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The effects of patent foramen ovale (PFO) on pulmonary gas exchange during incremental exercise

2008· article· en· W3362436 on OpenAlexaff
Andrew Thomas Lovering, Michael K. Stickland, Markus Amann, Joan C. Murphy, John S. Hokanson, Marlowe W. Eldridge

Bibliographic record

VenueThe FASEB Journal · 2008
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and Diving-Related Complications
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPatent foramen ovaleMedicineCardiologyInternal medicineShunt (medical)Right-to-left shuntIntracardiac injection

Abstract

fetched live from OpenAlex

The prevalence of a probe‐patent foramen ovale (PFO) reported in autopsy studies vary between 20 and 35%. We hypothesized that individuals with a PFO (PFO+) would have greater pulmonary gas exchange inefficiency during exercise than subjects without a PFO (PFO−) because a PFO could act as a right‐to‐left shunt. PFO+ (n=8) and PFO− (n=8) performed two incremental cycle ergometer exercise tests to max, separated by one hour, while breathing either room air or hypoxic gas ( FIO 2 =0.12). Using saline contrast echocardiography, both PFO− and PFO+ demonstrated significant intrapulmonary shunt (bubbles appearing in the left atrium (LA) after 5 heart beats) during both exercise conditions. However, at rest and during both exercise conditions in PFO+, contrast bubbles were also observed traveling through the foramen ovale as small, intermittent boluses entering directly into the LA within 3 heart beats. These findings suggest, qualitatively, a very small intracardiac shunt at rest and during exercise in PFO+. Consequently, the alveolar‐to‐arterial oxygen difference was not significantly different between PFO+ and PFO− at either peak normoxic (24.2 ± 7.8 vs. 17.5 ± 10.8 mm Hg, p= 0.18) or hypoxic (22.7 ± 2.9 vs. 20.2 ± 4.9 mm Hg, p= 0.25) exercise. We conclude that a PFO does not further exacerbate pulmonary gas exchange inefficiency occurring during exercise in healthy humans. Support: HL‐15469 & T32 HL07654; AHA 0550176Z.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.403
Threshold uncertainty score0.524

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.228
Teacher spread0.205 · 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 designBench or experimental
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

Citations1
Published2008
Admission routes1
Has abstractyes

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