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Record W1956705196 · doi:10.1111/cid.12013

Crestal Bone Loss and Oral Implants

2012· article· en· W1956705196 on OpenAlexvenueno aff
Tomas Albrektsson, D Buser, Lars Sennerby

Bibliographic record

VenueClinical Implant Dentistry and Related Research · 2012
Typearticle
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsPeri-implantitisMedicineDentistryImplantBleeding on probingImplant failurePeriodontitisSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: A consensus meeting was arranged to critically analyze whether the high figures of peri-implantitis at machined implants that recently have been reported in the literature are valid also for modern implants. PURPOSE: The aims of this paper were to present the outcomes from the consensus meeting and to evaluate recent long-term clinical studies on modern implants with regard to frequency of peri-implant infection. MATERIALS AND METHODS: Ten different studies of three modern implant brands of moderately rough surfaces with 10-year or longer follow-up times were found through a PubMed and manual search. RESULTS: It was concluded that bleeding on probing or probing depths are weak indicators of crestal bone loss (CBL); that CBL occurs for many other reasons than infection; that implant-, clinician-, and patient-related factors contribute to CBL; and that modern oral implants outperform older devices. Based on a literature search, the frequency of implants with reported peri-implant infection and significant bone loss leading to implant removal or other surgical intervention was on average 2.7% during 7 to 16 years of function. CONCLUSION: The summed frequency of peri-implantitis and implant failure is commonly less than 5% over 10 years of follow-up for modern implants when using established protocols.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.002

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 head0.171
GPT teacher head0.501
Teacher spread0.331 · 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.

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

Citations152
Published2012
Admission routes1
Has abstractyes

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