The Development of a Standardized Videofluoroscopic Swallow Study Barium Mixing Protocol: A Consensus-Based Approach
Bibliographic record
Abstract
Videofluoroscopic swallow assessments are considered the gold standard for dysphagia evaluation. Despite widespread use in clinical and research settings, standardization of barium mixing protocols is lacking. This study compared current barium mixing protocols across four Canadian acute care centres and aimed to establish standard consensus-based protocols for select target textures (i.e., thin liquid, nectar thick liquid, honey thick liquid, puree, and solid) feasible for clinical and research implementation. A representative speech-language pathologist at each site responded to an online questionnaire regarding their current barium mixing protocols. Each liquid protocol was assessed for accuracy in meeting its target using the International Dysphagia Diet Standardisation Initiative Flow Test. Early consensus was reached to use pudding and a biscuit as targets for puree and solid textures, respectively. The mixing protocols which met these criteria moved through the iterative feedback process with participating sites, identifying the protocol considered most accurate and feasible. Survey data identified use of common products across institutions, but barium mixing protocols differed. Flow Test results eliminated liquid mixing protocols that failed to align with our criteria. Acceptable liquid, puree, and solid protocols were reviewed by sites for feasibility of mixing, perceived accuracy, and visibility on imaging. Through this process, a single consensus-based barium mixing protocol was established for each target texture. Reproducibility for each final protocol was established by two sites. The iterative review process, clinician feedback, and Flow Test results successfully established barium mixing protocols for several textures which have the potential for widespread implementation.
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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 | 0.217 | 0.155 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".