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Record W3194900014 · doi:10.1111/ipd.12892

Prevalence of hypomineralised second primary molars (HSPM): A systematic review and meta‐analysis

2021· review· en· W3194900014 on OpenAlexaboutno aff
Charlotte McCarra, Isabel Cristina Olegário, Anne C. O’Connell, Rona Leith

Bibliographic record

VenueInternational Journal of Paediatric Dentistry · 2021
Typereview
Languageen
FieldMedicine
TopicBone and Dental Protein Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMeta-analysisScopusMolarPopulationMEDLINEDentistryEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

AIM: To evaluate the prevalence of HSPM worldwide on a child and a tooth level and investigate the influence of diagnostic criteria on the prevalence of HSPM. DESIGN: A comprehensive literature search was performed through MEDLINE/PubMed, Scopus, and Web of Science databases. The grey literature was also screened as were the reference lists of included studies. An adaptation of the Newcastle-Ottawa Scale was used to evaluate the quality of the studies. A meta-analysis was performed to determine the pooled prevalence of HSPM. RESULTS: The search strategy identified 1,988 articles, 487 were retrieved for full-text evaluation, and 37 studies were included in the meta-analysis (32 for child and 23 for tooth level prevalence), providing data from 26,805 individuals and 81,107 molars. The prevalence of HSPM was 6.8% (95% CI 4.98%-8.86%) on a child level and 4.08% on a tooth level (95% CI = 2.80%-5.59%). The diagnostic criteria used did not seem to influence the prevalence results (P > .05). The majority of the papers (75%) showed a low-to-moderate risk of bias. CONCLUSION: There was a broad variation in the prevalence reported that may be attributed to differences in the study population. The present meta-analysis showed a HSPM prevalence worldwide of 6.8% on a child level and 4.1% on a tooth level.

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: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.703
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0070.004
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.046
GPT teacher head0.357
Teacher spread0.311 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations38
Published2021
Admission routes1
Has abstractyes

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