Rare but Not so Rare? The Evolving Spectrum of Whipple′s Disease
Bibliographic record
Abstract
Knowledge about Whipple′s disease began to emerge in 1907, when George Hoyt Whipple recognized the first case of the disease that now bears his name. He reported the case of a 36‐year‐old physician with "a gradual loss of weight and strength, stools consisting chiefly of neutral fat and fatty acids, indefinite abdominal signs, and a peculiar multiple arthritis" (1). Findings at autopsy consisted of poly‐serositis, aortic valve vegetations and deposition of fat in the intestinal mucosa and regional lymph nodes with marked infiltration by foamy macrophages (1). It was originally thought to be a disorder of fat metabolism, and the term ′intestinal lipodystrophy′ was proposed. Whipple′s disease has since been recognized as a rare, multivisceral, chronic disease with a clinical presentation dominated by a symptom triad of diarrhea, weight loss and malabsorption. However, digestive symptoms are often preceded for months or years by other symptoms, the most common being arthralgia, although cardiovascular, neurological or pulmonary involvement may be more prominent at times. Once considered the ideal case report, recent characterization of Tropheryma whippelii by means of broad range bacterial ribosomal DNA polymerase chain reaction (PCR) analysis (2,3) and its subsequent cultivation (4) has led to a veritable explosion of individual case reports, case series and hitherto unrecognized manifestations of the disease, such that it is now considered an underdiagnosed infectious disease (5). It is timely to provide an update on new developments in Whipple′s disease.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".