Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,362

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

Discovery and validation of cell cycle arrest biomarkers in human acute kidney injury

Open access
Kashani, Kianoush, Al-Khafaji, Ali, Ardiles, Thomas, Artigas, Antonio, Bagshaw, Sean M, Bell, Max, Bihorac, Azra, Birkhahn, Robert, Cely, Cynthia M, Chawla, Lakhmir S, Davison, Danielle L, Feldkamp, Thorsten, Forni, Lui G, Gong, Michelle Ng, Gunnerson, Kyle J, Haase, Michael, Hackett, James, Honore, Patrick M, Hoste, Eric AJ, Joannes-Boyau, Olivier, Joannidis, Michael, Kim, Patrick, Koyner, Jay L, Laskowitz, Daniel T, Lissauer, Matthew E, Marx, Gernot, McCullough, Peter A, Mullaney, Scott, Ostermann, Marlies, Rimmelé, Thomas, Shapiro, Nathan I, Shaw, Andrew D, Shi, Jing, Sprague, Amy M, Vincent, Jean-Louis, Vinsonneau, Christophe, Wagner, Ludwig, Walker, Michael G, Wilkerson, R Gentry, Zacharowski, Kai, Kellum, John A·2013·Critical Care

Abstract

Introduction: Acute 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. Methods: We 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. Results: Moderate 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 G 1 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. Conclusions: Two 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 registration: ClinicalTrials.gov number NCT01209169 .

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/cc12503

Cites

8 of 8 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 8 references

Cited by

See all 1,362

Metadata

Authors
Kashani, K., Al-Khafaji, A., Ardiles, T., Artigas, A., Bagshaw, S. M., Bell, M., Bihorac, A., Birkhahn, R., Cely, C. M., Chawla, L. S., Davison, D. L., Feldkamp, T., Forni, L. G., Gong, M. N., Gunnerson, K. J., Haase, M., Hackett, J., Honore, P. M., Hoste, E. A., Joannes-Boyau, O., Joannidis, M., Kim, P., Koyner, J. L., Laskowitz, D. T., Lissauer, M. E., Marx, G., McCullough, P. A., Mullaney, S., Ostermann, M., Rimmelé, T., Shapiro, N. I., Shaw, A. D., Shi, J., Sprague, A. M., Vincent, J.-L., Vinsonneau, C., Wagner, L., Walker, M. G., Wilkerson, R. G., Zacharowski, K., & Kellum, J. A.
Venue
Critical Care
Published
2013-02-06
Volume
17
Issue
1
Pages
R25-R25
ISSN
1364-8535 (ISSN-L)
OpenAlex
W2148152947
Cited by
1,362
References
8
FWCI
68.72
Type
journal article
Language
en
Open access
gold

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Discovery and validation of cell cycle arrest biomarkers in human acute kidney injury. https://app.cochat.ai/papers/10.1186/cc12503
The paper
Kashani, K., Al-Khafaji, A., Ardiles, T., Artigas, A., Bagshaw, S. M., Bell, M., Bihorac, A., Birkhahn, R., Cely, C. M., Chawla, L. S., Davison, D. L., Feldkamp, T., Forni, L. G., Gong, M. N., Gunnerson, K. J., Haase, M., Hackett, J., Honore, P. M., Hoste, E. A., . . . Kellum, J. A. (2013). Discovery and validation of cell cycle arrest biomarkers in human acute kidney injury. Critical Care. https://doi.org/10.1186/cc12503

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.