Clinical Data for Infective Endocarditis Mortality Nomogram

A clinical study dataset of 383 patients with infective endocarditis was used to develop a nomogram predicting 1-year mortality. The model, created by Zhaojun Yu, identified five independent prognostic factors and achieved an AUC of 0.965 in the training cohort.

Use Cases

• Validate the published nomogram model using the five identified factors: age, heart failure, embolic events, vegetation diameter >10 mm, and surgical treatment.
• Replicate the multivariate Cox regression analysis to assess the hazard ratios for the five independent prognostic factors.
• Perform decision curve analysis to evaluate the clinical utility of mortality predictions based on the study's patient cohort.

Strengths

• Model validation on a distinct cohort of 115 patients, with a reported AUC of 0.939.
• Five statistically significant prognostic factors identified with hazard ratios and confidence intervals (e.g., heart failure HR=5.759).
• Clinical data from 383 confirmed infective endocarditis patients, split into training and validation sets.

Limitations

• The dataset is small, containing only 383 patient records, which limits the generalizability of findings.
• Data is presented in a DOCX document, requiring manual extraction for computational analysis.
• The specific clinical variables and raw patient-level data are not detailed, only the final model factors.

Provenance

Source

Zhaojun Yu via figshare.

Collection Method

Retrospective analysis of clinical data from confirmed infective endocarditis patients.

Freshness

Last updated in March 2026.