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Record W2992545801 · doi:10.22462/05.06.2018.1

Incidence of otic barotrauma in Canadian Armed Forces shallow-water diver candidate students 2011-2015

2018· article· en· W2992545801 on OpenAlexaffabout
KD Brett, Waj Meintjes

Bibliographic record

VenueUndersea and Hyperbaric Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and Diving-Related Complications
Canadian institutionsCanadian Armed Forces
Fundersnot available
KeywordsIncidence (geometry)MedicineProspective cohort studyRetrospective cohort studyCohortCohort studySurgeryInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: While otic barotrauma (OBT) is a common condition experienced by divers, data related to military divers is limited. This study aimed to determine the incidence of OBT in Canadian armed forces (CAF) shallow-water diver (SWD) students trained through the Fleet Dive Unit (Atlantic) (FDU[A]) between 2011-2015. METHODS: A retrospective cohort evaluation was performed. The study group consisted of all SWD candidates who embarked on an SWD course through FDU(A) between 2011-2015. A total of 241 subjects comprised the final data analysis. RESULTS: A total of 56 individuals (23.2%) suffered 60 instances of OBT, yielding an incidence density rate of 8.68 per 1,000 person-days on course. A total of 73 diving days (10.44 per 1,000 planned person-course days, or 4.87 diving days per course) were lost due to OBT. Of the reported OBT cases, 18% resulted in cessation of training, 72% in temporary removal from diving. There was no statistically significant association between sex, history of environmental allergies, previous dive qualification, age or rank and the development of OBT. CONCLUSIONS: This study reveals that OBT is prevalent among CAF SWD candidates, with operational impact due to missed diving days. This study is limited, and further prospective study is recommended.

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 score0.082
Threshold uncertainty score0.893

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.020
GPT teacher head0.296
Teacher spread0.276 · 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

Citations4
Published2018
Admission routes2
Has abstractyes

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