Latar belakang: Populasi usia lanjut dengan penyakit jantung koroner yang menjalani tindakan intervensi koroner perkutan (IKP) menunjukkan tren meningkat. Di sisi lain, kelompok usia lanjut juga dihadapkan dengan major adverse cardiac events pasca tindakan IKP. Identifikasi faktor prediktor yang mempengaruhi terjadinya MACE 30 hari diharapkan dapat menjadi sarana stratifikasi risiko pratindakan, meningkatkan luaran klinis serta menjadi pertimbangan pemilihan strategi intervensi pada pasien PJK usia lanjut.Tujuan: Mengetahui insidens MACE 30 hari, faktor prediktor MACE 30 hari pada pasien PJK usia lanjut yang menjalani tindakan IKP, dan pengembangan model prediksi MACE 30 hari.Metode: studi kohort retrospektif dengan menulusuri rekam medis pasien usia lanjut yang menjalani IKP di RSCM periode Januari 2017-Desember 2021. Dilakukan analisis bivariat chi-square antara faktor usia, jenis kelamin, hiperglikemia saat admisi, kreatinin serum, kelas Killip, status fungsional, status nutrisi, status frailty, dan jenis PJK dengan kejadian MACE 30 hari pascatindakan IKP. Analisis multivariat dan model prediksi dilakukan dengan metode regresi logistik.Hasil: Terdapat 616 subjek penelitian untuk diteliti. Insidens MACE 30 hari pada pasien PJK usia lanjut sebesar 5,4%. Hasil analisis bivariat menunjukkan adanya hubungan antara faktor hiperglikemia saat admisi, kelas Killip, status fungsional, status nutrisi, dan jenis PJK dengan kejadian MACE 30 hari (p<0,05). Hasil regresi logistik menunjukkan Kelas Killip dan jenis PJK merupakan faktor prediktor independen terjadinya MACE 30 hari dengan adjusted OR 8,841 (IK95% 3,339-23,410) untuk kelas Killip dan adjusted OR 3,774 (1,365-10,426) untuk PJK. Model prediksi MACE 30 hari memiliki nilai AUC 0,7995 (IK95% 0,712-0,886)Kesimpulan: MACE 30 hari pada pasien PJK usia lanjut yang menjalani IKP sebesar 5,4% dengan faktor prediktor independen kelas Killip dan jenis PJK.

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Background: The elderly with coronary heart disease undergoing percutaneous coronary intervention (PCI) shows an increasing trend. On the other hand, the elderly group is also faced with major adverse cardiac events after PCI. Identification of predictors that influence the occurrence of 30-day MACE is expected to be a means of preprocedural risk stratification, improve clinical outcomes and become a consideration for selecting intervention strategies in elderly CHD patients.

Objectives: To determine the incidence of 30-day MACE, the predictors of 30-day MACE in elderly CHD patients undergoing PCI, and the development of 30-day MACE prediction model.

Methods: Retrospective cohort study by reviewing medical records of elderly patients undergoing PCI at RSCM for the period January 2017-December 2021. Chi-square bivariate analysis was performed between predictors of age, sex, hyperglycemia at admission, serum creatinine, Killip class, functional status, nutritional status, frailty status, and type of CHD with MACE events 30 days after PCI. Multivariate analysis and prediction models were performed using the logistic regression.

Results: There were 616 research subjects to be studied. The incidence of 30-day MACE in elderly CHD patients was 5.4%. The results of bivariate analysis showed a relationship between hyperglycemia at admission, Killip class, functional status, nutritional status, and type of CHD with 30-day MACE (p<0.05). Logistic regression results showed Killip class and CHD type were independent predictors of 30-day MACE with adjusted OR 8.841 (95%CI 3.339-23.410) for Killip class and adjusted OR 3,774 (1.365-10.426) for type of CHD. The 30-day MACE prediction model has an AUC value of 0.7995 (95%CI 0.712-0.886)

Conclusion: Incidence of 30-day MACE in elderly with CHD undergoing PCI is 5.4% with Killip class and type of CHD as independent predictor factors.