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Record W2969811476 · doi:10.1113/jp277695

Intra‐pulmonary arteriovenous anastomoses and pulmonary gas exchange: evaluation by microspheres, contrast echocardiography and inert gas elimination

2019· article· en· W2969811476 on OpenAlexafffund
Michael K. Stickland, Vincent Tedjasaputra, Cameron Seaman, Desi P. Fuhr, Sophie É. Collins, Harrieth Wagner, Sean van Diepen, Bradley W. Byers, Peter D. Wagner, Susan R. Hopkins

Bibliographic record

VenueThe Journal of Physiology · 2019
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsCovenant HealthUniversity of Alberta
FundersNational Heart, Lung, and Blood InstituteNatural Sciences and Engineering Research Council of CanadaCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsInert gasMedicineAnastomosisCardiologyMicrosphereInternal medicineChemistrySurgeryChemical engineering

Abstract

fetched live from OpenAlex

Key points Imaging techniques such as contrast echocardiography suggest that anatomical intra‐pulmonary arteriovenous anastomoses (IPAVAs) are present at rest and are recruited to a greater extent in conditions such as exercise. IPAVAs have the potential to act as a shunt, although gas exchange methods have not demonstrated significant shunt in the normal lung. To evaluate this discrepancy, we compared anatomical shunt with 25‐µm microspheres to contrast echocardiography, and gas exchange shunt measured by the multiple inert gas elimination technique (MIGET). Intra‐pulmonary shunt measured by 25‐µm microspheres was not significantly different from gas exchange shunt determined by MIGET, suggesting that MIGET does not underestimate the gas exchange consequences of anatomical shunt. A positive agitated saline contrast echocardiography score was associated with anatomical shunt measured by microspheres. Agitated saline contrast echocardiography had high sensitivity but low specificity to detect a ≥1% anatomical shunt, frequently detecting small shunts inconsequential for gas exchange. Abstract The echocardiographic visualization of transpulmonary agitated saline microbubbles suggests that anatomical intra‐pulmonary arteriovenous anastomoses are recruited during exercise, in hypoxia, and when cardiac output is increased pharmacologically. However, the multiple inert gas elimination technique (MIGET) shows insignificant right‐to‐left gas exchange shunt in normal humans and canines. To evaluate this discrepancy, we measured anatomical shunt with 25‐µm microspheres and compared the results to contrast echocardiography and MIGET‐determined gas exchange shunt in nine anaesthetized, ventilated canines. Data were acquired under the following conditions: (1) at baseline, (2) 2 µg kg−1 min−1 i.v. dopamine, (3) 10 µg kg−1 min−1 i.v. dobutamine, and (4) following creation of an intra‐atrial shunt (in four animals). Right to left anatomical shunt was quantified by the number of 25‐µm microspheres recovered in systemic arterial blood. Ventilation–perfusion mismatch and gas exchange shunt were quantified by MIGET and cardiac output by direct Fick. Left ventricular contrast scores were assessed by agitated saline bubble counts, and separately by appearance of 25‐µm microspheres. Across all conditions, anatomical shunt measured by 25‐µm microspheres was not different from gas exchange shunt measured by MIGET (microspheres: 2.3 ± 7.4%; MIGET: 2.6 ± 6.1%, P = 0.64). Saline contrast bubble score was associated with microsphere shunt (ρ = 0.60, P < 0.001). Agitated saline contrast score had high sensitivity (100%) to detect a ≥1% shunt, but low specificity (22–48%). Gas exchange shunt by MIGET does not underestimate anatomical shunt measured using 25‐µm microspheres. Contrast echocardiography is extremely sensitive, but not specific, often detecting small anatomical shunts which are inconsequential for gas exchange.

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 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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
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 head0.009
GPT teacher head0.255
Teacher spread0.246 · 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 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".

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Citations17
Published2019
Admission routes2
Has abstractyes

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