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Record W2002230611 · doi:10.1097/ccm.0b013e3182772ab6

The Role of Venous Return in Critical Illness and Shock—Part I

2012· article· en· W2002230611 on OpenAlexaff
Duane J. Funk, Eric Jacobsohn, Anand Kumar

Bibliographic record

VenueCritical Care Medicine · 2012
Typearticle
Languageen
FieldMedicine
TopicHemodynamic Monitoring and Therapy
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineShock (circulatory)Intensive care medicineVenous return curveDiseaseCritical illnessCardiovascular physiologyResuscitationCardiac outputCirculatory systemHemodynamicsCritically illCardiologyInternal medicineSurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: To provide a conceptual and clinical review of the physiology of the venous system as it is relates to cardiac function in health and disease. DATA: An integration of venous and cardiac physiology under normal conditions, critical illness, and resuscitation. SUMMARY: The usual teaching of cardiac physiology focuses on left ventricular function. As a result of the wide array of shock states with which intensivists contend, an approach that takes into account the function of the venous system and its interaction with the right and left heart may be more useful. This two-part review focuses on the function of the venous system and right heart under normal and stressed conditions. The first part describes the basic physiology of the venous system, and part two focuses on the role of the venous system in different pathophysiologic states, particularly shock. CONCLUSION: An improved understanding of the role of the venous system in health and disease will allow intensivists to better appreciate the complex circulatory physiology of shock and may allow for better hemodynamic management of this disorder.

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: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.347
Teacher spread0.328 · 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
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

Citations148
Published2012
Admission routes1
Has abstractyes

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