Dermatologic manifestations in end stage renal disease
Bibliographic record
Abstract
Skin manifestations are commonly seen in end stage renal disease (ESRD). Skin involvement in this population can be extensive and dramatically worsen quality of life. Close observation of the skin and nails of ESRD patients by clinicians allows for timely diagnosis and treatment, which ultimately improves quality of life and reduces mortality. In this article we focus on the cutaneous changes most commonly seen in ESRD patients. PubMed/Medline database search was done for published literature on skin manifestations in ESRD patients. All the available literature was reviewed and relevant articles were used to discuss about clinical features, pathogenesis, histology and treatment of each skin disorder in ESRD patients. Most commonly encountered skin manifestations in patients with ESRD are pruritus, xerosis, pigmentation changes, nail changes, perforating disorders, calcifying disorders, bullous dermatoses and nephrogenic systemic fibrosis. Skin manifestations in ESRD can be difficult to treat and multiple comorbidities in this patient population can exacerbate these disorders. Many of the treatment options are experimental with evidence largely derived from the case reports and small clinical trials. More large-scale trials are needed to firmly establish evidence based treatment guidelines. Prompt evaluation and management of these disorders improve morbidity and quality of life in ESRD patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".