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利用记录的深度-时间剖面研究减压病。

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

机构信息

DAN America, Durham, North Carolina U.S.

SULA Diving, Stromness, Orkney UK.

出版信息

Undersea Hyperb Med. 2020 First Quarter;47(1):75-91. doi: 10.22462/01.03.2020.9.

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.

摘要

简介

在一项探索性研究中,记录了 11 家制造商的潜水电脑记录的 10358 名休闲潜水员的 122129 次潜水,研究潜水剖面、呼吸气体(空气或氮氧混合气[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 份报告被判断为减压病。总体 DCSobs 为每 104 次潜水 3.1 例。

方法

研究了三组潜水员:基础组(住船和岸/日船潜水)、科苏梅尔潜水指导员和斯卡帕流沉船潜水员。概率减压模型 BVM(3)控制潜水剖面的可变性。卡方检验、t 检验、逻辑回归和对数秩检验评估了统计学关联。

结果

(a)DCSobs 分别为每 104 次潜水 0.7(基础组)、7.6(指导员)和 17.3(斯卡帕),在控制潜水变异性后差异显著(p≺0.001)。(b)22%-29%氮氧混合气(12.6/104)的 DCSobs 大于 30%-50%氮氧混合气(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 小时的水面间隔(SI)),只有在一到两次潜水后才会发生减压病(4.3/10104 次潜水的 DCSobs;p≺0.001),其中 SI 短于三次或更多次潜水后。(d)对于多日重复潜水(SI≺48 小时),仅在指导员中,高多日重复潜水次数与减压病相关(p=0.0018)。(e)DCSobs 随年龄以每年 3%的速度下降(p≤0.0144)。(f)男性潜水深度更深(p≺0.001),但潜水时间比女性短(p≺0.001)。

结论

使用潜水电脑收集潜水剖面并通过概率建模控制剖面变异性是可行的,但由于观察到的减压病病例有限,分析结果需要独立确认。如果收集到更多的减压病病例、利益相关者合作以及纠正已确定的数据收集问题,未来的研究似乎很有前景。

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