A prospective cohort study evaluating the state of medical readiness in the United States Air Force and risk factors to improve the medical readiness posture

A cohort of 418 United States Air Force (USAF) personnel from over 15 different bases deployed to Morocco in 1994. This was the first study of its kind and was designed with two primary goals: to determine if the USAF was medically prepared to deploy with its changing mission in the new world order, and to evaluate factors that might improve or degrade USAF medical readiness. The mean length of deployment was 21 days. The cohort was 95% male, 86% enlisted, 65% married, and 78% white.^ This study shows major deficiencies indicating the USAF medical readiness posture has not fully responded to meet its new mission requirements. Lack of required logistical items (e.g., mosquito nets, rainboots, DEET insecticide cream, etc.) revealed a low state of preparedness. The most notable deficiency was that 82.5% (95% CI = 78.4, 85.9) did not have permethrin pretreated mosquito nets and 81.0% (95% CI = 76.8, 84.6) lacked mosquito net poles. Additionally, 18% were deficient on vaccinations and 36% had not received a tuberculin skin test. Excluding injections, the overall compliance for preventive medicine requirements had a mean frequency of only 50.6% (95% CI = 45.36, 55.90).^ Several factors had a positive impact on compliance with logistical requirements. The most prominent was "receiving a medical intelligence briefing" from the USAF Public Health. After adjustment for mobility and age, individuals who underwent a briefing were 17.2 (95% CI = 4.37, 67.99) times more likely to have received an immunoglobulin shot and 4.2 (95% CI = 1.84, 9.45) times more likely to start their antimalarial prophylaxsis at the proper time. "Personnel on mobility" had the second strongest positive effect on medical readiness. When mobility and briefing were included in models, "personnel on mobility" were 2.6 (95% CI = 1.19, 5.53) times as likely to have DEET insecticide and 2.2 (95% CI = 1.16, 4.16) times as likely to have had a TB skin test.^ Five recommendations to improve the medical readiness of the USAF were outlined: upgrade base level logistical support, improve medical intelligence messages, include medical requirements on travel orders, place more personnel on mobility or only deploy personnel on mobility, and conduct research dedicated to capitalize on the powerful effect from predeployment briefings.^ Since this is the first study of its kind, more studies should be performed in different geographic theaters to assess medical readiness and establish acceptable compliance levels for the USAF. ^

An ordinal logistic regression model with misclassification of the outcome variable and categorical covariate

Ordinal outcomes are frequently employed in diagnosis and clinical trials. Clinical trials of Alzheimer's disease (AD) treatments are a case in point using the status of mild, moderate or severe disease as outcome measures. As in many other outcome oriented studies, the disease status may be misclassified. This study estimates the extent of misclassification in an ordinal outcome such as disease status. Also, this study estimates the extent of misclassification of a predictor variable such as genotype status. An ordinal logistic regression model is commonly used to model the relationship between disease status, the effect of treatment, and other predictive factors. A simulation study was done. First, data based on a set of hypothetical parameters and hypothetical rates of misclassification was created. Next, the maximum likelihood method was employed to generate likelihood equations accounting for misclassification. The Nelder-Mead Simplex method was used to solve for the misclassification and model parameters. Finally, this method was applied to an AD dataset to detect the amount of misclassification present. The estimates of the ordinal regression model parameters were close to the hypothetical parameters. β1 was hypothesized at 0.50 and the mean estimate was 0.488, β2 was hypothesized at 0.04 and the mean of the estimates was 0.04. Although the estimates for the rates of misclassification of X1 were not as close as β1 and β2, they validate this method. X 1 0-1 misclassification was hypothesized as 2.98% and the mean of the simulated estimates was 1.54% and, in the best case, the misclassification of k from high to medium was hypothesized at 4.87% and had a sample mean of 3.62%. In the AD dataset, the estimate for the odds ratio of X 1 of having both copies of the APOE 4 allele changed from an estimate of 1.377 to an estimate 1.418, demonstrating that the estimates of the odds ratio changed when the analysis includes adjustment for misclassification. ^