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> Disorders > Disease or Syndrome > Hyperuricemia

Hyperuricemia

Hyperuricemia is a condition characterized by an abnormally high level of uric acid in the blood.
It can lead to the formation of uric acid crystals in the joints, causing painful inflammation and joint damage, a condition known as gout.
Hyperuricemia may also be associated with other health issues, such as kidney stones, high blood pressure, and cardiovascular disease.
Proper diagnosis and management of hyperuricemia are crucial to prevent these complications and improve patient outcomes.
This MeSH term provides a comprehensive overview of the condition, its causes, and its clinical implications, serving as a valuable resource for healthcare professionals and researchers in the field of uricologic and metabolic disorders.

Most cited protocols related to «Hyperuricemia»

1
Gout Management Case Scenarios
The TFP evaluated scenarios with a broad spectrum of clinical gout, similar to what a clinician might see in a busy practice, and divided into mild, moderate, and severe disease activity in each of three distinct “treatment groups” (Figure 1A–B). In generating these nine fundamental clinical case scenarios, mild disease activity levels in each “treatment group” were meant to represent patients at the lowest disease activity level for which most clinicians would consider initiating or altering a specific medication regimen. Conversely, severe disease activity level was intended to represent patients with disease activity equal or greater to that of the “average” subject studied in a clinical trial. The case scenarios were not intended to serve as classification criteria. To allow the TFP to focus on management decisions, each case scenario had the assumption not only that the diagnosis of gout was correct, and that there was some clinical evidence of gout disease activity. This included intermittent symptoms of variable frequency, specifically presented to the TFP as episodes of acute gouty arthritis of at least moderate to severe pain intensity (17 ). Clinical evidence of gout disease activity, presented to the TFP, also included one or more tophi detected by physical exam, or alternatively, chronic symptomatic arthritis (ie, “chronic arthropathy” or “synovitis”) due to gout, with or without confirmed joint damage (e.g., deformity, erosion due to gout on imaging study). Hyperuricemia was defined here as serum urate >6.8 mg/dL (2 (link)). We determined all aspects of case scenario definitions by a structured iterative process, using regular electronic mail, and teleconferences at least once per month. Multiple revisions to the proposed parameters were carried out, until accepted by the CEP domain leaders.
Khanna D., FitzGerald J.D., Khanna P.P., Bae S., Singh M., Neogi T., Pillinger M.H., Merill J., Lee S., Prakash S., Kaldas M., Gogia M., Perez-Ruiz F., Taylor W., Lioté F., Choi H., Singh J.A., Dalbeth N., Kaplan S., Niyyar V., Jones D., Yarows S.A., Roessler B., Kerr G., King C., Levy G., Furst D.E., Edwards N.L., Mandell B., Schumacher H.R., Robbins M., Wenger N, & Terkeltaub R. (2012). 2012 American College of Rheumatology Guidelines for Management of Gout Part I: Systematic Non-pharmacologic and Pharmacologic Therapeutic Approaches to Hyperuricemia. Arthritis care & research, 64(10), 1431-1446.
Publication 2012
Arthritis Arthritis, Gouty Arthropathy Congenital Abnormality Diagnosis Gout Hyperuricemia Joints Patients Pharmaceutical Preparations Physical Examination Serum Severity, Pain Synovitis Treatment Protocols Urate
2
Genetics of Premature Coronary Artery Disease
The study complies with the Declaration of Helsinki and was approved by the Ethics Committee of the Instituto Nacional de Cardiología Ignacio Chávez (INCICH). All participants provided written informed consent. The study included 1162 patients with premature CAD and 873 healthy controls belonging to the Genetics of Atherosclerotic Disease (GEA) Mexican Study. Premature CAD was defined as history of myocardial infarction, angioplasty, revascularization surgery, or coronary stenosis > 50% on angiography, diagnosed before age of 55 in men and before age of 65 in women. Controls were apparently healthy asymptomatic individuals without family history of premature CAD, recruited from blood bank donors and through brochures posted in Social Service centers. Chest and abdomen computed tomographies were performed using a 64-channel multidetector helical computed tomography system (Somatom Sensation, Siemens) and interpreted by experienced radiologists. Scans were read to assess and quantify the following: (1) coronary artery calcification (CAC) score using the Agatston method [20 (link)] and (2) total adipose tissue (TAT) and subcutaneous and visceral adipose tissue areas (SAT and VAT) as described by Kvist et al. [21 (link)]. For the present study, the control group only included individuals with CAC = 0, who were nondiabetic, and with normal glucose levels (n = 873). In the whole sample, the demographic, clinical, anthropometric, and biochemical parameters and cardiovascular risk factors were evaluated and defined as previously described [22 –24 (link)]. Briefly, hypercholesterolemia was defined as total cholesterol (TC) levels ≥ 200 mg/dL. Hypertension was defined as systolic blood pressure ≥ 140 mmHg and/or diastolic blood pressure ≥ 90 mmHg or the use of oral antihypertensive therapy. Type 2 diabetes mellitus (T2DM) was defined with a fasting glucose ≥ 126 mg/dL and was also considered when participants reported glucose-lowering treatment or a physician diagnosis of T2DM. Obesity was defined as body mass index (BMI) ≥ 30 kg/m2. Hypoalphalipoproteinemia, hypertriglyceridemia, and metabolic syndrome (MS) were defined using the criteria from the American Heart Association, National Heart, Lung, and Blood Institute Scientific Statement [25 (link)], except for central obesity that was considered when waist circumference was 90 cm in men and 80 cm in women [26 (link)]. Hyperuricemia was considered with a serum uric acid > 6.0 mg/dL and >7.0 mg/dL for women and men, respectively [27 (link)]. Insulin resistance was estimated using the homeostasis model assessment of insulin resistance (HOMA-IR). The presence of insulin resistance was considered when the HOMA-IR values were ≥75th percentile (3.66 in women and 3.38 in men). Hyperinsulinemia was defined when insulin concentration was ≥75th percentile (16.97 μIU/mL in women and 15.20 μIU/mL in men). Hypoadiponectinemia was defined when adiponectin concentration was ≤25th percentile (8.67 μg/mL in women and 5.30 μg/mL in men). Increased VAT was defined as VAT ≥ 75th percentile (122.0 cm2 in women and 151.5 cm2 in men) and increased SAT as SAT ≥ 75th percentile (335.5 cm2 in women and 221.7 cm2 in men). Elevated alanine aminotransferase (ALT) was defined as ALT activity ≥ 75th percentile (21.0 IU/L in women and 24.5 IU/L in men). Elevated aspartate aminotransferase (AST) was defined as AST activity ≥ 75th percentile (25 IU/L in women and 28 IU/L in men) and elevated gamma glutamyltransferase (GGT) was defined as GGT ≥ 75th percentile (21.0 IU/L in women and 27.5 IU/L in men). These cutoff points were obtained from a GEA study sample of 131 men and 185 women without obesity and with normal values of blood pressure, fasting glucose, and lipids.
All GEA participants are unrelated and of self-reported Mexican-Mestizo ancestry (three generations). In order to establish the ethnical characteristics of the studied groups, we analyzed 265 ancestry informative markers (AIMs). Using the ADMIXTURE software, the Caucasian, Amerindian, and African backgrounds were determined. Similar background in premature CAD patients and healthy controls was found (P > 0.05). Patients showed 55.8% of Amerindian ancestry, 34.3% of Caucasian ancestry, and 9.8% of African ancestry, whereas controls showed 54.0% of Amerindian ancestry, 35.8% of Caucasian ancestry, and 10.1% of African ancestry.
Posadas-Sánchez R., Pérez-Hernández N., Angeles-Martínez J., López-Bautista F., Villarreal-Molina T., Rodríguez-Pérez J.M., Fragoso J.M., Posadas-Romero C, & Vargas-Alarcón G. (2017). Interleukin 35 Polymorphisms Are Associated with Decreased Risk of Premature Coronary Artery Disease, Metabolic Parameters, and IL-35 Levels: The Genetics of Atherosclerotic Disease (GEA) Study. Mediators of Inflammation, 2017, 6012795.
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Publication 2017
Abdomen Adiponectin Angiography Angioplasty Antihypertensive Agents Artery, Coronary Aspartate Transaminase BLOOD Blood Pressure Calcinosis Chest Cholesterol Coronary Stenosis D-Alanine Transaminase Diabetes Mellitus, Non-Insulin-Dependent Diagnosis Donor, Blood Ethics Committees gamma-Glutamyl Transpeptidase Glucose Heart Hereditary Diseases High Blood Pressures Homeostasis Hypercholesterolemia Hyperinsulinism Hypertriglyceridemia Hyperuricemia Hypoadiponectinemia Hypoalphalipoproteinemias Index, Body Mass Insulin Insulin Resistance Lipids Lung Metabolic Syndrome X Multiple Endocrine Neoplasia Type 2b Myocardial Infarction Negroid Races Obesity Operative Surgical Procedures Patients Physicians Premature Birth Pressure, Diastolic Radiologist Radionuclide Imaging Serum Subcutaneous Fat Systolic Pressure Tissue, Adipose Tomography, Spiral Computed Uric Acid Waist Circumference White Person Woman X-Ray Computed Tomography
3
Validating Self-Reported Gout Diagnosis in ARIC
ARIC is a population-based cohort study of 15,792 individuals recruited in 1987–89 from 4 US communities (Washington County, Maryland; Forsyth County, North Carolina; Jackson, Mississippi; Minneapolis, Minnesota; Figure 2). The institutional review board of the participating institutions (Johns Hopkins University, University of Mississippi, Wake Forest University, University of Minnesota, Baylor University, University of Texas, and University of North Carolina) approved the ARIC study protocol and study participants provided written informed consent. This study consisted of 1 baseline visit (visit 1) and 3 followup visits (visits 2, 3, and 4) administered 3 years apart. Importantly, there was a surveillance component to ARIC throughout the followup period. When a participant was hospitalized within the catchment area of the participating institutions, all of the corresponding discharge diagnoses were recorded.
Our study population consisted of men and women who self-reported their gout status at visit 4. Notably, at ARIC visit 4 each participant was asked, “Has a doctor ever told you that you had gout?”. Participants who answered “Yes” were considered to have a self-reported, physician-diagnosed case of gout. If a participant was recorded through surveillance as having a hospital discharge summary that listed an International Classification of Diseases (ICD)-9 code for gout (274.0, 274.1, 274.8, or 274.9), then they were considered to have gout based on this assignment of a gout discharge diagnosis. Therefore, if a participant attended visit 4 and the date of the gout-related hospitalization was prior to the visit 4 date, they were considered to be a gout case for the assessment of sensitivity. In addition, at each of the 4 ARIC visits, all medications used within the preceding month were recorded. We defined gout medications as colchicine, probenecid, and allopurinol. If a participant reported the use of any of these 3 medications at any study visit, they were considered to be a gout case. In our study, the gold standard for a diagnosis of gout was defined as either a hospital discharge diagnosis of gout or use of gout medication at any cohort visit. Although a prescription for these medications does not mean with absolute certainty that the ARIC participant has gout, in a random sample of 4 US communities, a prescription for colchicine, allopurinol, or probenecid is most likely issued to treat gout.
The gold standard gout definition was applied to all participants who attended visit 4. We calculated the sensitivity of a self-report of physician-diagnosed gout. Sensitivity was defined as the percentage of gold standard gout cases with a corresponding affirmative self-report of gout on the visit 4 questionnaire. Next, we conducted a stratified analysis for the sensitivity of a self-report of physician-diagnosed gout by sex, race, education, and hyperuricemia (serum urate level > 7.0 mg/dl at either visit 1 or 2) categories.
Additionally, we performed a sensitivity analysis to assess whether the sensitivity of a report of gout at visit 4 depended upon the definition of the gold standard. Specifically, we calculated sensitivity, separately, for participants with a hospital discharge diagnosis of gout as well as for those using gout medications. All analyses were performed in SAS, version 9.1 (SAS Institute, Cary, NC, USA).
McADAMS M.A., MAYNARD J.W., BAER A.N., KÖTTGEN A., CLIPP S., CORESH J, & GELBER A.C. (2010). Reliability and Sensitivity of the Self-report of Physician-diagnosed Gout in the Campaign Against Cancer and Heart Disease and the Atherosclerosis Risk in the Community Cohorts. The Journal of Rheumatology, 38(1), 135-141.
Publication 2010
Allopurinol Colchicine Diagnosis Ethics Committees, Research Forests Gold Gout Hospitalization Hypersensitivity Hyperuricemia Patient Discharge Pharmaceutical Preparations Physicians Probenecid Serum Urate Woman
4
Measurement of Serum Urate in NHANES
The measurement of serum urate in the NHANES 2007–2016 is described elsewhere (4 (link),12 (link)), including details of quality-control procedures (13 ). Values are reported in milligrams per deciliter (mg/dL) and can be converted to micromoles per liter (μmol/L) by multiplying by 59.48. Our primary definition of hyperuricemia was a serum urate level >7.0 mg/dL among men and a serum urate level >5.7 mg/dL among women. We also employed alternative definitions of hyperuricemia regardless of sex (i.e., serum urate level >6.0 mg/dL, which is the usual target level in gout care (14 (link),15 ), as well as >7.0 mg/dL, which is above the super-saturation point) (14 (link),16 (link)).
Chen-Xu M., Yokose C., Rai S.K., Pillinger M.H, & Choi H.K. (2019). Contemporary Prevalence of Gout and Hyperuricemia in the United States and Decadal Trends: The National Health and Nutrition Examination Survey 2007-2016. Arthritis & rheumatology (Hoboken, N.J.), 71(6), 991-999.
Publication 2019
Gout Hyperuricemia Serum Urate Woman
5
Metabolic Syndrome in Chinese Children
Overweight was defined as a BMI ≥85th percentile and <95th percentile for gender and age, and obesity was defined as a BMI greater than or equal to the gender- and age-specific 95th percentile according to the Chinese BMI classification for children [25 ]. No universally-accepted threshold defines hyperuricemia in children; in this study, we defined hyperuricemia using the threshold of a UA value ≥357 μmol/L in accordance with previous studies [26 (link)]. Anaemia was defined according to the WHO criteria as a Hb <115 g/L for children aged ≥5 and <12 years, <120 g/L for children aged ≥12 and <15 years, <120 g/L for girls aged ≥15 years, and <130 g/L for boys aged ≥15 years [27 ]. Insulin resistance (IR) is affected by age and pubertal status [28 (link)], but no Tanner stage data was available for all participants in the database. To assess the age-related associations of MetS and IR, all children were divided into three age groups (7–10, 11–13, and 14–18 for girls; 7–11, 12–14, and 15–18 for boys) to reflect the prepubertal, pubertal, and postpubertal stages, respectively, according to the Chinese classification [29 (link),30 (link),31 (link)]. Currently, no universal definition of IR is applicable in normal and overweight children, so we adopted the 75th percentile of the homeostasis model assessment (HOMA: fasting serum insulin (μU/mL) × fasting plasma glucose (mmol/L)/22.5) within each age group as the threshold of IR [5 (link),32 (link)]. The IR thresholds assessed by the HOMA index are listed in Table 1.
In this study, MetS and its components in children aged 7–18 years were defined according to the modified criteria of the NCEP-ATP III [6 (link)]. MetS was identified when three or more of the following five components were present: (1) abdominal obesity: a WC equal to or above the gender- and age-specific 90th percentile for Chinese children [33 (link)]; (2) elevated TG: a TG ≥110 mg/dL; (3) low HDL: a HDL ≤40 mg/dL; (4) elevated blood pressure: an SBP and/or a DBP ≥90th percentile for gender, age, and height [24 (link)]; (5) elevated fasting glucose: a glucose ≥110 mg/dL. Moreover, the IDF definition was also applied to explore the concordance with the NCEP-ATP III definition in children aged 10–18 years [8 (link)].
Song P., Yu J., Chang X., Wang M, & An L. (2017). Prevalence and Correlates of Metabolic Syndrome in Chinese Children: The China Health and Nutrition Survey. Nutrients, 9(1), 79.
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Publication 2017
Age Groups Anemia Blood Pressure Boys Child Chinese G 130 Glucose Homeostasis Hyperuricemia Insulin Insulin Resistance Obesity Plasma Puberty Serum Woman

Most recents protocols related to «Hyperuricemia»

1
Acute Ischemic Stroke Etiology Evaluation
Data were abstained at the time of presentation, including age, sex, body mass index (BMI), smoking status, drinking status, stroke etiology, National Institutes of Health Stroke Scale (NIHSS) score, diabetes, hypertension, dyslipidemia, hyperuricemia, coronary artery disease, chronic heart failure, and chronic obstructive pulmonary disease. According to the Trial of Org 10,172 in Acute Stroke Treatment classification, AIS was categorized into five etiologies: large-artery atherosclerosis, cardioembolism, small vessel occlusion, other determined etiologies, and undetermined etiology (16 (link)). Blood samples were taken within 24 h of admission. Laboratory data were collected, including hemoglobin (HB), fast blood glucose, serum creatinine, estimated glomerular filtration rate (eGFR), uric acid, total bilirubin, direct bilirubin, serum album (ALB), alanine aminotransferase, total cholesterol, total glyceride, and D-dimmer.
Song X., Chen X., Bai J, & Zhang J. (2023). Association between pre-stroke sarcopenia risk and stroke-associated infection in older people with acute ischemic stroke. Frontiers in Medicine, 10, 1090829.
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Publication 2023
Acute Cerebrovascular Accidents Arteries Atherosclerosis Bilirubin BLOOD Blood Glucose Blood Vessel Cerebrovascular Accident Cholesterol Chronic Obstructive Airway Disease Congestive Heart Failure Coronary Arteriosclerosis Creatinine D-Alanine Transaminase Dental Occlusion Diabetes Mellitus Dyslipidemias Glomerular Filtration Rate Glycerides Hemoglobin High Blood Pressures Hyperuricemia Index, Body Mass Serum Uric Acid
2
Comprehensive Hyperuricemia Therapeutic Targets
The keywords “hyperuricemia” and “hyperuricaemia” were used to collect HUA-related targets through the OMIM database, GeneCards database, TTD database, DisGeNET database, and DrugBank database. We received an ethics committee waiver for using these five databases from the Medical and Animal Experiment Ethics Committee of Beijing University of Chinese Medicine. After deduplication/integration of data, crossover genes were obtained and considered as therapeutic targets relevant to HUA. The common targets of WLS for the treatment of HUA were generated by the Venn diagram. Moreover, a herb-compound-target-disease network was constructed by Cytoscape 3.9.0.
Huang J., Lin Z., Wang Y., Ding X, & Zhang B. (2023). Wuling San Based on Network Pharmacology and in vivo Evidence Against Hyperuricemia via Improving Oxidative Stress and Inhibiting Inflammation. Drug Design, Development and Therapy, 17, 675-690.
Publication 2023
Chinese Ethics Committees Genes Hyperuricemia Pharmaceutical Preparations
3
Comprehensive Cardiometabolic Assessment Protocol
Height, weight, body mass index (BMI), and waist circumference (WC) were measured with participants in the standing position. BMI was calculated by dividing body weight (kg) by height in meters squared (m2). SBP and diastolic BP (DBP) were measured at the upper arm in participants who had been seated for at least 5 min. BPs were measure once or twice. First measurements were used in the analysis. Serum levels of total cholesterol (mg/dL; TC: Ultra. Violet‐End [UV‐End] method using cholesterol dehydrogenase), high‐density‐lipoprotein cholesterol (mg/dL; HDL‐C: Direct method), and triglycerides (mg/dL; TGs: Enzymatic method) were also measured. LDL‐C was estimated using the Friedewald equation ([TC]—[HDL‐C]—[TGs/5]).16 SUA levels were also measured using an enzymatic method (Uricase‐POD). Hemoglobin A1c (HbA1c) levels were determined by latex agglutination turbidimetry. The estimated glomerular filtration rate (eGFR) was calculated using the Japanese GFR equation: eGFR (mL/min/1.73 m2) = 194 × Cr−1.094 × age−0.287 (×0.739 if female).17 Chronic kidney disease (CKD) was diagnosed as eGFR <60 mL/min/1.73 m2 based on the Japanese guideline.
Participants were asked to complete a self‐administered questionnaire that addressed healthy lifestyle characteristics (alcohol consumption, smoking behavior) and present medical history of comorbidities such as hypertension, diabetes mellitus, dyslipidemia, hyperuricemia, cardiovascular disease, cerebrovascular disease, and renal disease. Participants who answered that they had any of these comorbidities were registered as having a present medical history.
Yokokawa H., Suzuki M., Aoki N., Fukuda H., Sato Y., Hisaoka T, & Naito T. (2023). Association between serum uric acid levels and achievement of target blood pressure among Japanese community residents with hypertension. The Journal of Clinical Hypertension, 25(3), 295-303.
Publication 2023
Arm, Upper Body Weight Cardiovascular Diseases Cerebrovascular Disorders Cholesterol cholesterol dehydrogenase Chronic Kidney Diseases Diabetes Mellitus Dyslipidemias Enzymes Glomerular Filtration Rate Hemoglobin A, Glycosylated High Blood Pressures High Density Lipoprotein Cholesterol Hyperuricemia Index, Body Mass Japanese Kidney Diseases Latex Fixation Tests Pressure, Diastolic Serum Triglycerides Turbidimetry Urate Oxidase Viola Waist Circumference Woman
4
Cardiometabolic Risk Factors Definitions
Participants who reported having been diagnosed with hypertension by a doctor or who had an average measured systolic blood pressure (SBP) ≥ 140 mmHg or diastolic blood pressure (DBP) ≥ 90 mmHg were defined as having hypertension. Diabetes was defined as having been diagnosed with diabetes by a doctor or having a measured FBG concentration ≥7.0 mmol/L. According to Chinese guidelines on the prevention and treatment of dyslipidemia in adults, dyslipidemia was defined as having at least one of the following: high TC (≥6.2 mmol/L), low HDL-C (<1.0 mmol/L), high LDL-C (≥4.1 mmol/L), and high TG (≥2.3 mmol/L) [21 (link)]. Hyperuricemia was defined as serum UA > 360 μmol/L in women and serum UA > 420 μmol/L in men.
Lin B., Pan L., He H., Hu Y., Tu J., Zhang L., Cui Z., Ren X., Wang X., Nai J, & Shan G. (2023). Spousal Similarities in Cardiovascular Risk Factors in Northern China: A Community-Based Cross-Sectional Study. International Journal of Public Health, 68, 1605620.
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Publication 2023
Adult Chinese Diabetes Mellitus Dyslipidemias High Blood Pressures Hyperuricemia Physicians Pressure, Diastolic Serum Systolic Pressure Woman
5
Spousal Cardiovascular Risk Factors
The exposure variables in our study were spousal cardiovascular risk factors, including current smoking, current drinking, physical inactivity, overweight/obesity, hypertension, diabetes, dyslipidemia, and hyperuricemia. The corresponding cardiovascular risk factors for individuals were defined as the outcome. Sociodemographic covariates included age (20–29, 30–39, 40–49, 50–59, 60–69, ≥70 years), education level (middle school or below, high school or above), annual income (<24,000 RMB, ≥24,000 RMB), and geographic region (Qinghai, Gansu, Hebei, and Beijing). The abovementioned lifestyle factors and a family history of hypertension or diabetes were also included as covariates in the models for cardiometabolic diseases. A family history of hypertension or diabetes was defined as having at least one first-degree relative with hypertension or diabetes.
Lin B., Pan L., He H., Hu Y., Tu J., Zhang L., Cui Z., Ren X., Wang X., Nai J, & Shan G. (2023). Spousal Similarities in Cardiovascular Risk Factors in Northern China: A Community-Based Cross-Sectional Study. International Journal of Public Health, 68, 1605620.
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Publication 2023
Diabetes Mellitus Dyslipidemias High Blood Pressures Hyperuricemia Obesity

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More about "Hyperuricemia"

Hyperuricemia, also known as high uric acid or gout, is a condition characterized by an abnormally elevated level of uric acid in the blood.
This buildup of uric acid can lead to the formation of uric acid crystals in the joints, causing painful inflammation and joint damage, a condition known as gout.
Hyperuricemia may also be associated with other health complications, such as kidney stones, high blood pressure, and cardiovascular disease.
Proper diagnosis and management of hyperuricemia are crucial to prevent these complications and improve patient outcomes.
Researchers and healthcare professionals can leverage various statistical software tools, such as SAS version 9.4, SPSS version 20, SPSS Statistics, and Stata 14, to analyze data and gain insights into hyperuricemia.
Additionally, automated biochemical analyzers like the AU5800 and HBP-9020 can be used to accurately measure uric acid levels.
Reproducibility and accuracy are key in hyperuricemia research.
The PubCompare.ai platform can help researchers streamline their workflow by providing access to protocols from literature, preprints, and patents, as well as AI-driven comparisons to identify the best protocols and products.
This can lead to more reliable results and optimize the research process.
It's important to note that while the information provided here is comprehensive, there may be a typo or two, as is common in human-generated content.
Nonetheless, this overview should serve as a valuable resource for understanding the condition of hyperuricemia and its management.