Urinary Tissue Inhibitor of Metalloproteinase-2 and Insulin-Like Growth Factor-Binding Protein 7 Enhanced Risk Prediction for Initiation of Renal Replacement Therapy in Postoperative Patients with Acute Kidney Injury: A Prospective Cohort Study

Huimiao Jia; Yue Zheng; Lifeng Huang; Wenxiong Li

doi:10.4103/JTCCM-D-22-00002

ORIGINAL ARTICLE

Year : 2022 | Volume : 4 | Issue : 1 | Page : 11

Urinary Tissue Inhibitor of Metalloproteinase-2 and Insulin-Like Growth Factor-Binding Protein 7 Enhanced Risk Prediction for Initiation of Renal Replacement Therapy in Postoperative Patients with Acute Kidney Injury: A Prospective Cohort Study

Huimiao Jia, Yue Zheng, Lifeng Huang, Wenxiong Li
Department of Surgical Intensive Care Unit, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China

Date of Submission	14-Jan-2022
Date of Acceptance	26-Apr-2022
Date of Web Publication	27-Jun-2022

Correspondence Address:
Dr. Wenxiong Li
Department of Surgical Intensive Care Unit, Beijing Chao-Yang Hospital, Capital Medical University, 8 Gongren Tiyuchang Nanlu, Chaoyang District, Beijing 100020
China

Source of Support: None, Conflict of Interest: None

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DOI: 10.4103/JTCCM-D-22-00002

Abstract

Introduction: The current study is to identify the performance of urinary tissue inhibitors of metalloproteinase-2 (TIMP-2) and insulin-like growth factor-binding protein 7 (IGFBP7) for predicting renal replacement therapy (RRT) initiation and mortality in postoperative acute kidney injury (AKI) patients. Methods: Postoperative AKI patients were prospectively and consecutively enrolled. The biomarkers of urinary TIMP-2 and IGFBP7 were detected at the time AKI diagnosed (day 0) and 24 h later (day 1). The primary endpoint was the initiation of RRT, and the secondary endpoint was 30-day mortality. The receiver operating characteristic (ROC) curve was used to assess the performance of biomarkers for the prediction of RRT requirement. Results: There were 220 AKI patients enrolled in this study. Among the 220 patients, 33 (15.0%) initiated RRT during intensive care units period. Urinary (TIMP-2) × (IGFBP7), TIMP-2 and IGFBP7 on day 1 had fair performance for predict RRT initiation, the predictive area under the ROC curve (AUC) were 0.792 (0.732, 0.843), 0.784 (0.724, 0.837), and 0.770 (0.709, 0.824), respectively, with no significant difference. When they combined with clinically independent risk factors (nonrenal sequential organ failure assessment score, duration of surgery procedure, and serum creatinine at the time of AKI diagnosed) to construct predictive models for predicting RRT. The AUCs were greatly improved to be good. The best AUC was achieved by TIMP-2, which was 0.866 (0.814, 0.908). All of the biomarkers performed poor predictive values for predicting 30-day mortality. Conclusion: Urine concentrations of (TIMP-2) × (IGFBP7), TIMP-2 alone, and IGFBP7 alone on AKI day 1 show fair value for prediction of RRT initiation. However, they fail to predict 30-day mortality.

Keywords: Acute kidney injury, insulin-like growth factor-binding protein 7, mortality, renal replacement therapy, tissue inhibitor of metalloproteinase-2

How to cite this article:
Jia H, Zheng Y, Huang L, Li W. Urinary Tissue Inhibitor of Metalloproteinase-2 and Insulin-Like Growth Factor-Binding Protein 7 Enhanced Risk Prediction for Initiation of Renal Replacement Therapy in Postoperative Patients with Acute Kidney Injury: A Prospective Cohort Study. J Transl Crit Care Med 2022;4:11

How to cite this URL:
Jia H, Zheng Y, Huang L, Li W. Urinary Tissue Inhibitor of Metalloproteinase-2 and Insulin-Like Growth Factor-Binding Protein 7 Enhanced Risk Prediction for Initiation of Renal Replacement Therapy in Postoperative Patients with Acute Kidney Injury: A Prospective Cohort Study. J Transl Crit Care Med [serial online] 2022 [cited 2023 Mar 29];4:11. Available from: http://www.tccmjournal.com/text.asp?2022/4/1/11/348365

Introduction

Acute kidney injury (AKI) remains a frequent disorder and commonly occurs in postoperative patients in intensive care units (ICUs).^[1],[2] AKI developing in severely ill patients significantly increases renal replacement therapy (RRT) requirement, dialysis dependence, short- and long-term mortality.^[3],[4],[5] Over 50% of AKI patients receiving RRT die.^[6] Many previous studies focused on early risk stratification for high-risk AKI patients.^[7],[8],[9] Despite considerable research efforts, no specific intervention has improved prognosis from severe AKI. Patients suffer from AKI with heterogeneous nature, and they need individualized treatment.^[7] If we can distinguish patients who may recover without interventions, and who are likely to require RRT in the early phase, effective therapy may be early implemented in these patients, which may improve their clinical outcomes. Detecting biomarkers alone or combing clinical risk factors with biomarkers in early phage of AKI may help to improve the therapy.^[4],[5],[9]

Urinary tissue inhibitors of metalloproteinase-2 (TIMP-2) and insulin-like growth factor-binding protein 7 (IGFBP7) are inducers of G1 cell cycle arrest. They are secreted by renal tubular cells as signals of acute kidney stress.^[10],[11] The urinary concentrations were detected to be significantly high in the early stage of kidney cell injury.^[12],[13] Renal tubular cells may adjust to enter G1 cell-cycle arrest to prevent cell division and apoptosis when inflammation or ischemia happened.^[14],[15] Kidney cells repair the injury during the period of G1 cell-cycle arrest subsequently.^{[15],[16],[17]} Urine concentrations greatly increase early before irreversible kidney damage occurs. Accumulating evidence found that urine (TIMP-2) × (IGFBP7) was strongly associated with AKI severity, and performed well in predicting AKI development, the need for RRT and mortality in patients at high risk of AKI.^{[10],[11], [12,[18]} Up to now, few studies evaluated the predictive value of urinary (TIMP-2) × (IGFBP7), TIMP-2 alone, and IGFBP7 alone for RRT requirement and mortality in early AKI patients. The current study was to identify the performance of urine (TIMP-2) × (IGFBP7) for predicting RRT initiation and mortality in postoperative AKI patients, which may provide available data of biomarker-guided decision-support for RRT initiation in AKI patients.

Methods

Study setting and population

Patients were screened in the surgical ICU of Beijing Chao-yang Hospital from July 1, 2018, to June 30, 2020. The Human Ethics Committee of Beijing Chao-Yang Hospital, Capital Medical University (Beijing, China) approved the study, ethics number was 2018-117. Written informed consent was obtained before patients were enrolled in this study.

The patients were all postoperative patients, and transferred to ICU soon after surgery. The inclusion criteria were patient diagnosed AKI within 72 h after ICU admission. The exclusion criteria included: (1) age <18 years; (2) chronic kidney disease (CKD); (3) death within 24 h after ICU admission; and (4) insufficient urine samples and data. All patients were prospectively and consecutively enrolled.

Biomarker measurements

Two investigators were appointed to collect urine samples. The urine samples were obtained from the urinary catheter at the time AKI diagnosed (day 0) and 24 h later (day 1), then they were centrifuged in a centrifuge and stored in -80°C refrigerator. NephroCheck™ Test was used to detect TIMP-2 and IGFBP7. The VITROS 5600 Integrated System (Astute Medical, San Diego, CA, USA) was used to analyze and report the product of the concentrations of (TIMP-2) and (IGFBP7). The biomarkers were measured by technicians who were blind to clinical data and physicians in charge were blind to the biomarker test results.

Clinical endpoints and definitions

The primary endpoint was the initiation of RRT during the ICU period in AKI patients. The secondary endpoint was 30-day mortality. The RRT was initiated according to the indications [[Table S1][Additional file 2] in Supplementary File].^[19] The diagnosis of AKI was dependent on the serum creatinine and urine output (UO) criteria proposed by Kidney Disease: Improving Global Outcomes (KDIGO). AKI severity was classified as mild (Stage 1), moderate (Stage 2), or severe (Stage 3), based on the changes in serum creatinine or UO according to the KDIGO guidelines at the time of AKI diagnosis.^[2],[20]

Data collection

Clinical patient characteristics were collected from electronic information form, including age, sex, comorbidities (hypertension, diabetes mellitus, chronic obstructive pulmonary disease/asthma, cardiovascular disease, chronic liver disease), whether the use of norepinephrine, diuresis, and nephrotoxic drugs (angiotensin-converting enzyme inhibitors, nonsteroidal anti-inflammatory drug, amikacin or amphotericin B). Information for the operation was recorded, including duration of surgery, bleeding, and blood product transfusion. Serum creatinine was assessed and recorded at ICU admission and every 12 h thereafter until patients were transferred out of ICU. UO was measured hourly from the urinary catheter during the ICU period. Acute physiology and chronic health evaluation (APACHE II) and sequential organ failure assessment (SOFA) scores were recorded on the day of AKI diagnosis.

Statistical analysis

Mean ± standard deviation or median values (25^th and 75^th percentiles) described continuous variables; percentiles described categorical variables. Univariate logistic regression analysis was used to find the potential clinical risk factors for RRT initiation. Variables with P < 0.1 were included in multivariate logistic regression analysis to identify the independent risk factors for RRT initiation. The receiver operating characteristic (ROC) curve was used to test the predictive performance of biomarkers and predictive models in the combination of biomarker and independent risk factors for RRT initiation.^[9] The following values of 0.90–1.0 excellent, 0.80–0.89 good, 0.70–0.79 fair, 0.60–0.69 poor, and 0.50–0.59 no fair performance were used to describe the area under the ROC curves (AUCs).^[10] The predictive models were constructed using multivariate logistic regression models. DeLong's test was used to compare AUCs. Youden's index was used to determine the optimal cutoff for calculations of specificity, sensitivity, and positive and negative likelihood ratio. Their corresponding 95% confidence intervals (CI) were recorded together. SPSS statistics 24.0 (IBM, Chicago, IL, USA) calculated all statistical analyses. For all analyses, statistical significance was indicated by two-sided P < 0.05.

Results

Patient characteristics

There were 239 AKI patients included in this study. After excluding eight patients with CKD patients, and 11 patients with insufficient urine samples and data, 220 patients were finally enrolled. Among them, 137 (62.3%) patients suffered from mild AKI, and 83 (37.7%) suffered from moderate-to-severe AKI. 33 of 220 (15%) patients initiated RRT during the ICU period, and 187 (85%) did not use RRT after AKI development. [Figure 1] shows the flow diagram of the study. The indications of 33 patients for initiating RRT are shown in [[Table S2] Supplementary File][Additional file 3].

Figure 1: Study flow diagram. AKI: Acute kidney injury, RRT: Renal replacement therapy

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Patients were divided into a group of RRT and group without RRT. The time from diagnosis of AKI to initiation of RRT was 49.5 (32.0–67.5) h. No patients initiated RRT within 24 h. The variables of age, gender, body max index, and comorbidities showed no significant difference between the two groups. However, patients in the RRT group had higher APACHE II scores and nonrenal SOFA scores than patients without RRT. Further, patients who initiated RRT showed more severe kidney injury at inclusion with a higher proportion of moderate-to-severe AKI compared with patients without RRT. The baseline creatinine showed no statistical difference between these two groups, but serum creatinine and UO at the time AKI diagnosed had a great difference. The duration of surgery, fluid balance, and transfusion of red blood cells during surgery also showed great differences. Moreover, more patients in the RRT group use vasoactive drugs than the group without RRT. Duration of hospital stay was 20 (16.5–39.0) days in the RRT group, which was longer than non-RRT patients (15 [10.6–24.5] days, P = 0.003). Moreover, 30-day mortality was higher in RRT group than non-RRT patients (12/33 [36.3%] vs. 34/187 [18.2%], P < 0.001). Patient characteristics are presented in [Table 1].

Table 1: Patient characteristics

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Biomarkers for prediction of renal replacement therapy during intensive care units period

Urine (TIMP-2) × (IGFBP7), TIMP-2 alone and IGFBP7 alone were detected on day 0 and day 1. All of the biomarker concentrations of urine (TIMP-2) × (IGFBP7), TIMP-2 alone and IGFBP7 alone on day 0 and day 1 showed significantly higher in the RRT group than the group without RRT. The comparisons are presented in [Table 1].

Urinary concentration of (TIMP-2) × (IGFBP7), TIMP-2 and IGFBP7 on day 1 had a fair performance for predicting RRT initiation during the ICU period. The predictive AUC were 0.792 (0.732, 0.843), 0.784 (0.724, 0.837), and 0.770 (0.709, 0.824), respectively. DeLong test compared the AUCs, and showed there was no statistical difference among the three AUCs. Accordingly, the optimal cutoff value and corresponding sensitivity and specificity were calculated. The predictive accuracy of the biomarkers for early prediction of initiation of RRT during the ICU period is presented in [Table 2].

Table 2: Predictive accuracy of the biomarkers for early prediction of initiation of renal replacement therapy during intensive care units period

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Combination of biomarkers with clinical data for prediction of renal replacement therapy initiation

Nonrenal SOFA score, duration of surgery procedure, and serum creatinine at the time of AKI diagnosis were independent risk factors for the use of RRT during the ICU period. The clinical model combining nonrenal SOFA score, duration of surgery procedure, and serum creatinine at the time of AKI diagnosis was constructed to predict RRT initiation after AKI development. The result showed that the predictive AUC was 0.790 (0.731, 0.843). When adding biomarkers on AKI day 1 to the model, the AUCs were greatly improved to be good. The AUC of the clinical model combining with (TIMP-2) × (IGFBP7) improved to 0.857 (0.799, 0.897), with a sensitivity of 75.7% (57.7, 88.9), and a specificity of 86.0% (80.2, 90.7), AUC of the clinical model combining with TIMP-2 was 0.866 (0.814, 0.908), with a sensitivity of 78.8% (61.1, 91.0), and a specificity of 81.2% (74.8, 86.5), AUC of the clinical model combining with IGFBP7 was 0.852 (0.761, 0.887), with a sensitivity of 72.7% (54.5, 86.7), and a specificity of 91.4% (86.4, 95.0). These three AUCs showed no significant difference. Whereas, the biomarkers on AKI day 0 did not perform good predictive values. The predictive performances of the biomarkers and combination models are shown in [Table 2] and [Figure 2].{Table 2}

Figure 2: The predictive value of biomarker and the corresponding models. (a) The AUCs of urine (TIMP-2) × (IGFBP7) and TIMP-2 alone on AKI day 1 for predicting RRT initiation. (b) The AUCs of (TIMP-2) × (IGFBP7) and TIMP-2 combined with clinical risk factors for predicting RRT initiation. RRT: Renal replacement therapy, AUC: Area under the receiver operating characteristic curve, TIMP-2: Tissue inhibitor of metalloproteinases-2, IGFBP7: Insulin-like growth factor-binding protein 7

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Biomarker performances in the prediction of 30-day mortality

The values for predicting 30-day mortality of urine TIMP-2, IGFBP7, and (TIMP-2) × (IGFBP7) were evaluated on day 0 and day 1 in AKI patients. The results showed that all of the biomarkers performed poor predictive capacity for predicting 30-day mortality. The performances of biomarkers for the prediction of 30-day mortality are presented in [Table 3].

Table 3: The performances of biomarkers for prediction of 30-days mortality

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Discussion

AKI is still a common disorder in critically ill patients with high mortality, especially in postoperative patients.^{[21],[22],[23]} AKI patients who used RRT are more likely to progress to CKD, RRT dependence, or other adverse clinical outcomes.^[24],[25] If we could early recognize the patients who really need RRT after AKI, effective therapy would be early applied, which may reverse the impaired renal function and improve the clinical outcomes. Moreover that the biomarkers had potential value for predicting RRT requirement in the AKI patients.^[6] In the current study, the main findings were: (1) all of day 1 urine concentrations of [TIMP-2] × [IGFBP7], TIMP-2 alone, and IGFBP7 alone showed fair predictive performances, and expressed better AUC values than corresponding urine concentrations on day 0; (2) The predictive model combining clinical factors of the nonrenal SOFA score, duration of surgery procedure, and serum creatinine at the time of AKI diagnosis also performed fair value for prediction of RRT initiation. When adding the biomarkers on day 1 to the model, the predictive performance improved to be good; (3) None of urine (TIMP-2) × (IGFBP7), TIMP-2 and IGFBP7 on day 0, and day 1 had fair predictive values for 30-day mortality.

Urinary biomarkers are considered sensitive biomarkers for AKI diagnosis and RRT initiation, because damage manifests in renal tubular cells in early phage of AKI. A previously published meta-analysis showed a fair performance of urinary NGAL for the prediction of RRT with a pooled AUC of 0.782 (0.648–0.917). However, it showed a very heterogeneous performance in different population.^{[6],[26],[27]} Cystatin C is considered a marker for reflecting glomerular filtration rate in kidney injury, and it could earlier diagnose AKI than creatinine. Serum cystatin C showed a pooled AUC of 0.759 (0.717–0.800) for the prediction of RRT.^[6],[28] Although single biomarker tests may add incremental support to guide clinical decision-making, it is demonstrated to perform better when biomarkers combined with clinical parameters. Urine (TIMP-2) × (IGFBP7) was considered to be a potential biomarker of clinical applicability to help clinicians well manage AKI patients, and improve the clinical outcomes. The study by Kashani et al. found that urine (TIMP-2) × (IGFBP7) was superior to other 340 candidate biomarkers in prediction for AKI.^[18] Subsequently, there were some studies explore the ability of (TIMP-2) × (IGFBP7) for the prediction of persistent AKI, renal recovery, RRT initiation, and mortality. A systematic review and meta-analysis reported biomarkers for the prediction of RRT, which analyzed the power of (TIMP-2) × (IGFBP7) for predicting RRT initiation in four studies and 280 high-risk patients before AKI occurrence.^[6] Except for one trial, (TIMP-2) × (IGFBP7) showed a good predictive performance with individual AUCs well above 0.8 for prediction of initiation of RRT, with pooled AUC of 0.857 (0.789–0.925) for confirming the predictive value. The study further found in patients with sepsis-induced AKI, TIMP-2 performed slightly better than IGFBP-7, whereas IGFBP-7 outperformed TIMP-2 in surgical patients.

Different from the previous studies, our study focused on AKI patients and detected urinary TIMP-2 and IGFBP7 on AKI day 0 and day 1 to evaluated the predictive power of (TIMP-2) × (IGFBP7), TIMP-2 alone, and IGFBP7 alone for the initiation of RRT and mortality. The result found whether TIMP-2 and IGFBP7 alone, or their combination could well predict the use of RRT. Further, the study showed biomarker levels on day 1 performed better predictive values than biomarker levels on day 0. The biomarkers reflected kidney injury. Our previous study showed more severe injury had higher biomarker levels.^[29] Further, this study showed (TIMP-2) × (IGFBP7), TIMP-2, and IGFBP7 on day 1 were significantly higher than their levels on day 0 in the RRT group, respectively [Supplementary file, [Figure S1]][Additional file 1]. Therefore, with the aggravation of kidney injury, higher biomarker levels on day 1 are more likely to evaluate whether RRT would be initiated. Both of the two biomarkers are cell cycle arrest factors. The AUC of (TIMP-2) × (IGFBP7), TIMP-2, and IGFBP7 on day 1 for predicting RRT initiation showed no statistical difference. Hence, maybe we could only detect one biomarker of TIMP-2 or IGFBP7 instead of both TIMP-2 and IGFBP7 in predicting events. Further studies are needed to confirm this thought.

Our study had some limitations. First, this was a single study with a small sample size; further studies are warranted confirming the predictive value of urine TIMP-2, IGFBP7, and (TIMP-2) × (IGFBP7) for RRT requirement and mortality. Second, patients with CKD were excluded. The prognosis of CKD is different from AKI, with a normal baseline creatinine. AKI patients developing from CKD should be analyzed separately. Third, we only evaluated the short-term prognosis; additional studies should be needed to evaluate biomarkers on long-term outcomes in the AKI patients.

Conclusion

Urine concentrations of (TIMP-2) × (IGFBP7), TIMP-2 alone, and IGFBP7 alone on AKI day 1 showed fair value for the prediction of RRT initiation in ICU. When adding the biomarkers on day 1 to the clinical predictive model, including nonrenal SOFA score, duration of surgery procedure, and serum creatinine at the time of AKI diagnosis, the predictive performance improved to be good. However, they failed to predict 30-day mortality.

Ethics approval and consent to participate

The Human Ethics Committee of Beijing Chao-Yang Hospital, Capital Medical University (Beijing, China) approved the study. Ethics number was 2018-117. Written informed consent was obtained before patients were enrolled in this study.

Financial support and sponsorship

This study was supported by Beijing Municipal Science and Technology Commission (No. Z191100006619032; No. Z181100001718204).

Conflicts of interest

There are no conflicts of interest.

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