Clinical Risk Model Research Articles

Validation of two risk models for perioperative mortality in patients undergoing elective abdominal aortic aneurysm surgery.

The authors validated 2 clinical risk models for perioperative mortality in patients scheduled for elective open abdominal aortic aneurysm surgery (AAA surgery). They studied 361 patients who underwent elective AAA surgery between 1991 and 1999 (validation population). Two clinical risk models were validated. The first was developed in 238 patients from Leiden University Hospital (Leiden risk model). The Leiden risk model was modified to provide predictions for the validation population based on 6 predictors including age, gender, a history of previous myocardial infarction, congestive heart failure, renal disease, and pulmonary disease. The second was a recently published simpler risk model developed in 820 patients in the UK Small Aneurysm Trial (UK risk model) and included 3 predictors (age and renal and pulmonary comorbidity). Logistic regression was used to quantify the relationship between predictors and outcome (mortality within 30 days of surgery). Validation further included the concordance statistic (c-statistic) for discriminative ability and the Hosmer-Lemeshow test for model reliability. The perioperative mortality in the validation population was 6.6% (24/361). Predictors had similar odds ratios, with particularly strong effects of congestive heart failure, pulmonary disease, and renal impairment. The Leiden risk model had reasonable good ability (c-statistic 0.72) and showed adequate calibration (chi(2)=3.3, p=0.97). It could particularly identify a low-risk group. The UK risk model did not perform well (c-statistic 0.60), showing statistically significant lack of fit (chi(2)=64.9, p<0.001). This study showed similar predictive ability of previously identified predictors for perioperative mortality. The Leiden risk model could identify a low-risk group, while the UK risk model showed a relatively poor performance. The current study supports the use of the Leiden model for preoperative risk assessment.

Challenges in comparing risk-adjusted bypass surgery mortality results: Results from the Cooperative Cardiovascular Project

OBJECTIVESWe sought to evaluate the predictive accuracy of four bypass surgery mortality clinical risk models and to examine the extent to which hospitals’ risk-adjusted surgical outcomes vary depending on which risk-adjustment method is applied.BACKGROUNDCardiovascular “report cards” often compare risk-adjusted surgical outcomes; however, it is unclear to what extent the risk-adjustment process itself may affect these metrics.METHODSAs part of the Cooperative Cardiovascular Project’s Pilot Revascularization Study, we compared the predictive accuracy of four bypass clinical risk models among 3,654 Medicare patients undergoing surgery at 28 hospitals in Alabama and Iowa. We also compared the agreement in hospital-level risk-adjusted bypass outcome performance ratings depending on which of the four risk models was applied.RESULTSAlthough the four risk models had similar discriminatory abilities (C-index, 0.71 to 0.74), certain models tended to overpredict mortality in higher-risk patients. There was high correlation between a hospital’s risk-adjusted mortality rates regardless of which of the four models was used (correlation between risk-adjusted rating, 0.93 to 0.97). In contrast, there was limited agreement in which hospitals were identified as “performance outliers” depending on which risk-adjustment model was used and how outlier status was defined.CONCLUSIONSA hospital’s risk-adjusted bypass surgery mortality rating, relative to its peers, was consistent regardless of the risk-adjustment model applied, supporting their use as a means of provider performance feedback. Designation of performance outliers, however, can vary significantly depending on the benchmark and methods used for this determination.

Predicting angiography-induced acute renal function impairment: clinical risk model.

Two hundred sixty-six patients were evaluated for development of acute renal function impairment after renal angiography. Forty-five (16.9%) had a significant increase in serum level of creatinine (sCr), six developed oliguria or anuria, and one required permanent dialysis. Age, proteinuria, abnormal baseline sCr, use of Renografin 76, and preexisting renal disease were the five independent risk factors in the series. An odds-ratio analysis establishes the relative risk (i.e., likelihood) of developing acute renal insufficiency when a given risk factor is present. For example, patients with underlying renal disease were 6.6 times more likely to develop a transient increase in sCr than those with no renal disease. A clinical test model was devised to predict the likelihood that a given individual would develop acute renal insufficiency after renal angiography on the basis of the number of risk factors present. An increasing relation was demonstrated; the more factors present, the more likely it becomes that a patient will develop acute renal insufficiency.