Stroke最新文献

{"title":"Accuracy of Large Language Models to Identify Stroke Subtypes Within Unstructured Electronic Health Record Data.","authors":"Dylan Owens, Danh Q Nguyen, Michael Dohopolski, Justin F Rousseau, Eric D Peterson, Ann Marie Navar","doi":"10.1161/STROKEAHA.125.051993","DOIUrl":"10.1161/STROKEAHA.125.051993","url":null,"abstract":"<p><strong>Background: </strong>While <i>International Classification of Diseases, Tenth Revision</i> codes suffice for identifying stroke events in surveillance, accurately classifying stroke types and subtypes using electronic health records remains challenging due to limitations in structured data. This often necessitates manual review of clinical documentation. This study evaluated whether a large language model, Generative Pre-Trained Transformer 4 Omni (GPT-4o), can accurately identify stroke types and subtypes from unstructured clinical notes.</p><p><strong>Methods: </strong>We implemented a retrieval-augmented generation framework with GPT-4o to classify stroke types (ischemic versus hemorrhagic) and ischemic stroke subtypes using electronic health records data. The American Heart Association Get With The Guidelines-Stroke registry served as the gold standard. Model development used a 20% subset of Get With The Guidelines-Stroke-linked data from UT Southwestern Medical Center (UTSW), with the remaining 80% reserved for testing. External validation used data from the Parkland Health and Hospital System (PHHS). A total of 4123 stroke hospitalizations from January 2019 to August 2023 were included (UTSW: n=2047; PHHS: n=2076). Three prompting strategies-zero-shot chain-of-thought, expert-guided, and instruction-based-were evaluated. Predictions of GPT-4os were compared with classifications made by trained abstractors contributing to the Get With The Guidelines-Stroke registry.</p><p><strong>Results: </strong>In the external validation set, 79.6% of patients had ischemic stroke and 20.4% hemorrhagic. GPT-4o achieved 98% accuracy (95% CI, 0.97-0.99) in classifying stroke type, where accuracy reflects the overall proportion of correctly classified patients. Sensitivity was 0.98 (95% CI, 0.97-0.99), and specificity was 0.97 (95% CI, 0.96-0.98). For ischemic stroke subtypes, sensitivity ranged from 0.40 (95% CI, 0.31-0.49) for cryptogenic to 0.95 (95% CI, 0.93-0.97) for small-vessel occlusion. Specificity ranged from 0.94 (95% CI, 0.92-0.96) for large-artery atherosclerosis to 0.98 (95% CI, 0.97-0.99) for cardioembolism. Zero-shot chain-of-thought prompting-requiring minimal human input-performed comparably to more labor-intensive strategies. Consistency analysis revealed <i>></i>99% agreement across repeated queries.</p><p><strong>Conclusions: </strong>GPT-4o demonstrated strong accuracy in classifying stroke types but faced challenges with ischemic subtypes.</p>","PeriodicalId":21989,"journal":{"name":"Stroke","volume":" ","pages":"2966-2975"},"PeriodicalIF":8.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12313299/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144708815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Guidelines in Action: New Considerations for Primary Prevention of Stroke Related to Premature and Early Menopause.","authors":"Eno Inikori, Diana C Yang, Grace Tan, Jocelyn Ho, Alexis N Simpkins","doi":"10.1161/STROKEAHA.125.051442","DOIUrl":"https://doi.org/10.1161/STROKEAHA.125.051442","url":null,"abstract":"","PeriodicalId":21989,"journal":{"name":"Stroke","volume":"56 10","pages":"e310-e312"},"PeriodicalIF":8.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145126000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Guidelines in Action: Dual Threat-Ischemic and Hemorrhagic Stroke Associated With Substance Use Disorder.","authors":"Caylee R McCain, Kelsey Rose Duncan","doi":"10.1161/STROKEAHA.125.051432","DOIUrl":"https://doi.org/10.1161/STROKEAHA.125.051432","url":null,"abstract":"","PeriodicalId":21989,"journal":{"name":"Stroke","volume":"56 10","pages":"e313-e316"},"PeriodicalIF":8.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145126004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geospatial Analysis to Determine Optimal Distribution of Mobile Stroke Units.","authors":"Ryan Ramphul, Yanchen Liu, James C Grotta","doi":"10.1161/STROKEAHA.125.051756","DOIUrl":"10.1161/STROKEAHA.125.051756","url":null,"abstract":"<p><strong>Background: </strong>Mobile stroke units (MSUs) provide faster stroke treatment with improved outcomes, but are expensive, and their urban and rural deployment differs. Geospatial analysis may be useful for planning optimal MSU distribution.</p><p><strong>Methods: </strong>We geo-coded Texas state-designated level I or II stroke centers that did not overlap catchment areas and mapped 30-, 60-, 120-, and 180-minute drive time buffers around each center, superimposing them on the distribution of patients with stroke in the state, including estimates of rural, vulnerable, and minority populations within each buffer. We assumed that an MSU deployed from these MSU centers could rendezvous with emergency medical services units halfway between a rural stroke location and the destination stroke center. For each buffer, we compared the number of patients potentially served by the MSU to a base case estimate of emergency medical services transport represented by a 30-minute drive time buffer surrounding all nonoverlapping level I, II, III, or IV stroke centers.</p><p><strong>Results: </strong>We identified 11 level I and 3 level II potential MSU stroke centers. A 180-minute buffer around each of these (MSU emergency medical services rendezvous 90 minutes from the stroke center) resulted in 741 852 patients with stroke potentially receiving thrombolysis within 3 hours of stroke onset representing 99.1% adult patients with stroke in the state; a net increase of 105 522 (16.6%) patients compared with base case and a 279% increase in patients from rural areas. A 120-minute buffer increased total and rural treatments by 12.3% and 232%. A 60-minute buffer resulted in no net increase in treated patients, though 600 101 more would receive faster care by MSUs.</p><p><strong>Conclusions: </strong>When distributed using geospatial analysis, MSUs can provide faster acute stroke treatment and potentially better outcomes to virtually the entire state of Texas, with a particular increase in rural populations that are not currently reached by emergency medical services. Our findings might be useful to health care planners in any state.</p>","PeriodicalId":21989,"journal":{"name":"Stroke","volume":" ","pages":"2988-2995"},"PeriodicalIF":8.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144776150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Guidelines in Action: The Multifactorial Nature of Ischemic Stroke in Malignancy.","authors":"Cara L Doyle, Bassam E Yaghmoor, Faisal K Al-Shaibi, Sophia Sundararajan","doi":"10.1161/STROKEAHA.125.051433","DOIUrl":"https://doi.org/10.1161/STROKEAHA.125.051433","url":null,"abstract":"","PeriodicalId":21989,"journal":{"name":"Stroke","volume":"56 10","pages":"e303-e306"},"PeriodicalIF":8.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145125967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Guidelines in Action: The Role of GLP-1 (Glucagon-Like Peptide-1) Receptor Agonists in Primary Stroke Prevention.","authors":"Eno Inikori, Diana C Yang, Ava Elahi, Malak Elokour, Jocelyn Ho, Alexis N Simpkins","doi":"10.1161/STROKEAHA.125.051441","DOIUrl":"https://doi.org/10.1161/STROKEAHA.125.051441","url":null,"abstract":"","PeriodicalId":21989,"journal":{"name":"Stroke","volume":"56 10","pages":"e307-e309"},"PeriodicalIF":8.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145126012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations Between Measures of Structural Racism and Acute Ischemic Stroke Outcomes in the United States.","authors":"Sai P Polineni, Praneet Polineni, Daniel Santos, David Daniel, Mandip S Dhamoon","doi":"10.1161/STROKEAHA.124.048737","DOIUrl":"10.1161/STROKEAHA.124.048737","url":null,"abstract":"<p><strong>Background: </strong>Structural inequity, including structural racism, is linked to stroke measures. Prior work showed that ecosocial models quantifying constituent domains of structural racism are associated with acute ischemic stroke incidence. It remains unclear if such models can further account for the not-yet-fully explained racial disparities in stroke outcomes.</p><p><strong>Methods: </strong>We performed a national, population-based analysis of 71 078 619 Medicare beneficiaries aged ≥65 years enrolled in Medicare from January 1, 2016 to December 31, 2019 of whom 844 406 had a primary diagnosis of acute ischemic stroke. We estimated the odds ratio and 95% CIs of 3 outcomes (inpatient mortality, 30-day mortality, and discharge home) using multilevel logistic models, with data clustered at the county level. County-level data from the US Census Bureau and Home Mortgage Disclosure Act were used to calculate 8 measures of structural racism. These were tested separately and as a summed, normally distributed composite structural racism score for associations with the outcomes, adjusting for sex, age, urban versus other location, and Black versus White race.</p><p><strong>Results: </strong>For each SD increase in the composite structural racism score, there was a 16% increase in poststroke inpatient mortality for the total population (odds ratio, 1.160 [95% CI, 1.10-1.215]) without a significant interaction with race (<i>P</i>=0.624). Both 30-day all-cause mortality (<i>P</i>=0.035) and odds of discharge home (<i>P</i>=0.023) significantly interacted with race. For each SD increase in the composite score, Black individuals had a 4.5% increased odds of 30-day mortality and a 5.8% decreased odds of being discharged home, whereas White patients had a 6.5% increase in 30-day mortality and a 3.5% decrease in odds of discharge home.</p><p><strong>Conclusions: </strong>Increasing levels of structural racism, as calculated using validated quantitative measures of an ecosocial model of structural racism, are correlated with increasing poststroke mortality and decreased odds of discharge home, regardless of race.</p>","PeriodicalId":21989,"journal":{"name":"Stroke","volume":" ","pages":"2957-2965"},"PeriodicalIF":8.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144795534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Signature White Matter Hyperintensity Locations Associated With Vascular Risk Factors Derived From 15 653 Individuals.","authors":"J Matthijs Biesbroek, Floor A S de Kort, Devasuda Anblagan, Mark E Bastin, Alexa Beiser, Henry Brodaty, Nishi Chaturvedi, Christopher P L H Chen, Bastian Cheng, Ching-Yu Cheng, Simon R Cox, Charles DeCarli, Christian Enzinger, Evan Fletcher, Richard Frayne, Marius de Groot, Saima Hilal, Felicia Huang, M Arfan Ikram, Jiyang Jiang, Bonnie Y K Lam, Pauline Maillard, Carola Mayer, Cheryl R McCreary, Vincent Mok, Susana Muñoz Maniega, Marvin Petersen, Genady Roshchupkin, Perminder S Sachdev, Reinhold Schmidt, Stephan Seiler, Sudha Seshadri, Carole H Sudre, Götz Thomalla, Maria Valdés Hernández, Narayanaswamy Venketasubramanian, Meike W Vernooij, Elisabeth J Vinke, Joanna M Wardlaw, Wei Wen, Hugo J Kuijf, Geert Jan Biessels","doi":"10.1161/STROKEAHA.125.051159","DOIUrl":"10.1161/STROKEAHA.125.051159","url":null,"abstract":"<p><strong>Background: </strong>White matter hyperintensities (WMHs) of presumed vascular origin are common in the elderly and are associated with vascular risk factors. There is evidence that vascular risk factors, in particular hypertension, are associated with WMH in particular locations of the white matter. However, it remains unclear whether this is true for all risk factors and whether signature WMH locations differ between risk factors. We aimed to identify WMH locations associated with vascular risk factors in community-dwelling individuals.</p><p><strong>Methods: </strong>We pooled cross-sectional data from 16 population-based cohorts (15 653 individuals; mean age, 64.2±11.8 years; 52.2% female) through the Meta VCI Map Consortium. We quantified associations between WMH volumes in 50 white matter regions and 6 vascular risk factors using linear mixed models. Analyses were corrected for age, sex, study site, and total WMH volume.</p><p><strong>Results: </strong>Hypertension (B=0.141; <i>P</i><0.001), smoking (B=0.096; <i>P</i><0.001), diabetes (B=0.059; <i>P</i><0.001), and history of vascular disease (B=0.056; <i>P</i>=0.034) were significantly associated with higher total WMH volume, whereas obesity (B=0.023; <i>P</i>=0.139) and hypercholesterolemia (B=0.009; <i>P</i>=0.531) were not. After correcting for total WMH volume, hypertension was associated with WMH volume in 10 regions (ie, bilateral external capsule, superior longitudinal fasciculus, superior corona radiata, anterior limb of the internal capsule, left anterior corona radiata, and left superior fronto-occipital fasciculus), smoking (body corpus callosum), diabetes (genu corpus callosum), and obesity (left inferior fronto-occipital fasciculus), each with one region.</p><p><strong>Conclusions: </strong>Hypertension has a signature WMH pattern, whereas associations between other vascular risk factors and regional WMH volumes seem to be mainly explained by a global increase in WMH rather than region-specific effects.</p>","PeriodicalId":21989,"journal":{"name":"Stroke","volume":" ","pages":"3047-3059"},"PeriodicalIF":8.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12447828/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144883754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diminished Cerebral Oxygen Extraction and Metabolic Rate in Neonates With Hypoxic Ischemic Encephalopathy.","authors":"Dengrong Jiang, W Christopher Golden, Zhiyi Hu, Sandrine Yazbek, Aylin Tekes, Shuo Chen, Wen Shi, Yifan Gou, Jennifer Shepard, Fulden Aycan, Charlamaine Parkinson, Lina F Chalak, Hanzhang Lu, Frances J Northington, Dina El-Metwally, Peiying Liu","doi":"10.1161/STROKEAHA.125.051107","DOIUrl":"10.1161/STROKEAHA.125.051107","url":null,"abstract":"<p><strong>Background: </strong>Hypoxic ischemic encephalopathy (HIE), which is associated with perinatal disruption of cerebral oxygen supply and utilization, is a leading cause of neonatal mortality and severe neurological impairment in childhood. The present study investigated whether key physiological parameters of cerebral oxygen utilization, specifically oxygen extraction fraction (OEF), cerebral blood flow, and cerebral metabolic rate of oxygen (CMRO₂), were altered in neonates with HIE, and whether these parameters were associated with clinical indices.</p><p><strong>Methods: </strong>In this case-control study, neonates with HIE and healthy control newborns were enrolled from the Johns Hopkins Children's Center and the Children's Hospital at the University of Maryland Medical Center. The brain's hemodynamic and metabolic parameters of OEF, cerebral blood flow, and CMRO₂ were measured with noncontrast magnetic resonance imaging and were compared between neonates with HIE and controls. We studied the relationships between the brain's physiological parameters and the presence of structural brain lesions and Apgar scores in neonates with HIE and controls. Additionally, we investigated the associations between these physiological parameters and the length of stay in the neonatal intensive care unit among neonates with HIE.</p><p><strong>Results: </strong>Forty-two neonates with HIE and 54 control neonates were included. Neonates with HIE exhibited lower OEF (control, 31.2±5.2% versus HIE, 28.3±7.3%; <i>P</i>=0.02) and CMRO₂ (control, 50.4±17.3 μmol/min per 100 grams versus HIE, 34.5±13.5 μmol/min per 100 gram; <i>P</i><0.0001) compared with control neonates, whereas cerebral blood flow showed no significant difference (control, 15.9±3.9 mL/min per 100 grams versus HIE, 15.2±4.6 mL/min per 100 grams; <i>P</i>=0.61). OEF and CMRO₂ were correlated with 1-minute and 5-minute Apgar scores (<i>P</i><0.05). Among neonates with HIE, lower OEF was associated with a longer neonatal intensive care unit stay (<i>P</i>=0.003).</p><p><strong>Conclusions: </strong>These findings suggest that cerebral oxygen utilization is compromised in neonates with HIE. The physiological parameters of OEF and CMRO₂ may serve as useful biomarkers for evaluating cerebral injury and planning treatment in HIE.</p>","PeriodicalId":21989,"journal":{"name":"Stroke","volume":" ","pages":"3014-3023"},"PeriodicalIF":8.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12483023/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144761297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Device-Detected Atrial Fibrillation in Patients With and Without Cryptogenic Ischemia: The ANTARCTICA Pooled Analysis.","authors":"Shadi Yaghi, Luciano A Sposato, Liqi Shu, Daniel García-Rodríguez, Victor Castro Urda, Fabienne Kreimer, Michael Gotzmann, Stefan Greisenegger, Fadi Nahab, Qasem N Alshaer, Junpei Koge, Hajime Ikenouchi, Alkisti Kitsiou, Georgios Tsivgoulis, Sokratis Triantafyllou, Loreta Skrebelyte-Strøm, Ole Morten Rønning, Anna Tancin Lambert, Anne Hege Aamodt, Gabriella Bufano, Giulia Renda, Elisa Cuadrado Godia, Slaven Pikija, Brian H Buck, Eva Ondraskova, Jeffrey S Healey, William F McIntyre, Michael D Hill, Jeffrey L Saver, Scott E Kasner, Hooman Kamel, Mitchell S V Elkind, Lee H Schwamm, David M Kent, Aristeidis H Katsanos, Sebastian Fridman","doi":"10.1161/STROKEAHA.125.051749","DOIUrl":"10.1161/STROKEAHA.125.051749","url":null,"abstract":"<p><strong>Background: </strong>Insertable cardiac monitoring (ICM) detects atrial fibrillation (AF) in substantial proportions of cryptogenic stroke, noncryptogenic ischemic stroke without known AF, and nonstroke patients who are at risk of underlying AF. Given differences in patient characteristics across studies, there may be differences in AF detection rates on ICM across these subgroups that have not been identified. We investigate whether AF detection rates on ICM are higher in cryptogenic stroke or transient ischemic attack (C-IS/TIA) patients compared with individuals with noncryptogenic stroke or without stroke, when accounting for differences in study populations.</p><p><strong>Methods: </strong>This is an individual-participant data meta-analysis of prospective studies and randomized controlled trials of ICM in C-IS/TIA, noncryptogenic ischemic stroke, and nonstroke patients. Multilevel multivariable logistic regression models were used to test whether C-IS/TIA is associated with increased AF detection relative to other categories. We performed multiple imputation to derive values for variables with <20% missing data and used Rubin's rules to estimate adjusted odds ratios by combining 100 postimputation data sets. The primary outcome was detection of AF. The attributable risk was derived by application of Bayes' Theorem.</p><p><strong>Results: </strong>Two randomized controlled trials and 12 prospective studies were included with a total of 1562 C-IS/TIA patients and 474 non-C-IS/TIA patients. In adjusted multilevel logistic regression analyses, AF detection was higher in C-IS/TIA patients (adjusted odds ratio, 1.90 [95% CI, 1.18-3.06]; <i>P</i>=0.009), indicating that 47% of AF detected in C-IS/TIA is pathogenic. Limiting the comparator group to ischemic stroke or history of stroke yielded similar results (adjusted odds ratio, 2.83 [95% CI, 1.47-5.44]; <i>P</i>=0.002). Days to AF detection were significantly shorter in C-IS/TIA patients (median 65 versus 169; <i>P</i><0.001).</p><p><strong>Conclusions: </strong>In this individual-participant data meta-analysis of patients undergoing ICM, AF detection was higher in C-IS/TIA patients, with shorter time to AF detection compared with noncryptogenic/nonstroke individuals. These findings suggest that some of the AF detected in patients with C-IS/TIA may be pathogenic.</p>","PeriodicalId":21989,"journal":{"name":"Stroke","volume":" ","pages":"2895-2903"},"PeriodicalIF":8.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144790112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}