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Although dangling is a common nursing intervention, little research has been conducted to test its effectiveness or to compare various dangling methods. By contrast, abundant information is available about orthostatic responses. In this article the authors explain the physiologic principles underlying orthostatic responses, focusing on blood volume distribution and the role of the mechanoreceptors, discuss typical and atypical responses to dangling and standing, describe clinical manifestations of orthostatic hypotension and syncope, present research-based practice guidelines, and, provide specific recommendations for future research. Because of the wide variability in heart rate and blood pressure responses to orthostasis, the authors stress the importance of signs and symptoms such as nausea, pallor, dizziness, visual dimming, and impaired consciousness in assessing orthostatic tolerance. Studying rituals such as dangling can advance nursing practice, improve patient outcomes, and move nursing to a research-based practice.
During the course of a clinical trial it is normally necessary to conduct periodic reviews of the data in order to determine whether the trial should be terminated. Since these reviews affect the probability of the final outcome, many statisticians recommend that the P values quoted for a clinical trial be sequentially adjusted to account for the possibility of premature termination. In this article it is argued that the sequentially adjusted P value is an inappropriate measure of the strength of evidence justified by a clinical trial. This is because the size of sequentially adjusted P values will vary according to actions that might have been taken if the trial had gone differently than it in fact did. Although such contingencies will effect the frequency of occurrence of certain events in hypothetical sequence of trial replications, it is hard to see why decisions that would have been made in response to outcomes that did not occur should have any bearing on the strength of evidence that can be attributed to the results that were actually observed. The credibility merited by a clinical trial depends not only on the implausibility of the observed results under the null hypothesis, but also on factors such as the medical plausibility of hypothesis well supported by the data, and the extent to which observed results have been predicted in advance. It is argued that publishing these factors along with fixed sample P values is the best way to indicate the degree of certainty that should be attributed to the conclusions of a clinical trial.
The effect of an alanine load per se on hepatic alanine balance and hepatic glucose production is unclear. To examine this question, alanine was infused into six postabsorptive dogs at a rate of 6 mumol/kg-min, while maintaining insulin and glucagon levels using the pancreatic clamp technique. The arterial alanine concentration rose from a basal level of 227 +/- 16 mumol/L to 497 +/- 40 mumol/L during alanine infusion (P less than .01). The net hepatic fractional extraction of alanine remained unchanged, while hepatic alanine uptake increased from 3.0 +/- 0.3 to 6.0 +/- 0.4 mumol/kg-min (P less than .01). Conversion of alanine into glucose increased 87% to 2.7 +/- 0.3 mumol/kg-min during alanine infusion (P less than .01) while gluconeogenic efficiency remained essentially unchanged. Despite the increased gluconeogenic rate, the total rate of glucose production was unchanged. These data suggest that an increase in the alanine load to the liver causes a proportional increase in net hepatic alanine uptake and the gluconeogenic rate, but that in an overnight fasted animal this increase is insufficient to significantly increase glucose production.
A study was designed to address the relative merits of different sampling strategies for detecting linkage. Genotypes of pedigree members were generated by the use of a single genetic model, and the pedigrees were subdivided into dominant-appearing, recessive-appearing, and "interesting" subsets. An investigator blind to how the data had been generated applied two different selection rules to determine which individuals in each pedigree would be "typed" for linkage analysis. Linkage analyses were then conducted on these pedigree subsets, as well as on the combined data, by the use of three autosomal dominant models, three autosomal recessive models, and the generating (i.e., "true") model. Results suggest (1) that linkage is likely to be detected even in the absence of knowledge of the mode of transmission, if a range of models can be examined; (2) that false evidence for heterogeneity will not necessarily result when pedigrees are selected according to apparent mode of transmission for analysis; (3) that recessive-appearing pedigrees (i.e., those with multiplex sibships) may be particularly useful for detecting linkage; and (4) that including information on unaffected second-degree relatives adds little to linkage studies of affected individuals and their first-degree relatives.
Recent advances in molecular biology make genetic linkage analysis an increasingly attractive tool for the identification and characterization of genes involved in the etiology of psychiatric illnesses. However, the complex nature of psychiatric illnesses engenders a host of methodological difficulties not encountered in linkage analyses of simple, Mendelian genetic traits. A previous paper reviewed the basic concepts of genetic linkage analysis. This paper focuses on the methodological difficulties associated with the application of genetic linkage methods to psychiatric illnesses.
Because of the high prevalence of prescription drug use and the incomplete understanding of drug effects at the time of licensing, ongoing epidemiologic monitoring is required to provide information for clinical and regulatory decisions. Data produced through the administration of Medicaid programs have been considered for this purpose because the computerized files include prescription and diagnostic information for large, defined populations. However, the limited amount of data available in the computerized files and the atypical demographic characteristics of Medicaid populations create formidable difficulties in the use of these data for pharmacoepidemiology. This paper reviews these methodological problems and describes pragmatic solutions that have been developed through the ongoing use of these data bases for epidemiologic studies.