Comparative pathophysiology and management of protein-losing enteropathy
Bibliographic record
Abstract
Protein-losing enteropathy, or PLE, is not a disease but a syndrome that develops in numerous disease states of differing etiologies and often involving the lymphatic system, such as lymphangiectasia and lymphangitis in dogs. The pathophysiology of lymphatic disease is incompletely understood, and the disease is challenging to manage. Understanding of PLE mechanisms requires knowledge of lymphatic system structure and function, which are reviewed here. The mechanisms of enteric protein loss in PLE are identical in dogs and people, irrespective of the underlying cause. In people, PLE is usually associated with primary intestinal lymphangiectasia, suspected to arise from genetic susceptibility, or "idiopathic" lymphatic vascular obstruction. In dogs, PLE is most often a feature of inflammatory bowel disease (IBD), and less frequently intestinal lymphangiectasia, although it is not proven which process is the true driving defect. In cats, PLE is relatively rare. Review of the veterinary literature (1977-2018) reveals that PLE was life-ending in 54.2% of dogs compared to published disease-associated deaths in IBD of <20%, implying that PLE is not merely a continuum of IBD spectrum pathophysiology. In people, diet is the cornerstone of management, whereas dogs are often treated with immunosuppression for causes of PLE including lymphangiectasia, lymphangitis, and crypt disease. Currently, however, there is no scientific, extrapolated, or evidence-based support for an autoimmune or immune-mediated mechanism. Moreover, people with PLE have disease-associated loss of immune function, including lymphopenia, severe CD4+ T-cell depletion, and negative vaccinal titers. Comparison of PLE in people and dogs is undertaken here, and theories in treatment of PLE are presented.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".