Comparison of kidney injury molecule-1, proenkephalin and presepsin as predictors of diagnostics and severity of sepsis associated acute kidney injury

Kidney Injury Molecule-1 (KIM-1), proenkephalin, and presepsin are some of the new AKI biomarkers being explored recently. This study aims to compare the accuracy of the predictive value between urine KIM-1, proenkephalin, and presepsin on the incidence and severity of SA-AKI. Samples were taken on days 1, 3, and 7. A receiver operating curve (ROC) was generated to estimate the area under the curve (AUC) and optimal cutoff values. Sensitivity and specificity accommodate the index for validity. Comparative accuracy is determined by multivariate analysis. As predictors of SA-AKI diagnosis, urine KIM-1 on the third day has the highest AUC value during the study (AUC 0.628, sensitivity 66.7%, and specificity 57.9%, p=0.154). As predictors of SA-AKI severity on the seventh day, proenkephalin and presepsin achieved AUC 0.600 (80% sensitivity and 71.4% specificity, p value = 0.5 for proenkephalin, and sensitivity of 60% and specificity 85.7%, p = 0.471 for presepsin). A p value <0.05 is considered for statistical significance, and a 95% confidence interval is used for all assessments. Based on the results, neither urine KIM-1, proenkephalin, nor presepsin has been proven to be accurate, and more studies are needed to determine diagnostic and severity predictors of SA-AKI.

Authors

Institutions

Publication Details

Journal
Edelweiss Applied Science and Technology
Published
2025-01-28
DOI
https://doi.org/10.55214/25768484.v9i2.4481
Citations
1
Primary Topic
Acute Kidney Injury Research
Type
article
Field-Weighted Citation Impact
1.43

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comparison of kidney injury molecule-1, proenkephalin and presepsin as predictors of diagnostics and severity of sepsis associated acute kidney injury

Maulydia Maulydia, Bambang Pujo Semedi, Sepsiana Puspitasari, Nancy Margarita Rehatta et al.
1 citations
Edelweiss Applied Science and Technology
Acute Kidney Injury Research
1.43
article

Comparison of kidney injury molecule-1, proenkephalin and presepsin as predictors of diagnostics and severity of sepsis associated acute kidney injury

Maulydia Maulydia, Bambang Pujo Semedi, Sepsiana Puspitasari, Nancy Margarita Rehatta, Windhu Purnomo
article en
1 citations

Abstract

Kidney Injury Molecule-1 (KIM-1), proenkephalin, and presepsin are some of the new AKI biomarkers being explored recently. This study aims to compare the accuracy of the predictive value between urine KIM-1, proenkephalin, and presepsin on the incidence and severity of SA-AKI. Samples were taken on days 1, 3, and 7. A receiver operating curve (ROC) was generated to estimate the area under the curve (AUC) and optimal cutoff values. Sensitivity and specificity accommodate the index for validity. Comparative accuracy is determined by multivariate analysis. As predictors of SA-AKI diagnosis, urine KIM-1 on the third day has the highest AUC value during the study (AUC 0.628, sensitivity 66.7%, and specificity 57.9%, p=0.154). As predictors of SA-AKI severity on the seventh day, proenkephalin and presepsin achieved AUC 0.600 (80% sensitivity and 71.4% specificity, p value = 0.5 for proenkephalin, and sensitivity of 60% and specificity 85.7%, p = 0.471 for presepsin). A p value <0.05 is considered for statistical significance, and a 95% confidence interval is used for all assessments. Based on the results, neither urine KIM-1, proenkephalin, nor presepsin has been proven to be accurate, and more studies are needed to determine diagnostic and severity predictors of SA-AKI.

Edelweiss Applied Science and TechnologyVol. 9(2)
Universitas Airlangga (ID)
Universitas Airlangga
Openalex Percentile: Top 23%
Acute Kidney Injury Research
1.43
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.