Palm-Coein Classification of Abnormal Uterine Bleeding and Clinicopathological Correlation
DOI:
https://doi.org/10.70749/ijbr.v3i4.1041Keywords:
Palm-Coein, Abnormal Uterine Bleeding, Classification, Clinicopathological CorrelationAbstract
Background: AUB is a prevalent gynaecological condition that has a substantial effect on women's social, emotional, and physical health. AUB causes are systematically divided into structural (PALM) and non-structural (COEIN) components using the PALM-COEIN categorisation system, which was introduced by the International Federation of Gynaecology and Obstetrics (FIGO). Although it has been widely used, there are still issues with its clinical application and diagnostics, especially in areas with low resources. Objective: The objective of this study was to establish a clinicopathological connection, classifying AUB patients using the PALM-COEIN system, and evaluating treatment outcomes and diagnostic difficulties in women of reproductive age. Methods: Purposive sampling was used in a qualitative study including 160 women with an AUB diagnosis. Comprehensive patient interviews, clinical assessments, and histological examination of endometrial samples were all part of the data collection process. Trends in clinical presentations, histology results, and therapy responses were found using thematic analysis. Findings: Non-structural reasons (COEIN) made up 37.4% of cases, with ovulatory dysfunction (18.8%) being the most common, while structural causes (PALM) accounted for 62.6% of cases, with leiomyomas (21.9%) being the most common. Women between the ages of 31 and 40 had the highest frequency of AUB (40.6%). The most common histological finding (34.4%) was proliferative endometrium, which suggests that ovulatory disruption had a significant role. In postmenopausal individuals, endometrial hyperplasia (15%) and carcinoma (5.6%) were more prevalent. Conclusion: The PALM-COEIN categorisation system offered a methodical way to diagnose AUB, allowing for focused therapeutic approaches. Diagnostic difficulties still exist, nevertheless, particularly when there are overlapping characteristics or insufficient histopathological resources. To improve patient care outcomes and improve classification accuracy, more research is required, especially in settings with limited resources.
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