Analysis of Stroke Detection during the COVID-19 Pandemic Using Natural Language Processing of Radiology Reports

BACKGROUND AND PURPOSE:The coronavirus disease 2019 (COVID-19) pandemic has led to decreases in neuroimaging volume. Our aim was to quantify the change in acute or subacute ischemic strokes detected on CT or MR imaging during the pandemic using natural language processing of radiology reports.MATERIALS AND METHODS:We retrospectively analyzed 32,555 radiology reports from brain CTs and MRIs from a comprehensive stroke center, performed from March 1 to April 30 each year from 2017 to 2020, involving 20,414 unique patients. To detect acute or subacute ischemic stroke in free-text reports, we trained a random forest natural language processing classifier using 1987 randomly sampled radiology reports with manual annotation. Natural language processing classifier generalizability was evaluated using 1974 imaging reports from an external dataset.RESULTS:The natural language processing classifier achieved a 5-fold cross-validation classification accuracy of 0.97 and an F1 score of 0.74, with a slight underestimation (−5%) of actual numbers of acute or subacute ischemic strokes in cross-validation. Importantly, cross-validation performance stratified by year was similar. Applying the classifier to the complete study cohort, we found an estimated 24% decrease in patients with acute or subacute ischemic strokes reported on CT or MR imaging from March to April 2020 compared with the average from those months in 2017–2019. Among patients with stroke-related order indications, the estimated proportion who underwent neuroimaging with acute or subacute ischemic stroke detection significantly increased from 16% during 2017–2019 to 21% in 2020 (P = .01). The natural language processing classifier performed worse on external data.CONCLUSIONS:Acute or subacute ischemic stroke cases detected by neuroimaging decreased during the COVID-19 pandemic, though a higher proportion of studies ordered for stroke were positive for acute or subacute ischemic strokes. Natural language processing approaches can help automatically track acute or subacute ischemic stroke numbers for epidemiologic studies, though local classifier training is important due to radiologist reporting style differences.

There is much concern regarding the impact of the coronavirus disease 2019 (COVID-19) pandemic on the quality of stroke care, including issues with hospital capacity, clinical resource re-allocation, and the safety of patients and clinicians.^1,2 Previous reports have shown that there have been substantial decreases in stroke neuroimaging volume during the pandemic.^3,4 In addition, acute ischemic infarcts have been found on neuroimaging studies in many hospitalized patients with COVID-19, though the causal relationship is unclear.^5,6 Studies like these and other epidemiologic analyses usually rely on the creation of manually curated databases, in which identification of cases can be time-consuming and difficult to update in real-time. One way to facilitate such research is to use natural language processing (NLP), which has shown utility for automated analysis of radiology report data.⁷ NLP algorithms have been developed previously for the classification of neuroradiology reports for the presence of ischemic stroke findings and acute ischemic stroke subtypes.^8,9 Thus, NLP has the potential to facilitate COVID-19 research.In this study, we developed an NLP machine learning model that classifies radiology reports for the presence or absence of acute or subacute ischemic stroke (ASIS), as opposed to chronic stroke. We used this model to quantify the change in ASIS detected on all CT or MR imaging studies performed at a large comprehensive stroke center during the COVID-19 pandemic in the United States. We also evaluated NLP model generalizability and different training strategies using a sample of radiology reports from a second stroke center.     

Mind the gap: Teachers’ conceptions of student-staff partnership and its potential to enhance educational quality

Abstract

Introduction: Student-staff partnerships as a concept to improve medical education have received a growing amount of attention. Such partnerships are collaborations in which students and teachers seek to improve education by each adding their unique contribution to decision-making and implementation processes. Although previous research has demonstrated that students are favourable to this concept, teachers remain hesitant. The present study investigated teachers’ conceptions of student-staff partnerships and of the prerequisites that are necessary to render such partnerships successful and enhance educational quality.

Method: We conducted semi-structured interviews with 14 course coordinators who lead course design teams and also teach in 4 bachelor health programmes, using Bovill and Bulley’s levels of student participation as sensitising concepts during data analysis.

Results: The results pointed to three different conceptions of student-staff partnerships existing among teachers: Teachers teach and students study; teachers teach and value students’ feedback; and teachers and students co-create. The prerequisites for effective co-creation teachers identified were: Teachers must be open to involve students and create dialogues; students must be motivated and have good communication skills; the organisation must be supportive; and teachers should have the final say.

Conclusion: We conclude that teachers’ conceptions are consistent with Bovill and Bulley’s levels of student participation. Under certain conditions, teachers are willing to co-create and reach the highest levels of student participation.     

The role of online videos in teaching procedural skills to post-graduate medical learners: A systematic narrative review

Abstract

Objective: Online videos are commonly used in medical education. The aim of this review was to investigate the role of online instructional videos in teaching procedural skills to postgraduate medical learners.

Methods: This systematic narrative review was conducted according to the PRISMA guidelines. MEDLINE, Cochrane Central Register of Controlled Trials, EMBASE, ERIC and Google Scholar were searched. Full texts that applied to online videos, postgraduate medical learners and procedural skills were included without language restrictions. The methodological quality of the studies was evaluated using a validated tool. A thematic analysis of the studies was carried out using a general inductive approach.

Results: A total of 785 articles were retrieved and the full text was reviewed for 66 articles that met the inclusion and exclusion criteria of the study. Twenty papers that were relevant to the role of online videos in postgraduate medical education of procedural skills were used for this review. They were heterogenous in the outcomes collected and the evidence was of variable quality. There was strong evidence for the use of online videos for procedural skill knowledge acquisition and retention. Online videos were used for various purposes, such as supervision, assessment, postoperative debriefing, providing feedback, and promoting reflection.

Conclusion: Online videos are a valuable educational tool especially for procedural skill knowledge acquisition and retention. Future research needs to be carried out on the appropriate use of platforms in disseminating and using online videos, identifying the factors surrounding the learners, video characteristics, and data protection.     

Does ablation of atrial fibrillation at the time of septal myectomy improve survival of patients with obstructive hypertrophic cardiomyopathy?

ObjectiveTo evaluate the outcomes after septal myectomy in patients with obstructive hypertrophic cardiomyopathy according to atrial fibrillation and surgical ablation of atrial fibrillation.MethodsWe reviewed patients with obstructive hypertrophic cardiomyopathy who underwent septal myectomy at the Mayo Clinic from 2001 to 2016. History of atrial fibrillation was obtained from patient histories and electrocardiograms. All-cause mortality was the primary end point.ResultsA total of 2023 patients underwent septal myectomy, of whom 394 (19.5%) had at least 1 episode of atrial fibrillation preoperatively. Among patients with atrial fibrillation, 76 (19.3%) had only 1 known episode, 278 (70.6%) had recurrent paroxysmal atrial fibrillation, and 40 (10.2%) had persistent atrial fibrillation. Surgical ablation was performed in 190 patients at the time of septal myectomy, including 148 with pulmonary vein isolation and 42 with the classic maze procedure. Among all patients, operative mortality was 0.4%, and there were no early deaths in patients undergoing surgical ablation. Over a median follow-up of 5.6 years, patients with preoperative atrial fibrillation had increased mortality (hazard ratio, 1.36; 95% confidence interval, 0.97-1.91; P = .070) after multivariable adjustment for comorbidities. When considering the impact of atrial fibrillation with or without surgical treatment, the adjusted hazard ratio for mortality in patients undergoing ablation compared with no ablation was 0.93 (95% confidence interval, 0.52-1.69; P = .824).ConclusionsAtrial fibrillation is present preoperatively in one-fifth of patients with obstructive hypertrophic cardiomyopathy undergoing myectomy and showed a trend toward higher all-cause mortality. Survival of patients undergoing septal myectomy with preoperative atrial fibrillation was similar between those who did and did not receive concomitant surgical ablation.     

Patterns of Use of Induction Therapy for T2N0 Esophageal Cancer

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Novel Risk Factors for Progression of Diabetic and Nondiabetic CKD: Findings From the Chronic Renal Insufficiency Cohort (CRIC) Study

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Chlorthalidone with potassium citrate decreases calcium oxalate stones and increases bone quality in genetic hypercalciuric stone-forming rats

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