A collaborative interdisciplinary approach for trigger finger management
Bibliographic record
Abstract
BACKGROUND: Stenosing tenosynovitis, or trigger finger, is a common cause of hand disability. This study outlines a trigger finger management protocol that redirects referrals for surgical consultations to conservative management first. PURPOSE: The primary outcome variable was the protocol endpoint based on the resolution of trigger finger symptoms (i.e. pain and triggering). Secondary outcome measures were to identify which patient characteristics were associated with an increased need for (i) surgical management and (ii) corticosteroid injections. STUDY DESIGN: Retrospective chart review. METHODS: The study sample included all patients referred for surgical consultation for trigger finger who were redirected to physical therapy first between the dates of August 2018 and January 2023 (n = 72). Participants initially received a physical therapy assessment and three treatment sessions. Further management was determined based on patient presentation following our protocol. Descriptive analysis involved frequency calculations of studied variables. Comparison of patient characteristics and treatment modalities across different sub-groups was examined as well as associations between various patient characteristics and increased need for (i) surgical management and (ii) corticosteroid injection. RESULTS: Seventy-two patients were included in the study, and 60 patients completed the protocol. Of these patients, 22% (n = 16) resolved with physical therapy (PT) alone, 48.5% (n = 35) resolved with 1-2 corticosteroid injections following initial PT management and 12.5% (n = 9) were referred back for surgical consult. Sub-group comparisons revealed no significant differences in patient characteristics and treatment modalities across patients who resolved with physical therapy alone, physical therapy plus 1-2 injections, or in cases referred back for surgical consults. CONCLUSION: The interdisciplinary care protocol in this study demonstrated that conservative management was successful in a majority of cases; facilitating timely access to evidence-based care, including corticosteroid injections and surgical management if necessary. Physical therapy treatment provides self-management and education strategies to those requiring further interventions, potentially reducing recurrence rates.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".