AIM: of the research was to develop a mathematical model for the preoperative assessing of the stroke risk in surgical operations for malignant neoplasms of the chest and abdomen for the early identification of high-risk patients optimization of diagnostics and enhancing the efficacy of personalized preventive measures. MATERIALS AND METHODS: 47 cases of perioperative stroke according to archived case histories patients with malignant neoplasms of various localization retrospective analysis anamnesis of life and underlying disease, analysis of clinical and laboratory examination data, analysis of parameters associated with surgery and anesthetic aid, analysis of the clinical and neuroimaging picture of perioperative stroke; 102 patients who underwent elective surgery for the malignant neoplasm of the chest or abdomen perioperative dynamic neurological support collection of anamnesis of life and disease, analysis of clinical and laboratory examination data, neurological examination with NIHSS and mRankin scores, neuropsychological testing using MoCA and FAB. RESULTS: Risk factors for perioperative stroke in oncosurgical patients, as well as cerebroprotective factors have been established. The valid mathematical model was developed for assessing of the likelihood of perioperative stroke in the surgical treatment of malignant neoplasms of the chest and abdomen with a predictive power of 85.4%, sensitivity of 77%, and specificity of 87%. CONCLUSION: The proposed mathematical model allows preoperatively assess the risk of perioperative stroke in percentage (according to the anamnesis and medical records data) and identify the group of high-risk patients.
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.
Aim of the research was to study the features of the structure of postoperative cerebral dysfunction, establishing the risk factors for the development of postoperative cerebral dysfunction and for the each of the clinical types during operations for malignant neoplasms of the chest and abdomen. The study was conducted in 2 stages: a retrospective study based on medical records and a prospective study. In a retrospective study by the method of directed selection from 93,129 clinical cases of patients, 47 cases of patients with acute stroke after surgery were selected. In prospective study, 102 patients (69 men, 33 women) aged 38 to 85 years were examined, the median age was 67 years. They were divided into two study groups: thoracic, abdominal. In a retrospective study, the incidence of perioperative stroke was 0.05%. In a prospective study of surgical operations for malignant neoplasms of the chest and abdomen, the incidence of postoperative cerebral dysfunction was 34%, perioperative stroke 2%, symptomatic delirium of the early postoperative period 11%, deferred cognitive impairment 31%. Statistical processing of the prospective study data revealed 10 risk factors for postoperative cerebral dysfunction, 12 risk factors for perioperative stroke, 7 risk factors for symptomatic delirium of the early postoperative period, and 6 risk factors for deferred cognitive impairment. For each of the clinical types of postoperative cerebral dysfunction the Charlson comorbidity index has a significant predictive value, and therefore it seems appropriate to include this parameter in the preoperative examination algorithm (3 tables, bibliography: 8 refs)
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