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Record W3100155045 · doi:10.1111/ctr.14155

The economic impact of increased length of stay associated with surgical site infections in liver transplantation on Canadian healthcare costs

2020· article· en· W3100155045 on OpenAlexaffabout
Yoichiro Natori, James Vu, Edwin C.Y. Chow, Micheal Guirguis, Shahid Husain, Deepali Kumar, Atul Humar, David Grant, Coleman Rotstein

Bibliographic record

VenueClinical Transplantation · 2020
Typearticle
Languageen
FieldMedicine
TopicOrgan Transplantation Techniques and Outcomes
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineInterquartile rangeLiver transplantationTransplantationHealth careDialysisEmergency medicineObservational studyRetrospective cohort studySurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Complications after liver transplantation cause additional healthcare costs. The objective of this study was to contrast the length of stay (LOS) costs for recipients with and without surgical site infections (SSIs). METHODS: This retrospective observational cohort study was conducted at a transplant center in Canada, between February 2011 and August 2014. The difference in the LOS costs was assessed by the Mann-Whitney U test, while multiple linear regression analysis was used to identify the variables that may have impacted on the costs. RESULTS: Two hundred and twenty-nine liver transplant recipients were enrolled. Thirty-six recipients developed SSIs (36/229, 15.7%). The median LOS costs in recipients with and without SSIs were $39,456 Canadian dollars (interquartile range $25,696- 59,722) and $31,084 Canadian dollars (interquartile range $22,712-49 610), respectively (p = .072). There was a trend that the costs were higher for those recipients with versus those without SSIs (p = .088). Transfusion of ≥ 5 units of red cells and dialysis before transplantation impacted on cost. CONCLUSION: There was a trend for higher healthcare facility costs for recipients with SSIs. Red cell transfusions and greater dialysis use before transplant were factors associated with the cost. Implementation of cost reduction strategies targeting high-cost recipients is necessary.

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 score0.111
Threshold uncertainty score0.957

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.038
GPT teacher head0.358
Teacher spread0.319 · 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

Citations7
Published2020
Admission routes2
Has abstractyes

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