Salunkhe et al reported a score for predicting preterm birth in a developing country. This can help to identify a patient who may require more aggressive management. The authors are from Krishna Institute of Nursing Sciences and Krishna Institute of Medical Sciences in India.
Patient selection: pregnant woman in India
Parameters:
(1) type of work performed
(2) number of meals per day
(3) number of hours of rest per day
(4) education
(5) weight gain during pregnancy in kg
(6) number of antenatal care (ANC) visits (as a measure of antenatal care)
(7) type of family
|
Parameter
|
Finding
|
Points
|
|
type of work performed
|
hard (physical)
|
4
|
|
|
other
|
0
|
|
number of meals per day
|
< 4
|
3
|
|
|
>= 4
|
0
|
|
hours of rest
|
< 2
|
2
|
|
|
>= 2
|
0
|
|
education
|
literate
|
2
|
|
|
illiterate
|
0
|
|
weight gain
|
< 10 kg
|
2
|
|
|
>= 10 kg
|
0
|
|
number of ANC visits
|
< 4
|
2
|
|
|
>= 4
|
0
|
|
type of family
|
nuclear
|
1
|
|
|
non-nuclear
|
0
|
total score =
= SUM(points for all of the parameters)
Interpretation:
• minimum score: 0
• maximum score: 16
• A score < 8 has a prevalence of preterm delivery of 7%
• A score of 8 or 9 has a prevalence of preterm delivery of 40-50%.
• A score >= 10 is associated with a high risk of preterm delivery.
Performance:
• The score had a sensitivity of 76% and specificity of 86% for preterm birth.
