Development of predisposition, injury, response, organ failure model for predicting acute kidney injury in acute on chronic liver failure.

Abstract

BACKGROUND AND AIM:

There is limited data on predictors of acute kidney injury in acute on chronic liver failure. We developed a PIRO model (Predisposition, Injury, Response, Organ failure) for predicting acute kidney injury in a multicentric cohort of acute on chronic liver failure patients.

PATIENTS AND METHODS:

Data of 2360 patients from APASL-ACLF Research Consortium (AARC) was analysed. Multivariate logistic regression model (PIRO score) was developed from a derivation cohort (n=1363) which was validated in another prospective multicentric cohort of acute on chronic liver failure patients (n=997).

RESULTS:

Factors significant for P component were serum creatinine[(≥2 mg/dL)OR 4.52, 95% CI (3.67-5.30)], bilirubin [(<12 mg/dL,OR 1) vs (12-30 mg/dL,OR 1.45, 95% 1.1-2.63) vs (≥30 mg/dL,OR 2.6, 95% CI 1.3-5.2)], serum potassium [(<3 mmol/LOR-1) vs (3-4.9 mmol/L,OR 2.7, 95% CI 1.05-1.97) vs (≥5 mmol/L,OR 4.34, 95% CI 1.67-11.3)] and blood urea (OR 3.73, 95% CI 2.5-5.5); for I component nephrotoxic medications (OR-9.86, 95% CI 3.2-30.8); for R component,Systemic Inflammatory Response Syndrome,(OR-2.14, 95% CI 1.4-3.3); for O component, Circulatory failure (OR-3.5, 95% CI 2.2-5.5). The PIRO score predicted acute kidney injury with C-index of 0.95 and 0.96 in the derivation and validation cohort. The increasing PIRO score was also associated with mortality (P<.001) in both the derivation and validation cohorts.

CONCLUSIONS:

The PIRO model identifies and stratifies acute on chronic liver failure patients at risk of developing acute kidney injury. It reliably predicts mortality in these patients, underscoring the prognostic significance of acute kidney injury in patients with acute on chronic liver failure.

• Authors: Rakhi Maiwall, Shiv Kumar Sarin, Suman Kumar, Priyanka Jain, Guresh Kumar, Ajeet Singh Bhadoria, Richard Moreau, Chandan Kumar Kedarisetty, Zaigham Abbas, Deepak Amarapurkar, Ankit Bhardwaj, Chhagan Bihari, Amna Subhan Butt, Albert Chan, Yogesh Kumar Chawla, Ashok Chowdhury, RadhaKrishan Dhiman, Abdul Kadir Dokmeci, Hasmik Ghazinyan, Saeed Sadiq Hamid, Dong Joon Kim, Piyawat Komolmit, George K Lau, Guan Huei Lee, Laurentius A Lesmana, Kapil Jamwal, Mamun-Al-Mahtab, Rajendra Prasad Mathur, Suman Lata Nayak, Qin Ning, Viniyendra Pamecha, Diana Alcantara-Payawal, Archana Rastogi, Salimur Rahman, Mohamed Rela, Vivek A Saraswat, Samir Shah, Gamal Shiha, Barjesh Chander Sharma, Manoj Kumar Sharma, Kapil Sharma, Soek Siam Tan, Shivendra Singh Chandel, Chitranshu Vashishtha, Zeeshan A Wani, Man-Fung Yuen, Osamu Yokosuka, Ajay Duseja, Wasim Jafri, Harshad Devarbhavi, C E Eapen, Ashish Goel, Ajit Sood, Jia Ji, Z Duan, Y Chen, of the APASL ACLF Research Consortium (AARC) working party
• Journal: Liver international : official journal of the International Association for the Study of the Liver (Liver Int) Vol. 37 Issue 10 Pg. 1497-1507 (10 2017) ISSN: 1478-3231 [Electronic] United States
• PMID: 28393476 (Publication Type: Journal Article, Multicenter Study, Validation Study)
• Copyright: © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Chemical References

• Biomarkers

Topics

• Acute Kidney Injury (blood, diagnosis, etiology, mortality)
• Acute-On-Chronic Liver Failure (blood, complications, diagnosis, mortality)
• Adult
• Asia
• Biomarkers (blood)
• Decision Support Techniques
• Female
• Humans
• Kaplan-Meier Estimate
• Linear Models
• Logistic Models
• Male
• Middle Aged
• Multivariate Analysis
• Nomograms
• Odds Ratio
• Predictive Value of Tests
• Prognosis
• Prospective Studies
• Reproducibility of Results
• Retrospective Studies
• Risk Assessment
• Risk Factors