IntroductionAcute kidney injury (AKI) can evolve quickly and clinical measures of function often fail to detect AKI at a time when interventions are likely to provide benefit. Identifying early markers of kidney damage has been difficult due to the complex nature of human AKI, in which multiple etiologies exist. The objective of this study was to identify and validate novel biomarkers of AKI.MethodsWe performed two multicenter observational studies in critically ill patients at risk for AKI - discovery and validation. The top two markers from discovery were validated in a second study (Sapphire) and compared to a number of previously described biomarkers. In the discovery phase, we enrolled 522 adults in three distinct cohorts including patients with sepsis, shock, major surgery, and trauma and examined over 300 markers. In the Sapphire validation study, we enrolled 744 adult subjects with critical illness and without evidence of AKI at enrollment; the final analysis cohort was a heterogeneous sample of 728 critically ill patients. The primary endpoint was moderate to severe AKI (KDIGO stage 2 to 3) within 12 hours of sample collection.ResultsModerate to severe AKI occurred in 14% of Sapphire subjects. The two top biomarkers from discovery were validated. Urine insulin-like growth factor-binding protein 7 (IGFBP7) and tissue inhibitor of metalloproteinases-2 (TIMP-2), both inducers of G1 cell cycle arrest, a key mechanism implicated in AKI, together demonstrated an AUC of 0.80 (0.76 and 0.79 alone). Urine [TIMP-2]·[IGFBP7] was significantly superior to all previously described markers of AKI (P <0.002), none of which achieved an AUC >0.72. Furthermore, [TIMP-2]·[IGFBP7] significantly improved risk stratification when added to a nine-variable clinical model when analyzed using Cox proportional hazards model, generalized estimating equation, integrated discrimination improvement or net reclassification improvement. Finally, in sensitivity analyses [TIMP-2]·[IGFBP7] remained significant and superior to all other markers regardless of changes in reference creatinine method.ConclusionsTwo novel markers for AKI have been identified and validated in independent multicenter cohorts. Both markers are superior to existing markers, provide additional information over clinical variables and add mechanistic insight into AKI.Trial registrationClinicalTrials.gov number NCT01209169.

Urinary [TIMP-2]·[IGFBP7] greater than 0.3 (ng/ml)(2)/1,000 identifies patients at risk for imminent AKI. Clinical trial registered with www.clinicaltrials.gov (NCT 01573962).

Islet duodenal homeobox 1 (IDX-1/PF-1/STF-1/PDX-1), a homeodomain protein that transactivates the insulin promoter, has been shown by targeted gene ablation to be required for pancreatic development. After 90% pancreatectomy (Px), the adult pancreas regenerates in a process recapitulating embryonic development, starting with a burst of proliferation in the epithelium of the common pancreatic duct. In this model, IDX-1 mRNA was detected by semiquantitative reverse transcription-polymerase chain reaction in total RNA from isolated common pancreatic ducts at levels 10% of those of isolated islets. The IDX-1 mRNA levels were not significantly different for common pancreatic ducts of Px, sham Px, and unoperated rats and did not change with time after surgery. By immunoblot analysis, IDX-1 protein was only faintly detected in these ducts 1 and 7 days after Px or sham Px but was easily detected at 2 and 3 days after Px. Similarly, IDX-1 immunostaining was barely detectable in sham or unoperated ducts but was strong in ducts at 2-3 days after Px. The increase of IDX-1 immunostaining followed that of BrdU incorporation (proliferation). These results indicate a posttranscriptional regulation of the IDX-1 expression in ducts. In addition, islets isolated 3-7 d after Px showed higher IDX-1 protein expression than control islets. Thus, in pancreatic regeneration IDX-1 is upregulated in newly divided ductal cells as well as in islets. The timing of enhanced expression of IDX-1 implies that IDX-1 is not important in the initiation of regeneration but may be involved in the differentiation of ductal cells to beta-cells.

The aim of the RUBY study was to evaluate novel candidate biomarkers to enable prediction of persistence of renal dysfunction as well as further understand potential mechanisms of kidney tissue damage and repair in acute kidney injury (AKI). Methods: The RUBY study was a multi-center international prospective observational study to identify biomarkers of the persistence of stage 3 AKI as defined by the KDIGO criteria. Patients in the intensive care unit (ICU) with moderate or severe AKI (KDIGO stage 2 or 3) were enrolled. Patients were to be enrolled within 36 h of meeting KDIGO stage 2 criteria. The primary study endpoint was the development of persistent severe AKI (KDIGO stage 3) lasting for 72 h or more (NCT01868724). Results: 364 patients were enrolled of whom 331 (91%) were available for the primary analysis. One hundred ten (33%) of the analysis cohort met the primary endpoint of persistent stage 3 AKI. Of the biomarkers tested in this study, urinary CC motif chemokine ligand 14 (CCL14) was the most predictive of persistent stage 3 AKI with an area under the receiver operating characteristic curve (AUC) (95% CI) of 0.83 (0.78-0.87). This AUC was significantly greater than values for other biomarkers associated with AKI including urinary KIM-1, plasma cystatin C, and urinary NGAL, none of which achieved an AUC > 0.75. Conclusion: Elevated urinary CCL14 predicts persistent AKI in a large heterogeneous cohort of critically ill patients with severe AKI. The discovery of CCL14 as a predictor of persistent AKI and thus, renal non-recovery, is novel and could help identify new therapeutic approaches to AKI.

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Sepsis has a unique gene expression profile that is different from uninfected inflammation and becomes apparent prior to expression of the clinical sepsis phenotype.

Background Survey data revealed that families of patients in a surgical intensive care unit were not satisfied with their participation in decision making or with how well the multidisciplinary team worked together. Objectives To develop and implement an evidence-based communication algorithm and evaluate its effect in improving satisfaction among patients’ families. Methods A multidisciplinary team developed an algorithm that included bundles of communication interventions at 24, 72, and 96 hours after admission to the unit. The algorithm included clinical triggers, which if present escalated the algorithm. A pre-post design using process improvement methods was used to compare families’ satisfaction scores before and after implementation of the algorithm. Results Satisfaction scores for participation in decision making (45% vs 68%; z = −2.62, P = .009) and how well the health care team worked together (64% vs 83%; z = −2.10, P = .04) improved significantly after implementation. Conclusions Use of an evidence-based structured communication algorithm may be a way to improve satisfaction of families of intensive care patients with their participation in decision making and their perception of how well the unit’s team works together.

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