Prolactin Inhibition in Peripartum Cardiomyopathy: Systematic Review and Meta-analysis.

Heart failure (HF) is one of the leading causes of maternal mortality and morbidity in the United States. Peripartum cardiomyopathy (PPCM) constitutes up to 70% of all HF in pregnancy. Cardiac angiogenic imbalance caused by cleaved 16kDa prolactin has been hypothesized to contribute to the development of PPCM, fueling investigation of prolactin inhibitors for the management of PPCM. We conducted a systematic review and meta-analysis to assess the impact of prolactin inhibition on left ventricular (LV) function and mortality in patients with PPCM. We included English language articles from PubMed and EMBASE published upto March 2022. We pooled the mean difference (MD) for left ventricular ejection fraction (LVEF) at follow-up, odds ratio (OR) for LV recovery and risk ratio (RR) for all-cause mortality using random-effects meta-analysis. Among 548 studies screened, 10 studies (3 randomized control trials (RCTs), 2 retrospective and 5 prospective cohorts) were included in the systematic review. Patients in the Bromocriptine + standard guideline directed medical therapy (GDMT) group had higher LVEF% (pMD 12.56 (95% CI 5.84-19.28, I2=0%) from two cohorts and pMD 14.25 (95% CI 0.61-27.89, I2=88%) from two RCTs) at follow-up compared to standard GDMT alone group. Bromocriptine group also had higher odds of LV recovery (pOR 3.55 (95% CI 1.39-9.1, I2=62)). We did not find any difference in all-cause mortality between the groups. Our analysis demonstrates that the addition of Bromocriptine to standard GDMT was associated with a significant improvement in LVEF% and greater odds of LV recovery, without significant reduction in all-cause mortality.

Towards Multimodal Equipment to Help in the Diagnosis of COVID-19 Using Machine Learning Algorithms.

COVID-19 occurs due to infection through respiratory droplets containing the SARS-CoV-2 virus, which are released when someone sneezes, coughs, or talks. The gold-standard exam to detect the virus is Real-Time Polymerase Chain Reaction (RT-PCR); however, this is an expensive test and may require up to 3 days after infection for a reliable result, and if there is high demand, the labs could be overwhelmed, which can cause significant delays in providing results. Biomedical data (oxygen saturation level-SpO2, body temperature, heart rate, and cough) are acquired from individuals and are used to help infer infection by COVID-19, using machine learning algorithms. The goal of this study is to introduce the Integrated Portable Medical Assistant (IPMA), which is a multimodal piece of equipment that can collect biomedical data, such as oxygen saturation level, body temperature, heart rate, and cough sound, and helps infer the diagnosis of COVID-19 through machine learning algorithms. The IPMA has the capacity to store the biomedical data for continuous studies and can be used to infer other respiratory diseases. Quadratic kernel-free non-linear Support Vector Machine (QSVM) and Decision Tree (DT) were applied on three datasets with data of cough, speech, body temperature, heart rate, and SpO2, obtaining an Accuracy rate (ACC) and Area Under the Curve (AUC) of approximately up to 88.0% and 0.85, respectively, as well as an ACC up to 99% and AUC = 0.94, respectively, for COVID-19 infection inference. When applied to the data acquired with the IMPA, these algorithms achieved 100% accuracy. Regarding the easiness of using the equipment, 36 volunteers reported that the IPMA has a high usability, according to results from two metrics used for evaluation: System Usability Scale (SUS) and Post Study System Usability Questionnaire (PSSUQ), with scores of 85.5 and 1.41, respectively. In light of the worldwide needs for smart equipment to help fight the COVID-19 pandemic, this new equipment may help with the screening of COVID-19 through data collected from biomedical signals and cough sounds, as well as the use of machine learning algorithms.

Global Prevalence and Impact of Hostility, Discrimination, and Harassment in the Cardiology Workplace.

BACKGROUND: Discrimination and emotional and sexual harassment create a hostile work environment (HWE). The global prevalence of HWE in cardiology is unknown, as is its impact. OBJECTIVES: This study sought to evaluate emotional harassment, discrimination, and sexual harassment experienced by cardiologists and its impact on professional satisfaction and patient interactions worldwide. METHODS: The American College of Cardiology surveyed cardiologists from Africa, Asia, the Caribbean, Eastern Europe, the European Union, the Middle East, Oceana, and North, Central, and South America. Demographics, practice information, and HWE were tabulated and compared, and their impact was assessed. The p values were calculated using the chi-square, Fisher exact, and Mann-Whitney U tests. Univariate and multivariate logistic regression analysis determined the association of characteristics with HWE and its subtypes. RESULTS: Of 5,931 cardiologists (77% men; 23% women), 44% reported HWE. Higher rates were found among women (68% vs. 37%; odds ratio [OR]: 3.58 vs. men), Blacks (53% vs. 43%; OR: 1.46 vs. Whites), and North Americans (54% vs. 38%; OR: 1.90 vs. South Americans). Components of HWE included emotional harassment (29%; n = 1,743), discrimination (30%; n = 1,750), and sexual harassment (4%; n = 221), and they were more prevalent among women: emotional harassment (43% vs. 26%), discrimination (56% vs. 22%), and sexual harassment (12% vs. 1%). Gender was the most frequent cause of discrimination (44%), followed by age (37%), race (24%), religion (15%), and sexual orientation (5%). HWE adversely affected professional activities with colleagues (75%) and patients (53%). Multivariate analysis showed that women (OR: 3.39; 95% confidence interval: 2.97 to 3.86; p < 0.001) and cardiologists early in their career (OR: 1.27; 95% confidence interval: 1.14 to 1.43; p < 0.001) had the highest odds of experiencing HWE. CONCLUSIONS: There is a high global prevalence of HWE in cardiology, including discrimination, emotional harassment, and sexual harassment. HWE has an adverse effect on professional and patient interactions, thus confirming concerns about well-being and optimizing patient care. Institutions and practices should prioritize combating HWE.