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Record W2294392237 · doi:10.1563/aaid-joi-d-15-00157

Use of Implant-Derived Minimally Invasive Sinus Floor Elevation: A Multicenter Clinical Observational Study With 12- to 65-Month Follow-Up

2016· article· en· W2294392237 on OpenAlexaff
Eitan Mijiritsky, Horia Mihail Barbu, Adi Lorean, Izhar Shohat, Matteo Danza, Liran Levin

Bibliographic record

VenueJournal of Oral Implantology · 2016
Typearticle
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineImplantDentistryMaxillary sinusDental implantPerforationSinus (botany)PremolarMulticenter studySurgeryMolarRandomized controlled trial

Abstract

fetched live from OpenAlex

The aim of this study is to evaluate the performance of implant-derived minimally invasive sinus floor elevation. A multicenter retrospective study was performed in 5 dental clinics. Patients requiring sinus augmentation for single implant placement were recorded and followed up. The dental implant used in this trial was a self-tapping endosseous dental implant that contains an internal channel to allow the introduction of liquids through the implant body into the maxillary sinus; those liquids include saline and a flowable bone grafting material. Overall, 37 implants were installed in 37 patients. The age range of the patients was 37-75 years (mean: 51.2 years). The average residual bone height prior to the procedure was 5.24 ± 1 mm. Of all cases, 25 implants replaced the maxillary first molar and 12 replaced the maxillary second premolar. All surgeries were uneventful with no apparent perforation of the sinus membrane. The mean follow-up time was 24.81 ± 13 months ranging from 12 to 65 months. All implants integrated and showed stable marginal bone level. No adverse events were recorded during the follow-up period. The presented method for transcrestal sinus floor elevation procedure can be accomplished using a specially designed dental implant. Further long-term studies are warranted to reaffirm the results of this study.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.715

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.195
GPT teacher head0.394
Teacher spread0.199 · 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 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

Citations4
Published2016
Admission routes1
Has abstractyes

Explore more

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