From ‘strong recommendation’ to practice: A pre-test post-test study examining adherence to stroke guidelines for fever, hyperglycaemia, and swallowing (FeSS) management post-stroke
Bibliographic record
Abstract
Background The Quality in Acute Stroke Care (QASC) Trial demonstrated that assistance to implement protocols to manage Fever, hyperglycaemia (Sugar) and Swallowing (FeSS) post-stroke reduced death and disability. In 2017, a ‘Strong Recommendation’ for use of FeSS Protocols was included in the Australian Clinical Guidelines for Stroke Management. We aimed to: i) compare adherence to FeSS Protocols pre- and post-guideline inclusion; ii) determine if adherence varied with prior participation in a treatment arm of a FeSS Intervention study, or receiving treatment in a stroke unit; and compare findings with our previous studies. Methods Pre-test post-test study using Australian acute stroke service audit data comparing 2015/2017 (pre-guideline) versus 2019/2021 (post-guideline) adherence. Primary outcome was adherence to all six FeSS indicators (composite), with mixed-effects logistic regression adjusting for age, sex, stroke type and severity (ability to walk on admission), stroke unit care, hospital prior participation in a FeSS Intervention study, and correlation of outcomes within hospital. Additional analysis examined interaction effects. Results Overall, 112 hospitals contributed data to ≥1 one Audit cycle for both periods (pre=7011, post=7195 cases); 42 hospitals had participated in any treatment arm of a FeSS Intervention study. Adherence to FeSS Protocols post-guideline increased (pre: composite measure 35% vs post: composite measure 40 %, aOR:1.2 95 %CI: 1.2, 1.3). Prior participation in a FeSS Intervention study (aOR:1.6, 95 %CI: 1.2, 2.0) and stroke unit care (aOR 2.3, 95 %CI: 2.0, 2.5) were independently associated with greater adherence to FeSS Protocols. There was no change in adherence over time based on prior participation in a FeSS Intervention study ( p = 0.93 interaction), or stroke unit care ( p = 0.07 interaction). Conclusions There is evidence of improved adherence to FeSS Protocols following a ‘strong recommendation’ for their use in the Australian stroke guidelines. Change in adherence was similar independent of hospital prior participation in a FeSS Intervention study, or stroke unit care. However, maintenance of higher pre-guideline adherence for hospitals prior participation in a FeSS Intervention study suggests that research participation can facilitate greater guideline adherence; and confirms superior care received in stroke units. Nevertheless, less than half of Australian patients are being cared for according to the FeSS Protocols, providing impetus for additional strategies to increase uptake.
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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 | 0.012 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".