Wikipedia as informal self-education for clinical decision-making in medical practice

Background For almost any topic, a Wikipedia page will appear among the first ten items of a search online. Wikipedia is also a site whose quality and reliability has been called into question. Methods In this paper, we aim to discuss medical practitioners’ use of Wikipedia, what this consists of and what it might be. We consider the context and history of Wikipedia before discussing the relationship between Wikipedia and the medical profession. In so doing, we will consider Wikipedia as a means of informal self-education and the extent to which it might inform clinical decision-making. We compare with the existing literature results from our two small-scale empirical studies of Wikipedia and clinical decision-making. Results Notwithstanding issues over quality and reliability, Wikipedia’s rules on verifiability are such that its articles are very heavily referenced, and this is just as true of health-related articles. The Cochrane/Wikipedia Initiative in improving the quality and reliability of medical and health pages in Wikipedia is significant in increasing reliability. Our respondents largely concurred with the results from earlier studies on the use of Wikipedia by medical practitioners. Conclusion Perhaps the very doubt over Wikipedia’s accuracy is its greatest strength as a means of informal education of doctors. That medical and health articles on Wikipedia can be so fully referenced and still be doubted is arguably a good thing and one whose effects may be spread into other, more trusted, publications. Hence, one might envisage a future where no one source is taken automatically on trust. Keywords Wikipedia, informal education, continued professional development, medical education

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations

Measurement of the tt¯ cross section and its ratio to the Z production cross section using pp collisions at √s = 13.6 TeV with the ATLAS detector

The inclusive top-quark-pair production cross section σtt¯ and its ratio to the Z-boson production cross section have been measured in proton–proton collisions at √s = 13.6 TeV, using 29 fb−1 of data collected in 2022 with the ATLAS experiment at the Large Hadron Collider. Using events with an opposite-charge electron-muon pair and b-tagged jets, and assuming Standard Model decays, the top-quark-pair production cross section is measured to be σtt¯=850±3(stat.)±18(syst.)±20(lumi.) pb. The ratio of the tt¯ and the Z-boson production cross sections is also measured, where the Z-boson contribution is determined for inclusive e+e− and μ+μ− events in a fiducial phase space. The relative uncertainty on the ratio is reduced compared to the tt¯ cross section, thanks to the cancellation of several systematic uncertainties. The result for the ratio, Rtt¯/Z=1.145±0.003(stat.)±0.021(syst.)±0.002(lumi.) is consistent with the Standard Model prediction using the PDF4LHC21 PDF set