Arteritis Mimicking Aortic Coarctation and Review of the Literature
Bibliographic record
Abstract
Arteritis is a chronic non-specific inflammation involving the aorta and its main branches, coronary and pulmonary arteries which lead to vascular stenosis or occlusion. Compared with coronary atherosclerosis, primary hypertension and other common cardiovascular disease, arteritis is relatively rare disease. The aortic isthmus arteritist is rarer. Because of a variety of clinical manifestations, there is a little difficulty in early diagnosis and treatment with little experience. An 18-year-old Chinese girl was sent to our hospital for blood pressure 180/70 mmHg in order to confirm the etiology of hypertension. One and a half years ago, she was diagnosed as “bronchiectasis” for hemoptysis and treated by using embolization intervention. Two months ago, she was again diagnosed as iron deficiency anaemia for fatigue. Physical examination discovered that right arm blood pressure was 180/70 mmHg and left arm blood pressure 165/60 mmHg, but double lower limb blood pressure was not measured. Murmur was heard easy in bilateral carotid, subclavian, the back and heart valve auscultation area. However, ultrasound showed normal vascellum in bilateral carotid, subclavian other than decrease of blood flow velocity in double lower limb arteries. The aorta computed tomography angiography scanning found that there was only about 0.45 cm wide in the aortic isthmus with thicker wall. The results of hemoglobin, globulin, C-reaction protein and erythrocyte sedimentation rate were abnormal. The aortic isthmus arteritist and secondary hypertension were clearly diagnosed and treated by using anti-inflammatory, corticosteroids, immunosuppressive agents and antihypertensive drugs until erythrocyte sedimentation rate returned to normal. Finally, artificial vascular was replaced successfully by surgery. Now the patient fells very fine and has already been working for more than two year. This case gives us the inspiration: A detailed examination to patient is very important, which avoid missed diagnosis or misdiagnosis and missed the best opportunity for treatment. As a doctor, we must have solid basic skills and do not underestimate the role of stethoscope in any time. J Med Cases. 2013;4(6):376-379 doi: https://doi.org/10.4021/jmc1251e
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".