- Messages
- 20,485
- Reaction score
- 19,847
- Location
- Philadelphia and Boynton Beach
- # of dives
- 1000 - 2499
DAN's Project Dive Exploration was published in early 2020. I was unaware of its publication and only recently found it, while perusing DAN's updated website
The results of the study were limited by the small number of cases of DCS reported. I entered nearly 400 dives into the database from 2006-2011, while I was diving a Cochran computer. I had no episodes of DCS. My hope was that the study might led some light on the relative risk for DCS when diving a liberal vs. a conservative computer. Unfortunately, that was not to be. The abstract is posted below, the full article has limited access.
Observational Study > Undersea Hypeb Med First-Quarter 2020;47(1):75-91
.
A study of decompression sickness using recorded depth-time profiles
Richard G Dunford 1, Petar D Denoble 1, Robert Forbes 2, Carl F Pieper 3, Laurens E Howle 4, Richard D Vann 5 4 6
Affiliations
Introduction: 122,129 dives by 10,358 recreational divers were recorded by dive computers from 11 manufacturers in an exploratory study of how dive profile, breathing gas (air or nitrox [N2/O2] mixes), repetitive diving, gender, age, and dive site conditions influenced observed decompression sickness (DCSobs). Thirty-eight reports were judged as DCS. Overall DCSobs was 3.1 cases/10⁴ dives.
Methods: Three dive groups were studied: Basic (live-aboard and shore/dayboat), Cozumel Dive Guides, and Scapa Flow wreck divers. A probabilistic decompression model, BVM(3), controlled dive profile variability. Chi-squared test, t-test, logistic regression, and log-rank tests evaluated statistical associations.
Results: (a) DCSobs was 0.7/10⁴ (Basic), 7.6/10⁴ (Guides), and 17.3/104 (Scapa) and differed after control for dive variability (p ≺ 0.001). (b) DCSobs was greater for 22%-29% nitrox (12.6/10⁴) than for 30%-50% nitrox (2.04/10⁴) (p ≤ 0.0064) which did not differ from air (2.97/1010⁴). (c) For daily repetitive dives (≺12-hour surface intervals (SI)), DCS occurred only following one or two dives (4.3/1010⁴ DCSobs; p ≺ 0.001) where SIs were shorter than after three or more dives. (d) For multiday repetitive dives (SIs ≺ 48 hours), DCS was associated with high multiday repetitive dive counts only for Guides (p = 0.0018). (e) DCSobs decreased with age at 3%/year (p ≤ 0.0144). (f) Males dived deeper (p ≺ 0.001) but for less time than females (p ≺ 0.001).
Conclusion: Collecting dive profiles with dive computers and controlling for profile variability by probabilistic modeling was feasible, but analytical results require independent confirmation due to limited observed DCS. Future studies appear promising if more DCS cases are gathered, stakeholders cooperate, and identified data collection problems are corrected.
Keywords: DCS incidence; DCS probability; age; decompression illness; decompression sickness; dive conditions; gender; nitrox breathing gases; repetitive diving.
Copyright© Undersea and Hyperbaric Medical Society.
The results of the study were limited by the small number of cases of DCS reported. I entered nearly 400 dives into the database from 2006-2011, while I was diving a Cochran computer. I had no episodes of DCS. My hope was that the study might led some light on the relative risk for DCS when diving a liberal vs. a conservative computer. Unfortunately, that was not to be. The abstract is posted below, the full article has limited access.
Observational Study > Undersea Hypeb Med First-Quarter 2020;47(1):75-91
.
A study of decompression sickness using recorded depth-time profiles
Richard G Dunford 1, Petar D Denoble 1, Robert Forbes 2, Carl F Pieper 3, Laurens E Howle 4, Richard D Vann 5 4 6
Affiliations
- PMID: 32176949
Introduction: 122,129 dives by 10,358 recreational divers were recorded by dive computers from 11 manufacturers in an exploratory study of how dive profile, breathing gas (air or nitrox [N2/O2] mixes), repetitive diving, gender, age, and dive site conditions influenced observed decompression sickness (DCSobs). Thirty-eight reports were judged as DCS. Overall DCSobs was 3.1 cases/10⁴ dives.
Methods: Three dive groups were studied: Basic (live-aboard and shore/dayboat), Cozumel Dive Guides, and Scapa Flow wreck divers. A probabilistic decompression model, BVM(3), controlled dive profile variability. Chi-squared test, t-test, logistic regression, and log-rank tests evaluated statistical associations.
Results: (a) DCSobs was 0.7/10⁴ (Basic), 7.6/10⁴ (Guides), and 17.3/104 (Scapa) and differed after control for dive variability (p ≺ 0.001). (b) DCSobs was greater for 22%-29% nitrox (12.6/10⁴) than for 30%-50% nitrox (2.04/10⁴) (p ≤ 0.0064) which did not differ from air (2.97/1010⁴). (c) For daily repetitive dives (≺12-hour surface intervals (SI)), DCS occurred only following one or two dives (4.3/1010⁴ DCSobs; p ≺ 0.001) where SIs were shorter than after three or more dives. (d) For multiday repetitive dives (SIs ≺ 48 hours), DCS was associated with high multiday repetitive dive counts only for Guides (p = 0.0018). (e) DCSobs decreased with age at 3%/year (p ≤ 0.0144). (f) Males dived deeper (p ≺ 0.001) but for less time than females (p ≺ 0.001).
Conclusion: Collecting dive profiles with dive computers and controlling for profile variability by probabilistic modeling was feasible, but analytical results require independent confirmation due to limited observed DCS. Future studies appear promising if more DCS cases are gathered, stakeholders cooperate, and identified data collection problems are corrected.
Keywords: DCS incidence; DCS probability; age; decompression illness; decompression sickness; dive conditions; gender; nitrox breathing gases; repetitive diving.
Copyright© Undersea and Hyperbaric Medical Society.
