Pediatric Heart Surgery Infections Risk Model | Medical Algorithm

Description

Barker et al developed a model for estimating the risk of a major infection following cardiac surgery performed on a pediatric patient. This can help to identify a patient who may benefit from more aggressive management. The authors are from Duke University, Oregon Health and Science University, Cleveland Clinic and the Congenital Heart Institute of Florida.

Patient selection: pediatric patient undergoing cardiac surgery <= 18 years of age

Outcome: sepsis, mediastinitis, sternal infection or endocarditis secondary to surgery

Parameters:

(1) age

(2) complexity of the procedure

(3) history of previous cardiac surgery

(4) preoperative length of stay

(5) preoperative ventilator support

(6) genetic abnormality

Parameter	Finding	Points
age	< 90 days	9
	90 days to 3 years	7
	3 to 5 years	3
	> 5 years	0
complexity	simple	0
	medium	3
	high	6
history of previous cardiac surgery	no	0
	yes	4
preoperative length of stay	<= 1 day	0
	> 1 day	3
preoperative ventilator support	no	0
	yes	4
genetic abnromality	no	0
	yes	3

where:

• Medium complexity = Aristotle basic complexity score 3 OR RACHS-1 score 3 or 4.

• High complexity = Aristotle complexity score > 3 and RACHS-1 score > 4.

total score =

= SUM(points for all 6 parameters)

Interpretation:

• minimum score: 0

• maximum score: 29

• The higher the score the greater the risk for a major infection following surgery.

Score	Risk of Major Infection
< 4	< 0.2%
4 to 20	(0.04 * ((points)^2)) – (0.448 * (points)) + 1.53
20 to 25	(-0.0518 * ((points)^2)) + (3.265 * (points)) – 35.9
26 to 29	> 13.3%

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Description

Specialty

Objective

ICD-10

Major Infection Following Pediatric Cardiac Surgery | Risk Model

Purpose: To predict the risk of major infection following cardiac surgery performed on a pediatric patient using the model of Barker et al.

Description

Specialty

Objective

ICD-10