MétaCan
Menu
Back to cohort
Record W2160274449 · doi:10.1517/14712598.2015.977249

The effect of parathyroid hormone and teriparatide on fracture healing

2014· review· en· W2160274449 on OpenAlexaff
Eric J. Campbell, Graeme M. Campbell, David A. Hanley

Bibliographic record

VenueExpert Opinion on Biological Therapy · 2014
Typereview
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsTeriparatideParathyroid hormoneBone healingMedicineInternal medicineOsteoporosisEndocrinologyBioinformaticsBiologySurgeryCalcium

Abstract

fetched live from OpenAlex

INTRODUCTION: Daily subcutaneous injections of parathyroid hormone (PTH), and its synthetic peptide fragment, teriparatide (PTH 1-34, TPTD), have a net anabolic effect on bone and prevent osteoporotic fractures. TPTD is currently approved for this indication worldwide. Because of the anabolic effect, there is an interest in a role for TPTD (and, where available, human PTH 1-84) in improving bone healing after a fracture. PTH has been studied in animal fracture healing models and in a limited number of human trials. We have reviewed current literature regarding possible mechanisms and efficacy for PTH and TPTD to improve the healing process in the setting of various types of fractures. AREAS COVERED: Our review focuses first on the role of PTH in normal bone. We then discuss mechanisms of normal bone healing as well as delayed and impaired fracture healing. We summarize pertinent animal data and then review human studies utilizing PTH or TPTD for fracture healing. In particular, we examine unique situations including osteoporotic fractures, diabetes, stress fractures, delayed or poor healing and combination with bisphosphonate therapy. EXPERT OPINION: Available data indicate there is likely an important role for TPTD and PTH in promoting fracture healing in selected patients, but more clinical trial data are needed.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score0.674

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.092
GPT teacher head0.434
Teacher spread0.342 · 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 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

Citations49
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueExpert Opinion on Biological TherapySame topicBone health and treatmentsFrench-language works237,207