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Record W2462454643 · doi:10.3233/bmr-160734

Case series of ultrasound-guided platelet-rich plasma injections for sacroiliac joint dysfunction

2016· article· en· W2462454643 on OpenAlexaffabout
Gordon Ko, Sean Mindra, Gordon E. Lawson, Scott Whitmore, Leigh Arseneau

Bibliographic record

VenueJournal of Back and Musculoskeletal Rehabilitation · 2016
Typearticle
Languageen
FieldMedicine
TopicPeriodontal Regeneration and Treatments
Canadian institutionsCanadian Centre for Policy AlternativesUniversity of OttawaHealth Sciences CentreCanadian Memorial Chiropractic CollegeUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineSacroiliac jointPlatelet-rich plasmaJoint (building)UltrasoundSeries (stratigraphy)RadiologyPlateletInternal medicineGeologyEngineering

Abstract

fetched live from OpenAlex

BACKGROUND: Two-thirds of adults worldwide will experience low back pain at some point in their life. In the following case series, we present four patients with sacroiliac (SI) joint instability and severe chronic low back pain, which was refractory to other treatment modalities. OBJECTIVE: We investigated the efficacy of platelet-rich plasma (PRP) injections, a novel orthobiologic therapy, for reducing SI joint pain, improving quality of life, and maintaining a clinical effect. METHODS: Short-form McGill Pain Questionnaire (SFM), Numeric Rating Scale (NRS), and Oswestry Low Back Pain and Disability Index were used for evaluation of treatment at pretreatment, 12-months and 48-months after treatment. RESULTS: At follow-up 12-months post-treatment, pooled data from all patients reported a marked improvement in joint stability, a statistically significant reduction in pain, and improvement in quality of life. The clinical benefits of PRP were still significant at 4-years post-treatment. CONCLUSIONS: Platelet-rich plasma therapy exhibits clinical usefulness in both pain reduction and for functional improvement in patients with chronic SI joint pain. The improvement in joint stability and low back pain was maintained at 1- and 4-years post-treatment.

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)0.001
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 score0.634
Threshold uncertainty score0.313

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.020
GPT teacher head0.286
Teacher spread0.266 · 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

Citations52
Published2016
Admission routes2
Has abstractyes

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