Cerebrovascular complications of hematopoetic stem cell transplantation in patients with hematologic malignancies

Introduction. Modern transplantation and biological therapy methods are associated with a wide range of adverse events and complications. Incidence and variety of neurological complications mostly depend on myelo- and immunosuppression severity and duration as well as on donor's and recipient's characteristics. The most frequent complications involving the nervous system include neurotoxic reactions, infections, autoimmune and lymphoproliferative diseases, and dysmetabolic conditions as well as cerebrovascular complications that potentially affect transplantation outcomes. Objective. To evaluate the impact of post-transplantation cerebrovascular events (CVEs) on transplantation outcomes in patients with hematologic malignancies. Materials and methods. We analyzed 899 transplantations performed at the Raisa Gorbacheva Memorial Research Institute for Pediatric Oncology, Hematology, and Transplantation, Pavlov First Saint Petersburg State Medical University, from 2016 to 2018. We assessed transplantation parameters and donor's and recipient's characteristics by intergroup comparison, pseudo-randomization (propensity score matching), KaplanMeier survival analysis, and log-rank tests. Results. Post-transplantatively, CVEs developed in 2.6% (n = 23) of cases: 13 (1.4%) ischemic strokes and 11 (1.2%) hemorrhagic strokes or intracranial hemorrhages were diagnosed. CVEs developed on days 99.5 39.2 post hematopoetic stem cell transplantation (HSCT). There were more patients with non-malignant conditions in the CVE group as compared to the non-CVE group (21.7% vs 7.9%; p = 0.017). Patients with CVE had a significantly lower Karnofsky index (75.6 21.3 vs 85.2 14.9; p = 0.008). Statistically, we also note some non-significant trends: patients with CVE more often underwent allogenic HSCT (82.6% vs 64.0%; p = 0.077) while donors were more often partially (rather than totally) HLA compatible for recipients (39.1% vs 21.1%; p = 0.33). Patients with CVE more often had a history of venous thromboses (13.3% vs 4.2%; p = 0.077). Post-HSCT stroke decreased post-transplantation longevity by approximately 3 times (331.8 81.6 vs 897.9 25.4 post HSCT; p = 0.0001). In the CVE group, survival during first 180 days post HSCT (landmarks post-HSCT Day+60 and Day+180) was significantly lower as compared to that in the CVE-free group. If CVE developed during first 30 days and 100 days post HSCT, vascular catastrophe did not affect post-HSCT survival significantly. Conclusion. Whereas ischemic stroke is a long-term HSCT complication (beyond D+100 post transplantation), hemorrhagic stroke is a short-term complication (D0D+100 post HSCT). CVEs affect survival in patients with hematologic malignancies, especially those developed between D+60 and D+180 post HSCT. History of venous abnormalities, low Karnofsky index at HSCT initiation, and the type of allogenic HSCT, especially from half-matched donors, can be considered as negative outcome risk factors in post-HSCT CVE

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

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

Innovative Approach in Creation of Integrated Technology of Desalination of Mineralized Water

In this study, the optimum parameters of membrane desalinization of model solutions were determined and the required efficiency was achieved. Methods for stabilizing treatment of water before barometric desalination were developed to improve the efficiency of membranes. Methods of reagent processing of concentrates after barometric water were proposed to create a low-waste technologies for demineralization of water. It was shown that the precipitate can be used as an additive for cements and a sulfate activator for slag-portland cement

Spent Biosorbents as Additives in Cement Production

The research is related to solving the problem of rational use of materials and to the creation of resource-saving technologies for the protection of the environment from pollution. Sorption technologies are quite effective in wastewater treatment, but most sorbents are quite expensive, and their regeneration raises the question of recycling of spent solutions. The cheapness and availability of raw material base of biosorbents makes these technologies attractive for wastewater treatment. The research is aimed at investigation of the ways to effectively utilize the spent sorbents, which are obtained after water purification, in the production of building materials. The obtained results allow creating a complex low-waste technology of water demineralization and purification from heavy metal ions