Download Free Altitude Decompression Sickness Risk Prediction Research Book in PDF and EPUB Free Download. You can read online Altitude Decompression Sickness Risk Prediction Research and write the review.

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.
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.
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.
Estimating the risk of decompression sickness (DCS) in aircraft operations remains a challenge, making the reduction of this risk through the development of operationally acceptable denitrogenation schedules difficult. In addition, the medical recommendations which are promulgated are often not supported by rigorous evaluation of the available data, but are instead arrived at by negotiation with the aircraft operations community, are adapted from other similar aircraft operations, or are based upon the opinion of the local medical community. We present a systematic approach for defining DCS risk in aircraft operations by analyzing the data available for a specific aircraft, flight profile, and aviator population. Once the risk of DCS in a particular aircraft operation is known, appropriate steps can be taken to reduce this risk to a level acceptable to the applicable aviation community. Using this technique will allow any aviation medical community to arrive at the best estimate of DCS risk for its specific mission and aviator population and will allow systematic reevaluation of the decisions regarding DCS risk reduction when additional data are available.
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.
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 exposure 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. In 1990, a new bubble growth algorithm and a statistical model based on the existing USAF DCS Database were initiated at Brooks AFB. The first version of this combined model was completed in 1996. A model validation study using human subjects was completed in 1999. An updated version of this model based on the validation results has been produced and the software developed. A portable hand-held model is being developed for use in situations requiring more flexible operations (e.g.; high altitude parachuting). Application of this technology would specifically aid aviators, special operations personnel, and civilian aviators in determining altitude DCS risk.
There is considerable variability in individual susceptibility to altitude decompression sickness (DCS). The air Force Research Laboratory Altitude DCS Research Database consists of extensive information on 2980 altitude exposures conducted with consistent procedures and endpoint criteria. We used this database to quantify the variation in susceptibility and determine if anthropometric and/or physiologic variables could be used to predict DCS risk. There were 240 subjects who participated in at least 4 of 70 exposure profiles in which between 5 and 95% of all subjects tested developed DCS symptoms. A Subject/Study Ratio (SSR) was calculated by dividing the DCS experienced by a subject during all their exposures by the DCS incidence for all subjects who participated in the identical exposures. The SSR was used to identify the relative susceptibility of subjects for use in analyzing possible relationships between DCS susceptibility and the variables of height, weight, body mass index, age, percent body fat, and aerobic capacity. The DCS incidence was 46.5% during 1879 subject-exposures by subjects exposed at least 4 times. A significant relationship existed between higher DCS susceptibility and only the combination of lower aerobic capacity and greater weight (P
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...
Air Force personnel are routinely exposed to atmospheric decompressions that often incur significant risk of decompression sickness (DCS). Management of these risks requires analytic methods able to: (a) define risk/hazard envelopes for all routine and emergency decompressions, (b) assess the DCS risks included or introduced in the contemplation or design of new operational procedures and equipment, and; (c) support real-time monitoring of DCS risk incurred by personnel during various chamber and aircraft operations. Present work contributed to meeting these requirements through development and application of methods by which DCS risks during decompression profiles are determined from statistical/biophysical models of in vivo gas exchange and bubble growth and resolution using maximum likelihood, both logistic and survival models were fit to DCS incidence data from the USAF Armstrong Laboratory (USAFAL) for a wide variety of decompression profiles. The models were incorporated into software that operates on personal computers. System software, including a data transcription routine to serve as a software interface between the USAFAL Hypobaric Decompression Sickness Database and the present modeling system, was delivered for use and evaluation of USAFAL personnel.