An impact of affective and cognitive impairment on the quality of life in patients with lymphoproliferative diseases
Bibliographic record
Abstract
AIM: To assess the neurological and cognitive status, identify the frequency of anxiety and depression in patients with lymphoproliferative diseases, and analyze their impact on the quality of life of patients. MATERIAL AND METHODS: Fifty-eight patients, including 35 (60.34%) men and 23 (39.66%) women aged from 42 to 86 years, with a diagnosis of chronic lymphocytic leukemia (CLL) or multiple myeloma (MM) were examined. Clinical and anamnestic methods, the Montreal scale of cognitive function assessment, the Hospital Anxiety and Depression Scale (HADS), the Functional Assessment of Cancer Therapy-General (FACT-G) were administered. RESULTS: Cognitive impairment was observed in 44 (75.86%) patients. Thirty-two (56.14%) patients had no symptoms of depression, clinically diagnosed depression was observed only in 8 (14.04%). In 37 (64.91%) patients, there were no symptoms of anxiety, clinically diagnosed anxiety was revealed in 6 (10.53%). The average score on the FACT-G scale for quality of life was 62.72±23.29 with a maximum score of 108. CONCLUSION: Cognitive impairment was observed in a large number of patients. Symptoms of depression were found in less than half of the patients, and manifestations of anxiety were found in one third. The presence of affective disorders, such as anxiety and depression, reduced quality of life evaluated in all its modules.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".