Background: Postoperative acute kidney injury (AKI) is frequent and associated with adverse outcomes. Unfortunately, the early diagnosis of AKI remains a challenge. Combining functional and tubular damage biomarkers may provide better precision for AKI detection. However, the diagnostic accuracy of this combination for AKI after neurosurgery is unclear. Serum cystatin C (sCysC) and urinary albumin/creatinine ratio (uACR) are considered functional biomarkers, while urinary N-acetyl-β-D-glucosaminidase (uNAG) represents tubular damage. We aimed to assess the performances of these clinical available biomarkers and their combinations for AKI prediction after resection of intracranial space-occupying lesions. Methods: A prospective study was conducted, enrolling adults undergoing resection of intracranial space-occupying lesions and admitted to the neurosurgical intensive care unit. The discriminative abilities of postoperative sCysC, uNAG, uACR, and their combinations in predicting AKI were compared using the area under the receiver operating characteristic curve (AUC-ROC), continuous net reclassification index (cNRI), and incremental discrimination improvement (IDI). Results: Of 605 enrolled patients, AKI occurred in 67 patients. The cutoff values of sCysC, uNAG, and uACR to predict postoperative AKI were 0.72 mg/L, 19.98 U/g creatinine, and 44.21 mg/g creatinine, respectively. For predicting AKI, the composite of sCysC and uNAG (AUC-ROC = 0.785) outperformed either individual biomarkers or the other two panels (uNAG plus uACR or sCysC plus uACR). Adding this panel to the predictive model improved the AUC-ROC to 0.808. Moreover, this combination significantly improved risk reclassification over the clinical model alone, with cNRI (0.633) and IDI (0.076). Superior performance of this panel was further confirmed with bootstrap internal validation. Conclusions: Combination of functional and tubular damage biomarkers improves the predictive accuracy for AKI after resection of intracranial space-occupying lesions.

Background It is not clear whether there are valuable inflammatory markers for prognosis judgment in the intensive care unit (ICU). We therefore conducted a multicenter, prospective, observational study to evaluate the prognostic role of inflammatory markers. Methods The clinical and laboratory data of patients at admission, including C-reactive protein (CRP), were collected in four general ICUs from September 1, 2018, to August 1, 2019. Multivariate logistic regression was used to identify factors independently associated with nonsurvival. The area under the receiver operating characteristic curve (AUC-ROC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were used to evaluate the effect size of different factors in predicting mortality during ICU stay. 3 -knots were used to assess whether alternative cut points for these biomarkers were more appropriate. Results A total of 813 patients were recruited, among whom 121 patients (14.88%) died during the ICU stay. The AUC-ROC values of PCT and CRP for discriminating ICU mortality were 0.696 (95% confidence interval [CI], 0.650–0.743) and 0.684 (95% CI, 0.633–0.735), respectively. In the multivariable analysis, only APACHE II score (odds ratio, 1.166; 95% CI, 1.129–1.203; P = 0.000) and CRP concentration > 62.8 mg/L (odds ratio, 2.145; 95% CI, 1.343–3.427; P = 0.001), were significantly associated with an increased risk of ICU mortality. Moreover, the combination of APACHE II score and CRP > 62.8 mg/L significantly improved risk reclassification over the APACHE II score alone, with NRI (0.556) and IDI (0.013). Restricted cubic spline analysis confirmed that CRP concentration > 62.8 mg/L was the optimal cut-off value for differentiating between surviving and nonsurviving patients. Conclusion CRP markedly improved risk reclassification for prognosis prediction.

Background Combining tubular damage and functional biomarkers may improve prediction precision of acute kidney injury (AKI). Serum cystatin C (sCysC) represents functional damage of kidney, while urinary N-acetyl-β-D-glucosaminidase (uNAG) is considered as a tubular damage biomarker. So far, there is no nomogram containing this combination to predict AKI in septic cohort. We aimed to compare the performance of AKI prediction models with or without incorporating these two biomarkers and develop an effective nomogram for septic patients in intensive care unit (ICU). Methods This was a prospective study conducted in the mixed medical-surgical ICU of a tertiary care hospital. Adults with sepsis were enrolled. The patients were divided into development and validation cohorts in chronological order of ICU admission. A logistic regression model for AKI prediction was first constructed in the development cohort. The contribution of the biomarkers (sCysC, uNAG) to this model for AKI prediction was assessed with the area under the receiver operator characteristic curve (AUC), continuous net reclassification index (cNRI), and incremental discrimination improvement (IDI). Then nomogram was established based on the model with the best performance. This nomogram was validated in the validation cohort in terms of discrimination and calibration. The decision curve analysis (DCA) was performed to evaluate the nomogram’s clinical utility. Results Of 358 enrolled patients, 232 were in the development cohort (69 AKI), while 126 in the validation cohort (52 AKI). The first clinical model included the APACHE II score, serum creatinine, and vasopressor used at ICU admission. Adding sCysC and uNAG to this model improved the AUC to 0.831. Furthermore, incorporating them significantly improved risk reclassification over the predictive model alone, with cNRI (0.575) and IDI (0.085). A nomogram was then established based on the new model including sCysC and uNAG. Application of this nomogram in the validation cohort yielded fair discrimination with an AUC of 0.784 and good calibration. The DCA revealed good clinical utility of this nomogram. Conclusions A nomogram that incorporates functional marker (sCysC) and tubular damage marker (uNAG), together with routine clinical factors may be a useful prognostic tool for individualized prediction of AKI in septic patients.