44 Spotting the clotting: a 3-year national surveillance study of paediatric pulmonary thromboembolism
Bibliographic record
Abstract
Abstract Background Pulmonary thromboembolism (PE) is a rare event in the paediatric population but can be acutely life-threatening and result in chronic complications. Awareness of contemporary patterns of clinical presentation, diagnostic modalities, and management may aid clinicians in ensuring that patients are promptly identified and treated. Objectives To describe the risk factors, symptoms, diagnostic modalities, therapeutic interventions, and short-term outcomes in paediatric patients (neonate up to 18 years) with PE through national surveillance. Design/Methods Between January 2020 and December 2022, monthly surveillance was conducted with over 2,800 paediatricians and sub-specialists through the Canadian Paediatric Surveillance Program. Voluntary reporting of cases meeting a standardized definition of PE was followed up with a detailed questionnaire. Results 58 confirmed cases were reported; 33 (57%) were females age 15 to 18 years. Detailed information was available for 31 (53%) of 58 cases. At least 1 risk factor was identified in 28 (90%) cases and 12 (39%) patients had 2 or more risk factors. The most common risk factors were oral contraceptive use (n=10 of 31; 32%) and obesity (n=9 of 31; 29%). Presentation was symptomatic in 28 (90%) cases; 24 (77%) patients presented with 2 or more symptoms. The most common symptoms were chest pain (n=18; 58%), dyspnea (n=13; 42%) and tachycardia (n=13; 42%). The most common diagnostic modality utilized was computed tomography pulmonary angiography (n=25; 81%). Initiation of systemic anticoagulation was reported for 24 (77%) of 31 cases; thrombolysis and surgical interventions were uncommon (< 5 cases). Treatment complications were common (n=8; 29%). Mortality was reported, but in fewer than 5 cases. Conclusion PE in children often presents with non-specific symptoms, but usually occurs in patients with known risk factors. Clinicians should maintain a high index of suspicion in symptomatic patients, particularly those with risk factors and in cases when other diagnoses that may explain symptoms have been excluded. Anticoagulation is the mainstay of treatment; complications can occur. Prompt recognition and management presumably reduce morbidity and mortality, but this cannot be inferred from our data.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".