Predictability performance of urinary C-C motif chemokine ligand 14 and renal resistive index for persistent sepsis-associated acute kidney injury in ICU patients

Persistent acute kidney injury biomarkers: A systematic review and meta-analysis

BACKGROUND

Various biomarkers reportedly predict persistent acute kidney injury (AKI) despite their varying predictive performance across clinical trials. This study aims to compare the accuracy of various biomarkers in predicting persistent AKI in different populations and regions.

METHODS

In this meta-analysis, we searched for urinary C-C motif chemokine ligand 14 (CCL14), Tissue inhibitor of metalloproteinase-2&insulin-like growth factor-binding protein-7 (TIMP-2&IGFBP7), Neutrophil Gelatinase-Associated Lipocalin (NGAL), plasma Cystatin C (pCysC), Soluble urokinase plasminogen activator receptor (suPAR), Proenkephalin (PenK) and urinary dickkopf-3:urinary creatinine (uDKK3:uCr) from various databases including Medline, PubMed, Embase, and Cochrane. This was geared towards predicting persistent AKI in adults (>18 years). Hierarchically summarized subject work characteristic curves (HSROC) and diagnostic odds ratio (DOR) values were used to summarize the diagnostic accuracy of the biomarkers. Further, meta-regression and subgroup analyses were carried out to identify sources of heterogeneity as well as evaluate the best predictive biomarkers in different populations and regions.

RESULTS

We screened 31 studies from 2,356 studies and assessed the diagnostic value of 7 biomarkers for persistent AKI. Overall, CCL14 had the best diagnostic efficacy with an AUC of 0.79 (95 % CI 0.75-0.82), whereas TIMP-2 & IGFBP7, NGAL, and pCysC had diagnostic efficacy of 0.75 (95 % CI 0.71-0.79),0.71 (95 % CI 0.67-0.75), and 0.7007, respectively. Due to a limited number of studies, PenK, uDKK3:uCr, and suPAR were not subjected to meta-analysis; however, relevant literature reported diagnostic efficacy above 0.70. Subgroup analyses based on population, region, biomarker detection time, AKI onset time, and AKI duration revealed that in the intensive care unit (ICU) population, the AUC of CCL14 was 0.8070, the AUC of TIMP-2 & IGFBP7 was 0.726, the AUC of pCysC was 0.72, and the AUC of NGAL was 0.7344; in the sepsis population, the AUC of CCL14 was 0.85, the AUC of TIMP-2&IGFBP7 was 0.7438, and the AUC of NGAL was 0.544; in the post-operative population, the AUC of CCL14 was 0.83-0.93, the AUC of TIMP-2&IGFBP7 was 0.71, and the AUC of pCysC was 0.683. Regional differences were observed in biomarker prediction of persistent kidney injury, with AUCs of 0.8558 for CCL14, 0.7563 for TIMP-2 & IGFBP7, and 0.7116 for NGAL in the Eurasian American population. In the sub-African population, TIMP-2 & IGFBP7 had AUCs of 0.7945, 0.7418 for CCL14, 0.7097 for NGAL, and 0.7007 for pCysC. for TIMP-2 & IGFBP7 was 0.7945, AUC for CCL14 was 0.7418, AUC for NGAL was 0.7097, and AUC for pCysC was 0.7007 in the sub-African population. Duration of biomarker detection, AKI onset, and AKI did not influence the optimal predictive performance of CCL14. Subgroup analysis and meta-regression of CCL14-related studies revealed that CCL14 is the most appropriate biomarker for predicting persistent stage 2-3 AKI, with heterogeneity stemming from sample size and AKI staging.

CONCLUSION

This meta-analysis discovered CCL14 as the best biomarker to predict persistent AKI, specifically persistent stage 2-3 AKI.

Chemokine (C-C Motif) Ligand 14 to Predict Persistent Severe Acute Kidney Injury: A Systematic Review and Meta-Analysis

INTRODUCTION

In this systematic review and meta-analysis, we aimed to review available data and provide pooled estimates of the predictive performance of urinary chemokine (C-C motif) ligand (uCCL14) for persistent (≥48 h) severe acute kidney injury (PS-AKI).

METHODS

We searched MEDLINE, PubMed, Cochrane Library, and EMBASE for studies published up to April 11, 2023. We considered all studies including adults and reporting on the ability of uCCL14 to predict PS-AKI as defined by AKI persisting for 48 or 72 h. Data extraction was performed by one investigator using a standardized form. It was checked for adequacy and completeness by another investigator.

RESULTS

After screening, we identified 13 relevant studies. Among those, four (561 patients) provided sufficient data regarding the outcome of interest and were included. Considering each study cutoff value, pooled sensitivity and specificity were 0.85 (95% CI: 0.77-0.90, I2 = 34.1%) and 0.96 (95% CI: 0.94-0.98, I2 = 53.7%), respectively. Pooled positive likelihood ratio (LR), negative LR, and diagnostic odds ratio were 8.98 (95% CI: 4.92-16.37, I2 = 23%), 0.25 (95% CI: 0.17-0.37, I2 = 0%), and 14.98 (95% CI: 3.55-63.27, I2 = 72.9%), respectively. The area under the curve estimated by summary receiver operating characteristics was 0.86 (95% CI: 0.70-0.95). Heterogeneity induced by the threshold effect was low (Spearman's correlation coefficient: -0.30, p value = 0.62) but significant for non-threshold effect. Risk of bias and concern for applicability according to the QUADAS-2 criteria was generally low. High risk in the index test due to the absence of prespecified thresholds was a concern for most studies.

CONCLUSION

Based on current evidence, uCCL14 appears to have a good predictive performance for the occurrence of PS-AKI. Interventional trials to study a biomarker-guided application of AKI care bundles and RRT are indicated.

Renal arterial resistive index versus novel biomarkers for the early prediction of sepsis-associated acute kidney injury

Acute kidney injury (AKI) is a critical complication of sepsis. There is a continuous need to identify and validate biomarkers for early detection. Serum and urinary biomarkers have been investigated, such as neutrophil gelatinase associated lipocalin (NGAL) and cystatin C (Cys C), but their reliability in the intensive care unit (ICU) remains unknown. Renal hemodynamics can be investigated by measuring the renal resistive index (RRI). This study aimed to compare the performance of RRI, serum NGAL (sNGAL), urinary NGAL (uNGAL), and serum Cys C levels as early predictors of the diagnosis and persistence of sepsis-associated AKI. A total of 166 adult patients with sepsis syndrome were enrolled immediately after ICU admission. Biomarkers were measured directly (T1) and on day 3 (T3). RRI was measured directly (T1) and 24 h later (T2). Patients were categorized (according to the occurrence and persistence of AKI within the first 7 days) into three groups: no AKI, transient AKI, and persistent AKI. The incidence rate of sepsis-associated AKI was 60.2%. Sixty-six patients were categorized as in the no AKI group, while another 61 were in transient AKI and only 39 were in persistent AKI. The RRI value (T1 ≥ 0.72) was the best tool for predicting AKI diagnosis (area under the receiver operating characteristic curve, AUROC = 0.905). Cys C (T1 ≥ 15.1 mg/l) was the best tool to predict the persistence of AKI (AUROC = 0.977). RRI (T1) was the best predictive tool for sepsis-associated AKI, while Cys C was the best predictor of its persistence and 28-day mortality.

Low HDL-C can be a biomarker to predict persistent severe AKI in septic patients? A retrospective cohort study

PURPOSES

Low HDL-C is associated with an increased risk of sepsis-associated AKI and subsequent decline in eGFR. HDL-C possesses anti-inflammatory, antioxidant, and endothelial repair-promoting properties. The use of Apo A-I mimetic peptides, which are the main structural components of HDL-C, has been shown to improve renal function in animal models of sepsis. However, the diagnostic value of low HDL-C in persistent sepsis-associated AKI remains unclear.

METHODS

This is a retrospective cohort study based on MIMIC IV (V 2.2). The study population consisted of all adult septic patients admitted to the Beth Israel Deaconess Medical Center Intensive Care Unit from 2008 to 2019, with plasma HDL-C measured within 24 h of ICU admission. The primary endpoint was persistent severe sepsis-associated acute kidney injury (SA-AKI) and the secondary endpoint is kidney replacement therapy (KRT). Logistic regression was used to assess the correlation between HDL-C and persistent severe SA-AKI and KRT, and receiver operating characteristic (ROC) curve analysis was performed to evaluate predictive ability.

RESULTS

A total of 604 cases of SA-AKI patients were included in the analysis, among which 88 cases (14.5%) experienced persistent severe SA-AKI. The median (IQR) HDL-C level in the group with persistent severe SA-AKI was lower (33.0 [24.0-45.5]) compared to the non-persistent severe SA-AKI group (42.0 [31.0-53.0]). However, HDL-C showed poor discriminatory ability with an AUROC [95%CI] of 0.62 [0.56-0.69]. Clinical prediction models based on serum creatinine concentration, 24-h creatinine change, APSIIIscore, lactate levels, APTT, and heart rate performed well in predicting persistent severe SA-AKI with an AUROC [95%CI] of 0.876 [0.84-0.91]. However, adding HDL-C to this model did not improve predictive performance.

CONCLUSIONS

The plasma HDL-C measured within 24 h after admission to the ICU does not provide a good prediction for persistent severe SA-AKI, and it does not improve the clinical predictive ability compared to conventional variables.

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.