Format

Send to

Choose Destination
Diabetes Care. 2020 Apr;43(4):852-859. doi: 10.2337/dc19-2057. Epub 2020 Feb 6.

Predicting 10-Year Risk of End-Organ Complications of Type 2 Diabetes With and Without Metabolic Surgery: A Machine Learning Approach.

Author information

1
Department of General Surgery, Bariatric & Metabolic Institute, Cleveland Clinic, Cleveland, OH aminiaa@ccf.org.
2
Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH.
3
Kaiser Permanente Washington Health Research Institute, Seattle, WA.
4
Department of Cardiovascular Medicine, Cleveland Clinic Coordinating Center for Clinical Research, Cleveland Clinic, Cleveland, OH.
5
Department of General Surgery, Bariatric & Metabolic Institute, Cleveland Clinic, Cleveland, OH.
6
Department of Surgery, The Ohio State University Wexner Medical Center, Columbus, OH.
7
Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA.

Abstract

OBJECTIVE:

To construct and internally validate prediction models to estimate the risk of long-term end-organ complications and mortality in patients with type 2 diabetes and obesity that can be used to inform treatment decisions for patients and practitioners who are considering metabolic surgery.

RESEARCH DESIGN AND METHODS:

A total of 2,287 patients with type 2 diabetes who underwent metabolic surgery between 1998 and 2017 in the Cleveland Clinic Health System were propensity-matched 1:5 to 11,435 nonsurgical patients with BMI ≥30 kg/m2 and type 2 diabetes who received usual care with follow-up through December 2018. Multivariable time-to-event regression and random forest machine learning models were built and internally validated using fivefold cross-validation to predict the 10-year risk for four outcomes of interest. The prediction models were programmed to construct user-friendly web-based and smartphone applications of Individualized Diabetes Complications (IDC) Risk Scores for clinical use.

RESULTS:

The prediction tools demonstrated the following discrimination ability based on the area under the receiver operating characteristic curve (1 = perfect discrimination and 0.5 = chance) at 10 years in the surgical and nonsurgical groups, respectively: all-cause mortality (0.79 and 0.81), coronary artery events (0.66 and 0.67), heart failure (0.73 and 0.75), and nephropathy (0.73 and 0.76). When a patient's data are entered into the IDC application, it estimates the individualized 10-year morbidity and mortality risks with and without undergoing metabolic surgery.

CONCLUSIONS:

The IDC Risk Scores can provide personalized evidence-based risk information for patients with type 2 diabetes and obesity about future cardiovascular outcomes and mortality with and without metabolic surgery based on their current status of obesity, diabetes, and related cardiometabolic conditions.

PMID:
32029638
DOI:
10.2337/dc19-2057

Supplemental Content

Full text links

Icon for HighWire
Loading ...
Support Center