Multi-inflammatory index as a new predictive and prognostic marker of acute symptomatic seizures in patients with cerebral venous sinus thrombosis

Agircan, Dilek; Bal, Mehmet; Demir, Tulin Gesoglu; Ethemoglu, Ozlem

doi:10.1016/j.jstrokecerebrovasdis.2023.107453

Cited by 2 publications

(2 citation statements)

References 40 publications

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“…Furthermore, an increase in RPR could also predict early neurological deterioration after intravenous thrombolysis in patients with AIS ( 65 ). It remains unclear whether any relationship exists between the MII-2 indicator and AIS patients, but a recent study elucidated that the MII-1 and MII-2 inflammatory markers were capable of predicting the occurrence of acute symptomatic seizures after IS ( 66 ). With advances in algorithms to develop prediction models by combining multiple variables, we can optimize models to identify the hidden complex relationships among variables, which may be of great utility in clinical practice.…”

Section: Discussionmentioning

confidence: 99%

Using a k-means clustering to identify novel phenotypes of acute ischemic stroke and development of its Clinlabomics models

Jiang,

Dang,

et al. 2024

Front. Neurol.

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ObjectiveAcute ischemic stroke (AIS) is a heterogeneous condition. To stratify the heterogeneity, identify novel phenotypes, and develop Clinlabomics models of phenotypes that can conduct more personalized treatments for AIS.MethodsIn a retrospective analysis, consecutive AIS and non-AIS inpatients were enrolled. An unsupervised k-means clustering algorithm was used to classify AIS patients into distinct novel phenotypes. Besides, the intergroup comparisons across the phenotypes were performed in clinical and laboratory data. Next, the least absolute shrinkage and selection operator (LASSO) algorithm was used to select essential variables. In addition, Clinlabomics predictive models of phenotypes were established by a support vector machines (SVM) classifier. We used the area under curve (AUC), accuracy, sensitivity, and specificity to evaluate the performance of the models.ResultsOf the three derived phenotypes in 909 AIS patients [median age 64 (IQR: 17) years, 69% male], in phenotype 1 (N = 401), patients were relatively young and obese and had significantly elevated levels of lipids. Phenotype 2 (N = 463) was associated with abnormal ion levels. Phenotype 3 (N = 45) was characterized by the highest level of inflammation, accompanied by mild multiple-organ dysfunction. The external validation cohort prospectively collected 507 AIS patients [median age 60 (IQR: 18) years, 70% male]. Phenotype characteristics were similar in the validation cohort. After LASSO analysis, Clinlabomics models of phenotype 1 and 2 were constructed by the SVM algorithm, yielding high AUC (0.977, 95% CI: 0.961–0.993 and 0.984, 95% CI: 0.971–0.997), accuracy (0.936, 95% CI: 0.922–0.956 and 0.952, 95% CI: 0.938–0.972), sensitivity (0.984, 95% CI: 0.968–0.998 and 0.958, 95% CI: 0.939–0.984), and specificity (0.892, 95% CI: 0.874–0.926 and 0.945, 95% CI: 0.923–0.969).ConclusionIn this study, three novel phenotypes that reflected the abnormal variables of AIS patients were identified, and the Clinlabomics models of phenotypes were established, which are conducive to individualized treatments.

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Section: Discussionmentioning

confidence: 99%

Using a k-means clustering to identify novel phenotypes of acute ischemic stroke and development of its Clinlabomics models

Jiang,

Dang,

et al. 2024

Front. Neurol.

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“…In another study, the prognostic and predictive abilities of MII-1 and MII-2 for acute symptomatic seizures in patients with cerebral venous sinus thrombosis (CVST) were searched. In the study, MII-1 and MII-2 were detected to significantly predict the occurrence of seizures in CVST, and it was stated that these indexes could be utilized as novel prognostic and predictive hematological markers of acute symptomatic seizures in patients with CVST [29]. Furthermore, apart from these aforementioned studies related to the prognostic and/or predictive role of MII in various cardiovascular diseases, in an interesting study, the relationship of MII-1 and MII-2 with mortality was investigated in operated patients due to Stanford type A aortic dissection.…”

Section: Discussionmentioning

confidence: 99%

Multi-inflammatory index as a novel predictor of new-onset atrial fibrillation after off-pump coronary artery bypass grafting

Yuksel,

Velioglu,

Atasoy

et al. 2024

Pol Heart J

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Multi-inflammatory index as a new predictive and prognostic marker of acute symptomatic seizures in patients with cerebral venous sinus thrombosis

Cited by 2 publications

References 40 publications

Using a k-means clustering to identify novel phenotypes of acute ischemic stroke and development of its Clinlabomics models

Using a k-means clustering to identify novel phenotypes of acute ischemic stroke and development of its Clinlabomics models

Multi-inflammatory index as a novel predictor of new-onset atrial fibrillation after off-pump coronary artery bypass grafting

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