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Record W4327857440 · doi:10.1038/s41598-023-31029-5

Cost consequence analysis of waiting for lumbar disc herniation surgery

2023· article· en· W4327857440 on OpenAlexaff
Charlotte Dandurand, Mohammad Sadegh Mashayekhi, Greg McIntosh, Supriya Singh, Jérôme Paquet, Hasaan Chaudhry, Edward Abraham, Christopher S. Bailey, Michael H. Weber, Michael G. Johnson, Andrew Nataraj, Najmedden Attabib, Adrienne Kelly, Hamilton Hall, Y. Raja Rampersaud, Neil Manson, Philippe Phan, Ken Thomas, Charles G. Fisher, Raphaële Charest-Morin, Alex Soroceanu, Bernard LaRue, Nicolas Dea

Bibliographic record

VenueScientific Reports · 2023
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of CalgaryOttawa HospitalUniversity Health NetworkNOSM UniversitySault Area HospitalUniversity of AlbertaUniversity of OttawaMcGill UniversityUniversity of ManitobaMontreal General HospitalCanada East Spine CentreSpinal Cord Injury BCSunnybrook HospitalUniversité de SherbrookeWestern UniversityUniversity of TorontoUniversité LavalCanadian Respiratory Research NetworkLondon Health Sciences CentreHorizon Health NetworkUniversity of British Columbia
Fundersnot available
KeywordsMedicineObservational studyIndirect costsRetrospective cohort studyLumbarSurgeryInformed consentLumbar disc herniationEmergency departmentCohortCost analysisInternal medicine

Abstract

fetched live from OpenAlex

The economic repercussions of waiting for lumbar disc surgery have not been well studied. The primary goal of this study was to perform a cost-consequence analysis of patients receiving early vs late surgery for symptomatic disc herniation from a societal perspective. Secondarily, we compared patient factors and patient-reported outcomes. This is a retrospective analysis of prospectively collected data from the CSORN registry. A cost-consequence analysis was performed where direct and indirect costs were compared, and different outcomes were listed separately. Comparisons were made on an observational cohort of patients receiving surgery less than 60 days after consent (short wait) or 60 days or more after consent (long wait). This study included 493 patients with surgery between January 2015 and October 2021 with 272 patients (55.2%) in the short wait group and 221 patients (44.8%) classified as long wait. There was no difference in proportions of patients who returned to work at 3 and 12-months. Time from surgery to return to work was similar between both groups (34.0 vs 34.9 days, p = 0.804). Time from consent to return to work was longer in the longer wait group corresponding to an additional $11,753.10 mean indirect cost per patient. The short wait group showed increased healthcare usage at 3 months with more emergency department visits (52.6% vs 25.0%, p < 0.032), more physiotherapy (84.6% vs 72.0%, p < 0.001) and more MRI (65.2% vs 41.4%, p < 0.043). This corresponded to an additional direct cost of $518.21 per patient. Secondarily, the short wait group had higher baseline NRS leg, ODI, and lower EQ5D and PCS. The long wait group had more patients with symptoms over 2 years duration (57.6% vs 34.1%, p < 0.001). A higher proportion of patients reached MCID in terms of NRS leg pain at 3-month follow up in the short wait group (84.0% vs 75.9%, p < 0.040). This cost-consequence analysis of an observational cohort showed decreased costs associated with early surgery of $11,234.89 per patient when compared to late surgery for lumbar disc herniation. The early surgery group had more severe symptoms with higher healthcare utilization. This is counterbalanced by the additional productivity loss in the long wait group, which likely have a more chronic disease. From a societal economic perspective, early surgery seems beneficial and should be promoted.

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)0.012
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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.053
GPT teacher head0.340
Teacher spread0.287 · 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

Citations15
Published2023
Admission routes1
Has abstractyes

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