Identification of poor prognosis predictors in patients with pulmonary embolism
Aim. To identify the predictors of poor prognosis in patients with pulmonary embolism (PE).Material and methods. The study included 120 patients with verified PE. The analysis included the clinical evidence collection, paraclinical investigations (including echocardiography) and genetic analysis. Co...
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«FIRMA «SILICEA» LLC
2024-11-01
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| Series: | Российский кардиологический журнал |
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| Online Access: | https://russjcardiol.elpub.ru/jour/article/view/6040 |
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| author | N. M. Kryuchkova S. Yu. Nikulina A. A. Chernova A. A. Alyabyeva V. N. Maksimov |
| author_facet | N. M. Kryuchkova S. Yu. Nikulina A. A. Chernova A. A. Alyabyeva V. N. Maksimov |
| author_sort | N. M. Kryuchkova |
| collection | DOAJ |
| description | Aim. To identify the predictors of poor prognosis in patients with pulmonary embolism (PE).Material and methods. The study included 120 patients with verified PE. The analysis included the clinical evidence collection, paraclinical investigations (including echocardiography) and genetic analysis. Cox regression analysis was used to assess mortality predictors. Statistical data processing was performed using Excel 2019, SPSS Statistica v. 26 (IBM, USA), MedCalc v. 20.104 and JMP Pro 17 (SAS, USA) software.Results. The following independent mortality predictors were identified using multivariate regression analysis: age (odds ratio (OR) 1,051, p=0,0002), prior venous thromboembolism (OR 2,090, p=0,0117), TT genotype of the F13A1 rs5985 polymorphism (OR 2,820, p=0,0427) and anteroposterior right ventricular size (OR 1,043, p=0,0294). Right ventricular wall hypokinesis (OR 5,040, p=0,0285), submassive pulmonary artery involvement (OR 2,714, p=0,0025), prior myocardial infarction (OR 2,839, p=0,0028) and other factors were significantly associated with an increased death risk. Based on these predictors, a prognostic model was developed that allows for effective stratification of the death risk.Conclusion. The predictors identified in the study can be used for risk stratification and optimization of patient management with PE, which can improve the prognosis and treatment outcomes. |
| format | Article |
| id | doaj-art-7769f25394584ff2b59834933fa5b0c9 |
| institution | Kabale University |
| issn | 1560-4071 2618-7620 |
| language | Russian |
| publishDate | 2024-11-01 |
| publisher | «FIRMA «SILICEA» LLC |
| record_format | Article |
| series | Российский кардиологический журнал |
| spelling | doaj-art-7769f25394584ff2b59834933fa5b0c92025-08-20T03:57:22Zrus«FIRMA «SILICEA» LLCРоссийский кардиологический журнал1560-40712618-76202024-11-01291010.15829/1560-4071-2024-60404182Identification of poor prognosis predictors in patients with pulmonary embolismN. M. Kryuchkova0S. Yu. Nikulina1A. A. Chernova2A. A. Alyabyeva3V. N. Maksimov4Voyno-Yasenetsky Krasnoyarsk State Medical University; Regional Clinical HospitalVoyno-Yasenetsky Krasnoyarsk State Medical UniversityVoyno-Yasenetsky Krasnoyarsk State Medical University; Federal Siberian Research Clinical CenterVoyno-Yasenetsky Krasnoyarsk State Medical UniversityResearch Institute for Therapy and Preventive Medicine — branch of the Institute of Cytology and GeneticsAim. To identify the predictors of poor prognosis in patients with pulmonary embolism (PE).Material and methods. The study included 120 patients with verified PE. The analysis included the clinical evidence collection, paraclinical investigations (including echocardiography) and genetic analysis. Cox regression analysis was used to assess mortality predictors. Statistical data processing was performed using Excel 2019, SPSS Statistica v. 26 (IBM, USA), MedCalc v. 20.104 and JMP Pro 17 (SAS, USA) software.Results. The following independent mortality predictors were identified using multivariate regression analysis: age (odds ratio (OR) 1,051, p=0,0002), prior venous thromboembolism (OR 2,090, p=0,0117), TT genotype of the F13A1 rs5985 polymorphism (OR 2,820, p=0,0427) and anteroposterior right ventricular size (OR 1,043, p=0,0294). Right ventricular wall hypokinesis (OR 5,040, p=0,0285), submassive pulmonary artery involvement (OR 2,714, p=0,0025), prior myocardial infarction (OR 2,839, p=0,0028) and other factors were significantly associated with an increased death risk. Based on these predictors, a prognostic model was developed that allows for effective stratification of the death risk.Conclusion. The predictors identified in the study can be used for risk stratification and optimization of patient management with PE, which can improve the prognosis and treatment outcomes.https://russjcardiol.elpub.ru/jour/article/view/6040pulmonary embolismrisk predictorsdeathgenetic markersclinical echocardiography |
| spellingShingle | N. M. Kryuchkova S. Yu. Nikulina A. A. Chernova A. A. Alyabyeva V. N. Maksimov Identification of poor prognosis predictors in patients with pulmonary embolism Российский кардиологический журнал pulmonary embolism risk predictors death genetic markers clinical echocardiography |
| title | Identification of poor prognosis predictors in patients with pulmonary embolism |
| title_full | Identification of poor prognosis predictors in patients with pulmonary embolism |
| title_fullStr | Identification of poor prognosis predictors in patients with pulmonary embolism |
| title_full_unstemmed | Identification of poor prognosis predictors in patients with pulmonary embolism |
| title_short | Identification of poor prognosis predictors in patients with pulmonary embolism |
| title_sort | identification of poor prognosis predictors in patients with pulmonary embolism |
| topic | pulmonary embolism risk predictors death genetic markers clinical echocardiography |
| url | https://russjcardiol.elpub.ru/jour/article/view/6040 |
| work_keys_str_mv | AT nmkryuchkova identificationofpoorprognosispredictorsinpatientswithpulmonaryembolism AT syunikulina identificationofpoorprognosispredictorsinpatientswithpulmonaryembolism AT aachernova identificationofpoorprognosispredictorsinpatientswithpulmonaryembolism AT aaalyabyeva identificationofpoorprognosispredictorsinpatientswithpulmonaryembolism AT vnmaksimov identificationofpoorprognosispredictorsinpatientswithpulmonaryembolism |