Examining lack of referrals to heart valve specialists as mechanisms of potential underutilization of aortic valve replacement.

BACKGROUND: Recent studies suggest that aortic valve replacement (AVR) remains underutilized. AIMS: Investigate the potential role of non-referral to heart valve specialists (HVS) on AVR utilization. METHODS: Patients with severe aortic stenosis (AS) between 2015 and 2018, who met class I indication for intervention, were identified. Baseline data and process-related parameters were collected to analyze referral predictors and evaluate outcomes. RESULTS: Among 981 patients meeting criteria AVR, 790 patients (80.5%) were assessed by HVS within six months of index TTE. Factors linked to reduced referral included increasing age (OR: 0.95; 95% CI: 0.94-0.97; P < .001), unmarried status (OR: 0.59; 95% CI: 0.43-0.83; P = .002) and inpatient TTE (OR: 0.27; 95% CI: 0.19-0.38; P < .001). Conversely, higher hematocrit (OR: 1.13; 95% CI: 1.09-1.16; P < .001) and eGFR (OR: 1.01; 95% CI: 1.00-1.02; P = .003), mean aortic valve gradient (OR: 1.03; 95% CI: 1.01-1.04; P < .001) and preserved LVEF (OR: 1.59; 95% CI: 1.02-2.48; P = .04), were associated with increased referral likelihood. Moreover, patients assessed by HVS referral as a time-dependent covariate had a significantly lower two-year mortality risk than those who were not (aHR: 0.30; 95% CI: 0.23-0.39; P < .001). CONCLUSION: A substantial proportion of severe AS patients meeting indications for AVR are not evaluated by HVS and experience markedly increased mortality. Further research is warranted to assess the efficacy of care delivery mechanisms, such as e-consults, and telemedicine, to improve access to HVS expertise.

EXIST: EXamining rIsk of excesS adiposiTy-Machine learning to predict obesity-related complications.

Background: Obesity is associated with an increased risk of multiple conditions, ranging from heart disease to cancer. However, there are few predictive models for these outcomes that have been developed specifically for people with overweight/obesity. Objective: To develop predictive models for obesity-related complications in patients with overweight and obesity. Methods: Electronic health record data of adults with body mass index 25-80 kg/m2 treated in primary care practices between 2000 and 2019 were utilized to develop and evaluate predictive models for nine long-term clinical outcomes using a) Lasso-Cox models and b) a machine-learning method random survival forests (RSF). Models were trained on a training dataset and evaluated on a test dataset over 100 replicates. Parsimonious models of <10 variables were also developed using Lasso-Cox. Results: Over a median follow-up of 5.6 years, study outcome incidence in the cohort of 433,272 patients ranged from 1.8% for knee replacement to 11.7% for atherosclerotic cardiovascular disease. Harrell C-index averaged over replicates ranged from 0.702 for liver outcomes to 0.896 for death for RSF, and from 0.694 for liver outcomes to 0.891 for death for Lasso-Cox. The Harrell C-index for parsimonious models ranged from 0.675 for liver outcomes to 0.850 for knee replacement. Conclusions: Predictive modeling can identify patients at high risk of obesity-related complications. Interpretable Cox models achieve results close to those of machine learning methods and could be helpful for population health management and clinical treatment decisions.

Outcomes in patients with cardiometabolic disease who develop hyperkalemia while treated with a renin-angiotensin-aldosterone system inhibitor.

BACKGROUND: Many patients with indications for renin-angiotensin-aldosterone system inhibitor (RAASi) therapy are not receiving these medications. Concern about hyperkalemia is thought to contribute to this lack of evidence-based therapy. METHODS: A retrospective cohort study included adult patients in primary care practices affiliated with an integrated health care delivery system treated with RAASi between 2000 and 2019 for any of the following indications: (a) coronary artery disease (CAD); (b) heart failure (HF) with a left ventricle ejection fraction ≤ 40%; (c) diabetes mellitus (DM) with proteinuria; or (d) chronic kidney disease (CKD) with proteinuria. Relationship between hyperkalemia (K > 5.0 mEg/L) over the first 12 months of follow-up and a composite end point of cardiovascular events, renal dysfunction, and all-cause mortality was evaluated. RESULTS: Among 82,732 study patients, 7,727 (9.34%) developed hyperkalemia. Patients with hyperkalemia were older (69.0 vs 64.6) and more likely to have CAD (57.8 vs 53.7%), CKD (57.3 vs 51.1%), HF (19.3 vs 9.7%), and DM (45.3 vs 33.3%) (P < .001 for all). Five-year cumulative risk of the primary outcome was higher in patients who did (63.9%; 95% CI: 62.8%-65.1%) versus did not (37.2%; 95% CI: 36.8%-37.6%) develop hyperkalemia. Five-year cumulative risk of ED visit or hospitalization for hyperkalemia was 15.6% (14.7%-16.6%) for patients with versus 2.7% (95% CI: 2.6-2.9) for patients without hyperkalemia, rising to 25.9% (95% CI: 22.4-29.9) for patients with severe (K > 6.0 mEq/dL) hyperkalemia. Patients who experienced hyperkalemia were more likely (34.4%) than patients who did not (29.2%) to deintensify RAASi therapy (P < .001). Five-year cumulative risk of the primary outcome was higher in patients who lowered RAASi dose (50.4%; 95% CI: 48.5%-52.4%) or stopped RAASi therapy completely (49.3%; 95% CI: 48.5%-50.1%), compared to patients who continued RAASi therapy (36.1%; 95% CI: 25.7-36.5). Similar findings were observed in multivariable analyses and for individual components of the primary outcome. CONCLUSIONS: Hyperkalemia is a common complication of RAASi therapy and is associated with an increased risk of multiple adverse outcomes. Patients who have their RAASi medications deintensified after a hyperkalemic event have higher incidence of cardiovascular events, renal dysfunction and death.

COVID-19 outcomes in patients taking cardioprotective medications.

INTRODUCTION: The coronavirus disease 2019 (COVID-19) caused a worldwide pandemic and has led to over five million deaths. Many cardiovascular risk factors (e.g. obesity or diabetes) are associated with an increased risk of adverse outcomes in COVID-19. On the other hand, it has been suggested that medications used to treat cardiometabolic conditions may have protective effects for patients with COVID-19. OBJECTIVES: To determine whether patients taking four classes of cardioprotective medications-aspirin, metformin, renin angiotensin aldosterone system inhibitors (RAASi) and statins-have a lower risk of adverse outcomes of COVID-19. METHODS: We conducted a retrospective cohort study of primary care patients at a large integrated healthcare delivery system who had a positive COVID-19 test between March 2020 and March 2021. We compared outcomes of patients who were taking one of the study medications at the time of the COVID-19 test to patients who took a medication from the same class in the past (to minimize bias by indication). The following outcomes were compared: a) hospitalization; b) ICU admission; c) intubation; and d) death. Multivariable analysis was used to adjust for patient demographics and comorbidities. RESULTS: Among 13,585 study patients, 1,970 (14.5%) were hospitalized; 763 (5.6%) were admitted to an ICU; 373 (2.8%) were intubated and 720 (5.3%) died. In bivariate analyses, patients taking metformin, RAASi and statins had lower risk of hospitalization, ICU admission and death. However, in multivariable analysis, only the lower risk of death remained statistically significant. Patients taking aspirin had a significantly higher risk of hospitalization in both bivariate and multivariable analyses. CONCLUSIONS: Cardioprotective medications were not associated with a consistent benefit in COVID-19. As vaccination and effective treatments are not yet universally accessible worldwide, research should continue to determine whether affordable and widely available medications could be utilized to decrease the risks of this disease.

Trends in Utilization of Aortic Valve Replacement for Severe Aortic Stenosis.

BACKGROUND: Despite the rapid growth of aortic valve replacement (AVR) for aortic stenosis (AS), limited data suggest symptomatic severe AS remains undertreated. OBJECTIVES: This study sought to investigate temporal trends in AVR utilization among patients with a clinical indication for AVR. METHODS: Patients with severe AS (aortic valve area <1 cm2) on transthoracic echocardiograms from 2000 to 2017 at 2 large academic medical centers were classified based on clinical guideline indications for AVR and divided into 4 AS subgroups: high gradient with normal left ventricular ejection fraction (LVEF) (HG-NEF), high gradient with low LVEF (HG-LEF), low gradient with normal LVEF (LG-NEF), and low gradient with low LVEF (LG-LEF). Utilization of AVR was examined and predictors identified. RESULTS: Of 10,795 patients, 6,150 (57%) had an indication or potential indication for AVR, of whom 2,977 (48%) received AVR. The frequency of AVR varied by AS subtype with LG groups less likely to receive an AVR (HG-NEF: 70%, HG-LEF: 53%, LG-NEF: 32%, LG-LEF: 38%, P < 0.001). AVR volumes grew over the 18-year study period but were paralleled by comparable growth in the number of patients with an indication for AVR. In patients with a Class I indication, younger age, coronary artery disease, smoking history, higher hematocrit, outpatient index transthoracic echocardiogram, and LVEF ≥0.5 were independently associated with an increased likelihood of receiving an AVR. AVR was associated with improved survival in each AS-subgroup. CONCLUSIONS: Over an 18-year period, the proportion of patients with an indication for AVR who did not receive AVR has remained substantial despite the rapid growth of AVR volumes.

Reasons for discontinuation of lipid-lowering medications in patients with chronic kidney disease.

BACKGROUND/AIMS: Many patients with chronic kidney disease (CKD) do not receive lipid-lowering therapy despite their high cardiovascular risk. The reasons for this are unknown. METHODS: We have conducted a retrospective cohort study of discontinuation of lipid-lowering drugs in patients with CKD stage 3 and higher treated in practices affiliated with two academic medical centers between 2000 and 2010. Information on medication discontinuation and its reasons was obtained from electronic medical records, including natural language processing of electronic notes using previously validated software. RESULTS: Out of 14,034 patients in the study cohort, 10,072 (71.8%) stopped their lipid-lowering drugs at least once, and 2,444 (17.4%) stopped them for at least 1 month. Patients who had a comorbidity associated with higher cardiovascular risk were less likely to stop lipid-lowering drugs. Insurance request was the most common explicitly documented reason for discontinuation, and adverse reactions were the most common reason for long-term discontinuation. In a multivariable analysis, patients were more likely to stop a lipid-lowering drug because of an insurance request if they had government insurance and they were also more likely to stop a lipid-lowering drug because of adverse reactions if they had a history of multiple adverse reactions to other medications. There was no significant relationship between CKD stage and the reason for discontinuation of lipid-lowering drugs. CONCLUSIONS: Patients with CKD frequently stop lipid-lowering drugs. Insurance requests and adverse reactions are common reasons for the discontinuation. Further research is needed to ensure appropriate lipid-lowering therapy for these individuals at high cardiovascular risk.