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Record W2990422290

Taping protocol for two presentations of pregnancy-related back pain: a case series.

2019· article· en· W2990422290 on OpenAlexaff
Crystal Draper, Ayla Azad, Donald Littlewood, Chloe Siner Morgan, Lindsay Barker, Carol Ann Weis

Bibliographic record

VenuePubMed · 2019
Typearticle
Languageen
FieldMedicine
TopicPregnancy-related medical research
Canadian institutionsCanadian Memorial Chiropractic College
Fundersnot available
KeywordsChiropracticMedicinePregnancyPhysical therapyLow back painSpinal manipulationBack painPopulationAlternative medicine
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Back pain is common during pregnancy and can have an adverse impact on the quality of life for some, yet treatment options for this population are limited. We document a chiropractic treatment that involves using kinesiology tape (tape) to help alleviate pregnancy-related back pain in two patients. CASE PRESENTATION AND MANAGEMENT: Two pregnant women reported to two different chiropractic offices with varying presentations of pregnancy-related back pain. A trial of chiropractic care was rendered in both chiropractic offices, which included the application of tape. OUTCOME AND DISCUSSION: In both case presentations, the addition of tape in the lumbosacral and/or abdominal regions, decreased pain intensity from 9-10/10 to 4/10 or less on the Numeric Rating Scale (NRS). Including a taping protocol to a plan of management in women with pregnancy-related LBP or PGP may be a safe and effective option to alleviate pain in this population.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.065
GPT teacher head0.360
Teacher spread0.295 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations6
Published2019
Admission routes1
Has abstractyes

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