STARTING-SICH Nomogram to Predict Symptomatic Intracerebral Hemorrhage After Intravenous Thrombolysis for Stroke

Cappellari, Manuel; Turcato, Gianni; Forlivesi, Stefano; Zivelonghi, Cecilia; Bovi, Paolo; Bonetti, Bruno; Toni, Danilo

doi:10.1161/strokeaha.117.018427

Cited by 70 publications

(76 citation statements)

References 29 publications

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“…Furthermore, our study showed a relationship among HT and different factors, such as NIHSS score, atrial fibrillation and fasting plasma glucose values, confirming the results of previous studies [4]. A higher NIHSS score was shown to increase the risk of HT in many studies [19,20]. Severe ischemic stroke is reflected by large areas of injured brain tissue, including injured blood vessels, which are prone to bleeding after r-tPA treatment.…”

Section: Discussionsupporting

confidence: 89%

Body mass index is a risk factor for hemorrhagic transformation in older ischemic stroke patients after intravenous thrombolysis: a single center retrospective study

Miao¹,

X²,

Mu³

et al. 2019

Preprint

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Background: The aim of our study was to determine whether body mass index is a predictor of hemorrhagic transformation in acute ischemic stroke patients after intravenous thrombolysis. Methods: A retrospective observational study was conducted to recruit 261 participants from a single center in China (67.0% males, median age 65 years). A head computed tomography scan was performed after 24 hours to evaluate hemorrhagic transformation occurrence, and a computed tomography scan was performed immediately in cases of clinical worsening. Multivariate logistic regression was used to estimate the association between risk factors and hemorrhagic transformation in acute ischemic stroke patients after intravenous administration of recombinant tissue plasminogen activator. Results: Of 261 patients, 40 (15.3%) developed hemorrhagic transformation (55% males, median age 70 years). Body mass index was higher in patients with hemorrhagic transformation than in patients without hemorrhagic transformation (25.7 vs 23.7; P value, 0.013). The multivariate logistic regression model showed that body mass index was an independent predictor of hemorrhagic transformation in patients aged ≥ 73 years (odds ratio, 1.74; 95% confidence interval, 1.22-2.49) but not in patients aged < 73 years (odds ratio, 1.01; 95% confidence interval, 0.87-1.18). In addition, the odds ratio was 5.16 (95% confidence interval, 2.21-12.04) when the body mass index was ≥ 25 kg/m2 compared to a body mass index < 25 kg/m2. Conclusions: The present study demonstrated that body mass index was an independent predictor of hemorrhagic transformation in older acute ischemic stroke patients after intravenous thrombolysis. Keywords: Body mass index, Hemorrhagic transformation, Intravenous thrombolysis, Ischemic stroke, Older patients.

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Section: Discussionsupporting

confidence: 89%

Body mass index is a risk factor for hemorrhagic transformation in older ischemic stroke patients after intravenous thrombolysis: a single center retrospective study

Miao¹,

X²,

Mu³

et al. 2019

Preprint

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“…Moreover, our study also demonstrated that NHISS on admission and age are stronger, significant and independent predictors of 3-month unfavorable outcome in ischemic stroke patients. As previously reported [2,[13][14][15][27][28][29], NIHSS score constitutes a strong independent predictor of poor outcome in patients with ischemic stroke, and age contribute to a long-term mortality and unfavorable outcome, this could be due to the fact that old age is associated with one or more cardiovascular disease such as coronary artery disease, high blood pressure, high cholesterol, atrial fibrillation, heart failure, peripheral artery disease, and cerebral amyloid angiopathy.…”

Section: Discussionmentioning

confidence: 70%

A COACHS Nomogram to Predict the Probability of Three-Month Unfavorable Outcome after Acute Ischemic Stroke in Chinese Patients

et al. 2019

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Background: Accurate prognostication of unfavorable outcome made at the early onset of stroke is important to both the clinician and the patient management. This study was aimed to develop a nomogram based on the integration of parameters to predict the probability of 3-month unfavorable functional outcome in Chinese acute ischemic stroke patients. Methods: We retrospectively collected patients who underwent acute ischemic stroke at Stroke Center of the Nanjing First Hospital (China) between May 2013 and May 2018. After exclusion, the study population includes 1,025 patients for nomogram development. The main outcome measure was 3-month unfavorable outcome (modified Rankin Scale > 2). Multivariable logistic regression analysis was used to develop the predicting model, and stepwise logistic regression with the Akaike information criterion was utilized to find best-fit nomogram model. We incorporated the creatinine, fast blood glucose, age, previous cerebral hemorrhage, previous valvular heart disease, and NHISS score (COACHS), and these factors were presented with a nomogram. We assessed the discriminative performance by using the area under curve (AUC) of receiver-operating characteristic (ROC) and calibration of risk prediction model by using the Hosmer-Lemeshow test. Results: Multivariate analysis of the 1,025 patients for logistic regression helped identify the independent factors as National Institutes of Health Stroke Scale score on admission, age, previous valvular heart disease, fasting blood glucose, creatinine, and previous cerebral hemorrhage, which were included in the COACHS nomogram. The AUC-ROC of nomogram was 0.799. Calibration was good (p = 0.1376 for the Hosmer-Lemeshow test). Conclusions: The COACHS nomogram may be used to predict unfavorable outcome at 3 months after acute ischemic stroke in Chinese population. It may be also a reliable tool that is effective in its clinical utilization to risk-stratify acute stroke patients.

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“…To the best of our knowledge, there have only 2 works carried out on nomograms for individualized prediction of the ICH probability in acute ischemic stroke patients undergoing thrombolysis [11,12].…”

Section: Discussionmentioning

confidence: 99%

“…The STARTING-SICH nomogram including 10 variables was designed to predict sICH in stroke patients treated with intravenous thrombolysis in a large cohort study of Italy [11], but it has not been external validated in Asian patients and the data on ethnicity are lacking. The other nomogram model including 3 variables (present of AF, NIHSS score and glucose level on admission) was developed in Asian patients [12].…”

Section: Discussionmentioning

confidence: 99%

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A nomogram by adding atrial fibrillation to multicenter stroke survey score to predict intracranial hemorrhage in stroke patients undergoing thrombolysis

Miao

Yin

Liang

et al. 2019

Preprint

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Background: Identiﬁcation of stroke patients at risk of postthrombolysis intracranial hemorrhage (ICH) in the clinical setting is essential. However, studies in this area spare.We aimed to develop a nomogram by adding atrial fibrillation to the Multicenter Stroke Survey (MSS) score to predict the probability of ICH in acute ischemic stroke patients undergoing thrombolysis. Methods: A retrospective observational study was conducted with 287 participants from a single center (67.2% males, median age 65 years). Head computed tomography scan was performed after 24 hour to evaluate ICH occurrence, and a computed tomography scan was done immediately in case of clinical worsening. The risk factors associated with ICH were analysed. Based on multivariate logistic model, a nomogram was generated for ICH on the basis of atrial fibrillation and the MSS score. We assessed the discriminative performance by using the area under curve (AUC) of receiver-operating characteristic (ROC) and calibration of risk prediction model by using calibration plot. Results: A total of 41(14.3%) ICH events occurred.The MSS score and atrial fibrillation were independent predictors of ICH in multivariate logistic regression analysis. Discrimination of the nomogram was superior to the MSS score alone (0.794 vs 0.741; P=0.034). The model was internally validated by using bootstrap (1000 samples) with AUC-ROC of 0.795. The calibration plot showed good agreement. Conclusion: We developed and internally validated a new nomogram using the MSS score and atrial fibrillation as predictors.The nomogram is a simple and accurate tool for predicting ICH in acute ischemic stroke patients undergoing thrombolysis. Further studies are warranted to validate our findings.

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STARTING-SICH Nomogram to Predict Symptomatic Intracerebral Hemorrhage After Intravenous Thrombolysis for Stroke

Abstract: The STARTING-SICH is the first nomogram developed and validated in a large SITS-ISTR cohort for individualized prediction of sICH in intravenous thrombolysis-treated stroke patients.

Cited by 70 publications

References 29 publications

Body mass index is a risk factor for hemorrhagic transformation in older ischemic stroke patients after intravenous thrombolysis: a single center retrospective study

Body mass index is a risk factor for hemorrhagic transformation in older ischemic stroke patients after intravenous thrombolysis: a single center retrospective study

A COACHS Nomogram to Predict the Probability of Three-Month Unfavorable Outcome after Acute Ischemic Stroke in Chinese Patients

A nomogram by adding atrial fibrillation to multicenter stroke survey score to predict intracranial hemorrhage in stroke patients undergoing thrombolysis

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