THE INFLUENCE OF SINGLE-NUCLEOTIDE POLYMORPHISMS OF CATECHOL-O-METHYLTRANSFERASE GENE ON THE FORMATION OF PAIN SYNDROME AND EFFECTIVENESS OF ANALGESIA IN ONCOLOGICAL PATIENTS
Bibliographic record
Abstract
The objective is to study the effect of single-nucleotide polymorphisms (SNPs) of COMT gene on the formation and characteristics of chronic pain, level of anxiety and depression, effectiveness of analgesia in oncological patients. Material and Methods. The study includes 196 patients with oncological pathology. The formation of chronic pain syndrome was estimated in all patients one year after surgery using the assessment of pain intensity by numeric rating scale, pain questionnaire of McGill, PainDetect. Basing on the patients genotyping data the genotypes and haplotypes frequency distribution on SNPs of rs4680, rs740603, rs2097603=rs2070577, rs4633 of COMT gene was estimated. The relationship between different genotypes, haplotypes and chronic pain intensity, severity of ranking index of pain for sensor and affective characteristics on McGill scale, presence of neuropathic component of pain and anxiety was studied in all patients sample. The same analysis was carried out in order to clarify difference in morphine consumption (mg/24h) and severity of adverse side effects such as drowsiness, confusion and hallucinations. Results. It is found that after one year the pain syndrome was developed in 134 patients. It was showed that there is direct relationship between chronic pain intensity, anxiety level and presence of mutant allele on polymorphisms of rs4680 in exon and rs740603 in intron of COMT gene. There was also revealed inverse relationship between morphine requirement and presence of pointed polymorphisms in comparison with the patients who have GG genotype of these markers. Conclusion. The determination of pointed SNPs may be useful for choosing the optimal tactics of analgesia in patients with chronic oncological pain syndrome.
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 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 | 0.000 |
| 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".