Potential clinical utility of 68Ga-DOTATATE PET/CT for detection and response assessment in cardiac sarcoidosis.

BACKGROUND: Somatostatin receptor is expressed in sarcoid granulomas, and preliminary clinical studies have shown that myocardial sarcoidosis can be identified on somatostatin receptor-targeted PET. We examined the potential clinical use of 68Ga-DOTATATE PET/CT for diagnosis and response assessment in cardiac sarcoidosis compared to 18F-FDG PET/CT. METHODS: Eleven cardiac sarcoidosis patients with 18F-FDG PET/CT were prospectively enrolled for cardiac 68Ga-DOTATATE PET/CT. The two PET/CT studies were interpreted independently and were compared for patient-level and segment-level concordance, as well as for the degree of radiotracer uptake. Follow-up 68Ga-DOTATATE PET/CT was performed in eight patients. RESULTS: Patient-level concordance was 91%: ten patients had multifocal DOTATATE uptake (active cardiac sarcoidosis) and one patient showed diffuse DOTATATE uptake. Segment-level agreement was 77.1% (Kappa 0.53 ± 0.07). The SUVmax-to-blood pool ratio was lower on 68Ga-DOTATATE PET/CT (3.2 ± 0.6 vs. 4.9 ± 1.5, P = 0.006 on paired t test). Follow-up 68Ga-DOTATATE PET/CT showed one case of complete response and one case of partial response, while 18F-FDG PET/CT showed four cases of response, including three with complete response. CONCLUSION: Compared to 18F-FDG PET/CT, 68Ga-DOTATATE PET/CT can identify active cardiac sarcoidosis with high patient-level concordance, but with moderate segment-level concordance, low signal-to-background ratio, and underestimation of treatment response.

Remote Monitoring and Behavioral Economics in Managing Heart Failure in Patients Discharged From the Hospital: A Randomized Clinical Trial.

Importance: Close remote monitoring of patients following discharge for heart failure (HF) may reduce readmissions or death. Objective: To determine whether remote monitoring of diuretic adherence and weight changes with financial incentives reduces hospital readmissions or death following discharge with HF. Design, Setting, and Participants: The Electronic Monitoring of Patients Offers Ways to Enhance Recovery (EMPOWER) study, a 3-hospital pragmatic trial, randomized 552 adults recently discharged with HF to usual care (n = 280) or a compound intervention (n = 272) designed to inform clinicians of diuretic adherence and changes in patient weight. Patients were recruited from May 25, 2016, to April 8, 2019, and followed up for 12 months. Investigators were blinded to assignment but patients were not. Analysis was by intent to treat. Interventions: Participants randomized to the intervention arm received digital scales, electronic pill bottles for diuretic medication, and regret lottery incentives conditional on the previous day's adherence to both medication and weight measurement, with $1.40 expected daily value. Participants' physicians were alerted if participants' weights increased 1.4 kg in 24 hours or 2.3 kg in 72 hours or if diuretic medications were missed for 5 days. Alerts and weights were integrated into the electronic health record. Participants randomized to the control arm received usual care and no further study contact. Main Outcomes and Measures: Time to death or readmission for any cause within 12 months. Results: Of the 552 participants, 290 were men (52.5%); 291 patients (52.7%) were Black, 231 were White (41.8%), and 16 were Hispanic (2.9%); mean (SD) age was 64.5 (11.8) years. The mean (SD) ejection fraction was 43% (18.1%). Each month, approximately 75% of participants were 80% adherent to both medication and weight measurement. There were 423 readmissions and 26 deaths in the control group and 377 readmissions and 23 deaths in the intervention group. There was no significant difference between the 2 groups for the combined outcome of all-cause inpatient readmission or death (unadjusted hazard ratio, 0.91; 95% CI, 0.74-1.13; P = .40) and no significant differences in all-cause inpatient readmission or observation stay or death, all-cause cardiovascular readmission or death, time to first event, and total all-cause deaths. Participants in the intervention group were slightly more likely to spend fewer days in the hospital. Conclusions and Relevance: In this randomized clinical trial, there was no reduction in the combined outcome of readmission or mortality in a year-long intensive remote monitoring program with incentives for patients previously hospitalized for HF. Trial Registration: ClinicalTrials.gov Identifier: NCT02708654.

An Increasing Burden of Disease: Emergency Department Visits Among Patients With Ventricular Assist Devices From 2010 to 2017.

Background With a growing population of patients supported by ventricular assist devices (VADs) and the improvement in survival of this patient population, understanding the healthcare system burden is critical to improving outcomes. Thus, we sought to examine national estimates of VAD-related emergency department (ED) visits and characterize their demographic, clinical, and outcomes profile. Additionally, we tested the hypotheses that resource use increased and mortality improved over time. Methods and Results This retrospective database analysis uses encounter-level data from the 2010 to 2017 Nationwide Emergency Department Sample. The primary outcome was mortality. From 2010 to 2017, >880 million ED visits were evaluated, with 44 042 VAD-related ED visits identified. The annual mean visits were 5505 (SD 4258), but increased 16-fold from 2010 to 2017 (824 versus 13 155). VAD-related ED visits frequently resulted in admission (72%) and/or death (3.0%). Median inflation-adjusted charges were $25 679 (interquartile range, $7450, $63 119) per encounter. The most common primary diagnoses were cardiac (22%), and almost 30% of encounters were because of bleeding, stroke, or device complications. From 2010 to 2017, admission and mortality decreased from 82% to 71% and 3.4% to 2.4%, respectively (P for trends <0.001, both). Conclusions We present the first study using national-level data to characterize the growing ED resource use and financial burden of patients supported by VAD. During the past decade, admission and mortality rates decreased but remain substantial; in 2017 ≈1 in every 40 VAD ED encounters resulted in death, making it critical that clinical decision-making be optimized for patients with VAD to maximize good outcomes.

Using Clinical Trial Data to Estimate the Costs of Behavioral Interventions for Potential Adopters: A Guide for Trialists.

Behavioral interventions involving electronic devices, financial incentives, gamification, and specially trained staff to encourage healthy behaviors are becoming increasingly prevalent and important in health innovation and improvement efforts. Although considerations of cost are key to their wider adoption, cost information is lacking because the resources required cannot be costed using standard administrative billing data. Pragmatic clinical trials that test behavioral interventions are potentially the best and often only source of cost information but rarely incorporate costing studies. This article provides a guide for researchers to help them collect and analyze, during the trial and with little additional effort, the information needed to inform potential adopters of the costs of adopting a behavioral intervention. A key challenge in using trial data is the separation of implementation costs, the costs an adopter would incur, from research costs. Based on experience with 3 randomized clinical trials of behavioral interventions, this article explains how to frame the costing problem, including how to think about costs associated with the control group, and describes methods for collecting data on individual costs: specifications for costing a technology platform that supports the specialized functions required, how to set up a time log to collect data on the time staff spend on implementation, and issues in getting data on device, overhead, and financial incentive costs.

Patient Characteristics Associated With Telemedicine Access for Primary and Specialty Ambulatory Care During the COVID-19 Pandemic.

Importance: The coronavirus disease 2019 (COVID-19) pandemic has required a shift in health care delivery platforms, necessitating a new reliance on telemedicine. Objective: To evaluate whether inequities are present in telemedicine use and video visit use for telemedicine visits during the COVID-19 pandemic. Design, Setting, and Participants: In this cohort study, a retrospective medical record review was conducted from March 16 to May 11, 2020, of all patients scheduled for telemedicine visits in primary care and specialty ambulatory clinics at a large academic health system. Age, race/ethnicity, sex, language, median household income, and insurance type were all identified from the electronic medical record. Main Outcomes and Measures: A successfully completed telemedicine visit and video (vs telephone) visit for a telemedicine encounter. Multivariable models were used to assess the association between sociodemographic factors, including sex, race/ethnicity, socioeconomic status, and language, and the use of telemedicine visits, as well as video use specifically. Results: A total of 148 402 unique patients (86 055 women [58.0%]; mean [SD] age, 56.5 [17.7] years) had scheduled telemedicine visits during the study period; 80 780 patients (54.4%) completed visits. Of 78 539 patients with completed visits in which visit modality was specified, 35 824 (45.6%) were conducted via video, whereas 24 025 (56.9%) had a telephone visit. In multivariable models, older age (adjusted odds ratio [aOR], 0.85 [95% CI, 0.83-0.88] for those aged 55-64 years; aOR, 0.75 [95% CI, 0.72-0.78] for those aged 65-74 years; aOR, 0.67 [95% CI, 0.64-0.70] for those aged ≥75 years), Asian race (aOR, 0.69 [95% CI, 0.66-0.73]), non-English language as the patient's preferred language (aOR, 0.84 [95% CI, 0.78-0.90]), and Medicaid insurance (aOR, 0.93 [95% CI, 0.89-0.97]) were independently associated with fewer completed telemedicine visits. Older age (aOR, 0.79 [95% CI, 0.76-0.82] for those aged 55-64 years; aOR, 0.78 [95% CI, 0.74-0.83] for those aged 65-74 years; aOR, 0.49 [95% CI, 0.46-0.53] for those aged ≥75 years), female sex (aOR, 0.92 [95% CI, 0.90-0.95]), Black race (aOR, 0.65 [95% CI, 0.62-0.68]), Latinx ethnicity (aOR, 0.90 [95% CI, 0.83-0.97]), and lower household income (aOR, 0.57 [95% CI, 0.54-0.60] for income <$50 000; aOR, 0.89 [95% CI, 0.85-0.92], for $50 000-$100 000) were associated with less video use for telemedicine visits. These results were similar across medical specialties. Conclusions and Relevance: In this cohort study of patients scheduled for primary care and medical specialty ambulatory telemedicine visits at a large academic health system during the early phase of the COVID-19 pandemic, older patients, Asian patients, and non-English-speaking patients had lower rates of telemedicine use, while older patients, female patients, Black, Latinx, and poorer patients had less video use. Inequities in accessing telemedicine care are present, which warrant further attention.

Heart Transplantation: An In-Depth Survival Analysis.

OBJECTIVES: This study aims to understand the complex factors affecting heart transplant survival and to determine the importance of possible sex-specific risk factors. BACKGROUND: Heart transplant allocation is primarily focused on preventing waitlist mortality. To prevent organ wastage, future allocation must balance risk of waitlist mortality with post-transplantation mortality. However, more information regarding risk factors after heart transplantation is needed. METHODS: We included all adults (30,606) in the Scientific Registry of Transplant Recipients database who underwent isolated heart transplantation from January 1, 2004, to July 1, 2018. Mortality (8,278 deaths) was verified with the complete Social Security Death Index with a median follow-up of 3.9 years. Temporal decomposition was used to identify phases of survival and phase-specific risk factors. The random survival forests method was used to determine importance of mortality risk factors and their interactions. RESULTS: We identified 3 phases of mortality risk: early post-transplantation, constant, and late. Sex was not a significant risk factor. There were several interactions predicting early mortality such as pretransplantation mechanical ventilation with presence of end-organ function (bilirubin, renal function) and interactions predicting later mortality such as diabetes and older age (donor and recipient). More complex interactions predicting early-, mid-, and late-mortality existed and were identified with machine learning (i.e., elevated bilirubin, mechanical ventilation, and dialysis). CONCLUSIONS: Post-heart transplant mortality risk is complex and dynamic, changing with time and events. Sex is not an important mortality risk factor. To prevent organ wastage, end-organ dysfunction should be resolved before transplantation as much as possible.

Variables of importance in the Scientific Registry of Transplant Recipients database predictive of heart transplant waitlist mortality.

The prelisting variables essential for creating an accurate heart transplant allocation score based on survival are unknown. To identify these we studied mortality of adults on the active heart transplant waiting list in the Scientific Registry of Transplant Recipients database from January 1, 2004 to August 31, 2015. There were 33 069 candidates awaiting heart transplantation: 7681 UNOS Status 1A, 13 027 Status 1B, and 12 361 Status 2. During a median waitlist follow-up of 4.3 months, 5514 candidates died. Variables of importance for waitlist mortality were identified by machine learning using Random Survival Forests. Strong correlates predicting survival were estimated glomerular filtration rate (eGFR), serum albumin, extracorporeal membrane oxygenation, ventricular assist device, mechanical ventilation, peak oxygen capacity, hemodynamics, inotrope support, and type of heart disease with less predictive variables including antiarrhythmic agents, history of stroke, vascular disease, prior malignancy, and prior tobacco use. Complex interactions were identified such as an additive risk in mortality based on renal function and serum albumin, and sex-differences in mortality when eGFR >40 mL/min/1.73 m. Most predictive variables for waitlist mortality are in the current tiered allocation system except for eGFR and serum albumin which have an additive risk and complex interactions.

Caveat emptor: the need for evidence, regulation, and certification of home telehealth systems for the management of chronic conditions.

The home telehealth market is rapidly expanding. The technology and capabilities currently available have the potential to significantly affect the clinical management of an aging population, particularly, the large number with multiple coexisting disease processes. Potential benefits of home-monitoring systems for patients with heart failure range from decreased rates of mortality and improved quality of life to providing third party payers, including the federal government (ie, Centers for Medicare and Medicaid Services), with significant long-term cost savings. The current regulatory process does not provide adequate oversight and standards for these systems that transmit and process data (telehealth systems) critical for patient management. Home telehealth vendors must address the possibility that increased utilization increases their risk of liability due to patient safety issues. In all, 5 major areas need to be addressed to maximize the benefits and safety of this technology: effectiveness of patient management; evidence-based outcomes; regulation; cost, including cost effectiveness and reimbursement; and certification to ensure reliability.