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Published on: September 22, 2020
A mortality prediction model for elderly patients with critical limb ischemia
Joost P Roijers1, Yannick S Rakké1, Cornelis J Hopmans1
1Department of Surgery, Amphia Hospital Breda, Breda, The Netherlands.
Insights
A new model predicts 6-month survival for elderly patients with critical limb ischemia (CLI) undergoing treatment. Key factors include age, nursing home residence, physical impairment, and ASA class, aiding shared decision-making.
Area of Science:
- Vascular Surgery
- Geriatric Medicine
- Health Outcomes Research
Background:
- Predictive models for critical limb ischemia (CLI) are crucial for shared decision-making but often lack widespread clinical adoption.
- Existing models may not adequately represent elderly populations undergoing revascularization procedures.
Purpose of the Study:
- To develop and validate a 6-month survival prediction model specifically for elderly patients (≥65 years) with CLI undergoing surgical or endovascular treatment.
- To identify key predictors of short-term mortality in this vulnerable patient group.
Main Methods:
- An observational cohort study included 449 elderly patients with CLI treated between January 2013 and June 2018.
- A multivariable Cox proportional hazards regression and penalized likelihood method were used to construct the survival model.
- Model performance was assessed using the area under the receiver operating characteristic curve (AUC).
Main Results:
- The study included 449 patients (median age 76 years, 52.8% male), with 67.5% receiving surgical and 32.5% endovascular treatment.
- The 6-month survival rate was estimated at 80% (SE, 1.9%).
- Factors strongly associated with 6-month mortality included advanced age, nursing home residence, physical impairment, and American Society of Anesthesiologists (ASA) class. The AUC for the 6-month mortality model was 0.81.
Conclusions:
- A validated prediction model for 6-month mortality in elderly CLI patients undergoing treatment was developed.
- Age, nursing home residence, physical impairment, and ASA class are significant predictors of increased mortality risk.
- These identified factors can assist clinicians in risk stratification and shared decision-making for elderly CLI patients.
Objective:
To aid physicians in the process of shared decision-making, many predictive models for critical limb ischemia (CLI) have been constructed. However, none of these models is in widespread use. Predicting survival outcomes for a specific individual may be used to guide treatment selection. The aim of this study was to construct a 6-month survival-predicting model representative of elderly patients with CLI undergoing surgical or endovascular treatment.
Methods:
An observational cohort study including all patients with CLI aged ≥65 years who underwent surgical or endovascular treatment of CLI between January 2013 and June 2018 was conducted. The model to predict survival at 6 months was based on a multivariable Cox proportional hazards regression model and a penalized likelihood method. The performance of the model was judged by means of the area under the receiver operating characteristic curve.
Results:
In total, 449 patients were included in the study population. The median age was 76 years (range, 65-97 years), and 52.8% of the population was male. Surgical treatment was performed in 303 patients (67.5%), and 146 underwent endovascular treatment (32.5%). The estimated 30-day survival was 92.7% (standard error [SE], 1.2%); 6-month survival, 80% (SE, 1.9%); and 12-month survival, 71% (SE, 2.1%). Variables with the strongest association with 6-month mortality were age, living in a nursing home, physical impairment, and American Society of Anesthesiologists class. The area under the receiver operating characteristic curve of the 6-month mortality model was 0.81 (95% confidence interval, 0.76-0.85; P < .001).
Conclusions:
A prediction model constructed for 6-month mortality of elderly patients undergoing surgical or endovascular treatment of CLI showed that age, living in a nursing home, physical impairment, and American Society of Anesthesiologists class have the highest association with an increase in mortality. These factors may be used to identify patients at risk for mortality in shared decision-making.
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