Abnormal uterine bleeding, FIGO, Heavy menstrual bleeding, PALM-COEIN, Practical applicability, Qualitative survey, Reproductive age group
Citation Information :
Karena ZV, Mehta AD, Vikani S. PALM-COEIN Classification for Abnormal Uterine Bleeding: A Study of its Practical Applicability and Distribution of Causes. J South Asian Feder Obs Gynae 2022; 14 (6):681-684.
Aim: The aim was to study the distribution of causes in nongravid women of reproductive age-group having abnormal uterine bleeding (AUB) as per the new International Federation of Gynecology and Obstetrics (FIGO) polyp; adenomyosis; leiomyoma; malignancy and hyperplasia; coagulopathy; ovulatory dysfunction; endometrial; iatrogenic; and not yet classified—(PALM-COEIN) classification system and to evaluate the practical applicability of this classification system in the clinical scenario.
Materials and methods: A prospective cross-sectional study was conducted among 300 women with AUB attending the outpatient department of gynecology, selected by the kth random sampling technique. The etiological diagnosis was made in the PALM-COEIN spectrum. The practical applicability of the AUB-FIGO classification system was assessed by the survey of clinicians with help of a scoring system.
Results: The majority of the study subjects were from 40 to 55 years age group with the median age of the study subjects being 42 years. Fifty-two subjects had two attributable causes from PALM-COEIN for AUB. In our study, 45% of subjects had leiomyoma, which turned out to be the most common etiology for AUB, and hypothyroidism was the most common endocrinopathy associated with 10% of AUB cases. Hysteroscopy was required to diagnose one case of amenorrhea. The clinician survey emphasized the high practical applicability of PALM-COEIN classification.
Conclusion: The data generated from the clinical settings with this classification could be more comparable due to homogeneity and consistency in nomenclature.
Clinical significance: The International Federation of Gynecology and Obstetrics classification for AUB is a clinician-friendly modality providing an easy algorithm for accurate diagnosis and definitive treatment of AUB.
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