Causes and Risk Factors of Pediatric Spontaneous Intracranial Hemorrhage—A Systematic Review

Ciochon, Urszula Maria; Bindslev, Julie; Hoei‐Hansen, Christina E.; Truelsen, Thomas; Larsen, Vibeke Andrée; Nielsen, Michael Bachmann

doi:10.3390/diagnostics12061459

Cited by 16 publications

(5 citation statements)

References 56 publications

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“…A study reported that in children over 5 years of age, like the patient in the case, SICH usually occurs due to vascular malformations. Vascular malformations in children can have several risk factors, such as connective tissue disorders, fibromuscular dysplasia, and vasculitis due to infection or inflammation [1,[5][6][7][8].…”

Section: Discussionmentioning

confidence: 99%

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Pediatric Spontaneous Intracranial Hemorrhage (SICH) with unknown etiology in rural area

Meilia Wulandari,

Whenny Aphrilia Pramusinta

2023

World J. Adv. Res. Rev.

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Background: Spontaneous intracranial haemorrhage (SICH) on paediatrics is a rare condition which usually doesn’t present specific sign and symptoms. Therefore, quick diagnosis followed by appropriate initial treatment is necessary to reduce morbidity and mortality rate. Case Presentation: An 11-year-old boy was admitted to the ER (emergency room) with sudden altered mental status 2 hours prior to admission. According to his parents, he complains headache after playing with friends previously. No history of trauma was found. Non contras CT scan shows intracerebral haemorrhage in the left and right lateral periventricular of the posterior horn (Vol 0.77 cc) and intraventricular haemorrhage in all the ventricles. EVD (External Ventricular Drain) placement surgery was performed. After two weeks of hospitalization, he was allowed to go home without any neurological deficits, and continued follow up in outpatient unit. Summary: Spontaneous intracranial bleeding in children have high mortality and morbidity rates, but children do not always have specific signs and symptoms. Therefore, a quick diagnosis accompanied by appropriate initial treatment is very necessary to reduce morbidity and mortality rate, such as those to reduce intracranial pressure.

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Section: Discussionmentioning

confidence: 99%

“…Recently, advances in diagnosis and earlier surgical intervention have improved the prognosis of SICH itself. In addition, the brain in pediatric has good tissue plasticity and ability to repair cerebrovascular lesions [5,7].…”

Section: Discussionmentioning

confidence: 99%

Pediatric Spontaneous Intracranial Hemorrhage (SICH) with unknown etiology in rural area

Meilia Wulandari,

Whenny Aphrilia Pramusinta

2023

World J. Adv. Res. Rev.

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“…Intracranial haemorrhage necessitates urgent evaluation and treatment by medical professionals. Early recognition and appropriate medical intervention are vital for a positive prognosis and recovery [3]. The stacking and blending method has the ability to combine the advantages of several basic models and has proven to be greater in terms of intrusion detection, electricity consumption prediction, and daily reference evaporation [10].…”

Section: Introductionmentioning

confidence: 99%

Cloud based Stacking and Bending Ensemble Approach for the classification of Brain Haemorrhage using Meta Diverse Model

Seeli,

Thanammal

2024

Preprint

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In the medical field, disease diagnosis through cloud computing is a promising technology to focus more on patient care. It offers benefits for both patients and doctors. We aimed to develop a cloud based classification method for patients with brain haemorrhage in rural (or) remote areas. The detection of brain haemorrhage is critical for neurological diagnosis and treatment. Although deep learning models have shown promise in medical image analysis, predicting brain haemorrhage remains challenging due to its complexity and variability. To address this, we propose an ensemble approach for detection of Intracranial Haemorrhage diagnosis using cloud computing. Cloud services enable data to be stored on remote servers and then be accessed via the Internet. The user does not need to be in a specific location to access it, which allows the user to work remotely. The ensemble comprises diverse deep learning models (ResNet50, VGG16, and DenseNet121) with Global Average Pooling 2D layers, benefiting from the cloud's computational resources for efficient training. Each model brings unique strengths, enabling us to capture a wider range of data patterns and improve prediction accuracy. Data pre-processing involves dividing the dataset into training and validation sets. The base models are trained on the training data, and hyper parameters are fine-tuned via cross-validation on the validation set. The stacking and blending techniques combine base model predictions. Stacking uses validation predictions to train a meta-model that intelligently combines individual predictions, while blending directly averages predictions for a simpler ensemble. To overcome the Challenges of privacy preserving, data protection, improve the performance and fast diagnosis, the proposed work is also deployed in a cloud based framework. Performance evaluation employs standard metrics on a separate test set. Results show that the ensemble approach significantly enhances Intracranial Haemorrhage Prediction, improving clinical decision-making for neurological emergencies and fast diagnosis. Our approach incorporates strategies to handle class imbalance, such as using suitable loss functions and data augmentation during training.

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“… 8 Although rare, intracranial hemorrhage can have devastating effects on pediatric populations. An estimated one-third of pediatric patients who experienced an ICH die, 9 and those that survive may suffer neurodevelopmental effects 10 from long-standing neurologic, cognitive, and adaptive behavior impairments affecting their potential independence and social functioning. 11 In the aforementioned study, Ishi et al found that all reported patients ( n = 4) with an FGFR1 mutation experienced spontaneous ICH at some point during their course of treatment.…”

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confidence: 99%

Fibroblast growth factor receptor 1 gene mutation as a potential risk factor for spontaneous intracranial hemorrhage in pediatric low-grade glioma patients

Gonzalez-Vega,

M. Lebert,

Campion

et al. 2024

Neuro-Oncology Advances

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Background Fibroblast Growth Factor Receptor 1 (FGFR1) mutations have been associated with poorer prognoses in pediatric CNS tumor patients. A recent study highlighted a link between FGFR1 mutations and spontaneous intracranial hemorrhage (ICH), demonstrating that all their patients with an FGFR1 alteration experienced hemorrhage at some point during their course of treatment. Methods The current study examined fifty out of sixty-seven pediatric patients with low grade gliomas that had genomic testing between 2011-2022 at our institution to determine whether a correlation exists between FGFR1 mutations and spontaneous ICH. Results We found that of the fifty patients with genomic data, seven (14%) experienced ICH, an additional spontaneous hemorrhage was recorded, however, no genomic testing was performed for this case. Five of the seven patients (71.4%) had an FGFR1 modification. In our patient population, six expressed a detectable FGFR1 mutation (66.7% [4/6] had N546K alteration, 16.7% [1/6] FGFR1 exons duplication, and 16.7% [1/6] had a variant of unknown significance). The patient with the FGFR1 variant of unknown significance had no reported spontaneous hemorrhage. Statistical analysis found a significant association between FGFR1 and spontaneous intracranial hemorrhage (p-value = <0.0001). In the patient population, all cases of PTPN11 alterations (n=3) co-occurred with FGFR1 mutations. Conclusions Our case series highlights this link between the FGFR1 mutation and spontaneous intracranial hemorrhage in pediatric Low-Grade Gliomas.

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Causes and Risk Factors of Pediatric Spontaneous Intracranial Hemorrhage—A Systematic Review

Cited by 16 publications

References 56 publications

Pediatric Spontaneous Intracranial Hemorrhage (SICH) with unknown etiology in rural area

Pediatric Spontaneous Intracranial Hemorrhage (SICH) with unknown etiology in rural area

Cloud based Stacking and Bending Ensemble Approach for the classification of Brain Haemorrhage using Meta Diverse Model

Fibroblast growth factor receptor 1 gene mutation as a potential risk factor for spontaneous intracranial hemorrhage in pediatric low-grade glioma patients

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