Pregnancy outcome among high-risk pregnant women in the rural area of Belagavi
Background: India has around 25% high-risk pregnant mothers, which leads to about 75% perinatal morbidities.(1) The early prediction of a high-risk pregnancy and planning interventions can help in preventing complications and result in good pregnancy outcomes. Aims: To study the pregnancy outcome am...
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Veröffentlicht in: | Journal of family medicine and primary care 2022-08, Vol.11 (8), p.4440-4446 |
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Sprache: | eng |
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Zusammenfassung: | Background: India has around 25% high-risk pregnant mothers, which leads to about 75% perinatal morbidities.(1) The early prediction of a high-risk pregnancy and planning interventions can help in preventing complications and result in good pregnancy outcomes. Aims: To study the pregnancy outcome among the high-risk pregnant women of a rural area and to associate pregnancy outcomes of high-risk pregnant women with modified Coopland's criteria. Material and Methods: Study design: 1-year Longitudinal study from 2016 to 2017, Study population: The high-risk pregnant women attending PMSMA camp, Study area: Kinaye, Primary Health Centre, Belagavi. Sample size: 147, Data collection was done using a pretested predesigned questionnaire after obtaining patient consent and ethical clearance. Chi-square test was used to study the association of variables and categorical data presented as percentages. Results: Among the participants, 40.4% of the pregnant women had low-risk scores; 45.9% had high-risk scores, and 13.7% had severe-risk scores according to Coopland's high-risk pregnancy scoring. Nearly 29.5% high-risk pregnancies resulted in bad fetal outcomes. As Coopland's score in the high-risk group increased, the chance of having good fetal outcomes decreased, and this association was found to be statistically significant. Conclusions: 70.5% of the high-risk mothers had good pregnancy outcomes. The scoring system can be used by health workers for the prediction of high-risk pregnancy and plan treatment and preventive measures. |
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ISSN: | 2249-4863 2278-7135 |
DOI: | 10.4103/jfmpc.jfmpc_10_22 |