Indmedica Home | About Indmedica | Medical Jobs | Advertise On Indmedica
Search Indmedica Web
Indmedica - India's premier medical portal

Indian Journal for the Practising Doctor

Original Paper Identification of High Risk Pregnancy by a Scoring System and its Correlation with Perinatal Outcome

Author(s): Samiya M, Samina M

Vol. 5, No. 1 (2008-03 - 2008-04)

Samiya M, Samina M

Dr Samiya Mufti, MD, is from the Department of Gynaecology & Obstetrics Government Medical College, Srinagar.
Dr Samina Mufti, MD, is from the Regional Institute of Health & Family Welfare, Kashmir
Correspondence: Dr Samiya Mufti,


Background: India, like other developing countries, has a very high perinatal mortality, interwoven with a high illiteracy, ignorance, teeming population and lack of facilities and resources. The ominous web of factors makes almost 30% of pregnant mothers high risk, who in turn jeopardize the health and life of their baby during perinatal period.
Research questions: 1. Can we use a simple scoring system to identify high risk mothers? 2. Can the score code qualify and quantify the risk to the baby in perinatal period?
Methodology: Case control study of 400 pregnant women enrolled in the 3rd trimester, who were categorized, on the basis of a simple scoring system (modified by Dutta and Das), into no risk, low risk, moderate risk and high risk pregnancies. Different scores were correlated with perinatal outcome.
Results: Maternal risk scores correlated well with birthweight, gestational age, 5-min Apgar and perinatal survival.
Conclusion: Categorizing mothers into risk groups using a simple scoring system, as used here, is a simple and cost-effective method to predict perinatal outcome as well as to guide the appropriate course of action to reduce perinatal morbidity and mortality.

Key words: Maternal risk score, perinatal mortality, perinatal morbidity, correlations


The perinatal mortality rate has often been used as an index of the level of development in a community. It not only reflects the socioeconomic status, educational level and cultural background of the mother but also comments on the quality of medical care provided to the mother and her neonate.

A number of biological and social factors during pregnancy influence the perinatal mortality. Although only 10-30% of the mothers seen in antenatal period can be classified as high risk they account for 70-80% of perinatal mortality and morbidity. Age, parity, social class and past obstetric history are only some of the factors that should be taken into account while assessing the risk for any pregnant woman. Early identification of the factors that influence perinatal mortality followed by proper management and therapy can frequently modify or prevent a poor perinatal outcome.

Despite recent advances in modern obstetrics and neonatal care India, is still facing a high (46/1000) perinatal mortality rate. One of the reasons for this dismal performance is failure to identify the foetus at risk in time. Perinatal outcome can be changed significantly by earlydetection followed by special intensive care of high risk pregnancies.

High-tech maternal and child health care (as electronic foetal monitoring, portable ultrasonography, intensive neonatal care units at PHC level etc) as is available in the West is not possible in rural India where poverty, ignorance and illiteracy prevail. Hence a need for a simplified and less invasive method for early detection of high risk pregnancy. According to Sundarka and Kacchap1 in our country where there is a lack of facility at each level a scoring system would be a cost effective and easily accessible method to screen the high risk pregnancy and to estimate the net perinatal outcome. The risk scoring provides a formalized method of recognizing, documenting and cumulating antepartum and intrapartum factors in order to predict the later complications for mother and her foetus.

The present study was intended to use one such simple, less invasive, cost effective and easily accessible scoring system for detection of high risk pregnancy and to find the correlation between perinatal outcome and various degrees of risk.

Materials and methods

The study was conducted on 400 women attending the Outpatient Department or admitted for safe delivery in the biggest maternity hospital of Kashmir (Lala Ded Hospital) attached to the Government Medical College, Srinagar, over a period of two years (2003-2005).

The study group comprised of randomly selected women in their third trimester, who were subjected to detailed history and thorough general and obstetrical examination.

Different scores were assigned to various factors like age, parity, past obstetric history, associated medical factors and relevant present pregnancy factors based on the prenatal scoring system developed by Dutta and Das2 in1990, which itself is a modification of the high risk scoring system proposed by Coopland et al in Manitoba in 1977.

Table 1. Prenatal Scoring Schedule (Dutta and Das2)

Reproductive History Factors Score Past Obstetrical History Score Present Pregnancy Factors Score Associated Disease Factors Score
Age Abortion 1 Bleeding < 20 weeks 1 Diabetes 3
<16 1 Postpartum haemorrhage/ Manual removal of Placenta 1 Bleeding > 20 weeks 3 Cardiac disease 2
16<35 0 Anaemia (Hb < 10gms) 1 Previous gynaecological surgery 1
>35 2 Baby wt > 4 Kg 1 Hypertension 2 Chronic renal disease 2
Parity Baby wt < 2.5 Kg 1 Oedema 3 Infective hepatitis 1
0 2 Pregnancy induced hypertension 1 Albuminuria 3 Pulmonary tuberculosis 2
1-4 0 Infertility 1 Multiple Pregnancy 3 Other diseases according to severity 1-3
5 and above 2 Previous Caesarian section 2 Breech 3 Under -nutrition 2
Still birth/ Neonatal death 3 Rh Isoimmunisation 3
Prolonged/ Difficult labour 1 Prolonged labour 1
Premature rupture of membranes 2
Polyhydramnios 2
Small foetus 1

Based on this scoring system patients were classified in to three risk groups: Low risk (1-2), Moderate risk (3-5) and High risk (6 and above). Out of the enrolled 400 women, 200 normal pregnant women with no risk factor (Risk score 0), were selected as controls.

Any mortality or morbidity occurring during the perinatal period ie from the age of viability up to the first seven days of life was noted. Postnatal examination of babies was done with particular reference to Apgar score at 5 Minutes, weight of the baby and gestational age. For statistical evaluation, Chi Square test for the analysis of significance was used.


Fig 1

Table 2. Distribution of cases as per the Risk Score

Risk score Risk
No (%)
1-2 Low 73 (36.5%)
3-5 Moderate 97 (48.5%)
6 and above High 30 (15%)

Out of the 200 women who had one or more risk factors (case group), 73 (36.5%) fell in the low risk category and 97 (48.5%) in the moderate risk category. The incidence of high risk pregnancy i.e. those with risk score of 6 or above was 15%.

Table 3. Relationship between socio-economic status and the risk score

Case group
Socio-economic status Total
Lower Middle Upper
1-2 5 58 10 73
3-5 11 82 4 97
≥6 12 17 1 30
Total 28
Control group
0 1 (.5%) 149

Majority of patients i.e. 78.5% in the case group belonged to the middle class; 14% were from the lower class and 7.5% from the upper class. Among the lower socio-economic status, 42.8% of the mothers had a risk score of 6 and above. In comparison, 10.7% of those from middle class and 6.6% patients from the upper class had a risk score of 6 and above. In the control group, 74.5% patients belonged to middle class, 25% to upper class and only one patient (0.5%) was from the lower class.

Table 4. Correlation between various risk groups and the birth weight

Score Birthweight Total
< 2.5 kg > 2.5 kg
Control group 0 3 (1.5% ) 197 (98.5%) 200
Low risk 1-2 9 (12.3%) 64 (87.6%) 73
Moderate risk 3-5 18 (17.64%) 84 (82.35%) 102
High risk 6 & above 16 (48.48%) 17 (51.51%) 33

The 200 pregnant women in the case group delivered 208 babies (including 1 triplet and 6 twins), of whom 43 babies were of low birth weight (LBW). On the other hand, in the control group, only 3 babies were of low birth weight. The incidence of LBW increased from 1.5% in no risk group to 12.3% in low risk, 17.64% in moderate risk, and 48.48% in high risk mothers. The likelihood of having low birth weight babies in women with risk factors (case group) was 17.11 times higher than in women with no risk (control group), which was statistically significant (p = .00002) The probability of delivering low birth weight babies in the high risk women (risk score >6) was 61.8 times higher.

Table 5. Correlation between preterm births and risk groups

Score Gestational age Total
< 37 weeks ≥37 weeks
Control 0 4 (2% ) 196 (98%) 200
Low 1-2 9 (12.3%) 64 (87.6%) 73
Moderate 3-5 16 (15.68%) 86 (84.3%) 102
High 6 & above 8 (24.24%) 25 (75.76%) 33

Of the 208 babies born to the case group, 33 were born preterm , as compared to only 4 in the control group. The incidence of preterm births increased from 2% in the control group to 12.32% in the low risk group, to 15.68% in moderate risk, and 24.24% in high risk group.

Mothers with one or more risk factors were at 9.24 time higher risk of giving birth to preterm babies when compared to women in the control group ( p = .0001). The incidence of preterm births among the highest risk groups (score 6 or more) was 15.68 times higher.

Table 6. Correlation between various risk groups and 5 minute Apgar Score

Score Apgar at 5 min Total
< 7 ≥ 7
Control 0 2 (1%) 198 (99%) 200
Low 1-2 10 (13.6%) 63 (86.4%) 73
Moderate 3-5 21 (20.6%) 81 (79.4%) 102
High 6 & above 13 (39.4%) 20 (60.6%) 33

Forty four babies in the case group had Apgar score < 7 at 5 minutes. In the low risk group the incidence of Apgar score < 7 at 5 minutes was 13.6% which progressively increased to 20.6% in the moderate risk and to 39.4% in the high risk group women. On the other hand in the 200 women of with zero risk score (control group) only 2 women gave birth to babies with Apgar score < 7 at 5 minutes.

Thus, the risk of delivering babies with an Apgar score < 7 at 5 minutes was 26.56 times higher in women with risk factors than in women with no risk factors ( p = .00004). The risk was still higher i.e. 64.35 times in women falling in the high risk category (risk score 6 or more).

Among the 208 births in the case group with one or more risk factors, 17 perinatal deaths occurred, of whom 6 occurred in the highest risk group. In the control group, on the other hand, only 1 perinatal death took place.

Table 7. correlation between perinatal mortality and various risk groups.

Score Perinatal mortality Total
Control 0 1 (0.5% ) 199 (99.5%) 200
Low 1-2 2 (2.74%) 71 (97.26%) 73
Moderate 3-5 9 (8.8%) 93 (91.2%) 102
High 6 & above 6 (18.2%) 27 (81.8%) 33

Babies born to women with risk score more than zero ran a 17.71 times higher risk of perinatal mortality ( p = .0059) when compared to women with no risk factor. Mothers falling in the high risk category (6 or above) were 44.22 times more likely to lose their baby in the perinatal period.

In the case group, 65 of the 200 mothers had instrumental delivery or caesarian section, compared to only 5 from the 200 women in control group. The incidence of instrumental vaginal delivery and LSCS was highest in the women falling in high risk category (6 ore more). The likelihood of women in case group of having instrumental delivery or caesarian section was 16.71 times higher than in those in control group ( p = .000001), which was statistically significant.


High risk pregnancy requires exemplary individualised care and special attention as this group is responsible for maximum perinatal mortality and morbidity even though they form a small proportion of the entire population.

Despite recent advances in maternal and neonatal care in India, perinatal mortality is still very high ie 46 per 1000 live births compared to 5-10 per 1000 live births in developed countries3. 70%-80% of perinatal mortality in developing countries including India is accounted for by the mothers falling in the high risk category. This underscores the need for early identification of thigh risk mothers so that they receive timely and appropriate care which can modify the perinatal outcome in these patients.

In the background of illiteracy, ignorance, poverty, resourcelessness, lack of quality care, screening high risk pregnancy by using a scoring system is simple, cost effective, non- invasive and easily accessible. Further, the data presented in our study confirms that the method is clinically useful to identify this critical proportion of patients.

In the present study, the incidence of high risk pregnancy was 15%, which was similar to the findings of Sundarka and Kacchap2, who in 2001 reported an incidence of 12.5%. While 14% of patients in the case group were from the lower class only one (0.5%) patient in control group belonged to this socioeconomic class. The incidence of patients with risk score of 6 and above in this socioeconomic class was 42.8% as compared to 10.7% in the middle class and only 6.6% in the upper class. Previous studies by Wallace (1970)4 and Mavalanker et al (1991)5 have also shown increased incidence of high risk pregnancy in lower socioeconomic class. These findings suggests that lower SES may be an independent risk factor for perinatal outcome in most communities.

Of the LBW babies only 3 were born to women in control group while 43 were born to women in case group who had one or more associated risk factors. Significantly, 79% of them were born to mothers falling in the moderate and high risk categories. Near similar observations (67.2%; 80.4%) were reported by Dutta and Das3 (1990) and Sundarka and Kacchap1 (2001) respectively. Low birth weight, which simply signifies that the baby is born malnourished, is a formidable challenge for India which, according to the WHO, tops the world with an incidence of 30%.

Preterm births (births occurring before the gestational age of 37 weeks) contribute significantly to perinatal mortality and morbidity. In our study the incidence of preterm births increased from 2% in women with no risk factor to 12.32% in low risk group, to 15.68% in moderate risk group and to 24.24% in the high risk group . Similar results were reported by Coopland (1977)6 (1.5%, 4%, 11.6% and 23.9%) and by Talsania and Lala (1994)7 (2.38%, 11.6%, 14.08% and 20%).

The risk factors had high sensitivity for LBW and preterm births (93.4% and 89.19% respectively) but low specificity (54.4% and 52.8%) and low positive predictive value (20.6% and 15.8% respectively). These findings are comparable with those of Talsania and Lala7 (1994) who found sensitivity of risk factors for preterm births equal to 95.77% but specificity of 19.69% and positive predictive value of 11.93%.

In our study 46 babies had Apgar score of less than 7 at 5 minutes. Of these only two were born to mothers with no risk factors, while in the study group the comparative incidence increased from 13.6% in low risk to 20.6% in moderate risk to 39.4% in high risk group. Near similar results (22.8%, 22.8%, 38.4%) have been reported by Sundarka and Kacchap1 in 2001.

The overall perinatal mortality rate in our study was 46.1/ 1000 live births which is almost the same as that reported by Malik and Mir8 in 1992 (40/1000) and Fazili and Mattoo9 in 1999 (43/1000). Similarly high perinatal mortality rates (46) are prevalent in India. In our study the perinatal mortality rate in women with no risk factor was 5.02 per 1000 live births, which rose with the level of risk from 27 per 1000 in low risk to 96 in moderate risk to 222 in the high risk group. The findings are comparable to those reported by Talsania and Lala in 1994 (0 risk - 7.94, moderate risk -92.20 and high risk - 200/1000 live births). The women with one or more risk factors were 17.1 times more likely to lose their baby during the perinatal period than those with no risk. The risk factors had high sensitivity (94.4%) for predicting perinatal mortality but low specificity (51.02%) and low positive predictive value (20.8%). Similar high sensitivity (98.5%) and low positive predictive value (10.34%) were reported by Talsania and Lala7 in 1994.

The objective of our study was identification of the high risk pregnancy by using a simple scoring system and correlating the risk score with perinatal outcome so that it could be used for timely identification followed by proper management of high risk cases to prevent, or at least modify, the sub- optimal perinatal outcome.

The scoring system was found to have high sensitivity for predicting low birth weight, preterm births and perinatal mortality in high risk group but low sensitivity in low risk groups. The results obtained were comparable with studies done elsewhere.


The risk scoring system can thus be used not only as a test for predicting perinatal mortality but also as a simple and cost effective screening tool for identifying pregnancies at higher risk of perinatal mortality and morbidity so that these are subjected to the special ‘high risk’ care they need. Women with risk score 0-2 are considered safe and no active interference apart from simple assistance is necessary.

Patients with risk score of 3-5 can be handled by doctors at primary health centre provided they received proper training in handling such cases. Scores higher than 6 justify provision of highly skilled management in a district hospital or tertiary care centre with a well-equipped intensive obstetric and neonatal care unit.


  1. Sundarak and Kacchap
  2. Dutta S and Das XS. Identification of high risk mothers by a scoring system and it’s correlation with perinatal outcome. J. Obstet Gynaecol India. 1990; 40: 181-190.
  3. WHO. World Health Report, 1996.World Health Organization, Geneva.
  4. Wallace et al, 1970
  5. Mavalankar DV, Trivedi CR, Gray RH. Levels and risk factors for perinatal mortality in Ahmedabad, India. Bull Wrld Hlth Org 1991; 69(4):435-42.
  6. Coopland et
  7. Talsania NJ and Lala MK. Evaluation of antenatal risk scoring in preterm birth Ind J Pract Doctor 2008; Vol V, No I: 23 prevention and perinatal loss. Ind J Matern Child Hlth. 1994; 5 (1): 5-9.
  8. Malik and Mir
  9. Fazilli and Mattoo

Additional Reading:

  1. Ambiye VR, Allahbadiya G, Shanbhag AM et al. Detection of high risk pregnancy – a simple scoring system. J Obstet Gynaecol India. 1990:40: 178-180.
  2. Aubry RH, Pennington JC. Identification and evaluation of high risk pregnancy: the perinatal concept. Clin Obstet Gynaecol 1973: 16: 3-27
  3. Bai NS, Mathews E, Nair PM, Sabarinathan K, Harikumar C. Perinatal mortality rate in South Indian population. J Ind Med Assoc 1991; 89:97-8.
  4. Dasgupta S, Saha I, Lahiri A, Mandal AK. A study of perinatal mortality and associated maternal profile in a medical college hospital. J Ind Med Assoc 1997; 95(3): 78-9.
  5. Erickson MT. Risk factors associated with complications of pregnancy, labour and delivery. Am. J. Obstet. Gynaecol. 1971; 111:658-662
  6. Roy Chowdhury NN, Sikadar K. Study on perinatal mortality. J Obstet Gynaecol India. 1981; 31: 125-29.
  7. Talsania NJ. Lala MK. Scoring of high risk pregnant women and related outcome. Ind J Matern Child Health. 1991; 2(3):92-94.
Access free medical resources from Wiley-Blackwell now!

About Indmedica - Conditions of Usage - Advertise On Indmedica - Contact Us

Copyright © 2005 Indmedica