Limiting Acute Kidney Injury Progression In Sepsis: Study Protocol and Trial Simulation*

Molinari, Luca; Heskia, Fabienne; Peerapornratana, Sadudee; Ronco, Claudio; Guzzi, Louis M.; Toback, Seth; Birch, Robert; Beyhaghi, Hadi; Kwan, Thomas; Kampf, J. Patrick; Yealy, Donald M.; Kellum, John A.

doi:10.1097/ccm.0000000000005061

Cited by 13 publications

(18 citation statements)

References 34 publications

(51 reference statements)

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“…They found associations between these biomarker signatures and both AKI occurrence and persistence, as defined by ADQI-16, finding significant differences in both. We chose to focus on the only commercially available biomarker test for AKI in the US because it is also available worldwide and has a published high-specificity cutoff and because an ongoing trial is already using it specifically for patients with sepsis . Future work is needed to evaluate other potential biomarkers alone or in combination to augment AKI staging, such as kidney injury molecule 1 and neutrophil gelatinase–associated lipocalin.…”

Section: Discussionsupporting

confidence: 75%

Utility of Biomarkers for Sepsis-Associated Acute Kidney Injury Staging

et al. 2022

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IMPORTANCEThe 23rd Acute Disease Quality Initiative (ADQI-23) consensus conference proposed a framework to integrate biomarkers into the staging of acute kidney injury (AKI). It is unknown whether tissue inhibitor of metalloproteinases 2 (TIMP-2) and insulinlike growth factor binding protein 7 (IGFBP7) could be used for staging. OBJECTIVETo test whether higher levels of urinary [TIMP-2] × [IGFBP7] are associated with lower survival among patients with the same functional stage of AKI. DESIGN, SETTING, AND PARTICIPANTS This cohort study was performed using data from the Protocolized Care for Early Septic Shock (ProCESS) trial, which enrolled critically ill patients with septic shock who presented at academic and community emergency departments and intensive care units in the US from March 2008 to May 2013. Patients with end-stage kidney disease, a reference serum creatinine level of 4 mg/dL or greater (to convert to μmol/L, multiply by 76.25), or missing data on serum creatinine levels or urinary levels of [TIMP-2] × [IGFBP7] were excluded. Data were analyzed from October 2020 to October 2021. EXPOSURES The presence of AKI, assessed using Kidney Disease: Improving Global Outcomes criteria within 24 hours after enrollment and the highest AKI stage as well as urinary [TIMP-2] × [IGFBP7] level at 6 hours after enrollment. A previously reported high-specificity cutoff level for [TIMP-2] × [IGFBP7] of 2.0 (ng/mL) 2 /1000 was used to categorize patients (including those without functional criteria of AKI) according to the new staging system proposed by the ADQI-23 as biomarker negative (urinary [TIMP-2] × [IGFBP7] level Յ2.0 [ng/mL] 2 /1000) or biomarker positive ([TIMP-2] × [IGFBP7] >2.0 [ng/mL] 2 /1000).MAIN OUTCOMES AND MEASURES Survival (assessed using Kaplan-Meier plots and the log-rank test) and mortality (assessed using relative risk [RR] 30 days after enrollment). RESULTSThe analysis included 999 patients with a median age of 61 years (IQR, 50-73 years); 554 (55.5%) were male. Biomarker-positive patients had lower survival and higher mortality at 30 days in the groups with AKI stage 1 (RR, 2.20; 95% CI, 1.02-4.72), stage 2 (RR, 1.53; 95% CI, 1.04-2.27), and stage 3 (RR, 1.61; 95% CI, 1.00-2.60). The associations were specific to patients with AKI. No difference in 30-day survival was found between biomarker-positive and biomarker-negative patients in the absence of functional criteria for AKI (RR, 1.16; 95% CI, 0.45-3.01). CONCLUSIONS AND RELEVANCEThe findings suggest that assessment of the cell-cycle arrest biomarkers TIMP-2 and IGFBP7 may augment AKI staging for patients with functional criteria for AKI.

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Section: Discussionsupporting

confidence: 75%

Utility of Biomarkers for Sepsis-Associated Acute Kidney Injury Staging

et al. 2022

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“…There is no specific effective therapy for AKI, partly due to its diverse clinical presentations and not well-understood pathophysiology. One personalized approach is the phenotypical- and/or biomarkers-based managements to prevent AKI or to timely treat AKI [ 24 , 44 , 45 ]. This study presents another approach to inform the planning of managements at the time of RRT initiation, when critical treatment decisions are often being made.…”

Section: Discussionmentioning

confidence: 99%

Unsupervised clustering identifies sub-phenotypes and reveals novel outcome predictors in patients with dialysis-requiring sepsis-associated acute kidney injury

et al. 2023

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Introduction Heterogeneity exists in sepsis-associated acute kidney injury (SA-AKI). This study aimed to perform unsupervised consensus clustering in critically ill patients with dialysis-requiring SA-AKI. Patients and Methods This prospective observational cohort study included all septic patients, defined by the Sepsis-3 criteria, with dialysis-requiring SA-AKI in surgical intensive care units in Taiwan between 2009 and 2018. We employed unsupervised consensus clustering based on 23 clinical variables upon initializing renal replacement therapy. Multivariate-adjusted Cox regression models and Fine–Gray sub-distribution hazard models were built to test associations between cluster memberships with mortality and being free of dialysis at 90 days after hospital discharge, respectively. Results Consensus clustering among 999 enrolled patients identified three sub-phenotypes characterized with distinct clinical manifestations upon renal replacement therapy initiation ( n = 352, 396 and 251 in cluster 1, 2 and 3, respectively). They were followed for a median of 48 (interquartile range 9.5–128.5) days. Phenotypic cluster 1, featured by younger age, lower Charlson Comorbidity Index, higher baseline estimated glomerular filtration rate but with higher severity of acute illness was associated with an increased risk of death (adjusted hazard ratio of 3.05 [95% CI, 2.35–3.97]) and less probability to become free of dialysis (adjusted sub-distribution hazard ratio of 0.55 [95% CI, 0.38–0.8]) than cluster 3. By examining distinct features of the sub-phenotypes, we discovered that pre-dialysis hyperlactatemia ≥3.3 mmol/L was an independent outcome predictor. A clinical model developed to determine high-risk sub-phenotype 1 in this cohort (C-static 0.99) can identify a sub-phenotype with high in-hospital mortality risk (adjusted hazard ratio of 1.48 [95% CI, 1.25–1.74]) in another independent multi-centre SA-AKI cohort. Conclusions Our data-driven approach suggests sub-phenotypes with clinical relevance in dialysis-requiring SA-AKI and serves an outcome predictor. This strategy represents further development toward precision medicine in the definition of high-risk sub-phenotype in patients with SA-AKI. Key messages Unsupervised consensus clustering can identify sub-phenotypes of patients with SA-AKI and provide a risk prediction. Examining the features of patient heterogeneity contributes to the discovery of serum lactate levels ≥ 3.3 mmol/L upon initializing RRT as an independent outcome predictor. This data-driven approach can be useful for prognostication and lead to a better understanding of therapeutic strategies in heterogeneous clinical syndromes.

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“…For this reason, it has recently been proposed that one use biomarkers of kidney stress and/or injury in addition to current KDIGO criteria to better stage and identify early forms of AKI [ 45 ]. In this regard, biomarker-guided treatment strategies to prevent AKI in patients undergoing surgery [ 46 , 47 ] and in patients with sepsis [ 48 ] have already been proposed. However, whether Gas6 and sMer could act as specific biomarkers of kidney injury still needs to be clarified.…”

Section: Discussionmentioning

confidence: 99%

Are Baseline Levels of Gas6 and Soluble Mer Predictors of Mortality and Organ Damage in Patients with Sepsis? The Need-Speed Trial Database

et al. 2022

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Soluble tyrosine kinase receptor Mer (sMer) and its ligand Growth arrest-specific protein 6 (Gas6) are predictors of mortality in patients with sepsis. Our aim is to clarify whether their measurement at emergency department (ED) presentation is useful in risk stratification. We re-analyzed data from the Need-Speed trial, evaluating mortality and the presence of organ damage according to baseline levels of sMer and Gas6. 890 patients were eligible; no association with 7- and 30-day mortality was observed for both biomarkers (p > 0.05). sMer and Gas6 levels were significantly higher in acute kidney injury (AKI) patients compared to non-AKI ones (9.8 [4.1–17.8] vs. 7.9 [3.8–12.9] ng/mL and 34.8 [26.4–47.5] vs. 29.8 [22.1–41.6] ng/mL, respectively, for sMer and Gas6), and Gas6 also emerged as an independent AKI predictor (odds ratio (OR) 1.01 [1.00–1.02]). Both sMer and Gas6 independently predicted thrombocytopenia in sepsis patients not treated with anticoagulants (OR 1.01 [1.00–1.02] and 1.04 [1.02–1.06], respectively). Moreover, sMer was an independent predictor of both prothrombin time-international normalized ratio (PT-INR) > 1.4 (OR 1.03 [1.00–1.05]) and sepsis-induced coagulopathy (SIC) (OR 1.05 [1.02–1.07]). An early measurement of the sMer and Gas6 plasma concentration could not predict mortality. However, the biomarkers were associated with AKI, thrombocytopenia, PT-INR derangement and SIC, suggesting a role in predicting sepsis-related organ damage.

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Limiting Acute Kidney Injury Progression In Sepsis: Study Protocol and Trial Simulation*

Abstract: Supplemental Digital Content is available in the text.

Cited by 13 publications

References 34 publications

Utility of Biomarkers for Sepsis-Associated Acute Kidney Injury Staging

Utility of Biomarkers for Sepsis-Associated Acute Kidney Injury Staging

Unsupervised clustering identifies sub-phenotypes and reveals novel outcome predictors in patients with dialysis-requiring sepsis-associated acute kidney injury

Are Baseline Levels of Gas6 and Soluble Mer Predictors of Mortality and Organ Damage in Patients with Sepsis? The Need-Speed Trial Database

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