Are Today’s Medical School Graduates Performing the Same Number of Medical Procedures Compared to Graduates Ten Years Ago? A case for Simulation?

INTRODUCTION: Medical schools are charged with providing both a strong basic science and clinical curriculum for their students. In most institutions instruction in performing the core clinical procedures is part of the curriculum, but because of many constraints do medical students practice these procedures as many times as medical students in the past? Several studies have concluded that medical students today feel incompetent to perform basic clinical procedures at the time of graduation. [See PDF for complete abstract]

Detection of nonrandom association of alleles from the distribution of the number of heterozygous loci in a sample.

The distribution of the number of heterozygous loci in two randomly chosen gametes or in a random diploid zygote provides information regarding the nonrandom association of alleles among different genetic loci. Two alternative statistics may be employed for detection of nonrandom association of genes of different loci when observations are made on these distributions: observed variance of the number of heterozygous loci (s2k) and a goodness-of-fit criterion (X2) to contrast the observed distribution with that expected under the hypothesis of random association of genes. It is shown, by simulation, that s2k is statistically more efficient than X2 to detect a given extent of nonrandom association. Asymptotic normality of s2k is justified, and X2 is shown to follow a chi-square (chi 2) distribution with partial loss of degrees of freedom arising because of estimation of parameters from the marginal gene frequency data. Whenever direct evaluations of linkage disequilibrium values are possible, tests based on maximum likelihood estimators of linkage disequilibria require a smaller sample size (number of zygotes or gametes) to detect a given level of nonrandom association in comparison with that required if such tests are conducted on the basis of s2k. Summarization of multilocus genotype (or haplotype) data, into the different number of heterozygous loci classes, thus, amounts to appreciable loss of information.

Evaluating statistical methods used to estimate the number of postsynaptic receptors.

Calcium levels in spines play a significant role in determining the sign and magnitude of synaptic plasticity. The magnitude of calcium influx into spines is highly dependent on influx through N-methyl D-aspartate (NMDA) receptors, and therefore depends on the number of postsynaptic NMDA receptors in each spine. We have calculated previously how the number of postsynaptic NMDA receptors determines the mean and variance of calcium transients in the postsynaptic density, and how this alters the shape of plasticity curves. However, the number of postsynaptic NMDA receptors in the postsynaptic density is not well known. Anatomical methods for estimating the number of NMDA receptors produce estimates that are very different than those produced by physiological techniques. The physiological techniques are based on the statistics of synaptic transmission and it is difficult to experimentally estimate their precision. In this paper we use stochastic simulations in order to test the validity of a physiological estimation technique based on failure analysis. We find that the method is likely to underestimate the number of postsynaptic NMDA receptors, explain the source of the error, and re-derive a more precise estimation technique. We also show that the original failure analysis as well as our improved formulas are not robust to small estimation errors in key parameters.

Increased sensitivity of ETEC detection in stool cultures by increasing the number of E. coli colonies tested

The cause of infection of about a third of all travelers' diarrhea patients studied is not identified. Stools of these diarrhea patients tested for known enteric pathogens are shown to be negative, and identified as pathogen negative stools. We proposed that the third of these diarrhea patients might not only include at present unknown pathogens, but also known pathogens that go undetected. Conventionally, a probability sample of five E. coli colonies are used detect enterotoxigenic E. coli (ETEC) and other diarrhea-producing E. coli from stool cultures. We compared this conventional method of using five E. coli colonies, to the use of up to twenty E. coli colonies. Testing for up to fifteen E. coli colonies detected about twice as many ETEC when compared to the detection of ETEC, testing for five E. coli colonies. When the number of E. coli colonies tested was increased from 5 to 15, the detection of ETEC increased from 19.0% to 38.8%. The sensitivity of the assay with 5 E. coli colonies was statistically significantly different to the sensitivity of the assay with 10 E. coli colonies, suggesting that for the detection of ETEC at least 10 colonies of E. coli should be tested.^

THE USE OF MULTIVARIATE ANALYSIS OF COVARIANCE IN EVALUATING THE COMPARABILITY OF LABORATORY DETERMINATIONS IN COOPERATIVE STUDIES

The role of clinical chemistry has traditionally been to evaluate acutely ill or hospitalized patients. Traditional statistical methods have serious drawbacks in that they use univariate techniques. To demonstrate alternative methodology, a multivariate analysis of covariance model was developed and applied to the data from the Cooperative Study of Sickle Cell Disease.^ The purpose of developing the model for the laboratory data from the CSSCD was to evaluate the comparability of the results from the different clinics. Several variables were incorporated into the model in order to control for possible differences among the clinics that might confound any real laboratory differences.^ Differences for LDH, alkaline phosphatase and SGOT were identified which will necessitate adjustments by clinic whenever these data are used. In addition, aberrant clinic values for LDH, creatinine and BUN were also identified.^ The use of any statistical technique including multivariate analysis without thoughtful consideration may lead to spurious conclusions that may not be corrected for some time, if ever. However, the advantages of multivariate analysis far outweigh its potential problems. If its use increases as it should, the applicability to the analysis of laboratory data in prospective patient monitoring, quality control programs, and interpretation of data from cooperative studies could well have a major impact on the health and well being of a large number of individuals. ^