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Record W6889077338 · doi:10.25384/sage.c.6567930.v1

Long-Term Outcomes Following Manipulation Under Anaesthetic for Patients with Primary and Secondary Frozen Shoulder

2023· other· en· W6889077338 on OpenAlexaff

Bibliographic record

VenueSage Journals Data · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsDalhousie University
Fundersnot available
KeywordsRotator cuffFrozen shoulderShouldersCuffRetrospective cohort studyLocal anaesthetic

Abstract

fetched live from OpenAlex

BackgroundFrozen Shoulder (FS) is a common, debilitating condition for which manipulation under anaesthetic (MUA) is a non-invasive and effective treatment option. Current literature evaluates short to medium-term outcomes, but there is a paucity of long-term (>10 years) studies. Knowledge of long-term outcomes is also needed to evaluate whether FS or its treatment pre-disposes to other shoulder pathology in the long-term.MethodsA retrospective analysis of 398 shoulders undergoing MUA for FS between Jan 1999 and Jan 2010; 240 complete datasets were obtained. Outcomes were Oxford Shoulder Score (OSS), recurrence and development of other shoulder pathology (arthritis or rotator cuff tear).ResultsAt long-term follow-up (mean 13.2 years), 71.3% had no symptoms (OSS 48), 16.6% had minor symptoms (OSS 42–47) and 12.1% had significant symptoms (OSS < 42). There were 4/240 (1.7%) self-reported recurrences > 5 years after initial MUA and 2/240 (0.8%) repeat MUAs. In the long-term 6.7% developed rotator cuff pathology and 3.8% shoulder OA.DiscussionThis study suggests that long-term outcome after MUA for FS is favourable. Late recurrence of FS is uncommon and the development of OA or rotator cuff pathology is no greater than that of the general 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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.591
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.070
GPT teacher head0.335
Teacher spread0.265 · 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.

Study designObservational
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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Same venueSage Journals DataFrench-language works237,207