VBHOM, a data economic model for predicting the outcome after open abdominal aortic aneurysm surgery

Area of Science:

• Vascular Surgery
• Medical Informatics
• Biostatistics

Background:

• Vascular Biochemistry and Haematology Outcome Models (VBHOM) utilize minimum data sets for outcome prediction.
• This study evaluated the VBHOM approach in patients undergoing abdominal aortic aneurysm (AAA) repair.
• The model was tested on both elective and non-elective AAA repair cohorts.

Purpose of the Study:

• To validate a predictive model for in-hospital mortality in patients undergoing AAA repair.
• To assess the accuracy of the VBHOM using a prospective cohort.
• To determine if a single model could predict outcomes for both elective and emergency AAA surgery.

Main Methods:

• A binary logistic regression model was developed using data from the UK National Vascular Database (NVD).
• The model incorporated routine clinical data: serum urea, sodium, potassium, hemoglobin, white cell count, sex, age, and admission mode.
• Prospective validation was performed using the Hosmer-Lemeshow methodology on a separate patient cohort.

Main Results:

• The validation cohort included 327 patients (208 elective, 119 emergency AAA repair).
• The VBHOM accurately predicted outcomes for both elective and non-elective AAA repair using a single model.
• The model showed good discrimination (c-index = 0.852) with no significant lack of fit (P = 0.590).

Conclusions:

• The VBHOM approach offers an advantage due to its reliance on simple, routinely collected clinical data.
• These VBHOM data items can potentially predict individual patient risk prior to aneurysm surgery.
• The validated model demonstrates clinical utility for risk stratification in AAA repair.