BM. Fernandez-Felix, L. Varela Barca, E. Garcia-Esquinas... J. Zamora. Prognostic models for mortality after cardiac surgery in patients with infective endocarditis: a systematic review and aggregation of prediction models

Clin Microbiol Infect. 2021

"A new calculator to predict mortality in patients with infective endocarditis could save lives" - Borja M. Fernández Félix and Javier Zamora

Summary:

Background: There are several prognostic models to estimate the risk of mortality after surgery for active infective endocarditis (IE). However, these models incorporate different predictors and their performance is uncertain.

Objective: We systematically reviewed and critically appraised all available prediction models of post-operative mortality in patients undergoing surgery for IE, and aggregated them into a meta-model. Data sources: We searched Medline and EMBASE databases from inception to June 2020.Study eligibility criteria: We included studies that developed or updated a prognostic model of post-operative mortality in patient with IE.

Methods: We assessed the risk of bias of the models using PROBAST (Prediction model Risk Of Bias ASsessment Tool) and we aggregated them into an aggregate meta-model based on stacked regressions and optimized it for a nationwide registry of IE patients. The meta-model performance was assessed using bootstrap validation methods and adjusted for optimism.

Results: We identified 11 prognostic models for postoperative mortality. Eight models had a high risk of bias. The meta-model included weighted predictors from the remaining three models (EndoSCORE, specific ES-I and specific ES-II), which were not rated as high risk of bias and provided full model equations. Additionally, two variables (age and infectious agent) that had been modelled differently across studies, were estimated based on the nationwide registry. The performance of the meta-model was better than the original three models, with the corresponding performance measures: C-statistic 0.79 (95% CI 0.76; 0.82), calibration slope 0.98 (95% CI 0.86; 1.13) and calibration-in-the-large -0.05(95% CI -0.20;0.11).

Conclusions: The meta-model outperformed published models and showed a robust predictive capacity for predicting the individualized risk of postoperative mortality in patients with IE.

Why do you highlight this publication?

The meta-model online calculator has been developed and internally validated following a robust methodology which allows us to aggregate the best available evidence using a wide-national registry of endocarditis. Results shown that the meta-model outperform existing models. The tool, freely available online, will be useful for clinicians in making-decisions and will individualize the risk profile of the patients.

Borja M. Fernández Félix & Dr. Javier Zamora
Clinical Biostatistics Unit
Hospital Universitario Ramón y Cajal

Epidemiology and Clinical Biostatistics
IRYCIS

Dr. Javier Zamora and Borja M. Fernández Félix, authors of the publication

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