Tesis

Analisis Kejadian Kegagalan Implantasi Pada Fertilisasi In Vitro Siklus Tandur Alih Embrio Segar Di RSUPN Dr. Cipto Mangunkusumo = Analysis of Implantation Failure in In Vitro Fertilization Fresh Embryo Transfer Cycles at Dr. Cipto Mangunkusumo National General Hospital.

Latar Belakang Fertilisasi in vitro (FIV) merupakan salah satu teknologi reproduksi berbantu (TRB) yang paling efektif untuk mengatasi infertilitas. Namun, meskipun kemajuan teknologi FIV meningkat pesat, tingkat keberhasilan klinisnya masih relatif rendah, dengan lebih dari separuh siklus berakhir tanpa kehamilan klinis. Kegagalan implantasi merupakan penyebab utama rendahnya angka keberhasilan tersebut, yang dapat dipengaruhi oleh berbagai faktor maternal, paternal, embrional, dan endometrial. Ketebalan endometrium, kualitas embrio, cadangan ovarium, serta fragmentasi DNA sperma merupakan parameter yang paling sering dikaitkan dengan luaran FIV. Hingga kini, belum terdapat model prediksi yang tervalidasi untuk memprediksi kegagalan implantasi pada populasi Indonesia, sehingga penelitian ini dilakukan untuk mengidentifikasi faktor-faktor prediktif serta membangun model prediksi yang aplikatif di tingkat klinik. Metode Penelitian ini merupakan studi kohort retrospektif menggunakan data pasien program FIV di Klinik Yasmin RSUPN Dr. Cipto Mangunkusumo periode 2013–2021, melibatkan 3.078 siklus FIV dengan tandur alih embrio segar. Variabel yang dianalisis meliputi karakteristik demografis, faktor endometrium, oosit, embrio, dan sperma. Luaran utama adalah kegagalan implantasi/kegagalan kehamilan klinis. Analisis meliputi uji univariat, bivariat, korelasi, dan multivariat menggunakan regresi logistik. Kinerja model dievaluasi dengan kurva ROC, AUC, sensitivitas, spesifisitas, serta F1-score dan precision–recall untuk menentukan performa diskriminatif model. Kegagalan kehamilan biokimia terjadi pada 40,2% siklus, sementara kehamilan klinis tercapai pada 31,0%. Analisis multivariat menunjukkan peningkatan risiko kegagalan implantasi pada usia maternal (OR 1,076; 95% IK 1,053–1,099), IMT maternal (OR 1,409; 95% IK 1,358–1,462), durasi stimulasi (OR 1,123; 95% IK 1,106–1,140), kadar LH hari pemicu hCG (OR 1,113; 95% IK 1,084–1,142), DNA fragmentation index (OR 1,107; 95% IK 1,085–1,129), serta jumlah embrio kualitas average yang ditransfer (OR 1,691; 95% IK 1,344–2,127). Faktor protektif meliputi jumlah oosit yang dipetik (OR 0,895; 95% IK 0,874–0,917), ketebalan endometrium (OR 0,754; 95% IK 0,720–0,790), dan jumlah embrio kualitas excellent yang ditransfer (OR 0,414; 95% IK 0,328–0,522). Model menunjukkan diskriminasi sangat baik (AUC 0,933) dan kalibrasi baik (p Hosmer–Lemeshow = 0,127). Kesimpulan Kegagalan implantasi pada FIV merupakan hasil interaksi multifaktor yang melibatkan komponen endometrium, kualitas embrio, serta faktor paternal dan maternal. Model prediksi multivariat yang dihasilkan menunjukkan akurasi tinggi dan berpotensi digunakan sebagai alat bantu klinis dalam memberikan konseling prediktif, perencanaan terapi individual, serta peningkatan efisiensi program FIV di Indonesia. Kata Kunci: fertilisasi in vitro (FIV); siklus tandur alih embrio segar; kegagalan implantasi; faktor maternal; faktor paternal


Background In vitro fertilization (IVF) is one of the most effective assisted reproductive technologies (ART) for overcoming infertility. However, despite significant technological advancements, clinical success rates remain relatively low, with more than half of all IVF cycles ending without a clinical pregnancy. Implantation failure is the leading cause of these suboptimal outcomes and may be influenced by multiple maternal, paternal, embryonic, and endometrial factors. Endometrial thickness, embryo quality, ovarian reserve, and sperm DNA fragmentation are among the most frequently reported predictors of IVF outcomes. To date, no validated predictive model for implantation failure has been developed for the Indonesian population. Therefore, this study aimed to identify predictive factors associated with implantation failure and to construct a clinically applicable prediction model tailored to the local population. Methods This was a retrospective cohort study using data from IVF patients treated at the Yasmin Clinic, Dr. Cipto Mangunkusumo National General Hospital, between 2013 and 2021, comprising 3,078 fresh embryo transfer IVF cycles. Variables analyzed included demographic characteristics, endometrial, oocyte, embryo, and sperm parameters. The primary outcome was implantation failure or clinical pregnancy failure. Statistical analyses consisted of univariate, bivariate, correlation, and multivariate tests using logistic regression. Model performance was evaluated using receiver operating characteristic (ROC) curves, area under the curve (AUC), sensitivity, specificity, F1- score, and precision–recall metrics to assess the model’s discriminative ability. xiii Universitas Indonesia Results Biochemical pregnancy failure occurred in 40.2% of cycles, while clinical pregnancy was achieved in 31.0%. Multivariable analysis identified advanced maternal age (OR 1.076; 95% CI 1.053–1.099), higher maternal BMI (OR 1.409; 95% CI 1.358–1.462), longer stimulation duration (OR 1.123; 95% CI 1.106–1.140), elevated LH on trigger day (OR 1.113; 95% CI 1.084–1.142), increased sperm DNA fragmentation index (OR 1.107; 95% CI 1.085–1.129), and transfer of average-quality embryos (OR 1.691; 95% CI 1.344– 2.127) as independent risk factors for implantation failure. Protective factors included a greater number of retrieved oocytes (OR 0.895; 95% CI 0.874–0.917), increased endometrial thickness (OR 0.754; 95% CI 0.720–0.790), and transfer of excellent-quality embryos (OR 0.414; 95% CI 0.328–0.522). The final model demonstrated excellent discrimination (AUC 0.933) and good calibration (Hosmer–Lemeshow p = 0.127). Conclusion Implantation failure in IVF is a multifactorial process involving endometrial receptivity, embryo quality, and both maternal and paternal factors. The multivariate prediction model developed in this study demonstrated high accuracy and has potential clinical utility for predictive counseling, individualized treatment planning, and improving IVF program efficiency in Indonesia.
Keywords: in vitro fertilization (IVF); fresh embryo transfer; implantation failure; maternal factors; paternal factors.