The impact of contemporary treatments on the perioperative care of children with mucopolysaccharidoses: A case series and review of the literature.
Bibliographic record
Abstract
Abstract Background: Patients with mucopolysaccharidosis (MPS) present significant perioperative challenges. We aimed to document the perioperative care of children with MPS undergoing anesthesia and to describe the impact of hematopoietic stem cell transplantation (HSCT) or enzyme replacement therapy (ERT) on the anesthetic management of these patients. Methods: We performed a retrospective chart review of patients with MPS anesthetised for surgical or investigative procedures at the Hospital for Sick Children in Toronto between January 2000 and December 2014. Data on MPS treatment, co-morbidities, anesthetic techniques, airway management, post-operative care and perioperative complications were collected. Results: 66 children with MPS underwent 332 anesthetics for 345 procedures. The overall rate of difficult airway was 42%. Of 29 patients with MPS I (Hurler syndrome), 66% were treated with HSCT and 34% with ERT. In those treated with HSCT, 19% had difficult airways, compared with 67% in patients who received neither treatment. 90% of patients with MPS II (Hunter syndrome) had difficult airways. ERT did not improve airway difficulty in MPS I or II patients. 32% of all anesthetics were conducted without airway instrumentation. Direct laryngoscopy, was used in 26% of all anesthetics, the laryngeal mask airway in 26%, fibreoptic bronchoscope in 7%, and video laryngoscope in 5%.Conclusions: Patients with MPS I who have had HSCT are less likely to have a difficult airway compared with those not treated with HSCT. ERT in MPS I and II patients did not alter the incidence of difficult airway. A third of MPS patients underwent anesthesia for diagnostic imaging or minor interventional radiology procedures without airway instrumentation.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".