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Derivation and Validation of a Geriatric-Sensitive Perioperative Cardiac Risk Index
Rami Alrezk1,2,3,4, Nicholas Jackson4, Mohanad Al Rezk5
1VA Greater Los Angeles Healthcare System, Los Angeles, CA ramialrezk1@ucla.edu.
Insights
A new Geriatric-Sensitive Cardiac Risk Index (GSCRI) accurately predicts cardiac risk in older surgical patients. This index outperforms existing tools like RCRI and Gupta MICA for the geriatric population.
Area of Science:
- Geriatric Medicine
- Cardiology
- Surgical Risk Assessment
Background:
- Older adults (65+) face elevated cardiac risks during noncardiac surgery.
- Current risk indices (RCRI, Gupta MICA) lack geriatric specificity.
- A novel index is needed to address unique geriatric risk factors.
Purpose of the Study:
- To develop and validate a geriatric-sensitive cardiac risk index.
- To improve prediction of myocardial infarction or cardiac arrest (MICA) in elderly surgical patients.
- To compare the performance of the new index against existing tools.
Main Methods:
- Utilized the National Surgical Quality Improvement Program (NSQIP) 2013 geriatric cohort for model development (N=584,931).
- Validated the index on the NSQIP 2012 geriatric cohort (N=485,426).
- Employed Least Angle Shrinkage and Selection Operator regression for variable selection.
Main Results:
- The Geriatric-Sensitive Cardiac Risk Index (GSCRI) achieved an AUC of 0.76 in the validation cohort.
- GSCRI significantly outperformed RCRI (AUC=0.63) and Gupta MICA (AUC=0.70) in geriatric patients.
- Gupta MICA showed significant underestimation (≈17%) of risk in this population.
Conclusions:
- The GSCRI demonstrates superior accuracy in predicting cardiac risk for geriatric patients undergoing noncardiac surgery.
- The GSCRI offers a more reliable risk assessment tool for this vulnerable patient group.
- This index addresses the limitations of current risk prediction models in the elderly.
Background:
Surgical patients aged 65 and over face a higher risk of cardiac complications from noncardiac surgery. The Revised Cardiac Risk Index (RCRI) and the Gupta Myocardial Infarction or Cardiac Arrest (MICA) calculator are widely used to predict this risk, but they are not specifically designed to predict MICA in geriatric patients. Our hypothesis is that a new geriatric-sensitive index, derived from geriatric data, will capture this population's unique response to risk factors.
Methods And Results:
The model was developed using the NSQIP (National Surgical Quality Improvement Program) 2013 geriatric cohort (N=584,931) (210,914 age ≥65) and validated on the NSQIP 2012 geriatric cohort (N= 485,426) (172,905 age ≥65). Least Angle Shrinkage and Selection Operator regression was used for initial variable selection. The Geriatric-Sensitive Cardiac Risk Index (GSCRI) was then evaluated in the 2012 data set. The area under the curve (AUC) was compared among the GSCRI, RCRI, and Gupta MICA in the 2012 data set. The GSCRI had an AUC of 0.76 in the validation cohort among geriatric patients. When the Gupta MICA was tested on geriatric patients in the validation cohort, a significant deterioration (≈17%) was noted, as well as a significant underestimation of the risk. The GSCRI AUC of 0.76 in the geriatric subset was significantly greater (P<0.001) than those in the RCRI (AUC=0.63) or Gupta MICA (AUC=0.70) models, outperforming the RCRI and Gupta MICA models in geriatric patients by 13% and 6%, respectively, with a ΔAUC and P-value of 0.13 (P<0.001), and 0.06 (P<0.001).
Conclusions:
The GSCRI is a significantly better predictor of cardiac risk in geriatric patients undergoing noncardiac surgery.
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