Evidence map›Paper›PMID 32188431›Full record

ArticleBMC oral health2020

Artificial intelligence in fixed implant prosthodontics: a retrospective study of 106 implant-supported monolithic zirconia crowns inserted in the posterior jaws of 90 patients.

Henriette Lerner, Jaafar Mouhyi, Oleg Admakin, Francesco Mangano

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC oral health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 2 pooled it
14.9field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

38 citing papers in PubMed, 2 syntheses or guidelines pooled it, 110 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

Henriette LernerPrivate Practice, Ludwing-Wilhelm Strasse, 17, Baden-Baden, Germany. h.lerner@web.de.
Jaafar MouhyiCasablanca Oral Rehabilitation Training & Education Center (CORTEC), Casablanca, Morocco.
Oleg AdmakinDepartment of Prevention and Communal Dentistry, Sechenov First Moscow State Medical University, 119992, Moscow, Russia.
Francesco ManganoLecturer, Department of Prevention and Communal Dentistry, Sechenov First Moscow State Medical University, Moscow, Russia.
Sechenov University · RUUniversiapolis - Université Internationale d'Agadir · MA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) is a branch of computer science concerned with building smart software or machines capable of performing tasks that typically require human intelligence. We present a protocol for the use of AI to fabricate implant-supported monolithic zirconia crowns (MZCs) cemented on customized hybrid abutments.

methodsThe study protocol consisted of: (1) intraoral scan of the implant position; (2) design of the individual abutment and temporary crown using computer-aided design (CAD) software; (3) milling of the zirconia abutment and the temporary polymethyl-methacrylate (PMMA) crown, with extraoral cementation of the zirconia abutment on the relative titanium bonding base, to generate an individual hybrid abutment; (4) clinical application of the hybrid abutment and the temporary PMMA crown; (5) intraoral scan of the hybrid abutment; (6) CAD of the final crown with automated margin line design using AI; (7) milling, sintering and characterisation of the final MZC; and (8) clinical application of the MZC. The outcome variables were mathematical (quality of the fabrication of the individual zirconia abutment) and clinical, such as (1) quality of the marginal adaptation, (2) of interproximal contact points and (3) of occlusal contacts, (4) chromatic integration, (5) survival and (6) success of MZCs. A careful statistical analysis was performed.

results90 patients (35 males, 55 females; mean age 53.3 ± 13.7 years) restored with 106 implant-supported MZCs were included in the study. The follow-up varied from 6 months to 3 years. The quality of the fabrication of individual hybrid abutments revealed a mean deviation of 44 μm (± 6.3) between the original CAD design of the zirconia abutment, and the mesh of the zirconia abutment captured intraorally at the end of the provisionalization. At the delivery of the MZCs, the marginal adaptation, quality of interproximal and occlusal contacts, and aesthetic integration were excellent. The three-year cumulative survival and success of the MZCs were 99.0% and 91.3%, respectively.

conclusionsAI seems to represent a reliable tool for the restoration of single implants with MZCs cemented on customised hybrid abutments via a full digital workflow. Further studies are needed to confirm these positive results.

Indexed as

Artificial IntelligenceComputer-Aided DesignDental Prosthesis, Implant-SupportedAdultAgedCrownsDental Implant-Abutment DesignFemaleHumansMaleMiddle AgedProsthodonticsRetrospective StudiesTitaniumZirconiumTitaniumZirconiumzirconium oxideArtificial intelligenceFull digital workflowIndividual hybrid abutmentsMarginal adaptationMonolithic zirconia crownsSuccessSurvival

Identifiers

PMID32188431
PMCPMC7081700
OpenAlexW3012795646

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.