To analyze the clinic-demographic pattern of the patient with ovarian tumors: an observational study
European Journal of Molecular & Clinical Medicine,
2020, Volume 7, Issue 10, Pages 3905-3911
AbstractAim: to analyze the demographic pattern and the clinical presentation of the patient with ovarian tumors.
Material and methods: A Prospective study was conducted in the Department of Obstetrics and Gynaecology, Narayan Medical College and Hospital, Sasaram, Bihar, India from October 2018 to April 2019. Total 100 cases of ovarian tumours were included in this study. The tumours were cut and allowed to fix in 10% formalin for 24-48 hours. After formalin fixation, multiple bits were taken for histopathological examination. The blocks were cut at 3-5 microns thickness and stained with Haematoxylin and Eosin. Detailed microscopic examination of the tumour was done.
Results: Out of 100 cases of ovarian tumours, 71 were benign, 6 were tumours of low malignant potential and 23 were malignant. The youngest patient was 12 years and the oldest was 67 years forming a range of 12 years to 67 years. Highest incidence of ovarian tumour was noted in the 40-50years 38cases out of 100 cases accounting for 38%. Highest incidence of benign ovarian tumour was noted in 30-40years 26 cases out of 71 accounting for 36.62%. Highest incidence of malignant tumour was noted in the 40-50years 12 out of 23 cases accounting for 52.17%. 37% of the patients complained of dull aching lower abdominal pain, 24% complained of abdominal mass and 6% of the patients gave history of menstrual disturbance like menorrhagia. Urinary disturbances were found in 5% patients with tumours. Out of 100 patients 9 patients were not married and all were below twenty years of age. Among married, 83were parous and remaining were 8 nulliparous. Out of 100 cases of ovarian tumors, 29 were associated with appendicitis and 14 were associated with uterovaginal prolapse.
Conclusion: The ovarian tumors manifest a complex and varied spectrum of clinical, morphological and pathological features. Correlating the clinical parameters and categorizing the tumors according to the WHO classification help us in coming to an early diagnosis, management and hence in the prognosis of ovarian tumors.
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