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Record W4398203837 · doi:10.46743/1540-580x/2024.2400

Effect of Russian Current and Structured Exercise Program on Postpartum Diastasis Recti Abdominis: A Case Series

2024· article· en· W4398203837 on OpenAlexaboutno aff
Nagma Khan, Ashwini Bulbuli

Bibliographic record

VenueInternet Journal of Allied Health Sciences and Practice · 2024
Typearticle
Languageen
FieldMedicine
TopicPelvic and Acetabular Injuries
Canadian institutionsnot available
Fundersnot available
KeywordsSeries (stratigraphy)MedicinePhysical medicine and rehabilitationPhysical therapyOrthodonticsGeologyPaleontology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.983
Threshold uncertainty score0.327

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.419
Teacher spread0.392 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueInternet Journal of Allied Health Sciences and PracticeSame topicPelvic and Acetabular InjuriesFrench-language works237,207