Feature engineering and a proposed decision-support system for systematic reviewers of medical evidence

Objectives: Evidence-based medicine depends on the timely synthesis of research findings. An important source of synthesized evidence resides in systematic reviews. However, a bottleneck in review production involves dual screening of citations with titles and abstracts to find eligible studies. For this research, we tested the effect of various kinds of textual information (features) on performance of a machine learning classifier. Based on our findings, we propose an automated system to reduce screeing burden, as well as offer quality assurance. Methods: We built a database of citations from 5 systematic reviews that varied with respect to domain, topic, and sponsor. Consensus judgments regarding eligibility were inferred from published reports. We extracted 5 feature sets from citations: alphabetic, alphanumeric +, indexing, features mapped to concepts in systematic reviews, and topic models. To simulate a two-person team, we divided the data into random halves. We optimized the parameters of a Bayesian classifier, then trained and tested models on alternate data halves. Overall, we conducted 50 independent tests. Results: All tests of summary performance (mean F3) surpassed the corresponding baseline, P<0.0001. The ranks for mean F3, precision, and classification error were statistically different across feature sets averaged over reviews; P-values for Friedman's test were .045, .002, and .002, respectively. Differences in ranks for mean recall were not statistically significant. Alphanumeric+ features were associated with best performance; mean reduction in screening burden for this feature type ranged from 88% to 98% for the second pass through citations and from 38% to 48% overall. Conclusions: A computer-assisted, decision support system based on our methods could substantially reduce the burden of screening citations for systematic review teams and solo reviewers. Additionally, such a system could deliver quality assurance both by confirming concordant decisions and by naming studies associated with discordant decisions for further consideration. © 2014 Bekhuis et al

Assessment, endoscopy, and treatment in patients with acute severe ulcerative colitis during the COVID-19 pandemic (PROTECT-ASUC): a multicentre, observational, case-control study

BackgroundThere is a paucity of evidence to support safe and effective management of patients with acute severe ulcerative colitis during the COVID-19 pandemic. We sought to identify alterations to established conventional evidence-based management of acute severe ulcerative colitis during the early COVID-19 pandemic, the effect on outcomes, and any associations with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and severe COVID-19 outcomes. MethodsThe PROTECT-ASUC study was a multicentre, observational, case-control study in 60 acute secondary care hospitals throughout the UK. We included adults (≥18 years) with either ulcerative colitis or inflammatory bowel disease unclassified, who presented with acute severe ulcerative colitis and fulfilled the Truelove and Witts criteria. Cases and controls were identified as either admitted or managed in emergency ambulatory care settings between March 1, 2020, and June 30, 2020 (COVID-19 pandemic period cohort), or between Jan 1, 2019, and June 30, 2019 (historical control cohort), respectively. The primary outcome was the proportion of patients with acute severe ulcerative colitis receiving rescue therapy (including primary induction) or colectomy. The study is registered with ClinicalTrials.gov, NCT04411784. FindingsWe included 782 patients (398 in the pandemic period cohort and 384 in the historical control cohort) who met the Truelove and Witts criteria for acute severe ulcerative colitis. The proportion of patients receiving rescue therapy (including primary induction) or surgery was higher during the pandemic period than in the historical period (217 [55%] of 393 patients vs 159 [42%] of 380 patients; p=0·00024) and the time to rescue therapy was shorter in the pandemic cohort than in the historical cohort (p=0·0026). This difference was driven by a greater use of rescue and primary induction therapies with biologicals, ciclosporin, or tofacitinib in the COVID-19 pandemic period cohort than in the historical control period cohort (177 [46%] of 387 patients in the COVID-19 cohort vs 134 [36%] of 373 patients in the historical cohort; p=0·0064). During the pandemic, more patients received ambulatory (outpatient) intravenous steroids (51 [13%] of 385 patients vs 19 [5%] of 360 patients; p=0·00023). Fewer patients received thiopurines (29 [7%] of 398 patients vs 46 [12%] of 384; p=0·029) and 5-aminosalicylic acids (67 [17%] of 398 patients vs 98 [26%] of 384; p=0·0037) during the pandemic than in the historical control period. Colectomy rates were similar between the pandemic and historical control groups (64 [16%] of 389 vs 50 [13%] of 375; p=0·26); however, laparoscopic surgery was less frequently performed during the pandemic period (34 [53%] of 64] vs 38 [76%] of 50; p=0·018). Five (2%) of 253 patients tested positive for SARS-CoV-2 during hospital treatment. Two (2%) of 103 patients re-tested for SARS-CoV-2 during the 3-month follow-up were positive 5 days and 12 days, respectively, after discharge from index admission. Both recovered without serious outcomes. InterpretationThe COVID-19 pandemic altered practice patterns of gastroenterologists and colorectal surgeons in the management of acute severe ulcerative colitis but was associated with similar outcomes to a historical cohort. Despite continued use of high-dose corticosteroids and biologicals, the incidence of COVID-19 within 3 months was low and not associated with adverse COVID-19 outcomes

The SAMe-TT2R2 score and quality of anticoagulation in atrial fibrillation: a simple aid to decision-making on who is suitable (or not) for vitamin K antagonists

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