The role of s100b as a predictor of the functional outcome in geriatric patients with acute cerebrovascular stroke

Abdel-Ghaffar, Walae E.; Ahmed, Soha Magdy; Reweny, Ehab M El; Elfatatry, Amr; Elmesky, Mona; Hashad, Doaa

doi:10.1186/s41983-019-0105-8

Cited by 4 publications

(4 citation statements)

References 27 publications

(35 reference statements)

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“…They found a strong correlation on day 3, but not on day 1. The AUC calculated based on the ROC curve was characterized by a high sensitivity and specificity (91.0% and 80.0%, respectively) and was similar to our results [25]. The lack of correlation on day 1 may be due to the methodology as the measurement of the S100B level can vary in time up to several minutes.…”

Section: Discussionsupporting

confidence: 84%

Predicting Short- and Long-Term Functional Outcomes Based on Serum S100B Protein Levels in Patients with Ischemic Stroke

Jalali,

Zwiernik,

Rotkiewicz

et al. 2024

JPM

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Background: Ischemic stroke is one of the leading causes of mortality and disability. The neuroimaging methods are the gold standard for diagnostics. Biomarkers of cerebral ischemia are considered to be potentially helpful in the determination of the etiology and prognosis of patients with ischemic stroke. Aim: This study aimed to investigate the usefulness of serum S100B protein levels as a short- and long-term prognostic factor in patients with ischemic stroke. Study design and methods: The study group comprised 65 patients with ischemic stroke. S100B protein levels were measured by immunoenzymatic assay. Short-term functional outcome was determined by the NIHSS score on day 1 and the difference in the NIHSS scores between day 1 and day 9 (delta NIHSS). Long-term outcome was assessed by the modified Rankin Scale (MRS) at 3 months after the stroke. At the end of the study, patients were divided into groups based on the NIHSS score on day 9 (0–8 “good” and >8 “poor”), the delta NIHSS (“no improvement” ≤0 and >0 “improvement”), and the MRS (“good” 0–2 and >2 “poor”). Differences in S100B levels between groups were analyzed with the ROC curve to establish the optimal cut-off point for S100B. The odds ratio was calculated to determine the strength of association. Correlations between S100B levels at three time points and these variables were evaluated. Results: We revealed a statistically significant correlation between S100B levels at each measurement point (<24 h, 24–48 H, 48–72 h) and the NIHSS score on day 9 (R Spearman 0.534, 0.631, and 0.517, respectively) and the MRS score after 3 months (R Spearman 0.620, 0.657, and 0.617, respectively). No statistically significant correlation was found between S100B levels and the delta NIHSS. Analysis of the ROC curve confirmed a high sensitivity and specificity for S100B. The calculated AUC for the NIHSS on day 9 were 90.2%, 95.0%, and 82.2%, respectively, and for the MRS, 83.5%, 83.4%, and 84.0%, respectively. After determining the S100B cut-off, the odds ratio for beneficial effect (NIHSS ≤ 8 at day 9 or MRS 0–2 after 3 months) was determined for each sampling point. Conclusion: S100B is a useful marker for predicting short- and long-term functional outcomes in patients with ischemic stroke.

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Section: Discussionsupporting

confidence: 84%

Predicting Short- and Long-Term Functional Outcomes Based on Serum S100B Protein Levels in Patients with Ischemic Stroke

Jalali,

Zwiernik,

Rotkiewicz

et al. 2024

JPM

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“…S100B is a member of the S100 protein superfamily. It is an intracellular protein found in glial cells and Schwann cells and is released into the blood circulation following cellular activation caused by tissue damage [ 24 , 25 ]. Zhou et al, (2016) reported a sensitivity of 95.7% and specificity of 70.4% for stroke for S100B, as well as an area under the curve (AUC) of 0.903 in differentiating between IS and intracranial haemorrhage (ICH) [ 18 ].…”

Section: Resultsmentioning

confidence: 99%

“…Zhou et al, (2016) reported a sensitivity of 95.7% and specificity of 70.4% for stroke for S100B, as well as an area under the curve (AUC) of 0.903 in differentiating between IS and intracranial haemorrhage (ICH) [ 18 ]. In another study, this biomarker was found useful in predicting the patient’s short-term functional outcome after a stroke event [ 24 ]. However, the elevations of the plasma levels of this biomarker in other neurological and neuropsychological disorders such as Alzheimer’s disease and schizophrenia means it would be of a reduced value in triaging the suspected patients for stroke [ 25 ].…”

Section: Resultsmentioning

confidence: 99%

Blood Biomarkers for Triaging Patients for Suspected Stroke: Every Minute Counts

Jadav

Mortazavi

Yee

2022

JCM

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Early stroke diagnosis remains a big challenge in healthcare partly due to the lack of reliable diagnostic blood biomarkers, which in turn leads to increased rates of mortality and disability. Current screening methods are optimised to identify patients with a high risk of cardio-vascular disease, especially among the elderly. However, in young adults and children, these methods suffer low sensitivity and specificity and contribute to further delays in their triage and diagnosis. Accordingly, there is an urgent need to develop reliable blood biomarkers for triaging patients suspected of stroke in all age groups, especially children and young adults. This review explores some of the existing blood biomarkers, as single biomarkers or biomarker panels, and examines their sensitivity and specificity for predicting stroke. A review was performed on PubMed and Web of Science for journal articles published in English during the period 2001 to 2021, which contained information regarding biomarkers of stroke. In this review article, we provide comparative information on the availability, clinical usefulness, and time-window periods of seven single blood biomarkers and five biomarker panels that have been used for predicting stroke in emergency situations. The outcomes of this review can be used in future research for developing more effective stroke biomarkers.

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“…In general, biomarkers assessing the outcome and prognosis of stroke utilize speci c parameters from blood test. 1 Several biomarkers that can predict short-term and long-term outcomes of stroke patients include high sensitive C-Reactive Protein (hs-CRP) 2 , homocysteine 1,3 , D-dimer 4 , interleukin-6 (IL-6) 5 , matrix metalloproteinase (MMP) 6 , S100β 7 , vascular endothelial growth factor (VEGF) 8 , glycated hemoglobin (HbA1c) 9 , and hyperglycemia. 10 Stress hyperglycemia ratio (SHR) is one of the parameters that can be used as a biomarker of clinical outcomes of ischemic stroke.…”

Section: Introductionmentioning

confidence: 99%

Stress Hyperglycemia Ratio Predicts Neurological Deterioration during Stroke Patient Hospitalization

Utomo,

Prodjohardjono,

Gofir

2023

Preprint

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Background: Clinical parameters have been largely studied as a prognostic biomarker for stroke patients. Stress hyperglycemia ratio (SHR) is one of potential and affordable biomarkers to predict acute ischemic stroke outcome. Its ability to predict neurological deterioration in acute ischemic stroke remain demonstrates variable results in previous studies particularly in diabetic group. This research aims to study the association between SHR and neurological deterioration in ischemic stroke patient during hospitalization, especially in Indonesia population. Methods: This is a retrospective cohort utilizing in-patient data from Stoke Unit Registry of Sardjito General Hospital from January 2020 until December 2022 to obtain first-ever ischemic stroke. The researchers applied inclusion and exclusion criteria for the subjects. Stress hyperglycemia ratio represents ratio between random blood glucose at admission and estimated mean glucose. Neurological deterioration is at discharge and admission difference of NIHSS (National Institutes of Health Stroke Scale) or Delta NIHSS. Results: Of the 207 subjects who met criteria, there was 15.5% incidence of neurological deterioration during acute care (mean 5 days). Most subjects (85%) had mild and moderate NIHSS (score 0-15), and ASPECT score >7 (78.3%). The DM group was 32.9%. Hyperglycemia and increased SHR were more prevalent in the DM group. SHR with a cut-off of 1,147 was associated with neurological deterioration with a sensitivity of 50% and specificity of 71.4% (OR=2.14, p=0.017). Hyperglycemia, DM, HbA1c, and baseline NIHSS had no significant association with neurological deterioration (p>0,05). On subgroup analysis, SHR with the same cut-off had a significant association (p<0.009, OR=3.77) only in the non-DM group. Other variables associated with neurological worsening were dyslipidemia (OR=0.414, p=0.042) and sepsis (OR=4.827, p=0.031). Conclusion: SHR predicts neurological deterioration in the first-ever acute ischemic stroke population. In subgroup analysis SHR is significantly associated with neurological deterioration in non-DM group only.

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The role of s100b as a predictor of the functional outcome in geriatric patients with acute cerebrovascular stroke

Cited by 4 publications

References 27 publications

Predicting Short- and Long-Term Functional Outcomes Based on Serum S100B Protein Levels in Patients with Ischemic Stroke

Predicting Short- and Long-Term Functional Outcomes Based on Serum S100B Protein Levels in Patients with Ischemic Stroke

Blood Biomarkers for Triaging Patients for Suspected Stroke: Every Minute Counts

Stress Hyperglycemia Ratio Predicts Neurological Deterioration during Stroke Patient Hospitalization

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