Influência da eletroacupuntura na percepção da dor, desempenho funcional, temperatura local e mediadores inflamatórios plasmáticos de pacientes portadores de dor lombar crônica atendidos pelo SUS
Bibliographic record
Abstract
Introduction. Chronic low back pain is the most incapacitating and therapeutic challenging condition that affect the population. For the treatment of low back pain, many techniques have been employed as electroacupuncture (EA). This technique is a non-pharmacological method that combines acupuncture and electrical stimulation in acupoint and promotes the release of neurotransmitters that will act directly on pain. Objectives. Evaluate the effects of EA on the nociceptive threshold and the functional capacity of patients with chronic low back pain by unspecific origin. Methods. A quasi-experimental study was established with a weekly session of EA in a group of 20 individuals who were evaluated in three times: before the treatment (AV1), after one week (AV2) and after one month (AV3). The outcomes involved: a) Visual Analog Score of Pain (VAS); b) McGill Questionnaire; c) Roland-Morris Brazil Questionnaire (QRM-Br); d) pressure algometry; e) thermography; f) electromyography (EMG), and; g) evaluation of blood inflammatory cytokines (TNF-α and IL-6). EA sessions had a frequency of once a week, for four weeks, 2 Hz for 20 minutes in acupoints (BP6, B23, B31, B32 and B33). For statistical analysis we used repeated measures ANOVA followed by Bonferroni post-test. Results. The subjects had a reduction in mean VAS index of 7.30 in AV1 to 6.65 in AV2 and 4.35 in AV3 (F2,59 = 15.43, p <0.05); in McGill Index of 14.55 in AV1 to 13.10 in AV2 and 9.35 in AV3 (F2,59 = 5.75, p <0.05); in QRM-Br 10.15 in AV1 to 8.65 in AV2 and 5.95 in AV3 (F2,59 = 2.95, p <0.05); in algometry was found an increase in average of 5.58 and 5.29 in AV1, the right and left respectively, to 8.63 and 8.34 in the AV2 and 12.15 and 11.43 in AV3 (F5,119 = 15.97); EMG had an increase of 50% in isometric contraction in AV3, thermography and blood cytokines had no difference in all times evaluated. Conclusion. Our data show that 2Hz EA in the acupoints BP6, B23, B31, B32 and B33, reduces pain perception index (VAS and McGill), improves the functional capacity of the lumbar spine (QRM-Br), increase the threshold pressure in algometry and in isometric muscle activity (EMG) after four weeks of treatment.
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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 | 0.000 |
| 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) | 0.003 | 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".