A study of decompression sickness using recorded depth-time profiles.

IF 0.7
Richard G Dunford, Petar D Denoble, Robert Forbes, Carl F Pieper, Laurens E Howle, Richard D Vann
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Abstract

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.

利用记录的深度-时间剖面研究减压病。
介绍:在一项探索性研究中,来自11家制造商的潜水计算机记录了10358名休闲潜水员的122129次潜水,研究了潜水剖面、呼吸气体(空气或氮气[N2/O2]混合物)、重复潜水、性别、年龄和潜水地点条件如何影响观察到的减压病(DCSobs)。38份报告被判定为DCS。总体DCSobs为3.1例/10⁴次。方法:研究了三个潜水组:基本潜水组(船上生活和岸上/日船),科苏梅尔潜水向导和斯卡帕流沉船潜水员。概率减压模型BVM(3)控制了潜水剖面的可变性。卡方检验、t检验、逻辑回归和log-rank检验评估了统计相关性。结果:(a) DCSobs为0.7/10⁴(Basic), 7.6/10⁴(Guides)和17.3/104 (Scapa),并且在控制后潜水变异性不同(p < 0.001)。(b) 22%-29%硝基(12.6/10⁴)的DCSobs大于30%-50%硝基(2.04/10⁴)(p≤0.0064),与空气(2.97/1010⁴)无差异。(c)对于每日重复潜水(12小时水面间隔(SI)), DCS仅在一次或两次潜水后发生(4.3/1010⁴DCSobs;p < 0.001),其中SIs比三次或更多次潜水后短。(d)对于多日重复潜水(SIs = 48小时),DCS与高多日重复潜水计数仅与向导相关(p = 0.0018)。(e) DCSobs随着年龄的增长而下降,为3%/年(p≤0.0144)。(f)雄性比雌性潜水更深(p{0.001}),但时间较短(p{0.001})。结论:利用潜水计算机收集潜水剖面并通过概率建模控制剖面变异性是可行的,但由于观测到的DCS有限,分析结果需要独立验证。如果收集更多的DCS案例,利益相关者合作,并纠正已确定的数据收集问题,那么未来的研究似乎很有希望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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