Plasma cystatin C versus renal resistive index as early predictors of acute kidney injury in critically ill neonates

Kidney Doppler ultrasonography in critical care nephrology

Color pulsed-wave Doppler ultrasound (CPWD-US) emerges as a pivotal tool in intensive care units (ICUs) for diagnosing acute kidney injury (AKI) swiftly and non-invasively. Its bedside accessibility allows for rapid assessments, making it a primary imaging modality for AKI characterization. Furthermore, CPWD-US serves as a guiding instrument for key diagnostic-interventional procedures such as renal needle biopsy and percutaneous nephrostomy, while also facilitating therapy response monitoring and AKI progression tracking. This review shifts focus towards the integration of renal ultrasound into ICU workflows, offering contemporary insights into its utilization through a diagnostic standard-oriented approach. By presenting a flow chart, this review aims to provide practical guidance on the appropriate use of point-of-care ultrasound in critical care scenarios, enhancing diagnostic precision, patient management and safety, albeit amidst a backdrop of limited evidence regarding long-term outcomes.

Application of multimodal ultrasonography to predicting the acute kidney injury risk of patients with sepsis: artificial intelligence approach

The occurrence of acute kidney injury in sepsis represents a common complication in hospitalized and critically injured patients, which is usually associated with an inauspicious prognosis. Thus, additional consequences, for instance, the risk of developing chronic kidney disease, can be coupled with significantly higher mortality. To intervene in advance in high-risk patients, improve poor prognosis, and further enhance the success rate of resuscitation, a diagnostic grading standard of acute kidney injury is employed to quantify. In the article, an artificial intelligence-based multimodal ultrasound imaging technique is conceived by incorporating conventional ultrasound, ultrasonography, and shear wave elastography examination approaches. The acquired focal lesion images in the kidney lumen are mapped into a knowledge map and then injected into feature mining of a multicenter clinical dataset to accomplish risk prediction for the occurrence of acute kidney injury. The clinical decision curve demonstrated that applying the constructed model can help patients whose threshold values range between 0.017 and 0.89 probabilities. Additionally, the metrics of model sensitivity, specificity, accuracy, and area under the curve (AUC) are computed as 67.9%, 82.48%, 76.86%, and 0.692%, respectively, which confirms that multimodal ultrasonography not only improves the diagnostic sensitivity of the constructed model but also dramatically raises the risk prediction capability, thus illustrating that the predictive model possesses promising validity and accuracy metrics.

Elevated Renal-Resistive Index as an Indicator of Acute Kidney Injury Associated With Neonatal Extracorporeal Membrane Oxygenation

OBJECTIVE

The authors aimed to assess the relationship between elevated renal-resistive index (RRI) and acute kidney injury (AKI) related to extracorporeal membrane oxygenation (ECMO) in neonatal patients.

DESIGN

This was a retrospective study.

SETTING

The study was conducted at a teaching hospital.

PARTICIPANTS

Sixteen neonates treated with ECMO at the authors' hospital between June 2021 and December 2022 were included in this study.

INTERVENTIONS

Demographic and clinical data of patients were collected from the computer database. The RRI of patients before and during ECMO treatment was measured by bedside ultrasound. A receiver operating characteristic (ROC) curve was constructed to evaluate the diagnostic value of elevation of RRI as evidence of neonatal ECMO-related AKI. Logistic regression analysis was utilized to calculate the odds ratio (OR) with a 95% CI.

MEASUREMENTS AND MAIN RESULTS

A total of 16 patients met the inclusion criteria. For the primary outcome, the authors observed that the RRI during ECMO therapy was significantly elevated in patients with AKI compared to those without AKI. As for the secondary outcome, ROC curve analysis revealed an optimal RRI cutoff of 0.797, with an area under the curve of 0.855 (95% CI, 0.664-1, p = 0.027). The sensitivity and specificity of RRI values >0.797 for diagnosing AKI were 72.7% and 80%, respectively. Univariate logistic regression analysis indicated an OR of 1.433 (95% CI 1.192-1.873, p < 0.05) for RRI values above 0.797. This association remained statistically significant even after adjusting for serum cystatin C and Sequential Organ Failure Assessment score, with an adjusted OR of 1.352 (95% CI 1.108-1.612, p < 0.05).

CONCLUSION

The elevation of the RRI demonstrated a strong correlation with the onset of neonatal ECMO-related AKI, which may offer valuable support for diagnosing neonatal ECMO-related AKI.

Classification and Regression Tree Predictive Model for Acute Kidney Injury in Traumatic Brain Injury Patients

Background

Acute kidney injury (AKI) is prevalent in hospitalized patients with traumatic brain injury (TBI), and increases the risk of poor outcomes. We designed this study to develop a visual and convenient decision-tree-based model for predicting AKI in TBI patients.

Methods

A total of 376 patients admitted to the emergency department of the West China Hospital for TBI between January 2015 and June 2019 were included. Demographic information, vital signs on admission, laboratory test results, radiological signs, surgical options, and medications were recorded as variables. AKI was confirmed since the second day after admission, based on the Kidney Disease Improving Global Outcomes criteria. We constructed two predictive models for AKI using least absolute shrinkage and selection operator (LASSO) regression and classification and regression tree (CART), respectively. Receiver operating characteristic (ROC) curves of these two predictive models were drawn, and the area under the ROC curve (AUC) was calculated to compare their predictive accuracy.

Results

The incidence of AKI on the second day after admission was 10.4% among patients with TBI. Lasso regression identified five potent predictive factors for AKI: glucose, serum creatinine, cystatin C, serum uric acid, and fresh frozen plasma transfusions. The CART analysis showed that glucose, serum uric acid, and cystatin C ranked among the top three in terms of the feature importance of the decision tree model. The AUC value of the decision-tree predictive model was 0.892, which was higher than the 0.854 of the LASSO regression model, although the difference was not statistically significant.

Conclusion

The decision tree model is valuable for predicting AKI among patients with TBI. This tree-based flowchart is convenient for physicians to identify patients with TBI who are at high risk of AKI and prompts them to develop suitable therapeutic strategies.

Gut microbiota and neonatal acute kidney injury biomarkers

One of the most frequent issues in newborns is acute kidney injury (AKI), which can lengthen their hospital stay or potentially raise their chance of dying. The gut-kidney axis establishes a bidirectional interplay between gut microbiota and kidney illness, particularly AKI, and demonstrates the importance of gut microbiota to host health. Since the ability to predict neonatal AKI using blood creatinine and urine output as evaluation parameters is somewhat constrained, a number of interesting biomarkers have been developed. There are few in-depth studies on the relationships between these neonatal AKI indicators and gut microbiota. In order to gain fresh insights into the gut-kidney axis of neonatal AKI, this review is based on the gut-kidney axis and describes relationships between gut microbiota and neonatal AKI biomarkers.

An Exploratory Review on the Potential of Artificial Intelligence for Early Detection of Acute Kidney Injury in Preterm Neonates

A preterm birth is a live birth that occurs before 37 completed weeks of pregnancy. Approximately 15 million babies are born preterm annually worldwide, indicating a global preterm birth rate of about 11%. Up to 50% of premature neonates in the gestational age (GA) group of <29 weeks' gestation will develop acute kidney injury (AKI) in the neonatal period; this is associated with high mortality and morbidity. There are currently no proven treatments for established AKI, and no effective predictive tool exists. We propose that the development of advanced artificial intelligence algorithms with neural networks can assist clinicians in accurately predicting AKI. Clinicians can use pathology investigations in combination with the non-invasive monitoring of renal tissue oxygenation (rSO2) and renal fractional tissue oxygenation extraction (rFTOE) using near-infrared spectroscopy (NIRS) and the renal resistive index (RRI) to develop an effective prediction algorithm. This algorithm would potentially create a therapeutic window during which the treating clinicians can identify modifiable risk factors and implement the necessary steps to prevent the onset and reduce the duration of AKI.

Lower serum cystatin C level predicts poor functional outcome in patients with hypertensive intracerebral hemorrhage independent of renal function

We explored the association between the serum level of cystatin C (CysC) at admission and short-term functional outcome in patients with hypertensive intracerebral hemorrhage (HICH) without chronic kidney disease (CKD). A total of 555 patients with HICH were consecutively recruited after admission and were followed-up for 3 months after admission. The primary outcome was poor functional outcome (modified Rankin Scale [mRS] score ≥ 3). The median serum CysC level in our cohort was 1.03 mg/L (interquartile range, .89-1.20). Patients were categorized into four groups according to the serum CysC quartiles. Multivariate logistic regression analysis revealed a negative association between serum CysC and poor functional outcome at 3-month follow-up (quartile [Q]1 vs. Q4: adjusted odds ratio [OR] = .260, 95% confidence interval [CI] = .098, .691, p < .001). The negative association between serum CysC and poor functional outcome at 3 months was more pronounced in subgroups with smaller hematoma volume (≤ 30 mL), and absence of secondary intraventricular hemorrhage (IVH). Addition of serum CysC to a model containing conventional risk factors improved the model performance with net reclassification index (NRI) of .426% (p < .001) and integrated discrimination improvement (IDI) of .043% (p < .001) for poor functional outcome. Serum CysC was found to be a negative predictor of poor short-term functional outcome in HICH patients independent of renal function.

A nomogram based on serum cystatin C for predicting acute kidney injury in patients with traumatic brain injury

BACKGROUND

Acute kidney injury (AKI) is a common complication in traumatic brain injury (TBI) patients and is associated with unfavorable outcome of these patients. We designed this study to explore the value of serum cystatin C, an indicator of renal function, on predicting AKI after suffering TBI.

METHODS

Patients confirmed with TBI and hospitalized in the West China Hospital of Sichuan University between January 2015 and December 2019 were included. Patients were divided into two groups according to occurrence of AKI. Univariate and multivariate logistic regression analyses were sequentially utilized to find risk factors of AKI in included TBI patients. Nomogram composed of discovered risk factors for predicting AKI was constructed. Receiver operating characteristics (ROC) curves were drawn and area under the ROC curve (AUC) were calculated to evaluate the predictive value of cystatin C alone and the constructed nomogram.

RESULTS

Among 234 included TBI patients, 55 were divided into AKI group. AKI group had shorter length of stay (p < 0.001) and higher in-hospital mortality (p < 0.001). Multivariate logistic regression analysis showed absolute lymphocyte count (p = 0.034), serum creatinine (p < 0.001), serum cystatin C (p = 0.017) and transfusion of red blood cell (p = 0.005) were independently associated with development of AKI after TBI. While hypertonic saline use was not associated with the development of AKI (p = 0.067). The AUC of single cystatin C and predictive nomogram were 0.804 and 0.925, respectively.

CONCLUSION

Higher serum cystatin C is associated with development of AKI in TBI patients. Predictive nomogram incorporating cystatin C is beneficial for physicians to evaluate possibilities of AKI and consequently adjust treatment strategies to avoid occurrence of AKI.

Neonatal acute kidney injury: a case-based approach

Neonatal acute kidney injury (AKI) is increasingly recognized as a common complication in critically ill neonates. Over the last 5-10 years, there have been significant advancements which have improved our understanding and ability to care for neonates with kidney disease. A variety of factors contribute to an increased risk of AKI in neonates, including decreased nephron mass and immature tubular function. Multiple factors complicate the diagnosis of AKI including low glomerular filtration rate at birth and challenges with serum creatinine as a marker of kidney function in newborns. AKI in neonates is often multifactorial, but the cause can be identified with careful diagnostic evaluation. The best approach to treatment in such patients may include diuretic therapies or kidney support therapy. Data for long-term outcomes are limited but suggest an increased risk of chronic kidney disease (CKD) and hypertension in these infants. We use a case-based approach throughout this review to illustrate these concepts and highlight important evidence gaps in the diagnosis and management of neonatal AKI.

Risk Factors for Acute Kidney Injury in Critically Ill Neonates: A Systematic Review and Meta-Analysis

Background and Objective: Acute kidney injury (AKI) is recognized as an independent risk factor for mortality and long-term poor prognosis in neonates. The objective of the study was to identify the risk factors for AKI in critically ill neonates to provide an important basis for follow-up research studies and early prevention. Methods: The PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure, WanFang Med, SinoMed, and VIP Data were searched for studies of risk factors in critically ill neonates. Studies published from the initiation of the database to November 19, 2020, were included. The quality of studies was assessed by the Newcastle-Ottawa Scale and the Agency for Healthcare Research and Quality (AHRQ) checklist. The meta-analysis was conducted with Stata 15 and drafted according to the guidelines of the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement. Results: Seventeen studies (five cohort studies, ten case-control studies, and two cross-sectional studies) were included in meta-analysis, with 1,627 cases in the case group and 5,220 cases in the control group. The incidence of AKI fluctuated from 8.4 to 63.3%. Fifteen risk factors were included, nine of which were significantly associated with an increased risk of AKI in critically ill neonates: gestational age [standardized mean difference (SMD) = -0.31, 95%CI = (-0.51, -0.12), P = 0.002], birthweight [SMD = -0.37, 95%CI = (-0.67, -0.07), P = 0.015], 1-min Apgar score [SMD = -0.61, 95%CI = (-0.78, -0.43), P = 0.000], 5-min Apgar score [SMD = -0.71, 95%CI = (-1.00, -0.41), P = 0.000], congenital heart disease (CHD) [odds ratio (OR) = 2.94, 95%CI = (2.08, 4.15), P = 0.000], hyperbilirubinemia [OR = 2.26, 95%CI = (1.40, 3.65), P = 0.001], necrotizing enterocolitis (NEC) [OR = 6.32, 95%CI = (2.98, 13.42), P = 0.000], sepsis [OR = 2.21, 95%CI = (1.25, 3.89), P = 0.006], and mechanical ventilation [OR = 2.37, 95%CI = (1.50, 3.75), P = 0.000]. Six of them were not significantly associated with AKI in critically ill neonates: age [SMD = -0.25, 95%CI = (-0.54, 0.04), P = 0.095], male sex [OR = 1.10, 95%CI =(0.97, 1.24), P = 0.147], prematurity [OR = 0.90, 95%CI(0.52, 1.56), P = 0.716], cesarean section [OR = 1.52, 95%CI(0.77, 3.01), P = 0.234], prenatal hemorrhage [OR = 1.41, 95%CI = (0.86, 2.33), P = 0.171], and vancomycin [OR = 1.16, 95%CI = (0.71, 1.89), P = 0.555]. Conclusions: This meta-analysis provides a preliminary exploration of risk factors in critically ill neonatal AKI, which may be useful for the prediction of AKI. Systematic Review Registration: PROSPERO (CRD42020188032).