Comorbid disorders and risk factors for neiropathic pain in distal diabetic polyneuropathy
Bibliographic record
Abstract
Diabetic polyneuropathy (DPN) is the most common complication of diabetes mellitus (DM). In 50% of cases, DPN is accompanied by neuropathic pain. Recently, the influence of comorbid disorders, which often determine the course of DPN, has been actively studied. Objective. To analyze comorbid disorders and risk factors for the development of pain syndrome in patients with DPN. Material and methods. In 40 patients with a painful form of DPN, the severity of symptoms of polyneuropathy was assessed using the Neuropathy Total Symptom Score-9 (NTSS-9), the Neuropathy Impairment Score in the Lower Limbs (NIS-LL), the Toronto Clinical Neuropathy Score (TCNS). The assessment of the intensity of the pain syndrome was carried out using a visual analog scale (VAS). For a comprehensive assessment of the emotional status of patients, the Beck’s Depression Inventory, the State-Trait Anxiety Inventory, the Insomnia Severity Index (ISI), the Pittsburgh Sleep Quality Index (PSQI), the International Physical Activity Questionnaire Short Form (IPAQ-SF), and the 12-item Short Form Survey for quality of life were used. Results. The relationship between the intensity of pain and the level of depression (r=0.785, p<0.001), as well as the degree of anxiety disorders (r=0.753, p<0.001) was revealed, which indicates the catastrophization of pain syndrome in patients with reduced mental health. The increase in scores on the NTSS-9 scale corresponded to low scores on the Montreal Cognitive Assessment (MoCA) (r=0.489, p=0.04) and the Münsterberg’s test (r= –0.476, p=0.04), which indicates the participation of cognitive disorders in the formation of a subjective assessment of pain syndrome. The relationship between the degree of insomnia and polyneuropathic syndrome on the NIS-LL and PSQI scales (r=0.641, p<0.001) was one of the most significant, indicating an important effect of sleep disorders on the pain symptoms of DPN. The relationship between the severity of the pain syndrome and the duration of DM was not found. Conclusion. The influence of emotional disorders, cognitive disorders, insomnia on the severity of pain syndrome in diabetic polyneuropathy was revealed. Diagnosis and effective treatment of comorbid disorders can be effective for reducing pain in diabetic polyneuropathy.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".