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Record W4293105015 · doi:10.22462/05.06.2022.9

Cardiovascular risk assessment in divers: Toward safer diving

2022· article· en· W4293105015 on OpenAlexaboutno aff
Rienk Rienks, Mattijn Buwalda, Jeroen J.J. Bucx, Emile Dubois, Thijs T. Wingelaar, Rob van Hulst

Bibliographic record

VenueUndersea and Hyperbaric Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and Diving-Related Complications
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineScuba divingDiseaseRisk assessmentHarmCase fatality rateMedical emergencyEmergency medicineEnvironmental healthPopulationPsychologyInternal medicineComputer security

Abstract

fetched live from OpenAlex

Similar to aviation, diving is performed in an environment in which acute incapacitation may lead to a fatal outcome. In aeromedicine, a pilot is considered "unfit to fly" when the cardiovascular event risk exceeds one percent per annum, the so-called 1% rule. In diving no formal limits to cardiovascular risk have been established. Cardiovascular risk of divers can be calculated using the modified Canadian Cardiovascular Society (CCS) Risk of Harm formula: risk of harm (RH: cardiovascular fatality rate per year during diving: number × 10-⁵/divers/year) = time diving (TD: number of dives × 10-⁴) × sudden cardiac incapacitation (SCI: cardiovascular diver event rate per year (number × 10-⁵/year). The SCI and thus the RH are strongly dependent on age. Using the CCS criterion for RH, 5 × 10-⁵ divers/year, and considering an average of 25 dives per year per diver, the calculated maximum acceptable SCI is 2%/year, consistent with current practice for dive medical examinations. If the SCI were to exceed 2%/year, a diver could be considered "unfit to dive," which could particularly benefit older (≥ 50 years) divers, in whom cardiovascular risk factors are often not properly treated. For the prevention of fatal diving accidents due to atherosclerotic cardiovascular disease, a dive medical examination is of limited value for young (≺ 50 years) divers who have no cardiovascular risk factors. Introducing a cardiovascular risk management system for divers may achieve a reduction in fatal diving accidents that result from cardiovascular disease in older divers engaged in both recreational and professional diving.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.346
Threshold uncertainty score0.702

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.267
Teacher spread0.236 · 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 teacher head, 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

Citations2
Published2022
Admission routes1
Has abstractyes

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