An observational study to classify cause of abnormal uterine bleeding according to PALM-COEIN classification

Abnormal uterine bleeding (AUB) is a frequent gynecological complaint affecting women of all ages, significantly impacting quality of life. To standardize its diagnosis and management, the International Federation of Gynecology and Obstetrics (FIGO) introduced the PALM-COEIN classification system, which categorizes AUB into structural and non-structural causes. To classify AUB according to PALM-COEIN classification, to know associated risk factors, to know their demography and modality of treatment required.

This observational cross-sectional study was conducted in the Department of Obstetrics and Gynaecology at New Civil Hospital, Surat, from May 2024 to April 2025. Approval was obtained from the Institutional Research Review Committee (Approval ID: GMCS/RRC-2/13433/24). A total of 200 consenting women with AUB (non-pregnancy related) were included. Exclusion criteria: pregnancy-related bleeding or refusal to consent. Detailed clinical history, examination, investigations, imaging and biopsy when indicated were done. Classification was as per PALM-COEIN. Treatment included medical or surgical modalities. Response was assessed over a 3-month follow-up.

The most common cause of AUB was adenomyosis (AUB-A, 33%), followed by leiomyoma (AUB-L, 30.5%) and ovulatory dysfunction (AUB-O, 14%). Among non-structural causes, AUB-O was predominant. In this study simple endometrial hyperplasia without atypia in 4 cases and half of those patients improved with medical treatment. Medical management was effective in 64.48% of treated patients, while 65.5% required surgical intervention. Obesity (26%) and thyroid disorders (17.5%) were the most common comorbid risk factors.

The PALM-COEIN classification system was a useful and thorough tool for understanding the causes of AUB, helping to standardize diagnoses, plan better treatments and achieve better results in patient care. It also facilitated effective communication and comparison across clinical and research settings. Metrics

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