Abstract
Decompression sickness is a complex phenomenon involving gas exchange, bubble dynamics and tissue response. Relatively simple deterministic compartmental models using empirically derived parameters have been the mainstay of the practice for preventing decompression sickness since the early 1900s. Decades of research have improved our understanding of decompression physiology, and the insights incorporated in decompression models have allowed people to dive deeper into the ocean. However, these efforts have not yet, and are unlikely in the near future, to result in a ‘universal’ deterministic model that can predict when decompression sickness will occur. Divers using current recreational dive computers need to be aware of their limitations. Probabilistic models based on the estimation of parameters using modern statistical methods from large databases of dives offer a new approach and can provide a means of standardisation of deterministic models. Future improvements in decompression practice will depend on continued improvement in understanding the kinetics and dynamics of gas exchange, bubble evolution and tissue response, and the incorporation of this knowledge in risk models whose parameters can be estimated from large databases of human and animal data.
Similar content being viewed by others
References
Elliot DH, Moon RE. Manifestations of the decompression disorders. In: Bennett PB, Elliott DH, editors. The physiology and medicine of diving. London: WB Saunders, 1993: 481–505
Francis TJR, Gorman DF. Pathogenesis of the decompression disorders. In: Bennett PB, Elliott DH, editors. The physiology and medicine of diving. London: WB Saunders, 1993: 454–80
Vann RD, Thalmann ED. Decompression physiology and practice. In: Bennett PB, Elliott DH, editors. The physiology and medicine of diving. London: WB Saunders, 1993: 376–432
Berghage TE, Durman D. US Navy air decompression schedule risk analysis. Bethesda (MD): Naval Medical Research Institute 1980, Report No. NMRI: 80-1
Flynn ET, Parker EC, Ball R. Risk of decompression sickness in shallow no-stop air diving: an analysis of Naval Safety Center data 1990–1994. Bethesda (MD): Naval Medical Research Institute 1998: NMRI Technical Report 98-108
Arness MK. Scuba decompression illness and diving fatalities in an overseas military community. Aviat Space Environ Med 1997; 68: 325–33
Hempleman HV. History of decompression procedures. In: Bennett PB, Elliott DH, editors. The physiology and medicine of diving. London: WB Saunders, 1993: 342–75
Boycott AE, Damant GCC, Haidane JS. Prevention of compressed air illness. J Hyg (Lond) 1908; 8: 342–443
Gray JS, Wigodski HS, Masland RL, et al. Studies on altitude decompression sickness IV: attempts to avoid decompression sickness by selection of resistant personnel. J Aviat Med 1947; 18: 88–95
Berghage TE, Wooley JM, Keating LJ. The probabilistic nature of decompression sickness. Undersea Biomed Res 1974; 1: 189–96
Weathersby PK, Homer LD, Flynn ET. On the likelihood of decompression sickness. J Appl Physiol 1984; 57: 815–25
Weathersby PK, Survanshi SS, Homer LD, et al. Predicting the time of occurrence of decompression sickness. J Appl Physiol 1992; 72: 1541–8
Weathersby PK. Quantitative risk management of DCS. In: Lang MA, Lehner CE, editors. Proceedings of reverse dive profiles workshop; 1999 Oct 29–30; Washington DC: Smithsonian Institution, 2000: 203–6
Woodward CM. A History of the St. Louis Bridge. St. Louis (MS): GI Jones and Company, 1881
Yarborough OD. Calculation of decompression tables. Panama City (FL): US Navy Experimental Diving Unit Report, 1937
Flynn ET, Catron PW, Bayne CG. Diving Medical Officer Student Guide. Panama City (FL): Naval Technical Training Command, Naval Diving and Salvage Training Center, 1981
Workman RD. Calculation of air saturation decompression tables. Panama City (FL): Naval Experimental Diving Unit; 1957: Report No. 11-57
Naval Sea Systems Command. US Navy Diving Manual, Vol. 1 (Air Diving). Revision 3. Washington DC: Naval Sea Systems Command, 1993
Thalmann ED. Phase II testing of decompression algorithms for use in the US Navy underwater decompression computer. Panama City (FL): Naval Experimental Diving Unit; 1984: Report No. NEDU 1-84
Thalmann ED. Air N2-O2 decompression computer algorithm development. Panama City (FL): Naval Experimental Diving Unit, 1986: Report No. NEDU 8-85
Hamilton RW, Powell MR, Vann RD. The DSAT recreational dive planner. Tarrytown (NY): Diving Science and Technology Inc. and Hamilton Research Ltd, 1994
Spencer MP. Decompression limits for compressed air determined by ultrasonically detected blood bubbles. J Appl Physiol 1976; 40: 229–35
Hamilton RW, editor. The effectiveness of dive computers in repetitive diving. Kensington (MD): Undersea and Hyperbaric Medical Society, 1995
Edmonds C. Misuse of model based decompression computers: the need for validation. In: Hamilton RW, editor. The effectiveness of dive computers in repetitive diving. Kensington (MD): Undersea and Hyperbaric Medical Society, 1995: 3–10
Buhlmann AA. Behavior of dive computer algorithms in repetitive dives. Experience and needed modifications. In: Hamilton RW, editor. The effectiveness of dive computers in repetitive diving. Kensington (MD): Undersea and Hyperbaric Medical Society, 1995: 11–8
Hahn MH. Workman-Buhlmann algorithm for dive computers: a critical analysis. In: Hamilton RW, editor. The effectiveness of dive computers in repetitive diving. Kensington (MD): Undersea and Hyperbaric Medical Society, 1995: 19–26
Lang MA, moderator. Dive computers panel discussion. In: Lang MA, Lehner CE, editors. Proceedings of reverse dive profiles workshop; 1999 Oct 29–30; Washington (DC): Smithsonian Institution, 2000: 172–80
Weathersby PK, Meyer P, Flynn ET, et al. Nitrogen gas exchange in the human knee. J Appl Physiol 1986; 61: 1534–45
Novotny JA, Mayers DL, Parsons YF, et al. Xenon kinetics in muscle are not explained by a model of parallel perfusion-limited compartments. J Appl Physiol 1990; 68: 876–90
Homer LD, Weathersby PK, Survanshi S. How countercurrent blood flow and uneven perfusion affect the motion of inert gas. J Appl Physiol 1990; 69: 162–70
Himm JF, Homer LD, Novotny JA. Effect of lipid on inert gas kinetics. J Appl Physiol 1994; 77: 303–12
Hills BA. Effect of decompression per se on nitrogen elimination. J Appl Physiol 1978; 45: 916–21
D’Aoust BG, Smith KH, Swanson HT. Decompression-induced decrease in nitrogen elimination rate in awake dogs. J Appl Physiol 1976; 41: 348–55
Kindwall EP, Baz A, Lightfoot EN, et al. Nitrogen elimination in man during decompression. Undersea Biomed Res 1975; 4: 285–97
Van Liew HD, Burkard ME. Density of decompression bubbles and competition for gas among bubbles, tissue, and blood. J Appl Physiol 1993; 75: 2293–30
Desgrange M. Standard air decompression table. Panama City (FL): Naval Experimental Diving Unit 957; Report No. 5-57
Weathersby PK, Survanshi SS, Hays JR, et al. Statistically based decompression tables III: comparative risk using US Navy, British, and Canadian standard air schedules. Bethsheda (MD): Naval Medical Research Institute, 1986: NMRI Technical Report 86-50
Schubert RW, Zhang X. The equivalent Krogh cylinder and axial oxygen transport. Adv Exp Med Biol 1997; 411: 191–202
Van Liew HD. Simulation of the dynamics of decompression sickness bubbles and the generation of new bubbles. Undersea Biomed Res 1991; 4: 333–45
Ball R, Himm J, Homer LD, et al. A model of bubble evolution during decompression based on a Monte Carlo simulation of inert gas diffusion. Bethesda (MD): Naval Medical Research Institute, 1994: Report No. NMRI 94-36
Ball R, Himm J, Homer LD, et al. Does the time course of bubble evolution explain decompression sickness risk? Undersea Hyperb Med 1995; 22: 263–80
Burkard ME, Van Liew HD. Effects of physical properties of the breathing gas on decompression-sickness bubbles. J Appl Physiol 1995; 79: 1828–36
Van Liew HD, Burkard ME. Bubbles in circulating blood: stabilization and simulations of cyclic changes of size and content. J Appl Physiol 1995; 79: 1379–85
Jiang Y, Homer LD, Thalmann ED. Development and interactions of two inert gas bubbles during decompression. Undersea Hyperb Med 1996; 23: 131–40
Srinivasan RS, Gerth WA, Powell MR. Mathematical models of diffusion-limited gas bubble dynamics in tissue. J Appl Physiol 1999; 86: 732–41
Himm JF, Homer LD. A model of extravascular bubble evolution: effect of changes in breathing gas. J Appl Physiol 1999; 87: 1521–31
Halpern D, Jiang Y, Himm JF. Mathematical model of gas bubble evolution in a straight tube. J Biomech Eng 1999; 121: 505–13
Nikolae VP. Effects of heterogeneous structure and diffusion permeability of body tissues on decompression gas bubble dynamics. Aviat Space Environ Med 2000; 71: 723–9
Thalmann ED, Parker EC, Survanshi SS, et al. Improved probabilistic decompression model risk predictions using linearexponential kinetics. Undersea Hyperb Med 1997; 24: 255–74
Parker EC, Survanshi SS, Massell PB, et al. Probabilistic models of the role of oxygen in human decompression sickness. J Appl Physiol 1998; 84: 1096–102
Survanshi SS. Statistically based decompression tables X. Real time decompression algorithm using a probabilistic model. Bethesda (MD): Naval Medical Research Institute, 1996: Report No. NMRI 96-06
Thalmann ED, Kelleher PC, Survanshi SS, et al. Statistically based decompression tables XI: manned validation of the LE probabilistic model for air and nitrogen-oxygen diving. Bethesda (MD): Naval Medical Research Center, 1999: Report No. NMRC 99-01
Survanshi SS, Parker EC, Thalmann ED, et al. Statistically based decompression tables XII: repetitive decompression tables for air and constant 0.7 ATA PO2 in N2 using a probabilistic model. Bethesda (MD): Naval Medical Research Institute, 1997: Report No. NMRI 97-36
Valaik DJ, Parker EC, Survanshi SS. Calculating decompression in naval special warfare SEAL delivery vehicle diving operations utilizing the real time dive planner. Bethesda (MD): Naval Medical Research Institute, 1996: Report No. NMRI 96-54
Ball R, Parker EC. A trial to determine the risk of decompression sickness after a 40 feet of sea water for 200 minute nostop air dive. Aviat Space Environ Med 2000; 71: 102–8
Tikuisis P, Gault KA, Nishi RY. Prediction of decompression illness using bubble models. Undersea Hyperb Med 1994; 21: 129–43
Gerth WA, Vann RD. Probabilistic gas and bubble dynamics models of decompression sickness occurrence in air and nitrogen-oxygen diving. Undersea Hyperb Med 1997; 24: 275–92
Gerth WA, Vann RD. Development of iso-DCS risk air and nitrox decompression tables using statistical bubble dynamics models. Washington (DC): National Oceanic and Atmospheric Administration, 1996: NOAA Award No. NA46RU0505
Eckehoff RG, Olstad CS, Carrod G. Human dose-response relationship for decompression and endogenous bubble formation. J Appl Physiol 1990; 69: 914–8
Bayne CG, Hunt WS, Johanson DC, et al. Doppler bubble detection and decompression sickness: a prospective clinical trial. Undersea Biomed Res 1985; 12: 327–32
Tikuisis P, Gault K, Carrod G. Maximum likelihood analysis of bubble incidence for mixed gas diving. Undersea Biomed Res 1990; 17: 159–69
Gault KA, Tikuisis P, Hishi RY. Calibration of a bubble evolution model to observed bubble incidence in divers. Undersea Hyperb Med 1995; 22: 249–62
Lehner CE, moderator. Physiology/modeling session discussion. In: Lang MA, Lehner CE, editors. Proceedings of Reverse Dive Profiles Workshop; 1999 Oct 29–30; Washington DC: Smithsonian Institution, 2000: 141–44
Nishi RY, Tikuisis P, Survanshi SS, et al. A comparison of probabilistic models of decompression based on DCS and VGE [abstract]. Undersea Hyperb Med 1997; 24 Suppl.: 29
Piantadosi S. Clinical trials: a methodologic perspective. New York: John Wiley & Sons, Inc., 1997
Survanshi SS, Weathersby PK. Rational decompression trials produce biased data [abstract]. Undersea and Hyperbaric Medicine 1998; 25 Suppl.: 36
Rubin DB. More powerful randomization-based p-values in double-blind trials with non-compliance. Stat Med 1998; 17: 371–85
Sheiner LB, Ludden TM. Population pharmacokinetics/dynamics. Annu Rev Pharmacol Toxicol 1992; 32: 185–209
Gernhart ML. Development and evaluation of a decompression stress index based on tissue bubble dynamics [dissertation]. Philadelphia (PA): University of Pennsylvania, 1991
Gerth WA, Thalmann ED. Estimated DCS risks of reverse profiles. In: Lang MA, Lehner CE, editors. Proceedings of reverse dive profiles workshop; 1999 Oct 29–30; Washington DC. Smithsonian Institution, 2000: 145–70
Donald KW. Oxygen bends. J Appl Physiol 1955; 7: 639–44
Weathersby PK, Hart BL, Flynn ET, et al. Role of oxygen in the production of human decompression sickness. J Appl Physiol 1987; 63: 2380–7
Harabin AL, Survanshi SS, Homer LD. A model for predicting central nervous system oxygen toxicity from hyperbaric oxygen exposures in humans. Toxicol Appl Pharmacol 1995; 132: 19–26
Temple D, Ball R, Weathersby PK, et al. Dive profiles and manifestations of decompression sickness cases after air and nitrogen oxygen dives. Bethesda (MD): Naval Medical Research Center, 1999: Report No. NMRC 99-02
Divers Alert Network. Project dive exploration [online]. Available from URL: http://www.diversalertnetwork.org. [Accessed 2002 Apr 30]
Ball R, Lehner CE, Parker EC. Predicting decompression sickness risk in humans from outcomes in sheep. J Appl Physiol 1999; 86: 1920–9
Acknowledgements
The opinions expressed in this paper are those of the authors and do not reflect the official policy or position of the Food and Drug Administration, the Department of Health and Human Services, the Department of Defense, or the US Government.
Author information
Authors and Affiliations
Corresponding author
Additional information
Dr Ball was affiliated to the Naval Medical Research Unit between 1995 and 1997.
Rights and permissions
About this article
Cite this article
Ball, R., Schwartz, S.L. Kinetic and Dynamic Models of Diving Gases in Decompression Sickness Prevention. Clin Pharmacokinet 41, 389–402 (2002). https://doi.org/10.2165/00003088-200241060-00001
Published:
Issue Date:
DOI: https://doi.org/10.2165/00003088-200241060-00001