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Emergency surface decompression and treatment procedures for project Tektite aquanauts, determining safe interval and schedules for return to habitat on ocean floor
Scanning ultrasonic imaging technique for in vivo monitoring of microscopic bubble formation in decompression sickness, presenting image displays
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.
A review of case reports, hypobaric chamber training data, and experimental evidence indicated that the threshold for incidence of altitude decompression sickness (DCS) was influenced by various factors such as prior denitrogenation, exercise or rest, and period of exposure, in addition to individual susceptibility. Fitting these data with appropriate statistical models makes it possible to examine the influence of various factors on the threshold for DCS. This approach was illustrated by logistic regression analysis on the incidence of DCS below 9144 m. Estimations using these regressions showed that, under a noprebreathe, 6-h exposure, simulated EVA profile, the threshold for symptoms occurred at approximately 3353 m; while under a noprebreathe, 2-h exposure profile with knee-bends exercise, the threshold occurred at 7925 m.
In a case-control study, researchers examined the risk of decompression sickness (DCS) in individual subjects with higher number of exposures. Of the 126 subjects, 42 showed one or more episodes of DCS. Examination of the exposure-DCS relationship by odds ratio showed a linear relationship. Stratification analysis showed that sex, tissue ratio, and the presence of Doppler microbubbles were cofounders of this risk. A higher number of exposures increased the risk of DCS in this analysis.
This study investigated the association between time at onset of circulating microbubbles (CMB) and symptoms of altitude decompression sickness (DCS), using Cox proportional hazard regression models. The study population consisted of 125 individuals who participated in direct ascent, simulated extravehicular activities profiles. Using individual CMB status as a time-dependent variable, we found that the hazard for symptoms increased significantly (at the end of 180 min at altitude) in the presence of CMB (Hazard Ratio = 29.59; 95 percent confidence interval (95 percent CI) = 7.66-114.27), compared to no CMB. Further examination was conducted on the subgroup of individuals who developed microbubbles during the test (n = 49), by using Cox regression. Individuals with late onset of CMB (greater than 60 min at altitude) showed a significantly reduced risk of symptoms (hazard ratio = 0.92; 95 percent CI = 0.89-0.95), compared to those with early onset (equal to or less than 60 min), while controlling for other risk factors. We conclude that time to detection of circulating microbubbles is an independent determinant of symptoms of DCS.
Hypobaric decompression sickness (DCS) research presents the medical monitor with the difficult task of assessing the onset and progression of DCS largely on the basis of subjective symptoms. Even with the introduction of precordial Doppler ultrasound techniques for the detection of venous gas emboli (VGE), correct prediction of DCS can be made only about 65 percent of the time according to data from the Armstrong Laboratory's (AL's) hypobaric DCS database. An AL research protocol concerned with exercise and its effects on denitrogenation efficiency includes implementation of a performance assessment test battery to evaluate cognitive functioning during a 4-h simulated 30,000 ft (9144 m) exposure. Information gained from such a test battery may assist the medical monitor in identifying early signs of DCS and subtle neurologic dysfunction related to cases of asymptomatic, but advanced, DCS. This presentation concerns the selection and integration of a test battery and the timely graphic display of subject test results for the principal investigator and medical monitor. A subset of the Automated Neuropsychological Assessment Metrics (ANAM) developed through the Office of Military Performance Assessment Technology (OMPAT) was selected. The ANAM software provides a library of simple tests designed for precise measurement of processing efficiency in a variety of cognitive domains. For our application and time constraints, two tests requiring high levels of cognitive processing and memory were chosen along with one test requiring fine psychomotor performance. Accuracy, speed, and processing throughout variables as well as RMS error were collected. An automated mood survey provided 'state' information on six scales including anger, happiness, fear, depression, activity, and fatigue. An integrated and interactive LOTUS 1-2-3 macro was developed to import and display past and present task performance and mood-change information.
A model that predicts the probability of developing decompression sickness (DCS) with various denitrogenation schedules is being developed by the Armstrong Laboratory, using human data from previous exposures. It was noted that refinements are needed to improve the accuracy and scope of the model. A commercially developed ultrasonic echo imaging system is being used in this model development. Using this technique, bubbles images from a subject at altitude can be seen in the gall bladder, hepatic veins, vena cava, and chambers of the heart. As judged by their motion and appearance in the vena cava, venous bubbles near the heart range in size from 30 to 300 M. The larger bubbles skim along the top, whereas the smaller ones appear as faint images near the bottom of the vessel. Images from growing bubbles in a model altitude chamber indicate that they grow rapidly, going from 20 to 100 M in 3 sec near 30,000 ft altitude. Information such as this is valuable in verifying those aspects of the DCS model dealing with bubble size, their growth rate, and their site of origin.
It would be of operational significance if one possessed a device that would indicate the presence of gas phase formation in the body during hypobaric decompression. Automated analysis of Doppler gas bubble signals has been attempted for 2 decades but with generally unfavorable results, except with surgically implanted transducers. Recently, efforts have intensified with the introduction of low-cost computer programs. Current NASA work is directed towards the development of a computer-assisted method specifically targeted to EVA, and we are most interested in Spencer Grade 4. We note that Spencer Doppler Grades 1 to 3 have increased in the FFT sonogram and spectrogram in the amplitude domain, and the frequency domain is sometimes increased over that created by the normal blood flow envelope. The amplitude perturbations are of very short duration, in both systole and diastole and at random temporal positions. Grade 4 is characteristic in the amplitude domain but with modest increases in the FFT sonogram and spectral frequency power from 2K to 4K over all of the cardiac cycle. Heart valve motion appears to characteristic display signals: (1) the demodulated Doppler signal amplitude is considerably above the Doppler-shifted blow flow signal (even Grade 4); and (2) demodulated Doppler frequency shifts are considerably greater (often several kHz) than the upper edge of the blood flow envelope. Knowledge of these facts will aid in the construction of a real-time, computer-assisted discriminator to eliminate cardiac motion artifacts. There could also exist perturbations in the following: (1) modifications of the pattern of blood flow in accordance with Poiseuille's Law, (2) flow changes with a change in the Reynolds number, (3) an increase in the pulsatility index, and/or (4) diminished diastolic flow or 'runoff.' Doppler ultrasound devices have been constructed with a three-transducer array and a pulsed frequency generator.
In both the aviation and space environments, decompression sickness (DCS) is an operational limitation. Hyperbaric recompression is the most efficacious treatment for altitude DCS. However, the inherent recompression of descent to ground level while breathing oxygen is in itself therapy for altitude DCS. If pain-only DCS occurs during a hypobaric exposure, and the symptoms resolver during descent, ground level post-flight breathing of 100% O2 for 2 hours (GLO2) is considered sufficient treatment by USAF Regulation 161-21. The effectiveness of the GLO2 treatment protocol is defined.
The perceived quality of images reconstructed from low bit rate compression is severely degraded by the appearance of transform coding artifacts. This paper proposes a method for producing higher quality reconstructed images based on a stochastic model for the image data. Quantization (scalar or vector) partitions the transform coefficient space and maps all points in a partition cell to a representative reconstruction point, usually taken as the centroid of the cell. The proposed image estimation technique selects the reconstruction point within the quantization partition cell which results in a reconstructed image which best fits a non-Gaussian Markov random field (MRF) image model. This approach results in a convex constrained optimization problem which can be solved iteratively. At each iteration, the gradient projection method is used to update the estimate based on the image model. In the transform domain, the resulting coefficient reconstruction points are projected to the particular quantization partition cells defined by the compressed image. Experimental results will be shown for images compressed using scalar quantization of block DCT and using vector quantization of subband wavelet transform. The proposed image decompression provides a reconstructed image with reduced visibility of transform coding artifacts and superior perceived quality.
Circulating microbubbles (CMB) are frequently detected prior to the appearance of symptoms of Decompression Sickness (DCS). It is difficult to analyze the effect of CMB on symptoms due to differences in the time to detection of CMB. This paper uses survival analysis models to evaluate the risk of symptoms in the presence of CMB. Methods: Information on 81 exposures to an altitude of 6,400 m (6.5 psi) for a period of three hours, with simulated extravehicular activities, was examined. The presence or absence of CMB was included as a time dependent covariate of the Cox proportional hazards regression model. Using this technique, the subgroup of exposures with CMB was analyzed further. Mean (S.D.) time in minutes to onset of CMB and symptoms were 125 (63) and 165 (33) respectively, following the three hours exposure. The risk of symptoms (17/81) increased 14 times in the presence of CMB, after controlling for variations in time to detection of CMB. Further, the risk was lower when time to detection of CMB was greater than 60 minutes (risk ratio = 0.96; 95 percent confidence intervals = 0.94 - 0.99 0.99 P less than 0.01) compared to CMB before 60 minutes at altitude. Conclusions: Survival analysis showed that individual risk of DCS changes significantly due to variations in time to detection of CMB. This information is important in evaluating the risk of DCS in the presence of CMB.
This paper presents algorithms for inferring global and spatially local estimates of the squared-error distortion measures for the Embedded Zerotree Wavelet (EZW) image compression algorithm. All distortion estimates are obtained at the decoder without significantly compromising EZW's rate-distortion performance. Two methods are given for propagating distortion estimates from the wavelet domain to the spatial domain, thus giving individual estimates of distortion for each pixel of the decompressed image. These local distortion estimates seem to provide only slight improvement in the statistical characterization of EZW compression error relative to the global measure, unless actual squared errors are propagated. However, they provide qualitative information about the asymptotic nature of the error that may be helpful in wavelet filter selection for low bit rate applications.
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.
We evaluated four 2-hour oxygen prebreathe protocols combining adynamia (non-walking) and 4 different amounts of exercise for potential use with extravehicular activity (EVA) on the International Space Station. Phase I: upper and lower body exercises using dual-cycle ergometry (75% VO2 max for 10 min). Phase 11: same ergometry plus 24 min of light exercise that simulated space suit preparations. Phase III: same 24 min of light exercise but no ergometry, and Phase IV: 56 min of light exercise without ergometry. After 80 min on 100% O2, the subjects breathed 26.5% O2 - 73.5% N2 for 30 min at 10.2 psi. All subjects performed a series of upper body exercises from a recumbent position for 4 hrs at 4.3 psi to simulate EVA work. Venous gas emboli (VGE) were monitored every 12 min using precordial Doppler ultrasound. The 39 female and 126 male exposures were analyzed for correlations between decompression sickness (DCS) or VGE, and risk variables. The duration and quantity of exercise during prebreathe inversely relates to DCS and VGE incidence. The type and distribution of the 19 cases of DCS were similar to historical cases. There was no correlation of age, gender, body mass index, or fitness level with greater incidence of DCS or all VGE. However there were more Grade IV VGE in males > 40 years (10 of 19) than in those =< 40 years (3 of 107), with p<0.01 from Fisher's Exact Chi square The latency time for VGE was longer (103 min +/- 56 SD, n = 15 versus 53 min +/- 31, n =13) when the ergometry occurred about 15 min into the prebreathe than when performed at the start of the prebreathe, but the order of the ergometry did not influence the overall DCS and VGE incidence. An increasing amount of exercise during prebreathes reduced the risk of DCS during subsequent exposures to 4.3 psi. Age, gender, or fitness level did not correlate with the incidence of DCS or VGE (combination of Grades I-IV). However males greater than 40 years had a higher incidence of Grade IV VGE.
The purpose was to develop an enhanced plan to diagnose, treat, and manage decompression sickness (DCS) during extravehicular activity (EVA). This plan is merited by the high frequency of upcoming EVAs necessary to construct and maintain the International Space Station (ISS). The upcoming ISS era will demand a significant increase in EVA. The DCS Risk and Contingency Plan provided a new and improved approach to DCS reporting, treatment, management, and training.
Exercise PB can reduce the risk of decompression sickness on ascent to 4.3 psia when performed at the proper intensity and duration. Data are from seven tests. PB times ranged from 90 to 150 min. High intensity, short duration dual-cycle ergometry was done during the PB. This was done alone, or combined with intermittent low intensity exercise or periods of rest for the remaining PB. Nonambulating men and women performed light exercise from a semi-recumbent position at 4.3 psia for four hrs. The Research Model with age tested the probability that DCS increases with advancing age. The NASA Model with gender hypothesized that the probability of DCS increases if gender is female. Accounting for exercise and rest during PB with a variable half-time compartment for computed tissue N2 pressure advances our probability modeling of hypobaric DCS. Both models show that a small increase in exercise intensity during PB reduces the risk of DCS, and a larger increase in exercise intensity dramatically reduces risk. These models support the hypothesis that aerobic fitness is an important consideration for the risk of hypobaric DCS when exercise is performed during the PB.
Mechanistic insight about "pain-only" decompression illness (DCI) is limited given indirect information about venous gas emboli (VGE) detected in the pulmonary artery with Doppler ultrasound. However, we show that VGE first detected late in an altitude exposure are closely associated with subsequent symptom onset. Knowing that VGE occur late is an indication that a symptom will occur soon, but this is not a sufficient condition to guarantee that a symptom will occur.