Quality of Evidence in European Stroke Organisation and American Heart Association Stroke Guidelines
Bibliographic record
Abstract
BACKGROUND: Evidence-based practice relies on clinical guidelines, whose recommendations depend on the quality, relevance, and validity of supporting research. We evaluated the class/strength and level of evidence (LOE) or quality of evidence (QOE) supporting American Heart Association/American Stroke Association and European Stroke Organisation guideline recommendations, and examined temporal changes in LOE. METHODS: Stroke guidelines from American Heart Association/American Stroke Association (1995-2025) and European Stroke Organisation (2014-2025) were identified through society websites and EMBASE/MEDLINE. Eligible documents contained recommendations with class/strength and LOE/QOE. Consensus statements were excluded. Since 2006, American Heart Association/American Stroke Association has classified LOE as A (multiple or large randomized-controlled trials), B (single trial or observational studies), or C (expert opinion). European Stroke Organisation applies the Grading of Recommendations Assessment, Development, and Evaluation system (high, moderate, low, and very low QOE). RESULTS: Across 1102 recommendations in 9 current American Heart Association/American Stroke Association stroke guidelines, 156 (14.2%) were supported by LOE A, 559 (50.7%) by LOE B, and 387 (35.1%) by LOE C. Of 407 class I recommendations (ie, should do), and 117 class III recommendations (ie, should not do), 116 (22.1%), 258 (49.2%), and 150 (28.6%) were supported by LOE A, B, and C, respectively. Although the number of recommendations increased across guideline updates (median, 22 [interquartile range, 25th-75th percentiles, 18.0-42.0]), the proportion supported by LOE A declined (median, -4.6% [interquartile range, -7.8 to -0.8]). Across 260 recommendations in 30 European Stroke Organisation guidelines, 19 (7.3%) were supported by high, 62 (23.8%) by moderate, 81 (31.2%) by low, and 98 (37.7%) by very low QOE. Among 90 strong recommendations, 18 (20.0%) were supported by high QOE, and 66.7% of guideline topics had no recommendations supported by high QOE. There was insufficient evidence to make recommendations for 123 (32.7%) clinical questions. CONCLUSIONS: Due to limited randomized data for many important clinical questions, most stroke guideline recommendations are based on low-to-moderate-quality evidence. These findings emphasize the need to improve the funding, design, and delivery of efficient, patient-focused clinical trials.
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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 | 0.185 | 0.533 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.043 | 0.033 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".