### Description

O'Connor et al developed a model for predicting the risk of mortality after discharge for a patient hospitalized with heart failure. This can help to identify a patient who may benefit from more aggressive management. The authors are Duke University and other medical centers around the United States.

Parameters:

(1) age in years

(2) body weight in kilograms

(3) systolic blood pressure in mm Hg

(4) serum sodium in mmol/L

(5) serum creatinine in mg/dL

(6) history of liver disease

(7) history of depression

(8) history of reactive airway disease

points for age over a range of 25 to 95 years =

= (0.2476 * (age in years)) - 6.357

points for body weight over a range of 60 to 140 kg =

= (0.000357 * ((weight)^2)) - (0.1614 * (weight)) + 17.49

points for systolic blood pressure over a range of 80 to 280 mm Hg =

= (0.000280 * ((pressure)^2)) - (0.2134 * (pressure)) + 38.60

points for serum sodium over a range of 110 to 140 mmol/L =

= (-0.4 * (sodium)) + 56

points for serum creatinine over a range of 0 to 4 mg/dL =

= (4.7 * (creatinine))

Parameter

Finding

Points

history of liver disease

no

0

yes

8

history of depression

no

0

yes

4

history of reactive airway disease

no

0

yes

4

total points =

= SUM(points for all 8 parameters)

Interpretation:

• minimum score: 0

• maximum score: 97

• The higher the score the greater the mortality rate.

If the data in Figure 1 is modeled in Minitab:

probability of mortality =

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

X =

= (0.00094 * ((total points)^2)) + (0.00498 * (total points)) - 5.409

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