Abstract
The mortality of patients with severe sepsis and septic shock is still high, and the prognosis of elderly patients tends to be particularly poor. Therefore, this study sought to conduct a comparative analysis of the abbreviated mortality in emergency department sepsis (abbMEDS) score, sequential organ failure assessment (SOFA) score, infection probability score (IPS), initial procalcitonin (PCT), and cytokine levels to investigate the effectiveness of each index in predicting the prognosis of elderly patients with sepsis in the emergency department (ED). This was a single-center prospective study, and classified 55 patients (≥65years of age) with systemic inflammatory response syndrome (SIRS) from January 2013 to December 2013 in the ED. A total of 36 elderly patients were diagnosed with sepsis. The prediction of prognosis using the prognostic scores (abbMEDS, SOFA, IPS) was analyzed. An early blood examination (WBC count, C-reactive protein, PCT, and cytokines) was conducted within the first 2h of the patient's arrival at the ED. The median (IQR) age of subjects was 76.5 (70.5-81.5). After 28days, 27 subjects (75%) had survived, and 9 (25%) had died. Fifteen (41.7%) were sent to intensive care units (ICUs). The SOFA score and abbMEDS showed higher median (IQR) values of 9.5 (7.0-11.0) and 13.5 (12.0-15.0), respectively, in the ICU group than in the general ward group (p<0.001). Analysis of the levels of PCT, IL-10, IL-6, and IL-5 had a significantly better ability to predict ICU admission (p=0.001, p=0.023, p=0.030, p=0.001). The prediction of mortality in the first 28days via SOFA and the abbMEDS resulted in scores of 11.0 (8.0-11.0) and 14.0 (12.5-15.5) (p=0.004, p=0.003), respectively. However, levels of IPS, PCT, and cytokines did not show significant differences. In predicting ICU admission and the death of elderly sepsis patients in ED, SOFA and abbMEDS scores were effective. Of the various biomarkers, PCT, IL-10, IL-6, and IL-5 were effective in predicting ICU admission, but were not effective in predicting the death of elderly sepsis patients.
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