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6442 Frenulectomy as management for tongue-tie in breastfeeding problems: a rapid review

2024· review· en· W4401130657 on OpenAlexaff
Heidi Lawson, Laith Evans, Felicity Knights, Komal Chadha, Pippa Oakeshott

Bibliographic record

Venuenot available
Typereview
Languageen
FieldHealth Professions
TopicOral and Craniofacial Lesions
Canadian institutionsPopulation Health Research Institute
Fundersnot available
KeywordsBreastfeedingTongueMedicinePediatricsBreast feedingFirst languageFamily medicinePathology

Abstract

fetched live from OpenAlex

Objectives Tongue-tie (ankyloglossia) is a common condition affecting up to 60 000 babies each year in the UK, and is characterised by a short lingual frenulum that may restrict tongue tip mobility.1 275% of infants with tongue-tie are asymptomatic and do not experience feeding difficulties.2 Despite this, the rates of frenulectomy (surgical division of the lingual frenulum) in relation to breast-feeding difficulties in high-income countries have quadrupled over the past 10 years.3 Operation rates are highest in babies of first-time mothers, and mothers that are more affluent.4 Frenulectomy risks include bleeding, infection, discomfort and condition recurrence.4 There remains a lack of consensus regarding diagnosis and treatment of tongue-tie globally, and guidance is changing over time.3 5 A rapid review was conducted to establish the current evidence base for the use of frenulectomy as management for tongue-tie in babies with breastfeeding problems. Methods A structured literature search was conducted using PubMED. A grey literature search was conducted using search engines and NICE guidelines. All data published before 03/11/22 was reviewed. Inclusion and exclusion criteria were applied. No limit was set by date published or article language. Papers focusing on frenulectomy for speech difficulties were excluded. Results 9 articles were included in the rapid review, consisting of systematic reviews, narrative reviews, RCTs, prospective cohort studies, and guidelines. All articles highlighted the lack of robust evidence to support frenulectomy in the management of tongue tie in breastfeeding problems, due to small sample sizes and high risk of bias. A systematic review demonstrated a reduction in nipple pain for the mother, but no consistent positive effect on breastfeeding. A prospective RCT showed evidence of improvement in feeding in infants undergoing frenulectomy, however the sample size was very small, introducing bias. Rates of complications were low in infants undergoing frenulectomy. Conclusion There is little high-quality evidence to support frenulectomy for the management of tongue tie in breastfeeding problems. There may be some evidence to support frenulectomy in a limited number of cases. Clinicians should consider a multifactorial evaluation of other potential factors contributing to breastfeeding problems before referral for frenulectomy. Clinicians can support mothers concerned about breastfeeding problems and ankyloglossia by explaining the limited evidence for frenulectomy, and signposting to other support, including lactation experts. There is a need for further, high-quality RCTs in order to inform clinical guidelines in the management of ankyloglossia. References Rowan-Legg A. Ankyloglossia and breastfeeding. Paediatric Child Health. 2015. LeFort Y, et al. Academy of Breastfeeding Medicine position statement on ankyloglossia in breastfeeding dyads. Breastfeeding Medicine. 2021. O’Shea JE, et al. Frenotomy for tongue-tie in newborn infants. Cochrane Database Systematic Review. 2017. Van Biervliet S, et al. Primum non nocere: lingual frenotomy for breastfeeding problems, not as innocent as generally accepted. European Journal of Pediatrics. 2020. Power RF, et al. Tongue-tie and frenotomy in infants with breastfeeding difficulties: achieving a balance. Arch Dis Child. 2014.

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)0.003
metaresearch head score (Gemma)0.010
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: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0120.009
Science and technology studies0.0010.000
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0130.002

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.

Opus teacher head0.182
GPT teacher head0.500
Teacher spread0.318 · 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
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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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