The Impact of Neonatal Sepsis on Long-Term Neurodevelopment: A Systematic Review of Cognitive and Sensory Outcomes
Bibliographic record
Abstract
This systematic review examines the long-term cognitive and sensory outcomes associated with neonatal sepsis. A comprehensive literature search was conducted in PubMed, Web of Science, Scopus, and Embase from January 2020 to July 2025, following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Studies were included if they reported neurodevelopmental outcomes among survivors of neonatal sepsis. A total of 14 eligible studies were identified and evaluated for risk of bias using the Newcastle-Ottawa Scale. Due to methodological heterogeneity, a narrative synthesis was performed. The included studies investigated a range of neurodevelopmental domains, with particular attention to cognitive, motor, and sensory outcomes. Findings varied across study populations and settings. Most studies reported a low risk of bias. This review highlights the need for standardized definitions of neonatal sepsis and outcome measures, as well as increased research focus on sensory outcomes and data from low-resource settings. Further prospective studies are recommended to enhance understanding of risk stratification and inform long-term follow-up strategies.
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 | 0.008 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".