Models of Giles et al for Predicting Perioperative Mortality in a Patient with an Abdominal Aortic Aneurysm: Logistic Regression Model

Description

Giles et al developed models for predicting perioperative mortality in Medicare patients undergoing repair of an abdominal aortic aneurysm. One uses logistic regression. The authors are from Beth Israel Deaconess Medical Center, Harvard Medical School and CMS.

Patent selection: repair of an abdominal aortic aneurysm, >= 67 years old

Parameters for patient characteristics and comorbidities:

(1) age in years

(2) sex

(3) renal failure

(4) congestive heart failure (CHF)

(5) peripheral vascular and/or cerebrovascular disease

(6) open versus endovascular

Parameter	Finding	Points
age in years	65 to 70	0
	71 to 75	0.15
	76 to 80	0.63
	> 80	1.14
sex	male	0
	female	0.42
renal failure	none	0
	no dialysis	0.71
	dialysis dependent (ESRD)	0.95
CHF	absent	0
	present	0.55
peripheral or cerebral vascular disease	absent	0
	present	0.33
treatment	endovaascular	0
	open	1.17

X =

= SUM(points for all 6 parameters) - 5.02

probability of mortality =

= 1 /(1 + EXP((-1) * X))

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Models of Giles et al for Predicting Perioperative Mortality in a Patient with an Abdominal Aortic Aneurysm: Logistic Regression Model

Description

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