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Record W3135801617 · doi:10.12968/bjon.2021.30.4.230

Central venous pressure monitoring in critical care settings

2021· article· en· W3135801617 on OpenAlexaff
Barry Hill, Catherine Smith

Bibliographic record

VenueBritish Journal of Nursing · 2021
Typearticle
Languageen
FieldMedicine
TopicHemodynamic Monitoring and Therapy
Canadian institutionsUniversity of the Fraser Valley
Fundersnot available
KeywordsCentral venous pressureMedicineCentral venous catheterResuscitationSubclavian veinIntensive care medicineSuperior vena cavaHemodynamicsCritically illCatheterInternal jugular veinCardiologyAnesthesiaSurgeryBlood pressureInternal medicine

Abstract

fetched live from OpenAlex

Patients who present with acute cardiovascular compromise require haemodynamic monitoring in a critical care unit. Central venous pressure (CVP) is the most frequently used measure to guide fluid resuscitation in critically ill patients. It is most often done via a central venous catheter (CVC) positioned in the right atrium or superior or inferior vena cava as close to the right atrium as possible. The CVC is inserted via the internal jugular vein, subclavian vein or via the femoral vein, depending on the patient and their condition. Complications of CVC placement can be serious, so its risks and benefits need to be considered. Alternative methods to CVC use include transpulmonary thermodilution and transoesophageal Doppler ultrasound. Despite its widespread use, CVP has been challenged in many studies, which have reported it to be a poor predictor of haemodynamic responsiveness. However, it is argued that CVP monitoring provides important physiologic information for the evaluation of haemodynamic instability. Nurses have central roles during catheter insertion and in CVP monitoring, as well as in managing these patients and assessing risks.

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)0.010
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: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.026
GPT teacher head0.351
Teacher spread0.326 · 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

Citations17
Published2021
Admission routes1
Has abstractyes

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Same venueBritish Journal of NursingSame topicHemodynamic Monitoring and TherapyFrench-language works237,207