Pediatric pulmonary thromboembolism: a 3-year Canadian Pediatric Surveillance Program study
Bibliographic record
Abstract
BACKGROUND: Pediatric pulmonary embolism (PE) is a rare event associated with significant morbidity and mortality. Awareness of clinical presentation and practices unique to children may aid clinicians in prompt identification and treatment. OBJECTIVES: To describe the incidence, risk factors, clinical presentation, diagnostic and therapeutic practices, and short-term outcomes of pediatric PE. METHODS: We conducted a 3-year national surveillance study through the Canadian Pediatric Surveillance Program. Over 2800 pediatric specialists and subspecialists were contacted monthly from 2020 to 2022 and requested to report all new cases of PE in patients up to 18 years of age. Case-specific data were obtained through voluntary completion of a detailed questionnaire. RESULTS: Fifty-eight cases (78% female, n = 45) were reported (2.4 cases per million children), with rates highest in adolescents 15 to 18 years (6.6 cases per million). Detailed information, available for 31 (53%) cases, documented at least 1 risk factor in 28 (90%) cases; 24 (77%) patients presented with 2 or more symptoms. Computed tomography pulmonary angiography was used for diagnostic confirmation in 25 (81%) cases. Anticoagulation was initiated in 24 (77%) of 31 cases; fewer than 5 patients underwent thrombolysis or surgical interventions. Of 28 patients who received therapeutic interventions, 8 (29%) experienced treatment-related complications. Fewer than 5 mortalities were reported. CONCLUSION: Pediatric PE is a rare event, with female adolescents at the highest risk. Although the presentation is often nonspecific, clinicians should maintain a high index of suspicion, particularly in patients with risk factors and when other diagnoses that may explain symptoms have been excluded.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".