Attributable mortality of ARDS among critically ill patients with sepsis: a multicenter, retrospective cohort study.

BACKGROUND: Both sepsis and acute respiratory distress syndrome (ARDS) are common severe diseases in the intensive care unit (ICU). There is no large-scale multicenter study to clarify the attributable mortality of ARDS among septic patients. This study aimed to evaluate the excess mortality of ARDS in critically ill patients with sepsis. METHODS: The data were obtained from a multicenter, prospective cohort study in 18 Chinese ICUs between January 2014 and August 2015. The study population was septic patients after ICU admission. The patients were categorized into two groups: those who developed ARDS (ARDS group) within seven days following a sepsis diagnosis and those who did not develop ARDS (non-ARDS group). Applying propensity score matching (PSM), patients were matched 1:1 as ARDS and non-ARDS groups. Mortality attributed to ARDS was calculated. Subsequently, we conducted a survival analysis to estimate the impact of ARDS on mortality. The primary endpoint was 30-day mortality after sepsis diagnosis. RESULTS: 2323 septic patients were eligible, 67.8% developed ARDS. After PSM, 737 patients with ARDS were matched 1:1 with 737 non-ARDS patients. ARDS's overall 30-day attributable mortality was 11.9% (95% CI 7.5-16.3%, p < 0.001). Subgroup analysis showed that the 30-day attributable mortality of mild, moderate, and severe ARDS was 10.5% (95% CI 4.0-16.8%, p < 0.001), 11.6% (95% CI 4.7-18.4%, p < 0.001) and 18.1% (95% CI 4.5-30.9%, p = 0.006), respectively. ARDS was an independent risk factor for 30-day mortality, with adjusted hazard ratios of 1.30 (95% CI 1.03-1.64, p = 0.027), 1.49 (95% CI 1.20-1.85, p < 0.001), and 1.95 (95% CI 1.51-2.52, p < 0.001) for mild, moderate, and severe ARDS, respectively. CONCLUSIONS: The overall 30-day attributable mortality of ARDS among critically ill patients with sepsis was 11.9%. Compared with mild and moderate ARDS, severe ARDS contributed more to death. ARDS was significantly associated with an increase in the 30-day mortality.

Association between the levels of urinary cell cycle biomarkers and non-recovery of renal function among critically ill geriatric patients with acute kidney injury.

The lack of early renal function recovery among geriatric patients with acute kidney injury (AKI) in the intensive care unit (ICU) is a commonly observed and acknowledged poor prognostic factor, especially for older adults. However, no reliable prognostic biomarker is available for identifying individuals at risk of renal non-recovery or mortality in older adults. In this prospective observational cohort study, we enrolled critically ill older adults (aged ≥ 60 years) with AKI from the ICU and followed their disease progression. The primary endpoint was renal non-recovery within seven days of follow-up, while the secondary endpoint was the determinants of 30-day mortality after AKI. We assessed the predictive accuracy using receiver operating characteristic curves and performed between-group comparisons using the log-rank test. Among 209 older adults, 117 (56.0%) experienced renal recovery. Multiple regression analysis revealed that urine levels of tissue inhibitor of metalloproteinase-2 (TIMP-2) multiplied by insulin-like growth factor-binding protein 7 (IGFBP7) ([TIMP-2]*[IGFBP7]), AKI stages 2-3, and the Acute Physiology and Chronic Health Evaluation (APACHE II) score were independently associated with renal non-recovery. The regression model incorporating [TIMP-2]*[IGFBP7] demonstrated a fair predictive value (AUC 0.774, p < 0.001), with the optimal threshold set at 0.81 (ng/mL)2/1000. When [TIMP-2]*[IGFBP7] was combined with AKI severity and the APACHE score, the AUC increased to 0.851. In conclusion, urine [TIMP-2]*[IGFBP7] is a reliable biomarker associated with renal non-recovery in critically ill older adults, and its predictive efficacy can be further enhanced when combined with AKI severity and the APACHE score.

Urinary cell cycle biomarkers for the prediction of renal non-recovery in patients with septic acute kidney injury: a prospective study.

BACKGROUND: Poor prognosis has been associated with the absence of renal recovery after acute kidney injury (AKI). This study aimed to investigate whether urinary biomarkers at 0 and 24 h could be used independently or in conjunction with a clinical model to predict renal non-recovery in septic AKI. METHODS: A prospective observational study was conducted to measure the urinary levels of insulin-like growth factor-binding protein 7 (IGFBP7) and tissue inhibitor of metalloproteinase-2 (TIMP-2) at the time of AKI diagnosis (0 h) and 24 h later. Renal non-recovery within 7 days was defined as the outcome. The predictive value of urinary biomarkers for renal non-recovery in septic AKI was assessed using the area under the curve (AUC). RESULTS: A total of 198 individuals with septic AKI were included in the final analysis. Among them, 38.9% (n = 77) did not experience renal recovery within 7 days. The combination of urinary IGFBP7 and TIMP-2 at the initial time point demonstrated prognostic value for non-recovery of renal function, with an AUC of 0.782. When [TIMP-2]*[IGFBP7] was measured at 0 h, the clinical prognostic model, incorporating AKI stage 2-3 and the non-renal sequential organ failure assessment score, showed an improved AUC of 0.822 (with a sensitivity of 88.3% and specificity of 59.5%). CONCLUSIONS: The combination of urinary [TIMP-2]*[IGFBP7] at 0 h exhibited moderate predictive ability for renal non-recovery in cases of septic AKI. However, there is potential to enhance the prognostic capabilities of the [TIMP-2]*[IGFBP7]-clinical prediction model.

Predictive Value of Perioperative Cardiac Troponin I in Patients Undergone Liver Transplantation: A Retrospective Cohort Study.

Objective: To examine the change rule and clinical significance of cardiac troponin I (cTnI) in the perioperative period of liver transplantation in adults, as well as its association with 28-day mortality. Methods: This was a retrospective cohort study: patients who underwent elective orthotopic liver transplantation (OLT) in Beijing Chao-Yang Hospital between June 2015 and June 2020 were selected, and plasma cTnI values were collected through the electronic medical record system within 7 days after surgery. Furthermore, the baseline clinical data of these patients were collected, and the change curve of cTnI values following liver transplantation was plotted. Using univariate and multivariate logistic regression models, the relationship between the level of postoperative cTnI and short-term mortality was investigated. The primary study endpoint was mortality within 28 days after surgery. Results: We included 414 patients who had undergone liver transplantation in this study, 48 of whom died within 28 days after surgery. cTnI, a specific marker of myocardial injury, could predict that the postoperative cardiovascular complications were higher in the death group and significantly affect the short-term prognosis of patients; however, its prognostic cut-off value was approximately 0.545 ng/mL (13×URL), indicating that a minor elevation of cTnI after liver transplantation did not significantly affect the prognosis. Moreover, a comparison of the baseline data and postoperative ICU management scores of the two groups revealed that diabetes, maximum value of cTnI >0.545 ng/mL within 7 days, and the need for postoperative renal replacement therapy (RRT) were independent prognostic factors of death within 28 days after liver transplantation. Conclusion: Within 7 days after surgery, an increase in cTnI to the maximum value of 0.545 ng/mL (13×URL) could have a significant impact on the short-term prognosis of patients. Diabetes and postoperative RRT were two independent prognostic factors for liver transplantation perioperative mortality.

Analysis of urinary C-C motif chemokine ligand 14 (CCL14) and first-generation urinary biomarkers for predicting renal recovery from acute kidney injury: a prospective exploratory study.

BACKGROUND: Acute kidney injury (AKI) is a frequent syndrome in the intensive care unit (ICU). AKI patients with kidney function recovery have better short-term and long-term prognoses compared with those with non-recovery. Numerous studies focus on biomarkers to distinguish them. To better understand the predictive performance of urinary biomarkers of renal recovery in patients with AKI, we evaluated C-C motif chemokine ligand 14 (CCL14) and two first-generation biomarkers (cell cycle arrest biomarkers and neutrophil gelatinase-associated lipocalin) in two ICU settings. METHODS: We performed a prospective study to analyze urinary biomarkers for predicting renal recovery from AKI. Patients who developed AKI after ICU admission were enrolled and urinary biomarkers including tissue inhibitor of metalloproteinase-2 (TIMP-2), insulin-like growth factor-binding protein 7 (IGFBP7), CCL14, and neutrophil gelatinase-associated lipocalin (NGAL) were detected on the day of AKI diagnosis. The primary endpoint was non-recovery from AKI within 7 days. The individual discriminative ability of CCL14, [TIMP-2] × [IGFBP7] and NGAL to predict renal non-recovery were evaluated by the area under receiver operating characteristics curve (AUC). RESULTS: Of 164 AKI patients, 64 (39.0%) failed to recover from AKI onset. CCL14 showed a fair prediction ability for renal non-recovery with an AUC of 0.71 (95% CI 0.63-0.77, p < 0.001). [TIMP-2] × [IGFBP7] showed the best prediction for renal non-recovery with an AUC of 0.78 (95% CI 0.71-0.84, p < 0.001). However, NGAL had no use in predicting non-recovery with an AUC of 0.53 (95% CI 0.45-0.60, p = 0.562). A two-parameter model (non-renal SOFA score and AKI stage) predicted renal non-recovery with an AUC of 0.77 (95% CI 0.77-0.83, p = 0.004). When [TIMP-2] × [IGFBP7] was combined with the clinical factors, the AUC was significantly improved to 0.82 (95% CI 0.74-0.87, p = 0.049). CONCLUSIONS: Urinary CCL14 and [TIMP-2] × [IGFBP7] were fair predictors of renal non-recovery from AKI. Combing urinary [TIMP-2] × [IGFBP7] with a clinical model consisting of non-renal SOFA score and AKI stage enhanced the predictive power for renal non-recovery. Urinary CCL14 showed no significant advantage in predicting renal non-recovery compared to [TIMP-2] × [IGFBP7].

The attributable mortality of sepsis for acute kidney injury: a propensity-matched analysis based on multicenter prospective cohort study.

BACKGROUND: Both sepsis and AKI are diseases of major concern in intensive care unit (ICU). This study aimed to evaluate the excess mortality attributable to sepsis for acute kidney injury (AKI). METHODS: A propensity score-matched analysis on a multicenter prospective cohort study in 18 Chinese ICUs was performed. Propensity score was sequentially conducted to match AKI patients with and without sepsis on day 1, day 2, and day 3-5. The primary outcome was hospital death of AKI patients. RESULTS: A total of 2008 AKI patients (40.9%) were eligible for the study. Of the 1010 AKI patients with sepsis, 619 (61.3%) were matched to 619 AKI patients in whom sepsis did not develop during the screening period of the study. The hospital mortality rate of matched AKI patients with sepsis was 205 of 619 (33.1%) compared with 150 of 619 (24.0%) for their matched AKI controls without sepsis (p = 0.001). The attributable mortality of total sepsis for AKI patients was 9.1% (95% CI: 4.8-13.3%). Of the matched patients with sepsis, 328 (53.0%) diagnosed septic shock. The attributable mortality of septic shock for AKI was 16.2% (95% CI: 11.3-20.8%, p < 0.001). Further, the attributable mortality of sepsis for AKI was 1.4% (95% CI: 4.1-5.9%, p = 0.825). CONCLUSIONS: The attributable hospital mortality of total sepsis for AKI were 9.1%. Septic shock contributes to major excess mortality rate for AKI than sepsis. REGISTRATION FOR THE MULTICENTER PROSPECTIVE COHORT STUDY: registration number ChiCTR-ECH-13003934.

Calprotectin as a diagnostic marker for sepsis: A meta-analysis.

Introduction: Sepsis is a life-threatening condition, and biomarkers are needed to diagnose sepsis fast and accurately. We aimed to perform this meta-analysis to investigate the diagnostic value of calprotectin on sepsis in critically ill patients. Methods: The investigators searched MEDLINE, Embase, Web of Science and Cochrane Library. Studies were included if they assessed the diagnostic accuracy of serum calprotectin for sepsis in intensive care unit (ICU). We estimated its diagnostic value and explored the source of heterogeneity. The bivariate model and the hierarchical summary receiver operating characteristic (HSROC) curve were used in the meta-analysis. Results: Six records assessing 821 patients were included in this meta-analysis. The pooled sensitivity, specificity, positive likelihood ratio (PLR), and diagnostic odds ratio (DOR) were separately as 0.77, 0.85, 5.20, 0.27, respectively. The Fagan's nomogram showed post-test probabilities of 91% and 35% for positive and negative outcomes, respectively. Subgroup analysis indicated that sepsis definition could be a possible source of heterogeneity, but there's no sufficient data to investigate sepsis-3 definition. Sensitivity analysis suggested that two studies could affect the stability of pooled results. Conclusion: On the basis of our meta-analysis, calprotectin is a helpful marker for early diagnosis of sepsis on ICU admission.

Cell cycle arrest biomarkers for predicting renal recovery from acute kidney injury: a prospective validation study.

BACKGROUND: Acute kidney injury (AKI) is a common disease in the intensive care unit (ICU). AKI patients with nonrecovery of renal function have a markedly increased risk of death compared with patients with recovery. The current study aimed to explore and validate the utility of urinary cell cycle arrest biomarkers for predicting nonrecovery in patients who developed AKI after ICU admission. METHODS: We prospectively and consecutively enrolled 379 critically ill patients who developed AKI after admission to the ICU, which were divided into a derivation cohort (194 AKI patients) and a validation cohort (185 AKI patients). The biomarkers of urinary tissue inhibitor of metalloproteinase-2 (TIMP-2) and insulin-like growth factor-binding protein 7 (IGFBP7) were detected at inclusion immediately after AKI diagnosis (day 0) and 24 h later (day 1). The optimal cut-off values of these biomarkers for predicting nonrecovery were estimated in the derivation cohort, and their predictive accuracy was assessed in the validation cohort. The primary endpoint was nonrecovery from AKI (within 7 days). RESULTS: Of 379 patients, 159 (41.9%) patients failed to recover from AKI onset, with 79 in the derivation cohort and 80 in the validation cohort. Urinary [TIMP-2]*[IGFBP7] on day 0 showed a better prediction ability for nonrecovery than TIMP-2 and IGFBP7 alone, with an area under the reciever operating characteristic curve (AUC) of 0.751 [95% confidence interval (CI) 0.701-0.852, p < 0.001] and an optimal cut-off value of 1.05 ((ng/mL)2/1000). When [TIMP-2]*[IGFBP7] was combined with the clinical factors of AKI diagnosed by the urine output (UO) criteria, AKI stage 2-3 and nonrenal SOFA score for predicting nonrecovery, the AUC was significantly improved to 0.852 (95% CI 0.750-0.891, p < 0.001), which achieved a sensitivity and specificity of 88.8% (72.9, 98.7) and 92.6% (80.8, 100.0), respectively. However, urine [TIMP-2]*[IGFBP7], TIMP-2 alone, and IGFBP7 alone on day 1 performed poorly for predicting AKI recovery. CONCLUSION: Urinary [TIMP-2]*[IGFBP7] on day 0 showed a fair performance for predicting nonrecovery from AKI. The predictive accuracy can be improved when urinary [TIMP-2]*[IGFBP7] is combined with the clinical factors of AKI diagnosed by the UO criteria, AKI stage 2-3 and nonrenal SOFA score.

The attributable mortality of new-onset acute kidney injury among critically ill patients: a propensity-matched analysis based on a multicentre prospective cohort study.

PURPOSE: This study aimed to evaluate the attributable mortality of new-onset acute kidney injury (AKI). METHODS: The data in the present study were derived from a multi-center, prospective cohort study in China that was performed at 18 Chinese ICUs. A propensity-matched analysis was performed between matched patients with and without AKI selected from all eligible patients to estimate the attributable mortality of new-onset AKI. RESULTS: A total of 2872 critically ill adult patients were eligible. The incidence of new-onset AKI was 29.1% (n = 837). After propensity score matching, 788 patients with AKI were matched 1:1 with 788 controls (patients without AKI). Thirty-day mortality was significantly higher among the patients with AKI than among their matched controls (25.5% versus 17.4%, p < 0.001). Subgroup analysis in terms of AKI classification showed that there was no significant difference (p = 0.509) in 30-day mortality between patients with stage 1 AKI and their matched controls. The attributable mortality values of stage 2 and stage 3 AKI were 12.4% [95% confidence interval (CI) 2.6-21.8%, p = 0.013] and 16.1% (95% CI 8.2-23.8%, p < 0.001), respectively. The attributable mortality of persistent AKI was 15.7% (95% CI 8.8-22.4%, p = 0.001), while no observable difference in 30-day mortality was identified between transient AKI patients and their matched non-AKI controls (p = 0.229). CONCLUSION: The absolute excess 30-day mortality that is statistically attributable to new-onset AKI is substantial (8.1%) among general ICU patients. However, neither stage 1 AKI nor transient AKI increases 30-day mortality.

Development of a Multivariable Prediction Model for Citrate Accumulation in Liver Transplant Patients Undergoing Continuous Renal Replacement Therapy with Regional Citrate Anticoagulation.

INTRODUCTION: Patients with impaired citrate metabolism may experience citrate accumulation (CA), which causes life-threatening metabolic acidosis and hypocalcemia. CA poses a challenge for clinicians when deciding on the use of regional citrate anticoagulation (RCA) for patients with liver dysfunction. This study aimed to develop a prediction model integrating multiple clinical variables to assess the risk of CA in liver transplant patients. METHODS: This single-center prospective cohort study included postoperative liver transplant patients who underwent continuous renal replacement therapy (CRRT) with RCA. The study end point was CA. A prediction model was developed using a generalized linear mixed-effect model based on the Akaike information criterion. The predictive values were assessed using the receiver operating characteristic curve and bootstrap resampling (times = 500) to estimate the area under the curve (AUC) and the corresponding 95% confidence interval (CI). A nomogram was used to visualize the model. RESULTS: This study included 32 patients who underwent 133 CRRT sessions with RCA. CA occurred in 46 CRRT sessions. The model included lactate, norepinephrine >0.1 µg/kg/min, alanine aminotransferase, total bilirubin, and standard bicarbonate, which were tested before starting each CRRT session and body mass index, diabetes mellitus, and chronic kidney disease as predictors. The AUC of the model was 0.867 (95% CI 0.786-0.921), which was significantly higher than that of the single predictor (p < 0.05). A nomogram visualized the prediction model. CONCLUSIONS: The prediction model integrating multiple clinical variables showed a good predictive value for CA. A nomogram visualized the model for easy application in clinical practice.

Risk factors, clinical features and outcome of new-onset acute kidney injury among critically ill patients: a database analysis based on prospective cohort study.

BACKGROUND: Acute kidney injury (AKI) newly-emerged in intensive care unit (ICU), has not been thoroughly studied in previous researches, is likely to differ from AKI developed before ICU admission. This study aimed to evaluate the incidence, risk factors, clinical features and outcome of new-onset AKI in critically ill patients. METHODS: The data of present study derived from a multicenter, prospective cohort study in17 Chinese ICUs (January 2014 - August 2015). The incidence, risk factors, clinical features and survival analysis of new-onset AKI were assessed. RESULTS: A total of 3374 adult critically ill patients were eligible. The incidence of new-onset AKI was 30.0 % (n = 1012). Factors associated with a higher risk of new-onset AKI included coronary heart disease, hypertension, chronic liver disease, use of nephrotoxic drugs, sepsis, SOFA score, APACHEII score and use of vasopressors. The new-onset AKI was an independent risk factor for 28-day mortality (adjusted hazard ratio, 1.643; 95 % CI, 1.370-1.948; P < 0.001). 220 (21.7 %) patients received renal replacement therapy (RRT), 71 (32.3 %) of them were successfully weaning from RRT. More than half of the new-onset AKI were transient AKI (renal recovery within 48 h). There was no statistical relationship between transient AKI and 28-day mortality (hazard ratio, 1.406; 95 % CI, 0.840-1.304; P = 0.686), while persistent AKI (non-renal recovery within 48 h) was strongly associated with 28-day mortality (adjusted hazard ratio, 1.486; 95 % CI, 1.137-1.943; P < 0.001). CONCLUSIONS: New-onset AKI is common in ICU patients and is associated with significantly higher 28-day mortality. Only persistent AKI, but not transient AKI is associated with significantly higher 28-day mortality.

Prognostic value of dynamic plasma endostatin for the prediction of mortality in acute kidney injury: A prospective cohort study.

OBJECTIVE: The aim of the current study was to evaluate the value of plasma endostatin for predicting 30-day mortality of patients with acute kidney injury (AKI). METHODS: Patients who underwent non-cardiac major surgery and developed AKI in the first 48 hours after admission to the intensive care unit were consecutively included. Concentrations of plasma neutrophil gelatinase-associated lipocalin (NGAL), cystatin C (Cys C), and endostatin were measured at three time points: 0, 24, and 48 hours after the AKI diagnosis. Clinical patient characteristics were recorded after AKI was diagnosed. RESULTS: A total of 256 new-onset AKI patients were enrolled. Of these, 48 (18.7%) patients died within 30 days. The difference in plasma endostatin values between 0 and 24 hours (ΔEndostatin-24h) yielded the best area under the curve (AUC) of 0.747 for predicting 30-day mortality in AKI patients; NGAL and Cys C achieved AUC of 0.672 and 0.647, respectively. The predictive AUC increased to 0.833 when ΔEndostatin-24h was combined with sequential organ failure assessment score and AKI classification. CONCLUSION: Dynamic plasma endostatin is useful for predicting 30-day mortality in AKI patients. The predictive power of dynamic plasma endostatin can be significantly improved when it is combined with clinical patient data.

Derivation and validation of plasma endostatin for predicting renal recovery from acute kidney injury: a prospective validation study.

BACKGROUND: Acute kidney injury (AKI) is associated with high morbidity and mortality in surgical patients. Nonrecovery from AKI may increase mortality and early risk stratification seems key to improving clinical outcomes. The aim of the current study was to explore and validate the value of endostatin for predicting failure to recover from AKI. METHODS: We conducted a prospective cohort study of 198 patients without known chronic kidney disease who underwent noncardiac major surgery and developed new-onset AKI in the first 48 h after admission to the ICU. The biomarkers of plasma endostatin, neutrophil gelatinase-associated lipocalin (NGAL) and cystatin C were detected immediately after AKI diagnosis. The primary endpoint was nonrecovery from AKI (within 7 days). Cutoff values of the biomarkers for predicting nonrecovery were determined in a derivation cohort (105 AKI patients). Predictive accuracy was then analyzed in a validation cohort (93 AKI patients). RESULTS: Seventy-six of 198 (38.4%) patients failed to recover from AKI onset, with 41 in the derivation cohort and 35 in the validation cohort. Compared with NGAL and cystatin C, endostatin showed a better prediction for nonrecovery, with an area under the receiver operating characteristic curve (AUC) of 0.776 (95% confidence interval (CI) 0.654-0.892, p < 0.001) and an optimal cutoff value of 63.7 ng/ml. The predictive ability for nonrecovery was greatly improved by the prediction model combining endostatin with clinical risk factors of Sequential Organ Failure Assessment (SOFA) score and AKI classification, with an AUC of 0.887 (95% CI 0.766-0.958, p < 0.001). The value of the endostatin-clinical risk prediction model was superior to the NGAL-clinical risk and cystatin C-clinical risk prediction models in predicting failure to recover from AKI, which was supported by net reclassification improvement and integrated discrimination improvement. Further, the endostatin-clinical risk prediction model achieved sensitivity and specificity of 94.6% (76.8-99.1) and 72.7% (57.2-85.0), respectively, when validated in the validation cohort. CONCLUSION: Plasma endostatin shows a useful value for predicting failure to recover from AKI. The predictive ability can be greatly improved when endostatin is combined with the SOFA score and AKI classification.

Prognostic value of cell cycle arrest biomarkers in patients at high risk for acute kidney injury: A systematic review and meta-analysis.

Urinary tissue inhibitor of metalloproteinase-2 (TIMP-2) and insulin-like growth factor binding protein 7 (IGFBP7) are G1 cell cycle arrest biomarkers. This systematic review aimed to evaluate the prognostic value of urinary [TIMP-2]·[IGFBP7] in patients at high risk for AKI. The MEDLINE (via PubMed), Ovid, EMBASE and Cochrane Library databases were systematically searched from inception to December 25, 2016. Original clinical studies which met the eligibility criteria were included in this study. The prognostic accuracy of urinary [TIMP-2]·[IGFBP7] for assessing the need for renal replacement therapy (RRT) and mortality was evaluated by pooled sensitivity, specificity, diagnostic odds ratio, and summary receiver operating characteristic curves. A total of four prospective cohort studies evaluating 277 patients were included. The estimated area under the receiver operating characteristic curve (AUC) of urinary [TIMP-2]·[IGFBP7] for predicting the need for RRT in patients at high risk for AKI was 0.915 (standard error [SE] = 0.040). Pooled sensitivity and specificity with corresponding 95% confidence intervals (CI) were 0.69 (95% CI 0.53-0.82) and 0.81 (95% CI 0.75-0.86), respectively. Urinary [TIMP-2]·[IGFBP7] for mortality prediction in patients at high risk for AKI was assessed by qualitative description. Based on the above data, urinary [TIMP-2]·[IGFBP7] performs well in predicting the need for RRT and mortality in patients at high risk for AKI. However, further meta-analyses are warranted as more data become available.

Diagnostic value of urinary tissue inhibitor of metalloproteinase-2 and insulin-like growth factor binding protein 7 for acute kidney injury: a meta-analysis.

BACKGROUND: Tissue inhibitor of metalloproteinase-2 (TIMP-2) and insulin-like growth factor binding protein 7 (IGFBP7), inducers of G1 cell cycle arrest, are two recently discovered good biomarkers for early diagnosis of acute kidney injury (AKI). To obtain a more robust performance measurement, the present meta-analysis was performed, pooling existing studies. METHODS: Literature in the MEDLINE (via PubMed), Ovid, Embase, and Cochrane Library databases was systematically searched from inception to 12 October 2016. Studies that met the set inclusion and exclusion criteria were identified by two independent investigators. The diagnostic value of urinary [TIMP-2] × [IGFBP7] for AKI was evaluated by pooled sensitivity, specificity, likelihood ratio (LR), diagnostic odds ratio (DOR), and summary receiver operating characteristic (SROC) curve analyses. The causes of heterogeneity were explored by sensitivity and subgroup analyses. RESULTS: A total of nine published and eligible studies assessing 1886 cases were included in this meta-analysis. Early diagnostic value of urinary [TIMP-2] × [IGFBP7] for AKI was assessed using a random-effects model. Pooled sensitivity and specificity with corresponding 95% CIs were 0.83 (95% CI 0.79-0.87, heterogeneity I 2 = 68.8%) and 0.55 (95% CI 0.52-0.57, I 2 = 92.9%), respectively. Pooled positive LR, negative LR, and DOR were 2.37 (95% CI 1.87-2.99, I 2 = 82.6%), 0.30 (95% CI 0.21-0.41, I 2 = 43.4%), and 9.92 (95% CI 6.09-16.18, I 2 = 38.5%), respectively. The AUC estimated by SROC was 0.846 (SE 0.027) with a Q* value of 0.777 (SE 0.026). Sensitivity analysis indicated that one study significantly affected the stability of pooled results. Subgroup analysis showed that population setting and AKI threshold were the key factors causing heterogeneity in pooled sensitivity and specificity. CONCLUSIONS: On the basis of recent evidence, urinary [TIMP-2] × [IGFBP7] is an effective predictive factor of AKI. TRIAL REGISTRATION: PROSPERO registration number: CRD42016051186 . Registered on 10 November 2016.