Effect of Russian Current and Structured Exercise Program on Postpartum Diastasis Recti Abdominis: A Case Series
Bibliographic record
Abstract
Background: Diastasis recti abdominis (DRA) is the most common complication occurring post-delivery that limits the functional well-being of the affected individuals. Management of diastasis recti can include an abdominal binder, core strengthening, taping, and various surgical procedures. There is limited evidence to support the Russian current and structured exercise intervention in managing patients with DRA. Methodology: Three patients identified with DRA underwent a multi-modal treatment regimen including a hot moist pack, Russian current, abdominal binder, transverse abdominus activation exercises, treadmill training, and stationary cycling training. Outcomes were assessed using the visual analogue scale, abdominal girth, Ranney DRA scale, Oswestry low back disability questionnaire, and McGill’s torso battery test. These measures were administered at baseline and discharge. Results: Each patient demonstrated improvements in all outcome measures. The visual analogue scale improved by a mean of 7.3 on a 0–10 point scale, DRA reduced to 1 finger and the Oswestry disability questionnaire showed no disability. Conclusion: Structured exercises and Russian current were effective in managing three patients with DRA. The inclusion of Russian current and structured exercise within this multi-modal approach may enhance the conservative management of patients with DRA.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".