Prevalencia y evaluación de síntomas en enfermedad renal crónica avanzada
Bibliographic record
Abstract
The patient with advanced chronic kidney disease (ACKD) has a high symptom burden that contribute to increased suffering and diminish their quality of life. The use of symptom assessment tools is essential for the control of symptoms. The aim of this review is to obtain a contrasted vision of the instruments commonly used to assess symptoms in ACKD, making a description of the prevalence of symptoms in this population. Method: A review of the literature on studies in which an instrument is used to measure the intensity of several symptoms in patients with ACKD was undertaken. The search was conducted in PubMed, Cochrane, SciELO and TESEO. Inclusion criteria were: studies in patients with ACKD, evaluating symptoms with an assessment tool, and also indicate the prevalence of various symptoms. Results: The instruments identified were the Memorial Symptom Assessment Scale Short Form (MSAS-SF), the Dialysis Symptom Index (DSI), the Edmonton Symptom Assessment System (ESAS) and the Palliative Care Outcome Scale-Symptoms Kidney (POS-S RENAL). In adult patients with ACKD undergoing renal replacement therapy with hemodialysis and peritoneal dialysis, the most prevalent symptoms were fatigue, pruritus, constipation, anorexia, pain, sleep disturbance, anxiety, dyspnea, nausea, restless legs, and depression. These symptoms were similar in patients with renal conservative management, and showed a common pattern to the symptoms of others advanced diseases. We conclude that we need to research about the prevalence and evaluation of symptoms in this population, and a systematic use of specific instruments for evaluating symptoms as an outcome measure is necessary.
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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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".