Model of Ariyaratne et al for Predicting Early Mortality Following Aortic Valve Replacement

Description

Ariyaratne et al developed a model for predicting early mortality following aortic valve replacement. This can help to identify a patient who may benefit from more aggressive management. The authors are from The Alfred Centre in Melbourne, the Geelong Hospital and Monash University in Australia.

Patient selection: aortic valve replacement surgery

Outcome: early death

Parameters:

(1) cerebrovascular disease

(2) grade of left ventricular ejection fraction LVEF)

(3) NYHA class

(4) previous cardiac surgery

(5) active infective endocarditis

(6) left main coronary artery disease

(7) renal dysfunction based on estimated GFR

(8) age in years

Parameter	Finding	Points	Beta
cerebrovascular disease	none	0	0
	coma	3	0.805
	CVA	2	0.422
	RIND/TIA	2	0.417
LVEF	normal	0	0
	mild	1	0.233
	moderate	1	0.377
	severe	3	0.742
NYHA class	I or II	0	0
	III	2	0.557
	IV	4	1.129
previous cardiac surgery	none	0	0
	previous CABG	4	0.959
	previous valve surgery	1	0.256
	previous other cardiac surgery	6	1.425
active infective endocarditis	no	0	0
	yes	5	1.351
left main coronary artery disease	no	0	0
	yes	3	0.775
renal dysfunction	none	0	0
	mild	3	0.789
	moderate	4	0.990
	severe	7	1.873
	end-stage	7	1.909
age	< 60 years	0	0
	60 to 69 years	2	0.576
	70 to 79 years	4	1.122
	>= 80 years	6	1.564

total score =

= SUM(points for all 8 parameters)

value of X =

= SUM(beta coefficients) – 6.084

probability of early mortality =

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

Interpretation:

• minimum score: 0

• maximum score: 37

• The higher the score the greater the risk of early mortality.

Total Score	Probability of Mortality
0 to 12	(0.0655 * ((score)^2)) - (0.506 * (score)) + 1.747
12 to 25	(0.2145 * ((score)^2)) - (3.59 * (score)) + 16.67
> 25	> 60%

To read more or access our algorithms and calculators, please log in or register.

Description

Specialty

ICD-10