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Development of a simple prediction model for mechanical complication in ST-segment elevation myocardial infarction patients after primary percutaneous coronary intervention

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Abstract

Mechanical complication (MC) is a rare but serious complication in patients with ST-segment elevation myocardial infarction (STEMI). Although several risk factors for MC have been reported, a prediction model for MC has not been established. This study aimed to develop a simple prediction model for MC after STEMI. We included 1717 patients with STEMI who underwent primary percutaneous coronary intervention (PCI). Of 1717 patients, 45 MCs occurred after primary PCI. Prespecified predictors were determined to develop a tentative prediction model for MC using multivariable regression analysis. Then, a simple prediction model for MC was generated. Age ≥ 70, Killip class ≥ 2, white blood cell ≥ 10,000/µl, and onset-to-visit time ≥ 8 h were included in a simple prediction model as “point 1” risk score, whereas initial thrombolysis in myocardial infarction (TIMI) flow grade ≤ 1 and final TIMI flow grade ≤ 2 were included as “point 2” risk score. The simple prediction model for MC showed good discrimination with the optimism-corrected area under the receiver-operating characteristic curve of 0.850 (95% CI: 0.798–0.902). The predicted probability for MC was 0–2% in patients with 0–4 points of risk score, whereas that was 6–50% in patients with 5–8 points. In conclusion, we developed a simple prediction model for MC. We may be able to predict the probability for MC by this simple prediction model.

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All data are available from the corresponding author on reasonable request.

References

  1. Damluji AA, van Diepen S, Katz JN, Menon V, Tamis-Holland JE, Bakitas M, Cohen MG, Balsam LB, Chikwe J, American Heart Association Council on Clinical C, Council on Arteriosclerosis T, Vascular B, Council on Cardiovascular S, Anesthesia, Council on C, Stroke N (2021) Mechanical complications of acute myocardial infarction: a scientific statement from the american heart association. Circulation 144(2):e16–e35

    PubMed Central  PubMed  Google Scholar 

  2. French JK, Hellkamp AS, Armstrong PW, Cohen E, Kleiman NS, O’Connor CM, Holmes DR, Hochman JS, Granger CB, Mahaffey KW (2010) Mechanical complications after percutaneous coronary intervention in ST-elevation myocardial infarction (from APEX-AMI). Am J Cardiol 105(1):59–63

    PubMed  Google Scholar 

  3. Magalhaes P, Mateus P, Carvalho S, Leao S, Cordeiro F, Moreira JI, Investigators of the Portuguese Registry on Acute Coronary S (2016) Relationship between treatment delay and type of reperfusion therapy and mechanical complications of acute myocardial infarction. Eur Heart J Acute Cardiovasc Care 5(5):468–474

    PubMed  Google Scholar 

  4. Honda S, Asaumi Y, Yamane T, Nagai T, Miyagi T, Noguchi T, Anzai T, Goto Y, Ishihara M, Nishimura K, Ogawa H, Ishibashi-Ueda H, Yasuda S (2014) Trends in the clinical and pathological characteristics of cardiac rupture in patients with acute myocardial infarction over 35 years. J Am Heart Assoc 3(5):e000984

    PubMed Central  PubMed  Google Scholar 

  5. Elbadawi A, Elgendy IY, Mahmoud K, Barakat AF, Mentias A, Mohamed AH, Ogunbayo GO, Megaly M, Saad M, Omer MA, Paniagua D, Abbott JD, Jneid H (2019) Temporal trends and outcomes of mechanical complications in patients with acute myocardial infarction. JACC Cardiovasc Interv 12(18):1825–1836

    PubMed  Google Scholar 

  6. Lopez-Sendon J, Gurfinkel EP, Lopez de Sa E, Agnelli G, Gore JM, Steg PG, Eagle KA, Cantador JR, Fitzgerald G, Granger CB, Global Registry of Acute Coronary Events I (2010) Factors related to heart rupture in acute coronary syndromes in the global registry of acute coronary events. Eur Heart J 31(12):1449–1456

    PubMed  Google Scholar 

  7. Arai R, Fukamachi D, Ebuchi Y, Migita S, Morikawa T, Monden M, Tamaki T, Kojima K, Akutsu N, Murata N, Kitano D, Okumura Y (2021) Mechanical complications of myocardial infarction. Int Heart J 62(3):499–509

    PubMed  Google Scholar 

  8. Shoji K, Yanishi K, Kawamata H, Hori Y, Fujioka A, Kohno Y, Kitamura M, Furukawa K, Teramukai S, Nakamura T, Matoba S, Group AM-KM-CRS (2022) New risk factors for early- and late-onset cardiac rupture in ST-elevation myocardial infarction patients after primary percutaneous coronary intervention. J Cardiol 79(3):400–407

    PubMed  Google Scholar 

  9. Bouisset F, Deney A, Ferrieres J, Panagides V, Becker M, Riviere N, Yvorel C, Commeau P, Adjedj J, Benamer H, Bonnet G, Cayla G, Investigators Mr (2021) Mechanical complications in ST-elevation myocardial infarction: the impact of pre-hospital delay. Int J Cardiol 345:14–19

    PubMed  Google Scholar 

  10. Xu Z, Li Y, Zhang R, Liu Y, Liu H, Yu J, Zhou X, Du Y, Cong H (2022) Risk factors for cardiac rupture after acute ST-segment elevation myocardial infarction during the percutaneous coronary intervention era: a retrospective case-control study. J of Thorac Dis 14(4):1256–1266

    Google Scholar 

  11. Nakatani D, Sato H, Kinjo K, Mizuno H, Hishida E, Hirayama A, Mishima M, Ito H, Matsumura Y, Hori M (2003) Effect of successful late reperfusion by primary coronary angioplasty on mechanical complications of acute myocardial infarction. Am J Cardiol 92(7):785–788

    PubMed  Google Scholar 

  12. Qian G, Jin RJ, Fu ZH, Yang YQ, Su HL, Dong W, Guo J, Jing J, Guo YL, Chen YD (2017) Development and validation of clinical risk score to predict the cardiac rupture in patients with STEMI. Am J Emerg Med 35(4):589–593

    PubMed  Google Scholar 

  13. Thygesen K, Alpert JS, Jaffe AS, Chaitman BR, Bax JJ, Morrow DA, White HD (2018) Fourth universal definition of myocardial infarction (2018). J Am Coll Cardiol 72(18):2231–2264

    PubMed  Google Scholar 

  14. Murakami T, Sakakura K, Jinnouchi H, Taniguchi Y, Tsukui T, Watanabe Y, Yamamoto K, Seguchi M, Wada H, Fujita H (2023) Acute ischemic stroke and transient ischemic attack in ST-segment elevation myocardial infarction patients who underwent primary percutaneous coronary intervention. J Clin Med 12:840

    PubMed Central  PubMed  Google Scholar 

  15. Murakami T, Sakakura K, Jinnouchi H, Taniguchi Y, Tsukui T, Watanabe Y, Yamamoto K, Seguchi M, Wada H, Fujita H (2022) Complications related to veno-arterial extracorporeal membrane oxygenation in patients with acute myocardial infarction: VA-ECMO complications in AMI. J Cardiol 79(2):170–178

    PubMed  Google Scholar 

  16. Ishibashi S, Sakakura K, Asada S, Taniguchi Y, Jinnouchi H, Tsukui T, Watanabe Y, Yamamoto K, Seguchi M, Wada H, Fujita H (2022) Association of collateral flow with clinical outcomes in patients with acute myocardial infarction. Heart Vessels 37(9):1496–1505

    PubMed  Google Scholar 

  17. Tsukui T, Sakakura K, Taniguchi Y, Yamamoto K, Seguchi M, Wada H, Momomura S-i, Fujita H (2020) Association between the door-to-balloon time and mid-term clinical outcomes in patients with ST-segment elevation myocardial infarction. Intern Med 59(13):1597–1603

    CAS  PubMed Central  PubMed  Google Scholar 

  18. Granger CB, Goldberg RJ, Dabbous O, Pieper KS, Eagle KA, Cannon CP, Van De Werf F, Avezum A, Goodman SG, Flather MD, Fox KA (2003) Predictors of hospital mortality in the global registry of acute coronary events. Arch Intern Med 163(19):2345–2353

    PubMed  Google Scholar 

  19. De Luca G, Suryapranata H, van’t Hof AWJ, de Boer MJ, Hoorntje JCA, Dambrink JHE, Gosselink ATM, Ottervanger JP, Zijlstra F (2004) Prognostic assessment of patients with acute myocardial infarction treated with primary angioplasty. Circulation 109(22):2737–2743

    PubMed  Google Scholar 

  20. Steyerberg EW, Eijkemans MJ, Harrell FE Jr, Habbema JD (2001) Prognostic modeling with logistic regression analysis: in search of a sensible strategy in small data sets. Med Decis Making 21(1):45–56

    CAS  PubMed  Google Scholar 

  21. O’Mahony C, Jichi F, Pavlou M, Monserrat L, Anastasakis A, Rapezzi C, Biagini E, Gimeno JR, Limongelli G, McKenna WJ, Omar RZ, Elliott PM (2014) A novel clinical risk prediction model for sudden cardiac death in hypertrophic cardiomyopathy (HCM risk-SCD). Eur Heart J 35(30):2010–2020

    PubMed  Google Scholar 

  22. Steyerberg EW (2019) Clinical prediction models: a practical approach to development, validation, and updating, 2nd edn. Springer, Cham, pp 191–206

    Google Scholar 

  23. Fu Y, Chen M, Sun H, Guo Z, Gao Y, Yang X, Li K, Wang L (2020) Blood group A: a risk factor for heart rupture after acute myocardial infarction. BMC Cardiovasc Disord 20:471

    PubMed Central  PubMed  Google Scholar 

  24. Qian G, Liu HB, Wang JW, Wu C, Chen YD (2013) Risk of cardiac rupture after acute myocardial infarction is related to a risk of hemorrhage. J Zhejiang Univ Sci B 14(8):736–742

    PubMed Central  PubMed  Google Scholar 

  25. Widmer A, Linka AZ, Attenhofer Jost CH, Buergi B, Brunner-La Rocca HP, Salomon F, Seifert B, Jenni R (2003) Mechanical complications after myocardial infarction reliably predicted using C-reactive protein levels and lymphocytopenia. Cardiology 99(1):25–31

    CAS  PubMed  Google Scholar 

  26. Yamamoto S, Yamazaki S, Shimizu T, Takeshima T, Fukuma S, Yamamoto Y, Tochitani K, Tsuchido Y, Shinohara K, Fukuhara S (2015) Prognostic utility of serum CRP levels in combination with CURB-65 in patients with clinically suspected sepsis: a decision curve analysis. BMJ Open 5(4):e007049

    PubMed Central  PubMed  Google Scholar 

  27. Steyerberg EW, Vergouwe Y (2014) Towards better clinical prediction models: seven steps for development and an ABCD for validation. Eur Heart J 35(29):1925–1931

    PubMed Central  PubMed  Google Scholar 

  28. Van Calster B, McLernon DJ, van Smeden M, Wynants L, Steyerberg EW (2019) Calibration: the Achilles heel of predictive analytics. BMC Med 17(1):230

    PubMed Central  PubMed  Google Scholar 

  29. Subramanian V, Mascha EJ, Kattan MW (2021) Developing a clinical prediction score: comparing prediction accuracy of integer scores to statistical regression models. Anesth Analg 132(6):1603–1613

    PubMed  Google Scholar 

  30. Moreyra AE, Huang MS, Wilson AC, Deng Y, Cosgrove NM, Kostis JB (2010) Trends in incidence and mortality rates of ventricular septal rupture during acute myocardial infarction. Am J Cardiol 106(8):1095–1100

    PubMed  Google Scholar 

  31. Moreno R, López-Sendón J, García E, de Isla LP, de Sá EL, Ortega A, Moreno M, Rubio R, Soriano J, Abeytua M, García-Fernández M-A (2002) Primary angioplasty reduces the risk of left ventricular free wall rupture compared with thrombolysis in patients with acute myocardial infarction. J Am Coll Cardiol 39(4):598–603

    PubMed  Google Scholar 

  32. Ipek G, Onuk T, Karatas MB, Güngör B, Atasoy I, Murat A, Aldag M, Yelgec NS, Dayi SU, Bolca O (2015) Relationship between neutrophil-to-lymphocyte ratio and left ventricular free wall rupture in acute myocardial infarction. Cardiology 132(2):105–110

    PubMed  Google Scholar 

  33. Bi X, Wang B, Tse G, Dai C, Chen X, Meng F, Wang Y (2022) Clinical manifestation of cardiac rupture in patients with ST-segment elevation myocardial infarction: early versus late primary percutaneous coronary intervention. Glob Heart 17(1):69

    PubMed Central  PubMed  Google Scholar 

  34. Figueras J, Calvo F, Cortadellas J, Soler-Soler J (1997) Comparison of patients with and without papillary muscle rupture during acute myocardial infarction. Am J Cardiol 80(5):625–627

    CAS  PubMed  Google Scholar 

  35. Kawano H, Miyauchi K, Okada R, Daida H, Yokoi H, Miyano H, Takaya J, Satoh H, Yamaguchi H, Suda K et al (1994) Histopathological study of cardiac rupture following myocardial infarction with and without thrombolytic therapy. J Cardiol 24(4):249–255

    CAS  PubMed  Google Scholar 

  36. Ortiz-Pérez JT, Lee DC, Meyers SN, Davidson CJ, Bonow RO, Wu E (2010) Determinants of myocardial salvage during acute myocardial infarction: evaluation with a combined angiographic and CMR myocardial salvage index. JACC Cardiovasc Imaging 3(5):491–500

    PubMed  Google Scholar 

  37. Ino Y, Kubo T, Tomobuchi Y, Oshika H, Kitabata H, Obana M, Tanimoto T, Takarada S, Tanaka A, Imanishi T, Okamura Y, Akasaka T (2009) Branch segment occlusion with acute myocardial infarction is a risk for left ventricular free wall rupture. Circ J 73(8):1473–1478

    PubMed  Google Scholar 

  38. Masci PG, Andreini D, Francone M, Bertella E, De Luca L, Coceani M, Mushtaq S, Mariani M, Carbone I, Pontone G, Agati L, Bogaert J, Lombardi M (2013) Prodromal angina is associated with myocardial salvage in acute ST-segment elevation myocardial infarction. Eur Heart J Cardiovasc Imaging 14(11):1041–1048

    PubMed  Google Scholar 

  39. Yamamoto K, Sakakura K, Akashi N, Watanabe Y, Noguchi M, Taniguchi Y, Ugata Y, Wada H, Momomura SI, Fujita H (2018) Clinical outcomes after acute myocardial infarction according to a novel stratification system linked to a rehabilitation program. J Cardiol 72(3):227–233

    PubMed  Google Scholar 

  40. Koeda Y, Itoh T, Ishikawa Y, Morino Y, Mizutani T, Ako J, Nakano M, Yoshioka K, Ikari Y, Inami S, Sakuma M, Taguchi I, Ishikawa T, Sugimura H, Sugi K, Matsumoto K, Mitarai T, Kunishima T, Akashi YJ, Nomura T, Fukushi K, Yoshino H, Cardiovascular Research Consortium U (2020) A multicenter study on the clinical characteristics and risk factors of in-hospital mortality in patients with mechanical complications following acute myocardial infarction. Heart Vessels 35(8):1060–1069

    PubMed  Google Scholar 

  41. Pavlou M, Ambler G, Seaman SR, Guttmann O, Elliott P, King M, Omar RZ (2015) How to develop a more accurate risk prediction model when there are few events. BMJ 351:h3868

    PubMed Central  PubMed  Google Scholar 

  42. Steyerberg EW (2019) Clinical prediction models: a practical approach to development, validation, and updating, 2nd edn. Springer, Cham, pp 329–344

    Google Scholar 

  43. Norrish G, Ding T, Field E, Ziólkowska L, Olivotto I, Limongelli G, Anastasakis A, Weintraub R, Biagini E, Ragni L, Prendiville T, Duignan S, McLeod K, Ilina M, Fernández A, Bökenkamp R, Baban A, Kubuš P, Daubeney PEF, Sarquella-Brugada G, Cesar S, Marrone C, Bhole V, Medrano C, Uzun O, Brown E, Gran F, Castro FJ, Stuart G, Vignati G, Barriales-Villa R, Guereta LG, Adwani S, Linter K, Bharucha T, Garcia-Pavia P, Rasmussen TB, Calcagnino MM, Jones CB, De Wilde H, Toru-Kubo J, Felice T, Mogensen J, Mathur S, Reinhardt Z, O’Mahony C, Elliott PM, Omar RZ, Kaski JP (2019) Development of a Novel risk prediction model for sudden cardiac death in childhood hypertrophic cardiomyopathy (HCM risk-kids). JAMA Cardiol 4(9):918–927

    PubMed Central  PubMed  Google Scholar 

  44. Dreyfus J, Audureau E, Bohbot Y, Coisne A, Lavie-Badie Y, Bouchery M, Flagiello M, Bazire B, Eggenspieler F, Viau F, Riant E, Mbaki Y, Eyharts D, Senage T, Modine T, Nicol M, Doguet F, Nguyen V, Le Tourneau T, Tribouilloy C, Donal E, Tomasi J, Habib G, Selton-Suty C, Raffoul R, Iung B, Obadia JF, Messika-Zeitoun D (2022) TRI-SCORE: a new risk score for in-hospital mortality prediction after isolated tricuspid valve surgery. Eur Heart J 43(7):654–662

    CAS  PubMed  Google Scholar 

  45. Honda T, Chen S, Hata J, Yoshida D, Hirakawa Y, Furuta Y, Shibata M, Sakata S, Kitazono T, Ninomiya T (2022) Development and validation of a risk prediction model for atherosclerotic cardiovascular disease in japanese adults: the hisayama study. J Atheroscler Thromb 29(3):345–361

    CAS  PubMed  Google Scholar 

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Acknowledgements

The authors acknowledge all staff in the catheter laboratory, cardiology units, and emergency and critical care units in Saitama Medical Center, Jichi Medical University for their technical support in this study.

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Correspondence to Kenichi Sakakura.

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Dr. Sakakura has received speaking honoraria from Abbott Vascular, Boston Scientific, Medtronic Cardiovascular, Terumo, OrbusNeich, Japan Lifeline, Kaneka, and NIPRO; he has served as a proctor for Rotablator for Boston Scientific, and he has served as a consultant for Abbott Vascular and Boston Scientific. Prof. Fujita has served as a consultant for Mehergen Group Holdings, Inc. Other authors have no conflicts of interest to declare.

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Murakami, T., Sakakura, K., Jinnouchi, H. et al. Development of a simple prediction model for mechanical complication in ST-segment elevation myocardial infarction patients after primary percutaneous coronary intervention. Heart Vessels 39, 288–298 (2024). https://doi.org/10.1007/s00380-023-02336-8

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