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Assessment of the renal angina index in patients hospitalized in a cardiac intensive care unit – Scientific Reports

Study design

This study was conducted in the Department of Cardiology, Fujita Health University School of Medicine (Toyoake, Japan). The Ethics Committee of Fujita Health University approved this study (study protocol number: HM19-264), which was conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all the patients.

Patients hospitalized in CICUs between November 2009 and December 2018 were enrolled in this study. Patients who had the following characteristics were excluded from participation: (1) age under 18 years; (2) absence of serum creatinine (SCr), N-terminal pro-B-type natriuretic peptide (NT-proBNP), or left ventricular ejection fraction (LVEF) data; (3) stage 5 chronic kidney disease (CKD); (4) stay in the CICU < 24 h; and (5) history of kidney transplantation. Physicians independently selected the appropriate therapy and managed the patients following standard protocols using outcome measurements as feedback, such as improvement in symptoms, physical examination findings, laboratory data, pulmonary congestion on chest radiography, and echocardiographic findings. Clinical characteristics were obtained from the patients’ medical records upon enrollment.

Definitions and calculations

AKI was diagnosed under the Kidney Disease: Improving Global Outcomes (KDIGO) criteria, as an increase in SCr by ≥ 0.3 mg/dL within 48 h or an increase in SCr to ≥ 1.5 times the baseline within 1 week10. Severe AKI was defined as stage 2 or 3 AKI according to the KDIGO criteria10. KDIGO characterizes stage 2 AKI as a greater than or equal to twofold increase in baseline SCr within 7 days and stage 3 AKI as a greater than or equal to threefold increase in baseline SCr within 7 days, an increase in SCr to greater than or equal to 4 mg/dL within 48 h, or the initiation of renal replacement therapy (RRT). Urinary criteria were not used to diagnose AKI because of inconsistent data and potential alterations in urine volume induced by medical therapy. The primary endpoint was the development of severe AKI.

The SCr-based estimated glomerular filtration rate (eGFR) was calculated using the CKD-EPI equations11. Incident end-stage kidney disease (ESKD) indicates the initiation of maintenance dialysis therapy, receipt of RRT during hospital stay, or kidney transplantation. CKD was defined as an eGFR of < 60 mL/min/1.73 m2. We routinely performed two-dimensional echocardiography to calculate LVEF using the modified Simpson method.

Renal Angina Index

The previously reported RAI3 was used for patients hospitalized in CICUs (Fig. 1). The RAI was calculated from creatinine and patient condition scores. The creatinine scores were assigned according to the changes in SCr within 24 h after CICU admission as follows: SCr ≥ 0.4 mg/dL, 8 points; SCr ≥ 0.3 mg/dL, 4 points; SCr ≥ 0.1 mg/dL, 2 points; and SCr < 0.1 mg/dL, 1 point. The condition of each patient was scored as follows: ventilation and/or vasopressor therapy, 5 points; diabetes mellitus, 3 points; and admission to the CICUs, 1 point. The RAI equaled the creatinine score multiplied by the worst patient condition score. Its possible values were 1, 2, 3, 4, 5, 6, 8, 10, 12, 20, 24, and 40.

Figure 1
figure 1

The elements of the RAI. The RAI score was defined as the creatinine score multiplied by the worst patient condition score. CICUs cardiac intensive care units; DM diabetes mellitus; RAI renal angina index.


All patients were clinically followed up for 12 months after study enrollment. The secondary endpoint, judged independently by the researchers, was all-cause mortality. Endpoint data were obtained from hospital charts and telephone interviews with patients. Telephone interviews were conducted by trained reviewers blinded to the study details.

Measurement of biochemical markers

Serum NT-proBNP was measured using an electrochemiluminescence immunoassay with the Cobas e601 system (Roche Diagnostics, Tokyo, Japan). SCr concentration was determined by an enzymatic method using the Liquitech® Creatinine PAP II (Roche Diagnostics, Tokyo, Japan) on admission, daily through day three, and then on day seven.

Statistical methods

JMP version Pro 15 software (SAS Institute Inc., Cary, NC, USA) and R Version 4.2.1 (R Foundation for Statistical Computing, Vienna, Austria) were used for statistical analyses. Data are presented as number and frequency for categorical variables and mean ± standard deviation or median with interquartile ranges for continuous variables.

Clinical characteristics were compared using the chi-squared test for categorical variables and the Mann–Whitney U test and Student’s t test for continuous variables. The odds ratios and 95% confidence intervals (CIs) were calculated for each factor using logistic regression, and all baseline variables (p < 0.05) in the univariate analyses were entered into the multivariate model to determine the independent predictors of severe AKI.

All baseline variables with p < 0.05 in the univariate analyses were integrated into the Cox multivariate model to determine the independent predictors of all-cause mortality. Hazard ratios and 95% CIs were calculated for each factor using Cox proportional hazards analysis. Receiver operating characteristic (ROC) curves were drawn to assess the ability of the RAI to differentiate between patients with and without severe AKI. In ROC analyses, the optimal cutoff value was defined as the level with the largest sum of sensitivity and specificity. We used R software to calculate the area under the ROC curve (AUC) and CIs by the bootstrapping method with 2,000 iterations. To compare different ROC curves from multi variable models without or with RAI, we used a function of roc.test() in the pROC package12. Kaplan–Meier curves were plotted and compared using the log-rank test. Statistical significance was set at p < 0.05.