Effectiveness of healthcare educational and behavioral interventions to improve gout outcomes: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: We aimed to systematically review the effectiveness of healthcare behavioral and education interventions for gout patients on clinical outcomes. Methods: We searched multiple databases to identify trials or observational studies of educational or behavioral interventions in gout. Risk of bias was assessed with the Cochrane tool for randomized control trials (RCTs) and the Newcastle–Ottawa Scale for observational studies. We estimated odds ratios (ORs) for categorical and standardized mean difference (SMD) for continuous measures using a random-effects model. Results: Overall, eight (five RCTs and three observational) studies met the inclusion criteria and examined pharmacist-led interventions ( n = 3), nurse-led interventions ( n = 3) and primary care provider interventions ( n = 2). Compared with the control intervention (usual care in most cases), a higher proportion of those in the educational/behavioral intervention arm achieved serum urate (SU) levels <6 mg/dl, 47.2% versus 23.8%, the OR was 4.86 [95% confidence interval (CI), 1.48, 15.97; 4 RCTs] with moderate quality evidence. Compared with the control intervention, a higher proportion of those in the educational/behavioral intervention arm were adherent to allopurinol, achieved at least a 2 mg/dl decrease in SU, achieved an SU < 5 mg/dl, had a reduction in the presence of tophi at 2 years, had improved quality of life as assessed with SF-36 physical component scores, had a higher knowledge about gout and higher patient satisfaction (moderate-low quality evidence). Conclusion: Educational and behavioral interventions can improve gout outcomes in the short-intermediate term. Randomized trials are needed to assess its impact on long-term gout outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".