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.     

Children’s right to smoke-free air: Public support in Norway for banning smoking in vehicles with children present

Background

Children have a statutory right to a smoke-free environment, and tobacco control advocates are now considering regulation of smoking behavior in the private sphere. The Norwegian Institute of Public Health has investigated the support for a ban on smoking in cars with children compared to other possible extensions of the tobacco act among the Norwegian public.

Optimizing resilience and wellbeing for healthcare professions trainees and healthcare professionals during public health crises – Practical tips for an ‘integrative resilience’ approach

Abstract

Public health crises, including pandemics, are associated with significant health risk and concomitant stress, fear, decreased sense of control, and uncertainty. Deleterious impact on both physical and mental health can result, including for healthcare professionals and health professions trainees. Changes in governmental policies and hospital protocols for healthcare professionals as well as disruption of educational formats and requirements for trainees can ensue. Difficult anxiety-provoking realities of public health crises including pandemics which involve caring for many seriously ill patients, moral distress including difficult care decisions, personal health risk, and/or potential risk to one’s family can take a dire toll on the mental health of healthcare professionals at all stages of the professional lifecycle. Educational disruptions can create significant anxiety for trainees about completing requirements and achieving competencies. Within this, coping skills may be challenged and strengths may be elucidated as well. Such crises create an imperative for medical educators to support trainees’ wellbeing through adaptive flexibility for curriculum innovation and culturally sensitive resilience and wellbeing interventions. Strategies (‘tips’) to optimize resilience and wellbeing with an integrative resilience approach of individual, learning environment, and organization/systems factors are presented.     

Prolonged mechanical ventilation after cardiac surgery: substudy of the Transfusion Requirements in Cardiac Surgery III trial

Purpose

Prolonged mechanical ventilation (MV) is a major complication following cardiac surgery. We conducted a secondary analysis of the Transfusion Requirements in Cardiac Surgery (TRICTS) III trial to describe MV duration, identify factors associated with prolonged MV, and examine associations of prolonged MV with mortality and complications.

Methods

Four thousand, eight hundred and nine participants undergoing cardiac surgery at 71 hospitals worldwide were included. Prolonged MV was defined based on the Society of Thoracic Surgeons definition as MV lasting 24 hr or longer. Adjusted associations of patient and surgical factors with prolonged MV were examined using multivariable logistic regression. Associations of prolonged MV with complications were assessed using odds ratios, and adjusted associations between prolonged MV and mortality were evaluated using multinomial regression. Associations of shorter durations of MV with survival and complications were explored.

Results

Prolonged MV occurred in 15% (725/4,809) of participants. Prolonged MV was associated with surgical factors indicative of complexity, such as previous cardiac surgery, cardiopulmonary bypass duration, and separation attempts; and patient factors such as critical preoperative state, left ventricular impairment, renal failure, and pulmonary hypertension. Prolonged MV was associated with perioperative but not long-term complications. After risk adjustment, prolonged MV was associated with perioperative mortality; its association with long-term mortality among survivors was weaker. Shorter durations of MV were not associated with increased risk of mortality or complications.

Conclusion

In this substudy of the TRICS III trial, prolonged MV was common after cardiac surgery and was associated with patient and surgical risk factors. Although prolonged MV showed strong associations with perioperative complications and mortality, it was not associated with long-term complications and had weaker association with long-term mortality among survivors.

Study registration

www.ClinicalTrials.gov (NCT02042898); registered 23 January 2014. This is a substudy of the Transfusion Requirements in Cardiac Surgery (TRICS) III trial.

     

Empowering future physicians to advocate for health equity: A blueprint for a longitudinal thread in undergraduate medical education

Abstract

In light of a growing body of evidence demonstrating pervasive health disparities, medical schools are increasingly incorporating educational programs on social medicine in undergraduate and graduate medical curricula. In 2015, we significantly restructured the cultural competency instruction for medical students at our institution, focusing on achieving greater health equity through caring for vulnerable populations and acknowledging and addressing bias and stereotyping. In order to facilitate educational sustainability while students were immersed in clinical care, a key element of our approach included extending teaching into the clerkship year. The resulting longitudinal thread, Health Equity and Social Justice, empowers future physicians with the knowledge and skills to work towards greater health equity. This article discusses the lessons learned in the implementation of this novel educational program. Our approach can serve as a model for other institutions considering similar instructional reform.     

Comparison of Patch Materials for Pulmonary Artery Reconstruction

Graphical abstract summarizing the overall results of our study comparing reintervention for a main or central branch pulmonary artery reconstruction site and various patch materials. Autologous pericardium was associate with the lowest reintervention and was free. Multivariable analysis demonstrated lack of superiority of homograft branch patch, which clearly has a much higher cost.

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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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A Diagnostic Algorithm for Posterior Fossa Tumors in Children: A Validation Study

BACKGROUND AND PURPOSE:Primary posterior fossa tumors comprise a large group of neoplasias with variable aggressiveness and short and long-term outcomes. This study aimed to validate the clinical usefulness of a radiologic decision flow chart based on previously published neuroradiologic knowledge for the diagnosis of posterior fossa tumors in children.MATERIALS AND METHODS:A retrospective study was conducted (from January 2013 to October 2019) at 2 pediatric referral centers, Children''s Hospital of Philadelphia, United States, and Great Ormond Street Hospital, United Kingdom. Inclusion criteria were younger than 18 years of age and histologically and molecularly confirmed posterior fossa tumors. Subjects with no available preoperative MR imaging and tumors located primarily in the brain stem were excluded. Imaging characteristics of the tumors were evaluated following a predesigned, step-by-step flow chart. Agreement between readers was tested with the Cohen κ, and each diagnosis was analyzed for accuracy.RESULTS:A total of 148 cases were included, with a median age of 3.4 years (interquartile range, 2.1–6.1 years), and a male/female ratio of 1.24. The predesigned flow chart facilitated identification of pilocytic astrocytoma, ependymoma, and medulloblastoma sonic hedgehog tumors with high sensitivity and specificity. On the basis of the results, the flow chart was adjusted so that it would also be able to better discriminate atypical teratoid/rhabdoid tumors and medulloblastoma groups 3 or 4 (sensitivity = 75%–79%; specificity = 92%–99%). Moreover, our adjusted flow chart was useful in ruling out ependymoma, pilocytic astrocytomas, and medulloblastoma sonic hedgehog tumors.CONCLUSIONS:The modified flow chart offers a structured tool to aid in the adjunct diagnosis of pediatric posterior fossa tumors. Our results also establish a useful starting point for prospective clinical studies and for the development of automated algorithms, which may provide precise and adequate diagnostic tools for these tumors in clinical practice.

In the past 10 years, there has been an exponential increase in knowledge of the molecular characteristics of pediatric brain tumors, which was only partially incorporated in the 2016 World Health Organization Classification of Tumors of the Central Nervous System.¹ The main update in the 2016 Classification was the introduction of the molecular profile of a tumor as an important factor for predicting different biologic behaviors of entities which, on histology, look very similar or even indistinguishable.² A typical example is the 4 main groups of medulloblastoma: wingless (WNT), sonic hedgehog (SHH) with or without the p53 mutation, group 3, and group 4. Although they may appear similar on microscopy, these categories have distinct molecular profiles, epidemiology, prognosis, and embryologic origin.³Subsequent to the publication of the 2016 World Health Organization Classification, further studies have identified even more molecular subgroups of medulloblastoma with possible prognostic implications⁴ and also at least 3 new molecular subgroups of atypical teratoid/rhabdoid tumor (AT/RT)⁵ and several subgroups of ependymoma.⁶ MR imaging shows promise as a technique for differentiating histologic tumors and their molecular subgroups. This capability relies on not only various imaging characteristics but also the location and spatial extension of the tumor, evident on MR imaging, which can be traced to the embryologic origin of the neoplastic cells.^5,7-10One approach to the challenge of identifying imaging characteristics of different tumors in children is to use artificial intelligence. Yet despite this exciting innovation, correctly identifying the location of the mass and its possible use as an element for differential diagnosis still requires the expertise of an experienced radiologist. Previously, D''Arco et al¹¹ proposed a flow chart (Fig 1) for the differential diagnosis of posterior fossa tumors in children based on epidemiologic, imaging signal, and location characteristics of the neoplasm. The aims of the current study were the following: 1) to validate, in a retrospective, large cohort of posterior fossa tumors from 2 separate pediatric tertiary centers, the diagnostic accuracy of that flow chart, which visually represents the neuroadiologist''s mental process in making a diagnosis of posterior fossa tumors in children, 2) to describe particular types of posterior fossa lesions that are not correctly diagnosed by the initial flow chart, and 3) to provide an improved, clinically accessible flow chart based on the results.Open in a separate windowFIG 1.Predesigned radiologic flow chart created according to the literature before diagnostic accuracy analysis. The asterisk indicates brain stem tumors excluded from the analysis. Double asterisks indicate relative to gray matter. Modified with permission from D''Arco et al.¹¹     

Incidence,Characteristics, and Outcome of COVID-19 in Adults on Kidney Replacement Therapy: A Regionwide Registry Study

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