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Record W2977220475 · doi:10.4103/cjrm.cjrm_26_18

Use of point-of-care ultrasound for the assessment of intravascular volume in five rural New Zealand hospitals

2019· article· en· W2977220475 on OpenAlexvenueno aff
Garry Nixon, Katharina Blattner, Wendy Finnie, Ross Lawrenson, Ngaire Kerse

Bibliographic record

VenueCanadian Journal of Rural Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicHemodynamic Monitoring and Therapy
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIntravascular volume statusInferior vena cavaContext (archaeology)Nuclear medicineRadiologyBlood pressureGeography

Abstract

fetched live from OpenAlex

INTRODUCTION: Measuring the diameter of the inferior vena cava (IVC) or the height of the jugular venous pressure (JVP) with point-of-care ultrasound (POCUS) is a practical alternative method for estimating a patient's intravascular volume in the rural setting. This study aims to determine whether or not POCUS of the IVC or JVP generates additional useful clinical information over and above routine physical examination in this context. METHODS: Twenty generalist physicians, working in five New Zealand rural hospitals, recorded their estimation of a patient's intravascular volume based on physical examination and then again after performing POCUS of the IVC or JVP, using a visual scale from 1 to 11. RESULTS: Data were available for 150 assessments. There was an only moderate agreement between the pre- and post-test findings (Spearman's correlation coefficient = 0.46). In 28% (42/150) of cases, the difference was four or more points on the scale, and therefore, had the potential to be clinically significant. CONCLUSION: In the rural context, POCUS provides new information that frequently alters the clinician's estimation of a patient's intravascular volume.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.011
GPT teacher head0.275
Teacher spread0.264 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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