Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Aug 11;7(1):7862.
doi: 10.1038/s41598-017-08440-w.

A new scoring model for the prediction of mortality in patients with acute kidney injury

Affiliations

A new scoring model for the prediction of mortality in patients with acute kidney injury

Min Luo et al. Sci Rep. .

Abstract

Currently, little information is available to stratify the risks and predict acute kidney injury (AKI)-associated death. In this present cross-sectional study, a novel scoring model was established to predict the probability of death within 90 days in patients with AKI diagnosis. For establishment of predictive scoring model, clinical data of 1169 hospitalized patients with AKI were retrospectively collected, and 731 patients of them as the first group were analyzed by the method of multivariate logistic regression analysis to create a scoring model and further predict patient death. Then 438 patients of them as the second group were used for validating this prediction model according to the established scoring method. Our results showed that Patient's age, AKI types, respiratory failure, central nervous system failure, hypotension, and acute tubular necrosis-individual severity index (ATN-ISI) score are independent risk factors for predicting the death of AKI patients in the created scoring model. Moreover, our scoring model could accurately predict cumulative AKI and mortality rate in the second group. In conclusion, this study identified the risk factors of 90-day mortality for hospitalized AKI patients and established a scoring model for predicting 90-day prognosis, which could help to interfere in advance for improving the quality of life and reduce mortality rate of AKI patients.

PubMed Disclaimer

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Figure 1
Figure 1
Flow chart of study population selection and research process.
Figure 2
Figure 2
Corresponding 90-day morality for each score between test group and validation group.
Figure 3
Figure 3
Comparison of areas under the receiver operating characteristic curve among new scores, SOFA and ATN-ISI in test group.
Figure 4
Figure 4
Comparison of areas under the receiver operating characteristic curve among new scores, SOFA and ATN-ISI in validation group.
Figure 5
Figure 5
Corresponding 90-day morality for different level of new score between test group and validation group.

References

    1. Waikar SS, Curhan GC, Wald R, McCarthy EP, Chertow GM. Declining mortality in patients with acute renal failure, 1988 to 2002. Journal of the American Society of Nephrology: JASN. 2006;17:1143–1150. doi: 10.1681/ASN.2005091017. - DOI - PubMed
    1. Murugan R, Kellum JA. Acute kidney injury: what’s the prognosis? Nature reviews. Nephrology. 2011;7:209–217. doi: 10.1038/nrneph.2011.13. - DOI - PMC - PubMed
    1. Susantitaphong P, et al. World incidence of AKI: a meta-analysis. Clinical journal of the American Society of Nephrology: CJASN. 2013;8:1482–1493. doi: 10.2215/CJN.00710113. - DOI - PMC - PubMed
    1. Fang Y, et al. Acute kidney injury in a Chinese hospitalized population. Blood purification. 2010;30:120–126. doi: 10.1159/000319972. - DOI - PubMed
    1. Uchino S, et al. Acute renal failure in critically ill patients: a multinational, multicenter study. Jama. 2005;294:813–818. doi: 10.1001/jama.294.7.813. - DOI - PubMed

Publication types

LinkOut - more resources