Non-invasive detection of cardiac allograft rejection among heart transplant recipients using an electrocardiogram based deep learning model.

Aims: Current non-invasive screening methods for cardiac allograft rejection have shown limited discrimination and are yet to be broadly integrated into heart transplant care. Given electrocardiogram (ECG) changes have been reported with severe cardiac allograft rejection, this study aimed to develop a deep-learning model, a form of artificial intelligence, to detect allograft rejection using the 12-lead ECG (AI-ECG). Methods and results: Heart transplant recipients were identified across three Mayo Clinic sites between 1998 and 2021. Twelve-lead digital ECG data and endomyocardial biopsy results were extracted from medical records. Allograft rejection was defined as moderate or severe acute cellular rejection (ACR) based on International Society for Heart and Lung Transplantation guidelines. The extracted data (7590 unique ECG-biopsy pairs, belonging to 1427 patients) was partitioned into training (80%), validation (10%), and test sets (10%) such that each patient was included in only one partition. Model performance metrics were based on the test set (n = 140 patients; 758 ECG-biopsy pairs). The AI-ECG detected ACR with an area under the receiver operating curve (AUC) of 0.84 [95% confidence interval (CI): 0.78-0.90] and 95% (19/20; 95% CI: 75-100%) sensitivity. A prospective proof-of-concept screening study (n = 56; 97 ECG-biopsy pairs) showed the AI-ECG detected ACR with AUC = 0.78 (95% CI: 0.61-0.96) and 100% (2/2; 95% CI: 16-100%) sensitivity. Conclusion: An AI-ECG model is effective for detection of moderate-to-severe ACR in heart transplant recipients. Our findings could improve transplant care by providing a rapid, non-invasive, and potentially remote screening option for cardiac allograft function.

Screening for peripartum cardiomyopathies using artificial intelligence in Nigeria (SPEC-AI Nigeria): Clinical trial rationale and design.

BACKGROUND: Artificial intelligence (AI), and more specifically deep learning, models have demonstrated the potential to augment physician diagnostic capabilities and improve cardiovascular health if incorporated into routine clinical practice. However, many of these tools are yet to be evaluated prospectively in the setting of a rigorous clinical trial-a critical step prior to implementing broadly in routine clinical practice. OBJECTIVES: To describe the rationale and design of a proposed clinical trial aimed at evaluating an AI-enabled electrocardiogram (AI-ECG) for cardiomyopathy detection in an obstetric population in Nigeria. DESIGN: The protocol will enroll 1,000 pregnant and postpartum women who reside in Nigeria in a prospective randomized clinical trial. Nigeria has the highest reported incidence of peripartum cardiomyopathy worldwide. Women aged 18 and older, seen for routine obstetric care at 6 sites (2 Northern and 4 Southern) in Nigeria will be included. Participants will be randomized to the study intervention or control arm in a 1:1 fashion. This study aims to enroll participants representative of the general obstetric population at each site. The primary outcome is a new diagnosis of cardiomyopathy, defined as left ventricular ejection fraction (LVEF) < 50% during pregnancy or within 12 months postpartum. Secondary outcomes will include the detection of impaired left ventricular function (at different LVEF cut-offs), and exploratory outcomes will include the effectiveness of AI-ECG tools for cardiomyopathy detection, new diagnosis of cardiovascular disease, and the development of composite adverse maternal cardiovascular outcomes. SUMMARY: This clinical trial focuses on the emerging field of cardio-obstetrics and will serve as foundational data for the use of AI-ECG tools in an obstetric population in Nigeria. This study will gather essential data regarding the utility of the AI-ECG for cardiomyopathy detection in a predominantly Black population of women and pave the way for clinical implementation of these models in routine practice. TRIAL REGISTRATION: Clinicaltrials.gov: NCT05438576.

Upregulation of Endothelin-1 May Predict Chemotherapy-Induced Cardiotoxicity in Women with Breast Cancer.

As survival in breast cancer patients from newer therapies increases, concerns for chemotherapy-induced cardiotoxicity (CIC) have offset some of these benefits, manifesting as a decline in left ventricular ejection fraction (LVEF). Patients receiving anthracycline-based chemotherapy followed by trastuzumab are at risk for CIC. Previous research evaluating whether clinical biomarkers predict cardiotoxicity has been inconsistent. Recently, angiotensin II type 1 receptor (ATR1) and endothelin 1 (ET1) have been shown to play a role in breast tumor growth. We evaluated ATR1 and ET1 expression in breast cancer tissue and its association with CIC. A total of 33 paraffin-embedded breast tissue specimens from women with breast cancer treated with anthracycline-based chemotherapy and trastuzumab were analyzed by immunohistochemistry (IHC) and qRT-PCR. We found that ET1 expression was increased in patients with an LVEF ≤ 50% (p = 0.032) with a lower LVEF correlating with higher ET1 expression (r = 0.377, p = 0.031). In patients with a change in LVEF of greater than 10%, greater ET1 expression was noted compared to those without a change in LVEF (p = 0.017). Increased ET1 expression in breast tumor tissue is associated with reduced LVEF. Future studies need to examine whether ET1 may be a tissue biomarker that helps predict the risk of developing CIC in women with breast cancer.

Sex and age differences in sST2 in cardiovascular disease.

Aims: The goal of this study was to determine whether sex and age differences exist for soluble ST2 (sST2) for several cardiovascular diseases (CVDs). Methods: We examined sST2 levels using an ELISA kit for myocarditis (n = 303), cardiomyopathy (n = 293), coronary artery disease (CAD) (n = 239), myocardial infarct (MI) (n = 159), and congestive heart failure (CHF) (n = 286) and compared them to controls that did not have CVDs (n = 234). Results: Myocarditis occurred in this study in relatively young patients around age 40 while the other CVDs occurred more often in older individuals around age 60. We observed a sex difference in sST2 by age only in myocarditis patients (men aged 38, women 46, p = 0.0002), but not for other CVDs. Sera sST2 levels were significantly elevated compared to age-matched controls for all CVDs: myocarditis (p ≤ 0.0001), cardiomyopathy (p = 0.0009), CAD (p = 0.03), MI (p = 0.034), and CHF (p < 0.0001) driven by elevated sST2 levels in females for all CVDs except myocarditis, which was elevated in both females (p = 0.002) and males (p ≤ 0.0001). Sex differences in sST2 levels were found for myocarditis and cardiomyopathy but no other CVDs and were higher in males (myocarditis p = 0.0035; cardiomyopathy p = 0.0047). sST2 levels were higher in women with myocarditis over 50 years of age compared to men (p = 0.0004) or women under 50 years of age (p = 0.015). In cardiomyopathy and MI patients, men over 50 had significantly higher levels of sST2 than women (p = 0.012 and p = 0.043, respectively) but sex and age differences were not detected in other CVDs. However, women with cardiomyopathy that experienced early menopause had higher sST2 levels than those who underwent menopause at a natural age range (p = 0.02). Conclusion: We found that sex and age differences in sera sST2 exist for myocarditis, cardiomyopathy, and MI, but were not observed in other CVDs including CAD and CHF. These initial findings in patients with self-reported CVDs indicate that more research is needed into sex and age differences in sST2 levels in individual CVDs.

A Case-Control Study of Peripartum Cardiomyopathy Using the Rochester Epidemiology Project.

BACKGROUND: The incidence of peripartum cardiomyopathy (PPCM) is known through referral center databases that may be affected by referral, misclassification, and other biases. We sought to determine the community-based incidence and natural history of PPCM using the Rochester Epidemiology Project. METHODS AND RESULTS: Incident cases of PPCM occurring between January 1, 1970, and December 31, 2014, were identified in Olmsted County, Minnesota. A total of 15 PPCM cases were confirmed yielding an incidence of 20.3 cases per 100,000 live births in Olmsted County, Minnesota. Clinical information, disease characteristics, and outcomes were extracted from medical records in a 27-county region of the Rochester Epidemiology Project including Olmsted County and matched in a 1:2 ratio with pregnant women without PPCM. A total of 48 women were identified with PPCM in the expanded 27-county region. There was 1 death and no transplants over a median of 7.3 years of follow-up. Six of the 23 women with subsequent pregnancies developed recurrent PPCM, all of whom recovered. Migraine and anxiety were identified as novel possible risk factors for PPCM. CONCLUSIONS: The population-based incidence of PPCM was 20.3 cases per 100,000 live births in Olmsted County, Minnesota. Cardiovascular outcomes were generally excellent in this community cohort.

Detecting cardiomyopathies in pregnancy and the postpartum period with an electrocardiogram-based deep learning model.

AIMS: Cardiovascular disease is a major threat to maternal health, with cardiomyopathy being among the most common acquired cardiovascular diseases during pregnancy and the postpartum period. The aim of our study was to evaluate the effectiveness of an electrocardiogram (ECG)-based deep learning model in identifying cardiomyopathy during pregnancy and the postpartum period. METHODS AND RESULTS: We used an ECG-based deep learning model to detect cardiomyopathy in a cohort of women who were pregnant or in the postpartum period seen at Mayo Clinic. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. We compared the diagnostic probabilities of the deep learning model with natriuretic peptides and a multivariable model consisting of demographic and clinical parameters. The study cohort included 1807 women; 7%, 10%, and 13% had left ventricular ejection fraction (LVEF) of 35% or less, <45%, and <50%, respectively. The ECG-based deep learning model identified cardiomyopathy with AUCs of 0.92 (LVEF ≤ 35%), 0.89 (LVEF < 45%), and 0.87 (LVEF < 50%). For LVEF of 35% or less, AUC was higher in Black (0.95) and Hispanic (0.98) women compared to White (0.91). Natriuretic peptides and the multivariable model had AUCs of 0.85 to 0.86 and 0.72, respectively. CONCLUSIONS: An ECG-based deep learning model effectively identifies cardiomyopathy during pregnancy and the postpartum period and outperforms natriuretic peptides and traditional clinical parameters with the potential to become a powerful initial screening tool for cardiomyopathy in the obstetric care setting.

Peripartum Cardiomyopathy.

Peripartum cardiomyopathy (PPCM) is a form of heart failure that occurs toward the end of pregnancy or in the months following pregnancy and is marked by left ventricular systolic dysfunction. The cause of PPCM remains unknown and there is no diagnostic test specific to PPCM. Outcomes vary and include complete left ventricular recovery, persistent cardiac dysfunction, transplant, and death. Numerous advances have been made in understanding this disease, but many knowledge gaps remain. This article reviews recent data and recommendations for clinical practice in addition to highlighting the multiple knowledge gaps related to PPCM that warrant further investigation.

A Randomized, Controlled Pilot Trial Comparing Platelet-Rich Plasma to Topical Minoxidil Foam for Treatment of Androgenic Alopecia in Women.

BACKGROUND: Androgenic alopecia (AGA) is a common hair loss disorder. Studies have demonstrated successful treatment with platelet-rich plasma (PRP) in men, but studies in women are few. OBJECTIVE: To evaluate PRP in the treatment of AGA in women, compared with topical minoxidil. MATERIALS AND METHODS: Twenty women with AGA received topical minoxidil for 12 weeks and injectable PRP for 12 weeks in a randomized crossover design with an 8-week washout between treatments. Standardized TrichoScan analysis and quality-of-life questionnaires were assessed at baseline and 12-week follow-up for each treatment. RESULTS: After PRP, significant increases from baseline to Week 12 in TrichoScan analysis hair count (p = .002) and vellus hair density (p = .009) occurred. However, minoxidil resulted in significant increases in hair count (p < .001), vellus hair density (p = .03), terminal hair density (p = .004), and cumulative thickness (p = .004). Several quality of life responses improved from baseline to Week 12 after PRP treatment, whereas no improvements were noted after minoxidil. CONCLUSION: Platelet-rich plasma is an effective treatment for hair regrowth in female AGA, although not as effective as minoxidil. However, the improved quality of life responses after PRP, but not minoxidil, suggest a potential overall greater degree of satisfaction with PRP. LEVELS OF EVIDENCE: I. CLINICAL TRIAL REGISTRATION: NCT03488108.

Elevated Sera sST2 Is Associated With Heart Failure in Men ≤50 Years Old With Myocarditis.

Background Myocarditis is an important cause of acute and chronic heart failure. Men with myocarditis have worse recovery and an increased need for transplantation compared with women, but the reason for the sex difference remains unclear. Elevated sera soluble (s) ST2 predicts mortality from acute and chronic heart failure, but has not been studied in myocarditis patients. Methods and Results Adults with a diagnosis of clinically suspected myocarditis (n=303, 78% male) were identified according to the 2013 European Society of Cardiology position statement. Sera sST2 levels were examined by ELISA in humans and mice and correlated with heart function according to sex and age. Sera sST2 levels were higher in healthy men ( P=8×10-6) and men with myocarditis ( P=0.004) compared with women. sST2 levels were elevated in patients with myocarditis and New York Heart Association class III - IV heart failure ( P=0.002), predominantly in men ( P=0.0003). Sera sST2 levels were associated with New York Heart Association class in men with myocarditis who were ≤50 years old ( r=0.231, P=0.0006), but not in women ( r=0.172, P=0.57). Sera sST2 levels were also significantly higher in male mice with myocarditis ( P=0.005) where levels were associated with cardiac inflammation. Gonadectomy with hormone replacement showed that testosterone ( P<0.001), but not estradiol ( P=0.32), increased sera sST2 levels in male mice with myocarditis. Conclusions We show in a well-characterized subset of heart failure patients with clinically suspected and biopsy-confirmed myocarditis that elevated sera sST2 is associated with an increased risk of heart failure based on New York Heart Association class in men ≤50 years old.

Induction of proinflammatory responses in macrophages by the glycosylphosphatidylinositols of Plasmodium falciparum: cell signaling receptors, glycosylphosphatidylinositol (GPI) structural requirement, and regulation of GPI activity.

The glycosylphosphatidylinositol (GPI) anchors of Plasmodium falciparum have been proposed to be the major factors that contribute to malaria pathogenesis through their ability to induce proinflammatory responses. In this study we identified the receptors for P. falciparum GPI-induced cell signaling that leads to proinflammatory responses and studied the GPI structure-activity relationship. The data show that GPI signaling is mediated mainly through recognition by TLR2 and to a lesser extent by TLR4. The activity of sn-2-lyso-GPIs is comparable with that of the intact GPIs, whereas the activity of Man(3)-GPIs is about 80% that of the intact GPIs. The GPIs with three (intact GPIs and Man(3)-GPIs) and two fatty acids (sn-2-lyso-GPIs) appear to differ considerably in the requirement of the auxiliary receptor, TLR1 or TLR6, for recognition by TLR2. The former are preferentially recognized by TLR2/TLR1, whereas the latter are favored by TLR2/TLR6. However, the signaling pathways initiated by all three GPI types are similar, involving the MyD88-dependent activation of extracellular signal-regulated kinase, c-Jun N-terminal kinase, and p38 and NF-kappaB-signaling pathways. The signaling molecules of these pathways differentially contribute to the production of various cytokines and nitric oxide (Zhu, J., Krishnegowda, G., and Gowda, D. C. (2004) J. Biol. Chem. 280, 8617-8627). Our data also show that GPIs are degraded by the macrophage surface phospholipases predominantly into inactive species, indicating that the host can regulate GPI activity at least in part by this mechanism. These results imply that macrophage surface phospholipases play important roles in the GPI-induced innate immune responses and malaria pathogenesis.