Artificial intelligence modelling to assess the risk of cardiovascular disease in oncology patients.

Aims: There are no comprehensive machine learning (ML) tools used by oncologists to assist with risk identification and referrals to cardio-oncology. This study applies ML algorithms to identify oncology patients at risk for cardiovascular disease for referrals to cardio-oncology and to generate risk scores to support quality of care. Methods and results: De-identified patient data were obtained from Vanderbilt University Medical Center. Patients with breast, kidney, and B-cell lymphoma cancers were targeted. Additionally, the study included patients who received immunotherapy drugs for treatment of melanoma, lung cancer, or kidney cancer. Random forest (RF) and artificial neural network (ANN) ML models were applied to analyse each cohort: A total of 20 023 records were analysed (breast cancer, 6299; B-cell lymphoma, 9227; kidney cancer, 2047; and immunotherapy for three covered cancers, 2450). Data were divided randomly into training (80%) and test (20%) data sets. Random forest and ANN performed over 90% for accuracy and area under the curve (AUC). All ANN models performed better than RF models and produced accurate referrals. Conclusion: Predictive models are ready for translation into oncology practice to identify and care for patients who are at risk of cardiovascular disease. The models are being integrated with electronic health record application as a report of patients who should be referred to cardio-oncology for monitoring and/or tailored treatments. Models operationally support cardio-oncology practice. Limited validation identified 86% of the lymphoma and 58% of the kidney cancer patients with major risk for cardiotoxicity who were not referred to cardio-oncology.

Smartphone Ownership and Interest in Mobile Health Technologies for Self-care Among Patients With Chronic Heart Failure: Cross-sectional Survey Study.

BACKGROUND: Heart failure (HF) is a highly prevalent chronic condition that places a substantial burden on patients, families, and health care systems worldwide. Recent advances in mobile health (mHealth) technologies offer great opportunities for supporting many aspects of HF self-care. There is a need to better understand patients' adoption of and interest in using mHealth for self-monitoring and management of HF symptoms. OBJECTIVE: The purpose of this study is to assess smartphone ownership and patient attitudes toward using mHealth technologies for HF self-care in a predominantly minority population in an urban clinical setting. METHODS: We conducted a cross-sectional survey of adult outpatients (aged ≥18 years) at an academic outpatient HF clinic in the Midwest. The survey comprised 34 questions assessing patient demographics, ownership of smartphones and other mHealth devices, frequently used smartphone features, use of mHealth apps, and interest in using mHealth technologies for vital sign and HF symptom self-monitoring and management. RESULTS: A total of 144 patients were approached, of which 100 (69.4%) participated in the study (63/100, 63% women). The participants had a mean age of 61.3 (SD 12.25) years and were predominantly Black or African American (61/100, 61%) and Hispanic or Latino (18/100, 18%). Almost all participants (93/100, 93%) owned a cell phone. The share of patients who owned a smartphone was 68% (68/100). Racial and ethnic minorities that identified as Black or African American or Hispanic or Latino reported higher smartphone ownership rates compared with White patients with HF (45/61, 74% Black or African American and 11/18, 61% Hispanic or Latino vs 9/17, 53% White). There was a moderate and statistically significant association between smartphone ownership and age (Cramér V [ΦC]=0.35; P<.001), education (ΦC=0.29; P=.001), and employment status (ΦC=0.3; P=.01). The most common smartphone features used by the participants were SMS text messaging (51/68, 75%), internet browsing (43/68, 63%), and mobile apps (41/68, 60%). The use of mHealth apps and wearable activity trackers (eg, Fitbits) for self-monitoring of HF-related parameters was low (15/68, 22% and 15/100, 15%, respectively). The most popular HF-related self-care measures participants would like to monitor using mHealth technologies were physical activity (46/68, 68%), blood pressure (44/68, 65%), and medication use (40/68, 59%). CONCLUSIONS: Most patients with HF have smartphones and are interested in using commercial mHealth apps and connected health devices to self-monitor their condition. Thus, there is a great opportunity to capitalize on the high smartphone ownership among racial and ethnic minority patients to increase reach and enhance HF self-management through mHealth interventions.

Mesenchymal stem cells improve cardiac conduction by upregulation of connexin 43 through paracrine signaling.

Mesenchymal stem cells (MSCs) were shown to improve cell survival and alleviate cardiac arrhythmias when transplanted into cardiac tissue; however, little is known about the mechanism by which MSCs modify the electrophysiological properties of cardiac tissue. We aimed to distinguish the influence of cell-cell coupling between myocytes and MSCs from that of MSC-derived paracrine factors on the spontaneous activity and conduction velocity (θ) of multicellular cardiomyocyte preparations. HL-1 cells were plated on microelectrode arrays and their spontaneous activity and θ was determined from field potential recordings. In heterocellular cultures of MSCs and HL-1 cells the beating frequency was attenuated (t(0h): 2.26 ± 0.18 Hz; t(4h): 1.98 ± 0.26 Hz; P < 0.01) concomitant to the intercellular coupling between MSCs and cardiomyocytes. In HL-1 monolayers supplemented with MSC conditioned media (ConM) or tyrode (ConT) θ significantly increased in a time-dependent manner (ConT: t(0h): 2.4 cm/s ± 0.2; t(4h): 3.1 ± 0.4 cm/s), whereas the beating frequency remained constant. Connexin (Cx)43 mRNA and protein expression levels also increased after ConM or ConT treatment over the same time period. Enhanced low-density lipoprotein receptor-related protein 6 (LRP6) phosphorylation after ConT treatment implicates the Wnt signaling pathway. Suppression of Wnt secretion from MSCs (IWP-2; 5 µmol/l) reduced the efficacy of ConT to induce phospho-LRP6 and to increase θ. Inhibition of ß-catenin (cardamonin; 10 µmol/l) or GSK3-α/ß (LiCl; 5 mmol/l) also suppressed changes in θ, further supporting the hypothesis that MSC-mediated Cx43 upregulation occurs in part through secreted Wnt ligands and activation of the canonical Wnt signaling pathway.

Tricuspid regurgitation causing a right to left interatrial shunt with normal pulmonary pressures.

We describe a patient who presented with asymptomatic hypoxia refractory to supplemental oxygen. Transthoracic echocardiography and angiography demonstrated a tricuspid valve with a large regurgitant jet oriented directly at a patent foramen ovale, producing a right to left shunt with systemic hypoxia. The patient was found to have normal right-sided cardiac pressures as well as normal pulmonary arterial pressures, demonstrating the shunt was secondary to the tricuspid regurgitant jet and not a result of a pressure gradient between atria. Surgical correction of the tricuspid valve and closure of the patent foramen ovale resulted in resolution of the patient's hypoxemia.