Volume 13, Issue 51 (6-2006)                   RJMS 2006, 13(51): 85-90 | Back to browse issues page

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Jalali S, Heydari M. Gynecomastia and Revising its Diagnostic Algorithm . RJMS 2006; 13 (51) :85-90
URL: http://rjms.iums.ac.ir/article-1-594-en.html
Abstract:   (9074 Views)

    Background & Aim: Gynecomastia or benign enlargement of breasts in males may occur at any age due to several reasons. The main problem in this disease is finding hidden feminizing tumors in testis or adrenals which can be considered as a dangerous but potentially treatable cause. In this study, we assessed 62 patients with gynecomastia to suggest a new algorithmic approach for evaluation of these patients. Patients & Method: In a case series study, all the patients hospitalized for surgical treatment of gynecomastia in general surgery wards of Tehran University of Medical Sciences from March 2002 to 2004 were enrolled. Required data such as history, physical examination, lab studies, testicular and adrenal sonographic reports, breast imaging, and surgery and pathology reports were collected and assessed. The pathology reports were considered as an approval to clinical diagnosis. All the patients underwent testicular and adrenal sonographic examinations. Results: 7 out of 69 patients were excluded because of incomplete data and 62 patients were finally assessed. The mean age was 30.35±14.06 years and the mean of disease duration was 42.83±37.77 months. Primary or idiopathic gynecomastia was seen in 42 patients(68%) and 20 patients(32%) presented with secondary gynecomastia. Low testosterone level, normal LH(Luteinizing Hormone) and high prolactin were noted in one patient who was diagnosed as idiopathic hyperprolactinemia. Apart from two cases of mild varicocele, no abnormalities were detected in testicular or adrenal sonographic examinations of the patients. Conclusion: This study suggests a new algorithmic approach for evaluation of patients with gynecomastia, which can lower the costs of treatment. Further studies are required to compare this algorithm with the current diagnostic approach.

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Type of Study: Research | Subject: General Surgery

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