Interventions to improve neurodevelopmental outcomes of children born moderate to late preterm: a systematic review protocol
Bibliographic record
Abstract
Introduction: Prematurity (birth before 37 +0 weeks’ gestation) is associated with wide-ranging neurodevelopmental impairment. Prognosis among moderate to late (32 +0 to <37 +0 weeks’ gestation) preterm infants (MLPT) is better compared to their counterparts born very preterm (<32 +0 weeks’ gestation). However the risk of developmental impairment among MLPT, who make up about 84% of all preterm infants, is 2-3 times higher when compared to infants born at term. Early interventions have aimed to improve outcomes in preterm infants generally, but there are limited data on their need and effect in MLPT specifically. Prioritising research, long-term follow-up and early interventions targeted at ameliorating the impact of preterm birth among MLPT is required. Objectives: To conduct a systematic review of the type of early childhood interventions (from birth until 4 years of age) offered to MLPT children and to evaluate their impact on neurodevelopmental outcomes (cognitive, neurobehavioural and motor) as assessed in these children during childhood (until 18 years of age). Methods and analysis: A systematic literature search in Web of Science, Medline Ovid, PsycINFO, CINAHL and EMBASE will be conducted. Data on MLPT children receiving developmental interventions until the age of 4 years will be evaluated. Interventions may involve parents or primary caregivers. Primary outcomes are cognitive, neurobehavioural and motor development as measured from birth until the age of 18 years. The Cochrane Risk of Bias Assessment Tool will be used to evaluate the methodological quality of randomised controlled trials (RCTs) included in the review and will be graded as low, high or unclear risk of bias. The quality of non-RCTs will be evaluated with the Newcastle-Ottawa Scale. The quality of evidence for each outcome will be evaluated using the Grading of Recommendations Assessment, Development and Evaluation Approach. Publication and reporting bias will be assessed using Egger’s test and funnel plots respectively.
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 | 0.026 | 0.040 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.017 | 0.015 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.056 | 0.005 |
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".