Olfactomedin 4 as a novel loop of Henle-specific acute kidney injury biomarker

Real-Time Acute Kidney Injury Risk Stratification-Biomarker Directed Fluid Management Improves Outcomes in Critically Ill Children and Young Adults

Introduction

Critically ill admitted patients are at high risk of acute kidney injury (AKI). The renal angina index (RAI) and urinary biomarker neutrophil gelatinase-associated lipocalin (uNGAL) can aid in AKI risk assessment. We implemented the Trial in AKI using NGAL and Fluid Overload to optimize CRRT Use (TAKING FOCUS 2; TF2) to personalize fluid management and continuous renal replacement therapy (CRRT) initiation based on AKI risk and patient fluid accumulation. We compared outcomes pre-TF2 and post-TF2 initiation.

Methods

Patients admitted from July 2017 were followed-up prospectively with the following: (i) an automated RAI result at 12 hours of admission, (ii) a conditional uNGAL order for RAI ≥8, and (iii) a CRRT initiation goal at 10% to 15% weight-based fluid accumulation.

Results

A total of 286 patients comprised 304 intensive care unit (ICU) RAI+ admissions; 178 patients received CRRT over the observation period (2014-2021). Median time from ICU admission to CRRT initiation was 2 days shorter (P < 0.002), and ≥15% pre-CRRT fluid accumulation rate was lower in the TF2 era (P < 0.02). TF2 ICU length of stay (LOS) after CRRT discontinuation and total ICU LOS were 6 and 11 days shorter for CRRT survivors (both P < 0.02). Survival rates to ICU discharge after CRRT discontinuation were higher in the TF2 era (P = 0.001). These associations persisted in each TF2 year; we estimate a conservative $12,500 health care cost savings per CRRT patient treated after TF2 implementation.

Conclusion

We suggest that automated clinical decision support (CDS) combining risk stratification and AKI biomarker assessment can produce durable reductions in pediatric CRRT patient morbidity.

Acute kidney injury biomarker olfactomedin 4 predicts furosemide responsiveness

BACKGROUND

Acute kidney injury (AKI) is associated with increased morbidity and mortality in critically ill patients. Olfactomedin 4 (OLFM4), a secreted glycoprotein expressed in neutrophils and stressed epithelial cells, is upregulated in loop of Henle (LOH) cells following AKI. We hypothesized that urine OLFM4 (uOLFM4) will increase in patients with AKI and may predict furosemide responsiveness.

METHODS

Urine from critically ill children was collected prospectively and tested for uOLFM4 concentrations with a Luminex immunoassay. Severe AKI was defined by KDIGO (stage 2/3) serum creatinine criteria. Furosemide responsiveness was defined as > 3 mL/kg/h of urine output in the 4 h after a 1 mg/kg IV furosemide dose administered as part of standard of care.

RESULTS

Fifty-seven patients contributed 178 urine samples. Irrespective of sepsis status or AKI cause, uOLFM4 concentrations were higher in patients with AKI (221 ng/mL [IQR 93-425] vs. 36 ng/mL [IQR 15-115], p = 0.007). uOLFM4 concentrations were higher in patients unresponsive to furosemide (230 ng/mL [IQR 102-534] vs. 42 ng/mL [IQR 21-161], p = 0.04). Area under the receiver operating curve for association with furosemide responsiveness was 0.75 (95% CI, 0.60-0.90).

CONCLUSIONS

AKI is associated with increased uOLFM4. Higher uOLFM4 is associated with a lack of response to furosemide. Further testing is warranted to determine whether uOLFM4 could identify patients most likely to benefit from earlier escalation from diuretics to kidney replacement therapy to maintain fluid balance. A higher resolution version of the Graphical abstract is available as Supplementary information.

Early recognition and prevention of acute kidney injury in hospitalised children

Acute kidney injury is common in hospitalised children and is associated with poor patient outcomes. Once acute kidney injury occurs, effective therapies to improve patient outcomes or kidney recovery are scarce. Early identification of children at risk of acute kidney injury or at an early injury stage is essential to prevent progression and mitigate complications. Paediatric acute kidney injury is under-recognised by clinicians, which is a barrier to optimisation of inpatient care and follow-up. Acute kidney injury definitions rely on functional biomarkers (ie, serum creatinine and urine output) that are inadequate, since they do not account for biological variability, analytical issues, or physiological responses to volume depletion. Improved predictive tools and diagnostic biomarkers of kidney injury are needed for earlier detection. Novel strategies, including biomarker-guided care algorithms, machine-learning methods, and electronic alerts tied to clinical decision support tools, could improve paediatric acute kidney injury care. Clinical prediction models should be studied in different paediatric populations and acute kidney injury phenotypes. Research is needed to develop and test prevention strategies for acute kidney injury in hospitalised children, including care bundles and therapeutics.

Precision management of acute kidney injury in the intensive care unit: current state of the art

Acute kidney injury (AKI) is a prototypical example of a common syndrome in critical illness defined by consensus. The consensus definition for AKI, traditionally defined using only serum creatinine and urine output, was needed to standardize the description for epidemiology and to harmonize eligibility for clinical trials. However, AKI is not a simple disease, but rather a complex and multi-factorial syndrome characterized by a wide spectrum of pathobiology. AKI is now recognized to be comprised of numerous sub-phenotypes that can be discriminated through shared features such as etiology, prognosis, or common pathobiological mechanisms of injury and damage. The characterization of sub-phenotypes can serve to enable prognostic enrichment (i.e., identify subsets of patients more likely to share an outcome of interest) and predictive enrichment (identify subsets of patients more likely to respond favorably to a given therapy). Existing and emerging biomarkers will aid in discriminating sub-phenotypes of AKI, facilitate expansion of diagnostic criteria, and be leveraged to realize personalized approaches to management, particularly for recognizing treatment-responsive mechanisms (i.e., endotypes) and targets for intervention (i.e., treatable traits). Specific biomarkers (e.g., serum renin; olfactomedin 4 (OLFM4); interleukin (IL)-9) may further enable identification of pathobiological mechanisms to serve as treatment targets. However, even non-specific biomarkers of kidney injury (e.g., neutrophil gelatinase-associated lipocalin, NGAL; [tissue inhibitor of metalloproteinases 2, TIMP2]·[insulin like growth factor binding protein 7, IGFBP7]; kidney injury molecule 1, KIM-1) can direct greater precision management for specific sub-phenotypes of AKI. This review will summarize these evolving concepts and recent innovations in precision medicine approaches to the syndrome of AKI in critical illness, along with providing examples of how they can be leveraged to guide patient care.