Порівняльна оцінка ефективності НПЗП у лікуванні пацієнтів з болем у спині залежно від стану мінеральної щільності кісткової тканини
Bibliographic record
Abstract
Objective: To compare the effectiveness of using of nonsteroidal anti-inflammatory drugs (NSAIDs) for reducing the severity of back pain in older patients depending on the bone mineral density (BMD).Methods: The study involved 45 postmenopausal female patients aged 46–75 years divided into groups: I (main) — with osteopenia / osteoporosis, II (comparison) — with normal BMD. The presence and intensity of pain were evaluated by means of 4-component visual analogous scale (VAS) and McGill questionnaire. BMD was measured by dual energy X-ray absorptiometry. Comparative assessment between the groups was carried out using the criterion of efficiency. Influence of therapy on treatment outcome was evaluated in terms of the size of the effect (effect size, ES).Results: After 14 days of treatment patients in both groups showed decreasing in the severity of back pain. Against the background of complex treatment with using of celecoxib in women in group I reliable dynamics determined according to all indeces of McGill questionnaire and VAS, in patients of group II revealed no reliable changes in the indices of descriptors and grades. Severity of pain at the time of the survey decresed in the I group on 54.7 %, in the II — on 61.5 %. According to calculation of criteria on efficiency reduction in the severity of pain in patients in group I marked on the index ranks which reliably more decreased in the group of women who took celecoxib compared to the group of diklofenac. Patients of group II according to VAS reliably higher criteria of effectiveness using celecoxib compared with diclofenac were determined.Conclusion: In treatment of patients with back pain and reduced BMD celecoxib with its efficacy prevails a little bit over diclofenac but the drug of choice for patients in this category can be any NSAID. In patients with normal BMD celecoxib proved more effective compared to diclofenac. To choose an anesthetic drug for the treatment of this group it is necessary depending on clinical situation and expected effect.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".