Breastfeeding After Spinal Cord Injury: A Systematic Review of Prevalence and Associated Complications
Bibliographic record
Abstract
Background: Breastfeeding can be a vital component for maternal and infant health, but successful breastfeeding may be especially difficult for mothers with spinal cord injury (SCI). No reliable research on prevalence or complications associated with breastfeeding for mothers with SCI currently exists. Methods: Our systematic review aimed to answer the following: (1) What are the breastfeeding rates in women after SCI? (2) What are the rates and nature of postpartum complications reported by women with SCI in conjunction with breastfeeding? Results: Ten studies were included; the reported rates at which women with SCI were able to breastfeed varied widely, ranging from 11% to 100%. Generally speaking, women with higher-level SCI (above T6) were less likely to breastfeed and would breastfeed less frequently than women with lower-level SCI and less frequently than women without SCI. Complications reported included problems with the let-down reflex, autonomic dysreflexia, and a higher incidence of postpartum depression in women with SCI. Conclusion: More research on mothers with SCI is needed, especially matched-control research comparing mothers with and without SCI on successful breastfeeding and associated complications.
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 | 0.006 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".