Acute symptomatic seizures during haematopoietic stem cell transplantation

Skiba, Ya. B.; Polushin, A. Yu.; Prokudin, M. Yu.; Vladovskaya, M. D.

doi:10.17749/2077-8333/epi.par.con.2021.049

Cited by 8 publications

(2 citation statements)

References 93 publications

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“…This factor increased its weight in patients with arterial hypertension. This may indicate a possible influence of the volume of a donor cell infusion, and the volume of injected cryopreservative on the development acute arterial hypertension and other complications, including ASS [ 54 ].…”

Section: Discussionmentioning

confidence: 99%

Application of Machine Learning Methods for Epilepsy Risk Ranking in Patients with Hematopoietic Malignancies Using

Skiba

Kopanitsa

Metsker

et al. 2022

JPM

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Machine learning methods to predict the risk of epilepsy, including vascular epilepsy, in oncohematological patients are currently considered promising. These methods are used in research to predict pharmacoresistant epilepsy and surgical treatment outcomes in order to determine the epileptogenic zone and functional neural systems in patients with epilepsy, as well as to develop new approaches to classification and perform other tasks. This paper presents the results of applying machine learning to analyzing data and developing diagnostic models of epilepsy in oncohematological and cardiovascular patients. This study contributes to solving the problem of often unjustified diagnosis of primary epilepsy in patients with oncohematological or cardiovascular pathology, prescribing antiseizure drugs to patients with single seizure syndromes without finding a disease associated with these cases. We analyzed the hospital database of the V.A. Almazov Scientific Research Center of the Ministry of Health of Russia. The study included 66,723 treatment episodes of patients with vascular diseases (I10–I15, I61–I69, I20–I25) and 16,383 episodes with malignant neoplasms of lymphoid, hematopoietic, and related tissues (C81–C96 according to ICD-10) for the period from 2010 to 2020. Data analysis and model calculations indicate that the best result was shown by gradient boosting with mean accuracy cross-validation score = 0.96. f1-score = 98, weighted avg precision = 93, recall = 96, f1-score = 94. The highest correlation coefficient for G40 and different clinical conditions was achieved with fibrillation, hypertension, stenosis or occlusion of the precerebral arteries (0.16), cerebral sinus thrombosis (0.089), arterial hypertension (0.17), age (0.03), non-traumatic intracranial hemorrhage (0.07), atrial fibrillation (0.05), delta absolute neutrophil count (0.05), platelet count at discharge (0.04), transfusion volume for stem cell transplantation (0.023). From the clinical point of view, the identified differences in the importance of predictors in a broader patient model are consistent with a practical algorithm for organic brain damage. Atrial fibrillation is one of the leading factors in the development of both ischemic and hemorrhagic strokes. At the same time, brain infarction can be accompanied both by the development of epileptic seizures in the acute period and by unprovoked epileptic seizures and development of epilepsy in the early recovery and in a longer period. In addition, a microembolism of the left heart chambers can lead to multiple microfocal lesions of the brain, which is one of the pathogenetic aspects of epilepsy in elderly patients. The presence of precordial fibrillation requires anticoagulant therapy, the use of which increases the risk of both spontaneous and traumatic intracranial hemorrhage.

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Section: Discussionmentioning

confidence: 99%

Application of Machine Learning Methods for Epilepsy Risk Ranking in Patients with Hematopoietic Malignancies Using

Skiba

Kopanitsa

Metsker

et al. 2022

JPM

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“…More than 50,000 HSCTs are performed annually worldwide [1,2]. The life-threatening diseases comprise major indication for HSCT which is routinely applied and consists of several stages: 1) myelo-and immunoablation with the use of chemotherapy of varying intensity (conditioning regimen); 2) prevention of the graft-versus-host disease (GvHD), 3) graft transfusion; 4) prevention and treatment of complications during postcytostatic aplasia of hematopoiesis and graft engraftment period [3].…”

Section: Introductionmentioning

confidence: 99%

Stroke before hematopoietic stem cell transplantation is a possible risk factor for post-transplant adverse outcomes

Polushin,

Skiba,

Vladovskaya

et al. 2024

CTT

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More than 50,000 hematopoietic stem cell transplants (HSCT) are performed annually in the world for blood malignancies, solid tumors, aplastic anemia, primary immunodeficiency, autoimmune and metabolic diseases. Stroke occurs in 3% of patients over post-transplant period (about 1,500 cases annually), whereas 70% of them are at risk for unfavorable outcome in the next 1.5 years. The data on effects of preceding acute cerebrovascular accident (CVA) on the outcomes of subsequent HSCT are not presented in the literature. Our aim was to evaluate the effects of stroke occurring before HSCT on the transplant outcomes in patients with hematological diseases. Patients and methodsThe stories of 899 HSCTs were reviewed at the RM Gorbacheva Research Institute of Pediatric Oncology, Hematology and Transplantation (Pavlov University) from january 2016 to january 2018. The HSCT parameters, characteristics of the donor and recipient were taken for analysis. In addition to comparing features between groups, pseudorandomization was performed using the Propensity Score Matching method. The survival analysis was carried out using the Kaplan-Meier method and the log-rank test. ResultsOf 899 HSCTs, 16 patients (1.8%) had a history of cerebrovascular events before transplantation (0.4%, ischemic stroke; 1.4%, hemorrhagic stroke or intracranial hemorrhage). In the group of patients with a history of stroke, compared with the group of patients without them, there were more patients with leukemia (p=0.02); allogeneic transplantation (vs autologous, p=0.01), donors were more likely to have partial rather than full HLA compatibility with recipients (p=0.06). These patients had lower body mass index (p=0.02) and Karnofsky/ECOG score (p=0.01). Presence of a cerebrovascular event was significantly associated with decreased overall survival among HSCT recipients (p=0.0012).

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Posterior reversible encephalopathy syndrome in children with hematological diseases

Bronina,

Shchederkina,

Polushin

et al. 2023

Z. nevrol. psikhiatr. im. S.S. Korsakova

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Acute symptomatic seizures during haematopoietic stem cell transplantation

Cited by 8 publications

References 93 publications

Application of Machine Learning Methods for Epilepsy Risk Ranking in Patients with Hematopoietic Malignancies Using

Application of Machine Learning Methods for Epilepsy Risk Ranking in Patients with Hematopoietic Malignancies Using

Stroke before hematopoietic stem cell transplantation is a possible risk factor for post-transplant adverse outcomes

Posterior reversible encephalopathy syndrome in children with hematological diseases

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