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.

Impact of thyroid function on cystatin C in detecting acute kidney injury: a prospective, observational study.

BACKGROUND: Cystatin C (Cys C) used clinically for detecting early acute kidney injury (AKI) was reported to be associated with thyroid function. Therefore, whether the performance of Cys C is affected by thyroid hormones has raised concern in critically ill patients. This study aimed to investigate the impact of thyroid hormones on the diagnostic and predictive accuracy of Cys C for AKI, and hence optimize the clinical application of Cys C. METHODS: A prospective observational study was conducted in the general intensive care units (ICUs). Serum creatinine (SCr), Cys C, and thyroid function were documented for all patients at ICU admission. Patients were separated into five quintiles based on free triiodothyronine (FT3) and total triiodothyronine (TT3), and two categories according to the presence of low T3 syndrome or not. The impact of thyroid function on the performance of Cys C in diagnosing and predicting AKI was assessed by area under the receiver operating characteristic curve (AUC). RESULTS: The AKI incidence was 30.0% (402/1339); 225 patients had AKI upon entry, and 177 patients developed AKI during the subsequent 7 days. The AUCs for Cys C in detecting total AKI, established AKI, and later-onset AKI was 0.753, 0.797, and 0.669, respectively. The multiple linear regression analysis demonstrated that TT3 and FT3 were independently associated with Cys C. Overall, although Cys C did not yield any significant difference in AUCs for detecting AKI among patients with different thyroid hormones, the optimal cut-off value of Cys C to detect AKI was markedly different between patients with and without low T3 syndrome. CONCLUSIONS: The thyroid function had no significant impact on the diagnostic and predictive accuracy of Cys C in detecting AKI in ICU patients. However, the optimal cut-off value of Cys C to detect AKI could be affected by thyroid function.

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.

Factors Associated With Prolonged Viral Shedding in Patients With Avian Influenza A(H7N9) Virus Infection.

Background: Data are limited on the impact of neuraminidase inhibitor (NAI) treatment on avian influenza A(H7N9) virus RNA shedding. Methods: In this multicenter, retrospective study, data were collected from adults hospitalized with A(H7N9) infection during 2013-2017 in China. We compared clinical features and A(H7N9) shedding among patients with different NAI doses and combination therapies and evaluated factors associated with A(H7N9) shedding, using Cox proportional hazards regression. Results: Among 478 patients, the median age was 56 years, 71% were male, and 37% died. The median time from illness onset to NAI treatment initiation was 8 days (interquartile range [IQR], 6-10 days), and the median duration of A(H7N9) RNA detection from onset was 15.5 days (IQR, 12-20 days). A(H7N9) RNA shedding was shorter in survivors than in patients who died (P < .001). Corticosteroid administration (hazard ratio [HR], 0.62 [95% confidence interval {CI}, .50-.77]) and delayed NAI treatment (HR, 0.90 [95% CI, .91-.96]) were independent risk factors for prolonged A(H7N9) shedding. There was no significant difference in A(H7N9) shedding duration between NAI combination treatment and monotherapy (P = .65) or between standard-dose and double-dose oseltamivir treatment (P = .70). Conclusions: Corticosteroid therapy and delayed NAI treatment were associated with prolonged A(H7N9) RNA shedding. NAI combination therapy and double-dose oseltamivir treatment were not associated with a reduced A(H7N9) shedding duration as compared to standard-dose oseltamivir.

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.

A Two-Stage Bedside Intubation Method to Improve Success Rate of Post-pyloric Placement of Spiral Nasoenteric Tubes in Critically Ill Patients: A Multi-Center, Prospective Study.

Backgrounds: Prokinetic agents could improve the success rate of post-pyloric placement of self-propelled spiral nasoenteric tubes (NETs), and bedside blind technique might apply as a rescue therapy subsequent to spontaneous transpyloric migration failure. The objective of this study was to investigated the validity and safety of these two bedside intubation methods as a sequential procedure for post-pyloric placement of spiral NETs in critically ill patients. Methods: The multicenter, prospective study was conducted in intensive care units of four tertiary hospitals (June 2020 to January 2021). Eligible patients received self-propelled spiral NET placements, promoted by prokinetic agents (Stage 1). An abdominal X-ray performed 24 h post-intubation confirmed the position of the tube tip. Patients with a failed transpyloric migration entered Stage 2, where beside blind intubation was conducted (reconfirmed by X-ray). The primary end point was the overall success rate of post-pyloric placement. Results: The overall success rate of post-pyloric placement of the spiral NET was 91.1% (73.4% in the third portion of the duodenum [D3] or beyond). The total adverse event rate was 21.0%, without any serious adverse events. In Stage 1, 55.6% of participants achieved transpyloric migration, of these, 44.4% migrated to D3 or beyond. The median time from decision to intubate to the initiation of enteral nutrition (EN) was 25 h. In Stage 2, 83.0% of patients had successful post-pyloric intubation (67.9% in D3 or beyond). The median time from decision to EN initiation after the two-stage process was 36 h. Conclusions: Prokinetic agents-assisted self-propelled intubation and remedial bedside blind technique as a sequential procedure for post-pyloric placement of spiral NETs were effective and safe, and this two-stage process did not affect the implementation of early EN in critically ill patients. Trial Registration: Chinese Clinical Trial Registry, ChiCTR1900026381. Registered on 6 October 2019.

[Construction and validation of a decision tree based on biomarkers for predicting severe acute kidney injury in critically ill patients].

OBJECTIVE: To construct and evaluate a decision tree based on biomarkers for predicting severe acute kidney injury (AKI) in critical patients. METHODS: A prospectively study was conducted. Critical patients who had been admitted to the department of critical care medicine of Xiaolan Hospital of Southern Medical University from January 2017 to June 2018 were enrolled. The clinical data of the patients were recorded, and the biomarkers, including serum cystatin C (sCys C) and urinary N-acetyl-ß-D-glucosaminidase (uNAG) were established immediately after admission to intensive care unit (ICU), and the end points were recorded. The test cohort was established with patient data from January to December 2017. The decision tree classification and regression tree (CART) algorithm was used, and the best cut-off values of biomarkers were used as the decision node to construct a biomarker decision tree model for predicting severe AKI. The accuracy of the decision tree model was evaluated by the overall accuracy and the receiver operating characteristic (ROC) curve. The validation cohort, established on patient data from January to June 2018, was used to further validate the accuracy and predictive ability of the decision tree. RESULTS: In test cohort, 263 patients were enrolled, of whom 57 developed severe AKI [defined as phase 2 and 3 of Kidney Disease: Improving Global Outcomes (KDIGO) criterion]. Compared with patients without severe AKI, severe AKI patients were older [years old: 64 (49, 74) vs. 52 (41, 66)], acute physiology and chronic health evaluation II (APACHE II) score were higher [23 (19, 27) vs. 15 (11, 20)], the incidence of hypertension, diabetes and other basic diseases and sepsis were higher (64.9% vs. 40.3%, 28.1% vs. 10.7%, 63.2% vs. 29.6%), the levels of sCys C and uNAG were higher [sCys C (mg/L): 1.38 (1.12, 2.02) vs. 0.79 (0.67, 0.98), uNAG (U/mmol Cr): 5.91 (2.43, 10.68) vs. 2.72 (1.60, 3.90)], hospital mortality and 90-day mortality were higher (21.1% vs. 4.4%, 52.6% vs. 13.1%), the length of ICU stay was longer [days: 6.0 (4.0, 9.5) vs. 3.0 (1.0, 6.0)], and renal replacement therapy requirement was higher (22.8% vs. 1.9%), with statistically significant differences (all P < 0.05). ROC curve analysis showed that the areas under ROC curve (AUC) of sCys C and uNAG in predicting severe AKI were 0.857 [95% confidence interval (95%CI) was 0.809-0.897)] and 0.735 (95%CI was 0.678-0.788), and the best cut-off values were 1.05 mg/L and 5.39 U/mmol Cr, respectively. The structure of the biomarker decision tree model constructed by biomarkers were intuitive. The overall accuracy in predicting severe AKI was 86.0%, and AUC was 0.905 (95%CI was 0.863-0.937), the sensitivity was 0.912, and the specificity was 0.796. In validation cohort of 130 patients, this decision tree yielded an excellent AUC of 0.909 (95%CI was 0.846-0.952), the sensitivity was 0.906, and the specificity was 0.816, with an overall accuracy of 81.0%. CONCLUSIONS: The decision tree model based on biomarkers for predicting severe AKI in critical patients is highly accurate, intuitive and executable, which is helpful for clinical judgment and decision.

Simo decoction versus domperidone suspension for post-pyloric spiral nasoenteric tube placement: A multicenter, randomized, non-inferiority trial.

BACKGROUND & AIMS: Leveraging prokinetics to facilitate trans-pyloric migration is a conventional strategy. However, due to restrictions on the use of domperidone suspension, oral prokinetics is relatively modest. The study aims to assess the effectiveness of simo decoction as an alternative to domperidone suspension in facilitating post-pyloric placement of spiral nasoenteric tubes. METHODS: A prospective, open-label, parallel, and non-inferiority randomized controlled trial was performed involving critically ill adults in 6 university hospitals in China between September 2017 and May 2019. Patients were randomly assigned to receive either simo decoction 20 ml q8h, or domperidone suspension 20 mg/20 ml q6h for 24 h. The primary outcome was procedure success defined as post-pyloric placement (spiral nasoenteric tubes reached the first portion of the duodenum or beyond confirmed by abdominal X-ray 24 h after tube insertion). RESULTS: Of 268 patients assessed for eligibility, 224 patients were enrolled and randomly assigned to the simo decoction group or the domperidone suspension group (n = 112 per group). The success rate of post-pyloric placement was 41.1% (46/112) in the simo decoction group, as compared with 47.3% (53/112) in the domperidone suspension group (a risk difference of -6.3%, 95% CI, -19.2% to 6.7%, adjusted risk difference -3.7%, 95% CI -16.3% to 9.0%), in the intention-to-treat analysis, crossing the prespecified margin of -10% for non-inferiority. There were no differences between groups in the success rates of post-D1 (reaching the second portion of the duodenum or beyond), post-D2 (reaching the third portion of the duodenum or beyond), post-D3 (reaching the fourth portion of the duodenum or beyond) and proximal jejunum placement, the incidences of any adverse events, length of ICU stay or mortality in ICU. CONCLUSIONS: Non-inferiority of simo decoction to domperidone suspension was not confirmed in facilitating post-pyloric placement of spiral nasoenteric tubes. Registration: The trial was registered with the Chinese Clinical Trial Registry at http://www.chictr.org.cn (registration number ChiCTR-INR-17011311).

Development and validation of a nomogram for predicting self-propelled postpyloric placement of spiral nasoenteric tube in the critically ill: Mixed retrospective and prospective cohort study.

BACKGROUND & AIMS: Equipment-aided or experience-dependent methods for postpyloric nasoenteric tube placement are not so readily accessible in the critically ill setting. Self-propelled postpyloric placement of a spiral nasoenteric tube can serve as an alternative approach. However, the success rate of this method is relatively low despite using prokinetics. This study aims to develop a user-friendly nomogram incorporating clinical markers to individually predict the probability of successful postpyloric nasoenteric tube placement and facilitate intensivists with improved decision-making before tube insertion. METHODS: Patients consecutively recruited in the stage between May 2012 through December 2016 constituted the development cohort for retrospective analysis to internally test the nomogram, and patients in the stage between January 2017 through March 2018 constituted the validation cohort for prospective analysis to external validate the nomogram. A multivariate logistic regression analysis was firstly performed in the development cohort by a backward stepwise method to identify the best-fit model, from which a nomogram was obtained. The nomogram was validated in the independent external validation cohort concerning discrimination, calibration. A decision curve analysis was also performed to evaluate the net benefit of insertion decision with the nomogram. RESULTS: A total of 364 and 119 patients, 52.7% and 55.5% with successful postpyloric placement, were included in the development and validation cohort, respectively. Predictors contained in the prediction nomogram included primary diagnosis, APACHE II score, AGI grade. The derived model showed good discrimination, with an area under the receiver operating characteristic curve (AUROC) of 0.809 (95%CI, 0.765-0.853) and good calibration. Application of the nomogram in the validation cohort also gave good discrimination with an AUROC of 0.776 (95%CI, 0.694-0.859) and good calibration. The decision curve analysis of the nomogram provided better net benefit than the alternate options (insert-all or insert-none). CONCLUSIONS: A prediction nomogram that incorporates primary diagnosis, together with APACHE II score and AGI grade can be conveniently used to facilitate the pre-insertion individualized prediction of postpyloric nasoenteric tube placement in critically ill patients.

Establishing Decision Trees for Predicting Successful Postpyloric Nasoenteric Tube Placement in Critically Ill Patients.

BACKGROUND: Despite the use of prokinetic agents, the overall success rate for postpyloric placement via a self-propelled spiral nasoenteric tube is quite low. METHODS: This retrospective study was conducted in the intensive care units of 11 university hospitals from 2006 to 2016 among adult patients who underwent self-propelled spiral nasoenteric tube insertion. Success was defined as postpyloric nasoenteric tube placement confirmed by abdominal x-ray scan 24 hours after tube insertion. Chi-square automatic interaction detection (CHAID), simple classification and regression trees (SimpleCart), and J48 methodologies were used to develop decision tree models, and multiple logistic regression (LR) methodology was used to develop an LR model for predicting successful postpyloric nasoenteric tube placement. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of these models. RESULTS: Successful postpyloric nasoenteric tube placement was confirmed in 427 of 939 patients enrolled. For predicting successful postpyloric nasoenteric tube placement, the performance of the 3 decision trees was similar in terms of the AUCs: 0.715 for the CHAID model, 0.682 for the SimpleCart model, and 0.671 for the J48 model. The AUC of the LR model was 0.729, which outperformed the J48 model. CONCLUSION: Both the CHAID and LR models achieved an acceptable discrimination for predicting successful postpyloric nasoenteric tube placement and were useful for intensivists in the setting of self-propelled spiral nasoenteric tube insertion.

Erythromycin versus metoclopramide for post-pyloric spiral nasoenteric tube placement: a randomized non-inferiority trial.

PURPOSE: To determine whether erythromycin is non-inferior to metoclopramide in facilitating post-pyloric placement of self-propelled spiral nasoenteric tubes (NETs) in critically ill patients. METHODS: A prospective, multicenter, open-label, parallel, and non-inferiority randomized controlled trial was conducted comparing erythromycin with metoclopramide in facilitating post-pyloric placement of spiral NETs in critically ill patients admitted to intensive care units (ICUs) of eight tertiary hospitals in China. The primary outcome was procedure success defined as post-pyloric placement (spiral NETs reached the first portion of the duodenum or beyond confirmed by abdominal radiography 24 h after tube insertion). RESULTS: A total of 5688 patients were admitted to the ICUs. Of these, in 355 patients there was a plan to insert a nasoenteric feeding tube, of whom 332 were randomized, with 167 patients assigned to the erythromycin group and 165 patients assigned to the metoclopramide group. The success rate of post-pyloric placement was 57.5% (96/167) in the erythromycin group, as compared with 50.3% (83/165) in the metoclopramide group (a difference of 7.2%, 95% CI - 3.5% to 17.9%), in the intention-to-treat analysis, not including the prespecified margin of - 10% for non-inferiority. The success rates of post-D1 (reaching the second portion of the duodenum or beyond), post-D2 (reaching the third portion of the duodenum or beyond), post-D3 (reaching the fourth portion of the duodenum or beyond), and proximal jejunum placement and the incidence of any adverse events were not significantly different between the groups. CONCLUSIONS: Erythromycin is non-inferior to metoclopramide in facilitating post-pyloric placement of spiral NETs in critically ill patients. The success rates of post-D1, post-D2, post-D3, and proximal jejunum placement were not significantly different.

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.