Enlighten-Research publications by members of the University of Glasgow http://eprints.gla.ac.uk Minimally invasive surgery with thrombolysis in intracerebral haemorrhage evacuation (MISTIE III): a randomised, controlled, open-label phase 3 trial with blinded endpoint

BACKGROUND:Minimally invasive surgery procedures, including stereotactic catheter aspiration and clearance of intracerebral hemorrhage (ICH) with recombinant tissue plasminogen activator hold a promise to improve outcome of supratentorial brain hemorrhage, a morbid and disabling type of stroke. A recently completed Phase III randomized trial showed improved mortality but was neutral on the primary outcome (modified Rankin scale score 0 to 3 at 1 yr). OBJECTIVE: To assess surgical performance and its impact on the extent of ICH evacuation and functional outcomes. METHODS: Univariate and multivariate models were used to assess the extent of hematoma evacuation efficacy in relation to mRS 0 to 3 outcome and postulated factors related to patient, disease, and protocol adherence in the surgical arm (n = 242) of the MISTIE trial. RESULTS: Greater ICH reduction has a higher likelihood of achieving mRS of 0 to 3 with a minimum evacuation threshold of ≤15 mL end of treatment ICH volume or ≥70% volume reduction when controlling for disease severity factors. Mortality benefit was achieved at ≤30 mL end of treatment ICH volume, or >53% volume reduction. Initial hematoma volume, history of hypertension, irregular-shaped hematoma, number of alteplase doses given, surgical protocol deviations, and catheter manipulation problems were significant factors in failing to achieve ≤15 mL goal evacuation. Greater surgeon/site experiences were associated with avoiding poor hematoma evacuation. CONCLUSION: This is the first surgical trial reporting thresholds for reduction of ICH volume correlating with improved mortality and functional outcomes. To realize the benefit of surgery, protocol objectives, surgeon education, technical enhancements, and case selection should be focused on this goal.

Key Points Question Can a prediction model for mortality in the intensive care unit be improved by using more laboratory values, vital signs, and clinical text in electronic health records? Findings In this cohort study of 101 196 patients in the intensive care unit, a machine learning–based model using all available measurements of vital signs and laboratory values, plus clinical text, exhibited good calibration and discrimination in predicting in-hospital mortality, yielding an area under the receiver operating characteristic curve of 0.922. Meaning Applying methods from machine learning and natural language processing to information already routinely collected in electronic health records, including laboratory test results, vital signs, and clinical free-text notes, significantly improves a prediction model for mortality in the intensive care unit compared with approaches that use only the most abnormal vital sign and laboratory values.

Importance Commercial virtual visits are an increasingly popular model of care for the management of common, acute illnesses. In commercial virtual visits, patients access a website to be connected synchronously—via videoconference, telephone, or webchat—to a physician with whom they have no prior relationship. There has been no assessment of whether the care delivered through those websites is similar, or whether quality varies among the sites. Objective To assess the variation in quality of care among virtual visit companies. Design We performed an audit study using trained standardized patients. Setting The standardized patients presented to commercial virtual visit companies with six common, acute illnesses (ankle pain, streptococcal pharyngitis, viral pharyngitis, acute rhinosinusitis, low back pain, and recurrent urinary tract infection). Participants The eight commercial virtual visit websites with the highest web traffic. Main Outcome Measures The primary outcomes were completeness of histories and physical examinations, naming the correct diagnosis (versus an incorrect diagnosis or not naming any diagnosis), and adherence to guidelines of key management decisions. Results Standardized patients completed 599 commercial virtual visits from May 2013 to July 2014. Histories and physical examinations were complete in 69.6% (95% confidence interval [CI], 67.7%-71.6%) of virtual visits, diagnoses were correctly named in 76.5% (CI, 72.9%-79.9%), and key management decisions were adherent to guidelines in 54.3% (CI, 50.2%-58.3%). Rates of guideline-adherent care ranged from 34.4% to 66.1% across the eight websites. Variation across websites was significantly greater for viral pharyngitis and acute rhinosinusitis (12.8-82.1%) than for streptococcal pharyngitis and low back pain (74.6-96.5%) or ankle pain and recurrent urinary tract infection (3.4-40.4%). There was no statistically significant variation in guideline adherence by mode of communication (video vs. telephone vs. webchat). Conclusions We found significant variation in quality among companies providing virtual visits for management of common acute illnesses. There was more variation in performance for some conditions than for others, but there was no variation by mode of communication.