Universitas Syiah Kuala | ELECTRONIC THESES AND DISSERTATION

Electronic Theses and Dissertation

Universitas Syiah Kuala

    THESES
Suhemi, ANALISIS NILAI SYSTEMIC IMMUNE-INFLAMATION INDEX SEBAGAI FAKTOR PROGNOSTIK PADA PASIEN HUMAN IMUNODEFICIENCY VIRUS. Banda Aceh Program Pendidkan Dokter Spesialis Penyakit Dalam,2026

Infeksi human immunodeficiency virus (hiv) masih menjadi masalah kesehatan dengan mortalitas tinggi, terutama pada pasien rawat inap, sehingga diperlukan biomarker sederhana untuk penilaian prognosis. penelitian ini bertujuan menganalisis nilai systemic immune-inflammation index (sii) sebagai faktor prognostik terhadap kematian selama perawatan pada pasien hiv. penelitian ini merupakan studi observasional analitik dengan desain kohort retrospektif menggunakan data rekam medis pasien hiv dewasa yang dirawat di rsud dr. zainoel abidin banda aceh periode januari 2021–desember 2025. nilai sii dihitung dari trombosit × neutrofil / limfosit. analisis dilakukan secara deskriptif, bivariat, roc, kaplan–meier, dan regresi cox multivariat. sebanyak 156 pasien dianalisis. nilai cut-off sii optimal adalah 1478,36 dengan auc 0,714, sensitivitas 83,9%, dan spesifisitas 54,0%. pasien dengan sii tinggi memiliki probabilitas survival lebih rendah (14,58 vs 25,63 hari; p



Abstract

Human Immunodeficiency Virus (HIV) infection remains a major global health challenge with substantial morbidity and mortality, particularly among hospitalized patients, underscoring the need for simple and accessible prognostic biomarkers. This study aimed to evaluate the prognostic value of the Systemic Immune-Inflammation Index (SII) for in-hospital mortality in patients with HIV. This analytic observational study employed a retrospective cohort design using medical records of 156 adult HIV patients admitted to dr. Zainoel Abidin General Hospital, Banda Aceh, between January 2021 and December 2025. SII was calculated at admission as platelet count × neutrophil count / lymphocyte count. Data were analyzed using bivariate analysis, receiver operating characteristic (ROC) curve analysis, Kaplan–Meier survival analysis, and multivariable Cox proportional hazards regression. During hospitalization, 56 patients (35.9%) died. The optimal SII cut-off value for predicting mortality was 1478.36 (AUC 0.714; sensitivity 83.9%; specificity 54.0%). Patients with high SII had significantly shorter mean survival compared to those with low SII (14.58 vs 25.63 days; log-rank p



    SERVICES DESK