Prospective surveillance of complications in a pediatric neurosurgery unit
Bibliographic record
Abstract
OBJECT: Complications of specific pediatric neurosurgical procedures are well recognized. However, focused surveillance on a specific neurosurgical unit, for all procedures, may lead to better understanding of the most important complications, and allow targeted strategies for quality improvement. METHODS: The authors prospectively recorded the morbidity and mortality events at a large pediatric neurosurgical unit over a 2-year period. Morbidity was defined as any significant adverse outcome or death (for obstructive shunt failure, within 30 days). Multiple and unrelated complications in the same patient were recorded as separate events. RESULTS: There were 1082 surgical procedures performed during the evaluation period. One hundred seventy-seven complications (16.4%) occurred in 147 patients. By procedure, the most common complications occurred in vascular surgery (41.7%) and brain tumor surgery (27.9%). The most common complications were CSF leakage (31 cases), a new neurological deficit (27 cases), early shunt or endoscopic third ventriculostomy obstruction (27 cases), and shunt infection (24 cases). Meningitis occurred in 19 cases: in 58% of shunt infections, 13% of CSF leaks, and 10% of wound infections. Sixty-four percent of adverse events required a second procedure, most commonly an external ventricular drain placement or shunt revision. CONCLUSIONS: Complications in pediatric neurosurgical procedures are common, result in significant morbidity, and more than half the time require a repeat surgical procedure. Targeted strategies to prevent common complications, such as shunt infections or CSF leaks, might significantly reduce this burden.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".