Smart-2d: a novel scoring system to predict non diagnostic exercise stress echocardiography in renal transplant candidates.

Abstract

Background: Exercise stress echocardiography (ESE) is often used for pre-renal transplant risk stratification. Nearly 20% of ESE may be non-diagnostic, resulting in delays to transplant and increased healthcare cost. A simple, reliable tool for predicting non-diagnostic ESE may streamline assessment. Method(s): Retrospective analysis of 898 kidney transplant candidates between 2013-2020 who underwent exercise stress echocardiography for pre-transplant cardiovascular assessment was performed. The cohort was separated into a derivation and validation set. Multivariable logistic regression identified predictors of non-diagnostic ESE. Covariates associated with non-diagnostic ESE (p<0.10) on univariate analysis were included in the multivariable model. From this model, only variables with p<0.05 were included for score development. Model discrimination was assessed by area under the receiver operating curve (AUROC). Result(s): Non-diagnostic ESE occurred in 17% (151/898). Predictors of non-diagnostic study formed the scoring system: 1 point for female sex, 2 points for BMI >40, 1 point for age >55, Heart Rate<55 4 points, <65 3 points and <75 2 points. LV Hypertrophy was assigned 2 points, Type 1 Diabetes 3 points and Type 2 diabetes 1 point, LV Dysfunction was assigned 2 points. This scoring system had excellent discriminative ability (derivation AUROC 0.80, validation AUROC 0.81). A score of 8 or more had a specificity of 97% and a positive likelihood ratio of 9.4 for non-diagnostic ESE. A score of <8 had a negative predictive value of 86%. Patients with Non-Diagnostic ESE had longer time to transplantation (695 vs 636 days), and more investigations performed (43.05% vs 17.94%, p<0.001) and less likely to receive a renal transplant (OR 0.47, p<0.001). Conclusion(s): Non diagnostic ESE in pre-transplant assessment causes significant delays to patient care. A simple clinical scoring system may identify patients likely to have non-diagnostic ESE and can be utilised to identify patients who may benefit from alternative risk-stratification investigations. (Table Presented).