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"ABSTRAKLatar Belakang: Salah satu modalitas yang dapat memprediksi aritmia ventrikel pasca-infark miokardium (MI), terutama MI anterior, adalah signal-averaged electrocardiogram (SA-ECG), melalui deteksi late potentials (LP) yang merupakan substrat aritmia ventrikel. Faktor-faktor ekstrakardiak yang sekaligus menjadi faktor risiko MI, misalnya hipertensi, diabetes, dislipidemia, dan obesitas, dipikirkan berhubungan dengan kejadian aritmia ventrikel pasca-MI melalui berbagai patomekanisme, yang kemungkinan berkaitan erat dengan timbulnya LP.Tujuan: Penelitian ini bertujuan untuk mengetahui pengaruh faktor-faktor ekstrakardiak terhadap timbulnya LP saat awal perawatan pada pasien MI anterior yang dirawat di intensive cardiac care unit (ICCU).Metode: Desain studi ini adalah potong lintang dengan pemeriksaan SA-ECG sewaktu terhadap 80 subjek penelitian yang mengalami MI anterior di ICCU selama periode Desember 2018-2019. Riwayat medis dan faktor risiko ekstrakardiak direkapitulasi, sedangkan data SA-ECG diambil dari pemeriksaan langsung maupun data SA-ECG pasien MI anterior ICCU dalam periode tersebut. Studi ini menggunakan analisis multivariat dengan uji regresi logistik.Hasil: Faktor yang paling umum ditemukan adalah hipertensi (70,00%), diikuti dislipidemia (56,25%), diabetes (46,25%), dan obesitas (38,75%). Obesitas dan dislipidemia merupakan faktor ekstrakardiak yang berperan paling besar terhadap prevalensi LP. Namun, dari analisis tambahan, kami menemukan bahwa diabetes dengan hiperglikemia akut juga memiliki pengaruh terhadap terjadinya LP. Besar OR untuk diabetes dengan hiperglikemia akut, obesitas, dan dislipidemia masing-masing adalah sebesar 4,806 (IK95% 0,522-44,232), 4,291 (IK95% 0,469-39,299), dan 3,237 (IK95% 0,560-18,707). Hubungan tersebut tidak bermakna secara statistik.Kesimpulan: Pasien MI anterior yang menderita diabetes dengan hiperglikemia akut, obesitas, dan dislipidemia cenderung memiliki prevalensi LP yang lebih tinggi, namun secara statistik hubungan tersebut tidak bermakna. Untuk meningkatkan nilai prognostik SA-ECG, diperlukan pemeriksaan serial selama perawatan.

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ABSTRACTIntroduction: One modality that can predict ventricular arrhythmias after myocardial infarction (MI), particularly anterior MI, is signal-averaged electrocardiogram (SA-ECG), through the detection of late potentials (LP) which is a substrate for ventricular arrhythmias. Extracardiac factors, which are also risk factors for MI, such as hypertension, diabetes, dyslipidemia, and obesity, are apparently associated with post-MI ventricular arrhythmias, which in turn may be correlated with LP.Aim: This study aims to determine the effect of extracardiac risk factors on LP incidence in anterior MI patients treated in the intensive cardiac care unit (ICCU).Methods: This was a cross-sectional study in which 80 subjects with anterior MI during December 2018-2019 underwent SA-ECG examination. The medical history and extracardiac risk factors were recapitulated, then the SA-ECG data was taken from either direct examination or ICCU patients database in that period. This study used multivariate analysis with logistic regression test.Results: The most common factors found were hypertension (70.00%), followed by dyslipidemia (56.25%), diabetes (46.25%), and obesity (38.75%). Obesity and dyslipidemia are extracardiac factors with biggest role in the prevalence of LP. However, from subgroup analysis, we found that diabetes with acute hyperglycemia also had immense influence on the occurrence of LP. The OR for diabetes with acute hyperglycemia, obesity, and dyslipidemia were 4.806 (IK95% 0.522-44.232), 4.291 (IK95% 0.469-39.299), and 3.237 (IK95% 0.560-18.707). However, the association is not statistically significant.Conclusion: Patients with anterior MI who suffer from diabetes with hyperglycemia in admission, obesity, and dyslipidemia potentially have a higher LP prevalence, despite statistically insignificance. To increase the prognostic value of SA-ECG, serial examinations are needed during hospitalization."

"Latar Belakang : Telah banyak dipublikasikan berbagai macam algoritme untukmenentukan lokasi jaras tambahan pada pasien dengan sindroma Wolff-ParkinsonWhite.Algoritme-algoritme tersebut memiliki akurasi yang baik meskipunmemiliki alur yang komplek dan sulit untuk diingat. Berbagai macam algoritmeyang berkembang menggunakan morfologi delta wave dan polaritas komplek QRSdalam penyusunannya. Dengan adanya teknologi kateter ablasi yang ada saat inialgoritme yang komplek tidak diperlukan lagi. Diperlukan suatu algoritme yangsederhana, memiliki akurasi yang baik dan mudah diingat. Penelitian ini bertujuan untuk menilai akurasi algoritme sederhana untuk memprediksi lokasi jarastambahan. Metode : Penelitian ini merupakan studi potong lintang yang dilakukan diDepartemen Kardiologi dan Kedokteran Vaskuler FKUI/ Pusat Jantung NasionalHarapan Kita PJNHK. Data yang diambil berupa elektrokardiografi EKG pada67 pasien dengan sindroma Wolff-Parkinson-White yang menjalani tindakan ablasiperiode Januari 2014 - Oktober 2016. Data EKG yang terkumpul dibacaberdasarkan algoritme baru oleh dua orang penilai independen kemudiandibandingkan dengan hasil ablasi pada tabel 2x2. Hasil Penelitian : sampel akhir sebanyak 47 data hasil bacaan EKG observerterpercaya dihitung berdasarkan tabel 2x2 dengan hasil ablasi. Hasil menunjukkanalgoritme ini memiliki sensitivitas left free wall 45, septal 80, right free wall92, spesifisitas left free wall 96, septal 69, right free wall 85. Nilai dugapositif NDP left free wall 90, septal 55, dan right free wall 67. Nilai duganegatif NDN left free wall 70, septal 88, dan right free wall 97. Akurasialgoritme bervariasi dari 73 -87. Didapatkan perhitungan kesepahaman antarpenilai dengan nilai kappa 0,74-0,93. Perhitungan likelihood ratio menunjukkanlikelihood ratio positif left free wall 11,23, septal 2,23, dan right free wall 6,57.Likelihood ratio negatif left free wall 0,57, septa 0,28, dan right free wall 0,09. Kesimpulan : Algoritme baru yang lebih sederhana ini memiliki akurasi yang baikdengan angka kesepahaman antar penilai yang baik sehingga dapat digunakansecara umum.

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Background : A lot of algorithms in localizing accessory pathway AP in patientswith Wolff Parkinson White Syndrome have been published. Although many ofthose methods have high accuracy, they are complicated and difficult to memorize.Most of the established algorithm use delta wave morphology and QRS polarity todetermine the location. With the technology of catheter ablation nowadays suchcomplex algorithms are not really needed. This study aim to investigate theaccuracy of a simple algorithm to predict the location of accessory pathways.

Methods : This was a cross sectional study conducted in the NationalCardiovascular Center Harapan Kita RSJPDHK Department Cardiology andVascular Medicine, FMUI. The electrocardiography ECG findings of 67 patientswith Wolff Parkinson White syndrome underwent ablations from January 2014until October 2016 were used in the current study. Those ECGs were analyzed usingthe new algorithm and were evaluated by two independent observers and comparedwith ablation results in a 2x2 table.

Results : The final number of samples was 47 ECGs. The algorithm showed it hada sensitivity of 45 on left free wall, 80 on septal, 92 on right free wall APs inaddition to the specificity of 96 on left free wall, 69 on septal, 85 on right freewall APs. Positive predictive value PPV were 90 on left free wall, 55 on septaland 67 on right free wall APs. Negative predictive value NPV were 70 on leftfree wall, 88 on septal and 97 on right free wall APs. Algorithm accuracy variedfrom 73 to 87. Inter observer agreement calculation was a kappa of 0.74 mdash 0.93.Likelihood ratio calculation identified the positive likelihood ratio of 11.23 on leftfree wall, 2.23 on septal and 6.57 on right free wall APs and negative likelihoodratio of 0.57 on left free wall, 0.28 on septal and 0.09 on right free wall APs.

Conclusion : This new and simple algorithm provide a remarkable accuracy with agood inter observer agreements. Therefore this algorithm is potential to beimplemented in general practice."

"High mortality in Indonesia, caused by acute coronary syndrome, has reached 26 %. In 10 years, National housing health survey or Survei Kesehatan Rumah Tangga Nasional ( SKRTN), under health departement of Republic of Indonesia, stated mortality which is caused by acute coronary syndrome has increased enourmously. It can be avoided by doing early acute coronary syndrome detection like ECG recording. Anyway, some those patients rarely do ECG recording because of expenses and time. By using Blutooth feature on PDA (Personal Digital Assistant) or a Bluetooth dongle on computer, a Telecardiology can be done anywhere and anytime so that coronary syndrome can be detected earlier by medics. Telecardiology research used a microcontroler, a computer and a PDA to record ECG signals. ECG recording is taken in real-time then stored in computer or PDA data base. To detec QRS waves in ECG signals, PanTompkins were used."