Intraoperative Regional Cerebral Oxygenation During Pediatric Thoracoscopic Surgery: A Systematic Review
Bibliographic record
Abstract
Background: Ventilating a pediatric patient during thoracoscopy is challenging. Few studies have highlighted the impact of capnothorax in children by measuring regional cerebral oxygen saturation (rcSO 2 ) with near infrared spectroscopy. In this systematic review, we aimed to summarize the data from relevant studies and assess whether thoracoscopy in children is associated with intraoperative pathological cerebral desaturation. Methods: The authors systematically searched four databases for relevant studies on the measurement of rcSO 2 during pediatric thoracoscopic procedures. The primary outcome was the proportion of patients with pathological desaturation, that is, >20% decline in the intraoperative rcSO 2 . Risk of bias among the included studies was estimated using the Newcastle–Ottawa scale. Results: The systematic search resulted in 776 articles, of which 7 studies were included in the analysis. In total, 88 patients (99 procedures) with an age ranging from 0 days to 8.1 years were included. Of these, 43 (49%) patients were neonates. The included cohort had esophageal atresia and tracheoesophageal fistula ( n = 26), long-gap esophageal atresia ( n = 5), congenital diaphragmatic hernia ( n = 14), and congenital pulmonary airway malformations and other conditions needing lung resection ( n = 43). Of the total 99 procedures, pathological desaturation was noticed in 13 (13.1%, 95% confidence interval 7.2–21.4) of them. Upon quality assessment, most of the studies were weaker in the selection and comparability domains. Conclusion: In this review, pathological cerebral desaturation was noticed in 13.1% of the pediatric thoracoscopic procedures. However, due to limited methodological quality of the included studies, further randomized multicentric studies comparing rcSO 2 in open versus thoracoscopic surgeries are needed to derive definitive conclusions.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".