Dataset Information

Cell-cycle arrest biomarkers in urine to predict acute kidney injury in septic and non-septic critically ill patients.

ABSTRACT:

Purpose

To analyse the usefulness of the composite index of the tissue inhibitor of metalloproteinases-2 (TIMP-2) and insulin-like growth factor-binding protein 7 (IGFBP7) as urinary biomarkers for the early prediction of AKI in septic and non-septic patients.

Methods

This is a prospective, observational study including patients admitted to ICU from acute care departments and hospital length of stay <48 h. The main exclusion criteria were pre-existing eGFR <30 mL/min/1.73 m² and hospitalisation 2 months prior to current admission. The [TIMP-2]·[IGFBP7] index was analysed twice, within the first 12 h of ICU admission.

Results

The sample included 98 patients. AKI incidence during ICU stay was 50%. Sepsis was diagnosed in 40.8%. Baseline renal variables were comparable between subgroups except for a higher baseline eGFR in non-septic patients. Patients were stratified based on the presence of AKI and their highest level of [TIMP-2]·[IGFBP7] within the first 12 h of stay. [TIMP-2]·[IGFBP7] index values were dependent on the incidence of AKI but not of sepsis. [TIMP-2]·[IGFBP7] values were significantly related to AKI severity according to AKIN criteria (p < 0.0001). The AUROC curve to predict AKI of the worst [TIMP-2]·[IGFBP7] index value was 0.798 (sensitivity 73.5%, specificity 71.4%, p < 0.0001). Index values below 0.8 ruled out any need for renal replacement (NPV 100%), whereas an index >0.8 predicted a rate of AKI of 71% and AKIN ? 2 of 62.9%.

Conclusions

In our study, urinary [TIMP-2]·[IGFBP7] was an early predictor of AKI in ICU patients regardless of sepsis. Besides, index values <0.8(ng/mL)²/1000 ruled out the need for renal replacement.

SUBMITTER: Cuartero M

PROVIDER: S-EPMC5589717 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Publications

Cell-cycle arrest biomarkers in urine to predict acute kidney injury in septic and non-septic critically ill patients.

Cuartero M M Ballús J J Sabater J J Pérez X X Nin N N Ordonez-Llanos J J Betbesé A J AJ

Annals of intensive care 20170907 1

<h4>Purpose</h4>To analyse the usefulness of the composite index of the tissue inhibitor of metalloproteinases-2 (TIMP-2) and insulin-like growth factor-binding protein 7 (IGFBP7) as urinary biomarkers for the early prediction of AKI in septic and non-septic patients.<h4>Methods</h4>This is a prospective, observational study including patients admitted to ICU from acute care departments and hospital length of stay <48 h. The main exclusion criteria were pre-existing eGFR <30 mL/min/1.73 m<sup>2< ...[more]

PMID: 28884304

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Project description:Background and Objectives: Critically ill surgical patients are susceptible to various postoperative complications, including acute kidney injury (AKI) and multiorgan distress syndrome (MODS). These complications intensify patient suffering and significantly increase morbidity and mortality rates. This study aimed to identify the biomarkers for predicting AKI and MODS in critically ill surgical patients. Materials and Methods: We prospectively enrolled critically ill surgical patients admitted to the intensive care unit via the emergency department between July 2022 and July 2023. A total of 83 patients were recruited, and their data were used to analyze MODS. Three patients who showed decreased creatinine clearance at the initial presentation were excluded from the analysis for AKI. Patient characteristics and laboratory parameters including white blood cell (WBC) count, neutrophil count, delta neutrophil index, urine and serum β2-microglobulin, and urine serum mitochondrial DNA copy number (mtDNAcn) were analyzed to determine the reliable biomarker to predict AKI and MODS. Results: The following parameters were independently correlated with MODS: systolic blood pressure (SBP), initial neutrophil count, and platelet count, according to a logistic regression model. The optimal cut-off values for SBP, initial neutrophil count, and platelet count were 113 mmHg (sensitivity 66.7%; specificity 73.9%), 8.65 (X3) (109/L) (sensitivity 72.2%; specificity 64.6%), and 195.0 (X3) (109/L) (sensitivity 66.7%; specificity 81.5%), respectively. According to the logistic regression model, diastolic blood pressure (DBP) and initial urine mtDNAcn were independently correlated with AKI. The optimal cut-off value for DBP and initial urine mtDNAcn were 68.5 mmHg (sensitivity 61.1%; specificity 79.5%) and 1225.6 copies/μL (sensitivity 55.6%; specificity 95.5%), respectively. Conclusions: SBP, initial neutrophil count, and platelet count were independent predictors of MODS in critically ill patients undergoing surgery. DBP and initial urine mtDNAcn levels were independent predictors of AKI in critically ill surgical patients. Large-scale multicenter prospective studies are needed to confirm our results.

Dataset Information

Cell-cycle arrest biomarkers in urine to predict acute kidney injury in septic and non-septic critically ill patients.

Purpose

Methods

Results

Conclusions

Publications

Cell-cycle arrest biomarkers in urine to predict acute kidney injury in septic and non-septic critically ill patients.

Similar Datasets

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