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.

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.

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.

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.