Explore the vast range of titles available.

Objectives: To describe variations in characteristics of randomized controlled trials conducted in the Gulf Cooperation Council (GCC) countries, and critically appraising the quality of design, conduct and analysis of the trials. Methods: We carried out a systematically comprehensive electronic search of articles published between 1990 and 2018 and indexed in several databases: i) MEDLINE/ PubMed, ii) EMBASE, iii) Cochrane Central Register of Controlled Trials (CENTRAL), iv) ClinicalTrials.gov, and v) World Health Organization International Clinical Trials Registry Platform. We summarized the overall risk of bias present in all analyzed studies using the Cochrane Collaboration risk of bias tool (CCRBT). Results: A remarkable shift in numbers of publications from 2006 onwards was found. The largest number of publications were from Saudi Arabia and consisted of hospitals/clinics based studies. Lack of randomization was found in the majority of reports, and nearly three-fourth of the studies involved the use of intention-to-treat (ITT) principle. However, the proportion of adequately generated random sequence methods has increased yearly, and this increase accounted for a relatively large proportion over the latter half of the studied period (p<0.001), in contrast to the proportion of allocation concealment and blinding. Journal impact factor was significantly correlated with the quality of random sequence generation (r=0.145; p=0.014). Conclusion: The randomization methods have gained more attention over the last 3 decades. Secondly, Journal impact factor can serve as an indicator of randomization quality. To mitigate the large rate of overall high risk of bias in GCC studies, high-quality trials must be considered by ensuring adequate allocation concealment and blinding methods. PROSPERO No. ID: CRD42022310331 Keywords: Clinical Trial, systematic review, bias, Arab world [phrase omitted]

Objectives:To describe variations in characteristics of randomized controlled trials conducted in the Gulf Cooperation Council (GCC) countries, and critically appraising the quality of design, conduct and analysis of the trials.Methods:We carried out a systematically comprehensive electronic search of articles published between 1990 and 2018 and indexed in several databases: i) MEDLINE/PubMed, ii) EMBASE, iii) Cochrane Central Register of Controlled Trials (CENTRAL), iv) ClinicalTrials.gov, and v) World Health Organization International Clinical Trials Registry Platform. We summarized the overall risk of bias present in all analyzed studies using the Cochrane Collaboration risk of bias tool (CCRBT).Results:A remarkable shift in numbers of publications from 2006 onwards was found. The largest number of publications were from Saudi Arabia and consisted of hospitals/clinics based studies. Lack of randomization was found in the majority of reports, and nearly three-fourth of the studies involved the use of intention-to-treat (ITT) principle. However, the proportion of adequately generated random sequence methods has increased yearly, and this increase accounted for a relatively large proportion over the latter half of the studied period (p<0.001), in contrast to the proportion of allocation concealment and blinding. Journal impact factor was significantly correlated with the quality of random sequence generation (r=0.145; p=0.014).Conclusion:The randomization methods have gained more attention over the last 3 decades. Secondly, Journal impact factor can serve as an indicator of randomization quality. To mitigate the large rate of overall high risk of bias in GCC studies, high-quality trials must be considered by ensuring adequate allocation concealment and blinding methods. PROSPERO No. ID: CRD42022310331

Artificial intelligence is dramatically transforming medical imaging. In Saudi Arabia, there are a lack of studies assessing the level of artificial intelligence use and reliably determining the perceived impact of artificial intelligence on the radiology workflow and the profession. We assessed the levels of artificial intelligence use among radiology trainees and correlated the perceived impact of artificial intelligence on the workflow and profession with the behavioral intention to use artificial intelligence. This cross-sectional study enrolled radiology trainees from Saudi Arabia, and a 5-part-structured questionnaire was disseminated. The items concerning the perceived impact of artificial intelligence on the radiology workflow conformed to the six-step standard workflow in radiology, which includes ordering and scheduling, protocoling and acquisition, image interpretation, reporting, communication, and billing. We included 98 participants. Few used artificial intelligence in routine practice (7%). The perceived impact of artificial intelligence on the radiology workflow was at a considerable level in all radiology workflow steps (range, 3.64–3.97 out of 5). Behavioral intention to use artificial intelligence was linearly correlated with the perceptions of its impact on the radiology workflow and on the profession (p < 0.001). Artificial intelligence is used at a low level in radiology. The perceived impact of artificial intelligence on radiology workflow and the profession is correlated to an increase in behavioral intention to use artificial intelligence. Thus, increasing awareness about the positive impact of artificial intelligence can improve its adoption.