Risk Stratification Score to Predict Readmission of Patients With Acute Decompensated Cirrhosis Within 90 Days

Abstract

Background and Aims: Patients with acute decompensated (AD) cirrhosis are frequently readmitted to the hospital. An accurate predictive model for identifying high-risk patients may facilitate the development of effective interventions to reduce readmission rates. Methods: This cohort study of patients with AD cirrhosis was conducted at six tertiary hospitals in China between September 2012 and December 2016 (with 705 patients in the derivation cohort) and between January 2017 and April 2020 (with 251 patients in the temporal validation cohort). Least absolute shrinkage and selection operator Cox regression was used to identify the prognostic factors and construct a nomogram. The discriminative ability, calibration, and clinical net benefit were evaluated based on the C-index, area under the curve, calibration curve, and decision curve analysis. Kaplan-Meier curves were constructed for stratified risk groups, and log-rank tests were used to determine significant differences between the curves. Results: Among 956 patients, readmission rates were 24.58, 42.99, and 51.78%, at 30, 60, and 90 days, respectively. Bacterial infection was the main reason for index hospitalization and readmission. Independent factors in the nomogram included gastrointestinal bleeding [hazard rate (HR): 2.787; 95% confidence interval (CI): 2.221-3.499], serum sodium (HR: 0.955; 95% CI: 0.933-0.978), total bilirubin (HR: 1.004; 95% CI: 1.003-1.005), and international normalized ratio (HR: 1.398; 95% CI: 1.126-1.734). For the convenience of clinicians, we provided a web-based calculator tool (https://cqykdx1111.shinyapps.io/dynnomapp/). The nomogram exhibited good discrimination ability, both in the derivation and validation cohorts. The predicted and observed readmission probabilities were calibrated with reliable agreement. The nomogram demonstrated superior net benefits over other score models. The high-risk group (nomogram score >56.8) was significantly likely to have higher rates of readmission than the low-risk group (nomogram score ≤ 56.8; p < 0.0001). Conclusions: The nomogram is useful for assessing the probability of short-term readmission in patients with AD cirrhosis and to guide clinicians to develop individualized treatments based on risk stratification.

Keywords: acute decompensated cirrhosis; independent predictors; nomogram; readmission; risk stratification.

Figure 1

The nomogram to predict the risk of readmission in patients with acute decompensated cirrhosis.

Figure 2

ROC curves for nomogram. ROC curves of nomogram in derivation cohort (A) and in temporal validation cohort (B). ROC, receiver operating characteristic; AUC, area under the curve.

Figure 3

The calibration curve of nomogram at 30, 60, and 90 days for the derivation cohort (A) and the temporal validation cohort (B). Dashed lines along the 45-degree line through the point of origin represent the perfect calibration models in which the predicted probabilities are identical to the actual probabilities.

Figure 4

Decision curve analysis at 30, 60, and 90 days for the derivation cohort (A–C) and the temporal validation cohort (D–F). The horizontal solid black line represents the assumption that no patients will experience the event, and the solid gray line represents the assumption that all patients will relapse. On decision curve analysis, the readmission nomogram showed superior net benefit compared with other models across a range of threshold probabilities.

Figure 5

Risk group stratification according to bisection of the nomogram predicted readmission in the derivation cohort (A) and the temporal validation cohort (B).