External validation of a multivariate model for predicting the risk of death in patients with chronic heart failure and an implantable cardioverter – defibrillator
N. B. Lebedeva,
P. G. Parfenov,
A. P. Egle,
V. I. Ivanov,
Yu. V. Galintsev,
V. V. Kashtalap,
O. L. Barbarash https://doi.org/10.20538/1682-0363-2024-2-74-82
Abstract
Aim. To perform external validation of a multivariate model for predicting the risk of death in patients with an implantable cardioverter – defibrillator (ICD) in an independent sample.
Materials and methods. The group for model development included 260 patients from the Implantable Cardioverter – Defibrillator Patient Registry who had an ICD implanted between 2015 and 2019. External validation of the model was carried out in an independent, prospective, observational cohort study of patients from the same registry, in whom an ICD was implanted between 2020 and 2021, a total of 94 patients, median age 66 (52;73) years, 73 (77.6%) men, 21 (22.4%) women. In 89 (94.7%) patients, an ICD was implanted for primary prevention of sudden cardiac death. Following a telephone survey and examination of medical records from hospital and clinic databases, data on the vital status (alive / dead) and causes of death were obtained during a 2.5-year follow-up. The actual and predicted mortality from the estimated multivariate model were compared.
Results. During the follow-up, a total of 26 (27.7%) patients died in the external validation group, which was comparable to the development group (p > 0.05). In the group of deceased, 15 (57.7%) people developed acute decompensated heart failure, 4 (14.8%) had myocardial infarction, 6 (23.1%) had pneumonia caused by a new coronavirus infection, and one (3.8%) patient died due to an infectious complication.
The diagnostic accuracy of the multivariate model for predicting the risk of death in patients with ICD in an independent sample was sufficient (the area under the curve (AUC) of the created model was 0.8). The sensitivity of the model was 76.2%, specificity – 76.1%. Previously, in the development cohort, AUC of the created model was 0.8, the sensitivity of the model was 75.7%, and the specificity was 80%. Model significance did not differ significantly between the development and external validation groups (p = 0.102, McNeil test).
Conclusion. The multivariate prediction model has sufficient statistical power to predict the risk of long-term death after ICD implantation, which was externally validated.
Keywords
Supporting agencies: The study was carried out within the basic research topic of Research Institute for Complex Problems of Cardiovascular Diseases “Developing innovative risk management models for cardiovascular diseases with account of comorbidity based on the study of fundamental, clinical, and epidemiological mechanisms and medical care organization technologies in conditions of the industrial region of Siberia” (state registration No. 122012000364-5 of 20.01.2022).
About the Authors
N. B. Lebedeva
Research Institute for Complex Problems of Cardiovascular Diseases
Russian Federation
Competing Interests:
Russian Federation
6, Sosnovy Blvd., Kemerovo, 650002
Competing Interests:
The authors declare the absence of obvious or potential conflict of interest related to the publication of this article.
P. G. Parfenov
Research Institute for Complex Problems of Cardiovascular Diseases
Russian Federation
Competing Interests:
Russian Federation
6, Sosnovy Blvd., Kemerovo, 650002
Competing Interests:
The authors declare the absence of obvious or potential conflict of interest related to the publication of this article.
A. P. Egle
Research Institute for Complex Problems of Cardiovascular Diseases
Russian Federation
Competing Interests:
Russian Federation
6, Sosnovy Blvd., Kemerovo, 650002
Competing Interests:
The authors declare the absence of obvious or potential conflict of interest related to the publication of this article.
V. I. Ivanov
Kemerovo State Medical University
Russian Federation
Competing Interests:
Russian Federation
22a, Voroshilova Str., Kemerovo, 650056
Competing Interests:
The authors declare the absence of obvious or potential conflict of interest related to the publication of this article.
Yu. V. Galintsev
Kemerovo State Medical University
Russian Federation
Competing Interests:
Russian Federation
22a, Voroshilova Str., Kemerovo, 650056
Competing Interests:
The authors declare the absence of obvious or potential conflict of interest related to the publication of this article.
V. V. Kashtalap
Research Institute for Complex Problems of Cardiovascular Diseases
Russian Federation
Competing Interests:
Russian Federation
6, Sosnovy Blvd., Kemerovo, 650002
Competing Interests:
The authors declare the absence of obvious or potential conflict of interest related to the publication of this article.
O. L. Barbarash
Research Institute for Complex Problems of Cardiovascular Diseases
Russian Federation
Competing Interests:
Russian Federation
6, Sosnovy Blvd., Kemerovo, 650002
Competing Interests:
The authors declare the absence of obvious or potential conflict of interest related to the publication of this article.
References
1. Терещенко С.Н., Галявич А.С., Ускач Т.М. Хроническая сердечная недостаточность. Клинические рекомендации 2020. Российский кардиологический журнал. 2020; 25(11):311–374. DOI: 10.15829/1560-4071-2020-4083.
2. Wellens H.J., Schwartz P.J., Lindemans F.W., Buxton A.E., Goldberger J.J., Hohnloser S.H. et al. Risk stratification for sudden cardiac death: current status and challenges for the future. Eur. Heart J. 2014;35(25):1642–1651. DOI: 10.1093/eurheartj/ehu176.
3. Ревишвили А.Ш., Неминущий Н.М., Голицын С.П. Всероссийские клинические рекомендации по контролю над риском внезапной остановки сердца и внезапной сердечной смерти, профилактике и оказанию первой помощи. M.: ГЭОТАР-Медиа, 2018:256.
4. Богачевская С.А., Богачевский А.Н. Развитие хирургической и интервенционной аритмологии в России за 10 лет. Особенности функционирования службы в Дальневосточном регионе. Социальные аспекты здоровья населения. 2017;1(53):2. DOI: 10.21045/2071-5021-2017-53-1-1.
5. Виноградова Н.Г., Поляков Д.С., Фомин И.В. Анализ смертности у пациентов с ХСН после декомпенсации при длительном наблюдении в условиях специализированной медицинской помощи и в реальной клинической практике. Кардиология. 2020;60(4):91–100. DOI: 10.18087/cardio.2020.4.n1014.
6. Adibi A., Sadatsafavi M., John P.A., Ioannidis J.P.A. Validation and utility testing of clinical prediction models time to change the approach. JAMA. 2020;324(3):235–236. DOI: 10.1001/jama.2020.1230
7. Boriani G., De Ponti R., Guerra F., Palmisano P., Zanotto G., D’Onofrio A. et al. Sinergy between drugs and devices in the fight against sudden cardiac death and heart failure. Eur. J. Prev. Cardiol. 2021;28(1):110–123. DOI: 10.1093/eurjpc/zwaa015.
8. Looi K.L., Sidhu K., Cooper L., Dawson L., Slipper D., Gavin A. et al. Long-term outcomes of heart failure patients who received primary prevention implantable cardioverter-defibrillator: An observational study. J. Arrhythm. 2017;34(1):46–54. DOI: 10.1002/joa3.12027.
9. Piccini J.P., Zhang M., Pieper K., Solomon S.D., Al-Khatib S.M., Van de Werf F. et al. Predictors of sudden cardiac death change with time after myocardial infarction: results from the VALIANT trial. Eur. Heart J. 2010;31(2):211–221. DOI: 10.1093/eurheartj/ehp425.
10. Verstraelen T.E., van Barreveld M., van Dessel P.H.F.M., Boersma L.V.A., Delnoy P.P.H.M., Tuinenburg A.E. et al. Development and external validation of prediction models to predict implantable cardioverter-defibrillator efficacy in primary prevention of sudden cardiac death. Europace. 2021;23(6):887–897. DOI: 10.1093/europace/euab012.
11. Илов Н.Н., Пальникова О.В., Нечепуренко А.А. Пациенты с высоким риском внезапной сердечной смерти: жизнь после имплантации кардиовертера-дефибриллятора (одноцентровое обсервационное исследование). Клиническая и экспериментальная хирургия. 2018;6(3):98–106. DOI: 10.24411/2308-1198-2018-13011.
12. Younis A., Goldberger J.J., Kutyifa V., Zareba W., Polonsky B., Klein H. et al. Predicted benefit of an implantable cardioverter-defibrillator: the MADIT-ICD benefit score. Eur. Heart J. 2021;42(17):1676–1684. DOI: 10.1093/eurheartj/ehaa1057.
13. Naksuk N., Akkaya M., Adabag S. Application of the Multicenter Automatic Defibrillator Implantation Trial II risk score in a nontrial setting. Am. J. Cardiol. 2013;112(4):530–532. DOI: 10.1016/j.amjcard.2013.04.019.
14. Cheng A., Zhang Y., Blasco-Colmenares E., Dalal D., Butcher B., Norgard S. et al. Protein Biomarkers Identify Patients Unlikely to Benefit from Primary Prevention ICDs: Findings from the PROSE-ICD Study. Circ. Arrhythmia Electrophysiol. 2014;7(6):1084–1091. DOI: 10.1161/CIRCEP.113.001705.
15. Levy W.C., Mozaffarian D., Linker D.T., Sutradhar S.C., Anker S.D., Cropp A.B. et al. The Seattle Heart Failure Model: prediction of survival in heart failure. Circulation. 2006;113(11):1424–1433. DOI: 10.1161/CIRCULATIONAHA.105.584102.
16. Khanam S.S., Choi E., Son J.W., Lee J.W., Youn Y.J., Yoon J. et al. Validation of the MAGGIC (Meta-Analysis Global Group in Chronic Heart Failure) heart failure risk score and the effect of adding natriuretic peptide for predicting mortality after discharge in hospitalized patients with heart failure. PLoS One. 2018;13(11):e0206380. DOI: 10.1371/journal.pone.0206380.
17. Хазова Е.В., Булашова О.В., Малкова М.И., Ослопов В.Н. Новый подход к прогнозированию исходов хронической сердечной недостаточности. Практическая медицина. 2014;6(14):101–104.
Review
For citations:
Lebedeva N.B., Parfenov P.G., Egle A.P., Ivanov V.I., Galintsev Yu.V., Kashtalap V.V., Barbarash O.L. External validation of a multivariate model for predicting the risk of death in patients with chronic heart failure and an implantable cardioverter – defibrillator. Bulletin of Siberian Medicine. 2024;23(2):74-82. https://doi.org/10.20538/1682-0363-2024-2-74-82
Views:
295
Email this article 