Stroke Registry Research Articles

Predicting poor functional outcomes for patients with large computed tomography perfusion core infarctions treated with endovascular thrombectomy

Objective Stroke patients with large core infarctions benefit from endovascular intervention, though only approximately 20% are functionally independent at 90 days. We studied prognostic factors for patients presenting with a large computed tomography perfusion (CTP) core. Methods Retrospective analysis from a health system stroke registry, including consecutive thrombectomy patients treated within 24 hours from August 2020-December 2022 with an anterior circulation large vessel occlusion and CTP core infarct ≥50 milliliters. Logistic regression was used to determine independent predictors of 90-day modified Rankin Scale (mRS) score 4–6. The prognostic ability of previously reported scales was also assessed. Results In 118 included patients, with mean age 64.3 ± 14.1 years, poor functional outcomes were present in 66 subjects (55.9%). The multivariable regression analysis demonstrated that higher presenting National Institutes of Health Stroke Scale (NIHSS) score (odds ratio [OR] 1.12, 95% confidence interval [CI] 1.02–1.23, p = 0.014), elevated glucose (OR 1.02, 95% CI 1.01–1.03, p = 0.002), absence of treatment with intravenous thrombolysis (OR 4.01, 95% CI 1.35–11.95, p = 0.013), and poor revascularization (OR 4.76, 95% CI 1.24–18.37, p = 0.023) were independently associated with primary outcome. The Charlotte Large artery occlusion Endovascular therapy Outcome Score (CLEOS) predicted 90-day mRS 4–6 (per 25-point increase, OR 1.22, 95% CI 1.10–1.34, p<0.001) and mRS 5–6 (per 25-point increase, OR 1.21, 95% CI 1.10–1.33, p<0.001). Nineteen of 20 (95%) patients with CLEOS ≥ 675 had 90-day mRS scores of 4–6, while 10 of 12 (83.3%) with CLEOS ≥ 725 had 90-day mRS scores of 5–6. Conclusion We report prognostic factors that can risk stratify thrombectomy patients with large CTP core infarctions.

Management of people after stroke in 383 Victorian general practices, 2014-2018: analysis of linked stroke registry and general practice data.

To evaluate the management in Victorian general practice of people who have been hospitalised with stroke or transient ischaemic attacks (TIA). Retrospective observational study; analysis of linked Australian Stroke Clinical Registry (AuSCR) and general practice data. 383 general practices in the Eastern Melbourne, South Eastern Melbourne, and Gippsland primary health networks (Victoria), 1 January 2014 - 31 December 2018. Adults who had been hospitalised with acute stroke or TIA and had at least two encounters with the same general practice during the observation period (7-18 months after the acute event). Assessment of cardiometabolic risk factors (blood pressure, serum lipids, blood glucose, urinary protein); prescribing of guideline-recommended prevention medications (blood pressure-, lipid-, or glucose-lowering, antithrombotic agents); attainment of guideline targets for cardiometabolic risk factors at final assessment during observation period. During 2014-2018, 3376 eligible AuSCR registrants (1465 women, 43.4%) had at least two encounters with one of the 383 general practices during the observation period; median age at stroke onset was 73.9 (interquartile range, 64.4-81.9) years, 737 events were TIAs (21.8%). Blood pressure was assessed in 2718 patients (80.5%), serum lipids in 1830 (54.2%), blood glucose in 1708 (50.6%). Prevention medications were prescribed for 2949 patients (87.4%), including lipid-lowering (2427, 71.9%) and blood pressure-lowering agents (2363, 70.0%). Blood glucose targets had been achieved by 1346 of 1708 patients assessed for this risk factor (78.8%), blood pressure targets by 1935 of 2717 (71.2%), and serum lipid targets by 765 of 1830 (41.8%). The incidence of having risk factors assessed was lower among patients aged 60 years or younger (incidence rate ratio [IRR], 0.97; 95% confidence interval [CI], 0.92-1.03) and those over 80 years of age (IRR, 0.92; 95% CI 0.88-0.97) than for those aged 61-80 years, and for women (IRR, 0.91; 95% CI, 0.87-0.95) and people with dementia (IRR, 0.89; 95% CI, 0.81-0.98). The likelihood of having classes of prevention medication prescribed was lower for patients aged 60 years or younger (IRR, 0.92; 95% CI, 0.88-0.97) and those over 80 years of age (IRR, 0.96; 95% CI, 0.92-0.997) than for patients aged 61-80 years, and for women (IRR, 0.95; 95% CI, 0.91-0.98) and people with dementia (IRR, 0.88; 95% CI, 0.78-0.98). The general practice management of people who have been hospitalised with stroke or TIA could be improved. Effective monitoring of cardiometabolic risk factors will enable general practitioners to optimise care for people who need careful attention to prevent adverse secondary events.

Adolescent Blood Pressure and Early Age Stroke.

Underdiagnosis of relevant risk factors has contributed to the increasing stroke incidence in young adults. Blood pressure cut-off values for adolescents are neither sex specific nor based on cardiovascular outcomes. This nationwide, population-based, retrospective cohort study included all Israeli adolescents 16-19 years of age who were medically evaluated before compulsory military service from 1985 to 2013, including routine blood pressure measurements. The primary outcome was the first occurrence of a stroke (ischemic or hemorrhagic) at a young age (≤52 years), as documented in the Israeli National Stroke Registry. Cox proportional hazard models were stratified by sex and adjusted for birth year, sociodemographic variables, and adolescent body mass index. The cohort comprised 1,897,048 adolescents (42.4% women). During 11,355,476 person-years of follow-up, there were 1470 first stroke events at a young age. In men, an adolescent diastolic blood pressure value of ≥80 mmHg, compared with the reference group (diastolic blood pressure value of <70 mmHg), was associated with an increased risk of stroke (adjusted hazard ratio 1.28; 95% confidence interval [CI], 1.04 to 1.58), while a diastolic blood pressure value of 70-79 mmHg was not associated with an increased risk of stroke (adjusted hazard ratio 1.11; 95% CI 0.90 to 1.34). Among women, an adolescent diastolic blood pressure value of ≥80 mmHg, compared with the reference group (diastolic blood pressure value of <70 mmHg) was associated with an increased risk of stroke at a young age (adjusted hazard ratio 1.38; 95% CI 1.03 to 1.88), as was a diastolic blood pressure value of 70-79 mmHg (adjusted hazard ratio 1.41; 95% CI 1.09 to 1.81). Elevated adolescent systolic blood pressure values (≥120 mmHg) were not associated with an increased risk of stroke. Diastolic blood pressure values of ≥80 mmHg in adolescence were associated with an increased risk of stroke at a young age in both men and women. No similar association was observed for elevated systolic blood pressure.

Machine learning-based prediction of one-year mortality in ischemic stroke patients

Abstract Background Accurate prediction of mortality following an ischemic stroke is essential for tailoring personalized treatment strategies. This study evaluates the effectiveness of machine learning models in predicting one-year mortality after an ischemic stroke. Methods Five machine learning models were trained using data from a national stroke registry, with logistic regression demonstrating the highest performance. The SHapley Additive exPlanations (SHAP) analysis explained the model’s outcomes and defined the influential predictive factors. Results Analyzing 8183 ischemic stroke patients, logistic regression achieved 83% accuracy, 0.89 AUC, and an F1 score of 0.83. Significant predictors included stroke severity, pre-stroke functional status, age, hospital-acquired pneumonia, ischemic stroke subtype, tobacco use, and co-existing diabetes mellitus (DM). Discussion The model highlights the importance of predicting mortality in enhancing personalized stroke care. Apart from pneumonia, all predictors can serve the early prediction of mortality risk which supports the initiation of early preventive measures and in setting realistic expectations of disease outcomes for all stakeholders. The identified tobacco paradox warrants further investigation. Conclusion This study offers a promising tool for early prediction of stroke mortality and for advancing personalized stroke care. It emphasizes the need for prospective studies to validate these findings in diverse clinical settings.

Abstract 4145883: Elevated International Normalized Ratio Is Associated with Severity of Intracerebral Hemorrhage for Patients Taking Direct Oral Anticoagulants

Introduction/Background: While the international normalized ratio (INR), a marker of functioning of the extrinsic and final common pathways of the coagulation cascade is associated with increased intracerebral hemorrhage (ICH) mortality for patients taking warfarin, it is not understood how it might be associated with outcomes in patients taking direct oral anticoagulants (DOACs), given the inconsistent and variable effect of DOACs on INR. Research Questions/Hypothesis: To determine whether INR is associated with increased ICH severity in patients with recent exposure to a DOAC. Methods/Approach: We included patients taking Apixaban or Rivaroxaban prior to acute presentation with ICH to hospitals participating in the Get With the Guidelines - Stroke registry, a nationwide quality improvement registry. The primary exposure was INR, which we modeled as a continuous variable with restricted cubic splines. The primary endpoint was stroke severity on presentation, measured by the National Institutes of Health Stroke Scale (NIHSS). Secondary endpoints included Glasgow Coma Scale (GCS) &lt;=8 on admission, in-hospital mortality, composite of in-hospital mortality and discharge to hospice, and modified Rankin Scale (mRS) at discharge. We adjusted for key confounding factors, specifically age, sex, race/ethnicity, insurance status, and medical history, while taking into account within-hospital clustering. Results/Data: In total, 13,251 patients were included of whom 7,545 were exposed to apixaban and 5,706 were exposed to rivaroxaban. As shown in Table 1, for patients taking Apixaban, elevated INR was associated with increased likelihood of NIHSS &gt;=21 (aOR 1.02 [95% CI 1.00-1.04, p=0.03] per 0.1 above 1.1) and in-hospital mortality (aOR 1.11 [95% CI 1.05-1.16, p&lt;.001) per 0.1 above 1.1). For patients taking Rivaroxaban, similar trends were seen (aOR 1.21 [95% CI 1.08-1.35, p&lt;.001] per 0.1 up to 1.2 for NIHSS &gt;=21, aOR 1.13, [95% CI 1.09-1.16, p&lt;.001] per 0.1 up to 1.6, for in-hospital mortality). Conclusion(s): Elevated INR at admission is associated with worsened ICH severity for patients taking Apixaban or Rivaroxaban.

Abstract 4119129: PREDICTING 30-DAY ALL-CAUSE READMISSION AFTER STROKE: THE APPLICATION OF MACHINE LEARNING TO LINKED REGISTRY DATA

Background: Thirty-day readmission following hospital discharge for stroke is an important quality measure for US hospitals. Current US prediction models for post stroke readmission based on electronic medical records from single healthcare systems or hospitals have modest discrimination (AUC range 0.64 - 0.74). Aim: To develop 30-day all-cause readmission prediction model using a machine learning (ML) based method trained on linked stroke registry and administrative claims data. Methods: Using probabilistic linking, we matched acute stroke (ICD-10 I61-I63) discharges from 31 hospitals participating in the Michigan Acute Stroke registry between 2016-2020 to multipayer administrative claims data provided by the Michigan Value Collaborative for Medicare and Blue Cross Blue Shield of Michigan commercial beneficiaries. Stroke registry data included patient demographics, clinical characteristics, past medical history, and treatments. Claims data was used to identify readmissions within 30 days of discharge. We used multivariable LASSO logistic regression- a simple ML technique to predict 30-day all-cause-readmission and evaluated the prediction accuracy using a hospital-split internal validation scheme to generate hospital-specific and pooled AUC estimates with 95% confidence intervals (Figure 1). Results: Of 19,382 linked stroke discharges, 2,724 (14.1%) were readmitted within 30-days. Readmitted patients were older, more likely to be male, black, and have higher stroke severity (NIHSS &gt;5). Registry hospitals were either primary (64%) or comprehensive (26%) stroke centers. Hospital-specific 30-day readmission ranged between 9.9%-23.1% ( P &lt;.001) with an average of 14.1% (95% CI:13.6%-14.5%) (Figure 2). Hospital specific AUC estimates ranged between 0.60-0.80 with a pooled AUC of 0.68 (95% CI:0.65-0.70) (Figure 2). Conclusions: ML prediction model fitted to linked registry data can be used to predict hospital-specific and statewide readmissions post stroke.

Evaluation of Door-to-Needle Stroke Patients With Thrombolytic Activation Code in Imam Reza Educational Center in Tabriz

Objectives: To investigate the therapeutic process and golden times for treating stroke patients receiving thrombolytic therapy at Imam Reza Hospital in Tabriz. Design: A cross-sectional descriptive study. Setting(s): The information for all patients entering the study was extracted from the stroke registry of the Neurosciences Research Center. Participants: Participants comprised all patients who were referred to Imam Reza Hospital emergency department (ED) in 2018, hospitalized as stroke patients, and had an indication for receiving thrombolytic therapy. Outcome measures: Data included demographic information, length of stay in the ED, time interval from the onset of symptom to ED arrival, time to CT scan, time to the start of thrombolytic therapy, outcomes (e.g., discharge, hospitalization, or death), and the use of tissue plasminogen activator (tPA) therapy. Results: A total of 140 patients were studied, with a mean and median age of 66.19±12.68 and 67.5 years, respectively. The mode age was 73 years, with the maximum age being 91 years and the minimum age being 34 years. Moreover, 82 (58.6%) of patients were male, and 58 (41.4%) were female. The mean time interval from ED arrival to the start of thrombolytic injection was 54.49±27.42 minutes, with a median and mode of 51 and 60 minutes, respectively. The minimum time was 17 minutes, and the maximum time was 218 minutes. The modified ranking scale (mRS) score at 7 days was significantly related to the National Institutes of Health Stroke Scale (NIHSS) at arrival, NIHSS 36 hours after treatment, NIHSS at 7 days after treatment, the incidence of intracerebral hemorrhage, and hospitalization duration (P≤0.001). Conclusions: Initiating thrombolytic injection within 60 minutes is feasible, and patients’ status 7 days after discharge has a significant relationship with NIHSS at arrival, NIHSS 36 hours post-treatment, and NIHSS 7 days post-treatment. Moreover, there is a significant correlation between mRS at 7 days and an interval of less than 60 minutes from ED arrival to the start of thrombolytic injection. In such cases, mRS is lower.

Impact of Ambient Air Pollution with PM2.5 on Stroke Occurrence: Data from Kaunas (Lithuania) Stroke Register (2010–2022)

Background: Ambient particulate matter of ≤2.5 μm in diameter (PM2.5) is named as a risk factor for cerebrovascular diseases. This investigation aimed to evaluate the impact of ambient air pollution with PM2.5 on stroke occurrence. Methods: The study was performed in Kaunas, Lithuania, from 2010 to 2022. The daily numbers of ISs, subarachnoid hemorrhages (SAHs), and intracerebral hemorrhages (ICHs) were obtained from the Kaunas Stroke Register. The association between stroke occurrence and PM2.5 exposure was assessed by time- and seasonally stratified Poisson regression. Results: Among middle-aged persons, 3377 had a stroke, of which 2686 (79.5%) had an IS, 469 (13.9%) had an ICH, and 222 (6.6%) had SAH. The relative risk (RR) of SAH was increased by 1.7% with an increase in daily PM2.5 by 1 μg/m3 on the same day and at a lag of 1 day, and by 2.2% with an increase in mean PM2.5 concentration at a lag 0–1 days by 1 μg/m3. The RR of having a SAH was increased by 0.7% with an increase in daily PM2.5 by 1 μg/m3 on the same day. Conclusions: Significant associations between stroke occurrence and air pollution with PM2.5 were found in the SAH and HS patients, and only in middle-aged subjects.

Preexisting Heart Disease Spectrum and In‐Hospital Outcomes for Patients With Acute Ischemic Stroke

Background Although many studies have examined the influence of individual preexisting heart conditions on stroke outcomes, the combined effects of these conditions remain understudied. Methods The data supporting this study's findings are available from the corresponding author upon reasonable request. Data on patients with acute ischemic stroke from the Third China National Stroke Registry were analyzed. Preexisting heart disease spectrum was defined based on the combination pattern of coronary heart disease, atrial fibrillation, and heart failure. In‐hospital stroke outcomes included moderate or severe stroke at admission (the National Institutes of Health Stroke Scale score ≥16), ambulation by day 2, and in‐hospital death. Results Among the 14 019 analyzed patients, 1856 (13.2%) had preexisting heart diseases, of which the most common single heart disease was coronary heart disease (1313 [70.7%]), and the most common combination was coronary heart disease and atrial fibrillation (116 [6.3%]). Patients with preexisting heart diseases had higherprevalence of moderate or severe stroke at admission (4.7% versus 1.9%; adjusted odds ratio [aOR], 2.25 [95% CI, 1.73–2.93]), in‐hospital mortality (0.5% versus 0.2%; aOR, 2.41 [95% CI, 1.11–5.25]), and a lower rate of ambulation by day 2 (73.9% versus 78.6%; aOR, 0.84 [95% CI, 0.75–0.95]). Atrial fibrillation alone (moderate or severe stroke: aOR, 4.82 [95% CI, 3.29–7.06]; in‐hospital mortality: aOR, 4.76 [95% CI, 1.58–14.36]; ambulation by day 2: aOR, 0.58 [95% CI, 0.46–0.72]) or in combination with coronary heart disease and heart failure (moderate or severe stroke: aOR, 11.47 [95% CI, 3.66–35.89]; ambulation by day 2: aOR, 0.41 [95% CI, 0.16–1.05]) had the strongest association with unfavorable outcomes. Conclusion Preexisting heart diseases, particularly atrial fibrillation combined with other heart diseases, are associated with unfavorable in‐hospital stroke outcomes.

Maximising the Quality of Stroke Care: Reporting of Data Collection Methods and Resourcing in National Stroke Registries: A Systematic Review.

Stroke registries are tools for improving care and advancing research. We aim to describe the methodology and resourcing of existing national stroke registries. We conducted a systematic search of the published, peer-reviewed literature and grey literature examining descriptions of data collection methods and resourcing of national stroke registries published from 2012 to 2023. The systematic review was registered in PROSPERO (CRD42023393841). 101 records relating to 21 registries in 19 countries were identified. They universally employed web-based platforms for data collection. The principal profession of data collectors was nursing. All included the acute phase of care, 28% (6) registered the pre-hospital (ambulance) phase and 14% (3) included rehabilitation. 80% (17) collected outcome data. The registries varied in their approach to outcome data collection; in 9 registries it was collected by hospitals, in 2 it was collected by the registry, and 7 had linkage to national administrative databases allowing follow-up of a limited number of end points. Coverage of the total number of strokes varies from 6 to 95%. Despite widespread use of Electronic Health Records (EHRs) the ability to automatically populate variables remained limited. Governance and management structures are diverse, making it challenging to compare their resourcing. Data collection for clinical registries requires time and necessary skills and imposes a significant administrative burden on the professionals entering data. We highlight the role of clinical registries as powerful instruments for quality improvement. Future work should involve creating a central repository of stroke registries to enable the development of new registries and facilitate international collaboration.

Chronic Illness and visiting clinic before hospitalization at the onset of Stroke: Shiga Registry

Abstract Background Prompt action at stroke onset is required to improve prognosis. Some previous studies indicated that visiting local clinics may initially delay access to specialized care. We examined the relationship between the presence of chronic diseases known as risk factors for stroke and visiting a local clinic before admission to the hospital for acute stroke care. Methods This study utilized data from stroke patients aged 18 and older who were registered in the Shiga Stroke and Heart Attack Registry (SSHR) from January 2011 to December 2015. We excluded cases with onset during hospitalization or those with impaired consciousness assessed by the Japan Coma Scale (JCS &amp;gt; =10). The presence of comorbid chronic diseases was determined based on the past history and medications presented at admission. Local clinics are defined as clinics or hospitals that are not equipped to provide acute stroke treatment. Multivariate logistic regression analyses, adjusting for sex, age, modified Rankin Scale score before onset, and stroke subtypes, were performed to calculate odds ratios and 95% confidence intervals for visiting a clinic before hospitalization according to the presence of chronic diseases such as hypertension, diabetes, dyslipidemia, and atrial fibrillation, respectively. Results Data from 11,111 out of 14,620 registered cases were analyzed. Among these participants, 5,774 had hypertension, 1,951 had diabetes, 2,111 had dyslipidemia, and 882 had atrial fibrillation. A total of 2,405 (21.6%) cases visited a local clinic at stroke on set. The adjusted odds ratios for visiting clinics by the presence of hypertension were (1.22, 95% CI: 1.11 -1.34), diabetes (1.14, 1.01-1.28), dyslipidemia (1.07, 0.95 -1.20), and atrial fibrillation (0.80, 0.67 -0.95). Conclusions The present study indicated that individuals with hypertension and/or diabetes are more likely to initially visit a local clinic at stroke onset, whereas those with atrial fibrillation were not. Key messages • Approximately 20% of mild stroke patients first consult local or primary care doctors at stroke onset. This trend was particularly observed in individuals with hypertension and diabetes. • Emphasizing the need for direct access to specialized emergency care for individuals with chronic diseases is important to avoid delays in acute stroke care.

High ABCD2-score after transient ischemic attack is associated with a two-fold higher stroke-rate during long-term follow-up

Abstract Background The ABCD2-score is a validated risk score used to estimate the short-term risk of stroke after transient ischemic attack (TIA). However, "real-world" contemporary data on the long-term risk of stroke after TIA according to ABCD2-score are needed in order to guide preventive strategies. Purpose To determine the long-term risk of stroke after TIA according to modified ABCD2-score (high-risk (≥4 points) versus low-risk (&amp;lt;4 points)). Methods Patients aged ≥18 years with first-time TIA were included from the Danish Stroke Registry (2014-2020). The study population was stratified in high-risk (≥4 points) and low-risk (&amp;lt;4 points) ABCD2-score group. We utilized a modified ABCD2-score consisting of the following parameters: age ≥60 years, hypertension, clinical features, and diabetes. The 3-year risk of ischemic stroke and all-cause mortality was compared between the high-risk and low-risk group using the Aalen-Johansen and Kaplan-Meier estimator. A cox regression model was also conducted. Results In total, 21,433 patients with first-time TIA were included; 1,281 (6.0%) in the high-risk and 20,152 (94.0%) in the low-risk group. Patients in the high-risk group were older (77.5 years [interquartile range [IQR] 70.8-84.1] versus 70.3 years [IQR 60.1-78.2]), more often females (52.2% versus 46.6%) (p &amp;lt;0.001), more comorbid and received more medication compared with the low-risk group at baseline. The 3-year cumulative incidence of stroke was 6.0% [95% CI: 4.6-7.5] in the high-risk group and 4.2% [95% CI: 3.9-4.5] in the low-risk group, and the unadjusted hazard ratio (HR) was 1.6 (95% CI 1.2 – 2.0) (Figure 1). The cumulative incidence of all-cause mortality within three-years after TIA was 28.9% [95% CI: 26.1-31.7] in the high-risk group and 10.3% [95% CI: 9.9-10.8] in the low-risk group. The unadjusted HR was 3.2 (95% CI 2.8 – 3.6). Conclusions Patients with high-risk ABCD2-scores had an almost two-fold higher associated long-term stroke-rate compared to those with low-risk scores. Trials focusing on preventive measures, including evidence-based antithrombotic strategies, especially for the high-risk group are warranted.

A severity comparison of leukoaraiosis in ischemic and hemorrhagic stroke: a retrospective study.

Leukoaraiosis (LA) is a common neuroradiological finding in patients suffering from stroke. Cerebral small-vessel disease (SVD) is one of the primary causes of both ischemic stroke and hemorrhagic stroke (intracerebral hemorrhage, ICH) and the development of LA. Significant evidence that LA predicts the risk of functional dependency and mortality exists. However, studies examining the difference in LA severity between ischemic stroke and hemorrhagic stroke are lacking. We therefore aimed to compare the severity and abundance of LA in the two stroke subgroups. All patients admitted to the Department of Neurology, Haukeland University Hospital, with an ischemic stroke and intracerebral hemorrhagic (ICH) stroke diagnosed between 2006 and 2020 were included in the study. We collected patient data on risk factors and clinical and radiological findings and outcomes from our local stroke registry. The presence and severity of LA were assessed using the Fazekas score based on CT imaging. We evaluated the outcome using the modified Rankin Score (mRS) 7 days post-stroke. A total of 5,084 patients were included in our analyses: 4437 (87%) with ischemic stroke and 647 (13%) with ICH. LA was present in 2476 (45%) patients. In our ordinal logistic regression model, adjusting for age, sex, known hypertension, known diabetes mellitus, and smoking, LA was more severe and more abundant in ICH patients compared to ischemic stroke patients (Fazekas score: 1, OR: 1.54; Fazekas score: 2, OR: 1.88; and Fazekas score: 3, OR 2.13; p < 0.001). Increasing severity of LA was associated with worse functional outcomes in both groups (ischemic stroke, OR: 1.49; p < 0.001 and ICH, OR: 1.36; p < 0.025). In this study, LA was more severe and abundant in patients with ICH.

Impact of age on clinical characteristics and 1-year outcomes of non-disabling ischemic cerebrovascular events: A multicenter prospective cohort study

BackgroundThe exploration of age-related clinical features and adverse outcomes of non-disabling ischemic cerebrovascular disease (NICE) has been largely unaddressed in current research. This study aimed to analyze the differences in clinical characteristics and prognostic outcomes of NICE across various age groups, utilizing data from the Xi’an Stroke Registry Study in China.MethodsThe age distribution of NICE was categorized into four groups: age ≤ 54 years, age 55–64 years, age 65–74 years, and age ≥ 75 years. Multivariate Cox logistic regression analysis was employed to evaluate the 1-year risk of outcome events in each age group of patients with NICE. A subgroup analysis was conducted to explore interaction factors influencing age-dependent outcomes in patients with NICE.ResultsThis study included 1,121 patients with NICE aged between 23 and 96 years, with an average age of 63.7 ± 12.2 years. Patients aged ≥ 75 years had a higher proportion of women, lower education levels, and a greater likelihood of having urban employee medical insurance. Those aged < 55 years had a higher prevalence of smoking, while individuals aged > 65 years showed a higher prevalence of comorbidities. Furthermore, there was a significant decrease in body mass index among patients aged ≥ 75 years. Laboratory tests indicated well-controlled blood lipids, liver function, and inflammation across all age groups, but renal function was notably reduced in patients with NICE aged ≥ 75 years. Adjusting for potential confounding factors revealed a significant increase in the one-year risk of all-cause mortality and poor prognosis among patients aged ≥ 75 years compared to those aged < 55 years, with no significant gender difference observed. Subgroup analysis indicated that patients with NICE who consumed alcohol were more prone to experience all-cause mortality with advancing age.ConclusionsAge significantly influences the clinical characteristics and prognostic outcomes of NICE patients. Clinicians should consider age-specific characteristics when diagnosing, treating, and developing prevention strategies. Tailored prevention and treatment strategies for different age groups can enhance prognosis and reduce adverse outcomes in NICE patients.

Automated Extraction of Stroke Severity From Unstructured Electronic Health Records Using Natural Language Processing.

Multicenter electronic health records can support quality improvement and comparative effectiveness research in stroke. However, limitations of electronic health record-based research include challenges in abstracting key clinical variables, including stroke severity, along with missing data. We developed a natural language processing model that reads electronic health record notes to directly extract the National Institutes of Health Stroke Scale score when documented and predict the score from clinical documentation when missing. The study included notes from patients with acute stroke (aged ≥18 years) admitted to Massachusetts General Hospital (2015-2022). The Massachusetts General Hospital data were divided into training/holdout test (70%/30%) sets. We developed a 2-stage model to predict the admission National Institutes of Health Stroke Scale, obtained from the GWTG (Get With The Guidelines) stroke registry. We trained a model with the least absolute shrinkage and selection operator. For test notes with documented National Institutes of Health Stroke Scale, scores were extracted using regular expressions (stage 1); when not documented, least absolute shrinkage and selection operator was used for prediction (stage 2). The 2-stage model was tested on the holdout test set and validated in the Medical Information Mart for Intensive Care (2001-2012) version 1.4, using root mean squared error and Spearman correlation. We included 4163 patients (Massachusetts General Hospital, 3876; Medical Information Mart for Intensive Care, 287); average age, 69 (SD, 15) years; 53% men, and 72% White individuals. The model achieved a root mean squared error of 2.89 (95% CI, 2.62-3.19) and Spearman correlation of 0.92 (95% CI, 0.91-0.93) in the Massachusetts General Hospital test set, and 2.20 (95% CI, 1.69-2.66) and 0.96 (95% CI, 0.94-0.97) in the MIMIC validation set, respectively. The automatic natural language processing-based model can enable large-scale stroke severity phenotyping from the electronic health record and support real-world quality improvement and comparative effectiveness studies in stroke.

Safety and efficacy of bridging intravenous thrombolysis plus mechanical thrombectomy versus direct mechanical thrombectomy in different age groups of acute ischemic stroke patients.

To evaluate the safety and efficacy of bridging intravenous thrombolysis plus mechanical thrombectomy (MT) versus direct MT in different age groups of patients with acute ischemic stroke (AIS) secondary to large vessel occlusion (LVO) of the anterior circulation. Consecutive patients from the prospective endovascular stroke registry of the Comprehensive Stroke Center, University of Rome Tor Vergata, Italy, between January 2015 and June 2021 were retrospectively analyzed. Patients were divided into age groups (≤ 80 years old and > 80 years old); for each age group, they were further divided in the bridging therapy group and the direct MT group. We performed a propensity score analysis according to baseline characteristics. Safety outcomes were any intracerebral hemorrhage (ICH), symptomatic ICH (sICH) and 3-month mortality. Efficacy outcomes were successful recanalization (modified Thrombolysis in Cerebral Infarction, mTICI, score ≥ 2b) and 3-month functional independence (modified Rankin Scale, mRS, ≤ 2). We included 761 AIS patients with anterior circulation LVO (mean age 73.5 ± 12.8 years; 44.8% males; mean baseline NIHSS 16 ± 5). After propensity score, there were 365 patients ≤ 80 years old (52% bridging therapy) and 187 patients > 80 years old (57% bridging therapy). In both age groups of patients, we found no statistically significant differences in the rates of any ICH, sICH, successful recanalization and 3-month mortality and functional independence between bridging therapy and direct MT groups. In our population, safety and efficacy outcomes of bridging therapy versus direct MT did not differ in both AIS patients ≤ 80 and > 80 years old.

Redefining Infarction Size for Small-Vessel Occlusion in Acute Ischemic Stroke: A Retrospective Case-Control Study.

Small-vessel occlusion, previously referred to as lacunar infarcts, accounts for approximately one-third of all ischemic strokes, using an axial diameter of less than 20 mm on diffusion-weighted imaging. However, this threshold may not adequately differentiate small-vessel occlusion from other pathologies, such as branch atheromatous disease (BAD) and embolism. This study aimed to assess the clinical significance and pathological implications of acute small subcortical infarctions (SSIs) based on infarct diameter. We conducted a retrospective case-control study using data from stroke patients recorded between 2016 and 2021 of the Stroke Registry in Chang Gung Healthcare System. Patients with acute SSIs in penetrating artery territories were included. Key variables such as patient demographics, stroke severity, and medical history were collected. Infarcts were categorized based on size, and the presence of early neurological deterioration (END) and favorable functional outcomes were assessed. Among the 855 patients with acute SSIs, the median age was 70 years and the median National Institutes of Health Stroke Scale (NIHSS) score at arrival was four. END occurred in 97 patients (11.3%). Those who experienced END were significantly less likely to achieve a favorable functional outcome compared to those who did not (18.6% vs. 59.9%, p < 0.001). The incidence of END increased progressively with infarct sizes of 15 mm or larger, with the optimal threshold for predicting END identified as 15.5 mm and for BAD, it was 12.1 mm. A multiple logistic regression analysis revealed that motor tract involvement [adjusted odds ratio (aOR) 2.3; 95% confidence interval (CI) 1.1-4.7], an initial heart rate greater than 90 beats per minute (aOR 2.3; 95% CI 1.2-4.3), and a larger infarct size (15 mm to less than 20 mm vs. 10 mm to less than 15 mm; aOR 3.0; 95% CI 1.4-6.3) were significantly associated with END. Our findings suggest that setting the upper limit for small-vessel occlusion at 15 mm would be more effective in distinguishing it from BAD. However, these findings should be interpreted in the context of the retrospective design and study population. Further multi-center research utilizing high-resolution vessel wall imaging is necessary to refine this threshold and enhance diagnostic accuracy.

Clinical Impact of Reperfusion Techniques and Occlusion Sites in Thrombectomy: Insights from the ASSIST Stroke Registry

BACKGROUND Mechanical thrombectomy has changed the landscape of acute ischemic stroke treatment, offering improved outcomes for patients with large vessel occlusions. The interplay between reperfusion techniques and occlusion sites remains a critical consideration in treatment decisions. This study investigates the impact of primary reperfusion techniques—stent retriever classic, stent retriever combination with aspiration, and direct aspiration—on procedural and clinical outcomes at different occlusion sites. METHODS Using data from the ASSIST registry, a prospective multinational initiative, patients with anterior circulation acute ischemic stroke with large vessel occlusions (n = 1477) were included. Three primary occlusion sites—M1 segment of the middle cerebral artery, M2 segment of the middle cerebral artery, and the internal carotid artery—were studied. Univariate tests and multivariable logistic regression models were used to assess associations between reperfusion techniques and procedural and clinical outcomes, including the expanded thrombolysis in cerebral infarction score and the modified Rankin Scale, stratified by occlusion site. RESULTS Achieving expanded thrombolysis in cerebral infarction ≥2c after first pass was lower in internal carotid artery occlusions (18.2%, P &lt;0.0001) with direct aspiration alone compared with stent retriever classic (38.2%) or stent retriever combination with aspiration (43.3%), while no differences were seen for M1 segment of the middle cerebral artery ( P = 0.77) and M2 segment of the middle cerebral artery ( P = 0.29) occlusions. Bailout maneuvers, which were more frequent in the direct aspiration group for all occlusion sites, did not result in longer procedure times or different final recanalization outcomes in direct aspiration compared with stent retriever classic or stent retriever combination with aspiration. Overall, there were no differences in the rate of patients with modified Rankin Scale scores of 0–2 at 90 days. No differences in safety outcomes were observed. CONCLUSIONS This study provides insight into the complex relationship between reperfusion techniques and occlusion sites in patients with acute ischemic stroke and shows that certain techniques have advantages in certain occlusion sites. As the field evolves, further research is warranted to refine our understanding of these dynamics and inform clinical practice.

Gait speed after mild stroke/transient ischemic attack was associated with long-term adverse outcomes: A cohort study.

The association between gait speed and adverse outcomes after stroke has not been fully illustrated. This study aimed to explore the association of gait speed on long-term outcomes in minor stroke or transient ischemic attack (TIA). We performed a longitudinal study with acute minor stroke or TIA based on a subgroup of the Third China National Stroke Registry data. The gait speed was evaluated using a 10-meter walking test at discharge and 3 months after the stroke onset. The primary outcomes were poor functional outcomes at 1 year, defined by a modified Rankin Score (mRS) of 2-6. Additional outcomes included all-cause death, ambulate dependency (mRS score 4-6), cognitive impairment (Montreal Cognitive Assessment <26), stroke recurrence, and composite vascular events. The study sample included a total of 1542 stroke patients with a median age of 60 (53-68). At 1-year follow-up, 140 (9.20%) patients experienced poor functional outcomes. Faster gait speed at discharge was associated with lower incidence of poor functional outcome (OR = 0.89; 95% CI, 0.84-0.94), cognitive impairment (OR = 0.93; 95% CI, 0.89-0.96), ischemic stroke recurrence (HR = 0.92; 95% CI, 0.87-0.98), and composite vascular events (HR =0.94; 95% CI, 0.89-0.99) at 1 year. Faster gait speed at 3 months was associated with lower incidence of poor functional outcome (OR = 0.90; 95% CI, 0.85-0.95), ambulate dependency (OR = 0.86; 95% CI, 0.77-0.97), and cognitive impairment (OR = 0.92; 95% CI, 0.88-0.95) at 1 year. Our findings indicated that slow gait speed after minor stroke or TIA may be an independent predictor for long-term poor outcomes. Gait speed may be considered as a vital sign during follow-up in post-stroke patients.

Predicting 3-month poor functional outcomes of acute ischemic stroke in young patients using machine learning

BackgroundPrediction of short-term outcomes in young patients with acute ischemic stroke (AIS) may assist in making therapy decisions. Machine learning (ML) is increasingly used in healthcare due to its high accuracy. This study aims to use a ML-based predictive model for poor 3-month functional outcomes in young AIS patients and to compare the predictive performance of ML models with the logistic regression model.MethodsWe enrolled AIS patients aged between 18 and 50 years from the Third Chinese National Stroke Registry (CNSR-III), collected between 2015 and 2018. A modified Rankin Scale (mRS) ≥ 3 was a poor functional outcome at 3 months. Four ML tree models were developed: The extreme Gradient Boosting (XGBoost), Light Gradient Boosted Machine (lightGBM), Random Forest (RF), and The Gradient Boosting Decision Trees (GBDT), compared with logistic regression. We assess the model performance based on both discrimination and calibration.ResultsA total of 2268 young patients with a mean age of 44.3 ± 5.5 years were included. Among them, (9%) had poor functional outcomes. The mRS at admission, living alone conditions, and high National Institutes of Health Stroke Scale (NIHSS) at discharge remained independent predictors of poor 3-month outcomes. The best AUC in the test group was XGBoost (AUC = 0.801), followed by GBDT, RF, and lightGBM (AUCs of 0.795, 0, 794, and 0.792, respectively). The XGBoost, RF, and lightGBM models were significantly better than logistic regression (P < 0.05).ConclusionsML outperformed logistic regression, where XGBoost the boost was the best model for predicting poor functional outcomes in young AIS patients. It is important to consider living alone conditions with high severity scores to improve stroke prognosis.