02181nas a2200169 4500000000100000008004100001260001800042100001100060700001100071700001200082245008200094856008100176300001000257490000700267520172300274022001401997 2022 d bFarname, Inc.1 aNaik S1 aMore S1 aJoshi S00aHistomorphological Correlation with Bacteriological Index in Leprosy Patients uhttps://ijp.iranpath.org/article_247997_3a89e30abd3704a07afd6269ff975b9c.pdf a48-550 v173 a

Background & Objective: Leprosy is characterized by various clinicopathological forms depending on the host's body. Therefore, the correlation of histopathological findings with bacteriological index is helpful in diagnosing, classification, and monitoring the treatment. We aimed to analyze the histomorphological findings correlation with the bacteriological index in different types of leprosy. Then, study the histopathological spectrum of leprosy. Methods: We carried out a histomorphological study of skin biopsies obtained from 100 new patients tested clinically in OPD (Out Patients Department) on the basis and calculation of bacteriological index on a slit-skin smear. The histomorphological findings correlation with the bacteriological index was to be found in different types of leprosy. Results: In the histopathological studies, 52% of the patients were diagnosed with borderline tuberculoid (BT) followed by 20% with borderline lepromatous (BL), 13% with lepromatous leprosy (LL), 8% with tuberculoid (TT), 4% with histoid Hansen's disease, and 3% with mid-borderline (BB). On the clinical and histopathological examinations, correlation was found for 80% of the cases. Considering the correlation of histopathological features with the bacteriological index, 63% of the cases showed good correlation which was comparable with that of other studies. Conclusion: Because of the underlying symptoms of leprosy, there is a difference between different types of leprosy and the clinical and environmental perceptions. Thus, the correlation of clinical, histopathological, and bacteriological indices could be more helpful in the diagnosis of leprosy rather than considering only one parameter.

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