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Journal of Endocrinology & Metabolism

Original Article

Volume 14, Number 5, October 2024, pages 221-225

The Cardiometabolic Clinic: Bridging Gaps in Care

Cardiometabolic diseases are the leading cause of death in the United States and are associated with a significantly lower quality of life [1]. Cardiometabolic diseases are a collection of pathologies that include cardiovascular disease, insulin resistance, central adiposity, hypertension, and hyperlipidemia. New evidence suggests that kidney function is intimately involved in this disease spectrum as well [2]. These patients are at a very high risk for myocardial infarction, stroke, and overall mortality [3]. Although there are strong, evidence-based treatment protocols for the constellation of conditions, many of these patients still are not on optimal medication regimens [4].

One reason for suboptimal medication regimens is the increasing degree of specialization within medicine resulting in care silos. These silos cause gaps where care is frequently missed [5]. The concept of a multidisciplinary cardiometabolic clinic was created for better subspecialty integration and to fill these gaps [5]. Cardiometabolic clinics can be variable in composition, but typically consist of cardiometabolic experts (typically an endocrinologist, cardiologist, or primary care provider), nurse specialists, behavioral psychologists, nutritionists, education specialists, and pharmacists [5]. Several research studies have shown success, with one retrospective study showing improved adherence to goal-directed medical therapy by 17-fold [6], and another showing a 10.8% reduction in A1c and a 2.7% reduction in body mass index (BMI) [7].

Our academic medical center’s Division of Endocrinology, Diabetes, and Osteoporosis established a cardiometabolic clinic in September 2021 in collaboration with the Division of Cardiology. The cardiometabolic clinic consisted of an endocrinologist and a specialty pharmacist focused on addressing cardiometabolic disease with an emphasis on medication optimization. Patients in the cardiometabolic clinic were primarily referred from cardiology. This study’s purpose was to describe the cardiometabolic clinic’s impact on medication regimens and health outcomes including BMI, hemoglobin A1c, blood pressure, and low-density lipoprotein (LDL).

This retrospective study of electronic health record data (Epic) was conducted at the University of Vermont Medical Center (UVMMC). UVMMC, located in Burlington, Vermont, serves over 1 million patients annually in Vermont and northern New York. All patients who attended the cardiometabolic clinic were included if they had at least two visits 6 - 18 months apart between September 1, 2021, and January 1, 2024. A control group was selected from four UVMMC Primary Care Clinics in the same county as the endocrinology clinic. Eligible controls included a diagnosis of diabetes, diagnosis of heart failure and/or coronary artery disease, and attendance at two primary care visits 6 - 18 months apart between September 1, 2021, and January 1, 2024. Control patients were matched in age and gender.

Baseline and initial visit data included date-of-birth, sex, race, ethnicity, insurance, smoking history, weight, height, BMI, and severity of heart failure and chronic kidney disease (CKD). Laboratory values included A1c, estimated glomerular filtration rate (eGFR), total cholesterol, triglycerides, LDL, and urine microalbumin. Systolic and diastolic blood pressure were also recorded. Medications for diabetes, cholesterol, and blood pressure were noted. The medical record was searched for medication changes or interventions that occurred at the initial visit. Data at the follow-up visit included the same information as baseline in addition to changes in medical history. Study data were collected and managed using REDCap electronic data capture tools hosted at the University of Vermont [8]. This study was approved as exempt research by the University of Vermont Committees on Human Research (STUDY00002901) and was conducted in compliance with the ethical standards of the responsible institution on human subjects as well as with the Helsinki Declaration.

The analysis of this study was primarily descriptive and included cardiometabolic medication regimen optimization measured by adherence to the American Diabetes Association (ADA) 2021 guidelines, and control of metabolic markers (BMI, A1c, LDL) on follow-up 6 - 18 months later. Additionally, comparisons between cardiometabolic clinic patients and controls were analyzed. Categorical variables were analyzed using Fisher’s exact test or Chi-square, and continuous variables were analyzed using Wilcoxon rank sum. Data were analyzed using Stata 18 (Stata Corporation, College Station, TX). P < 0.05 was required for statistical significance. As this retrospective project was largely exploratory, we did not correct for multiple comparisons.

A total of 65 patients attended the cardiometabolic clinic with at least two visits during our study timeframe. Matched controls were similar to cardiometabolic patients at baseline with notable differences between the groups for CKD history (cardiometabolic: 38% vs. control: 17%, P = 0.01) and mean diastolic blood pressure (cardiometabolic: 67.5 mm Hg vs. control: 72.2 mm Hg, P = 0.01) (Table 1).

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Table 1. Baseline Patient Characteristics in the Cardiometabolic Clinic Patients and Controls

At the initial cardiometabolic clinic visit, there were a high number of changes to medication regimens, with 51 patients (78.5%) started on a new medication and 24 patients (40%) who had medications discontinued (Table 2). Thirty-three patients (51%) were started on glucagon-like peptide-1 (GLP-1) medications, and 16 patients (24.6%) were started on sodium-glucose cotransporter-2 (SGLT2) inhibitors (Table 3). Follow-up visit 6 - 18 months later showed significantly different medication regimens between the two groups, with more patients prescribed GLP1 medications in the cardiometabolic clinic versus controls (63% vs. 24.6%, P < 0.001), and more SGLT2 inhibitor prescriptions in the cardiometabolic clinic versus controls (47.7% vs. 10.8%, P < 0.001) (Table 4). Notably there were no statistically significant differences in prescriptions of other cardiometabolic medications, including statins, angiotensin-converting-enzyme (ACE) inhibitors, angiotensin II receptor blockers (ARB), or angiotensin receptor/neprilysin inhibitor (ARNI).

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Table 2. Overall Medication Changes at an Initial Visit to the Cardiometabolic Clinic (N = 65)a

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Table 3. Specific Medication Changes at an Initial Visit to the Cardiometabolic Clinic (N = 65)a

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Table 4. Follow-Up Diabetes Medication Regimens (N = 65 per Group)

At the follow-up visit, there was a larger reduction in BMI of the cardiometabolic clinic patients compared to controls (-2.8 kg/m² vs. -0.5 kg/m², P < 0.001), and a larger reduction in A1c in cardiometabolic clinic patients compared to controls (-0.9% vs. -0.4%, P = 0.0155) (Table 5). There were no statistically significant differences in eGFR, LDL, or blood pressure between groups.

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Table 5. Follow-Up Visit Diabetes Medication Regimen (N = 65 per Group)

Cardiometabolic syndrome is common in the United States, and data suggest most of these patients are undertreated [4]. In our study, the cardiometabolic clinic was associated with statistically significant improvement in goal-directed medication prescriptions, especially GLP-1s and SGLT2 inhibitors. In addition to showing increased rates of prescriptions for these newer evidence-based agents, the study also showed a significant number of medication discontinuations in the cardiometabolic group, which represented a reduction of potentially harmful older medications, including insulin, sulfonylureas, and thiazolidinediones. The study also showed improved weight loss and A1c compared to primary care controls over 6 months. This finding cannot be explained by severity of disease in the cardiometabolic patients, as controls had equivalent disease burden, and the same medications were indicated. Notably, the changes in other goal-directed medical treatments (statins, ACE/ARB/ARNI), as well as LDL, eGFR, and blood pressure were not statistically significant.

The outcomes from poorly treated disease can be devastating, and the low prescription rates of medications known to reduce these risks underscore the need for urgent intervention. There are many reasons why patients are not on these medicines, including insurance coverage, access, lack of provider knowledge, and competing priorities in visits. While policies and prescribing rationales will largely be the same for providers regardless of clinic type, a focused cardiometabolic clinic creates the best possible circumstances for successful interventions. This is in part due to the specific expertise of cardiometabolic providers and dedicated ancillary staff in optimizing their documentation to increase the speed and rates of insurance reimbursement. Our data show the striking changes that can be made to medications in a brief time including initiation, discontinuation, and dose changes. Our study adds to the current body of evidence supporting cardiometabolic clinics. Other studies have shown similar results with improvement in both goal-directed medication regimens, as well as metabolic control [4, 7, 9-11]. Our clinic is similar with a multidisciplinary approach, with isolated focus on cardiometabolic disease and an emphasis on goal-directed medical therapy. The study differs because our team is smaller with only an endocrinologist and pharmacist working with the cardiology department.

There are limitations to the study. Given that it was a retrospective chart review, it was vulnerable to inaccuracies in charting information. Additionally, patients in the intervention group were not randomized, and most came directly from cardiology, which introduces biases. This population may have more severe diseases not managed by primary care, potentially more medical contact, and may have better resources to attend subspecialty appointments. The studies per protocol analysis can lead to an optimistic assessment of the clinic’s effectiveness. Lastly, there are limitations to the external validity of the study, as the population was from one health system, was primarily White and had a better A1c compared to the national average. Both a strength and weakness of the study is the degree of similarity between the two study groups. Both groups had statistically similar general demographic information and baseline medications regimens; however, the cardiometabolic group notably had a significantly higher degree of renal dysfunction. This could serve as a limitation to the study as these patients have greater disease burden possibly prompting initiation of more aggressive treatment (although notably there was no FLOW trial data available at the time of the study). Other strengths of the study include relatively rapid changes in BMI; we anticipate even stronger results at 12 months. Additional areas for study in the future could include differences in prescribing patterns (speed of up titration of GLP1s, recognition of true side effects, etc.), as well as counseling regarding medications and potential adverse effects.

This study’s intention is to describe the impact of a cardiometabolic clinic on health outcomes and adherence to goal-directed care for patients with cardiometabolic syndrome. We found that patients had rapid improvement in medication regimens, as well as A1c and BMI. This study suggests that cardiometabolic clinics could play an important role in the treatment of this high-risk group.

Acknowledgments

Kayla Davis is a pharmacist who contributed to planning and execution of the cardiometabolic clinic.

Financial Disclosure

This research did not receive any specific grant from any funding agency in the public, commercial or not-for-profit sector.

Conflict of Interest

No disclosures are necessary from Jacob Gabbay, Kaitlyn Barrett, Juvena Hitt, or Amanda Kennedy. Dr. Gilbert works as a consultant for Novo Nordisk.

Informed Consent

This study was approved as exempt research by the University of Vermont Committees on Human Research (STUDY00002901).

Author Contributions

Jacob Gabbay contributed to study design, data collection, data analysis, and manuscript production. Amanda G. Kennedy, Juvena Hitt, Matthew Gilbert and Katilin Barrett helped with study design, data analysis and manuscript production. Kaitlin Barrett was the lead faculty mentor.

Data Availability

Some or all datasets generated and/or analyzed during the current study are not publicly available but are available from the corresponding author upon reasonable request.

Abbreviations

BMI: body mass index; LDL: low-density lipoprotein; GLP: glucagon like peptide; SGLT2: sodium glucose cotransporter; UVMMC: University of Vermont Medical Center; CKD: chronic kidney disease; eGFR: estimated glomerular filtration rate; ADA: American Diabetes Association; ACE: angiotensin-converting-enzyme; ARB: angiotensin II receptor blockers; ARNI: angiotensin receptor/neprilysin inhibitor; SD: standard deviation; HFrEF: heart failure with reduced ejection fraction; HFmEF: heart failure with mid-range ejection fraction; HFpEF: heart failure with preserved ejection

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