STUDY ON CLINICAL PROFILE OF PATIENTS UNDERGOING ABDOMINAL HYSTERECTOMY AND THEIR CLINICO-PATHOLOGICAL CORRELATION

Autor: Rakshya Joshi, Sabita Shrestha, Basant Sharma, Renuka Tamrakar
Rok vydání: 2021
Předmět:
Zdroj: Journal of Chitwan Medical College. 9:65-71
ISSN: 2091-2889
2091-2412
DOI: 10.54530/jcmc.373
Popis: Background: Hysterectomy is an effective treatment for a wide range of gynaecological diseases, both benign and malignant. There must be a pe­riodic audit for the appropriate indication of the surgery and its complica­tion rate. Histopathological analysis is mandatory for definitive diagnosis and further management. This study aims to review the clinical profile, indications of hysterectomy and to assess the correlation between the clinical diagnosis and histopathological report. Methods: A retrospective study of all the patients undergoing abdominal hysterectomy was conducted in the Department of Obstetrics and Gyne­cology, Chitwan Medical College Teaching Hospital, Nepal from January to December 2018. Demographic and clinical informations were retrieved from the medical record section. Datas were entered in the pre-designed proforma. Statistical analysis was done in terms of percentages, standard deviation, correlation and mean. Results: During the study period, 111 patients underwent abdominal hys­terectomy. The mean age of the patients was 46 years. The mean dura­tion of hospital stay was 8.7 days. Abnormal menstrual flow and pain ab­domen were the commonest presenting symptoms. The most common preoperative diagnosis was fibroid followed by ovarian tumor. Leiomyoma was the commonest lesion on histopathological examination. The correla­tion between clinical diagnosis and histopathology was 96.07% for fibroid, 80.95% for ovarian tumor, 66.67% for adenomyosis and 38.46% for DUB. Conclusions: Fibroid uterus and ovarian mass are the common indications for abdominal hysterectomy. Histopathology is mandatory for confirming the diagnosis, proper counseling and holistic management of the patient.
Databáze: OpenAIRE