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Study objectives: To develop and validate a model for estimating the risk of lung cancer death in current and former smokers. The model is intended for use in analyzing a population of subjects who are undergoing lung cancer screening or receiving lung cancer chemoprevention, to determine whether the intervention has altered lung cancer mortality. Design/setting/patients: Model derivation was based on analyses of the placebo arm of the Carotene and Retinol Efficacy Trial. Model validation was based on analyses of three other longitudinal cohorts. Measurements: Observed and predicted number of deaths due to lung cancer. Results: In internal validation, the model was highly concordant and well calibrated. In external validation, the model predictions were similar to what was observed in all of the validation analyses. The predicted and observed deaths within 6 years were very similar when assessed in the Johns Hopkins Hospital trial of chest radiography and sputum cytology screening (176 predicted, 184 observed, p = 0.53), the Memorial Sloan-Kettering Cancer Center trial of chest radiography and sputum cytology screening (108 predicted, 114 observed, p = 0.57), and the National Health and Nutrition Evaluation Survey part I (24 predicted, 21 observed, p = 0.52). Conclusions: The number of lung cancer deaths in a population of current or former smokers can be accurately predicted, making model-based evaluations of prevention and early detection interventions a useful adjunct to definitive randomized trials. We illustrate this potential use with a small example. [ABSTRACT FROM AUTHOR]

Background: Bioterrorism using anthrax claimed five lives in the United States in 2001 and remains a potential public health threat. In the aftermath of a large-scale anthrax attack, mass screening to identify early inhalational anthrax may improve both the management of individual cases and the efficiency of health resource utilization. Purpose: To develop the evidence base for outpatient anthrax screening protocols by quantifying differences in clinical presentation between inhalational anthrax and common viral respiratory tract infections. Design: Review, compilation, and data extraction from English-language case reports of inhalational anthrax and epidemiologic studies of influenza and other viral respiratory infections. Data Sources: 13 reports of 28 cases of inhalational anthrax from 1920 to 2001 and 5 studies reporting on the clinical features of 2762 cases of influenza and 1932 cases of noninfluenza viral respiratory disease. Data Synthesis: Characterization of presenting clinical symptoms in anthrax and viral disease and calculation of likelihood ratios for the presence of selected clinical features. Results: Fever and cough do not reliably discriminate between inhalational anthrax and viral respiratory tract infection. Features suggestive of anthrax include the presence of nonheadache neurologic symptoms (positive likelihood ratio cannot be calculated), dyspnea (positive likelihood ratio, 5.3 [95% CI, 3.7 to 7.4]), nausea or vomiting (positive likelihood ratio, 5.1 [CI, 3.0 to 8.5]), and finding of any abnormality on lung auscultation (positive likelihood ratio, 8.1 [CI, 5.3 to 12.5]). In contrast, rhinorrhea (positive likelihood ratio, 0.2 [CI, 0.1 to 0.4]) and sore throat (positive likelihood ratio, 0.2 [CI, 0.1 to 0.5]) are more suggestive of viral respiratory tract infection. Conclusion: Inhalational anthrax has characteristic clinical features that are distinct from those seen in common viral respiratory tract infections. [ABSTRACT FROM AUTHOR]

This study assesses the importance of extramedical factors in the decision to hospitalize medical patients. Residents in a municipal hospital's emergency room completed a questionnaire on 252 consecutive patients at the time of admission. Extramedical factors contributed to the admission decision in 54 patients (21 percent): For twenty of these patients (8 percent of total) extramedical factors were the primary reason for admission. Factors noted most frequently related to patient behavior, such as being unlikely to follow instructions, and to home situations, such as social isolation. For 16 percent of the admissions, physicians left that treatment outside the hospital was possible if realistic alternatives existed. Results suggest that extramedical factors are important contributors to the need for hospitalization. Attempts to development quality assurance criteria, such as in utilization review or admission certification, must take such factors into account. [ABSTRACT FROM AUTHOR]

Background. Post-exposure prophylaxis is a critical component of the public health response to bioterrorism. Computer simulation modeling may assist in designing antibiotic distribution centers for this task. Methods. The authors used discrete event simulation modeling to determine staffing levels for entry screening, triage, medical evaluation, and drug dispensing stations in a hypothetical antibiotic distribution center operating in low medium, and high disease prevalence bioterrorism response scenarios. Patient arrival rates and processing times were based on prior mass prophylaxis campaigns. Multiple sensitivity analyses examined the relation-ship between average staff utilization rate (UR) (i.e., percentage of time occupied in patient contact) and capacity of the model to handle surge arrivals. Results. Distribution center operation required from 93 staff for the low-prevalence scenario to 111 staff for the high-prevalence scenario to process approximately 1000 people per hour within the baseline model assumptions. Excess capacity to process surge arrivals approximated (1-UR) for triage staffing. Conclusions. Discrete event simulation modeling is a useful tool in developing the public health infrastructure for bioterrorism response. Live exercises to validate the assumptions and outcomes presented here may improve preparedness to respond to bioterrorism. [ABSTRACT FROM PUBLISHER]