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Non‐Invasive Pulmonary Gas Exchange Measurements Following Deep Breath‐Hold Diving

2019· article· en· W3015537056 on OpenAlexafffundabout
Alexander Patrician, Ivan Drviš, Tony G. Dawkins, B. MUNCHOW OTTO, Geoff B. Coombs, Connor A. Howe, Hannah G. Caldwell, Nebojša Janjić, Boris Spajić, Željko Dujić, Philip N. Ainslie

Bibliographic record

VenueThe FASEB Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and Diving-Related Complications
Canadian institutionsOkanagan University College
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMedicinePulmonary arteryCardiologyAnesthesiaTidal volumeParasternal lineLungInternal medicineRespiratory system

Abstract

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Breath‐hold diving is a ubiquitous activity, with recreational, fishing, military and competitive divers. During a dive, immersion and the increasing hydrostatic pressure of descent facilitate cardiovascular adjustments that promote a blood volume shift into the heart and chest vasculature, further augmenting autonomic responses (i.e. diving bradycardia, peripheral vasoconstriction, and splenic contraction) to conserve O 2 . Exceeding the compliant capacity of the lung and associated tissues can result in pulmonary injury called squeeze, which is characterized by post‐dive coughing, wheezing and hemoptysis. To provide insight into the consequences of such lung squeeze, our objective was to evaluate the time‐course of a maximal deep dive on pulmonary gas exchange, pulmonary artery systolic pressures (PASP), and ultrasound lung comets (ULCs). Ten healthy trained breath‐hold divers (33±9 yr; 80±15 kg; 185±9 cm) performed a maximal effort dive (55±12 m; range 40–76 m). Pulmonary gas exchange and PASP were performed at baseline, and repeated at 10 and 60 min post dive. Pulmonary gas exchange was non‐invasively measured by collecting end‐tidal PO 2 and PCO 2 during steady‐state breathing, and derived arterial PO 2 via pulse oximetry. O 2 deficit was defined as the difference between end‐tidal and calculated arterial PO 2 ; consistent with the Bohr effect by utilizing end‐tidal PCO 2 . The ULCs were collected bilaterally, parasternal to mid‐axillary, at baseline and again 2.5 h post dive. Following the dive, although there was an impairment of pulmonary gas exchange, evident by an increase in O 2 deficit from 10.9±4.5 mmHg at baseline to 22.9±5.1 mmHg 10‐min post dive (p=0.02), this deficit had normalized by 60‐min post. There was persistent hyperventilation up to 60 min post dive, reflected by reductions in end‐tidal PCO 2 (p=0.02). PASP was unaltered post‐dive. Although ULCs trended to increase from baseline to 2.5 h post dive (3.7±3 to 10.4±13.2 comets; p=0.09), the delta change in ULC from baseline to post‐dive was positively correlated with depth (r=0.67, p=0.04) and, to a lesser extent, with both change in SpO 2 (r=−0.62, p=0.06) and O 2 deficit (r=0.58, p=0.08). The findings of this novel study suggest impairment in pulmonary gas exchange is present following diving to depth, even up to 10 min after surfacing. The mechanism(s) driving the slight hyperventilation are unclear, but potentially could be mediated via mild pulmonary edema and/or stimulation of juxtapulmonary capillary receptors. Together, there is transient impairment in gas exchange and associations with ULC during ‘modest’ dives. The development of pathological pulmonary edema, and severe and sustained impairment in pulmonary gas exchange, would seem likely at the forefront of breath‐hold diving performances (e.g, >100 m). There remains little data regarding safe return‐to‐dive practices following a squeeze, and non‐invasive pulmonary gas exchange monitoring could provide valuable utility. Support or Funding Information Canada Research Chair, NSERC This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.250
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2019
Admission routes3
Has abstractyes

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