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Record W2328542436 · doi:10.1097/brs.0b013e31822a58c1

Intraoperative Waste in Spine Surgery

2011· article· en· W2328542436 on OpenAlexaff
Alex Soroceanu, Elena G. Canacari, ERIC T. BROWN, Adam Robinson, Kevin J. McGuire

Bibliographic record

VenueSpine · 2011
Typearticle
Languageen
FieldMedicine
TopicHealthcare and Environmental Waste Management
Canadian institutionsDalhousie UniversityQueen Elizabeth II Health Sciences Centre
Fundersnot available
KeywordsMedicineSPINE (molecular biology)SurgeryRachisBioinformatics

Abstract

fetched live from OpenAlex

STUDY DESIGN: Prospective observational study. OBJECTIVE: This study aims to quantify the incidence of intraoperative waste in spine surgery and to examine the efficacy of an educational program directed at surgeons to induce a reduction in the intraoperative waste. SUMMARY OF BACKGROUND DATA: Spine procedures are associated with high costs. Implants are a main contributor of these costs. Intraoperative waste further exacerbates the high cost of surgery. METHODS: Data were collected during a 25-month period from one academic medical center (15-month observational period, 10-month post-awareness program). The total number of spine procedures and the incidence of intraoperative waste were recorded prospectively. Other variables recorded included the type of product wasted, cost associated with the product or implant wasted, and reason for the waste. RESULTS: Intraoperative waste occurred in 20.2% of the procedures prior to the educational program and in 10.3% of the procedures after the implementation of the program (P < 0.0001). Monthly costs associated with surgical waste were, on average, $17680 prior to the awareness intervention and $5876 afterwards (P = 0.0006). Prior to the intervention, surgical waste represented 4.3% of total operative spine budget. After the awareness program this proportion decrease to an average of 1.2% (P = 0.003). CONCLUSION: Intraoperative waste in spine surgery exacerbates the already costly procedures. Extrapolation of this data to the national level leads to an annual estimate of $126,722,000 attributable to intraoperative spine waste. A simple educational program proved to be and continues to be effective in making surgeons aware of the import of their choices and the costs related to surgical waste.

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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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)0.0020.000

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 head0.062
GPT teacher head0.280
Teacher spread0.218 · 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 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

Citations35
Published2011
Admission routes1
Has abstractyes

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