Prognostic algorithm for early diagnosis of subcritical conditions as predictors of sudden cardiac death
Aim. To develop a method for early diagnosis of subcritical homeostasis disorders leading to sudden cardiac death (SCD). The basis is to improve the efficiency of predictive algorithms.Material and methods. This pilot, controlled, open-label, randomized, prospective clinical trial included 220 patie...
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«FIRMA «SILICEA» LLC
2024-08-01
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| Series: | Российский кардиологический журнал |
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| Online Access: | https://russjcardiol.elpub.ru/jour/article/view/5987 |
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| author | A. V. Bykov P. S. Azarova S. A. Parkhomenko A. V. Bykov A. V. Polyakova M. V. Alymova A. V. Vinnikov |
| author_facet | A. V. Bykov P. S. Azarova S. A. Parkhomenko A. V. Bykov A. V. Polyakova M. V. Alymova A. V. Vinnikov |
| author_sort | A. V. Bykov |
| collection | DOAJ |
| description | Aim. To develop a method for early diagnosis of subcritical homeostasis disorders leading to sudden cardiac death (SCD). The basis is to improve the efficiency of predictive algorithms.Material and methods. This pilot, controlled, open-label, randomized, prospective clinical trial included 220 patients at risk of SCD and 150 patients without risk of SCD. Main and control groups was formed according to the global cardiovascular risk score. Based on the informative features proposed by specialized experts using multivariate statistics methods (discriminant analysis), two condition classes were formed. The conducted exploratory analysis confirmed the significance of diagnostic criteria in relation to SCD manifestation (manifestation of cardiac arrest — MCA), which is an integral assessment of a fatal complication. The development of decision rules was carried out on the basis of soft computing technology.Results. Taking into account the priority of clinical research, namely, the identification of subcritical stages of MCA, a classifier is proposed according to basic severity of patients — the severity of critical condition risk (SCCR). The discriminant function and intersection areas between MCA subclasses in the conditions of early SCD diagnosis determine the transition to soft computing technology. Membership functions for severe MCA are formed, followed by their iteration according to E. Shortliffe. The final decision rule, using a fuzzy classifier, differentiates the MCA into stages with different SCCR. In parallel with standard protocols for the management of severe somatic patients (chronic obstructive pulmonary disease, chronic kidney disease, hepatocellular failure), based on the proposed algorithm with an integral assessment of critical conditions, using the MCA decision rule in the main group in 30,5% of cases, subcritical stage was revealed, followed by targeted treatment and preventive support. In the first group, a subcritical condition was detected in 67 patients (30,5%); a critical condition without SCD — in 3 patients (1,4%). In all noted cases, early prevention of SCD was successfully carried out (these patients were transferred to a class with a lower SCD degree). Using conventional prognostic scores in this group, 46 patients (20,9%) were identified with a subcritical condition and 1 (0,4%) with a critical condition. In the control group, subcritical condition was determined in 35 patients (23,3%), of which 17 patients (11,3%) had a moderate risk of SCD. Using conventional prognostic scores, 23 patients (15,3%) with subcritical condition were identified.Conclusion. In the conditions of intensive care unit, general medicine departments, hemodialysis department, cardiac surgery, and organ transplantation department, an algorithm for early diagnosis and risk stratification of SCD with an integral assessment (MCA) should be used. The fuzzy classifier MCA according to SCCR makes it possible to carry out timely correction of treatment measures in addition to standard protocols. |
| format | Article |
| id | doaj-art-e3e2209bad9a49a896e7ce7195fbda12 |
| institution | DOAJ |
| issn | 1560-4071 2618-7620 |
| language | Russian |
| publishDate | 2024-08-01 |
| publisher | «FIRMA «SILICEA» LLC |
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| series | Российский кардиологический журнал |
| spelling | doaj-art-e3e2209bad9a49a896e7ce7195fbda122025-08-20T03:01:34Zrus«FIRMA «SILICEA» LLCРоссийский кардиологический журнал1560-40712618-76202024-08-0129710.15829/1560-4071-2024-59874127Prognostic algorithm for early diagnosis of subcritical conditions as predictors of sudden cardiac deathA. V. Bykov0P. S. Azarova1S. A. Parkhomenko2A. V. Bykov3A. V. Polyakova4M. V. Alymova5A. V. Vinnikov6Southwestern State University; Kursk Regional Multidisciplinary Clinical HospitalSouthwestern State UniversitySouthwestern State University; National Medical Research Center for High Medical Technologies — Vishnevsky Central Military Clinical HospitalSouthwestern State University; Korotkov Kursk City Hospital № 1Southwestern State UniversitySouthwestern State UniversitySouthwestern State University; Ostroverkhov Kursk Oncology Research and Clinical CenterAim. To develop a method for early diagnosis of subcritical homeostasis disorders leading to sudden cardiac death (SCD). The basis is to improve the efficiency of predictive algorithms.Material and methods. This pilot, controlled, open-label, randomized, prospective clinical trial included 220 patients at risk of SCD and 150 patients without risk of SCD. Main and control groups was formed according to the global cardiovascular risk score. Based on the informative features proposed by specialized experts using multivariate statistics methods (discriminant analysis), two condition classes were formed. The conducted exploratory analysis confirmed the significance of diagnostic criteria in relation to SCD manifestation (manifestation of cardiac arrest — MCA), which is an integral assessment of a fatal complication. The development of decision rules was carried out on the basis of soft computing technology.Results. Taking into account the priority of clinical research, namely, the identification of subcritical stages of MCA, a classifier is proposed according to basic severity of patients — the severity of critical condition risk (SCCR). The discriminant function and intersection areas between MCA subclasses in the conditions of early SCD diagnosis determine the transition to soft computing technology. Membership functions for severe MCA are formed, followed by their iteration according to E. Shortliffe. The final decision rule, using a fuzzy classifier, differentiates the MCA into stages with different SCCR. In parallel with standard protocols for the management of severe somatic patients (chronic obstructive pulmonary disease, chronic kidney disease, hepatocellular failure), based on the proposed algorithm with an integral assessment of critical conditions, using the MCA decision rule in the main group in 30,5% of cases, subcritical stage was revealed, followed by targeted treatment and preventive support. In the first group, a subcritical condition was detected in 67 patients (30,5%); a critical condition without SCD — in 3 patients (1,4%). In all noted cases, early prevention of SCD was successfully carried out (these patients were transferred to a class with a lower SCD degree). Using conventional prognostic scores in this group, 46 patients (20,9%) were identified with a subcritical condition and 1 (0,4%) with a critical condition. In the control group, subcritical condition was determined in 35 patients (23,3%), of which 17 patients (11,3%) had a moderate risk of SCD. Using conventional prognostic scores, 23 patients (15,3%) with subcritical condition were identified.Conclusion. In the conditions of intensive care unit, general medicine departments, hemodialysis department, cardiac surgery, and organ transplantation department, an algorithm for early diagnosis and risk stratification of SCD with an integral assessment (MCA) should be used. The fuzzy classifier MCA according to SCCR makes it possible to carry out timely correction of treatment measures in addition to standard protocols.https://russjcardiol.elpub.ru/jour/article/view/5987sudden cardiac deathsubcritical and critical conditionsfuzzy logic decision makingmembership functionrisk factors |
| spellingShingle | A. V. Bykov P. S. Azarova S. A. Parkhomenko A. V. Bykov A. V. Polyakova M. V. Alymova A. V. Vinnikov Prognostic algorithm for early diagnosis of subcritical conditions as predictors of sudden cardiac death Российский кардиологический журнал sudden cardiac death subcritical and critical conditions fuzzy logic decision making membership function risk factors |
| title | Prognostic algorithm for early diagnosis of subcritical conditions as predictors of sudden cardiac death |
| title_full | Prognostic algorithm for early diagnosis of subcritical conditions as predictors of sudden cardiac death |
| title_fullStr | Prognostic algorithm for early diagnosis of subcritical conditions as predictors of sudden cardiac death |
| title_full_unstemmed | Prognostic algorithm for early diagnosis of subcritical conditions as predictors of sudden cardiac death |
| title_short | Prognostic algorithm for early diagnosis of subcritical conditions as predictors of sudden cardiac death |
| title_sort | prognostic algorithm for early diagnosis of subcritical conditions as predictors of sudden cardiac death |
| topic | sudden cardiac death subcritical and critical conditions fuzzy logic decision making membership function risk factors |
| url | https://russjcardiol.elpub.ru/jour/article/view/5987 |
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