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Record W2164037544 · doi:10.2174/1874312900802010007

Improving the Postmarket Surveillance of Total Joint Arthroplasty Devices

2008· article· en· W2164037544 on OpenAlexafffund
Nizar N. Mahomed, Khalid Syed, Clement B. Sledge, Troyen A. Brennan, Matthew H. Liang

Bibliographic record

VenueThe Open Rheumatology Journal · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsToronto Western HospitalUniversity of TorontoUniversity Health Network
FundersArthritis SocietyOrthopedic Research and Education Foundation
KeywordsMedicineJoint arthroplastyArthroplastyInternet privacySurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the FDA's approval process and postmarket surveillance strategies for THR devices. DESIGN: The FDA Center for Devices and Radiological Health (CDRH) 510k releasable database was used to document approved THR devices. The CDRH Medical Device Reporting data files were used to study the efficiency of the FDA's post-market surveillance system. Manufacturers were contacted to supply information regarding their implants. Medline was searched between 1966-1996 to determine the percentage of THR devices with published data on clinical outcomes. RESULTS: Between 1976 and 1996, 701 new THR devices were approved by the Substantial Equivalent (SE) route and 34 were approved on the basis of Premarket Approval PMA. The number of approvals doubled between 1991-1995 compared to 1976-1990. Seventy-four different manufacturers obtained approval to market THR devices. Only four manufacturers obtained approval via the PMA application. Under Mandatory Device Reporting all revision arthroplasties should be reported. Using data from 2 independent services for which we had US hospital discharge data in 1993 we estimate that only 3% of all revision THR were reported to the FDA. Manufacturers of hip implants failed to provide useful information. Medline search revealed only 15% of the approved THR devices had published data on outcomes. CONCLUSION: Current FDA premarket approval and postmarket surveillance strategies fail to provide information for evidence-based selection of THR devices. Recommendations are made to avert problems with device failures.

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)0.024
metaresearch head score (Gemma)0.003
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 score0.083
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.235
GPT teacher head0.373
Teacher spread0.138 · 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

Citations13
Published2008
Admission routes2
Has abstractyes

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