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Record W4388128939 · doi:10.2196/51505

Reasons for Crown Failures in Primary Teeth: Protocol for a Systematic Review and Meta-Analysis

2023· review· en· W4388128939 on OpenAlexvenueno aff
Stephan Lampl, Deepa Gurunathan, Jogikalmat Krithikadatta, Deepak Mehta, Desigar Moodley

Bibliographic record

VenueJMIR Research Protocols · 2023
Typereview
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsnot available
Fundersnot available
KeywordsObservational studyProtocol (science)Funnel plotMedicineRandomized controlled trialMEDLINEMeta-analysisStudy heterogeneityPublication biasSystematic reviewDentistryMedical physicsAlternative medicineSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: There is a tendency nowadays to restore large defects in primary dentition with pediatric crowns instead of conventional restorations. Thus, understanding the factors contributing to the survival or failure of dental crowns in pediatric dentistry is essential for optimizing treatment outcomes. OBJECTIVE: The primary objective of this protocol is to outline the methodological approach for analyzing data from observational studies and randomized controlled trials to investigate reasons for the failure of dental crowns in primary teeth and to compute their survival and failure rates. METHODS: A comprehensive literature review will be performed in electronic databases, including PubMed (MEDLINE), Cochrane, Embase, and Web of Science. As per predefined inclusion criteria, we will include observational studies (prospective clinical studies) and randomized clinical trials that have an English abstract and involve children aged 1-10 years undergoing crown restorations. Two independent reviewers will independently screen all retrieved records and full-text articles and extract data. The study's methodological quality will be appraised using suitable tools. Assessments of publication bias will be performed using funnel plots. The findings will be described qualitatively for the systematic review. If possible, a meta-analysis will be performed to estimate failure rates by dividing the number of failures by the total exposure time. A Poisson regression model, assuming constant event rates, will be used to compute 3-year and 5-year survival proportions. The Pearson goodness-of-fit statistics will be used to assess the heterogeneity of the model. A P value <.05 will be considered significant. All analyses will be performed using R Statistical software (version 4.1.2; R Core Team). RESULTS: This systematic review and synthesis aim to assess the survival and failure rates of dental crowns in pediatric dentistry. By following this rigorous methodology, we seek to provide valuable insights into the factors contributing to the success or failure of these restorations. The results of our full review will have implications for pediatric dentists, researchers, and policy makers, helping to improve dental care for children. CONCLUSIONS: This systematic review protocol helps in establishing a thorough approach for reviewing failures in pediatric crowns. By following this methodology, standardization and transparency of the process as well as accountability for the stated methods and outcomes will be ensured. The findings of this review and analysis will provide useful data on the survival of crowns to pediatric dentists and researchers. TRIAL REGISTRATION: PROSPERO CRD42023442266; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=442266. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/51505.

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)0.077
metaresearch head score (Gemma)0.110
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.077
Threshold uncertainty score0.408

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0770.110
Meta-epidemiology (narrow)0.0070.005
Meta-epidemiology (broad)0.0210.029
Bibliometrics0.0110.009
Science and technology studies0.0030.004
Scholarly communication0.0070.007
Open science0.0050.005
Research integrity0.0080.007
Insufficient payload (model declined to judge)0.0650.006

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 head0.579
GPT teacher head0.637
Teacher spread0.058 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations6
Published2023
Admission routes1
Has abstractyes

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