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Record W2885486887 · doi:10.1097/sla.0000000000003000

The Impact of Corporate Payments on Robotic Surgery Research

2018· article· en· W2885486887 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAnnals of Surgery · 2018
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineObservational studyReceiver operating characteristicMEDLINEPaymentRandomized controlled trialSubspecialtyReceiptReimbursementSurgeryFinanceFamily medicineAccountingInternal medicineHealth care

Abstract

fetched live from OpenAlex

OBJECTIVE: To quantify the influence of financial conflict of interest (COI) payments on the reporting of clinical results for robotic surgery. DATA SOURCES AND STUDY SELECTION: A systematic search (Ovid MEDLINE databases) was conducted (May 2017) to identify randomized controlled trials (RCTs) and observational studies comparing the efficacy of the da Vinci robot on clinical outcomes. Financial COI data for authors (per study) were determined using open payments database. MAIN OUTCOMES AND MEASURES: Primary outcomes assessed were receipt of financial COI payments and overall conclusion reported between robotic versus comparative approach. Quality/risk of bias was assessed using Newcastle-Ottawa Scale (NOS)/Cochrane risk of bias tool. Disclosure discrepancies were also analyzed. DATA EXTRACTION AND SYNTHESIS: Study characteristics, surgical subspecialty, methodological assessment, reporting of disclosure statements, and study findings dual abstracted. The association of the amount of financial support received as a predictor of reporting positive findings associated robotic surgery was assessed at various cut-offs of dollar amount received by receiver operating curve (ROC). RESULTS: Thirty-three studies were included, 9 RCTs and 24 observational studies. There was a median, 111 patients (range 10 to 6420) across studies. A little more than half (17/33) had a conclusion statement reporting positive results in support of robotic surgery, with 48% (16/33) reporting results not in favor [equivocal: 12/33 (36%), negative: 4/33 (12%)]. Nearly all (91%) studies had authors who received financial COI payments, with a median of $3364.46 per study (range $9 to $1,775,378.03). ROC curve demonstrated that studies receiving greater than $9557.31 (cutpoint) were more likely to report positive robotic surgery results (sensitivity: 0.65, specificity: 0.81, area under the curve: 0.73). Studies with financial COI payment greater than this amount were more likely to report beneficial outcomes with robotic surgery [(78.57% vs 31.58%, P = 0.013) with an odds ratio of 2.07 (confidence interval: 0.47-3.67; P = 0.011)]. Overall, studies were high quality/low risk of bias [median NOS: 8 (range 5 to 9)]; Cochrane risk: "low risk" (9/9, 100%)]. CONCLUSION AND RELEVANCE: Financial COI sponsorship appears to be associated with a higher likelihood of studies reporting a benefit of robotic surgery. Our findings suggest a dollar amount where financial payments influence reported clinical results, a concept that challenges the current guidelines, which do not account for the amount of COI funding received.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaResearch integrity
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptMetaresearch
Domain: Incentives · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
models splitAgreement compares identical category sets and study designs across arms.

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)0.011
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.502
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.948
GPT teacher head0.685
Teacher spread0.263 · 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