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Record W4416654925 · doi:10.1016/j.jds.2025.11.011

Presence of a distolingual root in mandibular first molars as an indicator of association with other tooth canal anatomies: A systematic review

2025· article· en· W4416654925 on OpenAlexaboutno aff
Yu‐Chiao Wu, Ho-Sheng Chiang, Wei‐Cheng Lee, Ying-Wu Chen, Ling-Yu Kung, K T Chen, Ren‐Yeong Huang, Yi‐Shing Shieh

Bibliographic record

VenueJournal of Dental Sciences · 2025
Typearticle
Languageen
FieldDentistry
TopicEndodontics and Root Canal Treatments
Canadian institutionsnot available
FundersTri-Service General HospitalMinistry of Education
KeywordsRoot canalMolarMandibular second molarInclusion and exclusion criteriaMEDLINE

Abstract

fetched live from OpenAlex

Understanding anatomical variations in root canal morphology is crucial for achieving successful endodontic outcomes. The presence of a distolingual root (DLR) in mandibular first molars (MFMs) has been proposed as an indicator of complex root canal anatomy in other teeth. This systematic review aimed to evaluate the association between DLRs in MFMs and root canal configurations in other teeth across different ethnic populations. Following PRISMA guidelines, a comprehensive search of PubMed, MEDLINE Complete, Scopus, ClinicalKey, and relevant registries was performed up to October 10, 2025, using the keywords “distolingual root” and “radix entomolaris.” Inclusion criteria comprised in vivo CBCT-based clinical studies that reported both DLR prevalence and its association with root canal morphology of other teeth. Study quality was assessed using the Newcastle–Ottawa Scale. Twelve studies involving 8,024 participants and 51,762 teeth were included. Reported DLR prevalence ranged from 3.6 % to 41.2 %. Studies from East Asia (Taiwan, South Korea, China) consistently demonstrated positive correlations between DLRs in MFMs and complex canal anatomies in mandibular lateral and central incisors and first premolars. In contrast, data from India and Turkey showed variable or negative associations. The presence of a DLR in MFMs may serve as a reliable anatomical marker for anticipating complex canal configurations in adjacent or contralateral teeth. Ethnic differences were evident, highlighting the need for standardized CBCT-based multicenter studies to confirm these findings and improve predictive endodontic diagnosis.

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 score0.273
Threshold uncertainty score0.826

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.307
Teacher spread0.298 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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