# A New Risk Score for Predicting Postoperative Mortality in Suspected Heart Failure Patients Undergoing Valvular Surgery

## TL;DR

This study developed a new risk score to predict post-surgery death rates in heart failure patients undergoing valve surgery, showing better accuracy than existing tools.

## Contribution

A novel risk score model with 9 predictors was developed and validated for predicting postoperative mortality in suspected heart failure patients.

## Key findings

- The new risk score ranged from 0 to 19 and showed strong calibration and discrimination in both training and testing groups.
- The model outperformed EuroSCORE II in predicting postoperative mortality with higher AUC values in both groups.
- Observed and predicted mortality rates increased significantly with higher risk scores.

## Abstract

Heart failure (HF) is one of the most
important indications of the severity of valvular heart disease (VHD). VHD with
HF is frequently associated with a higher surgical risk. Our study sought to
develop a risk score model to predict the postoperative mortality of suspected HF
patients after valvular surgery.

Between January 2016 and
December 2018, all consecutive adult patients suspected of HF and undergoing
valvular surgery in the Chinese Cardiac Surgery Registry (CCSR) database were
included. Finally, 14,645 patients (55.39 ± 11.6 years, 43.5% female) were
identified for analysis. As a training group for model derivation, we used
patients who had surgery between January 2016 and May 2018 (11,292 in total). To
validate the model, patients who underwent surgery between June 2018 and December
2018 (a total of 3353 patients) were included as a testing group. In training
group, we constructed and validated a scoring system to predict postoperative
mortality using multivariable logistic regression and bootstrapping method (1000
re-samples). We validated the scoring model in the testing group. Brier score and
calibration curves using bootstrapping with 1000 re-samples were used to evaluate
the calibration. The area under the receiver operating characteristic curve
(AUROC) was used to evaluate the discrimination. The results were also compared
to EuroSCORE II.

The final score ranged from 0 to 19 points and
involved 9 predictors: age ≥60 years; New York Heart Association Class
(NYHA) IV; left ventricular ejection fraction (LVEF) <35%; estimated
glomerular filtration rate (eGFR) <50 mL/min/1.73 m2; preoperative
dialysis; Left main artery stenosis; non-elective surgery; cardiopulmonary bypass
(CPB) time >200 minutes and perioperative transfusion. In training group,
observed and predicted postoperative mortality rates increased from 0% to 45.5%
and from 0.8% to 50.3%, respectively, as the score increased from 0 up to
≥10 points. The scoring model’s Brier scores in the training and testing
groups were 0.0279 and 0.0318, respectively. The area under the curve (AUC)
values of the scoring model in both the training and testing groups were 0.776,
which was significantly higher than EuroSCORE II in both the training (AUC =
0.721, Delong test, p < 0.001) and testing (AUC = 0.669, Delong test,
p < 0.001) groups.

The new risk score is an
effective and concise tool that could accurately predict postoperative mortality
rates in suspected HF patients after valve surgery.