Musculoskeletal Ultrasound Evaluates Renal Injury and Predicts Renal Outcome in Patients with Gout

Gout is the most common inflammatory arthritis in the world, and its incidence and prevalence are increasing globally. A total of 3.9%, 2.4%, and 1.4% of the population are affected by gout in the USA, the UK, and China, respectively [1‒3]. Recent studies have shown that gout is associated with an increased risk of various complications, including diabetes mellitus, cardiovascular disease, and chronic kidney disease (CKD) [4, 5]. CKD in patients with end-stage renal disease (ESRD) almost inevitably leads to renal replacement therapy and early death. A meta-analysis incorporating data from 17 different countries revealed that up to 24% of gout patients had stage 3 CKD or higher [6]. Large-scale prospective studies have identified that gout is an independent risk factor for new-onset CKD and ESRD [7, 8], suggesting that more attention should be given to gout-related renal damage. Longstanding hyperuricemia-related vascular nephropathy [9], urate crystal-induced obstruction and chronic inflammation [10], impairment led by comorbidities (including hypertension and diabetes mellitus), and exposure to non-steroidal anti-inflammatory drugs (NSAIDs) could be possible mechanisms.

In clinical practice, gout-related renal injury often lacks specific symptoms, leading to difficulty in early diagnosis. Renal function usually declines early without pronounced proteinuria, thus requiring a more sensitive diagnostic method for high-risk patients. However, the current challenge is the lack of diagnostic criteria and methods for evaluating renal risk in patients with gout. Although gout-related renal pathological changes have been described [11], including tubular dilation, atrophy, interstitial fibrosis, and arteriolosclerosis, the specificity is limited. Therefore, it is critical to develop new methods to improve screening and diagnosis in gout-related renal impairment.

Musculoskeletal ultrasound (MSUS) is a valuable technology that has been widely applied in the diagnosis and follow-up of gout. MSUS has the advantages of visualization, patient friendliness, widespread availability, and absence of radiation exposure. Previous results have shown that MSUS has good specificity and sensitivity in the diagnosis of gouty arthritis [12] and can monitor changes in monosodium urate (MSU) deposition in the joint, tendon, and synovium after urate-lowering treatment (ULT) [13]. However, the characteristic findings by MSUS in gout patients with CKD and the association between MSUS findings and renal outcome in gout patients have not yet been studied. Therefore, the current study was designed to determine the musculoskeletal characteristics in gout patients with CKD using MSUS technology, to assess the correlation between MSUS signs and kidney-related indicators, and to investigate whether MSUS could be used as an effective and non-invasive assessment to evaluate kidney injury and predict renal outcome in patients with gout.

This was a single-centre, cross-sectional study. Patients were observed in the outpatient nephrology clinic of Shanghai Jiao Tong University Affiliated Sixth People’s Hospital from January 2018 to June 2021 (shown in Fig. 1). All patients included were aged 18–85 years and diagnosed with gout (fulfilling the 2015 ACR/EULAR gout classification criteria, i.e., an individual with a score of ≥8 was classified as having gout) [14]. Patients diagnosed with CKD met the KDIGO 2012 clinical practice guideline [15]. Exclusion criteria included diagnosed diabetes mellitus, autoimmune disease, polycystic kidney, hepatitis virus infection, other primary or secondary kidney disease, malignant tumour, ESRD or renal replacement therapy, and existing ULT. All patients underwent MSUS scanning, and the index date was the date when the ultrasound examination was completed. The subjects were divided into a gout without CKD group (gout – CKD) and a gout with CKD group (gout + CKD). This study was approved by the Ethics Committee for human research of the Shanghai Jiao Tong University Affiliated Sixth People’s Hospital and was in accordance with the Declaration of Helsinki, Approval No: 2020-KY-003(k). Informed consent was obtained from all patients.

For all subjects, the clinical assessments of interest were collected at the outpatient clinic, mainly including demographic information, gout-related conditions (duration, the frequency of episodes in the last year, family history), and relevant drug exposure. The duration of gout was defined as the number of years since the first typical episode. The characteristics of typical episodes were defined according to the 2015 ACR/EULAR criteria [14]. Information was collected through electronic medical records or paper medical records. To minimize information bias, a trained doctor collected information according to a predesigned questionnaire and statement. The previous (3 or more months prior) laboratory results were obtained from the electronic or paper reports. The laboratory indicators used for cross-sectional analysis were derived from results during the first visit to our centre. All the samples were collected and assayed in a standardized manner. The CKD-EPI equation was used to calculate estimated glomerular filtration (eGFR) [16].

The ultrasound examinations were performed by 2 experienced musculoskeletal sonographers with more than 10 years of experience who were blinded to the participants’ clinical history. The 2 sonographers performed MSUS examination and interpreted the characteristics of gout according to a standard operating procedure referring to the International Consensus established by the OMERACT Ultrasound Gout Task Force group [17]. An Aplio 500 ultrasound machine (Toshiba, Tokyo, Japan) equipped with a multifrequency linear transducer (12–14 MHz) was used in the study. The factory setting for superficial MSUS was used. The routine scanning sites included the bilateral knee, ankle, foot and the first to fifth metatarsophalangeal (MTP) joints, as well as periarticular soft tissues. Five signs were assessed [17]: double contour signs (DCss), tophi, synovial hypertrophy (SH), synovial fluid, and erosion (shown in Fig. 2). DCss were abnormal, regular or irregular hyperechoic bands over the superficial margin of the hyaline cartilage, independent of the angle of insonation. Tophi were homogeneous or inhomogeneous, hyperechoic or hypoechoic aggregations, sometimes with a peri-hypoechoic halo. SH was defined as hypoechoic or hyperechoic tissue within the joint cavity. Synovial fluid was identified as anechoic or hypoechoic widening of the joint cavity that was displaceable and compressible. Erosion was defined as a discontinuity of the bone surface. Finally, kidney stone and renal cyst data were obtained from the kidney ultrasound report at this visit. The findings of MSUS examination were scored using the semiquantitative scoring system developed by Liu et al. [18], which assigned scores to 10 independent ultrasound features (online suppl. Table 1; for all online suppl. material, see www.karger.com/doi/10.1159/000528200).

Quantitative variables are presented as the mean ± standard deviation for normally distributed variables, median (interquartile range) for abnormally distributed variables, and counts and percentages for categorical variables. Differences between the two groups were assessed using the independent-sample t test and Mann-Whitney U test for normally distributed and abnormally distributed variables, respectively, and the χ² test or Fisher’s exact test for frequencies. Univariate logistic regression was performed to obtain the crude odds ratio (OR). A variable having a significant univariate test at the level of p value smaller than 0.05 was selected as a candidate for multivariate analysis. Potential confounding variables, including age, sex, body mass index (BMI), hypertension, NSAID exposure, and antihypertensive drug use, were adjusted using multivariate logistic regression to obtain adjusted ORs. Spearman’s rank correlation coefficient was used to estimate the correlation between MSUS findings and kidney-related indicators. Two-sided significance levels of 0.05 were used for all analyses. SPSS 25.0 for Windows and R for Windows v.4.1.2 were used for statistical analysis.

A total of 176 participants with gout were included in the study. The mean age was 50.8 ± 14.4 years, and 167 (94.9%) were male. Eighty-nine (50.6%) patients had gout alone, and 87 (49.4%) patients had gout and CKD. As shown in Table 1, clinically, gout patients with CKD were older (56.6 ± 12.1 vs. 45.1 ± 14.2, p < 0.001), had a greater prevalence of hypertension (62.1% vs. 39.3%, p = 0.003), had a longer duration of disease (median duration, 7.0 vs. 5.0, p = 0.023), and had more frequent gout episodes in the previous year (median, 6.0 vs. 3.0, p < 0.001). No significant differences were found between the two groups in sex, BMI, family history of gout, or use of NSAIDs. Laboratory findings showed that the gout + CKD group had worse renal abnormalities, including higher levels of serum creatinine, urea nitrogen, and cystatin C; lower eGFR values; and more pronounced urine protein presence. Serum albumin, haemoglobin, and erythrocyte values were lower in the gout + CKD group. There was no significant difference in the levels of blood glucose, blood lipids, or uric acid; liver function; erythrocyte sedimentation rate; or C-reactive protein level.

We then compared the ultrasound features between these two groups. As shown in Table 2, gout patients with CKD had higher ultrasound semiquantitative scores than those without CKD (17.8 ± 9.5 vs. 12.6 ± 10.1, p < 0.001), according to the MSUS scoring system [19]. The proportion of patients with a high stratification (score ≥26) was significantly higher in the gout + CKD group than in the gout – CKD group (20.7% vs. 12.4%, p = 0.002). The gout + CKD group had more severe joint damage with a heavier tophus burden (75.9% vs. 50.6%, p = 0.001), more tophi with a larger maximum diameter (median, 15.5 vs. 12.0, p = 0.027), and a higher incidence rate of bone erosion (69.0% vs. 51.7%, p = 0.019). However, no significant differences were found between the two groups in synovial fluid and hypertrophy presence. By studying the anatomical distribution of MSUS findings in patients with and without CKD, we found that gout patients with CKD were more susceptible to suffering SH in the knee and ankle joints. The incidence of tophi in the first metatarsophalangeal joint was higher in the gout + CKD group than in the gout – CKD group (online suppl. Table 2), suggesting that the knee and ankle joints were the most common sites of gout episodes and were associated with renal dysfunction in patients with gout.

To identify the characteristics with more independent differences between these two groups, logistic regression analysis was performed (Table 3). Variables with p < 0.05 on univariate analysis were selected as candidate factors for the multivariate analysis. After adjusting for age, sex, BMI, hypertension, and NSAID and angiotensin-converting enzyme inhibitor/angiotensin receptor blocker exposure, the association remained statistically significant in the gout classification criteria score (OR, 1.186; 95% confidence interval [CI], 1.057–1.330), episodes in the previous year (OR, 1.216; 95% CI, 1.087–1.360), ultrasound score (OR, 1.037; 95% CI, 1.001–1.074), existence of tophi (OR, 2.756; 95% CI, 1.322–5.746), and number of tophi (OR, 1.207; 95% CI, 1.056–1.380) (shown in online suppl. Fig. 1), suggesting that these characteristics could be risk factors in gout patients with kidney injury.

To further examine whether musculoskeletal findings were associated with kidney abnormities, we explored the correlation between MSUS signs and kidney-related indicators, including eGFR, urine albumin creatinine ratio, renal calculus, and cysts, in all subjects. We found that patients with tophi, bone erosion, or SH had a lower eGFR and the eGFR was negatively correlated with the number of these lesions (shown in Fig. 3a–c). Additionally, patients with tophi had a higher incidence rate of kidney stones (31.8% vs. 15.7%, p = 0.036, shown in Fig. 3d). There was no significant association between MSUS features and urine albumin creatinine ratio, the existence of renal cysts, or the number and size of kidney stones and renal cysts. These data suggest that MSUS findings can evaluate kidney injury in patients with gout by reflecting renal function and the renal calculus condition.

To explore the association between tophi and renal prognosis, we performed an additional retrospective cohort analysis. The cohort consisted of patients who were followed up for more than 1 year from our cross-sectional study. The existence of tophi at baseline was used as an exposure variable, and a ≥10% decline in eGFR within the first year served as an outcome variable. A total of 111 patients were analysed, including 76 patients with tophi and 35 patients without tophi. They all received treat-to-target ULT (defined as UA <300 μmol/L in patients with tophi or bone erosion, UA <360 μmol/L in the rest [19]). A comparison of baseline characteristics is shown in online supplementary Table 3. Patients with tophi were older, had a longer duration of disease, had more episodes in the previous year, and had worse renal function. After 1 year, outcomes occurred in 36 (47.4%) of 76 patients with tophi and in 7 (20%) of 35 patients without tophi. As shown in online supplementary Table 4, univariate logistic regression revealed that the existence of tophi increased the risk of ≥10% eGFR decline (OR, 3.60; 95% CI, 1.402–9.241). In multivariate analysis, after adjusting for other variables with significant differences at baseline and the control rate of ULT at the first year, we found that the existence of tophi was an independent risk factor (OR, 3.56; 95% CI, 1.382–9.176) for a ≥10% decline in eGFR after 1-year follow-up, suggesting that tophus detection by MSUS can predict renal outcome in patients with gout.

The prevalence of gout is increasing globally [20], leading to a high risk of renal complications [7]. Gout patients with kidney injury often have an insidious onset and lack typical clinical manifestations in the early stage. Additionally, the deterioration of renal function may not parallel proteinuria. The challenge for clinicians is that biomarkers or non-invasive methods with high sensitivity and specificity to evaluate gout-related kidney injury are still limited. Therefore, it is urgent to develop novel methods for the assessment of renal injury in gout patients.

MSUS is a non-invasive technology with the advantages of visualization, patient friendliness, and the ability to scan multiple joints in a short time. Compared with plain radiographs, MSUS can visualize MSU deposits (DCs and tophi) and assess gout-related lesions in multiple aspects (number, size, thickness, etc.) with good sensitivity and specificity [17]. MSUS also shows great value in the follow-up of gout. Esther et al. [13] found decreased sizes of tophi and numbers of DCs in patients who received ULT. Several semiquantitative scoring systems have been developed in recent years [18, 21], making ultrasound characteristics more practical for evaluating prognosis in gout patients. The new scoring system showed a sensitivity of 0.83 and a specificity of 0.76 in the diagnosis of gout [18].

Previous studies have revealed that gout patients with subcutaneous tophi by physical examination (PE) had a lower eGFR than those without tophi, regardless of whether they had complications [22]. Perez-Ruiz et al. [23] identified that clinical tophi were an independent risk factor for elevated mortality in a prospective gout cohort. However, gout crystal burden may be underestimated by PE or clinical manifestation. The sensitivity of tophus detection by MSUS in our study was significantly higher than that by PE in Fernando’s study (60% vs. 30%), which is consistent with the findings in another study [24]. This difference can be interpreted based on the ability of ultrasound to visualize tophi hidden in deep tissue space. Hence, the use of MSUS may be beneficial to provide more accurate and stronger evidence.

There are few studies regarding the correlation between MSUS signs and renal abnormities in gout. There are only some appendix observations simply mentioned in the studies focusing on the joint characteristics in gout patients. For example, Lu et al. [24] found that patients with tophi may have a lower eGFR. Patients with urate deposits seemed more susceptible to nephrolithiasis [25]. In the current study, we first used MSUS technology to compare the musculoskeletal characteristics in gout patients with or without CKD. We further studied the correlation between MSUS signs and kidney-related indicators and renal outcome in gout patients. Our data showed that advanced gout features such as tophi, chronic gouty synovitis, and bone erosion were associated with worse renal function in gout patients. These findings suggest that the MSUS technique has potential value in reflecting kidney injury in gout patients.

Tophi, the product of the chronic inflammatory response to MSU crystals [26], can lead to bone erosion by enhancing osteoclastogenesis and inhibiting osteoblast viability [27]. The existence of tophi and erosion reflects a heavier crystal burden that can activate innate immunity and promote proinflammatory responses [28]. Microcrystalline nephropathy is regarded as a critical mechanism of gout-related renal impairment [11]. Bardin et al. [29] recently found that over one third of untreated gout patients had a hyperechoic renal medulla, and dual-energy computed tomography showed the presence of urate deposits in the hyperechoic medulla [30]. In our study, we found that chronic gouty synovitis (SH) and frequent gout flares were also associated with renal abnormalities in gout patients. In addition, we are the first to explore the application of MSUS in assessing the renal prognosis of gout patients. In the retrospective cohort, we found that the existence of tophi at baseline was independently associated with an increased risk of a ≥10% decline in eGFR after 1-year follow-up, suggesting that MSUS could be a helpful measurement in assessing renal prognosis in patients with gout.

This is the first study to evaluate renal injury and predict renal outcome in patients with gout based on MSUS. However, there are some limitations of the present study. First, the single-centre design, small sample size, and strict exclusion criteria may have led to selection bias and insufficient generalizability. Second, renal prognosis data obtained from a retrospective cohort with a short duration of follow-up may not be convincing enough and should be validated in a prospective study with a longer duration of follow-up. Finally, compared with dual-energy computed tomography, ultrasound cannot accurately identify the components of hyperechoic substances, and although the sonographers reached a consensus on the standards of scanning and interpretation, interobserver reliability was not assessed, which may cause potential deviations in the results.

In conclusion, ultrasound-detected tophi, bone erosion, and SH were associated with worse renal function, and the existence of tophi was independently associated with a faster deterioration of renal function in the future. MSUS could be a potential auxiliary diagnostic method to evaluate kidney injury and predict renal outcome in gout patients. More convincing results remain to be provided by larger and more carefully designed clinical studies.

This study was reviewed and approved by the Ethics Committee for human research of the Shanghai Jiao Tong University Affiliated Sixth People’s Hospital and was in accordance with the Declaration of Helsinki, approval number (2020-KY-003[k]). Written informed consent was obtained for participation in this study.

The authors have no conflicts of interest to declare.

This work was supported by National Nature Science Foundation of China (82170727, 81870504 and 81870468), the Shanghai Jiao Tong University Gaofeng Talent Training Plan and a clinical project (20192833), Open Project of Shanghai Key Laboratory of Sleep Disordered Breathing (SHKSDB-KF-19-04), Three-Year Project of Shanghai TCM Development (ZT[2018-2020]-FWTX-2003), Star Program of Shanghai Jiao Tong University (20190102), and Open Project of National Science and Technology Infrastructure of translational medicine (Shanghai, TMSK-2021-109). The sponsors had no role in the design of the study; in the collection, analysis, and interpretation of data; in the writing of the article; and in the decision to submit the article for publication.

Ying Fan and Niansong Wang designed this study. Lixin Jiang, Yini Chen, Ze Li, and Li He performed the MSUS examination and interpreted the images. Junjie Jia, Ting Zhou, Qiming Zhang, and Haifan Xing participated in the acquisition of data. Jiali Jiao, Ze Li, and Li He performed all statistical analyses. Ze Li and Li He drafted the article. All authors were involved in interpreting data and revising the article critically for important intellectual content and gave final approval of the version to be published.

All data generated or analysed during this study are included in this article and its online supplementary material. Further enquiries can be directed to the corresponding author.

Ze Li and Li He contributed equally to this work.