Risk Factors for Unplanned Readmissions in Paediatric Neurosurgery: A Systematic Review
Bibliographic record
Abstract
Abstract Background Unplanned hospital readmission (UHR) after paediatric neurosurgery is an important indicator of surgical outcomes. As this field deals with complex cases, there is an increased likelihood of potential complications and the subsequent need for readmission. Hence, the study aims to identify factors contributing to 30-day and 90-day UHR rates in children undergoing neurosurgical procedures. Methods A systematic review (Prospero CRD 42023455779) was conducted, which included studies from Embase, Medline, CINAHL, and Global Index Medicus databases that reported unplanned readmissions within 30-/90-days of an index neurosurgical procedure. Quality and risk of bias assessment was done using the Newcastle-Ottawa scale. Data extraction and narrative synthesis were performed to identify significant factors associated with UHR. Results 2593 titles were identified following the search strategy. 52 studies were included after screening and quality appraisal. Most studies were from the United States and are retrospective cohort in nature. Majority were cranial procedures (n = 30), with common ones being shunt procedures for hydrocephalus and cranial tumour resections. Aetiology-related, procedural complexities, and age emerged as the three most common significant risk factors. Age is a significant predictor (9/52), with younger children facing higher odds compared to their older counterparts across different procedures. While early readmissions can be due to disease progression, some are linked to preventable causes. The included studies also exhibited significant heterogeneity. Variations in definitions and examined variables, as well as the inclusion of studies from both national databases and single institutions, contributed to this heterogeneity. Conclusions Overall, findings from this study contribute to a collective understanding of factors affecting unplanned readmissions in paediatric neurosurgery. Key messages • Identified risk factors can help guide creating and refining surgical protocols for post-operative monitoring and follow-up. • UHRs reflect the interplay among surgical complexity, patient characteristics such as age, and disease aetiology.
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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 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".