Determining the role of statins in Parkinson's disease risk reduction and disease modification: A comprehensive meta-analysis of 4 million participants' data.

BACKGROUND: Many observational studies have examined the association between statins and the incidence of Parkinson's disease (PD) in high-risk populations. On the other hand, clinical trials as well as other observational studies investigated the safety and efficacy of statins in slowing disease progression in PD patients. However, the evidence has been inconclusive in both questions. To that end, we conducted this systematic review and meta-analysis to synthesize evidence on the role of statins in decreasing the risk of PD among high-risk populations and as a possible disease-modifying agent for patients with PD. METHODS: A comprehensive literature search of electronic databases including PubMed, Scopus, Cochrane, and Web of Science has been performed. Relevant studies were chosen and data were extracted and analyzed using RevMan software version 5.4.1. RESULTS: Twenty-five studies (14 cohort, 9 case-control, and 2 randomized controlled trials) have been included in the present systematic review. Of them, 21 studies reported the association between statins and PD risk. Statins were found to significantly reduce the risk of developing PD (pooled RR 0.86, 95% CI [0.77-0.95], p < 0.005). Four studies investigated statins as a disease-modifying agent. The pooled mean difference (MD) in the UPDRS-III from baseline to endpoint did not differ significantly between the statin and control groups (MD -1.34 points, 95% CI [-3.81 to 1.14], p = 0.29). CONCLUSION: Although epidemiological observational studies showed that statin use was associated with a reduced risk of PD, current evidence is insufficient to support the role of statins in slowing the progression of PD. These findings are limited by the fact that most of the included studies are observational studies which carry a high risk of confounding bias which highlights the need for future well-designed RCTs.

Machine learning-based prediction model for the efficacy and safety of statins.

Objective: The appropriate use of statins plays a vital role in reducing the risk of atherosclerotic cardiovascular disease (ASCVD). However, due to changes in diet and lifestyle, there has been a significant increase in the number of individuals with high cholesterol levels. Therefore, it is crucial to ensure the rational use of statins. Adverse reactions associated with statins, including liver enzyme abnormalities and statin-associated muscle symptoms (SAMS), have impacted their widespread utilization. In this study, we aimed to develop a predictive model for statin efficacy and safety based on real-world clinical data using machine learning techniques. Methods: We employed various data preprocessing techniques, such as improved random forest imputation and Borderline SMOTE oversampling, to handle the dataset. Boruta method was utilized for feature selection, and the dataset was divided into training and testing sets in a 7:3 ratio. Five algorithms, including logistic regression, naive Bayes, decision tree, random forest, and gradient boosting decision tree, were used to construct the predictive models. Ten-fold cross-validation and bootstrapping sampling were performed for internal and external validation. Additionally, SHAP (SHapley Additive exPlanations) was employed for feature interpretability. Ultimately, an accessible web-based platform for predicting statin efficacy and safety was established based on the optimal predictive model. Results: The random forest algorithm exhibited the best performance among the five algorithms. The predictive models for LDL-C target attainment (AUC = 0.883, Accuracy = 0.868, Precision = 0.858, Recall = 0.863, F1 = 0.860, AUPRC = 0.906, MCC = 0.761), liver enzyme abnormalities (AUC = 0.964, Accuracy = 0.964, Precision = 0.967, Recall = 0.963, F1 = 0.965, AUPRC = 0.978, MCC = 0.938), and muscle pain/Creatine kinase (CK) abnormalities (AUC = 0.981, Accuracy = 0.980, Precision = 0.987, Recall = 0.975, F1 = 0.981, AUPRC = 0.987, MCC = 0.965) demonstrated favorable performance. The most important features of LDL-C target attainment prediction model was cerebral infarction, TG, PLT and HDL. The most important features of liver enzyme abnormalities model was CRP, CK and number of oral medications. Similarly, AST, ALT, PLT and number of oral medications were found to be important features for muscle pain/CK abnormalities. Based on the best-performing predictive model, a user-friendly web application was designed and implemented. Conclusion: This study presented a machine learning-based predictive model for statin efficacy and safety. The platform developed can assist in guiding statin therapy decisions and optimizing treatment strategies. Further research and application of the model are warranted to improve the utilization of statin therapy.

Role of gut microbiota and metabolomics in the lipid-lowering efficacy of statins among Chinese patients with coronary heart disease and hypercholesterolemia.

Background: Statins, being the primary pharmacological intervention for hypercholesterolemia, exhibit a notable degree of interpatient variability in their effectiveness, which may be associated with gut microbiota. This study sought to identify the biomarkers for evaluating differences in statin efficacy. Methods: A quasi case-control study was conducted among participants with hypercholesterolemia and coronary heart disease taking rosuvastatin essential. According to the level of low density lipoprotein cholesterol (LDL-C), participants was divided into the "Up to standard" (US) group and the "Below standard" (BS) group. 16S rDNA sequencing and untargeted metabolomics were applied to detected the information of gut microbiota and related metabolites. Results: A total of 8 US and 8 BS group matched by age and sex were included in the final analysis. 16S rDNA sequencing results indicated that the characteristic strains of the US group were f-Eubacterium_coprostanoligenes and g-Papillibacter, while the characteristic flora of the BS group were o-C0119, g-Pseudolabrys, s-Dyella-Marensis and f-Xanthobacaceae. Metabolomic results suggested that the levels of chenodeoxycholic acid-3-ß-D-glucuronide, 1-methylnicotinamide and acetoacetate in stool samples of the US group were significantly higher than those of the BS group. By identifying the differentially abundant bacterial taxa, the gut microbiota could modulate the efficacy of statins through producing enzymes involved in cholesterol metabolism. Conclusions: The findings suggest that the difference in statin efficacy may be related to gut microbiota strains that can produce short-chain fatty acids and secondary bile acids and affect the efficacy of statins by regulating the activities of cholesterol metabolite-related proteins. Metabolites related to short-chain fatty acids and secondary bile acids in the gut are expected to be biomarkers indicating the efficacy of statins.

Additional statin treatment enhances the efficacy of HER2 blockade and improves prognosis in Rac1-high/HER2-positive breast cancer.

The prognosis of HER2-positive breast cancer (BC) has improved with the development of anti-HER2 therapies; however, the problem remains that there are still cases where anti-HER2 therapies do not respond well. We found that the expression of SREBF2, a master transcriptional factor in the mevalonate pathway, was correlated with ERBB2 (HER2) expression and a poor prognosis in HER2-positive BC. The target gene expressions of SREBF2 were associated with higher expression of ERBB2 in HER2-positive BC cells. Statins, anti-hypercholesterolemia drugs that inhibit the mevalonate pathway, enhanced the efficacy of HER2-targeting agents with inducing apoptosis in a geranylgeranylation-dependent manner. Mechanistically, statins specifically inhibited membrane localization of Rac1, a target protein of geranylgeranylation, and suppressed the activation of HER2 downstreams AKT and ERK pathways. Consistently, retrospective analysis showed a longer recurrence-free survival in Rac1-high/HER2-positive BC patients treated with HER2-targeting agents with statins than without statins. Our findings thus suggest that Rac1 expression could be used as a biomarker to stratify HER2-positive BC patients that could benefit from dual blockade, i.e., targeting HER2 with inhibition of geranylgeranylation of Rac1 using statins, thereby opening avenues for precision medicine in a new subset of Rac1-high/HER2-positive BC.

The Impact of Statins on Disease Severity and Quality of Life in Patients with Psoriasis: A Systematic Review and Meta-Analysis.

BACKGROUND: Psoriasis, a chronic autoimmune condition, imposes significant burdens on patients' well-being. While corticosteroid medications are commonly used, their prolonged use presents risks. Statins, known for their immunoregulatory and anti-inflammatory properties, have emerged as potential alternatives. Previous reviews indicated that statins might improve psoriasis symptoms but showed inconsistent results and lacked meta-analyses that generated pooled effect estimates. Therefore, this study addresses this gap by providing a comprehensive overview of the impact of statins on psoriasis severity and quality of life (QoL) for patients with psoriasis. METHODS: A thorough search of four electronic databases (PubMed, Cochrane Central Register of Controlled Trials, Scopus, and Science Direct) was conducted for relevant studies published before April 2024. RESULTS: Seven studies involving 369 patients were included. This meta-analysis showed a statistically significant reduction in PASI scores at week 8 with statin treatment (MD = -1.96, 95% CI [-3.14, -0.77], p = 0.001). However, no statistically significant difference was found between statins and placebo at week 12 (MD = 0.19, 95% CI [-0.18, 0.55]). Additionally, DLQI scores indicated a significant improvement in quality of life with statins compared to placebo (MD = -3.16, 95% CI [-5.55, -0.77]). CONCLUSIONS: Statins can improve disease severity and quality of life in psoriasis patients, suggesting the potential benefits of statin therapy. However, further research is needed to determine the optimal treatment duration, address outcome heterogeneity, and explore additional benefits such as cholesterol and triglyceride reduction.

Research advances in the therapy of metabolic syndrome.

Metabolic syndrome refers to the pathological state of metabolic disorder of protein, fat, carbohydrate, and other substances in the human body. It is a syndrome composed of a group of complex metabolic disorders, whose pathogenesis includes multiple genetic and acquired entities falling under the category of insulin resistance and chronic low-grade inflammationand. It is a risk factor for increased prevalence and mortality from diabetes and cardiovascular disease. Cardiovascular diseases are the predominant cause of morbidity and mortality globally, thus it is imperative to investigate the impact of metabolic syndrome on alleviating this substantial disease burden. Despite the increasing number of scientists dedicating themselves to researching metabolic syndrome in recent decades, numerous aspects of this condition remain incompletely understood, leaving many questions unanswered. In this review, we present an epidemiological analysis of MetS, explore both traditional and novel pathogenesis, examine the pathophysiological repercussions of metabolic syndrome, summarize research advances, and elucidate the mechanisms underlying corresponding treatment approaches.

Associations between Statin Use and Glaucoma in the All of Us Research Program.

PURPOSE: To investigate associations between statin use and glaucoma in the 2017-2022 All of Us (AoU) Research Program. DESIGN: Cross-sectional, population-based. PARTICIPANTS: 79,742 adult participants aged ≥ 40 years with hyperlipidemia and with electronic health record (EHR) data in the AoU database. METHODS: Hyperlipidemia, glaucoma status, and statin use were defined by diagnoses and medication information in EHR data collected by AoU. Logistic regression analysis was performed to evaluate the association between statin use and glaucoma likelihood. Logistic regression modeling was used to examine associations between glaucoma and all covariates included in adjusted analysis. Serum low-density lipoprotein cholesterol (LDL-C) was used to assess hyperlipidemia severity. Analyses stratified by LDL-C level and age were performed. MAIN OUTCOME MEASURES: Any glaucoma as defined by International Classification of Diseases (ICD) codes found in EHR data. RESULTS: Of 79,742 individuals with hyperlipidemia in AoU, there were 6,365 (8.0%) statin users. Statin use was associated with increased glaucoma prevalence when compared with statin non-use (adjusted odds ratio [aOR]: 1.13, 95% confidence interval [CI]: 1.01-1.26). Higher serum levels of LDL-C were associated with increased odds of glaucoma (aOR: 1.003, 95% CI: 1.003, 1.004). Statin users had significantly higher LDL-C levels compared to nonusers (144.9 mg/dL versus 136.3 mg/dL, p-value < 0.001). Analysis stratified by LDL-C identified positive associations between statin use and prevalence of glaucoma among those with optimal (aOR = 1.39, 95% CI = 1.05-1.82) and high (aOR = 1.37, 95% CI = 1.09-1.70) LDL-C levels. Age-stratified analysis showed a positive association between statin use and prevalence of glaucoma in individuals aged 60-69 years (aOR = 1.28, 95% CI = 1.05-1.56). CONCLUSIONS: Statin use was associated with increased glaucoma likelihood in the overall adult AoU population with hyperlipidemia, in individuals with optimal or high LDL-C levels, and in individuals 60-69 years old. Findings suggest that statin use may be an independent risk factor for glaucoma, which may furthermore be affected by one's lipid profile and age.

Early Management of Blood Lipid Levels with Non-Statin Lipid-Lowering Drugs in Acute Coronary Syndrome: A Mini Review.

Acute coronary syndrome (ACS) remains a major cause of morbidity and mortality, despite many improvements in its prevention and management. Lipid management is an important aspect of secondary prevention after ACS. Previous studies indicate that the early use of intensive statin therapy in patients with ACS may alleviate the risk of recurrent cardiovascular events and mortality. However, many patients do not reach the target low-density lipoprotein cholesterol (LDL-C) level of < 55 mg/dL with statin monotherapy, and muscle-related adverse effects caused by statins hinder adherence to treatment. Novel non-statin agents are recommended for patients who cannot achieve the target LDL-C levels with high-intensity statin therapy and those with statin intolerance. The combination of statins and non-statins may synergistically affect intensively lowering LDL-C through different mechanisms, which could lead to better cardiovascular outcomes than statin monotherapy. However, it remains uncertain whether the early use of combination lipid-lowering therapy is more beneficial. The present review summarizes the benefits of intensive statin monotherapy and their early combination with non-statin medications including ezetimibe, PCSK9 inhibitors, inclisiran, and bempedoic acid (BDA) in the management of ACS.

A pharmacovigilance study of chronic kidney disease in diabetes mellitus patients with statin treatment by using the US Food and Drug Administration adverse event reporting system.

Background: Statins were regarded as a main medication for managing hypercholesterolemia. Administration of statin therapy could reduce the incidence of cardiovascular disease in individuals diagnosed with type 2 diabetes mellitus (DM), which was recognized by multipal clinical guidelines. But previous studies had conflicting results on whether the long-term use of statins could benefit the renal function in diabetic patients. Aim: To evaluate the association between statin treatment and Chronic Kidney Disease in DM patients. Methods: This is a retrospective disproportionality analysis and cohort study based on real-world data. All DM cases reported in US Food and Drug Administration adverse event reporting system (FAERS) between the first quarter of 2004 and the fourth quarter of 2022 were included. Disproportionality analyses were conducted by estimating the reporting odds ratio (ROR) and the information component (IC). We further compared the CKD odds ratio (OR) between the statins group and the other primary suspected drug group among the included diabetes mellitus cases. Results: We finally included 593647 DM cases from FAERS, 5113 (5.31%) CKD cases in the statins group and 8810 (1.77%) CKD cases in the control group. Data analysis showed that the statins group showed a significant CKD signal (ROR: 3.11, 95% CI: 3.00-3.22; IC: 1.18, 95% CI: 1.07-1.29). In case group with two or more statins treatment history, the CKD signal was even stronger (ROR: 19.56, 95% CI: 18.10-21.13; IC: 3.70, 95% CI:3.44-3.93) compared with cases with one statin treatment history. Conclusion: The impact of statin therapy on the progression of renal disease in individuals diagnosed with type 2 diabetes mellitus (DM) remains inconclusive. After data mining on the current FAERS dataset, we discovered significant signals between statin treatment and CKD in diabetic patients. Furthermore, the incidence rate of CKD was higher among DM patients who used statins compared to those who did not.

Effect modification by statin use status on the association between fine particulate matter (PM2.5) and cardiovascular mortality.

BACKGROUND: Numerous studies have linked fine particulate matter (PM2.5) to increased cardiovascular mortality. Less is known how the PM2.5-cardiovascular mortality association varies by use of cardiovascular medications. This study sought to quantify effect modification by statin use status on the associations between long-term exposure to PM2.5 and mortality from any cardiovascular cause, coronary heart disease (CHD), and stroke. METHODS: In this nested case-control study, we followed 1.2 million community-dwelling adults aged ≥66 years who lived in Ontario, Canada from 2000 through 2018. Cases were patients who died from the three causes. Each case was individually matched to up to 30 randomly selected controls using incidence density sampling. Conditional logistic regression models were used to estimate odds ratios (ORs) for the associations between PM2.5 and mortality. We evaluated the presence of effect modification considering both multiplicative (ratio of ORs) and additive scales (the relative excess risk due to interaction, RERI). RESULTS: Exposure to PM2.5 increased the risks for cardiovascular, CHD, and stroke mortality. For all three causes of death, compared with statin users, stronger PM2.5-mortality associations were observed among non-users [e.g. for cardiovascular mortality corresponding to each interquartile range increase in PM2.5, OR = 1.042 (95% CI, 1.032-1.053) vs OR = 1.009 (95% CI, 0.996-1.022) in users, ratio of ORs = 1.033 (95% CI, 1.019-1.047), RERI = 0.039 (95% CI, 0.025-0.050)]. Among users, partially adherent users exhibited a higher risk of PM2.5-associated mortality than fully adherent users. CONCLUSIONS: The associations of chronic exposure to PM2.5 with cardiovascular and CHD mortality were stronger among statin non-users compared to users.

Short-Term Statin Therapy Induces Hepatic Insulin Resistance Through HNF4α/PAQR9/PPM1α Axis Regulated AKT Phosphorylation.

Statins, the first-line medication for dyslipidemia, are linked to an increased risk of type 2 diabetes. But exactly how statins cause diabetes is yet unknown. In this study, a developed short-term statin therapy on hyperlipidemia mice show that hepatic insulin resistance is a cause of statin-induced diabetes. Statin medication raises the expression of progesterone and adiponectin receptor 9 (PAQR9) in liver, which inhibits insulin signaling through degradation of protein phosphatase, Mg2+/Mn2+ dependent 1 (PPM1α) to activate ERK pathway. STIP1 homology and U-box containing protein 1 (STUB1) is found to mediate ubiquitination of PPM1α promoted by PAQR9. On the other hand, decreased activity of hepatocyte nuclear factor 4 alpha (HNF4α) seems to be the cause of PAQR9 expression under statin therapy. The interventions on PAQR9, including deletion of PAQR9, caloric restriction and HNF4α activation, are all effective treatments for statin-induced diabetes, while liver specific over-expression of PPM1α is another possible tactic. The results reveal the importance of HNF4α-PAQR9-STUB1-PPM1α axis in controlling the statin-induced hepatic insulin resistance, offering a fresh insight into the molecular mechanisms underlying statin therapy.

PCSK9 inhibition: from effectiveness to cost-effectiveness.

Dyslipidaemia is a complex disorder characterised by abnormal lipid levels in the blood, including cholesterol and triglycerides, and plays an important role in the development of atherosclerotic cardiovascular disease. Most risk factors for cardiovascular disease are modifiable, and dyslipidaemia is a key factor among them. It can result from a combination of genetic and environmental factors. A distinction is made between primary dyslipidaemia, which is mainly caused by inherited genetic changes, and secondary dyslipidaemia, which is due to underlying diseases or certain medications. The treatment of dyslipidaemia has evolved over the years. In the past, statins were the first choice, but newer drugs, such as proprotein convertase subtilisin-kexin type 9 (PCSK9) inhibitors, have gained prominence due to their effectiveness in lowering lipids. Although recent guidelines recommend PCSK9 inhibitors for high-risk patients and patients who cannot tolerate statins, their widespread use is limited because of cost. Several meta-analyses have confirmed the efficacy and safety of PCSK9 inhibitors and have shown a significant reduction in low-density lipoprotein (LDL) cholesterol levels. However, the long-term side effects and interactions with other risk factors for cardiovascular disease remain uncertain. In addition, cost-effectiveness analyses have shown mixed results, with some countries considering PCSK9 inhibitors to be cost-effective for certain patient groups, while others consider them less economical. Meanwhile, initial data from patients using PCSK9 inhibitors support the results of the clinical trials. To summarise, PCSK9 inhibitors represent a revolutionary solution for lowering LDL cholesterol, but their cost-effectiveness remains controversial. Despite the controversy, they offer clear benefits for high-risk patients and should therefore be considered in the treatment of dyslipidaemia.

Causal impact of statins on susceptibility to osteoarthritis: insights from a two-sample Mendelian randomization analysis.

BACKGROUND: Osteoarthritis is a widely prevalent cause of pain and disability among older adults. It is an incurable condition, and most treatments are aimed at alleviating symptoms. AIM: This study aimed to investigate the impact of statins on osteoarthritis by using a two-sample Mendelian randomization approach, using genetic variants associated with statin use as instrumental variables. METHOD: Information on single nucleotide polymorphisms associated with statin medication was obtained from the FinnGen study, and data on osteoarthritis were sourced from the UK Biobank. The inverse variance weighted method was used as the primary analytical approach for the Mendelian randomization analysis. Sensitivity analyses were conducted to evaluate horizontal pleiotropy and heterogeneity. To examine the genetic relationship between statins and osteoarthritis, linkage disequilibrium score regression-based estimates were used. RESULTS: Mendelian randomization analysis indicated a positive effect of statin use on the treatment of osteoarthritis (odds ratio 0.951, 95% confidence interval 0.914-0.99, p < 0.05). This conclusion was supported by various Mendelian randomization methods. Sensitivity analyses revealed no significant directional pleiotropy or influential single nucleotide polymorphisms that could compromise the overall causal inference. Linkage disequilibrium score regression-based estimates suggested a modest genetic correlation between statin use and osteoarthritis (Rg = 0.098, Se = 0.034, p < 0.05), thus reinforcing the robustness of the Mendelian randomization analysis. CONCLUSION: Statins reduce the risk of osteoarthritis, aligning with the results of observational studies. Further research is essential to validate these results and explore the underlying mechanisms in detail.

A systematic review of the drug-drug interaction between Statins and Quinolones.

BACKGROUND: Statins are widely used in cardiovascular disease (CVD) as a common lipid-lowering drug, while quinolones are widely used for the treatment of infectious diseases. It is common to see CVD in combination with infectious diseases, therefore it is often the case that statins and quinolones are used in combination. Data suggest combinations of statin and quinolone may be associated with potentially life-threatening myopathy, rhabdomyolysis and acute hepatitis. This systematic review aims to characterize data regarding patients affected by the statin-quinolone interaction. METHODS: The purpose of this systematic review was to collect and evaluate the evidence surrounding statin-quinolone drug interactions and to discuss related risk mitigation strategies. The following databases were searched: PubMed (Medline), Embase, Scopus, and Cochrane Library. The systematic electronic literature search was conducted with the following search terms. In this study, three types of search terms were used: statins-related terms, quinolones-related terms, and drug interactions-related terms. RESULTS: There were 16 case reports that met the criteria for qualitative analysis. Patients were involved in the following adverse reactions: rhabdomyolysis (n = 12), acute hepatitis (n = 1), muscle weakness (n = 1), hip tendinopathy (n = 1), or myopathy (n = 1). In the included literature, patients vary in the dose and type of statins they take, including simvastatin (n = 10) at a dose range of 20-80 mg/d and atorvastatin (n = 4) at a dose of 80 mg/d. There were 2 patients with unspecified statin doses, separately using simvastatin and atorvastatin. The quinolones in combination were ciprofloxacin (n = 9) at a dose range of 800-1500 mg/d, levofloxacin (n = 6) at a dose range of 250-1000 mg/d, and norfloxacin (n = 1) in an unspecified dose range. 81% of the case patients were over 60 years of age, and about 1/3 had kidney-related diseases such as diabetic nephropathy, post-transplantation, and severe glomerulonephritis. Nearly two-third of the patients were on concomitant cytochrome P450 3A4 (CYP3A4) inhibitors, P-glycoprotein (P-gp) inhibitors, or organic anion transporting polypeptide 1B1 (OATP1B1) inhibitors. CONCLUSION: Patients treated with statin-quinolone combination should be monitored more closely for changes in aspartate aminotransferase or creatine kinase (CK) levels, and muscle symptoms, especially in patients with ciprofloxacin or levofloxacin, with simvastatin and high-dose atorvastatin, over 60 years of age, with kidney-related diseases, and on concomitant CYP3A4 inhibitors.

Statins for the Primary Prevention of Anthracycline Cardiotoxicity: A Comprehensive Review.

PURPOSE OF REVIEW: The aim of this review is two-fold: (1) To examine the mechanisms by which statins may protect from anthracycline-induced cardiotoxicity and (2) To provide a comprehensive overview of the existing clinical literature investigating the role of statins for the primary prevention of anthracycline-induced cardiotoxicity. RECENT FINDINGS: The underlying cardioprotective mechanisms associated with statins have not been fully elucidated. Key mechanisms related to the inhibition of Ras homologous (Rho) GTPases have been proposed. Data from observational studies has supported the beneficial role of statins for the primary prevention of anthracycline-induced cardiotoxicity. Recently, several randomized controlled trials investigating the role of statins for the primary prevention of anthracycline-induced cardiotoxicity have produced contrasting results. Statins have been associated with a lower risk of cardiac dysfunction in cancer patients receiving anthracyclines. Further investigation with larger randomized control trials and longer follow-up periods are needed to better evaluate the long-term role of statin therapy and identify the subgroups who benefit most from statin therapy.

Prevalence of Tendon Rupture and Tendinopathies Among Patients with Atherosclerotic Cardiovascular Disease Derived From United States Administrative Claims Data.

INTRODUCTION: The prevalence of tendon rupture and tendinopathies (TRT) has not been determined in a large population of patients with atherosclerotic cardiovascular disease (ASCVD). We investigated TRT prevalence among patients with ASCVD and in the general population, using data from the Symphony Health Integrated Dataverse, a large US medical and pharmacy claims database. METHODS: This retrospective, observational study included patients aged ≥ 19 years from the claims database during the identification period (January 2019 to December 2020) and 12 months of continuous enrollment. The primary outcome was evidence of TRT in the 12 months following the index date (first ASCVD diagnosis in the ASCVD cohort; first claim in the claims database in the overall population). Diagnostic codes (ICD-10 and/or CPT) were used to define ASCVD and TRT diagnosis. RESULTS: The ASCVD cohort and overall population included 5,589,273 and 61,715,843 patients, respectively. In the ASCVD cohort, use of medications with a potential or known association with TRT was identified in 67.9% (statins), 17.7% (corticosteroids), and 16.7% (fluoroquinolones) of patients. Bempedoic acid use was reported in 1556 (< 0.1%) patients. TRT prevalence during 12-month follow-up was 3.4% (ASCVD cohort) and 1.9% (overall population). Among patients with ASCVD, 83.5% experienced TRT in only one region of the body. Factors most associated with TRT in the ASCVD cohort were increasing age, most notably in those aged 45-|64 years (odds ratio [OR] 2.19; 95% confidence interval [CI] 2.07-2.32), obesity (OR 1.51; 95% CI 1.50-1.53), and rheumatoid arthritis (OR 1.47; 95% CI 1.45-1.79). Use of statins or bempedoic acid was not associated with increased TRT risk. CONCLUSION: Patients with ASCVD may have greater risk of TRT than the general population, which may be driven by an increased prevalence of comorbidities and use of medications with a potential or known association with TRT.

Patients with atherosclerosis, the main cause of heart attacks, strokes, and peripheral vascular disease, typically require several drugs to control the disease. Some of the drugs used to treat atherosclerosis have been linked to a higher occurrence of tendon tears (or ruptures) or swelling/inflammation of the tendons (tendinopathies). However, there may be other factors present in these patients that increase the risk of tendon injuries that are not related to these drugs. This study used the medical records of over 5.5 million patients with atherosclerosis and over 63 million patients reflecting the general population in the United States to determine the prevalence of tendon injury. Additionally, the researchers looked at other factors that might be related to a higher risk of tendon injury in each group. Over a 12-month period, tendon injuries occurred in 3.4% of patients with atherosclerosis and 1.8% of patients in the general population. In patients with atherosclerosis, factors such as being obese, older (45­64 years), or having rheumatoid arthritis were also linked to an increased risk of tendon injuries. There was no association seen between statin or bempedoic acid use and tendon injuries. These results may help healthcare providers to determine the underlying risk of tendon injuries and guide treatment of this patient population.