Biomarkers in Acute Kidney Injury

AKIMLpred: An interpretable machine learning model for predicting acute kidney injury within seven days in critically ill patients based on a prospective cohort study

BACKGROUND

Early recognition and timely intervention for AKI in critically ill patients were crucial to reduce morbidity and mortality. This study aimed to use biomarkers to construct a optimal machine learning model for early prediction of AKI in critically ill patients within seven days.

METHODS

The prospective cohort study enrolled 929 patients altogether who were admitted in ICU including 680 patients in training set (Jiefang Campus) and 249 patients in external testing set (Binjiang Campus). After performing strict inclusion and exclusion criteria, 421 patients were selected in training set for constructing predictive model and 167 patients were selected in external testing for evaluating the predictive performance of resulting model. Urine and blood samples were collected for kidney injury associated biomarkers detection. Baseline clinical information and laboratory data of the study participants were collected. We determined the average prediction efficiency of six machine learning models through 10-fold cross validation.

RESULTS

In total, 78 variables were collected when admission in ICU and 43 variables were statistically significant between AKI and non-AKI cohort. Then, 35 variables were selected as independent features for AKI by univariate logistic regression. Spearman correlation analysis was used to remove two highly correlated variables. Three ranking methods were used to explore the influence of 33 variables for further determining the best combination of variables. The gini importance ranking method was found to be applicable for variables filtering. The predictive performance of AKIMLpred which constructed by the XGBoost algorithm was the best among six machine learning models. When the AKIMLpred included the nine features (NGAL, IGFBP7, sCysC, CAF22, KIM-1, NT-proBNP, IL-6, IL-18 and L-FABP) with the highest influence ranking, its model had the best prediction performance, with an AUC of 0.881 and an accuracy of 0.815 in training set, similarly, with an AUC of 0.889 and an accuracy of 0.846 in validation set. Moreover, the performace was slightly outperformed in testing set with an AUC of 0.902 and an accuracy of 0.846. The SHAP algorithm was used to interpret the prediction results of AKIMLpred. The web-calculator of AKIMLpred was shown for predicting AKI with more convenient(https://www.xsmartanalysis.com/model/list/predict/model/html?mid=8065&symbol=11gk693982SU6AE1ms21). AKIMLpred was better than the optimal model built with only routine tests for predicting AKI in critically ill patients within 7 days.

CONCLUSION

The model AKIMLpred constructed by the XGBoost algorithm with selecting the nine most influential biomarkers in the gini importance ranking method had the best performance in predicting AKI in critically ill patients within 7 days. This data-driven predictive model will help clinicians to make quick and accurate diagnosis.

Predictive performance of two types of urinary biomarkers for renal non-recovery in sepsis-associated acute kidney injury: a prospective observational study

BACKGROUND AND PURPOSE

Renal non-recovery is known to have negative prognostic implications in patients suffering from acute kidney injury (AKI). Nevertheless, the identification of biomarkers for predicting renal non-recovery in sepsis-associated AKI (SA-AKI) within clinical settings remains unresolved. This study aims to evaluate and compare the predictive ability for renal non-recovery, use of kidney replacement therapy (KRT) in the Intensive Care Unit (ICU), and 30-day mortality after SA-AKI by two urinary biomarkers, namely C-C motif chemokine ligand 14 (CCL14) and [TIMP-2]•[IGFBP7].

METHODS

We prospectively screened adult patients who met the criteria for AKI stage 2-3 and Sepsis-3.0 in two ICUs from January 2019 to May 2022. Patients who developed new-onset SA-AKI after ICU admission were enrolled and urinary biomarkers including [TIMP-2]•[IGFBP7] and CCL14 were detected at the time of SA-AKI diagnosis. The primary endpoint was non-recovery from SA-AKI within 7 days. The secondary endpoints were the use of KRT in the ICU and 30-day mortality after SA-AKI. The individual discriminative ability of [TIMP-2]•[IGFBP7] and CCL14 to predict renal non-recovery were evaluated by the area under receiver operating characteristics curve (AUC).

RESULTS

141 patients with stage 2-3 SA-AKI were finally included, among whom 54 (38.3%) experienced renal non-recovery. Urinary CCL14 exhibited a higher predictive capability for renal non-recovery compared to [TIMP-2]•[IGFBP7], with CCL14 showing an AUC of 0.901, versus an AUC of 0.730 for [TIMP-2]•[IGFBP7] (P = 0.001). Urinary CCL14 and [TIMP-2]•[IGFBP7] demonstrated a moderate predictive value for the need for KRT in ICU, with AUC values of 0.794 and 0.725, respectively; The AUC of [TIMP-2]•[IGFBP7] combined with CCL14 reached up to 0.816. Urinary CCL14 and [TIMP-2]•[IGFBP7] exhibited poor predictive power for 30-day mortality, with respective AUC values of 0.623 and 0.593.

CONCLUSION

Urinary CCL14 had excellent predictive value for renal non-recovery in SA-AKI patients. For predicting the use of KRT in the ICU, the predictive capability of urinary [TIMP-2]•[IGFBP7] or CCL14 was fair. However, a combination of [TIMP-2]•[IGFBP7] and CCL14 showed good predictive ability for the use of KRT.

Furosemide stress test to predict acute kidney injury progression in critically ill children

BACKGROUND

Furosemide stress test (FST) is a novel functional biomarker for predicting severe acute kidney injury (AKI); however, pediatric studies are limited.

METHODS

Children 3 months to 18 years of age admitted to the intensive care unit (ICU) of a tertiary care hospital from Nov 2019 to July 2021 were screened and those who developed AKI stage 1 or 2 within 7 days of admission underwent FST (intravenous furosemide 1 mg/kg). Urine output was measured hourly for the next 6 h; a value > 2 ml/kg within the first 2 h was deemed furosemide responsive. Other biomarkers like plasma neutrophil gelatinase-associated lipocalin (NGAL) and proenkephalin (PENK) were also evaluated.

RESULTS

Of the 480 admitted patients, 51 developed AKI stage 1 or 2 within 7 days of admission and underwent FST. Nine of these patients were furosemide non-responsive. Thirteen (25.5%) patients (eight of nine from FST non-responsive group) developed stage 3 AKI within 7 days of FST, nine (17.6%) of whom (seven from non-responsive group) required kidney support therapy (KST). FST emerged as a good biomarker for predicting stage 3 AKI and need for KST with area-under-the-curve (AUC) being 0.93 ± 0.05 (95% CI 0.84-1.0) and 0.96 ± 0.03 (95% CI 0.9-1.0), respectively. FST outperformed NGAL and PENK in predicting AKI stage 3 and KST; however, the combination did not improve the diagnostic accuracy.

CONCLUSIONS

Furosemide stress test is a simple, inexpensive, and robust biomarker for predicting stage 3 AKI and KST need in critically ill children. Further research is required to identify the best FST cut-off in children.

Urinary Collectrin as Promising Biomarker for Acute Kidney Injury in Patients Undergoing Cardiac Surgery

BACKGROUND

Early detection of acute kidney injury (AKI) is crucial for timely intervention and improved patient outcomes after cardiac surgery. This study aimed to evaluate the potential of urinary collectrin as a novel biomarker for AKI in this patient population.

METHODS

In this prospective, observational cohort study, 63 patients undergoing elective cardiac surgery with cardiopulmonary bypass (CPB) were studied at the Medical University of Vienna between 2016 and 2018. We collected urine samples prospectively at four perioperative time points, and urinary collectrin was measured using an enzyme-linked immunosorbent assay. Patients were divided into two groups, AKI and non-AKI, defined by Kidney Disease: Improving Global Outcomes Guidelines, and differences between groups were analyzed.

RESULTS

Postoperative AKI was found in 19 (30%) patients. Urine sample analysis revealed an inverse correlation between urinary collectrin and creatinine and AKI stages, as well as significant changes in collectrin levels during the perioperative course. Baseline collectrin levels were 5050 ± 3294 pg/mL, decreased after the start of CPB, reached their nadir at the end of surgery, and began to recover slightly on postoperative day (POD) 1. The most effective timepoint for distinguishing between AKI and non-AKI patients based on collectrin levels was POD 1, with collectrin levels of 2190 ± 3728 pg/mL in AKI patients and 3768 ± 3435 pg/mL in non-AKI patients (p = 0.01).

CONCLUSIONS

Urinary collectrin shows promise as a novel biomarker for the early detection of AKI in patients undergoing cardiac surgery on CPB. Its dynamic changes throughout the perioperative period, especially on POD 1, provide valuable insights for timely diagnosis and intervention. Further research and validation studies are needed to confirm its clinical usefulness and potential impact on patient outcomes.

A Combined Biomarker That Includes Plasma Fibroblast Growth Factor 23, Erythropoietin, and Klotho Predicts Short- and Long-Term Morbimortality and Development of Chronic Kidney Disease in Critical Care Patients with Sepsis: A Prospective Cohort

Acute Kidney Injury (AKI) is a frequent complication in intensive care unit (ICU) patients that increases mortality and chronic kidney disease (CKD) development. AKI is associated with elevated plasma fibroblast growth factor 23 (FGF23), which can be modulated by erythropoietin (EPO) and Klotho. We aimed to evaluate whether a combined biomarker that includes these molecules predicted short-/long-term outcomes. We performed a prospective cohort of ICU patients with sepsis and previously normal renal function. They were followed during their inpatient stay and for one year after admission. We measured plasma FGF23, EPO, and Klotho levels at admission and calculated a combined biomarker (FEK). A total of 164 patients were recruited. Of these, 50 (30.5%) had AKI at admission, and 55 (33.5%) developed AKI within 48 h. Patients with AKI at admission and those who developed AKI within 48 h had 12- and 5-fold higher FEK values than non-AKI patients, respectively. Additionally, patients with higher FEK values had increased 1-year mortality (41.9% vs. 18.6%, p = 0.003) and CKD progression (26.2% vs. 8.3%, p = 0.023). Our data suggest that the FEK indicator predicts the risk of AKI, short-/long-term mortality, and CKD progression in ICU patients with sepsis. This new indicator can improve clinical outcome prediction and guide early therapeutic strategies.

The early diagnosis and pathogenic mechanisms of sepsis-related acute kidney injury

Sepsis is a syndrome caused by an imbalance in the inflammatory response of the body caused by an infection that leads to organ dysfunction, with the kidney being one of the most commonly affected organs. Sepsis-related acute kidney injury (SAKI) is strongly linked to increased mortality and poor clinical outcomes. Early diagnosis and treatment can significantly reduce patient mortality. On the other hand, the pathogenesis of SAKI is not fully understood, and early diagnosis of SAKI is a clinical challenge. Therefore, the current review describes biomarkers of acute kidney injury in sepsis and discusses the various pathogenic mechanisms involved in the progression of acute kidney injury in sepsis to develop new clinical treatment avenues.

Performance of urinary C-C motif chemokine ligand 14 for the prediction of persistent acute kidney injury: a systematic review and meta-analysis

BACKGROUND

Urinary C-C motif chemokine ligand 14 (CCL14) has been described as an effective marker for delayed recovery of acute kidney injury (AKI), yet its efficacy has been found to vary between different trials. The goal of this research was to assess the predictive performance of urinary CCL14 as a marker for persistent AKI.

METHODS

In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched the PubMed, Embase, and Cochrane databases up to April 2023 for studies of adults (> 18 years) that reported the diagnostic performance of urinary CCL14. The sensitivity, specificity, number of events, true positive, and false positive results were extracted and evaluated. Hierarchical summary receiver operating characteristic curves (HSROCs) were used to summarize the pooled test performance, and the Grading of Recommendations, Assessment, Development and Evaluations criteria were used to appraise the quality of evidence.

RESULTS

We included six studies with 952 patients in this meta-analysis. The occurrence of persistent AKI among these patients was 39.6% (377/952). The pooled sensitivity and specificity results of urinary CCL14 in predicting persistent AKI were 0.81 (95% CI 0.72-0.87) and 0.71 (95% CI 0.53-0.84), respectively. The pooled positive likelihood ratio (LR) was 2.75 (95% CI 1.63-4.66), and the negative LR was 0.27 (95% CI 0.18-0.41). The HSROC with pooled diagnostic accuracy was 0.84.

CONCLUSION

Our results suggest that urinary CCL14 can be used as an effective marker for predicting persistent AKI.

Analysis of urinary C-C motif chemokine ligand 14 (CCL14) and first-generation urinary biomarkers for predicting renal recovery from acute kidney injury: a prospective exploratory study

BACKGROUND

Acute kidney injury (AKI) is a frequent syndrome in the intensive care unit (ICU). AKI patients with kidney function recovery have better short-term and long-term prognoses compared with those with non-recovery. Numerous studies focus on biomarkers to distinguish them. To better understand the predictive performance of urinary biomarkers of renal recovery in patients with AKI, we evaluated C-C motif chemokine ligand 14 (CCL14) and two first-generation biomarkers (cell cycle arrest biomarkers and neutrophil gelatinase-associated lipocalin) in two ICU settings.

METHODS

We performed a prospective study to analyze urinary biomarkers for predicting renal recovery from AKI. Patients who developed AKI after ICU admission were enrolled and urinary biomarkers including tissue inhibitor of metalloproteinase-2 (TIMP-2), insulin-like growth factor-binding protein 7 (IGFBP7), CCL14, and neutrophil gelatinase-associated lipocalin (NGAL) were detected on the day of AKI diagnosis. The primary endpoint was non-recovery from AKI within 7 days. The individual discriminative ability of CCL14, [TIMP-2] × [IGFBP7] and NGAL to predict renal non-recovery were evaluated by the area under receiver operating characteristics curve (AUC).

RESULTS

Of 164 AKI patients, 64 (39.0%) failed to recover from AKI onset. CCL14 showed a fair prediction ability for renal non-recovery with an AUC of 0.71 (95% CI 0.63-0.77, p < 0.001). [TIMP-2] × [IGFBP7] showed the best prediction for renal non-recovery with an AUC of 0.78 (95% CI 0.71-0.84, p < 0.001). However, NGAL had no use in predicting non-recovery with an AUC of 0.53 (95% CI 0.45-0.60, p = 0.562). A two-parameter model (non-renal SOFA score and AKI stage) predicted renal non-recovery with an AUC of 0.77 (95% CI 0.77-0.83, p = 0.004). When [TIMP-2] × [IGFBP7] was combined with the clinical factors, the AUC was significantly improved to 0.82 (95% CI 0.74-0.87, p = 0.049).

CONCLUSIONS

Urinary CCL14 and [TIMP-2] × [IGFBP7] were fair predictors of renal non-recovery from AKI. Combing urinary [TIMP-2] × [IGFBP7] with a clinical model consisting of non-renal SOFA score and AKI stage enhanced the predictive power for renal non-recovery. Urinary CCL14 showed no significant advantage in predicting renal non-recovery compared to [TIMP-2] × [IGFBP7].

Biomarkers in Primary Focal Segmental Glomerulosclerosis in Optimal Diagnostic-Therapeutic Strategy

Focal segmental glomerulosclerosis (FSGS) involves podocyte injury. In patients with nephrotic syndrome, progression to end-stage renal disease often occurs over the course of 5 to 10 years. The diagnosis is based on a renal biopsy. It is presumed that primary FSGS is caused by an unknown plasma factor that might be responsible for the recurrence of FSGS after kidney transplantation. The nature of circulating permeability factors is not explained and particular biological molecules responsible for inducing FSGS are still unknown. Several substances have been proposed as potential circulating factors such as soluble urokinase-type plasminogen activator receptor (suPAR) and cardiolipin-like-cytokine 1 (CLC-1). Many studies have also attempted to establish which molecules are related to podocyte injury in the pathogenesis of FSGS such as plasminogen activator inhibitor type-1 (PAI-1), angiotensin II type 1 receptors (AT1R), dystroglycan(DG), microRNAs, metalloproteinases (MMPs), forkheadbox P3 (FOXP3), and poly-ADP-ribose polymerase-1 (PARP1). Some biomarkers have also been studied in the context of kidney tissue damage progression: transforming growth factor-beta (TGF-β), human neutrophil gelatinase-associated lipocalin (NGAL), malondialdehyde (MDA), and others. This paper describes molecules that could potentially be considered as circulating factors causing primary FSGS.

Persistent Markers of Kidney Injury in Children Who Developed Acute Kidney Injury After Pediatric Cardiac Surgery: A Prospective Cohort Study

Background

Acute kidney injury (AKI) after pediatric cardiac surgery is common. Longer‐term outcomes and the incidence of chronic kidney disease after AKI are not well‐known.

Methods and Results

All eligible children (aged <16 years) who had developed AKI following cardiac surgery at our tertiary referral hospital were prospectively invited for a formal kidney assessment ≈5 years after AKI, including measurements of estimated glomerular filtration rate, proteinuria, α₁‐microglobulin, blood pressure, and kidney ultrasound. Longer‐term follow‐up data on kidney function were collected at the latest available visit. Among 571 patients who underwent surgery, AKI occurred in 113 (19.7%) over a 4‐year period. Fifteen of these (13.3%) died at a median of 31 days (interquartile range [IQR], 9–57) after surgery. A total of 66 patients participated in the kidney assessment at a median of 4.8 years (IQR, 3.9–5.7) after the index AKI episode. Thirty‐nine patients (59.1%) had at least 1 marker of kidney injury, including estimated glomerular filtration rate <90 mL/min per 1.73 m² in 9 (13.6%), proteinuria in 27 (40.9%), α₁‐microglobinuria in 5 (7.6%), hypertension in 13 (19.7%), and abnormalities on kidney ultrasound in 9 (13.6%). Stages 1 to 5 chronic kidney disease were present in 18 (27.3%) patients. Patients with CKD were more likely to have an associated syndrome (55.6% versus 20.8%, P=0.015). At 13.1 years (IQR, 11.2–14.0) follow‐up, estimated glomerular filtration rate <90 mL/min per 1.73 m² was present in 18 of 49 patients (36.7%), suggesting an average estimated glomerular filtration rate decline rate of −1.81 mL/min per 1.73 m² per year.

Conclusions

Children who developed AKI after pediatric cardiac surgery showed persistent markers of kidney injury. As chronic kidney disease is a risk factor for cardiovascular comorbidity, long‐term kidney follow‐up in this population is warranted.

Sevoflurane preconditioning prevents acute renal injury caused by ischemia‑reperfusion in mice via activation of the Nrf2 signaling pathway

Oxidative stress, caused by renal ischemia reperfusion (IR)/hypoperfusion, is one of the main causes of acute kidney injury (AKI). Previous studies have demonstrated that sevoflurane (SEV) protects organs from the damage caused by oxidative stress. In the present study, mice were randomly assigned to a sham operation group (Sham), IR-vehicle group (IR+ vehicle), IR + SEV low-dose preconditioning group and an IR + SEV high-dose preconditioning group. The effect of SEV on nuclear factor E2-related factor 2 (Nrf2), a key regulatory protein of the endogenous antioxidant defense system and, consequently oxidative stress, inflammation and apoptosis-related factors, were all quantified using commercial kits or by western blotting. SEV preconditioning was demonstrated to ameliorate kidney injury as a result of decreased blood urine nitrogen and serum creatinine levels, activated Nrf2 expression in the kidney and decreased oxidative stress and inflammatory index levels an AKI mouse model. SEV preconditioning also protected injured kidney via the downregulation of caspase-3 protein expression levels. In addition, using the Nrf2 inhibitor, Brusatol, significantly abolished the SEV preconditioning renal protective effect. Using an in vitro HK-2 cell model of hypoxia/reoxygenation, it was also demonstrated that Nrf2 pathway activation was necessary for SEV to exert its beneficial effect for tubular cell injury caused by hypoxia/reoxygenation. These results indicated that SEV may protect against renal injury caused by IR via Nrf2 upregulation.

Decreased preoperative urinary uromodulin as a predictor of acute kidney injury and perioperative kidney dysfunction in patients undergoing cardiac surgery: a prospective cohort study

BACKGROUND

Acute kidney injury (AKI) is a major complication following cardiac surgery that substantially increases mortality. We explored the clinical utility of urinary uromodulin (uUMOD), a marker of renal tubular reserve, for preoperative identification of patients at risk for AKI and perioperative kidney dysfunction.

METHODS

This prospective observational study included patients who underwent cardiac surgery between December 2019 and January 2021. AKI was defined according to the Kidney Disease Improving Global Outcomes criteria; perioperative kidney dysfunction was accessed using a longitudinal estimated glomerular filtration rate.

RESULTS

A total of 409 participants were enrolled. Patients with uUMOD ≤ 20.7 µg/mL were associated with a higher risk for AKI (odds ratio, 3.24; 95% confidence interval: 1.87-5.63, P < 0.001), independent of baseline kidney function. The uUMOD exhibits adequate discrimination for predicting AKI, with an area under the receiver operating characteristic curve of 0.713 (95% confidence interval: 0.652-0.773), and has well-fitted calibration (Hosmer-Lemeshow goodness-of-fit test, P = 0.163). The trajectory analysis revealed that decreased uUMOD levels were linked to a higher risk of patients being assigned to a worse perioperative kidney function cluster.

CONCLUSIONS

Decreased preoperative uUMOD is independently associated with an increased risk of AKI and perioperative kidney dysfunction after cardiac surgery.

Serum Lactate Level in Early Stage Is Associated With Acute Kidney Injury in Traumatic Brain Injury Patients

Background

Acute kidney injury (AKI) is a common complication in the clinical practice of managing patients with traumatic brain injury (TBI). Avoiding the development of AKI is beneficial for the prognosis of patients with TBI. We designed this study to testify whether serum lactate could be used as a predictive marker of AKI in patients with TBI.

Materials and Methods

In total, 243 patients with TBI admitted to our hospital were included in this study. Univariate and multivariate logistic regression analyses were utilized to analyze the association between lactate and AKI. The receiver operating characteristic (ROC) curves were drawn to verify the predictive value of lactate and the logistic model.

Results

Acute kidney injury group had higher age (p = 0.016), serum creatinine (p < 0.001), lactate (p < 0.001), and lower Glasgow Coma Scale (GCS; p = 0.021) than non-AKI group. Multivariate logistic regression showed that age [odds ratio (OR) = 1.026, p = 0.022], serum creatinine (OR = 1.020, p = 0.010), lactate (OR = 1.227, p = 0.031), fresh frozen plasma (FFP) transfusion (OR = 2.421, p = 0.045), and platelet transfusion (OR = 5.502, p = 0.044) were risk factors of AKI in patients with TBI. The area under the ROC curve (AUC) values of single lactate and predictive model were 0.740 and 0.807, respectively.

Conclusion

Serum lactate level in the early phase is associated with AKI in patients with TBI. Lactate is valuable for clinicians to evaluate the probability of AKI in patients with TBI.

Health system perspectives in acute kidney injury: commitment to kidney health and planning implementation interventions

PURPOSE OF REVIEW

To discuss a deliberate commitment by health systems to optimize kidney health and outcomes of patients who are at risk for or develop acute kidney injury (AKI) during hospitalization.

RECENT FINDINGS

In 2019, the US Department of Health and Human Services set national goals targeted at improving the care and outcomes of patients with kidney disease including prevention by reducing the number of Americans who develop end-stage kidney disease (ESKD) by 25% by 2030. In response to this call to action, there is a need to focus on education to identify patients at high-risk for kidney disease development and progression, active surveillance methods to ensure timely identification, offering better follow-up care after an episode of AKI. A strategic approach to determining the health systems level of commitment and developing a plan for organizational change is discussed in this commentary. Items for consideration are structuring sound implementation projects and selecting implementation interventions. Clinical interventions to consider for implementation include the use of clinical decision support for detecting patients with AKI, novel biomarkers to determine patients at high-risk for AKI and nephrotoxin stewardship to prevent medication safety complications and drug-associated AKI.

SUMMARY

There is a national call to action to improve the care and outcomes of patients with kidney disease. Health systems have an opportunity to respond by providing a high level of commitment towards ensuring the best kidney health for all patients equally. Deliberate change that is sustainable and scalable should be considered by all health systems.

Decreased urinary uromodulin is potentially associated with acute kidney injury: a systematic review and meta-analysis

BACKGROUND

Urinary uromodulin (uUMOD) is one of the novel biomarkers for predicting AKI. However, currently available publications showed inconsistent results. We designed this meta-analysis to evaluate the potential association between uUMOD and AKI.

METHODS

We searched research articles with no language restriction in Medline, Web of Science, Cochrane Library, Embase, and 3 Chinese datasets from inception to February 2021. We used random-effects models to estimate the standardized mean difference (SMD) between patients with AKI or not, while the leave-one-out method and random-effects meta-regression to evaluate the sensitivity and the impact of potential confounders such as age and surgery.

RESULTS

The meta-analysis comprising 3148 subjects from 11 studies showed that the uUMOD of the AKI group is significantly lower than the non-AKI group (SMD: - 0.71; 95% confidence interval (CI), - 1.00, - 0.42, P < 0. 001, I2 = 78.8%). Subgroup analysis revealed the difference is also significant in a different age, surgery condition, and assay time but not acute rejection (AR) group, especially in children (SMD: - 1.21, 95% CI: - 1.80, - 0.61; P < 0.001) and patients undergoing surgery (SMD: - 1.03, 95% CI: - 1.75, - 0.30; P < 0.001). Lower uromodulin is associated with higher odds for AKI incidence (odds ratio = 2.47, 95% CI: 1.12, 5.47; P < 0.001, I2 = 89%). Meta-reggression found that age was associated with the SMD of uUMOD. The study outcome was reliably confirmed by the sensitivity analysis.

CONCLUSION

The present study suggested a negative association between uUMOD and AKI especially in children and surgical patients.