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Risk Scoring Systems Including Electrolyte Disorders for Predicting the Incidence of Acute Kidney Injury in Hospitalized Patients

Overview
Journal Clin Epidemiol
Publisher Dove Medical Press
Specialty Public Health
Date 2021 Jun 7
PMID 34093042
Citations 5
Authors
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Abstract

Introduction: Electrolyte disorders are common among hospitalized patients with acute kidney injury (AKI) and adversely affect the outcome. This study aimed to explore the potential role of abnormal electrolyte levels on predicting AKI and severe AKI.

Methods: In this retrospective, observational study, we included all hospitalized patients in our hospital in China from October 01, 2014, to September 30, 2015. Since only a few patients had arterial blood gas analysis (ABG), all subjects involved were divided into two groups: patients with ABG and patients without ABG. Severe AKI was defined as AKI stage 2 or 3 according to KDIGO guideline.

Results: A total of 80,091 patients were enrolled retrospectively and distributed randomly into the test cohort and the validation cohort (2:1). Logistic regression was performed in the test cohort to analyze risk factors including electrolyte disorders and elucidate the association. The test data (derivation cohort) led to AUC values of 0.758 (95% CI: 0.743-0.773; AKI with ABG), 0.751 (95% CI: 0.740-0.763; AKI without ABG), 0.733 (95% CI: 0.700-0.767; severe AKI with ABG), 0.853 (95% CI: 0.824-0.882; severe AKI without ABG). Application of the scoring system in the validation cohort led to AUC values of 0.724 (95% CI: 0.703-0.744; AKI with ABG), 0.738 (95% CI: 0.721-0.755; AKI without ABG), 0.774 (95% CI: 0.732-0.815; severe AKI with ABG), 0.794 (95% CI: 0.760-0.827; severe AKI without ABG). Hosmer-Lemeshow tests revealed a good calibration.

Conclusion: The risk scoring systems involving electrolyte disorders were established and validated adequately efficient to predict AKI and severe AKI in hospitalized patients. Electrolyte imbalance needs to be carefully monitored and corrections should be made on time to avoid further adverse outcome.

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References
1.
Rothman K . Disengaging from statistical significance. Eur J Epidemiol. 2016; 31(5):443-4. DOI: 10.1007/s10654-016-0158-2. View

2.
Hu J, Wang Y, Geng X, Chen R, Xu X, Zhang X . Metabolic acidosis as a risk factor for the development of acute kidney injury and hospital mortality. Exp Ther Med. 2017; 13(5):2362-2374. PMC: 5443206. DOI: 10.3892/etm.2017.4292. View

3.
Matheny M, Miller R, Ikizler T, Waitman L, Denny J, Schildcrout J . Development of inpatient risk stratification models of acute kidney injury for use in electronic health records. Med Decis Making. 2010; 30(6):639-50. PMC: 4850549. DOI: 10.1177/0272989X10364246. View

4.
Bennett M, Dent C, Ma Q, Dastrala S, Grenier F, Workman R . Urine NGAL predicts severity of acute kidney injury after cardiac surgery: a prospective study. Clin J Am Soc Nephrol. 2008; 3(3):665-73. PMC: 2386703. DOI: 10.2215/CJN.04010907. View

5.
Jones D, HAYSLETT J . Outcome of pregnancy in women with moderate or severe renal insufficiency. N Engl J Med. 1996; 335(4):226-32. DOI: 10.1056/NEJM199607253350402. View