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It is important to understand the risk of serious hypobaric decompression sickness (DCS) to develop procedures and treatment responses to mitigate the risk. Since it is not ethical to conduct prospective tests about serious DCS with humans, the necessary information was gathered from 73 published reports. We hypothesize that a 4-hr 100% oxygen (O2) prebreathe results in a very low risk of serious DCS, and test this through analysis. We evaluated 258 tests containing information from 79,366 exposures in altitude chambers. Serious DCS was documented in 918 men during the tests. A risk function analysis with maximum likelihood optimization was performed to identify significant explanatory variables, and to create a predictive model for the probability of serious DCS [P(serious DCS)]. Useful variables were Tissue Ratio, the planned time spent at altitude (Talt), and whether or not repetitive exercise was performed at altitude. Tissue Ratio is P1N2/P2, where P1N2 is calculated (N2) pressure in a compartment with a 180-min half-time for N2 pressure just before ascent, and P2 is ambient pressure after ascent. A prebreathe and decompression profile Shuttle astronauts use for extravehicular activity (EVA) includes a 4-hr prebreathe with 100% O2, an ascent to P2=4.3 lb per sq. in. absolute, and a Talt=6 hr. The P(serious DCS) is: 0.0014 (0.00096-0.00196, 95% confidence interval) with exercise and 0.00025 (0.00016-0.00035) without exercise. Given 100 Shuttle EVAs to date and no report of serious DCS, the true risk is less than 0.03 with 95% confidence (Binomial Theorem). It is problematic to estimate the risk of serious DCS since it appears infrequently, even if the estimate is based on thousands of altitude chamber exposures. The true risk to astronauts may lie between the extremes of the confidence intervals since the contribution of other factors, particularly exercise, to the risk of serious DCS during EVA is unknown. A simple model that only accounts for four important variables in retrospective data is still helpful to increase our understanding about the risk of serious DCS.
Survival Analysis methods have been used to model the onset of Decompression Sickness (DCS) which occurs routinely as a result of high altitude exposure. Both parametric and nonparametric models were developed. These models were used to predict the risk of DCS for different flight profiles. The risk factors that have a significant effect on the risk of DCS were also identified. Cross validation techniques are provided to examine the goodness of fit of the model. The loglogistic model was modified to incorporate data on bubble grades and times.
In response to the need for a standardized methodology for altitude decompression sickness risk assessment across the wide range of exposures encountered in USAF flight operations, the Armstrong Laboratory's Crew Technology Division initiated a research program in this area in late 1989. The focus of work has been on determining whether development of an operational altitude decompression computer for both predictive and real-time DCS risk assessment is feasible, given the current level of understanding about altitude decompression sickness, the amount of available experimental data, and the inherent variability in individual susceptibility to altitude DCS. The results of this feasibility study indicate that although some technical risk is involved, development of the proposed altitude decompression computer is feasible. This was demonstrated through the implementation of a simplified, preliminary model for altitude DCS risk assessment. This technical report documents the work accomplished during this research effort and provides a road map for development of the desired operational altitude decompression computers.
The effect of different rates of ascent on the incidence of altitude decompression sickness (DCS) was analyzed by a retrospective study on 14,123 man-flights involving direct ascent up to 38,000 ft altitude. The data were classified on the basis of altitude attained, denitrogenation at ground level, duration of stay at altitude, rest or exercise while at altitude, frequency of exercise at altitude, and ascent rates. This database was further divided on the basis of ascent rates into different groups from 1000 ft/min up to 53,000 ft/min. The database was analyzed using multiple correlation and regression methods, and the results of the analysis reveal that ascent rates influence the incidence of DCS in combination with the various factors mentioned above. Rate of ascent was not a significant predictor of DCS and showed a low, but significant multiple correlation (R=0.31) with the above factors. Further, the effects of rates below 2500 ft/min are significantly different from that of rates above 2500 ft/min on the incidence of symptoms (P=0.03) and forced descent (P=0.01). At rates above 2500 ft/min and up to 53,000 ft/min, the effects of ascent rates are not significantly different (P greater than 0.05) in the population examined while the effects of rates below 2500 ft/min are not clear. Kumar, K. V. and Waligora, James M. Johnson Space Center...
High altitude exposure in aircraft hypobaric chambers and with extravehicular- activity (EVA) in space results in an inherent risk of altitude decompression sickness (DCS). In the past general guidelines for safer altitude exposures have been developed through costly time-consuming studies each specific to unique scenarios of altitude exposure. Rapidly changing technology in aircraft design and mission requirements demand improved capabilities in predicting DCS risk during mission planning and execution.
Periodically, the literature contains case histories of fatal decompression sickness or cases involving permanent residua due to exposure to high altitude.
To predict altitude decompression sickness (DCS) risk with any degree of accuracy, one must weigh variables such as prebreathe time, rate of ascent/ descent, time at altitude, altitude, mixed breathing gas (dependent upon altitude), and profiles with multiple ascents and descents. The length of research chamber exposures is fixed. Therefore, risk assessment is based on DCS incidence after this fixed period at simulated altitude. From an operational standpoint, variable time at altitude complicates any predictive capability, although a computer model to handle all of these variables is in development. In the interim, a retrospective study from the Armstrong Laboratory Decompression Sickness Research Database has produced risk curves which can be used to predict DCS or venous gas emboli (VGE) incidence as a function of time at various altitudes. We limited the data to: (1) zero-prebreathe exposures to less than 20,000 ft breathing 50% O2, 50% N2; (2) zero-prebreathe exposures to less than 20,000 ft breathing 100% O2; and (3) 1-h prebreathe exposures to greater than 20,000 ft breathing 100% 02. Using the curves, one can select a time/altitude of exposure and estimate the DCS and VGE percentage. Decompression sickness, Venous gas emboli, Prebreathe, Latency.
The investigation uses biomathematical modeling techniques and a computer to derive predictive formulas and other information about the incidence of altitude bends in humans with relation to prior denitrogenation, activity at altitude, and individual physiological characteristics. The models represent pertinent human functions such as respiration and metabolism, and predict the effects of changes in these functions, as induced by alterations in total pressure, work level, and denitrogenation, on the work level, and denitrogenation, on the formation and composition of bubbles in tissues. Bends is believed caused by the growth of gas bubbles in the blood and other tissues and their accumulation at specific locations, especially at the joints. The computer models are exposed to the range of conditions known to cause bends at altitude. Among other findings, model results strongly suggest that the rise in body-core temperature that accompies exercise increases the incidence of bends at altitude. Thus, techniques that control core temperature near normal at altitude may be useful preventives. (Author).