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MOC-PS(SM) CME Article: Dupuytren???s Disease

2008· review· en· W2060354366 on OpenAlexaff
William M. Swartz, Donald H. Lalonde

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2008
Typereview
Languageen
FieldMedicine
TopicDupuytren's Contracture and Treatments
Canadian institutionsSaint John Regional HospitalDalhousie UniversityUniversity of New Brunswick
Fundersnot available
KeywordsMedicineMuscle contractureDupuytren's contractureCertificationSurgeryMilestoneContracturePhysical therapyGeneral surgeryManagement

Abstract

fetched live from OpenAlex

Learning Objectives: After reviewing this article, the participant should be able to: 1. Describe the condition of Dupuytren’s disease in its various presentations and severity. 2. Describe the pathologic anatomy involved in palmar and digital contractures. 3. Understand recent elucidation of relevant pathophysiology. 4. Be familiar with treatment options and the management of complications. Summary: Dupuytren’s contracture is one of the most frequent conditions seen by practicing hand surgeons. Inherited in an autosomal dominant pattern, the disease is characterized by a nodular thickening of the palmar fascia metacarpophalangeal and proximal interphalangeal joints. Treatment is offered to symptomatic patients with painful nodular or disabling contracture. The most prevalent surgical procedure is limited fasciectomy of the involved abnormal structures. Recurrence is common. New treatments on the horizon include the injection of clostridial collagenase, which is now in U.S. Food and Drug Administration phase III trials. The Maintenance of Certification module series is designed to help the clinician structure his or her study in specific areas appropriate to his or her clinical practice. This article is prepared to accompany practice-based assessment of preoperative assessment, anesthesia, surgical treatment plan, perioperative management, and outcomes. In this format, the clinician is invited to compare his or her methods of patient assessment and treatment, outcomes, and complications with authoritative, information-based references. This information base is then used for self-assessment and benchmarking in parts II and IV of the Maintenance of Certification process of the American Board of Plastic Surgery. This article is not intended to be an exhaustive treatise on the subject. Rather, it is designed to serve as a reference point for further in-depth study by review of the reference articles presented.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.039
GPT teacher head0.293
Teacher spread0.255 · 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; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreReview

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

Citations39
Published2008
Admission routes1
Has abstractyes

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