An Examination of the Benefits of Lactation Consultant Services in NICUs for Mothers and Their Newborn: A Systematic Review
Bibliographic record
Abstract
Background: It is well accepted that lactation consultant (LC) services can enhance the breastfeeding success in mother–infant dyads. However, despite such advantages, not all neonatal intensive care units (NICUs) offer LC services. The objective of this systematic review was to assess the available evidence on the effect of LC service on breastfeeding outcomes for mothers whose infants are in the NICU. Methods: The PRISMA Extension for Systematic Reviews were used to conduct this systematic review. The following databases: Embase, Medline, CINAHL, and Cochrane library were searched. An initial 464 studies were obtained. Duplicates and studies that did not fit the inclusion criteria were removed, leaving 30 full-text articles to review. Nineteen were further excluded after full-text review. A total of 11 studies were included. Due to the heterogeneity of the included studies, a meta-analysis could not be performed, instead a qualitative numerical summary was conducted. Results: Overall, 10/11 (90%) of studies observed a 6–31% increase in the number of infants who received mother’s own milk, and 11–27% in the number of infants who received direct breastfeeds associated with the implementation of LC services in the NICU. The two most common types of LC services studied included: i) multidisciplinary lactation support—described as a team-based approach that includes at least one LC and ii) designation of LC formal role in the NICU. Conclusions: This review highlights that having LC services in the NICU is vital for meeting the unique needs and enhancing breastfeeding outcomes for mothers whose infants are in the NICU.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".