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Record W2793419442 · doi:10.1097/id.0000000000000743

Retrospective Study of 1087 Anodized Implants Placed in Private Practice

2018· article· en· W2793419442 on OpenAlexafffund
David French, Hannu Larjava, Marco Tallarico

Bibliographic record

VenueImplant Dentistry · 2018
Typearticle
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsMedicineImplantDentistrySoft tissueBleeding on probingRetrospective cohort studySurvival rateRadiographyPrivate practiceUnivariate analysisMultivariate analysisSurgeryInternal medicinePeriodontitis

Abstract

fetched live from OpenAlex

INTRODUCTION: To evaluate risk indicators associated with implant failure and relationship between bone levels and soft-tissue health of anodized implants placed in private practice. MATERIAL AND METHODS: Partially or completely edentulous patients who received an anodized implant between 2003 and 2013 were included. Univariate and multivariate analysis was used to identify the relationship between study variables and implant failure. Mean marginal bone level changes (MBLΔ) were assessed using periapical radiographs. Periimplant soft tissue was evaluated using a modified bleeding index (implant mucosal index, IMI). RESULTS: A total of 1087 implants placed in 414 patients were followed for 3.9 ± 2.7 years. The cumulative implant survival rate after 10 years of function was 97.0%. Shorter (P = 0.0068) and maxillary implants (P = 0.0314) were associated with lower implant survival rate. Mean MBL decreased from -0.16 ± 0.43 mm at baseline to -0.53 ± 0.53 mm 8 to 10 years later. Implants with healthier mucosa were associated with less bone loss. CONCLUSIONS: Implants with an anodized surface showed a high long-term survival rate in a daily practice. Longer implants and implants placed in the mandible were associated with greater survival. Immediate loading and tapered design did not affect implant survival. Profuse multipoint bleeding and suppuration on recall were associated with greater bone loss.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.028
GPT teacher head0.359
Teacher spread0.332 · 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

Citations9
Published2018
Admission routes2
Has abstractyes

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