevant research networks and organizations.
CONCLUSIONS: SPIRIT/CONSORT-C may serve as resources to facilitate comprehensive reporting needed to understand pediatric clinical trial protocols and reports, which may improve transparency within pediatric clinical trials and reduce research waste.
BACKGROUND: The development of these reporting guidelines is registered with the EQUATOR Network: SPIRIT-Children ( https://www.equator-network.org/library/reporting-guidelines-under-development/reporting-guidelines-under-development-for-clinical-trials-protocols/#35 ) and CONSORT-Children ( https://www.equator-network.org/library/reporting-guidelines-under-development/reporting-guidelines-under-development-for-clinical-trials/#CHILD ).

The aim of this study was to explore adherence to the Consolidated Standards of Reporting Trials (CONSORT) reporting standards in abstracts of randomized controlled trials on glaucoma. A cross-sectional observational study was conducted on the aforementioned abstracts, indexed in MEDLINE/PubMed between the years 2017 and 2021. In total, 302 abstracts met the inclusion criteria and were further analyzed. The median score of CONSORT-A items was 8 (interquartile range, 7-10) out of 17 (47.0%). Most analyzed studies were conducted in a single center (80.5%) and the abstracts were predominantly structured (95.0%). Only 20.5% of the abstracts adequately described the trial design, while randomization and funding were described by 6.0% of the abstracts. Higher overall scores were associated with structured abstracts, a multicenter setting, statistically significant results, funding by industry, a higher number of participants, and having been published in journals with impact factors above four (p < 0.001, respectively). The results of this study indicate a suboptimal adherence to CONSORT-A reporting standards, especially in particular items such as randomization and funding. Since these factors could contribute to the overall quality of the trials and further translation of trial results into clinical practice, an improvement in glaucoma research reporting transparency is needed.

The Japanese macaque (Macaca fuscata) has become a key species for studying homosexual behavior over recent decades. With the non-conceptive nature, their same-sex consortships illustrate that individual partner preferences can exist beyond direct reproductive benefits or apparent sociosexual strategies. An open question is whether the behavior shared between partners in consortship directly affects their choice to remain with a partner. With this study, we examined behavioral aspects underlying consortship temporal patterns in these promiscuous and bisexual primates. While these patterns could be relevant in both homo- and heterosexual consortships, our study primarily focused on female-female pairs. We hypothesized that the stability of consortships (duration and occurrence) is influenced by a pair\'s sexual behavior, mutual sexual stimulation, and close affiliative inter-mount behaviors involving high-intensity body contact. A semi-free population of Japanese macaques was observed over one mating season. In total, 40 h of focal data on female-female consortship behaviors were analyzed. Forty-six percent of all sexually mature females engaged in homosexual interactions. Our behavioral analyses of female-female pairs found that close body contact, rather than grooming or sexual interactions, was correlated with the stability of homosexual consortships. The greater the amount of huddling and embracing a pair engaged in, the more likely they were to stay together and reunite again. However, the frequency of mounting, rubbing or thrusting had no discernable effect on consortship stability. The results of this study thus add important knowledge to partner qualities in promiscuous primates as well as to inter-group differences of homosexual behavior in Japanese macaques.

OBJECTIVE: Adherence to pharmacological interventions in clinical trials is crucial for accurate identification of beneficial and adverse outcomes. The ways in which adherence to interventions should be reported in trial publications are described in the Template for Intervention Description and Replication (TIDieR), a 12-item extension of the Consolidated Standards of Reporting Trials reporting guidelines. The objective of this study was to assess compliance with TIDieR Items 11 and 12 of randomized controlled trials (RCTs) of interventions in SARS-CoV-2 infection published in 5 selected journals during 2021.
METHODS: We assessed pharmacological interventions for SARS-CoV-2 infection reported in RCTs published in 2021 in the Annals of Internal Medicine, The BMJ, JAMA, The Lancet and The New England Journal for Medicine for compliance with TIDieR items addressing intervention adherence (Items 11 and 12). We calculated proportional adherence for pharmacological and comparator interventions where available.
RESULTS: We found 75 eligible RCTs. Twenty-eight (37%) reported results of SARS-CoV-2 vaccinations. Compliance with Items 11 and 12 could be assessed in 71 of these 75. Of the 71 RCTs, 37 (52%) reported how adherence was assessed (Item 11), and 70 reported adherence rates (Item 12). Only 1 of the 71 RCTs (1.4%, 0-7.6%) fully complied with TIDieR Items 11 and 12.
CONCLUSIONS: Half of RCTs of SARS-CoV-2 pharmacological interventions published in leading medical journals in 2021 complied with reporting of how adherence assessments were made and almost none complied with both TIDieR Items 11 and 12. The implications for interpretation, application and replication of findings based on these publications warrant consideration.