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Record W4384828509 · doi:10.3389/fphys.2023.1221829

Understanding cardiopulmonary interactions through esophageal pressure monitoring

2023· review· en· W4384828509 on OpenAlexaff
Elena Spinelli, Gaetano Scaramuzzo, Douglas Slobod, Tommaso Mauri

Bibliographic record

VenueFrontiers in Physiology · 2023
Typereview
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsMcGill University
FundersMinistero della Salute
KeywordsAfterloadMedicineVenous return curveCardiologyVentricleCentral venous pressureTranspulmonary pressureInternal medicineCardiac outputBlood pressureAnesthesiaLungHemodynamicsHeart rateLung volumes

Abstract

fetched live from OpenAlex

Esophageal pressure is the closest estimate of pleural pressure. Changes in esophageal pressure reflect changes in intrathoracic pressure and affect transpulmonary pressure, both of which have multiple effects on right and left ventricular performance. During passive breathing, increasing esophageal pressure is associated with lower venous return and higher right ventricular afterload and lower left ventricular afterload and oxygen consumption. In spontaneously breathing patients, negative pleural pressure swings increase venous return, while right heart afterload increases as in passive conditions; for the left ventricle, end-diastolic pressure is increased potentially favoring lung edema. Esophageal pressure monitoring represents a simple bedside method to estimate changes in pleural pressure and can advance our understanding of the cardiovascular performance of critically ill patients undergoing passive or assisted ventilation and guide physiologically personalized treatments.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.201
GPT teacher head0.382
Teacher spread0.181 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations15
Published2023
Admission routes1
Has abstractyes

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