Pre-Interventional Risk Assessment in The Elderly (PIRATE): Development of a scoring system to predict 30-day mortality using data of the Peri-Interventional Outcome Study in the Elderly

Abstract

Risk assessment before interventions in elderly patients becomes more and more vital due to an increasing number of elderly patients requiring surgery. Existing risk scores are often not tailored to marginalized groups such as patients aged 80 years or older. We aimed to develop an easy-to-use and readily applicable risk assessment tool that implements pre-interventional predictors of 30-day mortality in elderly patients (≥80 years) undergoing interventions under anesthesia. Using Cox regression analysis, we compared different sets of predictors by taking into account their ease of availability and by evaluating predictive accuracy. Coefficient estimates were utilized to set up a scoring system that was internally validated. Model building and evaluation were based on data from the Peri-Interventional Outcome Study in the Elderly (POSE), which was conducted as a European multicenter, observational prospective cohort study. Our risk assessment tool, named PIRATE, contains three predictors assessable at admission (urgency, severity and living conditions). Discriminatory power, as measured by the concordance index, was 0.75. The estimated prediction error, as measured by the Brier score, was 0.036 (covariate-free reference model: 0.043). PIRATE is an easy-to-use risk assessment tool that helps stratifying elderly patients undergoing interventions with anesthesia at increased risk of mortality. PIRATE is readily available and applies to a wide variety of settings. In particular, it covers patients needing elective or emergency surgery and undergoing in-hospital or day-case surgery. Also, it applies to all types of interventions, from minor to major. It may serve as a basis for multidisciplinary and informed shared decision-making.

Fig 1. Development of PIRATE.

(A) Mean C-index values that were obtained from applying the models in Step 1 to the 100 different training data sets. There was an upwards trend in prediction accuracy as the number of predictors increased in each model. (B) Permutation importance of the ten initially available predictors in Step 2. Permutation importance was defined as the difference between the C-index values obtained from the full model (from Step 0) with original data and the model(s) with permuted data. (C) Stepwise evaluation of the mean C-index from Step 0 (full model) to Step 5 (PIRATE).

Fig 2. Calibration plots.

Calibration plots for six exemplary validation cohorts. The plots depict the predicted probabilities based on the scoring system versus the Kaplan-Meier estimates in subgroups.

Fig 3. Evaluation of the PIRATE tool.

(A) Distribution of the risk score values. The grey bars represent the relative frequencies of the risk score values in the full POSE cohort, the black line represents the respective estimated probabilities obtained from PIRATE, and the blue line refers to the death probabilities (one minus Kaplan-Meier estimates) for patients having the respective score. (B) Stratified Kaplan-Meier estimates in subgroups. Groups were defined by the 25%, 50% and 75% percentiles of the risk score values in POSE. The non-overlapping survival curves reflect the score’s ability to distinguish among high risk and low risk patients.