PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 4037480

Methodology reporting in three acute care journals: replication and reliability.

C G Brown·G D Kelen·M Moser·M L Moeschberger·D A Rund
View original source ↗Export metadata ↓

Abstract

As the sciences of emergency medicine and acute care medicine develop, it becomes imperative for researchers in these fields to accurately and completely report the methodology of their investigations. It is only through complete reporting that other investigators can critically examine, replicate, or expand on the results of an investigation. The purpose of our study was to compare the completeness of methodology reporting in three acute care journals, Annals of Emergency Medicine, Critical Care Medicine, and Journal of Trauma. Thirty-eight criteria characteristics necessary for the replication of a clinical trial were identified and grouped into ten categories. The categories were experimental design, recruitment and exclusion of subjects, selection of study sample, subject allocation, therapeutic regimen, blindness, outcome criteria, analysis of confounders, withdrawal of subjects, and statistical analysis. All prospective, interventional, controlled trials appearing in these journals from January 1980 to June 1983 were identified. A total of 45 trials were found. Each trial was read independently by two reviewers to determine whether each of the 38 criteria was clearly reported, not clearly reported, or not applicable. Disagreements were resolved by a third reader (adjudicator). The results are reported as the mean proportion of items clearly reported +/- standard deviation: Annals of Emergency Medicine (n = 16), 0.39 +/- 0.10; Journal of Trauma (n = 18), 0.33 +/- 0.14; and Critical Care Medicine (n = 11), 0.32 +/- 0.09. A one-way analysis of variance found no statistically significant difference between journals with respect to these proportions (P = .25).(ABSTRACT TRUNCATED AT 250 WORDS)

Explore related subjects

Clinical Trials as TopicEvaluation Studies as TopicHumansPeriodicals as TopicResearch DesignComparative StudyJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

C G Brown, G D Kelen, M Moser, M L Moeschberger, D A Rund. 1985. Methodology reporting in three acute care journals: replication and reliability.. https://doi.org/10.1016/s0196-0644(85)80244-4

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2008

On the exact interval estimation for the difference in paired areas under the ROC curves.

An important measure for comparison of accuracy between two diagnostic procedures is the difference in paired areas under the receiver operating characteristic (ROC) curves. Non-parametric and maximum likelihood methods have been proposed for interval estimation for the difference in paired areas under ROC curves. However, these two methods are asymptotic procedures and their performance in finite sample sizes has not been thoroughly investigated. We propose to use the concept of generalized pivotal quantities (GPQs) to construct an exact confidence interval for the difference in paired areas under ROC curves. A simulation study is conducted to empirically investigate the probability coverage and expected length of the three methods for various combinations of sample sizes, values of the area under the ROC curve and correlations. Simulation results demonstrate that the exact confidence interval based on the concept of GPQs provides not only sufficient probability coverage but also reasonable expected length. Numerical examples using published data sets illustrate the proposed method.

Clinical Trials as Topic↗
PubMed2007

An efficient test for the analysis of dichotomized variables when the reliability is known.

A difference in an outcome variable between the treatment groups in a trial does not necessarily mean that there is a difference in the number of patients who experience relevant improvement on that variable. When the relevant improvement corresponds with an outcome or change in outcome that exceeds a certain threshold, the outcome variable can be dichotomized. A responder is a patient whose outcome exceeds the threshold. Comparisons can be made between the number of responders in the two treatment groups using logistic regression, or some other method to evaluate binary outcomes. An important disadvantage of this approach is the loss of power. In general, it is more efficient to test the difference between the mean values. We developed a statistical test that compares response rates for a dichotomized variable. It requires that an estimate of the reliability of the outcome variable is available. Simulations showed that the test was valid and robust over a wide range of distributions and sample sizes. The power was greater than the power of a chi(2) test, which would enable substantial reduction in the sample size.

Clinical Trials as Topic↗
PubMed2007

Sample size determination for logistic regression revisited.

There is no consensus on the approach to compute the power and sample size with logistic regression. Some authors use the likelihood ratio test; some use the test on proportions; some suggest various approximations to handle the multivariate case. We advocate the use of the Wald test since the Z-score is routinely used for statistical significance testing of regression coefficients. The null-variance formula became popular from early studies, which contradicts modern software, which utilizes the method of maximum likelihood estimation (MLE), when the variance of the MLE is estimated at the MLE, not at the null. We derive general Wald-based power and sample size formulas for logistic regression and then apply them to binary exposure and confounder to obtain a closed-form expression. These formulas are applied to minimize the total sample size in a case-control study to achieve a given power by optimizing the ratio of controls to cases. Approximately, the optimal number of controls to cases is equal to the square root of the alternative odds ratio. Our sample size and power calculations can be carried out online at www.dartmouth.edu/ approximately eugened.

Clinical Trials as Topic↗