Combining Renal Cell Arrest And Damage Biomarkers To Predict Progressive AKI in Patient With Sepsis
Mar 19, 2022
Background Acute kidney injury (AKI) is a common complication in patients admitted to the intensive care unit (ICU), especially in those with sepsis [1]. Sepsis-associated AKI accounts for approximately half of all AKI in ICU, which is associated with a significantly increased risk for in-hospital death. Moreover, septic AKI is also associated with an increased risk of later chronic kidney disease and end-stage kidney disease [2]. AKI occurred in about 45-53% of patients with sepsis, and most septic AKI was mild or moderate AKI (KDIGO stage 1 or stage 2) [3, 4]. However, a previous study showed that up to 40% of these mild or moderate AKI would progress to more severe AKI (KDIGO stage 3), of which 30% required dialysis and the risk of death increased by 3-fold, as high as 70% [5]. Therefore, early identifying patients at high risk for progressive AKI might help clinicians to enhance individualized monitoring and personalized management in patients with septic AKI, which might prevent or halt the ongoing renal injury and improve the outcome of patients with sepsis.
CISTANCHE WILL IMPROVE KIDNEY/RENAL FUNCTION
Recently, there has been rising interest in searching and validating new biomarkers for early predicting AKI development and prognosis in different clinical settings. Renal cell cycle arrest biomarkers, urinary tissue inhibitor of metalloproteinases-2 (TIMP-2), and insulin-like growth factor binding protein-7 (IGFBP-7), have been shown to efficiently predict the risk of severe AKI development in ICU and were approved by U.S. FDA as a test of determining the risk of AKI development [6, 7]. It has been reported that renal tubular cells may produce and release TIMP-2 and IGFBP7 when exposed to cellular stress or injury, and may help renal cells maintain energy balance, prevent further DNA damage and division [7, 8]. But sustained renal cell cycle arrest will result in a senescent cell phenotype and lead to progressive injury [9]. A recent study reported that urinary [TIMP-2]*[IGFBP7] concentration at the early phase of septic shock was an independent factor to identify the population at high risk of progression from mild and moderate to severe AKI over the next 24h with an AUC of 0.83 [5]. In addition, there were other novel renal injury biomarkers, such as kidney injury molecular-1 (KIM-1) and interleukin-18 (IL-18), which refecting renal tubular damage and inflammation of AKI, also shown to predict the progression of AKI in the setting of ICU and cardiac surgery, and presented modest performance [10, 11]. To further improve the ability of biomarkers for predicting AKI progression in sepsis, carefully selecting and combining biomarkers might be a better approach for greater use. Compared with other AKI etiologies, septic AKI was thought to be associated with multi-mechanisms, such as renal microcirculation disorder, renal cell cycle stress, tubular injury, and inflammation [1, 7, 12]. Combining renal cell arrest biomarkers with renal injury/inflammation biomarkers to predict the progression of septic AKI was not addressed before, and whether combining renal cell arrest and damage biomarkers could improve risk classification for progressive AKI in sepsis warrants further investigation. We conducted a prospective, multicenter cohort study that included 149 adult septic patients who initially developed stage 1 or stage 2 AKI during ICU stay. Levels of novel urinary biomarkers ([TIMP-2]*[IGFBP7], KIM- 1, and IL-18) were measured at the time of AKI clinical diagnosis, and the utility of biomarkers for predicting septic AKI progression in combination was evaluated. Furthermore, the risk classification improvement of combining these biomarkers for predicting progressive septic AKI was investigated.
Keywords: Sepsis, AKI, Progression, Risk prediction, Biomarker, Renal, Kidney
Methods
Study design and study population We prospectively screened adult (age≥18years) patients who were admitted to the ICU in two academic teaching hospitals in China from January 2014 to March 2018. Eligible participants were patients who were admitted with sepsis and initially developed stage 1 or 2 AKI on admission or during hospitalization. The value of serum creatinine over a 6-month period before admission was used as a baseline. Exclusion criteria included preexisting advanced CKD (baseline eGFR<30ml/min per 1.73m2 ) and a life expectancy less than 24h. Patients with stage 3 AKI could not progress further and were excluded from analysis (Fig. S1). AKI was diagnosed according to the Kidney Disease Improving Global Outcomes (KDIGO) Clinical Practice Guidelines for AKI based on serum creatinine criteria [13]. Not all patients in this study had precise records of urine output per hour, and we only used serum creatinine for AKI diagnosis and stages. Serum creatinine was measured once to twice per day to precisely define AKI and determine AKI progression. Sepsis was defined according to Te Third International Consensus Definitions for Sepsis and Septic Shock [14]. This study was approved by the Institutional Review Board of the National Clinical Research Center for Kidney Disease and the Research Ethics Committee of Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences. This study was carried out in accordance with the code of ethics of the World Medical Association Declaration of Helsinki, and patients or the next of kin of the patients were informed and gave written informed consent.
CISTANCHE WILL IMPROVE KIDNEY/RENAL DISEASE
Procedures All septic patients were treated according to Surviving Sepsis Campaign guidelines for the management of severe sepsis and septic shock. Spot urine samples were collected daily for the first 14days during hospitalization. Urine samples on the day of AKI clinical diagnosis were used for biomarker measuring. Urine samples were centrifuged at 3000rpm for 10min and the supernatants were stored at −80°C. Serum creatinine was measured on admission and twice a day during the first 5days and at least daily thereafter. Clinical data for the study were collected from the hospital records, such as demographic, medication on admission, baseline renal function, Acute Physiology, and Chronic Health Evaluation II (APACHE II) scores, Sequential Organ Failure Assessment (SOFA) scores, Multiple Organ Dysfunction Syndrome (MODS) scores, hemoglobin, blood urea nitrogen, serum albumin, blood lactate, and procalcitonin. There was not any use of special membranes or cartridges in septic patients who received acute dialysis.
Laboratory measurements All biomarkers were measured in our central laboratory by standard protocols in a technician-blinded manner. Te levels of renal cell arrest biomarkers, urinary TIMP- 2*IGFBP7 (u[TIMP-2]*[IGFBP7]), were measured by ELISA kits (TIMP-2: DTM200, R&D Systems; IGFBP7: DY1334-05, R&D Systems) according to the manufacturer’s instructions. Te levels of renal cell injury and inflammation biomarkers, urinary KIM-1 (uKIM-1), and urinary IL-18 (uIL-18), were measured by ELISA kits (KIM-1: DY1750B, R&D Systems; IL-18: ELH-IL18, RayBiotech) on the manufacturer’s instructions. All biomarkers were measured in triplicate and the intra- and inter-assay variability ranged 2–6% and 5–9%. Urinary albumin was quantified by an automatic analyzer and expressed as the ratio to urinary creatinine (UACR). All urinary biomarkers were normalized to urinary creatinine. Baseline eGFR was estimated by the CKD-Epidemiology Collaboration Eq. [15]. Levels of biomarkers measured on the day of initial AKI clinical diagnosis were used for all analyses.
Outcome Definitions As previously reported [16, 17], the primary outcome was the progression of AKI, defined as worsening of the KDIGO stage (from stage 1 to either stage 2 or stage 3, or from stage 2 to stage 3). Patients treated with acute dialysis at any point during hospitalization were defined as stage 3. The secondary outcome was AKI progression with death. Patients who died without AKI progression were excluded from the primary analysis because the death may have been a competing risk for progression for these patients as previously reported [16, 17].
Statistical analyses We used the two-sample t-test or the Mann-Whitney U test to compare continuous variables; and used the chi-squared/ Fisher exact test and categorical variables, respectively. All tests were two-tailed and P<0.05 was considered signifcant. To evaluate the performance of u[TIMP-2]*[IGFBP7] for predicting septic AKI progression, in single or in combination with renal damage biomarkers or clinical risk factors, we used the conventional area under the receiver-operating characteristic (ROC) curve (AUC). We employed Logistic regression models to calculate the AUCs of urinary biomarkers in all analyses. To evaluate the utility of renal arrest and damage biomarkers on risk classification, we determined the category-free net reclassification improvement (NRI) and the integrated discrimination improvement (IDI), as previously described [18, 19].
CISTANCHE WILL IMPROVE KIDNEY/RENAL FAILURE
Results
Cohort characteristics A total of 433 patients admitted with sepsis in two hospitals were screened, and finally, 149 patients with sepsis and stage 1 or 2 AKI were included for analysis (Fig. S1). Among 149 septic patients with AKI,79(53.0%)developed AKI on admission and 70 (47.0%) during hospitalization. Among 149 patients with stage 1 or 2 AKI,63 patients (42.3%)progressed to a higher stage of AKI during their hospitalization (32 individuals progressed to stage 2 and 31 progressed to stage 3);23 of 63 (36.5%)progressors received acute dialysis; 45 of 63(71.4%) developed AKI progression and subsequently died during hospitalization;86patients (57.7%)persisted in stage 1 or2AKL The characteristics of 149 septic patients with or without AKI progression were showed in Table 1. Compared to those with AKI that did not progress, patients with AKI progression had a lower proportion of males, more usage of nephrotoxic antibiotics before AKI diagnosis. AKI progressors had higher scores of illness severity, such as the APACHE II, SOFA, and MODS scores(Table 1). There was no statistical difference in age, baseline renal function, serum albumin, levels of blood lactate and procalcitonin, and proportion of morbidities (hypertension, diabetes, and pre-CKD)on admission between patients with or without AKI progression.
Table 2 compared the characteristics at the time of AKI diagnosis and the in-hospital outcomes between patients with or without AKI progression. Patients with AKI progression had higher serum creatinine levels on the day of AKI diagnosis and a greater increase of serum creatinine levels from the baseline at the time of AKI diagnosis. Lev-els of renal cell arrest biomarker (u[TIMP-2]*[IGFBP7)and damage biomarkers (uKIM-1 and IL-18)were significantly higher in patients with AKI progression as compared to those without. Patients with AKI progression had more adverse outcomes, such as receiving acute dialysis and in-hospital death, as compared with those without AKI progression (Table 2).In patients with AKI progression, the average timing from AKI initial diagnosis to serum creatinine peak was 2 days.
Performance of combining u[TIMP‑2]*[IGFBP7] and renal damage biomarkers for predicting progressive AKI in Sepsis Compared to those without AKI progression, patients with progressive AKI had significantly increased levels of u[TIMP-2]*[IGFBP7], uKIM-1, and until-18 at time of AKI clinical diagnosis (Table 2). As shown in Supplemental Table S1, u[TIMP-2]*[IGFBP7], uKIM-1 and until-18 predicted the progression of AKI in sepsis, with u[TIMP- 2]*[IGFBP7] presented the greatest AUC (0.745, 95%CI 0.667-0.823) as compared to uKIM-1 (AUC 0.719, 95%CI 0.638-0.800) and rule-18 (AUC 0.619, 95%CI 0.525-0.713). For predicting AKI progression with death, u[TIMP- 2]*[IGFBP7] also showed the greatest AUC (0.777, 95%CI 0.700-0.854) as compared to uKIM-1 (AUC 0.738, 95%CI 0.653-0.822), and uIL-18 (AUC 0.657, 95%CI 0.557- 0.758) (Supplemental Table S1). Combining renal cell arrest biomarker (u[TIMP- 2]*[IGFBP7]) with renal damage biomarkers (uKIM-1 and uIL-18) improved the performance for predicting AKI progression, with AUCs of 0.752 for u[TIMP-2]*[IGFBP7] with uKIM-1, and 0.747 for u[TIMP-2]*[IGFBP7] with uIL-18, respectively (Table 3). For predicting AKI progression with death, combining u[TIMP-2]*[IGFBP7]
with uKIM-1 produced an increased AUC of 0.782, as compared to u[TIMP-2]*[IGFBP7] alone. However, combining u[TIMP-2]*[IGFBP7] with uIL-18 could not improve the performance for predicting AKI progression with death as compared to u[TIMP-2]*[IGFBP7] alone. Combining u[TIMP-2]*[IGFBP7] with UACR could not further improve the performance both for predicting AKI progression or AKI progression with death in sepsis (Table 3).
Performance of combining u[TIMP‑2]*[IGFBP7] with clinical risk factors for predicting progressive AKI in Sepsis Combining u[TIMP-2]*[IGFBP7] with clinical risk factors, such as APACHE II and SOFA score, serum creatinine and Cys-C at time of AKI diagnosis, improved the performance for predicting septic AKI progression and AKI progression with death (Table 4). The clinical risk factor model comprised of age, gender, APACHE II, serum creatinine, and albuminuria at the time of diagnosis predicted the primary and secondary outcomes with AUCs of 0.746 (95%CI, 0.668-0.823) and 0.779 (95%CI, 0.702-0.855), respectively (Figs. 1 and 2). Combining u[TIMP-2]*[IGFBP7] with the clinical risk factor model further improved the AUCs to 0.797 (95%CI, 0.726- 0.867) and 0.845 (95%CI, 0.780-0.910) as compared to the clinical model alone both for predicting AKI progression or AKI progression with death. When combining both u[TIMP-2]*[IGFBP7] and uKIM-1 with the clinical model, the predicting performance further improved, with AUCs of 0.806 (95%CI, 0.738-0.874) and 0.846 (95%CI, 0.780-0.910) for the primary and secondary outcomes (Table 4 and Fig. 1). However, a combination of u[TIMP-2]*[IGFBP7] and uIL-18 only improved the performance for the secondary outcome (Fig. 2).
Risk classification improvement of combining u[TIMP‑2]*[IGFBP7] with renal damage biomarker or clinical risk factors As shown in Table S2, adding u[TIMP-2]*[IGFBP7] to the clinical risk factor model resulted in the greatest improvement in risk reclassification both for the primary and the secondary outcomes, with a category-free net reclassification index (NRI) of 0.63 and 0.59 for AKI progression and AKI progression with death. Adding u[TIMP-2]*[IGFBP7] and uKIM-1 to the clinical risk factor model further improved risk classification over the clinical model alone, both for AKI progression and AKI progression with category-free NRI of 0.61 and 0.67, respectively (Table S2).
Discussion In this perspective, multicenter cohort study of adult patients with sepsis, we firstly showed that combining renal cell arrest biomarker and renal injury biomarkers could enhance the ability of biomarkers for predicting the progression of septic AKI. u[TIMP-2]*[IGFBP7], measured at the time of AKI diagnosis, predicted both AKI progression and AKI progression with death in the setting of sepsis. Compared to u[TIMP-2]*[IGFBP7] alone, a combination of u[TIMP-2]*[IGFBP7] with uKIM-1 slightly improved the performance for predicting both above outcomes, with AUC increased from 0.745 to 0.752 for AKI progression and from 0.777 to 0.782 for AKI progression with death. Moreover, we first showed that adding u[TIMP-2]*[IGFBP7] to the clinical risk factor model, alone or combined with renal injury biomarkers, significantly improved the risk classification of AKI progression and AKI progression with death in sepsis, as evidenced by signifcant NRI and IDI.
Sepsis was the most common trigger for AKI, septic patients were at the highest risk for developing AKI with an incidence ranging 22 -51% according to current KDIGO 2012 criteria [1, 20, 21]. Patients who developed mild or moderate AKI and subsequently progressed to severe AKI had the highest risk for death [7]. In our cohort, nearly 80% of sepsis patients with progressive AKI died during hospitalization, consistent with previous reports. Therefore, using novel biomarkers to enhance the risk classification of AKI progression upon clinical risk factors might help clinicians initiate close patient monitoring and plan appropriate management, which in turn might reduce the risk of death of these patients based on the above additional prognostic information. Previous studies have shown that renal arrest biomarkers, u[TIMP-2]*[IGFBP7], predicted the progression of AKI in the setting of ICU and septic shock [5, 22–24]. Other novel renal injury or inflammation biomarkers, such as KIM-1, IL18, were also shown to predict progressive septic AKI [24–26], respectively. In this prospective study in patients with sepsis, we further directly compared the predictive performance of u[TIMP-2]*[IGFBP7] with the other novel injury/inflammation biomarkers in single or combination. Our results showed that combining u[TIMP-2]*[IGFBP7] with uKIM-1 could further improve the prediction of septic AKI progression compared to single biomarker prediction, which was also true for predicting AKI progression with death, suggesting that carefully selecting and combining biomarkers might be a better approach for greater application. Biomarkers
of different types provide relevant information that improves their application and predictive value. Albuminuria and serum creatinine are traditional markers of kidney injury. However, these existing markers had less sensitivity and specificity and were not sufficient for determining the risk of AKI progression [26–29]. Therefore, adding novel biomarkers to the clinical risk factor model which includes albuminuria and serum creatinine would be a new way to increase risk assessment and stratification for AKI progression.
Te NRI denoted an improvement in reclassification as any increase in model-based predicted probabilities after the addition of the biomarker for events (AKI progression) and a decrease in probabilities for nonevents, and large effect sizes had an NRI greater than 0.6 [30]. The results of our study have shown that adding u[TIMP-2]*[IGFBP7] to the clinical risk factor model could significantly improve risk classification for AKI progression alone or in combination with uKIM-1, with NRIs of 0.63 and 0.61 respectively. And this was also true for risk classification for the secondary outcome, i.e. AKI progression with death, with NRIs of 0.59 and 0.67. u[TIMP-2]*[IGFBP7], measured at the time of septic AKI diagnosis, could not only be used as a tool assessing the risk of AKI progression in sepsis but also provided additional prognostic information in hospital, such as subsequent death after AKI. Interestingly, combining u[TIMP-2]*[IGFBP7] with uKIM-1 and uIL-18 together could not significantly improve the prediction of septic AKI progression as compared to u[TIMP-2]*[IGFBP7] with uKIM-1 combination. Whether this funding is due to the modest ability of uIL-18 in unclear; however, it suggests that efficiently selecting and combining biomarkers for a multi-biomarker approach, prediction needs more investigation. Furthermore, larger studies are warranted to explore the role of biomarkers in clinical practice, in order to entail advances in the management of septic patients and improve their outcomes.
Strengths and limitations Our study has the following strength. First, this was a multicenter, prospective cohort study. AKI and sepsis were diagnosed based on standardized criteria (KDIGO 2012 and sepsis-3) that are currently used in the international renal and critical care community. Second, we simultaneously measured well-reported renal cell arrest biomarker and renal damage biomarkers and assessed the predictive performance and risk classification alone or combination with clinical risk factors in the setting of sepsis, which directly compared the predictive ability of biomarkers alone or in combination. This study also had limitations. Urinary creatinine excretion is not at a steady state during AKI; 24h urinary excretion of biomarkers would be more meaningful. The number of primary outcomes was relatively small, and all patients were Chinese adults. Tough this study showed an improvement of combining renal cell arrest and damage biomarkers to predict progressive AKI in patients with sepsis, terms of cost-effectiveness, ease of the tests, and time-consuming needed to be evaluated in a larger size patient population.
Conclusions The combination of renal arrest and damage biomarkers enhanced the prediction of AKI progression in patients with sepsis and improved risk reclassification over the clinical risk factor model alone. As this study was conducted in a pure sepsis population of ICU patients, our findings might have useful clinical implications for sepsis adults at risk for AKI progression.
