<![CDATA[Pendeteksi awal pada saat pasien masuk di Intensive Care Unit (ICU) merupakan bagian penting dalam membantu menurunkan angka kematian. Tujuan penelitian ini untuk menganalisis faktor-faktor yang berhubungan dengan angka kematian pasien ICU. Cross sectional study design digunakan dalam penelitian ini, dan pengambilan sample menggunakan total sampling dari rekam medis pasien di ICU pada bulan Oktober 2023 sampai September 2024. Analisis statistik yang digunakan adalah Pearson correlation coefficient, t-test, one-way ANOVA, and Hierarchical multiple regression. Sebanyak 73 data pasien meninggal di ICU diambil dalam penelitian ini. Hasinya mendapati bahwa, variable yang berhubungan significant dengan angka kematian pasien di ICU adalah usia (r= 0.24, p= 0.05), komorbiditas (r= -0.87, p= 0.01), kesadaran (r= -0.27, p= 0.01), dan diastolic pasien (r= 0.28, p= 0.05); Sedangkan veriabel ventilator mekanik, admisi, dan diagnostic tidak mempunyai hubungan yang significant dengan angka kematian pasien di ICU. Selain itu, variable predictor dari angka kematian pasien di ICU adalah usia, komorbiditas, systolic, diastolic dan diagnostic akut dari pasien dengan menyumbang 99.5% kematian di ICU. Implikasi penelitian ini adalah untuk memonitor ketat pasien ICU dengan usia lanjut, komorbidity, status kesadaran, dan tekanan darah terhadap angka kematian; Selain itu, tenaga kesehatan perlu memperhatikan secara cermat terhadap predictor dari angka kematian pasien di ICU seperti usia lansia, masuk dengan diagnosa akut, memiliki banyak komorbiditas, serta tidak stabilnya tekanan darah (systolic maupun diastolic) pada saat pasien masuk ke ICU. Early detection upon patient admission to the Intensive Care Unit (ICU) is crucial in reducing mortality rates. This study analyzes the factors associated with ICU patient mortality. A cross-sectional study design was employed, with total sampling conducted using medical records of ICU patients from October 2023 to September 2024. The statistics analysis were used by Pearson correlation coefficient, t-test, one-way ANOVAs, and Hierarchical multiple regression. A total of 73 ICU patient mortality cases were analyzed. The findings indicate that variables significantly associated with ICU mortality included age (r = 0.24, p = 0.05), comorbidities (r= -0.87, p= 0.01), level of consciousness (r= -0.27, p= 0.01), and diastolic blood pressure (r= 0.28, p= 0.05). However, mechanical ventilation, admission type, and primary diagnosis were not significantly associated with ICU mortality. Additionally, the predictive factors for ICU mortality included age, comorbidities, systolic blood pressure, diastolic blood pressure, and acute diagnosis, collectively accounting for 99.5% of ICU deaths. The findings highlight the need for close monitoring of ICU patients, particularly those who are elderly, have multiple comorbidities, exhibit altered consciousness, or have unstable blood pressure. Furthermore, healthcare providers should carefully assess key predictors of ICU mortality, including advanced age, acute admission diagnosis, high comorbidity burden, and blood pressure instability (both systolic and diastolic) upon ICU admission.]]>
