Systematic Review of Tongue Tie Publications: Exponential Rise in Publications Without Exponential Increase in Evidence
Bibliographic record
Abstract
OBJECTIVE: Ankyloglossia and lingual frenotomy in young children and infants remains an area of debate, with a body of research with poor quality-but increasing number-of studies, a trend that has continued into the present day. To systematically review the published literature to identify the number, type, and quality of studies on the evaluation, diagnosis, and treatment of ankyloglossia. DATA SOURCES: In this Preferred Reporting Items for Systematic Reviews and Meta-Analyses systematic review, a literature search of PubMed, Embase, and Ovid MEDLINE was conducted in 2024 using keywords related to ankyloglossia and frenotomy. REVIEW METHODS: Studies from 2017 to 2024 were assessed by two independent reviewers. Articles were included if they focused on ankyloglossia in children and in the English language. RESULTS: Overall, 462 articles were included for full-text extraction, of which cohort studies were the most common (179, 38.7%), and randomized controlled trials (RCTs; 13, 2.8%) were among the least common. Studies on different frenotomy techniques were common, despite no evidence suggesting that no intervention may be superior. There was an overall lack of study endpoints with objective measures such as breastfeeding duration or infant growth rates postprocedure. Despite the presence of several classification systems for ankyloglossia, none of those described in the literature focuses primarily on function as opposed to appearance or other factors. CONCLUSION: This systematic review provides an update demonstrating the continued exponential rise of publications focused on ankyloglossia and lingual frenotomy without a rise in evidence clarifying the controversies surrounding these important topics. Future studies in this area should be quality RCTs with meaningful outcome measures.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.058 | 0.235 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.010 |
| Bibliometrics | 0.036 | 0.033 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".