3.1 Study design and framework

This study is a scoping review conducted according to the methodological framework proposed by Arksey and O’Malley [13]. We chose the scoping review method because our primary objective is to examine the existing literature on the relationship between hyperuricemia and erectile dysfunction, identify key concepts and knowledge gaps, and examine the scope and nature of research activity in this field. Scoping reviews are suitable for exploring emerging topics because the literature on these topics may vary in study design, populations, and outcomes [14]. This scoping review was conducted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines [15].

3.2 Research questions

The research questions include primary and secondary questions. The primary research question is: what evidence currently exists indicating an association between hyperuricemia and erectile dysfunction, and what are the potential mechanisms of this relationship? Secondary questions include: (1) What study designs have been used to investigate this association? (2) Which populations have been studied? (3) What are the characteristics of this association in different patient groups? (4) What biological mechanisms have been proposed?

3.3 Search strategy and data sources

We searched literature from database inception to the present, with data sources including PubMed/MEDLINE, Web of Science Core Collection, Scopus, and Google Scholar. The search strategy was reviewed by a medical librarian and integrated Medical Subject Headings (Mesh) and free-text terms. Core search concepts were: (1) Population: males (“male”, “men”, “adult”); (2) Exposure: hyperuricemia (“hyperuricemia”, “hyperuricaemia”), uric acid (“uric acid”, “serum uric acid”, “SUA”), gout (“gout”); (3) Outcome: erectile dysfunction (“erectile dysfunction”, “ED”, “impotence”), sexual dysfunction (“sexual dysfunction”, “sexual function”).

The PubMed search strategy example is as follows: (hyperuricemia [Mesh Terms] OR hyperuricemia [Title/Abstract] OR hyperuricaemia [Title/Abstract] OR “uric acid” [Mesh Terms] OR “uric acid” [Title/Abstract] OR “serum uric acid” [Title/Abstract] OR gout [Mesh Terms] OR gout [Title/Abstract]) AND (erectile dysfunction [Mesh Terms] OR “erectile dysfunction” [Title/Abstract] OR impotence [Mesh Terms] OR impotence [Title/Abstract] OR “sexual dysfunction” [Title/Abstract] OR “sexual function” [Title/Abstract]) AND (male [Mesh Terms] OR male [Title/Abstract] OR men [Title/Abstract]). The search was not limited by publication time or language, but non-English literature for which English versions could not be obtained was excluded during the full-text screening stage.

3.4 Study selection

3.4.3 Screening process

Two reviewers (reviewer initials were anonymized) independently screened titles and abstracts according to pre-established inclusion and exclusion criteria. Full texts of all potentially relevant studies were then obtained. The same two reviewers independently assessed the full texts to determine final inclusion. Disagreements were resolved through discussion; if consensus could not be reached, a third reviewer was consulted. The screening process was documented using a PRISMA flow diagram (Fig. 1).

Fig. 1.Literature selection flowchart (based on PRISMA statement).

3.5 Data extraction

Data extraction was completed independently by two reviewers, extracting the following information from each included study: (1) Study characteristics: first author, publication year, country, study design, sample size; (2) Population characteristics: age, comorbidities, study setting (clinical studies vs. population studies); (3) Hyperuricemia assessment: definitions used, measurement methods, cutoff values; (4) Erectile dysfunction assessment: assessment tools, definitions, severity classification; (5) Statistical analysis: analytical methods, confounding variable adjustment, effect measures; (6) Main conclusions: primary results on the relationship between hyperuricemia and erectile dysfunction; (7) Study quality indicators: response rates, loss to follow-up, potential sources of bias.

3.6 Quality assessment

The methodological quality of included studies was assessed using standardized tools with categorical evaluation, including two types: cohort studies/case-control studies and cross-sectional studies. Cohort studies/case-control studies used the NOS scale (Newcastle-Ottawa Scale) [16], scoring detailed criteria across three dimensions, with a total score of 9 points, ≥7 points indicating high quality, 4–6 points moderate quality, and ≤3 points low quality. Cross-sectional studies: The AXIS tool (Appraisal tool for Cross-Sectional Studies) [17, 18] was used, covering 11 dimensions of bias risk (such as sample representativeness, measurement standards, etc.).

3.7 Data synthesis and analysis

Given the heterogeneity in study design, study populations, and outcome measurements, the study employed a narrative synthesis approach rather than quantitative meta-analysis. Studies were categorized into three groups based on their main conclusions regarding the relationship: (1) studies showing a positive correlation between the two; (2) studies showing no significant correlation between the two; (3) studies showing that uric acid has a protective effect. For each category, we examined study characteristics, population characteristics, methodological approaches, and potential sources of heterogeneity. We also analyzed the biological mechanisms proposed by authors and summarized and calculated the risk coefficients for hyperuricemia leading to ED.

4.1 Study selection and characteristics

The initial database search yielded a total of 122 articles (PubMed = 82 articles; Web of Science = 24 articles; Google Scholar = 10 articles; Scopus = 6 articles). After excluding duplicate articles (n = 18), 104 articles underwent title and abstract screening. Of these, 31 articles were selected for full-text review. After full-text evaluation, 15 articles were excluded for the following reasons: review articles (n = 6), insufficient data on the relationship between hyperuricemia and erectile dysfunction (n = 4), animal studies (n = 2), case reports (n = 2), and pediatric population (n = 1). Finally, 16 studies met the inclusion criteria and were included in this scoping review.

4.2 Study characteristics and quality assessment

The 16 included studies involved a total of 295,705 participants and were published between 2014 and 2024, indicating growing research interest in this field. Twelve studies (n = 13, 75%) used cross-sectional design, and 4 studies used cohort design. Specifically, cross-sectional studies using the AXIS tool scored between 7–9 points (moderate-high), while cohort studies using the NOS scale all achieved full scores of 9 points (high quality). Methodological rigor was high (81% scored AXIS ≥8 points or NOS = 9 points) (as shown in Table 1, Ref. [19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34]).

4.3 Population characteristics

The studies primarily focused on middle-aged and elderly Asian males, with a large total sample size but extremely uneven distribution, showing a “bimodal distribution”—4 ultra-large cohort studies (totaling 295,705 people) coexisting with 12 small-to-medium cross-sectional studies (median sample of 200 people); 62.5% focused on specific disease populations (cardiovascular/metabolic disease patients), with only 37.5% covering general populations; geographic distribution was significantly skewed toward Asia (62.5%), with relatively weak evidence from Europe and America; although covering the 20–83 age range, the core focus was on the 45–70 age group. High-quality evidence mainly came from national cohorts (NOS = 9 points), while more than half of the cross-sectional studies had hospital-centric bias (single-center studies accounting for 25%).

4.4 Definitions of hyperuricemia and erectile dysfunction

The definition of hyperuricemia was highly heterogeneous across the 16 studies: only 1 US study (6.3%) used the international standard (>7.0 mg/dL), while the remaining 93.7% used non-standardized definitions, including relative grouping methods (18.8%, such as grouping by quartiles/median, with generally low cutoff points), disease proxy methods (18.8%, indirectly defined by gout diagnosis or medication treatment), and undefined definitions (56.3%, only reporting values without thresholds). Future studies are recommended to uniformly use the >7.0 mg/dL standard and supplement with sensitivity analyses to improve conclusion reliability. Unlike the high heterogeneity in hyperuricemia definitions, ED assessment methods have been largely standardized internationally, mainly evaluated through the International Index of Erectile Function-5 (IIEF-5) questionnaire, with the cutoff score for diagnosing ED typically set at ≤21 [18].

4.5 Relationship between hyperuricemia and erectile dysfunction

5.1 Main findings

This scoping review included 16 studies (295,705 participants) and systematically evaluated the association between hyperuricemia and erectile dysfunction. Results showed that 93.8% of studies (15/16) supported a positive correlation between the two, with one study reporting a protective association and no studies reporting null associations after proper adjustment, but only 31.3% of studies (5/16) confirmed an independent association. Exploratory pooled analysis of high-quality cohort studies indicated that gout patients had a 16% increased risk of developing ED (HR = 1.160, 95% CI 1.104–1.219, p < 0.001), with no heterogeneity (I² = 0.0%). This exploratory estimate should be interpreted with high caution given the limited number of studies and heterogeneity in populations and definitions.

5.2 Evidence quality of association strength

Cohort studies provided the most reliable evidence support. Chen et al.’s [19] large cohort study based on Taiwan’s National Health Insurance Database (19,368 gout patients vs. 77,472 controls) showed that gout patients had a 21% increased risk of ED (HR = 1.21, 95% CI 1.03–1.44). Similarly, a UK cohort study based on national electronic medical records confirmed this association (HR = 1.15) [29]. These large-sample, long-term follow-up cohort studies overcame the temporal limitations of cross-sectional designs and provided stronger evidence support for causal inference.

However, the independence of the association remains controversial. Two high-quality studies found no independent association after fully adjusting for cardiovascular risk factors: a Finnish community study (OR = 1.14, 95% CI 0.59–2.19, p = 0.7) [22] and a US study based on NHANES data (OR = 1.02, 95% CI 0.84–1.24, p = 0.5) [23]. This suggests that the association between hyperuricemia and ED may be partially mediated by coexisting metabolic-cardiovascular risk factors.

5.3 Comprehensive model of pathophysiological mechanisms

Based on the biological pathways summarized from included studies (Figs. 2,3,4), we synthesize previous mechanistic links into an integrated conceptual triad that HUA may lead to ED through the “oxidative stress-inflammation-metabolism” triad axis:

Fig. 2.Mechanism by which hyperuricemia inhibits nitric oxide synthesis through oxidative stress and inflammatory response, leading to erectile dysfunction.

Fig. 3.Mechanism of hyperuricemia damaging vascular endothelial function through inflammatory pathways and oxidative stress.

Fig. 4.Molecular pathways by which hyperuricemia mediates insulin resistance and vascular endothelial dysfunction.

Evidence supporting the triad mechanism is organized by evidence level: (1) In vitro studies demonstrate uric acid crystal activation of inflammatory pathways; (2) Animal models show HUA-induced endothelial dysfunction; (3) Clinical observations include Salavati et al. [26] in coronary heart disease patients, Ticoalu et al. [21] in hypertensive cohorts, and Kim et al. [27] in insulin resistance/gut microbiome studies; (4) Limited intervention data from uric acid-lowering therapy studies. Each element of the triad is supported by oxidative stress (ROS (reactive oxygen species) generation, NADPH (Nicotinamide Adenine Dinucleotide Phosphate, reduced form) oxidase activation), inflammation (NF-κB (Nuclear Factor kappa-B) pathway, cytokine release), and metabolism (insulin resistance, endothelial dysfunction).

5.4 Explanation of contradictory results

Gao et al.’s [24] study based on the Chinese general population reached the opposite conclusion, suggesting that serum uric acid has a protective effect on ED (OR = 0.998) [23]. This contradiction may reflect the biphasic biological effects of uric acid: at physiological concentrations, uric acid serves as an important antioxidant, accounting for approximately 60% of plasma antioxidant capacity; however, when pathologically elevated, it becomes a pro-oxidant and pro-inflammatory factor [41]. Additionally, this study was based on the general population rather than clinical patients, which may involve population selection differences. Differences in genetic background, dietary patterns, and environmental factors may also affect uric acid metabolism and vascular reactivity.

5.5 Impact of methodological heterogeneity

The high heterogeneity in hyperuricemia definitions is an important finding of this review. Only 6.3% of studies used the international standard definition (>7.0 mg/dL), while 93.7% used non-standardized definitions, including relative grouping methods (18.8%), disease proxy methods (18.8%), and undefined definitions (56.3%). This inconsistency in definitions may lead to systematic bias in association strength, affecting the comparability and clinical translational value of results.

The limitations of study design should not be overlooked. Cross-sectional studies accounted for 75%, which cannot establish temporal relationships or causal inference. The uneven geographic distribution (62.5% from Asia) limits the global applicability of results. Furthermore, 62.5% of studies focused on specific disease populations, which may overestimate association strength.

5.6 Clinical significance

Based on existing evidence, the association between hyperuricemia and ED has important clinical significance, particularly in patients with comorbid cardiovascular metabolic diseases. However, the evidence is insufficient to support routine uric acid screening for all ED patients or uric acid-lowering therapy as first-line treatment for ED. Further research is needed before routine clinical application can be supported [42]. Clinical management should adopt a comprehensive cardiovascular risk assessment strategy, as hyperuricemia and ED may jointly reflect underlying endothelial dysfunction and metabolic disorders.

For patients with both hyperuricemia and ED, focus should be placed on modifiable cardiovascular risk factors, including management of hypertension, diabetes, dyslipidemia, and lifestyle factors. The benefits of uric acid-lowering therapy need to be further validated through prospective intervention studies.

5.7 Study limitations

This review has several important limitations. First, the heterogeneity in study design and populations excluded the possibility of quantitative meta-analysis, limiting precise estimation of effect sizes. Second, cross-sectional studies dominated, making it impossible to establish causal relationships. Third, the non-uniform definition of hyperuricemia affected the comparability of results. Fourth, geographic distribution bias may limit the universal applicability of results. Finally, the possibility of publication bias cannot be excluded.

5.8 Future research directions

Future research should prioritize large-sample, multicenter prospective cohort studies using standardized hyperuricemia definitions (>7.0 mg/dL) and ED assessment tools. Intervention studies should evaluate the impact of uric acid-lowering therapy on erectile function to determine causality and clinical relevance. Mechanistic studies should explore dose-response relationships between uric acid levels and erectile function, particularly potential non-linear relationships. Genetic studies may help explain differences between populations and identify high-risk individuals.