Timely diagnostics and safe procedures in children with anterior mediastinal masses (AMMs): a qualitative review of the AMM protocol at BC Children’s Hospital in Vancouver BC
Bibliographic record
Abstract
The presence of an anterior mediastinal mass should prompt rapid triage, workup and treatment to effectively manage and prevent emergent complications. Implementation of an AMM protocol can ensure the response is standardized and coordinated. Importantly, such a protocol can encourage prompt multi-disciplinary communication to mitigate risks associated with procedures required for timely diagnosis. The aim of this review is to evaluate the BC Children’s Hospital’s Pediatric New/Suspected Anterior Mediastinal Mass (AMM) Protocol. Retrospective chart review was conducted for 18 patients admitted from February 2016 to May 2020 with AMM for whom the protocol was enacted. Primary parameters assessed presence of high-risk feature at time of presentation, time from admission and/or protocol activation to specific time points, including imaging, first diagnostic procedure, and diagnosis. Data regarding perioperative management, including anesthetic considerations and peri-operative complications, was also collected. Mean time from protocol activation to first diagnostic procedure and diagnosis were 1.88 days (range 0–7) and 2.24 days (range 0–7), respectively. The majority of procedures were conducted under sedation (n = 77, 64%), followed by general anesthetic (GA; n = 34, 28%) and local anesthetic (n = 10, 8%). Despite 15 cases having more than one high risk feature, pre-operative steroids were only administered for four of the total 158 procedures (3%) and extracorporeal life support (ECLS) and otolaryngology (ENT) were only required for immediate availability for seven procedures (4%). Furthermore, only 10 procedures (8%) had associated complications and none of these complications resulted in patient death. Our data demonstrate that implementation of a streamlined multi-disciplinary protocol can expedite time to diagnosis without impacting patient safety.
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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 | 0.016 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".