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Record W7120735379

Association des sérotypes de Streptococcus mutans avec la survenue et la gravité des caries dentaires : une revue systématique

2024· dissertation· pt· W7120735379 on OpenAlexaboutno aff
Deborah Penteado Martins [UNESP] Dias

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2024
Typedissertation
Languagept
FieldDentistry
TopicOral microbiology and periodontitis research
Canadian institutionsnot available
Fundersnot available
KeywordsObservational studySerotypeStreptococcus mutansCohortCohort studyOral healthRandomized controlled trial
DOInot available

Abstract

fetched live from OpenAlex

One of the main microorganisms related to dental caries, Streptococcus mutans, has four known serotypes (c, e, f and k). However, knowledge about the distribution of different S. mutans serotypes, including their association with dental caries, remains scarce. The objective of this study was to carry out a systematic review in order to answer the following question: “Are serotypes e, f and k of S. mutans more associated with the occurrence and severity of dental caries when compared to serotype c of S. mutans?” This review was reported in accordance with PRISMA recommendations and its protocol was registered on the PROSPERO platform (CRD42021251 176). The bibliographic search was carried out in the PubMed, Embase, Scopus and W eb of Science databases, without restrictions on year of publication or language. Observational studies (cross-sectional, case-control and cohort) are included. Randomized and non-randomized clinical trials selected for eligibility only baseline data were extracted for the present study . Reviews, letters, books, conference summaries, opinion articles, case reports, case series, animal studies and in vitro studies were excluded from the selection of studies.Study selection, data extraction and risk of bias assessment were carried out independently by two reviewers, and, in case of discrepancies, a third reviewer was consulted. For assessing risk of bias, Joanna Briggs Institute tool, for cross-sectional studies, and Newcastle-Ottawa tool, for cohort studies, were used. Of the 4778 studies retrieved from the databases, 13 studies (1 1 cross-sectional and two cohorts) were included. The studies included were conducted in ten countries, involving between 10 and 499 individuals aged between 5 months and 78 years. The Polymerase Chain Reaction was the most used identification method for identifying serotypes. The samples evaluated were collected from dental plaque, saliva, softened material taken from cavitated carious lesions and softened dentin from decayed teeth. All articles identified serotype c as the most frequently detected, with a range of 45.7% to 98%. Serotypes e, f and k showed a lower occurrence. Serotype c was the most commonly detected among individuals in the groups with dental caries. In individuals from the caries-free groups, the serotypes identified were c, e and f. Regarding the severity of dental caries, six studies associated serotype c with higher DMFT rates, two associated serotype e with a greater risk of caries, five studies did not find a relationship between serotype and caries severity and one did not verify this relationship. As for serotypes f and k, no study found a statistical association with the severity of dental caries. Five cross-sectional studies presented a moderate risk of bias, and six were assessed as having a low risk of bias. The two cohort studies were adequate in the dimensions assessed. It was concluded that serotype c had a higher occurrence than serotypes e, f and k. Most studies associated serotype c with a greater severity of dental caries. Serotypes e, f and k are not more associated with a greater occurrence and severity of dental caries when compared to serotype c of S. mutans.

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)0.050
metaresearch head score (Gemma)0.121
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.050
Threshold uncertainty score0.265

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0500.121
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0120.009
Bibliometrics0.0220.023
Science and technology studies0.0010.004
Scholarly communication0.0100.009
Open science0.0040.004
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.021
GPT teacher head0.297
Teacher spread0.276 · 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 designSystematic review
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

Citations0
Published2024
Admission routes1
Has abstractyes

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