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.     

Psychosocial mechanisms of a behavioral treatment for urinary incontinence of prostate cancer survivors

Abstract

Purpose: We examined underlying psychosocial processes of a behavioral treatment for urinary incontinence (UI) of prostate cancer survivors.

Design: Secondary analysis of data collected from a clinical trial.

Sample: Two hundred forty-four prostate cancer survivors who participated in a clinical trial of behavioral intervention to UI as intervention or control subjects.

Methods: The participants had a 3-month behavioral intervention or usual care and were followed up for an additional 3?months. They were assessed at baseline, 3, and 6?months. Latent growth curve models were performed to examine trajectories of each study variable and relationships among the variables.

Findings: Increasing self-efficacy and social support were significantly and independently associated with more reduction of urinary leakage frequency over time.

Implications for psychosocial oncology: Providing problem-solving skills and social support, including peer support, are essential for empowering patients to reduce UI.     

Can Liking,Commenting, and Sharing Enhance Persuasion? The Interaction Effect between Modality Interactivity and Agency Affordances on Smokers’ Quitting Intentions

ABSTRACT

This article examines whether the persuasive potential of modality interactivity on anti-smoking websites can be harnessed by adding agency affordances, such as the like, comment, and share features. Using a 2 × 2 factorial experiment with a current smoker sample (N = 154), we investigated the interaction effects between modality interactivity (low vs. high) and agency affordances (absence vs. presence) on persuasion outcomes. The results showed that the effects of modality interactivity on telepresence, systematic processing, and change in quitting intentions varied depending on the existence of agency affordances on the website. Agency affordances on the anti-smoking website led to a greater sense of agency and systematic processing on the website content. Only in the presence of agency affordances did modality interactivity enhance the feeling of telepresence, which led to greater quitting intentions than in the control condition. Without agency affordances, modality interactivity diminished systematic processing, leading to lower quitting intentions.     

Short or Long Sleep Duration and CKD: A Mendelian Randomization Study

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A small molecule LS-1-2F promotes the endocytosis of macromolecules into tumor cells

In the previous research, we found that anticancer agent LS-1-2F could cause the vacuolation of tumor cells. Herein we investigated the effect of compound LS-1-2F on the endocytosis of macromolecules, including fluorescence quantum dots, human serum albumin, single-stranded RNA, and monoclonal antibody, into tumor cells. We found that LS-1-2F could accelerate the endocytosis of these large molecules by laser confocal microscope and flow cytometry. The effect of LS-1-2F on the improvement of the internalization efficiency of Herceptin biosimilar was particularly significant. Promoting endocytosis will help increase the efficiency of liquid-phase drug uptake in drug-resistant cancer cells and could potentially facilitate the use of drugs in nanoparticle delivery vehicles.     

Genome-Wide Meta-Analysis Identifies Three Novel Susceptibility Loci and Reveals Ethnic Heterogeneity of Genetic Susceptibility for IgA Nephropathy

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Social support and self-esteem on the association between stressful life events and mental health outcomes among college students

ABSTRACT

The purpose of this research is to determine whether social support (informal and formal) and self-esteem can moderate the associations between life stress and mental health among college students.     

生物黏附辅料对葛根总黄酮类化合物在Caco-2细胞模型中转运的影响

目的:葛根总黄酮（PTF）可治疗心脑血管疾病，但膜通透性差，口服生物利用度低。一些辅料如卡波姆、壳聚糖和羟丙基甲基纤维素可以提高口服生物利用度。传统的体外评价技术，包括大鼠肠灌流和细胞模型，不能评价PTF整体的吸收机制。方法:本研究评价辅料的黏附性及对PTF在Caco-2细胞单层模型中转运的影响。采用cDNA微阵列测定PTF和PTF+辅料给药后的Caco-2细胞的基因表达变化，从基因水平揭示辅料对PTF整体吸收的影响机制。结果:体外黏附和Caco-2细胞转运实验表明，与单独PTF相比，加入辅料后对胃黏膜具有更高的黏附性，且在Caco-2细胞模型中的转运效率更高。PTF与辅料的相互作用显著改变了某些基因的表达，可能影响PTF的吸收效率。结论:不同的生物黏附聚合物能提高PTF的肠道吸收，可能与ATP结合盒(ABC)和溶质载体转运体(SLC)的表达基因有关。