Montori, Víctor M.

OBJECTIVE To examine whether glucagon-like peptide 1 receptor agonists (GLP-1RA) and sodium–glucose cotransporter 2 inhibitors (SGLT2i) are preferentially initiated among patients with cardiovascular disease, heart failure (HF), or nephropathy, where these drug classes have established benefit, compared with dipeptidyl peptidase 4 inhibitors (DPP-4i), for which corresponding benefits have not been demonstrated. RESEARCH DESIGN AND METHODS We retrospectively analyzed claims of adults with type 2 diabetes included in OptumLabs Data Warehouse, a deidentified database of commercially insured and Medicare Advantage beneficiaries, who first started GLP-1RA, SGLT2i, or DPP-4i therapy between 2016 and 2019. Using multinomial logistic regression, we examined the relative risk ratios (RRR) of starting GLP-1RA and SGLT2i compared with DPP-4i for those with a history of myocardial infarction (MI), cerebrovascular disease, HF, and nephropathy after adjusting for demographic and other clinical factors. RESULTS We identified 75,395 patients who started GLP-1RA, 58,234 who started SGLT2i, and 91,884 who started DPP-4i. Patients with prior MI, cerebrovascular disease, or nephropathy were less likely to start GLP-1RA rather than DPP-4i compared with patients without these conditions (RRR 0.83 [95% CI 0.78–0.88] for MI, RRR 0.77 [0.74–0.81] for cerebrovascular disease, and RRR 0.87 [0.84–0.91] for nephropathy). Patients with HF or nephropathy were less likely to start SGLT2i (RRR 0.83 [0.80–0.87] for HF and RRR 0.57 [0.55–0.60] for nephropathy). Both medication classes were less likely to be started by non-White and older patients. CONCLUSIONS Patients with cardiovascular disease, HF, and nephropathy, for whom evidence suggests a greater likelihood of benefiting from GLP-1RA and/or SGLT2i therapy, were less likely to start these drugs. Addressing this treatment/benefit paradox, which was most pronounced in non-White and older patients, may help reduce the morbidity associated with these conditions.

Objectives: Patient involvement in the choice of whether to undergo emergency department observation unit (EDOU) admission and cardiac stress testing or follow-up with a physician could increase knowledge, increase satisfaction, and safely decrease resource use. We test this hypothesis in a randomized trial. Methods: We developed and tested Chest Pain Choice, a decision aid that communicates the pre-test probability of an acute coronary syndrome (ACS) within 45 days and makes management options (EDOU admission and stress testing or 24-72 hr follow-up with a physician) explicit to the patient. Patients with a primary complaint of chest pain and no known coronary artery disease who were being considered for EDOU admission were eligible. Patient-clinician pairs were randomized to intervention (decision aid plus risk estimate) or usual care (no decision aid, no risk estimate). We used patient surveys and 30-day phone follow-up to assess the primary outcome (patient knowledge regarding their short-term risk for ACS), patient satisfaction, safety (delayed or missed ACS defined as acute myocardial infarction, ventricular arrhythmia, cardiogenic shock, or cardiac/unknown death), and resource use. Analysis was by intention to treat. Results: The 205 patients had the following characteristics: mean age (SD) 54.7 (11.8), 59% female, 36% history of HTN and 10% history of diabetes. Compared with usual care patients (n=104), patients receiving the decision aid (n=101) less frequently decided to be admitted to the EDOU for cardiac stress testing (58% vs 77%, absolute difference = 19%, 95% CI 6, 31), had a lower rate of stress testing (74% vs 90%, absolute difference = 16%, 95% CI 6, 26), greater knowledge of their exact pre-test probability of ACS (25% vs 1%, absolute difference = 24%, 95% CI 15, 33) and reported greater satisfaction with the decision-making process (strongly agree: 61% vs 40%, absolute difference = 21%, 95% CI 7, 33). There were no cases of delayed or missed ACS in either arm. Conclusion: Use of a decision aid in ED chest pain patients increased knowledge, increased satisfaction, and safely decreased resource use. In an era of health care reform, shared decision-making is a promising approach that may both increase patient engagement and decrease resource use.Funding(This research has received full or partial funding support from the American Heart Association, National Center)

Background: Shared decision-making with decision aids (DA) improves patient knowledge and reduces decisional conflict. The extent to which they do so across sociodemographic subgroups remains unknown. Methods: An encounter-level meta-analysis of five DA randomized trials examined the impact of sociodemographic variables on knowledge transfer and decisional conflict using a generalized linear model stratified by study and adjusted by treatment arm. Results: We analyzed 595 patient-clinician encounters. Significantly higher knowledge transfer with DA occurred in nearly all patient subgroups when compared to usual care (UC). Patients with more formal education tended to have greater knowledge transfer with UC; this was diminished with DA. There was a trend towards improved decisional conflict in all subgroups with the use of DA; overall decisional conflict was low. (see Table) Conclusion: The use of DA compared to UC significantly increases knowledge transfer across diverse subgroups and there is a tendency towards reduced decisional conflict. Differences at baseline, such as knowledge transfer across educational strata, may be mitigated with use of DA. In conclusion, DA are found to be effective across patient subgroups and may represent a novel strategy to lessen disparities.

Objectives: To understand how patients and family members experience dehumanizing or humanizing treatment when in the ICU. Design: Qualitative study included web-based focus groups and open-ended surveys posted to ICU patient/family social media boards. Focus groups were audio recorded and transcribed. Social media responses were collected and organized by stakeholder group. Data underwent qualitative analysis. Setting: Remote focus groups and online surveys. Patients: ICU patient survivors, family members, and ICU teams. Interventions: Not available. Measurements and Main Results: Semi-structured questions and open-ended survey responses. We enrolled 40 patients/family members and 31 ICU team members. Focus groups and surveys revealed three primary themes orienting humanizing/dehumanizing ICU experiences: 1) communication, 2) outcomes, and 3) causes of dehumanization. Dehumanization occurred during “communication” exchanges when ICU team members talked “over” patients, made distressing remarks when patients were present, or failed to inform patients about ICU-related care. “Outcomes” of dehumanization were associated with patient loss of trust in the medical team, loss of motivation to participate in ICU recovery, feeling of distress, guilt, depression, and anxiety. Humanizing behaviors were associated with improved recovery, well-being, and trust. “Perceived causes” of dehumanizing behaviors were linked to patient, ICU team, and healthcare system factors. CONCLUSIONS: Behaviors of ICU clinicians may cause patients and families to feel dehumanized when in the ICU. Negative behaviors are noticed by patients and families, possibly contributing to poor outcomes including mental health, recovery, and lack of trust in ICU teams. Supporting ICU clinicians may enable a more empathic environment and in turn more humanizing clinician-patient encounters.

Introduction: Current risk equations for coronary heart disease (CHD) do not take into account family history or cumulative exposure to LDL-C. We modified CHD risk equations for use in familial hypercholesterolemia (FH) patients and developed a decision aid (DA) for FH to facilitate shared decision making (SDM). Methods: Literature review, evidence synthesis and expert input were used to adapt the 30-year Framingham Risk Score (FRS) and 10-year ACC/AHA pooled cohort equations to calculate the CHD risk in individuals with FH aged 20-39 years and ≥40 years, respectively. Based on published data, estimated risk was multiplied by 2 for family history of early CHD or 3 in the presence of a pathogenic variant. Treatment benefit of lipid lowering was estimated based on the ‘cumulative exposure to LDL-C’ model ( JACC 2012; 60 ) using the following equations: Post-treatment 30-yr risk in those aged 20-39 years = Baseline Risk (FRS) x 0.54 delta LDL-C (mmol/L) Post-treatment 10-yr risk in those aged ≥40 years = Baseline Risk (ACC/AHA Pooled Cohort) x 0.72 delta LDL-C (mmol/L) To convey CHD risk and treatment benefit, we developed a DA using an iterative, patient-centered design process for use in FH encounters. Results: Using the DA, providers can discuss baseline CHD risk estimates, lipid lowering drug (LLD) options and the expected post-treatment risk reduction with FH patients. The estimated % LDL-C reduction for each LLD and the predicted risk reduction per mmol/L of LDL-C lowered were obtained from literature review. Lowering LDL-C by 1 mmol/L (39 mg/dL) was associated with a 28% CHD risk reduction over 10 years and a 46% reduction over 30 years ( Eur Heart J 2017; 38 ). We describe 2 examples of estimating CHD risk and treatment benefit in FH cases in Table 1 . Conclusion: We adapted CHD risk prediction equations to account for family history of CHD and presence of a pathogenic FH variant and designed a DA to convey personalized CHD risk estimates and treatment benefit to facilitate SDM with FH patients.

Objective Shared decision making (SDM) tools can help implement guideline recommendations for patients with atrial fibrillation (AF) considering stroke prevention strategies. We sought to characterize all available SDM tools for this purpose and examine their quality and clinical impact. Methods We searched through multiple bibliographic databases, social media, and an SDM tool repository from inception to May 2020 and contacted authors of identified SDM tools. Eligible tools had to offer information about warfarin and ≥1 direct oral anticoagulant. We extracted tool characteristics, assessed their adherence to the International Patient Decision Aids Standards, and obtained information about their efficacy in promoting SDM. Results We found 14 SDM tools. Most tools provided up-to-date information about the options, but very few included practical considerations (e.g., out-of-pocket cost). Five of these SDM tools, all used by patients prior to the encounter, were tested in trials at high risk of bias and were found to produce small improvements in patient knowledge and reductions in decisional conflict. Conclusion Several SDM tools for stroke prevention in AF are available, but whether they promote high-quality SDM is yet to be known. The implementation of guidelines for SDM in this context requires user-centered development and evaluation of SDM tools that can effectively promote high-quality SDM and improve stroke prevention in patients with AF.