Airliner cabin air quality exposure assessment

The airliner cabin environment and its effects on occupant health have not been fully characterized. This dissertation is: (1) A review of airliner environmental control systems (ECSs) that modulate the ventilation, temperature, relative humidity (RH), and barometric pressure (PB) of the cabin environment---variables related to occupant comfort and health. (2) A review and assessment of the methods and findings of key cabin air quality (CAQ) investigations. Several significant deficiencies impede the drawing of inferences about CAQ, e.g., lack of detail about investigative methods, differences in methods between investigations, limited assessment of CAQ variables, small sample sizes, and technological deficiencies of data collection. (3) A comprehensive evaluation of the methods used in the subsequent NIOSH-FAA Airliner CAQ Exposure Assessment Feasibility Study (STUDY) in which this author participated. A number of problems were identified which limit the usefulness of the data. (4) An analysis of the reliable 10-flight STUDY data. Univariate and multivariate methods applied to CO2 (a surrogate for air contaminants), temperature, RH, and PB, in association with percent passenger load, ventilation system, flight duration, airliner body type, and measurement location within the cabin, revealed neither the measured values nor their variability exceeded established health-based exposure limits. Regression analyses suggest CO2, temperature, and RH were affected by percent passenger load. In-flight measurements of CO2 and RH were relatively independent of ventilation system type or flight duration. Cabin temperature was associated with percent passenger load, ventilation system type, and flight duration. (5) A synthesis of the implications of the airliner ECS and cabin O2 environment on occupant health. A model was developed to predict consequences of the airliner cabin pressure altitude 8,000 ft limit and resulting model-estimated PO2 on cardiopulmonary status. Based on the PB, altitude, and environmental data derived from the 10 STUDY flights, the predicted PaO2 of adults with COPD, or elderly adults with or without COPD, breathing ambient cabin air could be < 55 mm Hg (SaO2 < 88%). Reduction in cabin PB found in the STUDY flights could aggravate various medical conditions and require the use of in-flight supplemental O2. ^

Evaluating minimal important differences for the FACT-Melanoma quality of life questionnaire

Objectives. Minimal Important Differences (MIDs) establish benchmarks for interpreting mean differences in clinical trials involving quality of life outcomes and inform discussions of clinically meaningful change in patient status. As such, the purpose of this study was to assess MIDs for the Functional Assessment of Cancer Therapy–Melanoma (FACT-M). ^ Methods. A prospective validation study of the FACT-M was performed with 273 patients with stage I to IV melanoma. FACT-M, Karnofsky Performance Status (KPS), and Eastern Cooperative Oncology Group Performance Status (ECOG-PS) scores were obtained at baseline and 3 months following enrollment. Anchor- and distribution-based methods were used to assess MIDs, and the correspondence between MID ranges derived from each method was evaluated. ^ Results. This study indicates that an approximate range for MIDs of the FACT-M subscales is between 5 to 8 points for the Trial Outcome Index, 4 to 5 points for the Melanoma Combined Subscale, 2 to 4 points for the Melanoma Subscale, and 1 to 2 points for the Melanoma Surgery Subscale. Each method produced similar but not identical ranges of MIDs. ^ Conclusions. The properties of the anchor instrument employed to derive MIDs directly affect resulting MID ranges and point values. When MIDs are offered as supportive evidence of a clinically meaningful change, the anchor instrument used to derive thresholds should be clearly stated along with evidence supporting the choice of anchor instrument as the most appropriate for the domain of interest. In this analysis, the KPS was a more appropriate measure than the ECOG-PS for assessing MIDs. ^

Improving the Quality of Life of spousal caregivers of stroke survivors: A cost effectiveness analysis

Back ground and Purpose. There is a growing consensus among health care researchers that Quality of Life (QoL) is an important outcome and, within the field of family caregiving, cost effectiveness research is needed to determine which programs have the greatest benefit for family members. This study uses a multidimensional approach to measure the cost effectiveness of a multicomponent intervention designed to improve the quality of life of spousal caregivers of stroke survivors. Methods. The CAReS study (Committed to Assisting with Recovery after Stroke) was a 5-year prospective, longitudinal intervention study for 159 stroke survivors and their spousal caregivers upon discharge of the stroke survivor from inpatient rehabilitation to their home. CAReS cost data were analyzed to determine the incremental cost of the intervention per caregiver. The mean values of the quality-of-life predictor variables of the intervention group of caregivers were compared to the mean values of usual care groups found in the literature. Significant differences were then divided into the cost of the intervention per caregiver to calculate the incremental cost effectiveness ratio for each predictor variable. Results. The cost of the intervention per caregiver was approximately $2,500. Statistically significant differences were found between the mean scores for the Perceived Stress and Satisfaction with Life scales. Statistically significant differences were not found between the mean scores for the Self Reported Health Status, Mutuality, and Preparedness scales. Conclusions. This study provides a prototype cost effectiveness analysis on which researchers can build. Using a multidimensional approach to measure QoL, as used in this analysis, incorporates both the subjective and objective components of QoL. Some of the QoL predictor variable scores were significantly different between the intervention and comparison groups, indicating a significant impact of the intervention. The estimated cost of the impact was also examined. In future studies, a scale that takes into account both the dimensions and the weighting each person places on the dimensions of QoL should be used to provide a single QoL score per participant. With participant level cost and outcome data, uncertainty around each cost-effectiveness ratio can be calculated using the bias-corrected percentile bootstrapping method and plotted to calculate the cost-effectiveness acceptability curves.^