Rahmat, Rosyadi Aziz
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Training On Improving Early Detection And Management Of Sepsis: Education On The Use Of Biomarkers And Clinical Parameters For Health Care Workers Rahmat, Rosyadi Aziz
JURNAL PENGMAS KESTRA (JPK) Vol. 4 No. 1 (2024): Jurnal Pengmas Kestra (JPK)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LP2M) Institut Kesehatan Medistra Lubuk Pakam

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Abstract

Sepsis is a systemic syndrome that results from an infection that causes an uncontrolled inflammatory response in the body. This inflammatory response can lead to tissue damage, organ dysfunction and even multiple organ failure. Sepsis can progress to septic shock, a condition where blood pressure is extremely low and fails to recover despite fluid administration. In Indonesia, sepsis is also a serious health problem, with prevalence increasing along with the development of infectious diseases. A study in Indonesian hospitals showed that sepsis is the leading cause of death in the intensive care unit (ICU). The incidence rate of sepsis in Indonesia is estimated to range between 10-20% of patients admitted to the ICU. Sepsis is a leading cause of death in hospitals, especially if not detected or treated quickly. Approximately 30-50% of patients with severe sepsis or septic shock will die if they do not receive appropriate treatment. Based on the data obtained from the pre-test and post-test, it can be seen that there is a significant improvement in the understanding and skills of health workers, which reflects the success of the training conducted. In the pre-test, the average comprehension score of the participants was 55%, while after the training it increased to 80%. With the application of knowledge about biomarkers and clinical parameters, early detection of sepsis is significantly improved.
MORTALITY PREDICTION MODEL IN SEPSIS EMERGENCIES: COMBINATION OF BIOMARKERS AND CLINICAL PARAMETERS Rahmat, Rosyadi Aziz
JURNAL KEPERAWATAN DAN FISIOTERAPI (JKF) Vol. 6 No. 1 (2023): Jurnal Keperawatan dan Fisioterapi (JKF)
Publisher : Fakultas Keperawatan dan Fisioterapi Institut Kesehatan Medistra Lubuk Pakam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35451/jkf.v6i1.2525

Abstract

Sepsis is a medical emergency characterized by a systemic inflammatory response due to infection and can cause organ dysfunction leading to death. Identification of patients with high risk of mortality is a challenge in clinical practice. Predictive models based on biomarkers and clinical parameters can help in early detection and patient management. This study aims to develop a mortality prediction model in sepsis patients by analyzing a combination of inflammatory biomarkers such as procalcitonin (PCT), C-reactive protein (CRP), and interleukin-6 (IL-6) and clinical parameters such as Sequential Organ Failure Assessment (SOFA) score, serum lactate levels, and blood pressure. Data were obtained from sepsis patients at a referral hospital and analyzed using multivariate logistic regression methods to evaluate the relationship between independent variables and mortality. The results showed that the combination of biomarkers and clinical parameters provided better predictive value than single-based models. The developed prediction model had an accuracy of 87% with an area under the curve (AUC) of 0.91, indicating a high level of reliability in detecting patients at risk of death. Implementation of this model in clinical practice is expected to assist physicians in decision making and improve the prognosis of sepsis patients. Further research is needed for external validation and application of this model in various patient populations.