Citations

Abstract Aims Cardiotoxicity is a serious side effect of anthracycline treatment, most commonly manifesting as a reduction in left ventricular ejection fraction (EF). Early recognition and treatment have been advocated, but robust, convenient, and cost-effective alternatives to cardiac imaging are missing. Recent developments in artificial intelligence (AI) techniques applied to electrocardiograms (ECGs) may fill this gap, but no study so far has demonstrated its merit for the detection of an abnormal EF after anthracycline therapy. Methods and results Single centre consecutive cohort study of all breast cancer patients with ECG and transthoracic echocardiography (TTE) evaluation before and after (neo)adjuvant anthracycline chemotherapy. Patients with HER2-directed therapy, metastatic disease, second primary malignancy, or pre-existing cardiovascular disease were excluded from the analyses as were patients with EF decline for reasons other than anthracycline-induced cardiotoxicity. Primary readout was the diagnostic performance of AI-ECG by area under the curve (AUC) for EFs < 50%. Of 989 consecutive female breast cancer patients, 22 developed a decline in EF attributed to anthracycline therapy over a follow-up time of 9.8 ± 4.2 years. After exclusion of patients who did not have ECGs within 90 days of a TTE, 20 cases and 683 controls remained. The AI-ECG model detected an EF < 50% and ≤ 35% after anthracycline therapy with an AUC of 0.93 and 0.94, respectively. Conclusion These data support the use of AI-ECG for cardiotoxicity screening after anthracycline-based chemotherapy. This technology could serve as a gatekeeper to more costly cardiac imaging and could enable patients to monitor themselves over long periods of time.

Background: Multimorbidity is common in atrial fibrillation (AF), particularly among older patients who generally have multiple cardiovascular and non-cardiovascular chronic conditions. However, less is known about the accumulation of chronic conditions in younger patients with AF. Methods: Patients aged <65 with incident AF from 2013-2019 from a 27-county region in the Midwest (N=4907) were matched 1:1 on age (±5 years) and sex to referents from the same community. The index date for the matched pair was the date of first diagnosis of AF. Diagnosis of 20 other chronic conditions was ascertained from 3 years prior to index through 12/31/2022. Mean cumulative function curves were used to visualize the accumulation of conditions; Andersen-Gill models estimated associations between AF/referent status and accumulation of conditions. Results: The mean age was 55 years for both patients with AF and matched referents; 71% were male. In the 3 years leading up to AF diagnosis, only 4% of patients with AF had no additional chronic conditions and 69% had ≥3 chronic conditions. In contrast, 35% of referents had 0 and 32% had ≥3 chronic conditions. The accumulation of chronic conditions was accelerated in patients with AF compared to referents prior to AF diagnosis/index (Figure). After index, patients with AF had increased accumulation of chronic conditions (HR (95% CI): 1.93 (1.71-2.20), 1.82 (1.62-2.05), 1.68 (1.55-1.83), and 1.53 (1.44-1.64) for ages <50, 50-54, 55-59, and 60-64 years, respectively). After 1 year, the differences were attenuated in all age groups with no difference observed between patients with AF and referents in the oldest age group (1.26 (1.08-1.46), 1.28 (1.11-1.47), 1.13 (1.02-1.24), and 1.05 (0.97-1.13) for ages <50, 50-54, 55-59, and 60-64 years). Conclusion: Patients <65 years with AF have an increased accumulation of chronic conditions compared to those without AF, in particular prior to their AF diagnosis and within the first year after AF diagnosis.

AbstractThe discrimination of ventricular tachycardia (VT) versus supraventricular wide complex tachycardia (SWCT) via 12‐lead electrocardiogram (ECG) is crucial for achieving appropriate, high‐quality, and cost‐effective care in patients presenting with wide QRS complex tachycardia (WCT). Decades of rigorous research have brought forth an expanding arsenal of applicable manual algorithm methods for differentiating WCTs. However, these algorithms are limited by their heavy reliance on the ECG interpreter for their proper execution. Herein, we introduce the Mayo Clinic ventricular tachycardia calculator (MC‐VTcalc) as a novel generalizable, accurate, and easy‐to‐use means to estimate VT probability independent of ECG interpreter competency. The MC‐VTcalc, through the use of web‐based and mobile device platforms, only requires the entry of computerized measurements (i.e., QRS duration, QRS axis, and T‐wave axis) that are routinely displayed on standard 12‐lead ECG recordings.

Introduction: Using a digital process that leverages electronic health records (EHRs) can ease many of the challenges presented by the traditional enrollment process for clinical trials. We tested if automated batch enrollment using a technology-enabled subject recruitment system (TESRS) enhances recruitment while preserving representation of research subjects for the study population in our study setting. Methods: An ongoing community-based prospective adult cohort study was used to randomize 600 subjects who were eligible by age and residential address to TESRS (n = 300) and standard mailing method (n = 300), respectively, for 3 months. Then, TESRS was initiated and included automatic identification of patients’ preference for being contacted (online patient portal vs postal mail) from EHRs and automatic sending out of invitation letters followed by completion of a short online survey for checking eligibility and the digital consent process if eligible. We compared (1) median time to consent from invitation sent out per subject and total subjects recruited after a 3-month recruitment period, (2) the estimated study staff’s time, and (3) representation of sociodemographic characteristics (e.g., age, sex, race, SES measured by HOUSES index, and rural residence) between subjects recruited via TESRS and those via traditional mailing methods. Results: Median age of randomized subjects (n = 600) was 63 years with 52.0% female and 89.2% non-Hispanic White. Over a 3-month period, results showed consent rate via TESRS was 13% (39/297) similar to 11% (31/295) via standard mailing. However, recruitment was significantly faster with the TESRS approach (median 7 vs 26 days) given the study staff’s effort. Study staff’s time saved by using TESRS compared to standard mailing approach was estimated at 40 min per subject (equivalent to 200 h for 300 subjects). No significant differences in characteristics of research subjects from the study population were found. Conclusion: Our study demonstrated the utility of TESRS as a subject recruitment digital technology which significantly enhanced the recruitment effort while reducing the study staff burden of recruitment while maintaining the consistency of characteristics of recruited subjects. The strategy and support for implementing and testing TESRS in other study settings should be considered.

Background/aims There has been growing interest in better understanding the potential of observational research methods in medical product evaluation and regulatory decision-making. Previously, we used linked claims and electronic health record data to emulate two ongoing randomized controlled trials, characterizing the populations and results of each randomized controlled trial prior to publication of its results. Here, our objective was to compare the populations and results from the emulated trials with those of the now-published randomized controlled trials. Methods This study compared participants’ demographic and clinical characteristics and study results between the emulated trials, which used structured data from OptumLabs Data Warehouse, and the published PRONOUNCE and GRADE trials. First, we examined the feasibility of implementing the baseline participant characteristics included in the published PRONOUNCE and GRADE trials’ using real-world data and classified each variable as ascertainable, partially ascertainable, or not ascertainable. Second, we compared the emulated trials and published randomized controlled trials for baseline patient characteristics (concordance determined using standardized mean differences <0.20) and results of the primary and secondary endpoints (concordance determined by direction of effect estimates and statistical significance). Results The PRONOUNCE trial enrolled 544 participants, and the emulated trial included 2226 propensity score-matched participants. In the PRONOUNCE trial publication, one of the 32 baseline participant characteristics was listed as an exclusion criterion on ClinicalTrials.gov but was ultimately not used. Among the remaining 31 characteristics, 9 (29.0%) were ascertainable, 11 (35.5%) were partially ascertainable, and 10 (32.2%) were not ascertainable using structured data from OptumLabs. For one additional variable, the PRONOUNCE trial did not provide sufficient detail to allow its ascertainment. Of the nine variables that were ascertainable, values in the emulated trial and published randomized controlled trial were discordant for 6 (66.7%). The primary endpoint of time from randomization to the first major adverse cardiovascular event and secondary endpoints of nonfatal myocardial infarction and stroke were concordant between the emulated trial and published randomized controlled trial. The GRADE trial enrolled 5047 participants, and the emulated trial included 7540 participants. In the GRADE trial publication, 8 of 34 (23.5%) baseline participant characteristics were ascertainable, 14 (41.2%) were partially ascertainable, and 11 (32.4%) were not ascertainable using structured data from OptumLabs. For one variable, the GRADE trial did not provide sufficient detail to allow for ascertainment. Of the eight variables that were ascertainable, values in the emulated trial and published randomized controlled trial were discordant for 4 (50.0%). The primary endpoint of time to hemoglobin A1c ≥7.0% was mostly concordant between the emulated trial and the published randomized controlled trial. Conclusion Despite challenges, observational methods and real-world data can be leveraged in certain important situations for a more timely evaluation of drug effectiveness and safety in more diverse and representative patient populations.

Abstract Aims Atrial functional mitral regurgitation (AFMR) has been associated with atrial fibrillation (AF) and heart failure with preserved ejection fraction. However, data on incident AFMR are scarce. We aimed to study the incidence, risk factors, and clinical significance of AFMR in AF or sinus rhythm (SR). Methods and results Adults with new diagnosis of AF and adults in SR were identified. Patients with &gt;mild MR at baseline, primary mitral disease, cardiomyopathy, left-sided valve disease, previous cardiac surgery, or with no follow-up echocardiogram were excluded. Diastolic dysfunction (DD) was indicated by ≥2/4 abnormal diastolic function parameters [mitral medial e′, mitral medial E/e′, tricuspid regurgitation velocity, left atrial volume index (LAVI)]. Overall, 1747 patients with AF and 29 623 in SR were included. Incidence rate of &gt;mild AFMR was 2.6 per 100 person-year in new-onset AF and 0.7 per 100 person-year in SR, P &lt; 0.001. AF remained associated with AFMR in a propensity score-matched analysis based on age, sex, and comorbidities between AF and SR [hazard ratio: 3.80 (95% confidence interval 3.04–4.76)]. Independent risk factors associated with incident AFMR were age ≥65 years, female sex, LAVI, and DD in both AF and SR, in addition to rate (vs. rhythm) control in AF. Incident AFMR was independently associated with all-cause death in both groups (both P &lt; 0.001). Conclusions AF conferred a three-fold increase in the risk of incident AFMR. DD, older age, left atrial size, and female sex were independent risk factors in both SR and AF, while rhythm control was protective. AFMR was universally associated with worse mortality.

Background Physiological monitoring systems, like Masimo, used during inpatient hospitalisation, offer a non-invasive approach to capture critical vital signs data. These systems trigger alarms when measurements deviate from preset parameters. However, often non-urgent or potentially false alarms contribute to ‘alarm fatigue,’ a form of sensory overload that can have adverse effects on both patients and healthcare staff. The Joint Commission, in 2021, announced a target to mitigate alarm fatigue-related fatalities through improved alarm management. Yet, no established guidelines are presently available. This study aims to address alarm fatigue at the Mayo Clinic to safeguard patient safety, curb staff burnout and improve the sensitivity of oxygen saturation monitoring to promptly detect emergencies. Methods A quality improvement project was conducted to combat minimise the false alarm burden, with data collected 2 months prior to intervention commencement. The project’s goal was to decrease the total alarm value by 20% from 55%–85% to 35%–75% within 2 months, leveraging quality improvement methodologies. Interventions February to April 2021, we implemented a two-pronged intervention: (1) instituting a protocol to evaluate patients’ continuous monitoring needs and discontinuing it when appropriate, and (2) introducing educational signage for patients and Mayo Clinic staff on monitoring best practices. Results Baseline averages of red alarms (158.6), manual snoozes (37.8) and self-resolves (120.7); the first postintervention phase showed reductions in red alarms (125.5), manual snoozes (17.8) and self-resolves (107.8). Second postintervention phase recorded 138 red alarms, 13 manual snoozes and 125 self-resolves. Baseline comparison demonstrated an average of 16.92% reduction of alarms among both interventions (p value: 0.25). Conclusion Simple interventions like education and communication techniques proved instrumental in lessening the alarm burden for patients and staff. The findings underscore the practical use and efficacy of these methods in any healthcare setting, thus contributing to mitigating the prevalent issue of alarm fatigue.

Introduction Decision aids (DAs) are helpful instruments used to support shared decision making (SDM). Patients with atrial fibrillation (AF) face complex decisions regarding stroke prevention strategies. While a few DAs have been made for AF stroke prevention, an encounter DA (EDA) and patient DA (PDA) have not been created to be used in conjunction with each other before. Design Using iterative user-centered design, we developed 2 DAs for anticoagulation choice and stroke prevention in AF. Prototypes were created, and we elicited feedback from patients and experts via observations of encounters, usability testing, and semistructured interviews. Results User testing was done with 33 experts (in AF and SDM) and 51 patients from 6 institutions. The EDA and PDA underwent 1 and 4 major iterations, respectively. Major differences between the DAs included AF pathophysiology and a preparation to meet with the clinician in the PDA as well as different language throughout. Content areas included personalized stroke risk, differences between anticoagulants, and risks of bleeding. Based on user feedback, developers 1) addressed feelings of isolation with AF, 2) improved navigation options, 3) modified content and flow for users new to AF and those experienced with AF, 4) updated stroke risk pictographs, and 5) added structure to the preparation for decision making in the PDA. Limitations These DAs focus only on anticoagulation for stroke prevention and are online, which may limit participation for those less comfortable with technology. Conclusions Designing complementary DAs for use in tandem or separately is a new method to support SDM between patients and clinicians. Extensive user testing is essential to creating high-quality tools that best meet the needs of those using them. Highlights First-time complementary encounter and patient decision aids have been designed to work together or separately. User feedback led to greater structure and different experiences for patients naïve or experienced with anticoagulants in patient decision aids. Online tools allow for easier dissemination, use in telehealth visits, and updating as new evidence comes out.

Abstract Funding Acknowledgements Type of funding sources: None. Background Atrial functional mitral regurgitation (AFMR) has been associated with atrial fibrillation (AF) and heart failure with preserved ejection fraction. However, data on its incidence, risk factors, and clinical outcomes are scarce. Objective We aimed to study the incidence, risk factors and clinical significance of AFMR, defined as &gt;mild functional MR in the absence of more than mild left ventricle enlargement or dysfunction, in AF and sinus rhythm (SR). Methods Adults with a new diagnosis of AF between 2010–2021 who had a transthoracic echocardiogram (TTE) were identified (n=57,109). Similarly, adults with no diagnosis of AF who had a TTE between 2010–2021 were identified for comparison (n= 364,767). Patients with &gt;mild MR at baseline, primary mitral valve disease, cardiomyopathy, ≥moderate aortic valve disease, current or previous low ejection fraction, enlarged left ventricle, cardiac devices, previous cardiac surgeries, or with no follow up TTE ≥6 months from baseline were excluded. Furthermore, patients with AF had to have a TTE within 1 month of AF diagnosis. The presence of ≥2 of 4 abnormal diastolic function parameters [mitral septal e’ &lt;0.07 m/sec, mitral septal E/e’ &gt;15 in SR and &gt;11 in AF, TR velocity &gt;2.80 m/sec, left atrial volume index &gt;34 ml/m2] was determined. Cox proportional hazards regression was used to determine risk factors associated with incident AFMR and all-cause death. Patients without the event of interest were censored at last follow up. Patients who developed &gt;mild MR of other types (primary or functional ventricular) were censored at that time. Results Overall, 1,747 (median age 67 years; 34% females) patients with AF and 29,623 (median age 59; 51% females) in SR were included. Incident AFMR occurred in 167 patients with AF over median 3.1 (IQR 1.6–5.1) years [incidence rate of 2.6 per 100-person year] and in 780 patients in SR over median 3.1 (IQR 1.5–5.8) years [incidence rate 0.7 per 100-person year] (Figure 1). AF remained associated with AFMR after adjusting to confounding factors [age ≥65, female sex, ≥2 abnormal diastolic function parameters, and low hemoglobin; adjusted HR 3.23 (2.71–3.85)]. Independent risk factors associated with incident AFMR in AF were age ≥65, female sex, persistent AF, and ≥2 abnormal diastolic function parameters, whereas successful rhythm control without recurrence was a protective factor (Figure 2a). Risk factors for AFMR in SR were age ≥65 years, female sex, presence of ≥2 abnormal diastolic function parameters, and low hemoglobin (Figure 2a). Incident AFMR was independently associated with all-cause death in both AF and SR (Figure 2b). Conclusions AF confers more than 3-fold increase in the risk of AFMR. Diastolic dysfunction, older age, and female sex were independent risk factors for incident AFMR in both SR and AF. Paroxysmal AF and successful rhythm control were protective factors against AFMR in AF. AFMR is universally associated with worse mortality.