Development and Validation of a Model to Predict Acute Kidney Injury in Hospitalized Patients With Cirrhosis

Kavish R. Patidar, Chenjia Xu, Hani Shamseddeen, Yao Wen Cheng, Marwan S. Ghabril, V. V.Pavan K. Mukthinuthalapati, Zachary P. Fricker, Samuel Akinyeye, Lauren D. Nephew, Archita P. Desai, Melissa Anderson, Tarek M. El-Achkar, Naga P. Chalasani, Eric S. Orman

Research output: Contribution to journalArticle

Abstract

OBJECTIVES: Acute kidney injury (AKI) is a common complication in hospitalized patients with cirrhosis which contributes to morbidity and mortality. Improved prediction of AKI in this population is needed for prevention and early intervention. We developed a model to identify hospitalized patients at risk for AKI. METHODS: Admission data from a prospective cohort of hospitalized patients with cirrhosis without AKI on admission (n = 397) was used for derivation. AKI development in the first week of admission was captured. Independent predictors of AKI on multivariate logistic regression were used to develop the prediction model. External validation was performed on a separate multicenter cohort (n = 308). RESULTS: In the derivation cohort, the mean age was 57 years, the Model for End-Stage Liver Disease score was 17, and 59 patients (15%) developed AKI after a median of 4 days. Admission creatinine (OR: 2.38 per 1 mg/dL increase [95% CI: 1.47-3.85]), international normalized ratio (OR: 1.92 per 1 unit increase [95% CI: 1.92-3.10]), and white blood cell count (OR: 1.09 per 1 × 10/L increase [95% CI: 1.04-1.15]) were independently associated with AKI. These variables were used to develop a prediction model (area underneath the receiver operator curve: 0.77 [95% CI: 0.70-0.83]). In the validation cohort (mean age of 53 years, Model for End-Stage Liver Disease score of 16, and AKI development of 13%), the area underneath the receiver operator curve for the model was 0.70 (95% CI: 0.61-0.78). DISCUSSION: A model consisting of admission creatinine, international normalized ratio, and white blood cell count can identify patients with cirrhosis at risk for in-hospital AKI development. On further validation, our model can be used to apply novel interventions to reduce the incidence of AKI among patients with cirrhosis who are hospitalized.

Original languageEnglish (US)
Pages (from-to)e00075
JournalClinical and translational gastroenterology
Volume10
Issue number9
DOIs
StatePublished - Sep 1 2019
Externally publishedYes

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Acute Kidney Injury
Fibrosis
End Stage Liver Disease
International Normalized Ratio
Leukocyte Count
Creatinine
Logistic Models
Morbidity
Mortality
Incidence

ASJC Scopus subject areas

  • Gastroenterology

Cite this

Patidar, K. R., Xu, C., Shamseddeen, H., Cheng, Y. W., Ghabril, M. S., Mukthinuthalapati, V. V. P. K., ... Orman, E. S. (2019). Development and Validation of a Model to Predict Acute Kidney Injury in Hospitalized Patients With Cirrhosis. Clinical and translational gastroenterology, 10(9), e00075. https://doi.org/10.14309/ctg.0000000000000075

Development and Validation of a Model to Predict Acute Kidney Injury in Hospitalized Patients With Cirrhosis. / Patidar, Kavish R.; Xu, Chenjia; Shamseddeen, Hani; Cheng, Yao Wen; Ghabril, Marwan S.; Mukthinuthalapati, V. V.Pavan K.; Fricker, Zachary P.; Akinyeye, Samuel; Nephew, Lauren D.; Desai, Archita P.; Anderson, Melissa; El-Achkar, Tarek M.; Chalasani, Naga P.; Orman, Eric S.

In: Clinical and translational gastroenterology, Vol. 10, No. 9, 01.09.2019, p. e00075.

Research output: Contribution to journalArticle

Patidar, KR, Xu, C, Shamseddeen, H, Cheng, YW, Ghabril, MS, Mukthinuthalapati, VVPK, Fricker, ZP, Akinyeye, S, Nephew, LD, Desai, AP, Anderson, M, El-Achkar, TM, Chalasani, NP & Orman, ES 2019, 'Development and Validation of a Model to Predict Acute Kidney Injury in Hospitalized Patients With Cirrhosis', Clinical and translational gastroenterology, vol. 10, no. 9, pp. e00075. https://doi.org/10.14309/ctg.0000000000000075
Patidar, Kavish R. ; Xu, Chenjia ; Shamseddeen, Hani ; Cheng, Yao Wen ; Ghabril, Marwan S. ; Mukthinuthalapati, V. V.Pavan K. ; Fricker, Zachary P. ; Akinyeye, Samuel ; Nephew, Lauren D. ; Desai, Archita P. ; Anderson, Melissa ; El-Achkar, Tarek M. ; Chalasani, Naga P. ; Orman, Eric S. / Development and Validation of a Model to Predict Acute Kidney Injury in Hospitalized Patients With Cirrhosis. In: Clinical and translational gastroenterology. 2019 ; Vol. 10, No. 9. pp. e00075.
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abstract = "OBJECTIVES: Acute kidney injury (AKI) is a common complication in hospitalized patients with cirrhosis which contributes to morbidity and mortality. Improved prediction of AKI in this population is needed for prevention and early intervention. We developed a model to identify hospitalized patients at risk for AKI. METHODS: Admission data from a prospective cohort of hospitalized patients with cirrhosis without AKI on admission (n = 397) was used for derivation. AKI development in the first week of admission was captured. Independent predictors of AKI on multivariate logistic regression were used to develop the prediction model. External validation was performed on a separate multicenter cohort (n = 308). RESULTS: In the derivation cohort, the mean age was 57 years, the Model for End-Stage Liver Disease score was 17, and 59 patients (15{\%}) developed AKI after a median of 4 days. Admission creatinine (OR: 2.38 per 1 mg/dL increase [95{\%} CI: 1.47-3.85]), international normalized ratio (OR: 1.92 per 1 unit increase [95{\%} CI: 1.92-3.10]), and white blood cell count (OR: 1.09 per 1 × 10/L increase [95{\%} CI: 1.04-1.15]) were independently associated with AKI. These variables were used to develop a prediction model (area underneath the receiver operator curve: 0.77 [95{\%} CI: 0.70-0.83]). In the validation cohort (mean age of 53 years, Model for End-Stage Liver Disease score of 16, and AKI development of 13{\%}), the area underneath the receiver operator curve for the model was 0.70 (95{\%} CI: 0.61-0.78). DISCUSSION: A model consisting of admission creatinine, international normalized ratio, and white blood cell count can identify patients with cirrhosis at risk for in-hospital AKI development. On further validation, our model can be used to apply novel interventions to reduce the incidence of AKI among patients with cirrhosis who are hospitalized.",
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AU - Patidar, Kavish R.

AU - Xu, Chenjia

AU - Shamseddeen, Hani

AU - Cheng, Yao Wen

AU - Ghabril, Marwan S.

AU - Mukthinuthalapati, V. V.Pavan K.

AU - Fricker, Zachary P.

AU - Akinyeye, Samuel

AU - Nephew, Lauren D.

AU - Desai, Archita P.

AU - Anderson, Melissa

AU - El-Achkar, Tarek M.

AU - Chalasani, Naga P.

AU - Orman, Eric S.

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N2 - OBJECTIVES: Acute kidney injury (AKI) is a common complication in hospitalized patients with cirrhosis which contributes to morbidity and mortality. Improved prediction of AKI in this population is needed for prevention and early intervention. We developed a model to identify hospitalized patients at risk for AKI. METHODS: Admission data from a prospective cohort of hospitalized patients with cirrhosis without AKI on admission (n = 397) was used for derivation. AKI development in the first week of admission was captured. Independent predictors of AKI on multivariate logistic regression were used to develop the prediction model. External validation was performed on a separate multicenter cohort (n = 308). RESULTS: In the derivation cohort, the mean age was 57 years, the Model for End-Stage Liver Disease score was 17, and 59 patients (15%) developed AKI after a median of 4 days. Admission creatinine (OR: 2.38 per 1 mg/dL increase [95% CI: 1.47-3.85]), international normalized ratio (OR: 1.92 per 1 unit increase [95% CI: 1.92-3.10]), and white blood cell count (OR: 1.09 per 1 × 10/L increase [95% CI: 1.04-1.15]) were independently associated with AKI. These variables were used to develop a prediction model (area underneath the receiver operator curve: 0.77 [95% CI: 0.70-0.83]). In the validation cohort (mean age of 53 years, Model for End-Stage Liver Disease score of 16, and AKI development of 13%), the area underneath the receiver operator curve for the model was 0.70 (95% CI: 0.61-0.78). DISCUSSION: A model consisting of admission creatinine, international normalized ratio, and white blood cell count can identify patients with cirrhosis at risk for in-hospital AKI development. On further validation, our model can be used to apply novel interventions to reduce the incidence of AKI among patients with cirrhosis who are hospitalized.

AB - OBJECTIVES: Acute kidney injury (AKI) is a common complication in hospitalized patients with cirrhosis which contributes to morbidity and mortality. Improved prediction of AKI in this population is needed for prevention and early intervention. We developed a model to identify hospitalized patients at risk for AKI. METHODS: Admission data from a prospective cohort of hospitalized patients with cirrhosis without AKI on admission (n = 397) was used for derivation. AKI development in the first week of admission was captured. Independent predictors of AKI on multivariate logistic regression were used to develop the prediction model. External validation was performed on a separate multicenter cohort (n = 308). RESULTS: In the derivation cohort, the mean age was 57 years, the Model for End-Stage Liver Disease score was 17, and 59 patients (15%) developed AKI after a median of 4 days. Admission creatinine (OR: 2.38 per 1 mg/dL increase [95% CI: 1.47-3.85]), international normalized ratio (OR: 1.92 per 1 unit increase [95% CI: 1.92-3.10]), and white blood cell count (OR: 1.09 per 1 × 10/L increase [95% CI: 1.04-1.15]) were independently associated with AKI. These variables were used to develop a prediction model (area underneath the receiver operator curve: 0.77 [95% CI: 0.70-0.83]). In the validation cohort (mean age of 53 years, Model for End-Stage Liver Disease score of 16, and AKI development of 13%), the area underneath the receiver operator curve for the model was 0.70 (95% CI: 0.61-0.78). DISCUSSION: A model consisting of admission creatinine, international normalized ratio, and white blood cell count can identify patients with cirrhosis at risk for in-hospital AKI development. On further validation, our model can be used to apply novel interventions to reduce the incidence of AKI among patients with cirrhosis who are hospitalized.

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