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Randomized Controlled Trial to Compare Two Bone Substitutes in the Treatment of Bony Dehiscences

2012· article· en· W2134353237 on OpenAlexvenueno aff
Nele Van Assche, Sofie Michels, Ignace Naert, Marc Quirynen

Bibliographic record

VenueClinical Implant Dentistry and Related Research · 2012
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDentistryImplantAbutmentRandomized controlled trialSurgery

Abstract

fetched live from OpenAlex

AIM: This in vivo split-mouth randomized controlled trial compared a synthetic bone substitute with a bovine bone mineral to cover bone dehiscences after implant insertion. MATERIALS AND METHODS: Fourteen patients received four to six implants to support an overdenture. Two comparable dehiscences within the same patient were first covered with a layer of autogenous bone, followed by a layer of either Bio-Oss® (group 1; Geistlich Pharma AG, Wolhusen, Switzerland) or Straumann BoneCeramic® (group 2; Institut Straumann AG, Basel, Switzerland) and sealed by a resorbable membrane. The change in vertical dimension of the defect was measured at implant placement and at abutment connection (6.5 months). Clinical and radiological parameters were evaluated up to 1 year of loading. RESULTS: The vertical size of the defect at surgery was 6.4 ± 1.6 mm for group 1 and 6.4 ± 2.2 mm for group 2 sites, measured from the implant shoulder. After 6.5 months, the depth of the defect was reduced to 1.5 ± 1.2 mm and 1.9 ± 1.2 mm for group 1 and group 2 sites, respectively (p > 0.05). No implants failed during follow-up. Mean marginal bone loss over the SLActive surface was 0.94 mm (group 1), 0.81 mm (group 2), and 0.93 mm (group 3, no dehiscence) after 1 year of loading. CONCLUSION: Both bone substitutes behaved equally effectively.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.003
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0120.001

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 head0.225
GPT teacher head0.535
Teacher spread0.309 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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

Citations32
Published2012
Admission routes1
Has abstractyes

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