An assessment of variation in quality of hypertension guidelines across income settings using the AGREE II tool

Hypertension affects over one billion people worldwide, posing a significant global health burden. Clinical practice guidelines could play a key role in guiding healthcare providers in improving hypertension management. However, how the quality of hypertension CPGs differs across country income settings is not well understood. This study aims to explore variation in the quality of hypertension CPGs, comparing low-, middle-, and high-income countries, using the Appraisal of Guidelines for Research and Evaluation (AGREE) II tool.

A Medline and grey literature search was conducted to identify hypertension CPGs in English from every country from January 2012 to September 2022. Two reviewers independently assessed and scored each CPG against the AGREE II tool. Results were described and the Kruskal-Wallis test was used to test for statistically significant difference in the domain scores across country income groups.

Forty-three CPGs were included for analysis from across income settings. Guidelines from HICs scored higher in four out of the six domains. The highest scoring domain was 4: "clarity and presentation" (median score 83%), the lowest scoring was domain 6 "editorial independence" (median score 0%). Statistically significant differences between income settings were observed for domain 3 "rigour of development" (p <0.001), domain 4 "clarity and presentation" (p = 0.03) and domain 6 "editorial independence" (p = 0.04).

Whilst some variation exists in guideline quality across country income levels, the greatest degree of variation exists across the domains of the AGREE II tool. Global efforts to improve the quality of hypertension guidelines should focus on the transparent statement of editorial independence of guideline committees and apply rigorous replicable methods in the authoring of guidelines. Establishing national and international communities of practice to collaborate across income settings may reduce duplication of resource, allow for shared learning and promote the development of high-quality hypertension CPGs.