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Record W3039214844 · doi:10.1515/jpm-2020-0143

Expert advice about therapeutic exercise during pregnancy reduces the symptoms of sacroiliac dysfunction

2020· article· en· W3039214844 on OpenAlexaboutno aff
Manuela Filipec, Ratko Matijević

Bibliographic record

VenueJournal of Perinatal Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicPregnancy-related medical research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineVisual analogue scalePhysical therapyPregnancyRandomized controlled trialLow back painInternal medicineAlternative medicine

Abstract

fetched live from OpenAlex

Objectives There are growing evidence that exercise improves sacroiliac dysfunction symptoms in pregnant women; but no data about the effect of expert advice regarding this matter. The aim of this study was to assess the effectiveness of expert advice about therapeutic exercise on sacroiliac dysfunction in pregnancy. Methods A total of 500 women with sacroiliac dysfunction diagnosed in pregnancy were randomized in study and control group. Study group has conducted expert advice on therapeutic exercise; while control group continued with their normal lifestyle. Pain intensity by Visual Analog Scale (VAS) and degree of functional disability by Quebec scale were assessed at enrolment and after 3 and 6 weeks. Results Significantly better reduction in pain intensity assessed by VAS (p=0.001) and degree of functional disability assessed by Quebec scale (p=0.001) was noted in study compared to control group. Better results for both outcome measures were obtained if intervention was implemented earlier i.e., in second (p=0.001; p=0.001) compared to third (p=0.005; p=0.001) trimester. Strong positive correlation was found between pain intensity and degree of functional disability in both groups. Conclusions Expert advice on therapeutic exercise is effective in reduction of sacroiliac dysfunction symptoms during pregnancy. Trial registration ACTRN12617000556347.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score0.854

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.317
Teacher spread0.292 · 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 designBench or experimental
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

Citations7
Published2020
Admission routes1
Has abstractyes

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