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Record W4213267440 · doi:10.1177/08903344221078802

Stimulation of Lactation Using Acupuncture: A Case Study

2022· article· en· W4213267440 on OpenAlexaff
Guillermo Pierdant, Kristin Westphal, Anja Lange, Taras Usichenko

Bibliographic record

VenueJournal of Human Lactation · 2022
Typearticle
Languageen
FieldMedicine
TopicBreastfeeding Practices and Influences
Canadian institutionsMcMaster University
Fundersnot available
KeywordsLactationBreastfeedingMedicineBreast milkAcupunctureBreast feedingCaesarean sectionObstetricsMilk productionPediatricsPregnancyAnimal scienceBiologyAlternative medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Breastfeeding is a recognized preferred method of infant feeding; however, for many women, difficulties in breastfeeding result in termination before the recommended period of time. Acupuncture is suggested to be a promising option to treat lactation insufficiency and enhance the production of maternal milk. MAIN ISSUE: We have reported the case of a woman with lactation insufficiency due to Caesarean section and congenital unilateral invaginated nipple. Milk production started on the 3rd day following delivery. The newborn was not provided with any food or fluids other than mother's milk. At 5 days of life, the newborn required long feeding periods and lost 4% of his birth weight, with the participant reporting lactation insufficiency described by the perception of inadequate milk production. MANAGEMENT: Despite the implementation of conventional measures to improve lactation, the difficulties in breastfeeding persisted. Acupuncture was tried on Day 6 of life, and enhanced milk production was observed, which could be measured as the volume of residual milk extracted using the breast pump each time after the newborn achieved satiety. After acupuncture treatment there was an augmentation of maternal milk production from both breasts and successful lactation. CONCLUSION: This case study provides information that might be useful for prospective investigation of acupuncture's efficacy in women with lactation insufficiency.

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 score0.232
Threshold uncertainty score0.270

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.074
GPT teacher head0.397
Teacher spread0.323 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

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