Utjecaj terapijskoga vježbanja na smanjenje sakroilijakalne disfunkcije u trudnoći [The influence of exercise on reduction of sacroiliac dysfunction in pregnancy]
Bibliographic record
Abstract
Introduction: Sacroiliac dysfunction is major pain syndrome in pregnancy. It is caused by specific structure and function of the sacroiliac joints and their adjustment during pregnancy. ----- \nAim: To establish the effectiveness of exercise in pregnancy on reducing sacroiliac dysfunction. ----- \nMaterials and methods: Randomised controlled trial has been undertaken in the line of inclusion and exclusion criteria. Study group has conducted four different exercises used in order to stabilize the pelvis performed twice weekly for 20 minutes. The control group was complied with their normal lifestyle. Visual Analog Scale was used to assess the pain intensity while Quebec scale was used for assessment of the degree of disability in everyday activities. ----- \nResults: Analysis is based on 408 pregnant women included (207 in the study and 201 in control group). Statistical significance was found (p<0.001) in reduction of pain intensity with significantly reduced disability in study group (p<0.001).The results showed a strong positive correlation between decreased/increased pain intensity and degree of disability in the study/control group. ----- \nConclusion: Our results supports effectiveness of exercise used in order to stabilize the sacroiliac joints during pregnancy, pointing importance of exercise in management of SID during pregnancy.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".