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Record W4293747356 · doi:10.1111/cid.13130

Mechanical properties and marginal fit of prefabricated versus customized dental implant abutments: A comparative study

2022· article· en· W4293747356 on OpenAlexvenueno aff
Mingchen Ma, Xuejing Li, Liyan Zou, Jing He, Baohong Zhao

Bibliographic record

VenueClinical Implant Dentistry and Related Research · 2022
Typearticle
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsnot available
FundersNatural Science Foundation of Liaoning ProvinceNational Natural Science Foundation of China
KeywordsMaterials scienceAbutmentDentistryCrown (dentistry)Dental AbutmentsOrthodonticsImplantComposite materialStructural engineeringEngineeringMedicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Dental implant abutments play an important role in the health and aesthetics of soft and hard tissues around implants. PURPOSE: To compare mechanical properties and marginal fit of prefabricated and customized dental implant abutments and provide references to evaluate the relationship between abutment choice and clinical indications. METHODS: Titanium abutments were randomly divided into prefabricated and customized abutments. Static and dynamic loads were applied according to ISO14801:2016. Mechanical properties, including fracture strength, fatigue strength, rotational torque value, and torque loss rate, were measured. The biological properties of the implant abutments were assessed using an internal marginal fit. The samples were sliced, and the internal marginal fit was examined using a scanning electron microscope before and after cyclic loading. The length of the tight contact was calculated at the level of the conical connection, lower internal connection, and screw threads. Microleakage was evaluated by immersing the samples in 1% methylene blue and measuring the absorbance. RESULTS: The fracture strengths of the prefabricated abutments were greater than those of the customized abutments before and after cyclic loading. The average fatigue strengths of the prefabricated and customized abutments were 350 and 300 N, respectively. The removal torque loss of the customized abutments was significantly greater than that of the prefabricated abutments. Significant differences were found in conical connection before loading, while the screw threads showed substantial differences between the two groups after loading. Microleakage in the customized abutments was significantly higher than that in the prefabricated abutments before and after loading. CONCLUSIONS: Prefabricated abutments showed superior mechanical and biological properties compared with customized abutments in vitro, suggesting a greater risk of mechanical and biological complications occurring with the use of customized abutments. This study provides a reference for the clinical selection of implant abutments.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.318
GPT teacher head0.484
Teacher spread0.166 · 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 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

Citations11
Published2022
Admission routes1
Has abstractyes

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