Family care reduces the incidence of neonatal sepsis: A systematic review and meta-analysis
Bibliographic record
Abstract
Purpose: Family-involved care in the neonatal intensive care unit (NICU) helps to alleviate neonatal anxiety and promotes breastmilk intake, body growth and neurological development, but its effect on reducing the incidence of neonatal sepsis is not known. We conducted a systematic review and meta-analysis of randomized controlled trials (RCT) to evaluate whether neonates receiving family care have a lower incidence of neonatal sepsis compared to neonates receiving standard NICU care. Methods: MEDLINE, Embase, Web of Science, and CENTRAL were searched for RCTs that compared preterm neonates receiving family care vs. standard NICU care. From 126 articles that were identified and screened, 34 full-text articles were assessed for eligibility, and 5 RCTs were included. The primary outcome was the development of sepsis. The RevMan 5.4 software was used to conduct the Meta-analysis. Results: The metanalysis, based on 5 RCTs demonstrated that neonates receiving family-involved care had significantly lower incidence of sepsis (12.0% vs. 16.3%), increased body weight, and reduced length of hospital stay compared to those receiving standard NICU care. Conclusion: This study suggests that family-involved care in NICU can (i) reduce the incidence of neonatal sepsis, (ii) improve growth, and (iii) reduce the length of hospital stay. This study highlights the need for evaluating whether family-involved care improves other neonatal outcomes.
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 | 0.009 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.024 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".