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Record W1977296329 · doi:10.1111/sdi.12115

The Economics of Hemodialysis Catheter‐Related Infection Prophylaxis

2013· review· en· W1977296329 on OpenAlexaff
Sarah Daisy Kosa, Charmaine E. Lok

Bibliographic record

VenueSeminars in Dialysis · 2013
Typereview
Languageen
FieldHealth Professions
TopicCentral Venous Catheters and Hemodialysis
Canadian institutionsUniversity of TorontoMcMaster University
Fundersnot available
KeywordsMedicineHemodialysisIntensive care medicineInfection riskPsychological interventionHemodialysis CatheterCentral venous catheterVascular accessCatheterInfection controlEmergency medicineInternal medicineSurgeryNursing

Abstract

fetched live from OpenAlex

Hemodialysis central venous catheter (CVC) use is associated with the highest morbidity, mortality, and cost of all types of hemodialysis vascular access. CVC-related infection drives much of the cost associated with CVC use. The magnitude of the cost associated with CVC-related infection varies depending on the type and severity of that infection; however, estimates of the total direct and indirect costs associated with hospitalizations due to hemodialysis CVC-related infections range from 17,000 USD to 32,000 USD per episode. Thus, it is critically important, to not only have effective strategies to limit CVC-related infection but also evaluate whether these strategies are an efficient use of resources. Prophylactic strategies can be considered economically efficient only if the value of its implementation and the corresponding drop in infection rate offer greater value than standard care. The optimal CVC-related infection prophylaxis strategy should work to limit infection risk with minimal risk, inconvenience, and discomfort to the patient, and at minimal cost. The aim of this review was to examine the clinical and economic impact of some commonly described interventions used for CVC infection prophylaxis.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.042
GPT teacher head0.359
Teacher spread0.317 · 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.

Study designOther design
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

Citations39
Published2013
Admission routes1
Has abstractyes

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