MétaCan
Menu
Back to cohort
Record W2022655330 · doi:10.1111/clr.12597

A systematic review on the correlation between skeletal and jawbone mineral density in osteoporotic subjects

2015· review· en· W2022655330 on OpenAlexaboutno aff
Elena Calciolari, Nikolaos Donos, Jung‐Chul Park, Aviva Petrie, Nikos Mardas

Bibliographic record

VenueClinical Oral Implants Research · 2015
Typereview
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineConfoundingBone mineralRank correlationDual-energy X-ray absorptiometrySpearman's rank correlation coefficientMeta-analysisDentistryBone densityCorrelationOsteoporosisInternal medicineStatisticsMathematics

Abstract

fetched live from OpenAlex

OBJECTIVES: The aim of this systematic review was to assess whether the systemic skeletal reduction of bone mineral density (BMD) that characterizes osteoporotic subjects is also associated with a reduction of BMD in the jawbones. MATERIAL AND METHODS: Two reviewers searched independently and in duplicate three databases up to May 2014 and assessed the risk of bias using a tailored version of the Newcastle-Ottawa scale (NOS). Only papers reporting either Pearson's correlation coefficient or Spearman's rank correlation coefficient between skeletal and jawbone mineral density in more than five osteoporotic subjects were selected. RESULTS: From 1763 citations, 64 full-text papers were screened and five papers that met the inclusion criteria were included in the final analysis. None of the included studies complied with all NOS criteria, and as only two studies were eligible for meta-analysis, this was not performed. CONCLUSIONS: Only limited conclusions can be drawn from this systematic review, due to the small number of studies included, their heterogeneity, and their high risk of bias. Future studies that take into consideration both upper and lower jaws, that use the same technique to measure skeletal and jaw BMD (ideally dual-energy X-ray absorptiometry, DXA), and that account for confounding variables (such as medications/diseases affecting bone metabolism and demographics) are needed to provide more robust conclusions.

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)0.038
metaresearch head score (Gemma)0.026
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.177
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0380.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.007
Insufficient payload (model declined to judge)0.0000.001

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 head0.429
GPT teacher head0.567
Teacher spread0.139 · 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 designSystematic review
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

Citations23
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueClinical Oral Implants ResearchSame topicBone health and osteoporosis researchFrench-language works237,207