{"title":"A Case of Complete Heart Block Presenting as Resistant Hypertensive Emergency","authors":"Larissa Check","doi":"10.47363/jcrrr/2022(3)159","DOIUrl":"https://doi.org/10.47363/jcrrr/2022(3)159","url":null,"abstract":"The nationally accepted guideline for hypertension is an elevated systolic and diastolic reading of >130/80. Unmanaged hypertension could eventually lead to hypertensive urgency if a patient’s blood pressure is >180/100 with no signs of organ damage, or hypertensive emergency if their blood pressure is >180/100 and there are signs of organ damage occurring. When a patient presents with hypertensive emergency that is difficult to control despite multiple antihypertensives, this is known as resistant hypertension. Persistently resistant hypertension can also be described as refractory hypertension. Here, we have an African-American gentleman who presented with bradycardia and hypertensive emergency that was refractory to medical therapies. Subsequently, it was found that he was in complete heart block. His blood pressure only improved two weeks after pacemaker implantation and required multiple antihypertensives.","PeriodicalId":430938,"journal":{"name":"Journal of Cardiology Research Review & Reports","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122931412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Enhanced Cardiovascular Risk Assessment in United States Subjects for Deployment to Antarctica","authors":"Masood Ahmad, Patricia Rodriguez-Lozano","doi":"10.47363/jcrrr/2022(3)158","DOIUrl":"https://doi.org/10.47363/jcrrr/2022(3)158","url":null,"abstract":"Introduction: Coronary artery disease (CAD) is the leading cause of death in developed nations. Nearly half of asymptomatic CAD cases initially present as acute myocardial infarction (MI) or sudden cardiac death.Therefore, assessment of cardiovascular health is important in subjects who are deployed to remote stations with limited access to medical care, such as Antarctica. Effective screening strategies for detecting CAD and minimizing the risk of acute cardiovascular events in the deployed subjects are essential to mission success. Our study for the first time describes cardiovascular risk assessment in US subjects prior to their deployment to Antarctica. Methods: This report is a single center retrospective analysis of 135 subjects who underwent advanced cardiovascular screening from October 2013 to November 2017 prior to their deployment to Antarctica. Of the 135 subjects, 128 were assessed to be acceptable cardiac risk and were approved for deployment. However, only a total of 100 subjects proceeded for deployment to the South Pole. The deployment periods ranged from 6 to 324 days with a mean of 94.4 days (SD 73.8). All deployed subjects were exposed to the harsh cold climate in Antarctica. Primary outcomes include cardiovascular events such as acute myocardial infarction, unstable angina pectoris, congestive heart failure, cardiac arrhythmias, and sudden cardiac death. Results: None of the 100 subjects had cardiac events reported during their deployment. Conclusions: The current enhanced cardiovascular screening process, prior to deployment to US Antarctic Program stations, appears effective in identifying subjects with low risk of cardiac events.","PeriodicalId":430938,"journal":{"name":"Journal of Cardiology Research Review & Reports","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121076121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Post-Stroke Fatigue: Difficulties in Measurement and Treatment","authors":"Ank A Agarwal","doi":"10.47363/jcrrr/2021(2)141","DOIUrl":"https://doi.org/10.47363/jcrrr/2021(2)141","url":null,"abstract":"Post-stroke fatigue (PSF) affects millions of patients worldwide. It is categorized by debilitating fatigue and lack of motivation pervading numerous aspects of daily life. These difficulties affect patients physically, mentally, socially, and emotionally. Current measurements show that anywhere from 25% to 75% of the 17 million people globally who suffer a first-time stroke every year may also suffer from post-stroke fatigue. However, measuring post-stroke fatigue is fraught with numerous issues. Researchers differ in their specific definitions of the condition, and there are various scales used to measure the severity of this fatigue. Moreover, many studies exclude patients in measurement if they have comorbidities such as depression, resulting in an added measure of complexity for comparing and creating meaningful conclusions. Post-stroke fatigue also has limited treatment options, many of which are limited in efficacy at best. Current efforts aim to treat the condition from a variety of lenses, including pharmacological, physical, psychological, and environmental. However, the best interventions are yet to be developed and will likely arise from improved understanding of post-stroke fatigue etiology and associated factors. Herein, we present a brief review of the difficulties in measuring stroke prevalence and treating the condition.","PeriodicalId":430938,"journal":{"name":"Journal of Cardiology Research Review & Reports","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129940244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Human Leukocyte Antigen Mismatch is Associated with Grade 3 Primary Graft Dysfunction at 72 Hours Following Bilateral Sequential Lung Transplantation: A Single-Center, Retrospective Cohort Study","authors":"Tjörvi E Perry","doi":"10.47363/jcrrr/2021(2)140","DOIUrl":"https://doi.org/10.47363/jcrrr/2021(2)140","url":null,"abstract":"Background: The role of donor-recipient human leukocyte antigen (HLA) mismatch as a risk factor for developing primary graft dysfunction (PGD) after lung transplantation is not well understood. We describe a novel association between increased donor-recipient HLA mismatch and grade 3 PGD after bilateral lung transplantation. Methods: We retrospectively evaluated donor and recipient demographic data, co-morbidities, intraoperative interventions and outcomes in 99 consecutive adult patients undergoing primary bilateral lung transplantation. The primary outcome of this study was grade 3 PGD at 72 hours. Secondary outcomes included intensive care and hospital lengths of stay and mortality. Results: Eighteen patients (18%) met criteria for grade 3 PGD at 72 hours postoperatively. More non-Caucasian recipients (27.8% vs. 7.4%, p=0.026), and more patients with interstitial lung disease (72.2% vs 43.2%, p=0.031) developed grade 3 PGD. The use of inhaled epoprostenol (OR 4.38, 95% CI: 1.02-20.16, p=0.048), increased HLA mismatches (OR 2.85, 95% CI: 1.31-7.45, p=0.017) and the use of each 250mL unit of PRBCs during the intraoperative period (OR 0.77, 95% CI: 0.58-0.97, p=0.048) were independently associated with grade 3 PGD. Patients diagnosed with grade 3 PGD spent significantly longer time in the intensive care unit (22 days [6;74 days] vs. 7 days [2;83 days], p=<0.001) and hospital (30.5 days [10;83 days] vs. 18 days [3;97 days], p=0.012), and survival was significantly worse for those with PGD3 at 72 hours (log-rank p=0.009). Conclusion: Our data indicate, for the first time, that HLA donor-recipient mismatch is an independent risk factor for developing grade 3 PGD at 72 hours after bilateral lung transplantation.","PeriodicalId":430938,"journal":{"name":"Journal of Cardiology Research Review & Reports","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114548736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Assessment of Clinician and Patient Baseline Knowledge and Preferences Regarding Red Blood Cell Transfusions in Cardiac and Non-Cardiac Surgery","authors":"Tjörvi E Perry","doi":"10.47363/jcrrr/2021(2)139","DOIUrl":"https://doi.org/10.47363/jcrrr/2021(2)139","url":null,"abstract":"Purpose: To delineate the current knowledge of, and preference for perioperative red blood cell transfusion by clinician and patients. Methods: In this single center study, clinicians and patients were asked to complete a 21-item survey, and a 19-item survey, respectively. Results: On a 7-point category scale, clinicians felt more knowledgeable about when red blood cells should be transfused (5.5 vs 2.1; p<0.0001), clinicians, in preparation for open heart surgery, were more interested in hearing about the risks and benefits of a blood transfusion (4.6 vs 2.6; p<0.0001), and more clinicians felt it was important for them to be involved in deciding whether they should receive a blood transfusion (5.7 vs 5.0; p=0.015). The majority of clinicians chose hemoglobin triggers of either <7.5 mg/dL for non-cardiac surgery or 7.5-8.9 mg/dL for cardiac surgery, while patients either felt they did not have enough information or did not know. Conclusion: Our results highlight important differences between clinicians and patients in the basic knowledge about, and preferences for perioperative red blood transfusion, and imply a clinician-driven decision model to transfuse RBCs, and supports future efforts to develop decision aids to facilitate patient involvement in the shared decision-making about perioperative transfusion.","PeriodicalId":430938,"journal":{"name":"Journal of Cardiology Research Review & Reports","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122898525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Risk Probability of Having a Cardiovascular Disease, Stroke, or Renal Complications Using Annual Segmented Data of Glucose and Metabolism Index (GH Method: Math-Physical Medicine)","authors":"Gerald C. Hsu","doi":"10.47363/jcrrr/2020(1)116","DOIUrl":"https://doi.org/10.47363/jcrrr/2020(1)116","url":null,"abstract":"Method In 2014, the author applied topology concept, finite-element engineering technique, and nonlinear algebra operations to develop a mathematical metabolism model, which contains ten categories including four output categories (weight, glucose, BP, other labtested data including lipids & ACR) and six input categories (food, water drinking, exercise, sleep, stress, routine life patterns and safety measures). These 10 metabolic categories include approximately 500 detailed elements. He further defined a new parameter referred to as the metabolism index (MI) that has a combined score of the above metabolic categories and elements. Since 2012, he has collected and stored ~2 million data from his own body health conditions and personal lifestyle details.","PeriodicalId":430938,"journal":{"name":"Journal of Cardiology Research Review & Reports","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115899106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Drug Repositioning For The Prophylaxis And Treatment Of Covid-19","authors":"M. Al-Noaemi","doi":"10.47363/jcrrr/2020(1)108","DOIUrl":"https://doi.org/10.47363/jcrrr/2020(1)108","url":null,"abstract":"Coronaviruses are large, enveloped, single-stranded, positive-sense RNA viruses and belong to the family coronaviridae. Other viruses from the same family include the severe acute respiratory syndrome coronavirus (SARS-CoV), which appeared in 2002 in China, and Middle East respiratory syndrome coronavirus (MERS-CoV ), which appeared in 2012 in Saudi Arabia. In december 2019, several patients from Wuhan, China were admitted with symptoms of pneumonia. A new virus was identified and initially called the 2019 novel coronavirus (2019-nCoV). On january 30, 2020, the World Health Organization (WHO) named the disease as “COVID-19” which is coronavirus disease 2019. On March 11, 2020, the WHO described its outbreak as a pandemic. Chloroquine (CQ), the antimalarial drug, elicit antiviral effects against several viruses. Previous studies reported the antiviral activity of CQ against many human coronaviruses (HCoVs) such as SARS-CoV, MERS-CoV, and HCoV-OC43. Recent in vitro studies (2020) reported that CQ and hydroxychloroquine (HCQ) is effective in inhibiting SARS-CoV-2 infection. In China, in February 2020 over 100 patients treated with (CQ) resulted in significant improvement of pneumonia. In France, on March 17, 2020, some of the COVID-19 patients were treated with (HCQ) and others treated with HCQ in combination with azithromycin to prevent bacterial infection.","PeriodicalId":430938,"journal":{"name":"Journal of Cardiology Research Review & Reports","volume":"233 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131166425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"How to Reverse Chronic Disease Induced Heart Conditions Using a Simple and Effective “Cookbook of Quantitative Formulas” (GHMethod: Math-Physical Medicine)","authors":"Gerald C. Hsu","doi":"10.47363/jcrrr/2020(1)110","DOIUrl":"https://doi.org/10.47363/jcrrr/2020(1)110","url":null,"abstract":"Volume 1(2): 1-5 Introduction The author uses GH-Method: math-physical medicine (MPM) approach to investigate his risk probability (Risk) of having a cardiovascular disease (CVD) or stroke. Here, the word of CVD implies the most common type of heart diseases. It is also called coronary artery disease (CAD), or coronary heart disease (CHD). All of these situations relate to plaque buildups to block the blood flow in arteries due to high glucose and high lipid, or rupture of arteries caused by high glucose and high blood pressure. Based on the research findings of his CVD and stroke risks investigation (Reference 1), this article specifically addresses how he “reversed” his chronic diseases induced heart conditions in a quantitative manner, via a stringent lifestyle management program without drugs or surgeries. The word “reverse” used in this context is to change the direction of his heart condition’s progression in order to prevent the condition from worsening.","PeriodicalId":430938,"journal":{"name":"Journal of Cardiology Research Review & Reports","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114387907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Using GH-Method: Math-Physical Medicine to Investigate the Risk Probability of Metabolic Disorders Induced Cardiovascular Diseases, Stroke, and Renal Complications","authors":"Gerald C. Hsu","doi":"10.47363/jcrrr/2020(1)111","DOIUrl":"https://doi.org/10.47363/jcrrr/2020(1)111","url":null,"abstract":"Volume 1(2): 1-4 Introduction The author uses GH-Method: math-physical medicine (MPM) approach to investigate two clinical cases A and B of risk probability on metabolic disorders induced cardiovascular diseases (CVD) or stroke (“Risk”). He addresses the multiple correlations among three metabolic bio markers, i.e. body weight, glucose, and blood pressure (BP), which are also closely related to both CVD and stroke. He further examines Case A’s bladder and renal complications due to diabetes and hypertension.","PeriodicalId":430938,"journal":{"name":"Journal of Cardiology Research Review & Reports","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125954405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Glycated Haemoglobin as Seen at the Plateau Specialist Hospital, Jos. Nigeria","authors":"Chundusu Caleb","doi":"10.47363/jcrrr/2020(1)115","DOIUrl":"https://doi.org/10.47363/jcrrr/2020(1)115","url":null,"abstract":"The use of glycated haemoglobin (Hba1C) in assessing long term glycemic control is well known. However, its use as cardiovascular risk remains controversial. Availability, technicality and cost has made it uncommon among the developing countries. A short over view may add up to the scanty literature on HBA1c in Plateau Specialist Hospital, Jos. Nigeria. Design and methods: We conducted a retrospective analysis of HBA1c records from the side-laboratory of the Jos University Teaching Hospital. The test was determined using STANDARD TM A1cCare analyzer. Results: A total of 264 patients were tested in the “point-of-care” laboratory within six months (1st quarter 2020). They consisting of 149 (56.4%) female, with a total mean age of 55years. 80.7% of total records were diabetic and 14.4% diabetic hypertensive. A heterogeneous group of non-diabetics consist of the remaining 19.3%. The non-diabetic group had a mean HBA1c of 6.79 % (+/- 2.2). The group of diabetes without hypertension had a mean HBA1c 8.54% (+/- 2.9) while diabetic hypertensive had a mean HBA1c of 8.8% (+/- 3.7). AVOVA showed significant variation in the three group (p<0.002). a two-unpaired t-test among the two diabetic group showed no statistical difference (p-0.66). Conclusion: Patients that are not diagnosed to be diabetic attending clinics for other aliments were more likely to be pre-diabetics. Long term diabetic control in the Jos University Teaching Hospital is rather poor and hypertension appear not to have significant effect on HBA1c level.","PeriodicalId":430938,"journal":{"name":"Journal of Cardiology Research Review & Reports","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122767147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}