Approaches to Microthrombotic Wounds: A Review of Pathogenesis and Clinical Features
Bibliographic record
Abstract
GENERAL PURPOSE: To discuss the pathogenesis and clinical features of wounds caused by microthrombi formation under the following categories of systemic diseases: cold-related and immune-complex deposition diseases, coagulopathies, abnormalities in red blood cell structure, emboli, and vasospasm. TARGET AUDIENCE: This continuing education activity is intended for physicians, physician assistants, nurse practitioners, and nurses with an interest in skin and wound care. LEARNING OBJECTIVES/OUTCOMES: After participating in this educational activity, the participant should be better able to:1. Recall the etiology, risk factors, and pathophysiology of the various types of microthrombotic wounds.2. Describe the clinical manifestations and treatment of the various types of microthrombotic wounds. ABSTRACT: Typical wounds such as diabetic foot ulcers, venous leg ulcers, pressure ulcers, and arterial ulcers are responsible for more than 70% of chronic wounds. Atypical wounds have broad differential diagnoses and can sometimes develop as a combination of different conditions. Regardless of the etiology, impaired blood circulation is characteristic of all chronic and acute wounds. Chronic wounds associated with microthrombi formation are an important group of atypical wounds commonly linked to an underlying systemic disease. In this perspective article, the pathogenesis and clinical features of wounds caused by microthrombi formation are discussed under the following categories of systemic diseases: cold-related and immune-complex deposition diseases, coagulopathies, abnormalities in red blood cell structure, emboli, and vasospasm.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".