Pulmonary Embolism Masquerading as Acute Abdominal Pain: A Rare and Challenging Diagnosis
Bibliographic record
Abstract
Pulmonary embolism (PE) is a potentially fatal condition with variable clinical presentations, ranging from classic respiratory symptoms to rare atypical manifestations. This report describes a 47-year-old woman who presented with acute, severe right upper quadrant abdominal pain, nausea, and vomiting without respiratory complaints. Initial investigations, including abdominal ultrasound and contrast-enhanced CT of the abdomen, revealed no intra-abdominal abnormalities. Elevated D-dimer levels and incidental findings on imaging prompted further evaluation with CT pulmonary angiography, which confirmed bilateral pulmonary emboli. The patient had a history of obesity but no other identifiable thrombotic risk factors. Anticoagulation with low-molecular-weight heparin followed by rivaroxaban led to rapid symptom resolution. Comprehensive thrombophilia screening was negative, and follow-up imaging confirmed the resolution of the emboli. This case highlights the diagnostic challenges posed by PE presenting as isolated abdominal pain, an uncommon but clinically significant phenomenon. A systematic diagnostic approach, including consideration of PE in patients with unexplained abdominal symptoms and elevated D-dimer levels, is critical to avoiding delays in diagnosis and treatment. Early recognition and prompt anticoagulation therapy are essential for preventing potentially fatal outcomes and ensuring optimal patient care.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".