Effectiveness of Plasma and Urine Neutrophil Gelatinase-Associated Lipocalin for Predicting Acute Kidney Injury in High-Risk Patients

Background@#Neutrophil gelatinase-associated lipocalin (NGAL) is a useful biomarker for acute kidney injury (AKI) prediction. However, studies on whether using both plasma NGAL (PNGAL) and urine NGAL (UNGAL) can improve AKI prediction are limited. We investigated the best approach to predict AKI in high-risk patients when using PNGAL and UNGAL together. @*Methods@#We enrolled 151 AKI suspected patients with one or more AKI risk factors. We assessed the diagnostic performance of PNGAL and UNGAL for predicting AKI according to chronic kidney disease (CKD) status by determining the areas under the receiver operating curve (AuROC). Independent predictors of AKI were assessed using univariate and multivariate logistic regression analyses. @*Results@#In the multivariate logistic regression analysis for all patients (N = 151), Model 2 and 3, including PNGAL (P = 0.012) with initial serum creatinine (S-Cr), showed a better AKI prediction power (R2 = 0.435, both) than Model 0, including S-Cr only (R2 = 0.390). In the non-CKD group (N = 135), the AuROC of PNGAL for AKI prediction was larger than that of UNGAL (0.79 vs 0.66, P = 0.010), whereas in the CKD group (N = 16), the opposite was true (0.94 vs 0.76, P = 0.049). @*Conclusions@#PNGAL may serve as a useful biomarker for AKI prediction in high-risk patients. However, UNGAL predicted AKI better than PNGAL in CKD patients. Our findings provide guidance for selecting appropriate specimens for NGAL testing according to the presence of CKD in AKI high-risk patients.

First Case in Korea of Group B Streptococcus With Reduced Penicillin Susceptibility Harboring Amino Acid Substitutions in Penicillin-Binding Protein 2X

No abstract available.

Prognostic Role of High-sensitivity Cardiac Troponin I and Soluble Suppression of Tumorigenicity-2 in Surgical Intensive Care Unit Patients Undergoing Non-cardiac Surgery

BACKGROUND: The prognostic utility of cardiac biomarkers, high-sensitivity cardiac troponin I (hs-cTnI) and soluble suppression of tumorigenicity-2 (sST2), in non-cardiac surgery is not well-defined. We evaluated hs-cTnI and sST2 as predictors of 30-day major adverse cardiac events (MACE) in patients admitted to the surgical intensive care unit (SICU) following major non-cardiac surgery. METHODS: hs-cTnI and sST2 concentrations were measured in 175 SICU patients immediately following surgery and for three days postoperatively. The results were analyzed in relation to 30-day MACE and were compared with the revised Goldman cardiac risk index (RCRI) score. RESULTS: Overall, 30-day MACE was observed in 16 (9.1%) patients. hs-cTnI and sST2 concentrations differed significantly between the two groups with and without 30-day MACE (P < 0.05). The maximum concentration of sST2 was an independent predictor of 30-day MACE (odds ratio=1.016, P=0.008). The optimal cut-off values of hs-cTnI and sST2 for predicting 30-day MACE were 53.0 ng/L and 182.5 ng/mL, respectively. A combination of hs-cTnI and sST2 predicted 30-day MACE better than the RCRI score. Moreover, 30-day MACE was observed more frequently with increasing numbers of above-optimal cut-off hs-cTnI and sST2 values (P < 0.0001). Reclassification analyses indicated that the addition of biomarkers to RCRI scores improved the prediction of 30-day MACE. CONCLUSIONS: This study demonstrates the utility of hs-cTnI and sST2 in predicting 30-day MACE following non-cardiac surgery. Cardiac biomarkers would provide enhanced risk stratification in addition to clinical RCRI scores for patients undergoing major non-cardiac surgery.

Performance Evaluation of Cartridge-Type Blood Gas Analyzer: i-Smart 300

BACKGROUND: Blood gas analysis plays a crucial role in critical care settings, and immediate and precise analysis improves clinical outcomes through prompt treatment. We evaluated the performance of a cartridge-type blood gas analyzer, i-Smart 300 (i-SENS, Korea), according to the Clinical and Laboratory Standard Institute (CLSI) guidelines and compared it to a conventional blood gas analyzer. METHODS: The precision was evaluated according to CLSI EP5-A3. The i-Smart 300 was compared to the Stat Profile Critical Care Xpress (STP CCX) (Nova CCX; Nova Biomedical, USA) according to CLSI EP9-A3 using the following eight parameters: pH, partial carbon dioxide pressure, partial oxygen pressure, sodium, potassium, chloride, ionized calcium, and hematocrit. Linearity was determined using five levels of control materials according to CLSI EP6-A. RESULTS: Within-run precision and total precision, demonstrated as coefficients of variation, ranged from 0.02 to 2.50% and from 0.05 to 3.46%, respectively. Correlation analysis yielded a correlation coefficient from 0.966 to 0.996 between the i-Smart 300 and the conventional analyzer (Nova CCX). The i-Smart 300 showed excellent linearity at eight parameters with acceptable percent recovery. CONCLUSIONS: The i-Smart 300, a portable cartridge-type blood gas analyzer, showed high precision and good correlation with a traditional bench-top blood gas analyzer. It could be useful in critical care settings.