24-hour Serum Creatinine Variation Associates with Short- and Long-Term All-Cause Mortality: A Real-World Insight into Early Detection of Acute Kidney Injury

Biomarkers vs Machines: The Race to Predict Acute Kidney Injury

BACKGROUND

Acute kidney injury (AKI) is a serious complication affecting up to 15% of hospitalized patients. Early diagnosis is critical to prevent irreversible kidney damage that could otherwise lead to significant morbidity and mortality. However, AKI is a clinically silent syndrome, and current detection primarily relies on measuring a rise in serum creatinine, an imperfect marker that can be slow to react to developing AKI. Over the past decade, new innovations have emerged in the form of biomarkers and artificial intelligence tools to aid in the early diagnosis and prediction of imminent AKI.

CONTENT

This review summarizes and critically evaluates the latest developments in AKI detection and prediction by emerging biomarkers and artificial intelligence. Main guidelines and studies discussed herein include those evaluating clinical utilitiy of alternate filtration markers such as cystatin C and structural injury markers such as neutrophil gelatinase-associated lipocalin and tissue inhibitor of metalloprotease 2 with insulin-like growth factor binding protein 7 and machine learning algorithms for the detection and prediction of AKI in adult and pediatric populations. Recommendations for clinical practices considering the adoption of these new tools are also provided.

SUMMARY

The race to detect AKI is heating up. Regulatory approval of select biomarkers for clinical use and the emergence of machine learning algorithms that can predict imminent AKI with high accuracy are all promising developments. But the race is far from being won. Future research focusing on clinical outcome studies that demonstrate the utility and validity of implementing these new tools into clinical practice is needed.

Combinative predictive effect of left ventricular mass index, ratio of HDL and CRP for progression of chronic kidney disease in non-dialysis patient

PURPOSE

This current study scrutinized the association among left ventricular mass index (LVMI), ratio of high-density lipoprotein (HDL) and C-reactive protein (CRP), and renal function. Furthermore, we examined the predictive effects of left ventricular mass index and HDL/CRP on progression of non-dialysis chronic kidney disease.

METHODS

We enrolled adult patients with chronic kidney disease (CKD) who were not receiving dialysis and obtained follow-up data on them. We extracted and compared data between different groups. To investigate the relationship between left ventricular mass index (LVMI), high-density lipoprotein (HDL)/C-reactive protein (CRP) levels, and CKD, we employed linear regression analysis, Kaplan-Meier analysis, and Cox proportional hazards regression analysis.

RESULTS

Our study enrolled a total of 2351 patients. Compared with those in the non-progression group, subjects in the CKD progression group had lower ln(HDL/CRP) levels (- 1.56 ± 1.78 vs. - 1.14 ± 1.77, P < 0.001) but higher left ventricular mass index (LVMI) values (115.45 ± 29.8 vs. 102.8 ± 26.31 g/m2, P < 0.001). Moreover, after adjusting for demographic factors, ln(HDL/CRP) was found to be positively associated with estimated glomerular filtration rate (eGFR) (B = 1.18, P < 0.001), while LVMI was negatively associated with eGFR (B = - 0.15, P < 0.001). In the end, we found that both LVH (HR = 1.53, 95% CI 1.15 to 2.05, P = 0.004) and lower ln(HDL/CRP) (HR = 1.46, 95% CI 1.08 to 1.96, P = 0.013) independently predicted CKD progression. Notably, the combined predictive power of these variables was stronger than either variable alone (HR = 1.98, 95% CI 1.5 to 2.62, P < 0.001).

CONCLUSION

Our study findings indicate that in pre-dialysis patients, both HDL/CRP and LVMI are associated with basic renal function and are independently correlated with CKD progression. These variables may serve as predictors for CKD progression, and their combined predictive power is stronger than that of either variable alone.

Prognostic significance of early acute kidney injury in COVID-19 patients requiring mechanical ventilation: a single-center retrospective analysis

Acute kidney injury (AKI) is associated with impaired outcomes in critically ill COVID-19 patients. However, the prognostic significance of early AKI is poorly described. We aimed to determine whether AKI on admission to the intensive care unit (ICU) and its development within the first 48 h predict the need for renal replacement therapy (RRT) and increased mortality. An analysis of 372 patients with COVID-19 pneumonia requiring mechanical ventilation without advanced chronic kidney disease from 2020 to 2021 was performed. The AKI stages on ICU admission and Day 2 were determined using adapted KDIGO criteria. The early development of renal function was assessed by the change in AKI score and the Day-2/Day-0 creatinine ratio. Data were compared between three consecutive COVID-19 waves and with data before the pandemic. Both ICU and 90-day mortality (79% and 93% vs. 35% and 44%) and the need for RRT increased markedly with advanced AKI stage on ICU admission. Similarly, an early increase in AKI stage and creatinine implied highly increased mortality. RRT was associated with very high ICU and 90-day mortality (72% and 85%), even surpassing that of patients on ECMO. No difference was found between consecutive COVID-19 waves, except for a lower mortality in the patients on RRT in the last omicron wave. Mortality and need for RRT were comparable in the COVID-19 and pre-COVID-19 patients, except that RRT did not increase ICU mortality in the pre-COVID-19 era. In conclusion, we confirmed the prognostic significance of both AKI on ICU admission and its early development in patients with severe COVID-19 pneumonia.

Predictive Effect of System Inflammation Response Index for Progression of Chronic Kidney Disease in Non-Dialyzing Patient

Purpose

Scant research has been conducted on the interplay between the systemic inflammation response index (SIRI) and chronic kidney disease (CKD). The present study endeavors to meticulously scrutinize the association between SIRI and renal function. Additionally, we aim to assess its efficacy in predicting the progression of CKD in non-dialysis patients.

Patients and Methods

Adult patients with CKD who were not undergoing dialysis were enrolled, and follow-up data were obtained. Data from distinct groups were extracted and meticulously compared. A comprehensive analytical approach was adopted, including logistic regression analysis, Kaplan-Meier analysis, Cox proportional hazards regression analysis, and subgroup analysis.

Results

Our study included 1420 patients, with a mean age of 61 ± 17 years, and 63% were male. 244 (17.2%) patients experienced the progression of CKD. As the level of ln(SIRI) increased, patients tended to be older, with a higher proportion of males, and increased prevalence rates of hypertension, stroke, heart failure, and progression of CKD. Additionally, the levels of baseline creatinine and C-reactive protein were elevated, while the levels of estimated glomerular filtration rate and hemoglobin decreased. Upon adjusting for demographic and biochemical variables, logistic regression analysis indicated that ln(SIRI) was independently associated with advanced CKD in pre-dialysis patients (OR=1.59, 95% CI: 1.29-1.95, P<0.001). Moreover, Cox proportional-hazard analysis revealed that ln(SIRI) independently predicted CKD progression (HR: 1.3, 95% CI: 1.07-1.59, P=0.009). Conducting a subgroup analysis, we observed significant interactions between ln(SIRI) levels and gender (p<0.001), age (p=0.046), and hypertension (p=0.028) in relation to the progression of CKD.

Conclusion

Our study's findings demonstrate a significant association between SIRI and fundamental renal function, and independently establish a correlation between SIRI and the progression of CKD in pre-dialysis patients. These observations suggest that SIRI holds promise as a potential predictor for CKD progression.

Contemporary laboratory assessment of acute cardiorenal syndrome for early diagnosis: A call for action

Acute cardiorenal syndrome (CRS), categorized as CRS type 1 and 3, is defined by the interplay of acute kidney injury or dysfunction and acute cardiac disease. For optimized diagnosis and management of CRS, strategies targeting multi-organ dysfunction must be adopted. Early diagnosis of acute CRS is important to enable timely initiation of appropriate treatment to prevent serious morbidity and mortality; however, traditional biomarkers are suboptimal. Over the past 2 decades, numerous biomarkers have been investigated for a better and more rapid diagnosis of CRS. Yet, the uptake of these contemporary biomarkers has been slow, possibly owing to the use of imperfect gold-standard reference tests. We believe that there is now scope for use of contemporary laboratory test panels to improve the diagnosis of acute CRS. In this review, we briefly discuss a proposed set of biomarkers for the diagnosis of type 1 and type 3 CRS.

Biomarker Rule-in or Rule-out in Patients With Acute Diseases for Validation of Acute Kidney Injury in the Emergency Department (BRAVA): A Multicenter Study Evaluating Urinary TIMP-2/IGFBP7

Background

Urine tissue inhibitor of metalloproteinases-2/insulin-like growth factor-binding protein 7 (TIMP-2/IGFBP7) (NephroCheck, Ortho Clinical Diagnostics, Raritan, NJ, USA) is a US Food and Drug Administration-approved biomarker for risk assessment of acute kidney injury (AKI) in critically ill adult patients in intensive care units; however, its clinical impact in the emergency department (ED) remains unproven. We evaluated the utility of NephroCheck for predicting AKI development and short-term mortality in the ED.

Methods

This was a prospective, observational, five-center international study. We consecutively enrolled ED patients admitted with ≥30% risk of AKI development (assessed by ED physician: ED score) or acute diseases. Serum creatinine was tested on ED arrival (T0), day 1, and day 2 (T48); urine for NephroCheck was collected at T0 and T48. We performed ROC curve and reclassification analyses.

Results

Among the 529 patients enrolled (213 females; median age, 65 years), AKI developed in 59 (11.2%) patients. The T0 NephroCheck value was higher in the AKI group than in the non-AKI group (median 0.77 vs. 0.29 (ng/m)2/1,000, P=0.001), and better predicted AKI development than the ED score (area under the curve [AUC], 0.64 vs. 0.53; P=0.04). In reclassification analyses, adding NephroCheck to the ED score improved the prediction of AKI development (P<0.05). The T0 NephroCheck value predicted 30-day mortality (AUC, 0.68; P<0.001).

Conclusions

NephroCheck can predict both AKI development and short-term mortality in at-risk ED patients. NephroCheck would be a useful biomarker for early ruling-in or ruling-out of AKI in the ED.

Real-Time Monitoring of Biomolecules: Dynamic Response Limits of Affinity-Based Sensors

Sensors for monitoring biomolecular dynamics in biological systems and biotechnological processes in real time, need to accurately and precisely reconstruct concentration–time profiles. This requirement becomes challenging when transport processes and biochemical kinetics are important, as is typically the case for biomarkers at low concentrations. Here, we present a comprehensive methodology to study the concentration–time profiles generated by affinity-based sensors that continuously interact with a biological system of interest. Simulations are performed for sensors with diffusion-based sampling (e.g., a sensor patch on the skin) and advection-based sampling (e.g., a sensor connected to a catheter). The simulations clarify how transport processes and molecular binding kinetics result in concentration gradients and time delays in the sensor system. Using these simulations, measured and true concentration–time profiles of insulin were compared as a function of sensor design parameters. The results lead to guidelines on how biomolecular monitoring sensors can be designed for optimal bioanalytical performance in terms of concentration and time properties.

Evaluation of clinical factors and three scoring systems for predicting mortality in perforated peptic ulcer patients, a retrospective study

Background/objective

Early identification of mortality risk in perforated peptic ulcer (PPU) patients is important for triage and risk stratification. This study aimed to compare clinical and laboratory factors and three scoring systems to predict mortality in PPU patients.

Methods

Retrospective data on PPU patients at M. Djamil Hospital who underwent emergency laparotomy repair surgery were collected from December 2018 to May 2021. The data included demographics, clinical characteristics, and three scoring systems. Data analysis used bivariate, multivariate, and ROC analysis.

Results

A total 72 patients were included and mortality rate was 52.8%. Bivariate analysis showed a significant association between age (p = 0.029), onset of illness (p = 0.001), alteration of consciousness (p = <0.001), respiratory rate (p = 0.04), duration of surgery (p = 0.040), preoperative shock (p = 0.049), preoperative creatinine (p = <0.001), Boey's scores (p = 0.002), ASA (p = 0.001), and qSOFA scores (p = <0.001) with mortality in PPU patients. From multivariate analysis, the strongest clinical factors associated with mortality were alteration of consciousness (p = <0.001) and preoperative creatinine (p = 0.001). Receiver Operating Characteristic (ROC) analysis showed the area under the curve (AUC) of Boey's Score 0.73, ASA classification 0.69, qSOFA score 0.77, alteration of consciousness 0.74, and preoperative creatinine 0.78.

Conclusion

Preoperative creatinine and altered consciousness had the strongest association with mortality in PPU patients. The qSOFA score predicted mortality better than Boey's score and ASA classification. Preoperative creatinine was the best single predictor of mortality.

AACC Guidance Document on Laboratory Investigation of Acute Kidney Injury

BACKGROUND

Acute kidney injury (AKI) is a sudden episode of kidney damage or failure affecting up to 15% of hospitalized patients and is associated with serious short- and long-term complications, mortality, and health care costs. Current practices to diagnose and stage AKI are variable and do not factor in our improved understanding of the biological and analytical variability of creatinine. In addition, the emergence of biomarkers, for example, cystatin C, insulin-like growth factor binding protein 7, and tissue inhibitor of metalloproteinases 2, and electronic notification tools for earlier detection of AKI, highlights the need for updated recommendations to address these developments.

CONTENT

This AACC Academy guidance document is intended to provide laboratorians and clinicians up-to-date information regarding current best practices for the laboratory investigation of AKI. Topics covered include: clinical indications for further investigating potential AKI, analytical considerations for creatinine assays, the impact of biological variability on diagnostic thresholds, defining "baseline" creatinine, role of traditional markers (urine sodium, fractional excretion of sodium, fractional excretion of urea, and blood urea-to-creatinine ratio), urinary microscopic examination, new biomarkers, improving AKI-associated test utilization, and the utility of automated AKI alerts.

SUMMARY

The previous decade brought us a significant number of new studies characterizing the performance of existing and new biomarkers, as well as potential new tools for early detection and notification of AKI. This guidance document is intended to inform clinicians and laboratorians on the best practices for the laboratory investigation of AKI, based on expert recommendations where the preponderance of evidence is available.

Clinical characteristics and prediction analysis of pediatric urinary tract infections caused by gram-positive bacteria

Gram-positive (GP) pathogens are less accounted for in pediatric urinary tract infection (UTI), and their clinical impact is underrecognized. This study aimed to identify predictors of GP uropathogens in pediatric UTI. In this 14-year retrospective cohort of pediatric patients with UTI, we classified first-time UTIs cases into those caused by GP or Gram-negative (GN) bacteria. We constructed a multivariable logistic regression model to predict GP UTI. We evaluated model performance through calibration and discrimination plots. We developed a nomogram to predict GP UTI that is clinically feasible. Of 3783 children with first-time UTI, 166 (4.4%) were infected by GP and 3617 (95.6%) by GN bacteria. Among children with GP UTI, the most common uropathogens were vancomycin-resistant Enterococcus faecalis (VRE) (27.1%), Staphylococcus saprophyticus (26.5%), and coagulase-negative Staphylococci (12.7%). Eight independent risk factors were associated with GP UTI: Age ≥ 24 months (odds ratio [OR]: 3.21), no prior antibiotic use (OR: 3.13), serum white blood cell (WBC) count < 14.4 × 103/μL (OR: 2.19), high sensitivity C-reactive protein (hsCRP) < 3.4 mg/dL (OR: 2.18), hemoglobin ≥ 11.3 g/dL (OR: 1.90), negative urine leukocyte esterase (OR: 3.19), negative urine nitrite (OR: 4.13), and urine WBC < 420/μL (OR: 2.37). The model exhibited good discrimination (C-statistic 0.879; 95% CI 0.845-0.913) and calibration performance. VR E. faecalis, the leading GP uropathogen causing pediatric UTI, requires early detection for infection control. Our model for predicting GP UTI can help clinicians detect GP uropathogens and administer antibiotic regimen early.

Twenty-four-hour serum creatinine variation is associated with poor outcome in the novel coronavirus disease 2019 (COVID-19) patients

Background

The prognostic value of within-day sCr variation serum creatinine variation is unknown in the setting of the novel coronavirus disease 2019 (COVID-19). We evaluated the prognostic significance of 24-hour serum creatinine variation in COVID-19 patients.

Methods

A monocentric retrospective analysis was conducted in COVID-19 patients not admitted to the intensive care unit. Three groups were subdivided based on 24 hours serum creatinine variation from admission. In the stable kidney function group, 24-hour serum creatinine variation ranged from +0.05 to –0.05 mg/dL; in the decreased kidney function group, 24-hour serum creatinine variation was >0.05 mg/dL; in the improved kidney function group, 24-hour serum creatinine variation was <–0.05 mg/dL.

Results

The study population included 224 patients with a median age of 66.5 years and a predominance of males (72.3%). Within 24 hours of admission, renal function remained stable in 37.1% of the subjects, whereas it displayed improved and deteriorated patterns in 45.5% and 17.4%, respectively. Patients with decreased kidney function were older and had more severe COVID-19 symptoms than patients with stable or improved kidney function. About half of patients with decreased kidney function developed an episode of acute kidney injury (AKI) during hospitalization. Decreased kidney function was significantly associated with AKI during hospitalization (hazard ratio [HR], 4.6; 95% confidence interval [CI], 1.9–10.8; p < 0.001) and was an independent risk factor for 30-day in-hospital mortality (HR, 5.5; 95% CI, 1.1–28; p = 0.037).

Conclusion

COVID-19 patients with decreased kidney function within 24 hours of admission were at high risk of AKI and 30-day in-hospital mortality.

Key Challenges in Providing Effective Antibiotic Therapy for Critically Ill Patients with Bacterial Sepsis and Septic Shock

Early initiation of effective antibiotic therapy is vitally important for saving the lives of critically ill patients with sepsis or septic shock. The susceptibility of the infecting pathogen and the ability of the selected dosage regimen to safely achieve the required antibiotic exposure need to be carefully considered to achieve a high probability of a successful outcome. Critically ill patients commonly experience substantial pathophysiological changes that impact the functions of various organs, including the kidneys. Many antibiotics are predominantly renally eliminated and thus renal function is a major determinant of the regimen needed to achieve the required antibiotic exposure. However, currently, there is a paucity of guidelines to inform antibiotic dosing in critically ill patients, including those with sepsis or septic shock. This paper briefly reviews methods that are commonly used in critically ill patients to provide a measure of renal function, and approaches that describe the relationship between the exposure to an antibiotic and its antibacterial effects. Two common conditions that very substantially complicate the use of antibiotics in critically ill patients with sepsis, unstable renal function, and augmented renal clearance, are considered in detail and their potential therapeutic implications are explored. Suggestions are provided on how treatment of bacterial infections in critically ill patients with sepsis might be improved. Of high potential are model-informed approaches that aim to individualize initial treatment regimens based on patient and bacterial characteristics, with refinement of regimens during treatment in response to monitoring antibiotic concentrations, responsive measures of renal function, and other important clinical data.