Online ISSN: 2515-8260

Keywords : Ectopic pregnancy

Study of ectopic pregnancy in a tertiary care center, Maharashtra, India

Dr. Priyanka Kunal Purohit, Dr. B B Yadav, Dr. Shwetambari S Navale, Dr. Chintan M Upadhyay

European Journal of Molecular & Clinical Medicine, 2022, Volume 9, Issue 2, Pages 757-762

Background: Ectopic pregnancy (EP) is a life threatening emergency commonly being
managed by primary care physicians where diagnosis is often being missed at the first
Objectives: To study the etiological factors, clinical presentation and maternal outcome of
cases of ectopic pregnancy.
Materials and Methods: This cross-sectional study was done among 50 confirmed cases of
ectopic pregnancy at department of obstetrics & Gynecology in Government Medical College
and Hospital, Latur, Maharashtra during October 2013 to September 2015. Data collection
was done after ethical permission from institutional ethical committee and informed consent
of clients. Inclusion criteria: All confirmed cases of ectopic pregnancy Exclusion criteria: All
cases of intrauterine pregnancies.
Results: Highest number of participants (34%) belonged to 26-30 years age group and mean
age was 27 years. Maximum participants (70%) were multipara. Present study noted 16%
misdiagnosed cases of EP. Most common site of EP was noted at ampulla (68%). Tubectomy
was the most common risk factor (28%), ‘amenorrhea (80%)’ was the most common clinical
feature. Blood transfusion required in 78% cases and post-op wound infection in 12% cases.
Conclusion: The rising number of cases of EP poses a serious concern over maternal
mortality. With advances in the field of medicine, more young women are adopting newer
fertility control methods such as newer oral contraceptives, infrastructure contraceptive
devices and various tubal surgeries to limit their families. Moreover, newer drugs for
ovulation induction and tubal reconstructive surgeries have led to delayed conception with
increased risk of EP.


Piyush Vohra, Geetika Gupta Syal, Rita Mittal, Binakshi Nevatia, Shivika Mittal

European Journal of Molecular & Clinical Medicine, 2022, Volume 9, Issue 3, Pages 1836-1841

Caesarean Scar Pregnancy (CSP) is a rare condition, yet its incidence is increasing owing to a rise in caesarean deliveries. It is associated with complications like uterine rupture, maternal hemorrhage, hemodynamic instability and ultimately increased maternal morbidity and mortality. Here we present a case series of 3 patients with CSP. Prompt diagnosis and intervention are imperative in preventing morbidity and improving outcome.

Analysis of Complications for Expectant Women and Comparative Study of Maternal Mortality in India

G. Keerthi; M.S. Abirami

European Journal of Molecular & Clinical Medicine, 2021, Volume 8, Issue 3, Pages 1481-1491

From the first maternal level up to the delivery, there is high risk in women's health factors. Nowadays, severe maternal problems lead to crucial health issues in pregnant women. These problems may occur either during pregnancy or delivery time or after delivery according to the women health conditions. These crucial issues will become a risk for the mother’s and baby’s life. These maternal conditions during delivery are not easy to detect at the early stage of pregnancy. In this paper, some of the important pregnancy complications are addressed with their symptoms and treatment. Based on the study, different methodologies are discussed to prevent and avoid pregnant women's complications and for childbirth. The main aim of this study is to improve the maternal and fetal outcomes irrespective of the places. In this paper, a sample dataset in India is taken to show the Maternal Mortality Rate (MMR) by considering the values from the year 2010 to 2030. More analysis of MMR can be done by considering different countries, which will be helpful to solve the occurrence of risk factors either during or after pregnancy. Consequently, this analysis may avoid pregnancy death rates. The main work is to improve the maternal and fetal outcomes by strengthening the pregnant women health. Future work will be applying different machine learning methodologies to detect the risk level of severe maternal morbidity.