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The Consolidated Standards of Reporting Trials extension for Artificial Intelligence interventions (CONSORT-AI) was published in September 2020. Since its publication, several randomised controlled trials (RCTs) of AI interventions have been published but their completeness and transparency of reporting is unknown. This systematic review assesses the completeness of reporting of AI RCTs following publication of CONSORT-AI and provides a comprehensive summary of RCTs published in recent years. 65 RCTs were identified, mostly conducted in China (37%) and USA (18%). Median concordance with CONSORT-AI reporting was 90% (IQR 77–94%), although only 10 RCTs explicitly reported its use. Several items were consistently under-reported, including algorithm version, accessibility of the AI intervention or code, and references to a study protocol. Only 3 of 52 included journals explicitly endorsed or mandated CONSORT-AI. Despite a generally high concordance amongst recent AI RCTs, some AI-specific considerations remain systematically poorly reported. Further encouragement of CONSORT-AI adoption by journals and funders may enable more complete adoption of the full CONSORT-AI guidelines. The CONSORT-AI extension was developed to provide specific guidance for randomised controlled trials involving Artificial Intelligence (AI) interventions. Here, the authors show that since publication of CONSORT-AI, several AI-specific considerations remain systematically underreported. [ABSTRACT FROM AUTHOR]

This correction notice is for an article titled "Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines" published in Nature Communications. The correction adds the names of two authors, Carrie D. Llewellyn and Richard O. de Visser, who were originally omitted from the author list. It also includes their affiliations and contributions to the article. The correction has been made to both the PDF and HTML versions of the article. [Extracted from the article]

Background: Tissue-agnostic drug development provides a paradigm shift in precision medicine and requires innovative trial designs. However, outcome selection for such trials can prove challenging. The objectives of this review were to: (i) Identify and map core outcome sets (COS), across 11 immune-mediated inflammatory diseases (IMIDs) in order to facilitate the selection of relevant outcomes across the conditions for innovative trials of tissue-agnostic drug therapies. (ii) Compare outcomes or endpoints recommended by the US Food and Drug Administration (FDA) and European Medicines Agency (EMA) to identify and highlight similarities and differences.Methods: The Core Outcome Measures in Effectiveness Trials (COMET), International Consortium for Health Outcomes Measurement (ICHOM), FDA and EMA databases were searched from inception to 28th December 2019. Two reviewers independently screened titles and abstracts of retrieved entries and conducted the subsequent full text screening. Hand searching of the reference lists and citation searching of the selected publications was conducted. The methodological quality of the included peer-reviewed articles was independently assessed by the reviewers based on the items of the COS-Standards for Development recommendations (COS-STAD) checklist. Core outcomes from the included publications were extracted and mapped across studies and conditions. Regulatory guidance from FDA and EMA, where available for clinical trials for the IMIDs, were obtained from their databases and recommendations on outcomes to measure directly compared.Results: Forty-four COS publications were included in the final analysis. Outcomes such as disease activity, pain, fatigue, quality of life, physical function, work limitation/productivity, steroid use and biomarkers were recommended across majority of the conditions. There were significant similarities and differences in FDA and EMA recommendations. The only instance where either regulatory body directly referenced a COS was for jSLE-both referenced the Paediatric Rheumatology International Trials Organization (PRINTO) COS.Conclusions: The findings from this systematic review provide valuable information to inform outcome selection in tissue-agnostic trials for IMIDs. There is a need for increased collaboration between regulators and COS developers and inclusion of regulators as key stakeholders in COS development to enhance the quality of COS.Trial Registration: Not registered. [ABSTRACT FROM AUTHOR]

Introduction: Systematic reviews are important for informing decision-making and primary research, but they can be time consuming and costly. With the advent of machine learning, there is an opportunity to accelerate the review process in study screening. We aimed to understand the literature to make decisions about the use of machine learning for screening in our review workflow. Methods: A pragmatic literature review of PubMed to obtain studies evaluating the accuracy of publicly available machine learning screening tools. A single reviewer used 'snowballing' searches to identify studies reporting accuracy data and extracted the sensitivity (ability to correctly identify included studies for a review) and specificity, or workload saved (ability to correctly exclude irrelevant studies). Results: Ten tools (AbstractR, ASReview Lab, Cochrane RCT classifier, Concept encoder, Dpedia, DistillerAI, Rayyan, Research Screener, Robot Analyst, SWIFT-active screener) were evaluated in a total of 16 studies. Fourteen studies were single arm where, although compared with a reference standard (predominantly single reviewer screening), there was no other comparator. Two studies were comparative, where tools were compared with other tools as well as a reference standard. All tools ranked records by probability of inclusion and either (i) applied a cut-point to exclude records or (ii) were used to rank and re-rank records during screening iterations, with screening continuing until most relevant records were obtained. The accuracy of tools varied widely between different studies and review projects. When used in method (ii), at 95 percent to 100 percent sensitivity, tools achieved workload savings of between 7 percent and 99 percent. It was unclear whether evaluations were conducted independent of tool developers. Conclusions: Evaluations suggest the potential for tools to correctly classify studies in screening. However, conclusions are limited since (i) tool accuracy is generally not compared with dual reviewer screening and (ii) the literature lacks comparative studies and, because of between-study heterogeneity, it is not possible to robustly determine the accuracy of tools compared with each other. Independent evaluations are needed. [ABSTRACT FROM AUTHOR]

Objective: adrenal masses are incidentally discovered in 5% of CT scans. In 2013/2014, 81 million CT examinations were undertaken in the USA and 5 million in the UK. However, uncertainty remains around the optimal imaging approach for diagnosing malignancy. We aimed to review the evidence on the accuracy of imaging tests for differentiating malignant from benign adrenal masses. Design: a systematic review and meta-analysis was conducted. Methods: We searched MEDLINE, EMBASE, cochrane CEBTRAL Register of controlled Trials, science citation Index, conference Proceedings citation Index, and ZETOC (January 1990 to august 2015). We included studies evaluating the accuracy of CT, MRI, or 18F-fluoro-deoxyglucose (FDG)-PET compared with an adequate histological or imaging-based follow-up reference standard. Results: We identified 37 studies suitable for inclusion, after screening 5469 references and 525 full-text articles. studies evaluated the accuracy of CT (n = 16), MRI (n = 15), and FDG-PET (n = 9) and were generally small and at high or unclear risk of bias. Only 19 studies were eligible for meta-analysis. Limited data suggest that CT density >10 HU has high sensitivity for detection of adrenal malignancy in participants with no prior indication for adrenal imaging, that is, masses with ≤10 HU are unlikely to be malignant. all other estimates of test performance are based on too small numbers. Conclusions: Despite their widespread use in routine assessment, there is insufficient evidence for the diagnostic value of individual imaging tests in distinguishing benign from malignant adrenal masses. future research is urgently needed and should include prospective test validation studies for imaging and novel diagnostic approaches alongside detailed health economics analysis. [ABSTRACT FROM AUTHOR]

Background: Tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral ribonucleic acid (RNA) using reverse transcription polymerase chain reaction (RT-PCR) are pivotal to detecting current coronavirus disease (COVID-19) and duration of detectable virus indicating potential for infectivity.Methods: We conducted an individual participant data (IPD) systematic review of longitudinal studies of RT-PCR test results in symptomatic SARS-CoV-2. We searched PubMed, LitCOVID, medRxiv, and COVID-19 Living Evidence databases. We assessed risk of bias using a QUADAS-2 adaptation. Outcomes were the percentage of positive test results by time and the duration of detectable virus, by anatomical sampling sites.Results: Of 5078 studies screened, we included 32 studies with 1023 SARS-CoV-2 infected participants and 1619 test results, from - 6 to 66 days post-symptom onset and hospitalisation. The highest percentage virus detection was from nasopharyngeal sampling between 0 and 4 days post-symptom onset at 89% (95% confidence interval (CI) 83 to 93) dropping to 54% (95% CI 47 to 61) after 10 to 14 days. On average, duration of detectable virus was longer with lower respiratory tract (LRT) sampling than upper respiratory tract (URT). Duration of faecal and respiratory tract virus detection varied greatly within individual participants. In some participants, virus was still detectable at 46 days post-symptom onset.Conclusions: RT-PCR misses detection of people with SARS-CoV-2 infection; early sampling minimises false negative diagnoses. Beyond 10 days post-symptom onset, lower RT or faecal testing may be preferred sampling sites. The included studies are open to substantial risk of bias, so the positivity rates are probably overestimated. [ABSTRACT FROM AUTHOR]