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Biomedical subjects

A Indrayan

Publications and source records attributed to A Indrayan.

At least 19 recordsLinked to original sources
PubMed2004

Elements of medical research.

Most medical research is empirical based on evidence rather than hunches or preferences. It follows a series of specific steps. There are no short cuts. Collection of evidence and its analysis should follow a carefully drawn protocol. Most of the modern medical research requires biostatistical tools to reach to a valid and reliable conclusion. Researcher must have an adequate knowledge and skill to be really effective. The endeavours should be consistent with the accepted medical and research ethics. Medical research can provide immense satisfaction when conducted on scientific lines, and can be occasionally frustrating when years of efforts fail to produce expected results. This article focuses on aspects that can increase the credibility of research. It is addressed to all interested in medical research, and seeking answers to questions such as what actually is research, what are its types, what specific steps should be followed, what a research protocol should contain, and what makes research credible etc.

Biomedical Research↗
PubMed1998

Is the heredity of reticulate acro pigmentation of Kitamura always autosomal dominant?

Reticulate acropigmentation of Kitamura (RAK) in three patients and their families is described. In one family, 2 women and 2 men were affected out of 9 individuals. In the other family, 6 women had lesions of reticulate acropigmentation out of total of 27 over three generations. In the third family, one man was affected. All of the cases had palmar pits; onset of lesions was after puberty in all the cases. The apparently different hereditary patterns in these three families are striking, and autosomal dominant inheritance appears unlikely in every case.

Acrodermatitis↗
PubMed1997

Rapid assessment of prevalence of cataract blindness at district level.

AIM: To find an optimal cluster size and number of clusters for a reasonable estimate of the prevalence of cataract blindness in people aged > or = 50 years in 19 rural districts of a state in India. MATERIALS: Cluster sampling methodology was used in 19 rural districts of Karnataka State, India. In each district, 15 clusters were randomly selected and 90 people aged > or = 50 years were examined in each cluster. As a result the visual acuity and lens status of a total of 22,218 people were assessed. METHODS: For each district, the design effect for cluster size ranging from 20 to 90 was calculated and the optimal cluster size and the required number of clusters to achieve an accuracy of 1% errors and 80% confidence was assessed. RESULTS: The age and gender adjusted prevalence of cataract blindness varied from 1.58% to 7.24%, which justifies district level surveys. The design effect is nearly 1.5 for clusters of sizes 30 and 40. With an average prevalence of 4.93% with 1% error and 80% confidence level, the optimal number of clusters is 37 and 28 for a cluster size of 30 and 40 respectively and the average sample size for a district around 1100. CONCLUSIONS: Rapid assessments for cataract blindness in those aged > or = 50 years can be conducted at district level in India with existing resources and at affordable costs. These provide reliable data, essential for effective monitoring and planning. Other parameters, for instance, surgical coverage can also be assessed. The availability of standardized software for data entry and analysis and strict adherence to survey procedures is essential.

Adult↗
PubMed1996

Statistical choropleth cartography in epidemiology.

BACKGROUND: The potential of maps in the study of regional variation and similarity in health and in understanding the underlying processes is being increasingly realized. It has thus become important that more care is exercised in drawing health maps and the subjective elements are minimized. Conventional choropleth maps based on qualitative data are mostly arbitrary with regard to the number of categories and the cutoff points. This can lead to substantially different pictures based on the same data set. METHODS: We suggest use of cluster methods to discover 'natural' groups of data points which to a large extent are suggested by the data themselves. These methods can determine not only the cutoff points but also the number of categories required to depict the variability in the data. The methods have natural extension to the multivariate set-up and thus can provide the strategy to construct integrated maps based on the simultaneous consideration of several variables. Since different cluster methods can yield different grouping we propose a simple method to identify cutoffs common to a majority of the methods. RESULTS: The details of the methods are explained on two real data sets. One is the indicators of mortality before one year of age in India and the other is years of life lost due to premature mortality in different countries. The maps obtained are compared with the conventional maps. CONCLUSION: The cutoff points obtained by a majority of cluster methods deserve attention for obtaining natural groups for choroplethic depiction. Maps based on such cutoffs seem to have promise for increasing the accuracy in perception and cognition of regional variation.

Analysis of Variance↗
PubMed1996

Computer-assisted learning package for frequency distribution of physiological variables.

There are a variety of ways of picturing a frequency distribution type, viz, the histogram, the frequency polygon, the smoothed curve and the ogive. We have developed a computer package to demonstrate gradual change of a histogram into a curve. For a given set of data on frequency distribution of, say blood pressure levels in specified categories, this package helps the computer to draw bars which gradually rise to the level of the frequencies, and lateron are replaced by the polygon and finally by the frequency curve of the Gaussian type on the computer screen pixel by pixel. This thus demonstrates the meaning and genesis of frequency curves. This package could be very useful in learning the concept of frequency curves particularly the Gaussian form.

Computer Graphics↗