A case of ARDS Overlooked Tsutstugamushi Disease that Presented as Simple Cutaneous Lesions
Bibliographic record
Abstract
Tsutstugamushi disease is a major febrile disease that generally occurs in the fall in Korea with hemorrhagic fever with renal syndrome and leptospirosis.This disease is often accompanied by interstitial pneumonia, acute renal failure and liver failure.The causative agent, namely Orientia tsutsugamushi, is transmitted to humans through the bite of a laval trombiculid mite, which is commonly known as a chigger.A 78 year old man was admitted in October 2004 with intractable fever and a drowsy mentality.Two weeks earlier, he visited a private clinic complaining of a simple skin rash.He was treated with antihistamine and steroid, but his symptoms were aggravated and he was referred to our hospital.His physical examination and laboratory findings showed a septic shock status.The maculopapular rash had spread over his face, chest, abdomen and extremities.Eschar was observed in lower back area but it was too difficult to distinguish it from other skin rashes.His chest X-ray appeared as diffuse nodular patchy consolidations in the bilateral lung parenchyme.He was treated with a mechanical ventilator and doxycycline under th suspicion of Tsutstugamushi disease.However, he suffered multiorgan failure accompanied by acute respiratory distress syndrome, acute renal failure and acute hepatitis.He was treated in the intensive care unit for approximately 12 weeks and his general condition was recovered.
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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) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".