Context: Verrucous lesions pose a diagnostic challenge to the clinicians as well as pathologists. There are few discrete histological features which if looked for carefully can help differentiate them. Aim: The aim of this study is to bring into light the histological features of several verrucous lesions occuring on skin and mucosa lined by squamous epithelium. Settings and Design: This is a 6-month prospective and retrospective study done on cutaneous and squamous mucosal biopsies with an exophytic pattern of growth. Clinical details along with the diagnosis were retrieved from the case files and correlated with the histological diagnosis. Subjects and Methods: Only hematoxylin and eosin-stained sections were studied. Results: Of the 35 cases, 10 (28.5%) were female and 25 (71.4%) were male. The size of the lesions ranged from 0.5 cm to 6.5 cm. The site of lesions included anogenital (8 cases, 22.8%), cutaneous (24 cases, 68.5%), and oral mucosal (3 cases, 8.5%) areas. Warts were found to be the most common lesions (14 cases, 40%), of which cutaneous warts comprised 9 cases (64%) and genital warts comprised 5 cases (36%). It was observed that benign warts were clinically confused with other rare cutaneous lesions such as polyps and cysts. Malignant counterpart of a wart or condyloma called as warty carcinoma was not known to many and was mistaken for a conventional squamous cell carcinoma. Conclusion: Histology is of utmost importance in differentiating the several verrucous lesions because sometimes clinical appearance may mimic one another.

Context: Z score defines the shift of an observed value from the mean. Aims: By determining the direction of this shift and its absolute value for mean corpuscular hemoglobin (MCH) and mean corpuscular hemoglobin concentration (MCHC), one can quickly screen the hemogram for any spurious results in RBC parameters and also predict the type of anemia. This is because MCH and MCHC are derived parameters (from Hb, RBC, MCV) and thereby reflect the true as well as false changes in an erythrogram. Materials and Methods: A total of 975 hemograms were studied retrospectively. Basic statistical formulae using mean and standard deviation were applied to calculate z scores for MCH and MCHC. Results obtained were compared with the standard method and validated by an independent cohort of 100 random samples run on a different machine. Results and Statistical Analysis: Z score was found to be statistically significant (p <.001) in diagnosing iron deficiency anemias, megaloblastic anemias, hemolytic anemias, regenerative anemias, anemia of chronic disease and spurious findings. Z score was not significant (p = 0.9) in predicting beta thalassemia trait. The sensitivity was low for the differentials of microcytic hypochromic anemias. Conclusions: Despite this, Z score can be of immense help to the clinicians and pathologists in making quick interpretation of the underlying red cell abnormalities. Also, it can be used as a quality assessment tool in hematology laboratories taking pre analytical and analytical factors into account.

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