Introduction: Height is used to calculating body mass index and body surface area which are used to interpret renal function tests and pulmonary function tests. The maximum vertical measurement of a person is the standing height. Arm span is the measurement between the tip of the middle finger of the right and left hands. The exact standing height of patients with abnormalities of disproportionate growth, spine deformities, skeletal dysplasia, limb deformities, amputated limb, pain, weakness or paralysis cannot be measured. In these conditions, an arm span may be used to determine the height of a person. Objective: This study aims to determine the association of height and arm span among the medical students of Maharajgunj, Medical Campus, Nepal. Methods: A cross-sectional analytical study was conducted among medical students in the Clinical Physiology Department of Maharajgunj Medical Campus from November 2020 to October 2021. Non-probability, the convenience sampling method was adopted and a total of 110 participants were enrolled in the study including 55 males and 55 females. Pearson’s correlation coefficient was used to find the association between height and arm span. A simple linear regression test was also used to formulate the equations of height and arm span and data analysis was done using SPSS version 25. Results: A significant positive correlation was observed between height and arm span where the total participants had r-value=0.765(p=0.00), males had r-value=0.557(p =0.00) and female had r-value=0.778(p=0.00). Conclusions: A strong positive correlation was observed between height and arm span among the participants.
Introduction Hand grip strength is used in evaluation of muscle strength and is also increasingly being used as an indicator for nutritional status. The maximum force applied voluntarily by the subject is called maximum handgrip strength, which is measured in kilograms. Muscular endurance is the ability of a muscle or muscle group to perform against a load for an extended period of time, measured in seconds. This study aims to correlate body mass index with handgrip strength and handgrip endurance in medical students. MethodsThis is a cross sectional, observational study which included 74 undergraduate students of Maharajgunj Medical Campus by convenient sampling method. Body mass index was calculated by Quetelet’s formula. Camry digital hand dynamometer was used to measure handgrip strength in the dominant hand in kilograms. Participants were instructed to hold dynamometer with maintained pressure of 30% of maximum handgrip strength for as long as possible to determine the handgrip endurance. Statistical analyses were performed with SPSS Statistics software. ResultsThe handgrip strength was more in males than females with a mean of 43.09±3.72 kg, while handgrip endurance was more in females with a mean of 123.60±50.65 sec. Positive correlation was seen between body mass index and handgrip strength (r=0.23 and p=0.045). Body mass index and handgrip endurance also showed positive correlation (r=0.34 and p=0.003). ConclusionSignificant correlation of body mass index with handgrip strength and handgrip endurance was seen in medical students.
Introduction: Differential leukocyte is a frequently ordered laboratory test. It is the percentage distribution of types of leukocytes on a stained film. There are two methods to determine differential leukocyte count which are manual and automated. Manual method is considered the gold standard and is used to validate differential counts obtained by automated method. The comparative knowledge about the different methods to determine differential leukocyte count may guide us to use of proper method to determine the differential count more accurately and in a shorter time. The study aims to compare differential leukocyte count of normal blood samples by manual and automatic methods. Materials and methods: A cross-sectional, analytical study was conducted in laboratory of Kasturba Hospital, Manipal. A total of 347 blood samples of adults that did not show abnormalities in automatic analyzer were included in the study by purposive sampling method. Blood smears for manual count were prepared by Leishman’s stain. Results: A significant difference was observed between manual and automated leukocyte differential counts in 100 and 200 cells per specimen in neutrophils, lymphocytes, monocytes, eosinophils and basophils. Conclusions: The study concludes the need of improving accuracy and reliability of the automated methods. A reference range generated by further studies could help provide more accurate determination of differential leukocyte count.
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