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Comparison of clinical outcomes between single metal-ceramic and zirconia crowns

2024· article· en· W4393927694 on OpenAlexafffundabout
Neena L. D’Souza, Emma ML Jutlah, Rachel A. Deshpande, Eszter Somogyi‐Ganss

Bibliographic record

VenueJournal of Prosthetic Dentistry · 2024
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreUniversity of WaterlooUniversity of Toronto
FundersFaculty of Dentistry, University of TorontoUniversity of Toronto
KeywordsMedicineCubic zirconiaDentistryCrown (dentistry)Mann–Whitney U testBonferroni correctionLogistic regressionRetrospective cohort studyCeramicInternal medicineMathematicsMaterials scienceStatisticsComposite material

Abstract

fetched live from OpenAlex

STATEMENT OF PROBLEM: Evidence comparing the survival of zirconia crowns with metal-ceramic crowns is sparse. Knowledge of their survival and a comparison of their clinical outcomes would improve clinical decision making. PURPOSE: The purpose of this university-based study was to compare the survival, failures, biological and technical complications encountered with zirconia and metal-ceramic crowns restored and followed up over a similar period. MATERIAL AND METHODS: This retrospective chart review consisted of 403 patients treated at the University of Toronto, Faculty of Dentistry, predoctoral dental clinic in whom zirconia (n=209) and metal-ceramic (n=306) crowns were inserted between September 2015 and July 2016 and followed for up to 7 years. Outcome measures included failure, causes for failure, and complications associated with survival. Inferential statistical analysis included the chi-squared test, t test, Mann-Whitney test, Bonferroni-adjusted z-test, Kaplan-Meier survival test, and logistic regression to examine differences between crown types and explore crown failures (α=.05). RESULTS: The mean follow-up period was 3.00 years (median 2.58 years). Forty-one (8.0%) crowns had no follow-up, with no difference in follow-up between crown type: metal-ceramic n=23(7.5%), zirconia n=18(8.6%), χ²(1)=0.20, P=.652). Excluding those with no follow-up, the follow-up time between metal-ceramic (mean=3.07, median=2.58) and zirconia (mean=3.54, median=3.32) crowns was statistically similar (P=.052). There were 62 anterior crowns (12.0%) and 453 posterior crowns (88.0%), χ²(1)=22.40, P<.001, with no difference between groups. Overall, 44 crowns (8.5%) failed, 30 (9.8%) metal-ceramic and 14 (6.7%) zirconia, with no statistical difference in proportion of failed crowns between groups (χ²(1)=1.53, P=.216). There were 35 crowns with biological failures (6.8%), 26 (8.5%) in the metal-ceramic and 9 (4.4%) in the zirconia group, with no statistical difference between groups (χ²(1)=3.33, P=.068). Nine crowns had technical failures (1.7%), 4 (1.4%) in the metal-ceramic group and 5 (2.5%) in the zirconia group, with no statistical difference between groups (χ²(1)=0.73, P=.394). Biological (79.5%) rather than technical complications were found to be the most frequent cause of failure, goodness-of-fit χ²(1)=15.36, P<.001. Tooth fracture (50.0%) specifically was found to be the most frequent cause of failure, χ²(3)=21.27, P<.001. The total number of crowns that survived was 471 (91.5%); 276 (90.1%) were metal-ceramic and 195(93.3%) zirconia. The survival time (years) for metal-ceramic was mean=6.26, 95% CI [6.01-6.51] and for zirconia crowns mean=6.54, 95% CI [6.31-6.77]. Of the crowns that survived, 370 (78.6%) had no clinical complications, and 101 (21.4%) crowns demonstrated similar clinical complications, with no statistical differences between groups. CONCLUSIONS: Within the study follow-up time, the survival of monolithic zirconia and metal-ceramic crowns was 91.5%, with similar clinical complications between groups. Biological complications, especially tooth fracture, were a significantly more frequent complication with both types of crowns.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.100
GPT teacher head0.438
Teacher spread0.338 · 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

Citations15
Published2024
Admission routes3
Has abstractyes

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