Associations of continuous anionic gap detection with the mortality in critically ill patients receiving renal replacement therapy.

PURPOSE: To investigate the associations of anion gap (AG) levels before and 1-day after hemodialysis as well as anion gap changes with the mortality in critically ill patients receiving renal replacement therapy (RRT). METHODS: Totally, 637 patients from MIMIC-III were included in this cohort study. The associations between AG (T0), AG (T1), or ∆AG [AG (T0) - AG (T1)], and the risk of 30-day or 1-year mortality were examined by Cox restricted cubic spline regression models. Univariate and multivariate Cox proportional-hazards model was applied to assess the associations between AG (T0), AG (T1), ∆AG with 30-day and 1-year mortality, respectively. RESULTS: The median follow-up time was 18.60 (8.53, 38.16) days and 263 (41.3%) patients were survived. There was a linear relationship between AG (T0), AG (T1) or ∆AG and the risk of 30-day or 1-year mortality, respectively. The risk of 30-day mortality was higher in AG (T0) > 21 group (HR = 1.723, 95% CI 1.263-2.350), and AG (T1) > 22.3 group (HR = 2.011, 95% CI 1.417-2.853), while lower in AG > 0 group (HR = 0.664, 95% CI 0.486-0.907). The risk of 1-year mortality was increased in AG (T0) > 21 group (HR = 1.666, 95% CI 1.310-2.119), and AG (T1) > 22.3 group (HR = 1.546, 95% CI 1.159-2.064), while decreased in AG > 0 group (HR = 0.765, 95% CI 0.596-0.981). Patients with AG (T0) ≤ 21 had higher 30-day and 1-year survival probability than those with AG (T0) > 21. CONCLUSION: AG before and after dialysis as well as the changes of AG were important factors associated with the risk of 30-day and 1-year mortality in critically ill patients receiving RRT.

Impact of blood glucose levels on the accuracy of urinary N-acety-ß-D-glucosaminidase for acute kidney injury detection in critically ill adults: a multicenter, prospective, observational study.

BACKGROUND: The performance of urinary N-acetyl-ß-D-glucosaminidase (uNAG) for the detection of acute kidney injury (AKI) was controversial. uNAG is positively correlated with blood glucose levels. Hyperglycemia is common in the critically ill adults. The influence of blood glucose levels on the accuracy of uNAG in AKI detection has not yet been reported. The present study evaluated the effect of blood glucose levels on the diagnostic accuracy of uNAG to detect AKI. METHODS: A total of 1585 critically ill adults in intensive care units at three university hospitals were recruited in this prospective observational study. uNAG, serum glucose, and glycosylated hemoglobin (HbA1c) were measured at ICU admission. Patients were categorized based on the history of diabetes and blood glucose levels. The performance of uNAG to detect AKI in different groups was assessed by the area under the receiver operator characteristic curve. RESULTS: Four hundred and twelve patients developed AKI, of which 109 patients were severe AKI. uNAG was significantly correlated with the levels of serum glucose (P < 0.001) and HbA1c (P < 0.001). After stratification based on the serum glucose levels, no significant difference was observed in the AUC of uNAG in detecting AKI between any two groups (P > 0.05). Stratification for stress hyperglycemic demonstrated similar results.However, among non-diabetic patients, the optimal cut-off value of uNAG for detecting AKI was higher in stress hyperglycemic patients as compared to those without stress hyperglycemia. CONCLUSIONS: The blood glucose levels did not significantly affect the performance of uNAG for AKI detection in critically ill adults. However, the optimal cut-off value of uNAG to detect AKIwas affected by stress hyperglycemia in non-diabetic patients.

The influence of glycemic status on the performance of cystatin C for acute kidney injury detection in the critically ill.

OBJECTIVE: Serum cystatin C (sCysC) used clinically for detecting early acute kidney injury (AKI) was reported to be independently associated with hemoglobin (HbA1c) levels, diabetes, and prediabetes. We aimed to assess the influence of HbA1c levels, diabetes, or prediabetes on the performance of sCysC for AKI detection in critically ill adults. METHODS: A prospective observational study was conducted in a mixed medical-surgical intensive care unit (ICU). Patients were divided into four quartiles based on levels of HbA1c or serum glucose at ICU admission, respectively. Additionally, patients were stratified into four subgroups according to HbA1c levels and history of diabetes, namely recognized diabetes (previous diagnosis of diabetes), unrecognized diabetes, prediabetes, and normal glycemic status. Comparisons were made using the area under the receiver operator characteristic curve (AUC) for AKI detection, and reassessed after patient stratification by above-mentioned glycemic status. RESULTS: Multivariable linear regression revealed that HbA1c levels and history of diabetes were positively related with sCysC (all p < .05). Although stratification for above-mentioned glycemic status displayed no significant difference between AUC of sCysC (all p > .05), sCysC yielded the highest AUCs for detecting AKI in diabetic patients. Moreover, higher optimal cutoff values of sCysC to detect AKI were observed in patients with versus without diabetes. CONCLUSION: Glycemic status has no significant impact on the accuracy of sCysC for AKI detection in critically ill adults and a higher optimal cutoff value of sCysC for AKI detection should be considered in diabetic patients.

The Incidence, Risk Factors and Outcomes of Postoperative Acute Kidney Injury in Neurosurgical Critically Ill Patients.

We investigated the incidence, perioperative risk factors, and outcomes of postoperative acute kidney injury (AKI) in neurosurgical critically ill patients. A prospective multicenter cohort study was conducted, enrolling adult patients who underwent neurosurgical procedure and admitted to the neurosurgical intensive care units (ICU). Postoperative AKI was diagnosed within 7 days after surgery based on the Kidney Disease Improving Global Outcomes criteria. Of 624 enrolled patients, postoperative AKI occurred in 84 patients. AKI was associated with increased rates of ICU and in-hospital mortality, postoperative renal replacement therapy, postoperative tracheotomy, and postoperative tracheal reintubation. Patients who developed AKI had higher total ICU costs, prolonged length of hospital and ICU stay, and longer duration of postoperative mechanical ventilation. Multivariate analysis identified postoperative reoperation (adjusted odds ratio [OR] 5.70 [95% CI, 1.61-20.14]), postoperative concentration of serum cystatin C (adjusted OR 4.53 [95% CI, 1.98-10.39]), use of mannitol during operation (adjusted OR 1.97 [95% CI, 1.13-3.43]), postoperative APACHE II score (adjusted OR 1.11 [95% CI, 1.06-1.16]), and intraoperative estimated blood loss (adjusted OR 1.04 [95% CI, 1.00-1.08]) as independent risk factors for postoperative AKI. Postoperative AKI in neurosurgical critically ill cohort is prevalent and associated with adverse in-hospital outcomes.

Evaluation of clinically available renal biomarkers in critically ill adults: a prospective multicenter observational study.

BACKGROUND: Although serum cystatin C (sCysC), urinary N-acetyl-ß-D-glucosaminidase (uNAG), and urinary albumin/creatinine ratio (uACR) are clinically available, their optimal combination for acute kidney injury (AKI) detection and prognosis prediction remains unclear. We aimed to assess the discriminative abilities of these biomarkers and their possible combinations for AKI detection and intensive care unit (ICU) mortality prediction in critically ill adults. METHODS: A multicenter, prospective observational study was conducted in mixed medical-surgical ICUs at three tertiary care hospitals. One thousand eighty-four adult critically ill patients admitted to the ICUs were studied. We assessed the use of individual biomarkers (sCysC, uNAG, and uACR) measured at ICU admission and their combinations with regard to AKI detection and prognosis prediction. RESULTS: AUC-ROCs for sCysC, uNAG, and uACR were calculated for total AKI (0.738, 0.650, and 0.683, respectively), severe AKI (0.839, 0.706, and 0.771, respectively), and ICU mortality (0.727, 0.793, and 0.777, respectively). The panel of sCysC plus uNAG detected total and severe AKI with significantly higher accuracy than either individual biomarkers or the other two panels (uNAG plus uACR or sCysC plus uACR). For detecting total AKI, severe AKI, and ICU mortality at ICU admission, this panel yielded AUC-ROCs of 0.756, 0.863, and 0.811, respectively; positive predictive values of 0.71, 0.31, and 0.17, respectively; and negative predictive values of 0.81, 0.97, and 0.98, respectively. Moreover, this panel significantly contributed to the accuracy of the clinical models for AKI detection and ICU mortality prediction, as measured by the AUC-ROC, continuous net reclassification index, and incremental discrimination improvement index. The comparable performance of this panel was further confirmed with bootstrap internal validation. CONCLUSIONS: The combination of a functional marker (sCysC) and a tubular damage marker (uNAG) revealed significantly superior discriminative performance for AKI detection and yielded additional prognostic information on ICU mortality.