Evaluation of predictive effect of PAF AH on the prognosis of intensive care unit patients Yoğun bakım hastalarında PAF AH ın prognoz üzerindeki prediktif etkisinin değerlendirilmesi

OpenAlex İngilizce

Abstract Objective: Determination of the factors associated with the intensive care unit (ICU) prognosis and mortality has important role in the clinical follow-up of the patients. Definition of novel biomarkers, beside older biomarkers available for evaluation of the outcome of these patients has been proposed. Platelet-activating factor acetylhydrolase (PAF-AH) is an enzyme that inactivates the platelet-activating factor. A reduction in the level of the PAF-AH has been demonstrated during systemic inflammation and multiple organ failure. This research aims to determine whether measurement of PAF-AH enzyme activity in ICUs can be used as a prognostic indicator like conventional biomarkers. Methods: Eighty five adult patients have been included. Following data have been recorded: preliminary C-reactive protein (CRP), lactate, albumin and PAF-AH values, APACHE II scores and discharge forms from ICU. Patients were divided in two groups with respect to APACHE II values: Group 1 (1-19) and Group 2 (≥20). Results: Observed mortality was 51.2%. In the APACHE II Group 2 patients, the values of CRP (p=0.001) and lactate (p=0.040) were significanty high, and the values of PAF-AH (p=0.008) and albumin (p=0.001) were significantly low. A statistically significant difference was found between PAF-AH values of exitus and alive patients (p=0.001). According to ROC analysis, the sensitivity and specificity of predicting mortality was 70.5% and 70.7% for CRP, 63.6% and 70.7% for lactate, 90.2% and 61.4% for albumin and 63.6% and 70% PAF-AH, respectively. Conclusion: Our study demonstrated that, in predicting the ICU mortality risk, sensitivity of the PAF-AH is similar to the sensitivity of the lactate, and specificity of the PAF-AH is better than that of the albumin. According to our results, PAF-AH can be included in the novel biomarkers.