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Record W4410029952 · doi:10.1016/j.cjco.2025.04.072

Cost Analysis for Minimally Invasive Mitral Valve Surgery: A Single-Centre Canadian Study

2025· article· en· W4410029952 on OpenAlexaffabout
Toshiro Sembo, Ali Fatehi Hassanabad, Amy Brown, Ken Kuljit S. Parhar, Corey Adams, William Kent

Bibliographic record

VenueCJC Open · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac and Coronary Surgery Techniques
Canadian institutionsLibin Cardiovascular Institute of AlbertaUniversity of Calgary
Fundersnot available
KeywordsMedicineMitral valveInvasive surgerySurgery

Abstract

fetched live from OpenAlex

Background: Stakeholders within a publicly funded healthcare system have a duty to consider costs and economics, to utilize finite resources in the most effective manner. We aimed to quantify the postoperative costs associated with mitral valve repair (MVR) at the Foothills Medical Centre in Calgary, Canada. Methods: A retrospective review of patients who underwent MVR from January 2020 to November 2023 was performed. For patients undergoing minimally invasive mitral valve surgery (MIMVS), a postoperative rapid recovery (RR) protocol was introduced. Postoperative costs were analyzed for 3 comparator groups: MIMVS with RR (MIMVS-RR), MIMVS without RR, , and median sternotomy. Results: Care in the cardiovascular intensive care unit (CVICU) is 2.83 times more expensive than care on the cardiac surgery ward. Length of stay (LOS) in the CVICU was identified to be the primary driver of postoperative costs. The CVICU LOS and total LOS for sternotomy patients was longer than those of MIMVS patients. This difference translated to increased postoperative costs for sternotomy compared to MIMVS on a per-patient basis. The postoperative costs associated with sternotomy are 1.42 times higher than those for MIMVS-RR. When modelled with 200 patients, MIMVS-RR represents a postoperative cost-savings of $3.657 million CAD, compared to sternotomy. Conclusions: Following MVR, a minimally invasive approach demonstrates cost-savings, compared to a sternotomy. Reduced CVICU LOS was the primary driver of cost-savings for MIMVS. Further analysis and investigations are required to fully quantify the true economic benefits of MIMVS-RR at our centre.

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)0.001
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 score0.304
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
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 head0.048
GPT teacher head0.318
Teacher spread0.270 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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