Objective To develop, through revision of the Cochrane Collaboration search strategy for OVID-MEDLINE, a highly sensitive search strategy to retrieve reports of controlled trials using PubMed. Methods The original highly sensitive Cochrane strategy was revised to take into account additional Medical Subject Headings (MeSH) and other terminology as well as the current unique features of PubMed. We compared the retrieval of the revised strategy with that of the original Cochrane strategy before and after translation of the strategies into PubMed format. Finally, we used a gold standard database of reports of controlled trials identified by electronic and hand search of selected journals to test the revised strategy in PubMed format. Results The revised strategy included a search statement modified for increased precision, and added ‘Cross-over Studies’ as a MeSH term and the term ‘latin square’ as a text word. Compared to the original Cochrane strategy, the revised strategy identified 53 additional reports of controlled trials accessing MEDLINE through OVID. When the revised strategy and original Cochrane strategy were translated into PubMed format, the revised strategy retrieved 90 reports of controlled trials not identified by the original strategy. Finally, the revised strategy in PubMed format retrieved all of the reports of controlled trials in the gold standard database. Ninety-eight per cent of the gold standard reports of controlled trials were retrieved by Phase 1 of the optimal PubMed search strategy. Conclusions Failure to identify all relevant trials for systematic review could result in bias. We developed a highly sensitive search strategy for the retrieval of reports of controlled trials for use with PubMed that retrieves more relevant citations (greater sensitivity) and fewer non-relevant citations (greater precision) than the original Cochrane search strategy.

Systematic reviews (SR) are vital to health care, but have become complicated and time-consuming, due to the rapid expansion of evidence to be synthesised. Fortunately, many tasks of systematic reviews have the potential to be automated or may be assisted by automation. Recent advances in natural language processing, text mining and machine learning have produced new algorithms that can accurately mimic human endeavour in systematic review activity, faster and more cheaply. Automation tools need to be able to work together, to exchange data and results. Therefore, we initiated the International Collaboration for the Automation of Systematic Reviews (ICASR), to successfully put all the parts of automation of systematic review production together. The first meeting was held in Vienna in October 2015. We established a set of principles to enable tools to be developed and integrated into toolkits. This paper sets out the principles devised at that meeting, which cover the need for improvement in efficiency of SR tasks, automation across the spectrum of SR tasks, continuous improvement, adherence to high quality standards, flexibility of use and combining components, the need for a collaboration and varied skills, the desire for open source, shared code and evaluation, and a requirement for replicability through rigorous and open evaluation. Automation has a great potential to improve the speed of systematic reviews. Considerable work is already being done on many of the steps involved in a review. The ‘Vienna Principles’ set out in this paper aim to guide a more coordinated effort which will allow the integration of work by separate teams and build on the experience, code and evaluations done by the many teams working across the globe.

There is growing interest in patient outcomes following critical illness, with an increasing number and different types of studies conducted, and a need for synthesis of existing findings to help inform the field. For this purpose we conducted a systematic review of qualitative studies evaluating patient outcomes after hospital discharge for survivors of critical illness. We searched the PubMed, EMBASE, CINAHL, PsycINFO, and CENTRAL databases from inception to June 2015. Studies were eligible for inclusion if the study population was >50 % adults discharged from the ICU, with qualitative evaluation of patient outcomes. Studies were excluded if they focused on specific ICU patient populations or specialty ICUs. Citations were screened in duplicate, and two reviewers extracted data sequentially for each eligible article. Themes related to patient outcome domains were coded and categorized based on the main domains of the Patient Reported Outcomes Measurement Information System (PROMIS) framework. A total of 2735 citations were screened, and 22 full-text articles were eligible, with year of publication ranging from 1995 to 2015. All of the qualitative themes were extracted from eligible studies and then categorized using PROMIS descriptors: satisfaction with life (16 studies), including positive outlook, acceptance, gratitude, independence, boredom, loneliness, and wishing they had not lived; mental health (15 articles), including symptoms of post-traumatic stress disorder, anxiety, depression, and irritability/anger; physical health (14 articles), including mobility, activities of daily living, fatigue, appetite, sensory changes, muscle weakness, and sleep disturbances; social health (seven articles), including changes in friends/family relationships; and ability to participate in social roles and activities (six articles), including hobbies and disability. ICU survivors may experience positive emotions and life satisfaction; however, a wide range of mental, physical, social, and functional sequelae occur after hospital discharge. These findings are important for understanding patient-centered outcomes in critical care and providing focus for future interventional studies aimed at improving outcomes of importance to ICU survivors.