Hematoma Expansion in Intracerebral Hemorrhage With Unclear Onset

Morotti, Andrea; Boulouis, Grégoire; Charidimou, Andreas; Li, Qi; Poli, Loris; Costa, Paolo; Giuli, Valeria De; Leuci, Eleonora; Mazzacane, Federico; Busto, Giorgio; Arba, Francesco; Brancaleoni, Laura; Giacomozzi, Sebastiano; Simonetti, L.; Laudisi, Michele; Micieli, Giuseppe; Cavallini, Anna; Candeloro, Elisa; Gamba, Massimo; Magoni, Mauro; Warren, Andrew; Anderson, Christopher; Gurol, M. Edip; Biffi, Alessandro; Viswanathan, Anand; Casetta, Ilaria; Fainardi, Enrico; Zini, Andrea; Pezzini, Alessandro; Padovani, Alessandro; Greenberg, Steven M.; Rosand, Jonathan; Goldstein, Joshua N.

doi:10.1212/wnl.0000000000011895

Cited by 17 publications

(19 citation statements)

References 46 publications

(77 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…48 Also, the quicker identification of an ICH as underlying cause of the symptoms and the emergency site management by specialised teams can lead to an earlier individualised blood pressure management, which has been shown to influence haematoma expansion and subsequent clinical outcome. 35,[74][75][76][77] Another advantage of the prehospital patient assessment is the possibility of emergency site reversal of anticoagulants to control haematoma volume in patients with anticoagulant-related ICH. 36,78,79 All-cause mortality of ICH patients at 7 and 90 days was not different in MSU treated compared to standard care patients.…”

Section: Discussionmentioning

confidence: 99%

European Stroke Organisation (ESO) guidelines on mobile stroke units for prehospital stroke management

Walter

Audebert

Katsanos

et al. 2022

European Stroke Journal

View full text Add to dashboard Cite

The safety and efficacy of mobile stroke units (MSUs) in prehospital stroke management has recently been investigated in different clinical studies. MSUs are ambulances equipped with a CT scanner, point-of-care lab, telemedicine and are staffed with a stroke specialised medical team. This European Stroke Organisation (ESO) guideline provides an up-to-date evidence-based recommendation to assist decision-makers in their choice on using MSUs for prehospital management of suspected stroke, which includes patients with acute ischaemic stroke (AIS), intracranial haemorrhage (ICH) and stroke mimics. The guidelines were developed according to the ESO standard operating procedure and Grading of Recommendations, Assessment, Development and Evaluation (GRADE) methodology. The working group identified relevant clinical questions, performed systematic reviews and aggregated data meta-analyses of the literature, assessed the quality of the available evidence and made specific recommendations. Expert consensus statements are provided where sufficient evidence was not available to provide recommendations based on the GRADE approach. We found moderate evidence for suggesting MSU management for patients with suspected stroke. The patient group diagnosed with AIS shows an improvement of functional outcomes at 90 days, reduced onset to treatment times and increased proportion receiving IVT within 60 min from onset. MSU management might be beneficial for patients with ICH as MSU management was associated with a higher proportion of ICH patients being primarily transported to tertiary care stroke centres. No safety concerns (all-cause mortality, proportion of stroke mimics treated with IVT, symptomatic intracranial bleeding and major extracranial bleeding) could be identified for all patients managed with a MSU compared to conventional care. We suggest MSU management to improve prehospital management of suspected stroke patients.

show abstract

Section: Discussionmentioning

confidence: 99%

European Stroke Organisation (ESO) guidelines on mobile stroke units for prehospital stroke management

Walter

Audebert

Katsanos

et al. 2022

European Stroke Journal

View full text Add to dashboard Cite

show abstract

“…Previous studies suggested that HE is associated with worse outcomes ( 15 – 17 ). Risk factors for the expansion of hematoma have become a major topic of hemorrhagic stroke research.…”

Section: Discussionmentioning

confidence: 97%

“…Given that a hematoma volume < 20 mL manifested in little mass effect ( 14), the patients with ICH along with hematoma volume more than 20 ml without cerebral hernia were enrolled in this study. Previous studies suggested that HE is associated with worse outcomes (15)(16)(17). Risk factors for the expansion of hematoma have become a major topic of hemorrhagic stroke research.…”

Section: Discussionmentioning

confidence: 99%

Early Deterioration and Long-Term Prognosis of Patients With Intracerebral Hemorrhage Along With Hematoma Volume More Than 20 ml: Who Needs Surgery?

Lin

Tong³

et al. 2022

Front. Neurol.

View full text Add to dashboard Cite

Background and Purpose: The treatment of patients with intracerebral hemorrhage along with moderate hematoma and without cerebral hernia is controversial. This study aimed to explore risk factors and establish prediction models for early deterioration and poor prognosis.Methods: We screened patients from the prospective intracerebral hemorrhage (ICH) registration database (RIS-MIS-ICH, ClinicalTrials.gov Identifier: NCT03862729). The enrolled patients had no brain hernia at admission, with a hematoma volume of more than 20 ml. All patients were initially treated by conservative methods and followed up ≥ 1 year. A decline of Glasgow Coma Scale (GCS) more than 2 or conversion to surgery within 72 h after admission was defined as early deterioration. Modified Rankin Scale (mRS) ≥ 4 at 1 year after stroke was defined as poor prognosis. The independent risk factors of early deterioration and poor prognosis were determined by univariate and multivariate regression analysis. The prediction models were established based on the weight of the independent risk factors. The accuracy and value of models were tested by the receiver operating characteristic (ROC) curve.Results: After screening 632 patients with ICH, a total of 123 legal patients were included. According to statistical analysis, admission GCS (OR, 1.43; 95% CI, 1.18–1.74; P < 0.001) and hematoma volume (OR, 0.9; 95% CI, 0.84–0.97; P = 0.003) were the independent risk factors for early deterioration. Hematoma location (OR, 0.027; 95% CI, 0.004–0.17; P < 0.001) and hematoma volume (OR, 1.09; 95% CI, 1.03–1.15; P < 0.001) were the independent risk factors for poor prognosis, and island sign had a trend toward significance (OR, 0.5; 95% CI, 0.16-1.57; P = 0.051). The admission GCS and hematoma volume score were combined for an early deterioration prediction model with a score from 2 to 5. ROC curve showed an area under the curve (AUC) was 0.778 and cut-off point was 3.5. Combining the score of hematoma volume, island sign, and hematoma location, a long-term prognosis prediction model was established with a score from 2 to 6. ROC curve showed AUC was 0.792 and cutoff point was 4.5.Conclusions: The novel early deterioration and long-term prognosis prediction models are simple, objective, and accurate for patients with ICH along with a hematoma volume of more than 20 ml.

show abstract

“…[8][9][10] However, unclear-onset sICH patients were excluded from these studies and it leaded to a high risk of selection bias. Developing models to identify the symptom onset time for unclear-onset sICH patients 4 could help clinicians investigate the benefit of time-dependent treatments.…”

Section: Introductionmentioning

confidence: 99%

“…1 Approximately one-third of patients did not know the symptom onset time and had a higher mortality than patients who knew onset time. 2–4…”

Section: Introductionmentioning

confidence: 99%

Weakly supervised multitask learning models to identify symptom onset time of unclear-onset intracerebral hemorrhage

Chang

Hanqi

Chen

et al. 2021

International Journal of Stroke

View full text Add to dashboard Cite

Background Approximately 1/3 of spontaneous intracerebral hemorrhage (sICH) patients did not know the onset time and were excluded from studies about time-dependent treatments for hyperacute sICH. Aims To help clinicians explore the benefit of time-dependent treatments for unclear-onset patients, we presented artificial intelligence models to identify onset time using non-contrast computed tomography (NCCT) based on weakly supervised multitask learning (WS-MTL) structure. Methods The patients with reliable symptom onset time (strong label) or repeat CT (weak label) were included and split into training set and test set (internal and external). The WS-MTL structure utilized strong and weak labels simultaneously to improve performance. The models included three binary classification models for classifying whether NCCT acquired within 6, 8 or 12 hours for different treatments measured by area under curve (AUC), and a regression model for determining the exact onset time measured by mean absolute error (MAE). The generalizability of models was also explored in comprehensive analysis. Results 4 004 patients with 10 780 NCCT scans were included. The performance of WS-MTL classification model showed high accuracy, and that of regression model was satisfactory in â¤ 6 hours subgroup. In comprehensive analysis, the WS-MTL showed better performance for larger hematomas and thinner scans. And the performance improved effectively as training amounts increasing and could be improved steadily through retraining. Conclusions The WS-MTL models showed good performance and generalizability. Considering the large number of unclear-onset sICH patients, it may be worth to integrate the WS-MTL model into clinical practice to identify the onset time.

show abstract

Hematoma Expansion in Intracerebral Hemorrhage With Unclear Onset

Cited by 17 publications

References 46 publications

European Stroke Organisation (ESO) guidelines on mobile stroke units for prehospital stroke management

European Stroke Organisation (ESO) guidelines on mobile stroke units for prehospital stroke management

Early Deterioration and Long-Term Prognosis of Patients With Intracerebral Hemorrhage Along With Hematoma Volume More Than 20 ml: Who Needs Surgery?

Weakly supervised multitask learning models to identify symptom onset time of unclear-onset intracerebral hemorrhage

Contact Info

Product

Resources

About