Stroke Recurrence Following 28 Days After First Stroke in Men and Women 2012 to 2020: Observations From the Swedish Stroke Register

Eriksson, Marie; Grundberg, Anton; Inge, Erik; Euler, Mia von

doi:10.1161/jaha.122.028222

Cited by 3 publications

(1 citation statement)

References 19 publications

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“… 33 Previous studies have clearly demonstrated that the risk of death is substantially greater after a recurrent stroke than after the first stroke, 34 despite a decrease in the risk of stroke recurrence. 35 These findings may argue for using aggregated recurrent stroke and mortality as the primary endpoint in stroke research. 33 Combining recurrent stroke and mortality allowed for an evaluation of the overall impact and consequences of the event or intervention on patient health.…”

Section: Methodsmentioning

confidence: 99%

Development and internal validation of machine learning–based models and external validation of existing risk scores for outcome prediction in patients with ischaemic stroke

Axford,

Sohel,

Abedi

et al. 2023

European Heart Journal - Digital Health

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Aims We developed new machine learning (ML) models and externally validated existing statistical models [ischaemic stroke predictive risk score (iScore) and totalled health risks in vascular events (THRIVE) scores] for predicting the composite of recurrent stroke or all-cause mortality at 90 days and at 3 years after hospitalization for first acute ischaemic stroke (AIS). Methods and results In adults hospitalized with AIS from January 2005 to November 2016, with follow-up until November 2019, we developed three ML models [random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGBOOST)] and externally validated the iScore and THRIVE scores for predicting the composite outcomes after AIS hospitalization, using data from 721 patients and 90 potential predictor variables. At 90 days and 3 years, 11 and 34% of patients, respectively, reached the composite outcome. For the 90-day prediction, the area under the receiver operating characteristic curve (AUC) was 0.779 for RF, 0.771 for SVM, 0.772 for XGBOOST, 0.720 for iScore, and 0.664 for THRIVE. For 3-year prediction, the AUC was 0.743 for RF, 0.777 for SVM, 0.773 for XGBOOST, 0.710 for iScore, and 0.675 for THRIVE. Conclusion The study provided three ML-based predictive models that achieved good discrimination and clinical usefulness in outcome prediction after AIS and broadened the application of the iScore and THRIVE scoring system for long-term outcome prediction. Our findings warrant comparative analyses of ML and existing statistical method–based risk prediction tools for outcome prediction after AIS in new data sets.

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Section: Methodsmentioning

confidence: 99%

Development and internal validation of machine learning–based models and external validation of existing risk scores for outcome prediction in patients with ischaemic stroke

Axford,

Sohel,

Abedi

et al. 2023

European Heart Journal - Digital Health

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Sex Differences in the Evaluation and Treatment of Stroke

Singh

McCullough

2023

Handbook of Experimental Pharmacology

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Prediction Value of High Serum Pentraxin-3 for Short-Term Recurrence of Cerebral Infarction in Patients Accompanied with Intracranial Atherosclerotic Stenosis Within One Year

Cao,

Chen,

Yang

et al. 2024

IJGM

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Objective Elevated serum pentraxin-3 levels are generally considered a risk factor for atherosclerosis. However, there is limited data on the relationship between pentraxin-3 and cerebral infarction (CI) accompanied by intracranial atherosclerotic stenosis (ICAS). This study aims to investigate the association between pentraxin-3 (PTX-3) and short-term recurrence in cerebral infarction caused by ICAS patients within one year. Methods A prospective observational study was conducted. Cerebral infarction accompanied by intracranial atherosclerotic stenosis (CI-ICAS) patients were selected from January 2020 to December 2023. Recurrent ischemic stroke (RIS) is defined as a new neurological deficit that appears after a period of clinical stabilization, lasting more than 24 hours, with an attributable new ischemic lesion that can be confirmed by CT or MRI. Serum pentraxin-3 levels were determined on admission. Multivariate logistic regression analysis was used to investigate the relationship between serum pentraxin-3 and RIS. Results Among 398 patients enrolled, 112 cases (28.1%) had recurrence within one year. The elevation of serum PTX-3 level in patients accompanied with ICAS was independently correlated with recurrent stroke. Therefore, it is worth considering the possibility of intervening in higher PTX-3 levels. Serum pentraxin-3 was significantly higher in patients with RIS (15.16 vs 10.21 µmol/L, P <0.001). Correlation analysis showed that PTX-3 was correlated with age, LDL, Hs-CRP, Baseline NIHSS score, and Hcy ( P < 0.001). Univariate logistic regression analysis showed that pentraxin-3 remained an independent predictor of recurrent ischemic stroke after adjusting for major confounding factors (OR = 1.21, 95% CI: 1.06–1.39, P = 0.007). Conclusion The elevation of serum pentraxin-3 level in patients with ischemic stroke was independently correlated with the recurrence of stroke within one year. Therefore, intervention in serum pentraxin-3 levels may be worth considering.

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Stroke Recurrence Following 28 Days After First Stroke in Men and Women 2012 to 2020: Observations From the Swedish Stroke Register

Cited by 3 publications

References 19 publications

Development and internal validation of machine learning–based models and external validation of existing risk scores for outcome prediction in patients with ischaemic stroke

Development and internal validation of machine learning–based models and external validation of existing risk scores for outcome prediction in patients with ischaemic stroke

Sex Differences in the Evaluation and Treatment of Stroke

Prediction Value of High Serum Pentraxin-3 for Short-Term Recurrence of Cerebral Infarction in Patients Accompanied with Intracranial Atherosclerotic Stenosis Within One Year

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