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Use of Combined Magnetic Field Treatment for Fracture Nonunion

2016· article· en· W2554047660 on OpenAlexaff
Mark Phillips, Judy Baumhauer, Sheila Sprague, Jon D. Zoltan

Bibliographic record

VenueJournal of Long-Term Effects of Medical Implants · 2016
Typearticle
Languageen
FieldMedicine
TopicBone fractures and treatments
Canadian institutionsMcMaster UniversityMcMaster University Medical Centre
Fundersnot available
KeywordsMedicineNonunionBone healingSurgeryIntramedullary rod

Abstract

fetched live from OpenAlex

The use of noninvasive bone growth stimulators is a nonoperative treatment option for fracture nonunions. The purpose of this study was to evaluate the initial effectiveness of the combined magnetic field (CMF) bone growth stimulation in the treatment of fracture nonunions. Using data from a large nonunion fracture registry, we reviewed fracture-healing-outcome data and healing times for all patients treated with a CMF bone growth stimulator during a 4-yr period. Overall, 75% of the 2370 included patients achieved fracture union. Healing rates ranged from 64.0% in patients with femoral fractures to 89.7% in patients with carpal/metacarpal fractures. The weighted mean time to heal was 4.9 ± 1.0 mo. Patients treated earlier than 6 mo with CMF following injury demonstrated significantly greater healing rates and shorter mean times to heal than patients treated 6 mo or more following injury. These results indicate that CMF bone stimulation is a potentially beneficial noninvasive treatment modality for nonunions; however, high-quality comparative research is required to further evaluate the efficacy, potential prognostic factors, and contraindications for the use of this treatment modality.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.602
Threshold uncertainty score0.383

Codex and Gemma teacher scores by category

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

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 head0.022
GPT teacher head0.324
Teacher spread0.302 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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