Sensory profile and its impact on quality of life in patients with painful diabetic polyneuropathy
Bibliographic record
Abstract
CONTEXT: Painful diabetic polyneuropathy (PDN) is common and causes significant disability. The sensory profile in each patient is different and affects quality of life. AIM: To describe the demographic, details of sensory profile and its impact on quality of life in patients with PDN. SETTINGS AND DESIGN: A cross-sectional survey in patients with PDN who were treated in a University Hospital. MATERIALS AND METHODS: They were interviewed with standard questionnaires, which included neuropathic pain scale (NPS), a short-form McGill Pain Questionnaire (SF-MPQ) and a short form-36 quality of life survey (SF-36). STATISTICAL ANALYSIS USED: Descriptive statistics were used in demographic data. Student's t test was used to analyze continuous data. Multiple comparisons for proportions and correlations were made using Fisher Exact test and Pearson's coefficient of correlation, respectively. RESULTS: Thirty three patients were included in this study. In NPS, sharp pain was the most common symptom and itching was the least common. Almost all patients had more than one type of pain. The mean VAS was 53 mm. In SFMPQ, the sensory score, affective score and the present pain score fell in the moderate range. In SF-36, physical functioning was the most affected and social function was the least affected. CONCLUSIONS: PDN significantly affects patients' quality of life, especially physical function and role limitation due to a physical problem. Almost all patients have many types of pain and sharp pain is the most common.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".