Deterioro cognitivo sin demencia en la insuficiencia renal crónica terminal. Datos de un centro argentino
Bibliographic record
Abstract
Objectives: To assess cognitive performance in a hemodialysis population. To know relationship between IRCT and the presence of cognitive impairment, as well as the influence of hemodialysis treatment. Identify other variables that could influence cognitive performance. Methods: quasi-experimental study design, cross section. 25 adult subjects with ESRD on hemodialysis were included. Control group consisted of 4 healthy subjects. Medical histories, information on dialysis and laboratory tests were recorded. Individual interviews were conducted using the Neuropsi test being performed by a single operator. Results: 36% of patients had alterations in attention and executive functions and 24% had impaired memory. Patients with abnormal results in attention and executive functions had older and proportion of women although not statistically significant, plus higher percentage of hypertension, ischemic heart disease and smoking. This group had lower levels of hematocrit (32.11 ± 4.96 vs 35.69 ± 1.40, p = 0.01) and hemoglobin (10.67 ± 1.55 vs 11.98 ± 0.51, P = <0.01) and a tendency to total cholesterol and lower triglycerides. Patients with abnormal results in memory had a greater number of episodes of hypotension (5.83 ± 2.64 vs 2.63 ± 3.29; p = 0.04), a higher proportion of patients with hypertension (66.7% vs 26.3%; p = 0.07) and more levels low hemoglobin (10.72 ± 1.75 vs 11.76 ± 0.84, P = 0.05); without significant differences in levels of calcium and phosphorus metabolism, PTH, albumin, glucose or lipids. Conclusions: HD patients are a high-risk population and higher prevalence of cognitive disorders. Both comorbid causes associated with chronic vascular disease and inflammation disorders and malnutrition are factors that are associated with worse outcomes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".