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Record W2517531532 · doi:10.1111/hdi.12474

Air contamination during hemodialysis should be minimized

2016· review· en· W2517531532 on OpenAlexvenueno aff
Bernd Stegmayr

Bibliographic record

VenueHemodialysis International · 2016
Typereview
Languageen
FieldHealth Professions
TopicCentral Venous Catheters and Hemodialysis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHemodialysisAir embolismExtracorporealArterial lineThrombosisLungSurgeryRadiologyIntensive care medicineInternal medicineComplication

Abstract

fetched live from OpenAlex

During preparation of the hemodialysis (HD) extracorporeal circuit (ECC) a priming solution is used to remove air from the tubes and dialyzer. Ultra sound techniques have verified micro embolic signals (MES) in the ECC that may derive from clots or gas embolies. In vitro studies could clarify that embolies of air develop within the ECC and also pass the safety systems such as air traps and enter the venous line that goes into the patient. Clinical studies have confirmed the presence of MES within the ECC that pass into the return-venous-line during conventional HD without inducing an alarm. In addition, studies confirmed that such MES were present within the AV fistula and subclavian vein, but also detected within the carotid artery. Autopsy studies revealed the presence of gas embolies surrounded by clots within the lung but also brain and myocardial tissue. This review will focus on how the MES develop and measures of how the exposure can be limited.

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)0.003
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.098
GPT teacher head0.412
Teacher spread0.314 · 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

Citations28
Published2016
Admission routes1
Has abstractyes

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