Mortality Outcomes in a Large Population with and without Covert Cerebrovascular Disease.

Covert cerebrovascular disease (CCD) is frequently reported on neuroimaging and associates with increased dementia and stroke risk. We aimed to determine how incidentally-discovered CCD during clinical neuroimaging in a large population associates with mortality. We screened CT and MRI reports of adults aged ≥50 in the Kaiser Permanente Southern California health system who underwent neuroimaging for a non-stroke clinical indication from 2009-2019. Natural language processing identified incidental covert brain infarcts (CBI) and/or white matter hyperintensities (WMH), grading WMH as mild/moderate/severe. Models adjusted for age, sex, ethnicity, multimorbidity, vascular risks, depression, exercise, and imaging modality. Of n=241,028, the mean age was 64.9 (SD=10.4); mean follow-up 4.46 years; 178,554 (74.1%) had CT; 62,474 (25.9%) had MRI; 11,328 (4.7%) had CBI; and 69,927 (29.0%) had WMH. The mortality rate per 1,000 person-years with CBI was 59.0 (95%CI 57.0-61.1); with WMH=46.5 (45.7-47.2); with neither=17.4 (17.1-17.7). In adjusted models, mortality risk associated with CBI was modified by age, e.g. HR 1.34 [1.21-1.48] at age 56.1 years vs HR 1.22 [1.17-1.28] at age 72 years. Mortality associated with WMH was modified by both age and imaging modality e.g., WMH on MRI at age 56.1 HR = 1.26 [1.18-1.35]; WMH on MRI at age 72 HR 1.15 [1.09-1.21]; WMH on CT at age 56.1 HR 1.41 [1.33-1.50]; WMH on CT at age 72 HR 1.28 [1.24-1.32], vs. patients without CBI or without WMH, respectively. Increasing WMH severity associated with higher mortality, e.g. mild WMH on MRI had adjusted HR=1.13 [1.06-1.20] while severe WMH on CT had HR=1.45 [1.33-1.59]. Incidentally-detected CBI and WMH on population-based clinical neuroimaging can predict higher mortality rates. We need treatments and healthcare planning for individuals with CCD.

Stratifying future stroke risk with incidentally-discovered white matter disease severity and covert brain infarct site.

BACKGROUND: Covert cerebrovascular disease (CCD) includes white matter disease (WMD) and covert brain infarction (CBI). Incidentally-discovered CCD is associated with increased risk of subsequent symptomatic stroke. However, it is unknown whether the severity of WMD or the location of CBI predicts risk. OBJECTIVES: To examine the association of incidentally-discovered WMD severity and CBI location with risk of subsequent symptomatic stroke. METHOD: This retrospective cohort study includes patients 50 years old in the Kaiser Permanente Southern California health system who received neuroimaging for a non-stroke indication between 2009-2019. Incidental CBI and WMD were identified via natural language processing of the neuroimage report, and WMD severity was classified into grades. RESULTS: 261,960 patients received neuroimaging; 78,555 (30.0%) were identified to have incidental WMD, and 12,857 (4.9%) to have incidental CBI. Increasing WMD severity is associated with increased incidence rate of future stroke. However, the stroke incidence rate in CT-identified WMD is higher at each level of severity compared to rates in MRI-identified WMD. Patients with mild WMD via CT have a stroke incidence rate of 24.9 per 1,000 person-years, similar to that of patients with severe WMD via MRI. Among incidentally-discovered CBI patients with a determined CBI location, 97.9% are subcortical rather than cortical infarcts. CBI confers a similar risk of future stroke, whether cortical or subcortical, or whether MRI- or CT-detected. CONCLUSIONS: Increasing severity of incidental WMD is associated with an increased risk of future symptomatic stroke, dependent on the imaging modality. Subcortical and cortical CBI conferred similar risks.

Management of covert brain infarction survey: A call to care for and trial this neglected population.

BACKGROUND: Covert brain infarction (CBI) is highly prevalent and linked with stroke risk factors, increased mortality, and morbidity. Evidence to guide management is sparse. We sought to gain information on current practice and attitudes toward CBI and to compare differences in management according to CBI phenotype. METHODS: We conducted a web-based, structured, international survey from November 2021 to February 2022 among neurologists and neuroradiologists. The survey captured respondents' baseline characteristics, general approach toward CBI and included two case scenarios designed to evaluate management decisions taken upon incidental detection of an embolic-phenotype and a small-vessel-disease phenotype. RESULTS: Of 627 respondents (38% vascular neurologists, 24% general neurologists, and 26% neuroradiologists), 362 (58%) had a partial, and 305 (49%) a complete response. Most respondents were university hospital senior faculty members experienced in stroke, mostly from Europe and Asia. Only 66 (18%) of respondents had established institutional written protocols to manage CBI. The majority indicated that they were uncertain regarding useful investigations and further management of CBI patients (median 67 on a slider 0-100, 95% CI 35-81). Almost all respondents (97%) indicated that they would assess vascular risk factors. Although most would investigate and treat similarly to ischemic stroke for both phenotypes, including initiating antithrombotic treatment, there was considerable diagnostic and therapeutic heterogeneity. Less than half of respondents (42%) would assess cognitive function or depression. CONCLUSIONS: There is a high degree of uncertainty and heterogeneity regarding management of two common types of CBI, even among experienced stroke physicians. Respondents were more proactive regarding the diagnostic and therapeutic management than the minimum recommended by current expert opinions. More data are required to guide management of CBI; meantime, more consistent approaches to identification and consistent application of current knowledge, that also consider cognition and mood, would be promising first steps to improve consistency of care.

Stratifying Future Stroke Risk with Incidentally Discovered White Matter Disease Severity and Covert Brain Infarct Site.

BACKGROUND: Covert cerebrovascular disease (CCD) includes white matter disease (WMD) and covert brain infarction (CBI). Incidentally discovered CCD is associated with increased risk of subsequent symptomatic stroke. However, it is unknown whether the severity of WMD or the location of CBI predicts risk. OBJECTIVES: The aim of this study was to examine the association of incidentally discovered WMD severity and CBI location with risk of subsequent symptomatic stroke. METHOD: This retrospective cohort study includes patients aged ≥50 years old in the Kaiser Permanente Southern California health system who received neuroimaging for a nonstroke indication between 2009 and 2019. Incidental CBI and WMD were identified via natural language processing of the neuroimage report, and WMD severity was classified into grades. RESULTS: A total of 261,960 patients received neuroimaging; 78,555 patients (30.0%) were identified to have incidental WMD and 12,857 patients (4.9%) to have incidental CBI. Increasing WMD severity is associated with an increased incidence rate of future stroke. However, the stroke incidence rate in CT-identified WMD is higher at each level of severity compared to rates in MRI-identified WMD. Patients with mild WMD via CT have a stroke incidence rate of 24.9 per 1,000 person-years, similar to that of patients with severe WMD via MRI. Among incidentally discovered CBI patients with a determined CBI location, 97.9% are subcortical rather than cortical infarcts. CBI confers a similar risk of future stroke, whether cortical or subcortical or whether MRI- or CT-detected. CONCLUSIONS: Increasing severity of incidental WMD is associated with an increased risk of future symptomatic stroke, dependent on the imaging modality. Subcortical and cortical CBI conferred similar risks.

Association of Incidentally Discovered Covert Cerebrovascular Disease Identified Using Natural Language Processing and Future Dementia.

Background Covert cerebrovascular disease (CCD) has been shown to be associated with dementia in population-based studies with magnetic resonance imaging (MRI) screening, but dementia risk associated with incidentally discovered CCD is not known. Methods and Results Individuals aged ≥50 years enrolled in the Kaiser Permanente Southern California health system receiving head computed tomography (CT) or MRI for nonstroke indications from 2009 to 2019, without prior ischemic stroke/transient ischemic attack, dementia/Alzheimer disease, or visit reason/scan indication suggestive of cognitive decline or stroke were included. Natural language processing identified incidentally discovered covert brain infarction (id-CBI) and white matter disease (id-WMD) on the neuroimage report; white matter disease was characterized as mild, moderate, severe, or undetermined. We estimated risk of dementia associated with id-CBI and id-WMD. Among 241 050 qualified individuals, natural language processing identified 69 931 (29.0%) with id-WMD and 11 328 (4.7%) with id-CBI. Dementia incidence rates (per 1000 person-years) were 23.5 (95% CI, 22.9-24.0) for patients with id-WMD, 29.4 (95% CI, 27.9-31.0) with id-CBI, and 6.0 (95% CI, 5.8-6.2) without id-CCD. The association of id-WMD with future dementia was stronger in younger (aged <70 years) versus older (aged ≥70 years) patients and for CT- versus MRI-discovered lesions. For patients with versus without id-WMD on CT, the adjusted HR was 2.87 (95% CI, 2.58-3.19) for older and 1.87 (95% CI, 1.79-1.95) for younger patients. For patients with versus without id-WMD on MRI, the adjusted HR for dementia risk was 2.28 (95% CI, 1.99-2.62) for older and 1.48 (95% CI, 1.32-1.66) for younger patients. The adjusted HR for id-CBI was 2.02 (95% CI, 1.70-2.41) for older and 1.22 (95% CI, 1.15-1.30) for younger patients for either modality. Dementia risk was strongly correlated with id-WMD severity; adjusted HRs compared with patients who were negative for id-WMD by MRI ranged from 1.41 (95% CI, 1.25-1.60) for those with mild disease on MRI to 4.11 (95% CI, 3.58-4.72) for those with severe disease on CT. Conclusions Incidentally discovered CCD is common and associated with a high risk of dementia, representing an opportunity for prevention. The association is strengthened when discovered at younger age, by increasing id-WMD severity, and when id-WMD is detected by CT scan rather than MRI.

Development of Parkinson Disease and Its Relationship with Incidentally Discovered White Matter Disease and Covert Brain Infarction in a Real-World Cohort.

OBJECTIVE: This study aimed to examine the relationship between covert cerebrovascular disease, comprised of covert brain infarction and white matter disease, discovered incidentally in routine care, and subsequent Parkinson disease. METHODS: Patients were ≥50 years and received neuroimaging for non-stroke indications in the Kaiser Permanente Southern California system from 2009 to 2019. Natural language processing identified incidentally discovered covert brain infarction and white matter disease and classified white matter disease severity. The Parkinson disease outcome was defined as 2 ICD diagnosis codes. RESULTS: 230,062 patients were included (median follow-up 3.72 years). A total of 1,941 Parkinson disease cases were identified (median time-to-event 2.35 years). Natural language processing identified covert cerebrovascular disease in 70,592 (30.7%) patients, 10,622 (4.6%) with covert brain infarction and 65,814 (28.6%) with white matter disease. After adjustment for known risk factors, white matter disease was associated with Parkinson disease (hazard ratio 1.67 [95%CI, 1.44, 1.93] for patients <70 years and 1.33 [1.18, 1.50] for those ≥70 years). Greater severity of white matter disease was associated with increased incidence of Parkinson disease(/1,000 person-years), from 1.52 (1.43, 1.61) in patients without white matter disease to 4.90 (3.86, 6.13) in those with severe disease. Findings were robust when more specific definitions of Parkinson disease were used. Covert brain infarction was not associated with Parkinson disease (adjusted hazard ratio = 1.05 [0.88, 1.24]). INTERPRETATION: Incidentally discovered white matter disease was associated with subsequent Parkinson disease, an association strengthened with younger age and increased white matter disease severity. Incidentally discovered covert brain infarction did not appear to be associated with subsequent Parkinson disease. ANN NEUROL 2022;92:620-630.

Risk Factors for Silent Brain Infarcts and White Matter Disease in a Real-World Cohort Identified by Natural Language Processing.

OBJECTIVE: To assess the frequency of silent brain infarcts (SBIs) and white matter disease (WMD) and associations with stroke risk factors (RFs) in a real-world population. PATIENTS AND METHODS: This was an observational study of patients 50 years or older in the Kaiser Permanente Southern California health system from January 1, 2009, through June 30, 2019, with head computed tomography or magnetic resonance imaging for nonstroke indications and no history of stroke, transient ischemic attack, or dementia. A natural language processing (NLP) algorithm was applied to the electronic health record to identify individuals with reported SBIs or WMD. Multivariable Poisson regression estimated risk ratios of demographic characteristics, RFs, and scan modality on the presence of SBIs or WMD. RESULTS: Among 262,875 individuals, the NLP identified 13,154 (5.0%) with SBIs and 78,330 (29.8%) with WMD. Stroke RFs were highly prevalent. Advanced age was strongly associated with increased risk of SBIs (adjusted relative risks [aRRs], 1.90, 3.23, and 4.72 for those aged in their 60s, 70s, and ≥80s compared with those in their 50s) and increased risk of WMD (aRRs, 1.79, 3.02, and 4.53 for those aged in their 60s, 70s, and ≥80s compared with those in their 50s). Magnetic resonance imaging was associated with a reduced risk of SBIs (aRR, 0.87; 95% CI, 0.83 to 0.91) and an increased risk of WMD (aRR, 2.86; 95% CI, 2.83 to 2.90). Stroke RFs had modest associations with increased risk of SBIs or WMD. CONCLUSION: An NLP algorithm can identify a large cohort of patients with incidentally discovered SBIs and WMD. Advanced age is strongly associated with incidentally discovered SBIs and WMD.

Acute ischaemic stroke associated with SARS-CoV-2 infection in North America.

BACKGROUND: To analyse the clinical characteristics of COVID-19 with acute ischaemic stroke (AIS) and identify factors predicting functional outcome. METHODS: Multicentre retrospective cohort study of COVID-19 patients with AIS who presented to 30 stroke centres in the USA and Canada between 14 March and 30 August 2020. The primary endpoint was poor functional outcome, defined as a modified Rankin Scale (mRS) of 5 or 6 at discharge. Secondary endpoints include favourable outcome (mRS ≤2) and mortality at discharge, ordinal mRS (shift analysis), symptomatic intracranial haemorrhage (sICH) and occurrence of in-hospital complications. RESULTS: A total of 216 COVID-19 patients with AIS were included. 68.1% (147/216) were older than 60 years, while 31.9% (69/216) were younger. Median [IQR] National Institutes of Health Stroke Scale (NIHSS) at presentation was 12.5 (15.8), and 44.2% (87/197) presented with large vessel occlusion (LVO). Approximately 51.3% (98/191) of the patients had poor outcomes with an observed mortality rate of 39.1% (81/207). Age >60 years (aOR: 5.11, 95% CI 2.08 to 12.56, p<0.001), diabetes mellitus (aOR: 2.66, 95% CI 1.16 to 6.09, p=0.021), higher NIHSS at admission (aOR: 1.08, 95% CI 1.02 to 1.14, p=0.006), LVO (aOR: 2.45, 95% CI 1.04 to 5.78, p=0.042), and higher NLR level (aOR: 1.06, 95% CI 1.01 to 1.11, p=0.028) were significantly associated with poor functional outcome. CONCLUSION: There is relationship between COVID-19-associated AIS and severe disability or death. We identified several factors which predict worse outcomes, and these outcomes were more frequent compared to global averages. We found that elevated neutrophil-to-lymphocyte ratio, rather than D-Dimer, predicted both morbidity and mortality.

Detection of symptoms of late complications after stroke in young survivors with active surveillance versus usual care.

PURPOSE: Stroke survivors develop late complications after stroke (LCAS) that impair return to pre-stroke responsibilities. Optimal strategies for detection have not been developed. We assessed differences in LCAS symptom detection among young stroke survivors undergoing active surveillance versus usual care. METHODS: This was a retrospective cohort study including patients age 18-50 with ischemic stroke, transient ischemic attack, or intracerebral hemorrhage evaluated in a Stroke Clinic between 1/1/2016-12/31/2017 with at least one outpatient evaluation during the first year after stroke. "Active surveillance" involved a semi-structured interview to elicit LCAS symptoms including headache, seizures, lethargy, mood disorders, cognitive impairment, central pain, insomnia, spasticity, dystonia, and orthostasis. "Usual care" did not involve the interview. Rates of LCAS symptom detection were assessed at 0-3 months and 3-12 months. RESULTS: One hundred twenty-one stroke survivors were included, of which 37% (45) underwent active surveillance. There were no differences in baseline characteristics except hospitalization location. Patients undergoing active surveillance were more likely to have at least one LCAS symptom detected (77% vs 49% at 0-3 months, p = 0.02; 81% vs. 54% at 3-12 months, p = 0.008). Active surveillance was more likely to detect symptoms of non-motor LCAS. There were no differences for motor LCAS. CONCLUSIONS: Active surveillance leads to higher rates of early symptom detection of non-motor LCAS in young stroke survivors.Implications for rehabilitationYoung stroke survivors frequently have late complications after stroke (LCAS) that impair return to pre-stroke responsibilities.Active surveillance for LCAS symptoms with a semi-structured interview increases detection of non-motor late complications.A bundled approach to screening for LCAS symptoms is pragmatic as a majority of young stroke survivors have at least one symptom but no single symptom is present in all stroke survivors.

Association of Silent Cerebrovascular Disease Identified Using Natural Language Processing and Future Ischemic Stroke.

BACKGROUND AND OBJECTIVES: Silent cerebrovascular disease (SCD), comprising silent brain infarction (SBI) and white matter disease (WMD), is commonly found incidentally on neuroimaging scans obtained in routine clinical care. Their prognostic significance is not known. We aimed to estimate the incidence of and risk increase in future stroke in patients with incidentally discovered SCD. METHODS: Patients in the Kaiser Permanente Southern California (KPSC) health system aged ≥50 years, without prior ischemic stroke, transient ischemic attack (TIA), or dementia/Alzheimer disease receiving a head CT or MRI between 2009 and 2019 were included. SBI and WMD were identified by natural language processing (NLP) from the neuroimage report. RESULTS: Among 262,875 individuals receiving neuroimaging, NLP identified 13,154 (5.0%) with SBI and 78,330 (29.8%) with WMD. The incidence of future stroke was 32.5 (95% confidence interval [CI] 31.1, 33.9) per 1,000 patient-years for patients with SBI: 19.3 (95% CI 18.9, 19.8) for patients with WMD and 6.8 (95% CI 6.7, 7.0) for patients without SCD. The crude hazard ratio (HR) associated with SBI was 3.40 (95% CI 3.25 to 3.56) and for WMD 2.63 (95% CI 2.54 to 2.71). With MRI-discovered SBI, the adjusted HR was 2.95 (95% CI 2.53 to 3.44) for those <65 years of age and 2.15 (95% CI 1.91 to 2.41) for those ≥65. With CT scan, the adjusted HR was 2.48 (95% CI 2.19 to 2.81) for those <65 and 1.81 (95% CI 1.71 to 1.91) for those ≥65. The adjusted HR associated with a finding of WMD was 1.76 (95% CI 1.69 to 1.82) and was not modified by age or imaging modality. DISCUSSION: Incidentally discovered SBI and WMD are common and associated with increased risk of subsequent symptomatic stroke, representing an important opportunity for stroke prevention.

Age and Acute Ischemic Stroke Outcome in North American Patients With COVID-19.

Background Acute ischemic stroke (AIS) in the context of COVID-19 has received considerable attention for its propensity to affect patients of all ages. We aimed to evaluate the effect of age on functional outcome and mortality following an acute ischemic event. Methods and Results A prospectively maintained database from comprehensive stroke centers in Canada and the United States was analyzed for patients with AIS from March 14 to September 30, 2020 who tested positive for SARS-CoV-2. The primary outcome was Modified Rankin Scale score at discharge, and the secondary outcome was mortality. Baseline characteristics, laboratory values, imaging, and thrombectomy workflow process times were assessed. Among all 126 patients with COVID-19 who were diagnosed with AIS, the median age was 63 years (range, 27-94). There were 35 (27.8%) patients with AIS in the aged ≤55 years group, 47 (37.3%) in the aged 56 to 70 group, and 44 (34.9%) in the aged >70 group. Intravenous tissue plasminogen activator and thrombectomy rates were comparable across these groups, (P=0.331 and 0.212, respectively). There was a significantly lower rate of mortality between each group favoring younger age (21.9% versus 45.0% versus 48.8%, P=0.047). After multivariable adjustment for possible confounders, a 1-year increase in age was significantly associated with fewer instances of a favorable outcome of Modified Rankin Scale 0 to 2 (odds ratio [OR], 0.95; 95 CI%, 0.90-0.99; P=0.048) and higher mortality (OR, 1.06; 95 CI%, 1.02-1.10; P=0.007). Conclusions AIS in the context of COVID-19 affects young patients at much greater rates than pre-pandemic controls. Nevertheless, instances of poor functional outcome and mortality are closely tied to increasing age.

Large-scale validation of the prediction model risk of bias assessment Tool (PROBAST) using a short form: high risk of bias models show poorer discrimination.

OBJECTIVE: To assess whether the Prediction model Risk Of Bias ASsessment Tool (PROBAST) and a shorter version of this tool can identify clinical prediction models (CPMs) that perform poorly at external validation. STUDY DESIGN AND SETTING: We evaluated risk of bias (ROB) on 102 CPMs from the Tufts CPM Registry, comparing PROBAST to a short form consisting of six PROBAST items anticipated to best identify high ROB. We then applied the short form to all CPMs in the Registry with at least 1 validation (n=556) and assessed the change in discrimination (dAUC) in external validation cohorts (n=1,147). RESULTS: PROBAST classified 98/102 CPMS as high ROB. The short form identified 96 of these 98 as high ROB (98% sensitivity), with perfect specificity. In the full CPM registry, 527 of 556 CPMs (95%) were classified as high ROB, 20 (3.6%) low ROB, and 9 (1.6%) unclear ROB. Only one model with unclear ROB was reclassified to high ROB after full PROBAST assessment of all low and unclear ROB models. Median change in discrimination was significantly smaller in low ROB models (dAUC -0.9%, IQR -6.2-4.2%) compared to high ROB models (dAUC -11.7%, IQR -33.3-2.6%; P<0.001). CONCLUSION: High ROB is pervasive among published CPMs. It is associated with poor discriminative performance at validation, supporting the application of PROBAST or a shorter version in CPM reviews.

Benefits and Risks of Dual Versus Single Antiplatelet Therapy for Secondary Stroke Prevention: A Systematic Review for the 2021 Guideline for the Prevention of Stroke in Patients With Stroke and Transient Ischemic Attack.

BACKGROUND: Dual antiplatelet therapy (DAPT) after ischemic stroke or transient ischemic attack may reduce recurrent stroke but also increase severe bleeding compared with single antiplatelet therapy (SAPT). The American Heart Association/American Stroke Association convened an evidence review committee to perform a systematic review and meta-analysis of the benefits and risks of DAPT compared with SAPT for secondary ischemic stroke prevention. METHODS: The Medline, Embase, and Cochrane databases were searched on December 5, 2019, to identify phase III or IV randomized controlled trials (n≥100) from December 1999 to December 2019. We calculated unadjusted relative risks (RRs) and performed meta-analyses of studies based on the duration of treatment (short [≤90 days] versus long [>90 days]). RESULTS: Three short-duration randomized controlled trials were identified that enrolled mostly patients with minor stroke or high risk transient ischemic attack. In these trials, DAPT, compared with SAPT, was associated with a lower 90-day risk of recurrent ischemic stroke (pooled RR, 0.68 [95% CI, 0.55-0.83], I 2=37.1%). There was no significant increase in major bleeding with DAPT in short-duration trials (pooled RR, 1.88 [95% CI, 0.93-3.83], I 2=8.9%). In 2 long-duration treatment randomized controlled trials (mean treatment duration, 18-40 months), DAPT was not associated with a significant reduction in recurrent ischemic stroke (pooled RR, 0.89 [95% CI, 0.79-1.02], I 2=1.4%), but was associated with a higher risk of major bleeding (pooled RR, 2.42 [95% CI, 1.37-4.30], I 2=75.5%). CONCLUSIONS: DAPT was more effective than SAPT for prevention of secondary ischemic stroke when initiated early after the onset of minor stroke/high-risk transient ischemic attack and treatment duration was <90 days. However, when the treatment duration was longer and initiated later after stroke or transient ischemic attack onset, DAPT was not more effective than SAPT for ischemic stroke prevention and it increased the risk of bleeding.

Agreement between neuroimages and reports for natural language processing-based detection of silent brain infarcts and white matter disease.

BACKGROUND: There are numerous barriers to identifying patients with silent brain infarcts (SBIs) and white matter disease (WMD) in routine clinical care. A natural language processing (NLP) algorithm may identify patients from neuroimaging reports, but it is unclear if these reports contain reliable information on these findings. METHODS: Four radiology residents reviewed 1000 neuroimaging reports (RI) of patients age > 50 years without clinical histories of stroke, TIA, or dementia for the presence, acuity, and location of SBIs, and the presence and severity of WMD. Four neuroradiologists directly reviewed a subsample of 182 images (DR). An NLP algorithm was developed to identify findings in reports. We assessed interrater reliability for DR and RI, and agreement between these two and with NLP. RESULTS: For DR, interrater reliability was moderate for the presence of SBIs (k = 0.58, 95 % CI 0.46-0.69) and WMD (k = 0.49, 95 % CI 0.35-0.63), and moderate to substantial for characteristics of SBI and WMD. Agreement between DR and RI was substantial for the presence of SBIs and WMD, and fair to substantial for characteristics of SBIs and WMD. Agreement between NLP and DR was substantial for the presence of SBIs (k = 0.64, 95 % CI 0.53-0.76) and moderate (k = 0.52, 95 % CI 0.39-0.65) for the presence of WMD. CONCLUSIONS: Neuroimaging reports in routine care capture the presence of SBIs and WMD. An NLP can identify these findings (comparable to direct imaging review) and can likely be used for cohort identification.

Exploiting telerobotics for sensorimotor rehabilitation: a locomotor embodiment.

BACKGROUND: Manual treadmill training is used for rehabilitating locomotor impairments but can be physically demanding for trainers. This has been addressed by enlisting robots, but in doing so, the ability of trainers to use their experience and judgment to modulate locomotor assistance on the fly has been lost. This paper explores the feasibility of a telerobotics approach for locomotor training that allows patients to receive remote physical assistance from trainers. METHODS: In the approach, a trainer holds a small robotic manipulandum that shadows the motion of a large robotic arm magnetically attached to a locomoting patient's leg. When the trainer deflects the manipulandum, the robotic arm applies a proportional force to the patient. An initial evaluation of the telerobotic system's transparency (ability to follow the leg during unassisted locomotion) was performed with two unimpaired participants. Transparency was quantified by the magnitude of unwanted robot interaction forces. In a small six-session feasibility study, six individuals who had prior strokes telerobotically interacted with two trainers (separately), who assisted in altering a targeted gait feature: an increase in the affected leg's swing length. RESULTS: During unassisted walking, unwanted robot interaction forces averaged 3-4 N (swing-stance) for unimpaired individuals and 2-3 N for the patients who survived strokes. Transients averaging about 10 N were sometimes present at heel-strike/toe-off. For five of six patients, these forces increased with treadmill speed during stance (R2 = .99; p < 0.001) and increased with patient height during swing (R2 = .71; p = 0.073). During assisted walking, the trainers applied 3.0 ± 2.8 N (mean ± standard deviation across patients) and 14.1 ± 3.4 N of force anteriorly and upwards, respectively. The patients exhibited a 20 ± 21% increase in unassisted swing length between Days 1-6 (p = 0.058). CONCLUSIONS: The results support the feasibility of locomotor assistance with a telerobotics approach. Simultaneous measurement of trainer manipulative actions, patient motor responses, and the forces associated with these interactions may prove useful for testing sensorimotor rehabilitation hypotheses. Further research with clinicians as operators and randomized controlled trials are needed before conclusions regarding efficacy can be made.

Intravenous tPA for Acute Ischemic Stroke in Patients with COVID-19.

BACKGROUND/PURPOSE: Coronavirus disease 2019 (COVID-19) is associated with increased risk of acute ischemic stroke (AIS), however, there is a paucity of data regarding outcomes after administration of intravenous tissue plasminogen activator (IV tPA) for stroke in patients with COVID-19. METHODS: We present a multicenter case series from 9 centers in the United States of patients with acute neurological deficits consistent with AIS and COVID-19 who were treated with IV tPA. RESULTS: We identified 13 patients (mean age 62 (±9.8) years, 9 (69.2%) male). All received IV tPA and 3 cases also underwent mechanical thrombectomy. All patients had systemic symptoms consistent with COVID-19 at the time of admission: fever (5 patients), cough (7 patients), and dyspnea (8 patients). The median admission NIH stroke scale (NIHSS) score was 14.5 (range 3-26) and most patients (61.5%) improved at follow up (median NIHSS score 7.5, range 0-25). No systemic or symptomatic intracranial hemorrhages were seen. Stroke mechanisms included cardioembolic (3 patients), large artery atherosclerosis (2 patients), small vessel disease (1 patient), embolic stroke of undetermined source (3 patients), and cryptogenic with incomplete investigation (1 patient). Three patients were determined to have transient ischemic attacks or aborted strokes. Two out of 12 (16.6%) patients had elevated fibrinogen levels on admission (mean 262.2 ± 87.5 mg/dl), and 7 out of 11 (63.6%) patients had an elevated D-dimer level (mean 4284.6 ±3368.9 ng/ml). CONCLUSIONS: IV tPA may be safe and efficacious in COVID-19, but larger studies are needed to validate these results.

Differences in presenting symptoms of acute stroke among young and older adults.

BACKGROUND: Prior studies demonstrated that young adults with stroke present later to medical attention, have lower initial NIHSS, and are frequently misdiagnosed as compared to older adults. We sought to assess potential differences in temporal and clinical characteristics of stroke symptoms between young (age 18-50 years) and older adults (age > 50). METHODS: This retrospective cohort study included patients age ≥ 18 years hospitalized at a comprehensive stroke center with acute ischemic stroke (AIS), transient ischemic attack (TIA), or intracerebral hemorrhage (ICH). Outcomes included progression of neurologic deficits over the first 24 h, fluctuation in neurologic deficits, and characterization of the triage chief complaint as typical or atypical (less specific) for stroke. Univariate analyses for baseline covariates were performed with Chi-square and Mann-Whitney U tests. Associations with the three outcomes were assessed with multivariable logistic regression. RESULTS: 432 adults (73 young adults, 359 older adults) were included in the analysis. Overall, 28% demonstrated progression of neurologic deficits, 14% had fluctuating deficits, and 26% presented with symptoms considered atypical for stroke. After adjustment for demographics, stroke subtype, diabetes, admission blood pressure, and acute revascularization treatments, increased age was inversely associated with progression of deficits (OR 0.97 per year of age, 95% CI 0.95-0.98) and fluctuation in deficits (OR 0.98 per year of age, 95% CI 0.96-0.99). Hemorrhagic stroke subtype was inversely associated with fluctuation in neurologic deficits (OR 0.050, CI 0.0028-0.24). CONCLUSION: Young adults are more likely to have progression or fluctuation of neurologic deficits in acute stroke. Patients with ischemic stroke are more likely to have fluctuation in neurologic deficits.

Assessment of the impact of EHR heterogeneity for clinical research through a case study of silent brain infarction.

BACKGROUND: The rapid adoption of electronic health records (EHRs) holds great promise for advancing medicine through practice-based knowledge discovery. However, the validity of EHR-based clinical research is questionable due to poor research reproducibility caused by the heterogeneity and complexity of healthcare institutions and EHR systems, the cross-disciplinary nature of the research team, and the lack of standard processes and best practices for conducting EHR-based clinical research. METHOD: We developed a data abstraction framework to standardize the process for multi-site EHR-based clinical studies aiming to enhance research reproducibility. The framework was implemented for a multi-site EHR-based research project, the ESPRESSO project, with the goal to identify individuals with silent brain infarctions (SBI) at Tufts Medical Center (TMC) and Mayo Clinic. The heterogeneity of healthcare institutions, EHR systems, documentation, and process variation in case identification was assessed quantitatively and qualitatively. RESULT: We discovered a significant variation in the patient populations, neuroimaging reporting, EHR systems, and abstraction processes across the two sites. The prevalence of SBI for patients over age 50 for TMC and Mayo is 7.4 and 12.5% respectively. There is a variation regarding neuroimaging reporting where TMC are lengthy, standardized and descriptive while Mayo's reports are short and definitive with more textual variations. Furthermore, differences in the EHR system, technology infrastructure, and data collection process were identified. CONCLUSION: The implementation of the framework identified the institutional and process variations and the heterogeneity of EHRs across the sites participating in the case study. The experiment demonstrates the necessity to have a standardized process for data abstraction when conducting EHR-based clinical studies.