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Record W2807961112 · doi:10.1111/vec.12728

Evaluation of pulse pressure variation and pleth variability index to predict fluid responsiveness in mechanically ventilated isoflurane‐anesthetized dogs

2018· article· en· W2807961112 on OpenAlexaff
Hiroki Sano, Joonbum Seo, Paul Wightman, Nick Cave, Mike A. Gieseg, Craig Johnson, Paul Chambers

Bibliographic record

VenueJournal of Veterinary Emergency and Critical Care · 2018
Typearticle
Languageen
FieldMedicine
TopicHemodynamic Monitoring and Therapy
Canadian institutionsHamilton Health Sciences
FundersMassey University
KeywordsMedicineIsofluraneAnesthesiaPulse pressurePulse (music)Mechanical ventilationBlood pressureInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate whether pulse pressure variation (PPV) and pleth variability index (PVI) are more accurate than central venous pressure (CVP) for predicting fluid responsiveness in mechanically ventilated isoflurane-anesthetized dogs after premedication with acepromazine. DESIGN: Prospective experimental trial. SETTING: University teaching hospital. ANIMALS: Twelve Harrier hound dogs. INTERVENTIONS: Each dog was anesthetized and had a fluid challenge performed. This was repeated 4 weeks later for a total of 24 fluid challenges. After premedication with intramuscular acepromazine, anesthesia was induced with propofol and maintained with isoflurane. The dogs were mechanically ventilated with constant settings. The fluid challenge consisted of 10 mL/kg of 6% hydroxyethyl starch intravenously over 13 minutes. MEASUREMENTS AND MAIN RESULTS: Before and after the fluid challenge, PPV, PVI, CVP, and other hemodynamics were recorded. Change in velocity time integral of pulmonary arterial blood flow by echocardiography was calculated as an indication of change in stroke volume. A fluid responder was defined as an increase in velocity time integral ≥ 15%. Receiver operator characteristic (ROC) curves were used to determine cutoff values. Areas under ROC curve were calculated and compared. Dogs responded on 14 fluid challenges and did not on 10. Cutoff values for PPV and PVI were 11% (sensitivity 79%; specificity 80%) and 9.3% (sensitivity 86%; specificity 70%), respectively. The areas under the ROC curve of PPV [0.85, 95% confidence interval (CI): 0.70-1.00, P = 0.038] and PVI (0.84, 95% CI: 0.68-1.00, P = 0.043) were significantly higher than CVP (0.56, 95% CI: 0.32-0.81). CONCLUSIONS: PPV and PVI predicted fluid responsiveness more accurately than CVP and may be useful to guide fluid administration in mechanically ventilated isoflurane-anesthetized dogs after premedication with acepromazine.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.884
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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)0.0000.000

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 head0.037
GPT teacher head0.372
Teacher spread0.335 · 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

Citations37
Published2018
Admission routes1
Has abstractyes

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