Soil Evaluators by Last Name (2012-08)

BACKGROUND:Diagnosing acute kidney injury quickly is imperative since it is known as an independent risk factor for mortality in burn patients. We evaluated the diagnostic power of creatinine, cystatin, serum and urine neutrophil gelatinase-associated lipocalin at different time periods and observed the changes from baseline for each biomarker. METHODS:This was a prospective observation study from January 2015 to February 2016. A total of 84 patients were enrolled consecutively. Serum creatinine, serum cystatin C, and serum and urine neutrophil gelatinase-associated lipocalin were measured at admission, 7th, 14th, 21st, and 28th days after admission. All samples were collected until acute kidney injury developed. RESULTS:Acute kidney injury developed in 35 patients. The mean age was 49.6 years with a male predominance. The median urine neutrophil gelatinase-associated lipocalin was the lowest (11.6 ng/dL) at admission, and the highest at 85.5 ng/dL on day 7. Mean creatinine level was the highest (0.88 mg/dL) at admission and the median creatinine level was the lowest (0.56 mg/dL) on the 14th day. The area under the curve of creatinine levels was the highest with 0.857 during the 1st week. The area under the curve of urine neutrophil gelatinase-associated lipocalin was the highest with 0.803 during the 5th week. CONCLUSIONS:Within 1 week of acute kidney injury, creatinine level was the optimal biomarker for diagnosis while urine neutrophil gelatinase-associated lipocalin showed better diagnostic performance following the 4- week period

Development of a risk prediction model (Hangang) and comparison with clinical severity scores in burn patients.

PURPOSE:The purpose of this study was to develop a new prediction model to reflect the risk of mortality and severity of disease and to evaluate the ability of the developed model to predict mortality among adult burn patients. METHODS:This study included 2009 patients aged more than 18 years who were admitted to the intensive care unit (ICU) within 24 hours after a burn. We divided the patients into two groups; those admitted from January 2007 to December 2013 were included in the derivation group and those admitted from January 2014 to September 2017 were included in the validation group. Shrinkage methods with 10-folds cross-validation were performed to identify variables and limit overfitting of the model. The discrimination was analyzed using the area under the curve (AUC) of the receiver operating characteristic curve. The Brier score, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were also calculated. The calibration was analyzed using the Hosmer-Lemeshow goodness-of-fit test (HL test). The clinical usefulness was evaluated using a decision-curve analysis. RESULTS:The Hangang model showed good calibration with the HL test (χ2 = 8.785, p = 0.361); the highest AUC and the lowest Brier score were 0.943 and 0.068, respectively. The NRI and IDI were 0.124 (p-value = 0.003) and 0.079 (p-value <0.001) when compared with FLAMES, respectively. CONCLUSIONS:This model reflects the current risk factors of mortality among adult burn patients. Furthermore, it was a highly discriminatory and well-calibrated model for the prediction of mortality in this cohort

Subgroup analysis of continuous renal replacement therapy in severely burned patients

<div><p>Continuous renal replacement therapy (CRRT) is administered to critically ill patients with renal injuries as renal replacement or renal support. We aimed to identify predictors of mortality among burn patients receiving CRRT, and to investigate clinical differences according to acute kidney injury (AKI) status. This retrospective observational study evaluated 216 Korean burn patients who received CRRT at a burn intensive care unit. Patients were categorized by AKI status. Data were collected regarding arterial pH, laboratory results, ratio of arterial oxygen partial pressure to fractional inspired oxygen (PF ratio), and urine production. Among surviving patients, CRRT duration and the sequential organ failure assessment score were 6.5 days and 4.7 in the non-AKI group and 23.4 days and 7.4 in the AKI group, respectively (p = 0.003 and p = 0.008). On logistic regression analyses, mortality was significantly associated with a pH of <7.2 (p = 0.004), potassium levels of >5.0 mEg/L (p = 0.045), creatinine levels of >2.0 mg/dL (p = 0.011), lactate levels of >2 mmol/L (p<0.001), a PF ratio of <200 (p = 0.042), and a platelet count of <100,000/μL (p<0.001). In the AKI group, poor outcomes were associated with a pH of <7.2, potassium levels of <5.0 mEg/L, lactate levels of >2 mmol/L, and a platelet count of <100,000/μL, while good outcomes were associated with creatinine levels of >2 mg/dL. In the non-AKI group, poor outcomes were associated with lactate levels of >1.5 mmol/L, a PF ratio of <200, and a platelet count of <100,000/μL, while good outcomes were associated with creatinine levels of >1.2 mg/dL. Duration of the CRRT application and the requirement for either renal replacement or renal support at the initiation of CRRT application are important considerations depending on its application.</p></div

Does inhalation injury predict mortality in burns patients or require redefinition?

<div><p>Inhalation injury is known to be an important factor in predicting mortality in burns patients. However, the diagnosis is complicated by the heterogeneous presentation and inability to determine the severity of inhalation injury. The purpose of this study was to identify clinical features of inhalation injury that affect mortality and the values that could predict the outcome more precisely in burns patients with inhalation injury. This retrospective observational study included 676 burns patients who were over 18 years of age and hospitalized in the Burns Intensive Care Unit between January 2012 and December 2015. We analyzed variables that are already known to be prognostic factors (age, percentage of total body surface area (%TBSA) burned, and inhalation injury) and factors associated with inhalation injury (carboxyhemoglobin and PaO₂/FiO₂ [PF] ratio) by univariate and multivariate logistic regression. Age group (odds ratio [OR] 1.069, <i>p</i><0.001), %TBSA burned (OR 1.100, <i>p</i><0.001), and mechanical ventilation (OR 3.774, <i>p</i><0.001) were identified to be significant predictive factors. The findings for presence of inhalation injury, PF ratio, and carboxyhemoglobin were not statistically significant in multivariate logistic regression. Being in the upper inhalation group, the lower inhalation group, and having a PF ratio <100 were identified to be significant predictors only in univariate logistic regression analysis (OR 4.438, <i>p</i><0.001; OR 2.379, <i>p</i><0.001; and OR 2.765, <i>p</i><0.001, respectively). History and physical findings are not appropriate for diagnosis of inhalation injury and do not predict mortality. Mechanical ventilation should be recognized as a risk factor for mortality in burns patients with inhalation injury.</p></div

Patients’ characteristics and prognostic factors of the survivors and non-survivors, and according to AKIN stage.

<p>Patients’ characteristics and prognostic factors of the survivors and non-survivors, and according to AKIN stage.</p

Patient demographics and comparisons between survivors and non-survivors.

<p>Patient demographics and comparisons between survivors and non-survivors.</p

Demographics of the patients classified by the AKI development.

<p>Demographics of the patients classified by the AKI development.</p

AUC of ROC curve for the prediction of mortality at the time of CRRT application.

<p>AUC of ROC curve for the prediction of mortality at the time of CRRT application.</p

Univariate logistic regression for predicting mortality according to presence of AKI.

<p>Univariate logistic regression for predicting mortality according to presence of AKI.</p

Changes in biomarker levels over time between the AKI and non-AKI group.

<p>Changes in biomarker levels over time between the AKI and non-AKI group.</p