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Logistic Regression Formula of Sermet-Gaudelus et al for Identifying a Hospitalized Child at Risk for Malnutrition

Purpose: To identify a hospitalizaed child at risk for malnutrition using the logistic regression formula of Sermet-Gaudelus et al.

Description

In addition to the risk score described in the previous section, Sermet-Gaudelus developed a logistic regression formula to identify a hospitalized child at risk for malnutrition. This can allow for early intervention prior to the development of complications. The authors are from Hopital Necker-Enfants Malades in Paris.


Parameters:

(1) food intake

(2) pain

(3) grade of pathologic condition

 

Grade 1 (Mild) Conditions

Grade 2 (Moderate) Conditions

Grade 3 (Severe) Conditions

admission for diagnostic procedure

severe infections but not life-threatening

AIDS

minor infection

routine surgery

malignancy

mild episodic illness

fractures

severe sepsis

minor surgery

chronic illness without acute deterioration

major surgery (cardiac surgery, major abdominal)

gastroenteritis

inflammatory bowel disease

multiple injuries

 

cystic fibrosis

acute deterioration of a chronic disease

 

sickle cell disease

major depression

from Table 1 page 66 and text page 65

 

Parameter

Finding

Points

food intake

>= 50% of dietary allowance

0

 

< 50% of dietary allowance

1

pain

child <= 6 years with no sign of pain

0

 

child <= 6 years with any visible sign of pain

1

 

child > 6 years with visual analogue pain score <= 40 out of 100

0

 

child > 6 years with visual analogue pain score > 40 out of 100

1

grade 2 condition

absent

0

 

present

1

grade 3 condition

absent

0

 

present

1

 

where:

• Signs of pain in a small child may include incessant crying or abnormal movements.

• The visual analogue scale (VAS) for pain ranged from 0 for no pain to 100 for worst pain imaginable.

• Although not specifically mentioned in the paper, I assume that a grade 2 condition is not scored if a grade 3 condition is present.

 

F =

= (0.9594 * (points for food intake)) + (0.7789 * (points for pain)) + (1.004 * (points for grade 2 condition)) + (3.214 * (points for grade 3 condition)) - 2.498

 

probability of a > 2% weight loss =

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


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Specialty

Objective

ICD-10