The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions. 

https://www.ahajournals.org/doi/pdf/10.1161/CIR.0000000000001052

Heart Disease and Stroke Statistics—2022 Update: A Report From the American Heart Association

Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). Methods: The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year’s worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year’s edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. Results: Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. Conclusions: The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions. 

Heart Disease and Stroke Statistics—2023 Update: A Report From the American Heart Association

Objective To review and appraise the validity and usefulness of published and preprint reports of prediction models for diagnosing coronavirus disease 2019 (covid-19) in patients with suspected infection, for prognosis of patients with covid-19, and for detecting people in the general population at increased risk of covid-19 infection or being admitted to hospital with the disease. Design Living systematic review and critical appraisal by the COVID-PRECISE (Precise Risk Estimation to optimise covid-19 Care for Infected or Suspected patients in diverse sEttings) group. Data sources PubMed and Embase through Ovid, up to 1 July 2020, supplemented with arXiv, medRxiv, and bioRxiv up to 5 May 2020. Study selection Studies that developed or validated a multivariable covid-19 related prediction model. Data extraction At least two authors independently extracted data using the CHARMS (critical appraisal and data extraction for systematic reviews of prediction modelling studies) checklist; risk of bias was assessed using PROBAST (prediction model risk of bias assessment tool). Results 37 421 titles were screened, and 169 studies describing 232 prediction models were included. The review identified seven models for identifying people at risk in the general population; 118 diagnostic models for detecting covid-19 (75 were based on medical imaging, 10 to diagnose disease severity); and 107 prognostic models for predicting mortality risk, progression to severe disease, intensive care unit admission, ventilation, intubation, or length of hospital stay. The most frequent types of predictors included in the covid-19 prediction models are vital signs, age, comorbidities, and image features. Flu-like symptoms are frequently predictive in diagnostic models, while sex, C reactive protein, and lymphocyte counts are frequent prognostic factors. Reported C index estimates from the strongest form of validation available per model ranged from 0.71 to 0.99 in prediction models for the general population, from 0.65 to more than 0.99 in diagnostic models, and from 0.54 to 0.99 in prognostic models. All models were rated at high or unclear risk of bias, mostly because of non-representative selection of control patients, exclusion of patients who had not experienced the event of interest by the end of the study, high risk of model overfitting, and unclear reporting. Many models did not include a description of the target population (n=27, 12%) or care setting (n=75, 32%), and only 11 (5%) were externally validated by a calibration plot. The Jehi diagnostic model and the 4C mortality score were identified as promising models. Conclusion Prediction models for covid-19 are quickly entering the academic literature to support medical decision making at a time when they are urgently needed. This review indicates that almost all pubished prediction models are poorly reported, and at high risk of bias such that their reported predictive performance is probably optimistic. However, we have identified two (one diagnostic and one prognostic) promising models that should soon be validated in multiple cohorts, preferably through collaborative efforts and data sharing to also allow an investigation of the stability and heterogeneity in their performance across populations and settings. Details on all reviewed models are publicly available at https://www.covprecise.org/. Methodological guidance as provided in this paper should be followed because unreliable predictions could cause more harm than benefit in guiding clinical decisions. Finally, prediction model authors should adhere to the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) reporting guideline. Systematic review registration Protocol https://osf.io/ehc47/, registration https://osf.io/wy245. Readers’ note This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication. This version is update 3 of the original article published on 7 April 2020 (BMJ 2020;369:m1328). Previous updates can be found as data supplements (https://www.bmj.com/content/369/bmj.m1328/related#datasupp). When citing this paper please consider adding the update number and date of access for clarity.

https://www.bmj.com/content/bmj/369/bmj.m1328.full.pdf

Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal

Cardiovascular Considerations for Patients, Health Care Workers, and Health Systems During the COVID-19 Pandemic.

A novel human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified in Wuhan, China, in December 2019. Since then, the virus has made its way across the globe to affect over 180 countries. SARS-CoV-2 has infected humans in all age groups, of all ethnicities, both males and females while spreading through communities at an alarming rate. Given the nature of this virus, there is much still to be learned; however, we know that the clinical manifestations range from a common cold to more severe diseases such as bronchitis, pneumonia, severe acute respiratory distress syndrome (ARDS), multi-organ failure, and even death. It is believed that COVID-19, in those with underlying health conditions or comorbidities, has an increasingly rapid and severe progression, often leading to death. This paper examined the comorbid conditions, the progression of the disease, and mortality rates in patients of all ages, infected with the ongoing COVID-19 disease. An electronic literature review search was performed, and applicable data was then collected from peer-reviewed articles published from January to April 20, 2020. From what is known at the moment, patients with COVID-19 disease who have comorbidities, such as hypertension or diabetes mellitus, are more likely to develop a more severe course and progression of the disease. Furthermore, older patients, especially those 65 years old and above who have comorbidities and are infected, have an increased admission rate into the intensive care unit (ICU) and mortality from the COVID-19 disease. Patients with comorbidities should take all necessary precautions to avoid getting infected with SARS CoV-2, as they usually have the worst prognosis.

/pdf/comorbidity-and-its-impact-on-patients-with-covid-19-tf2lukp8c7.pdf

Comorbidity and its Impact on Patients with COVID-19.

Studies have reminded that cardiovascular metabolic comorbidities made patients more susceptible to suffer 2019 novel corona virus (2019-nCoV) disease (COVID-19), and exacerbated the infection. The aim of this analysis is to determine the association of cardiovascular metabolic diseases with the development of COVID-19. A meta-analysis of eligible studies that summarized the prevalence of cardiovascular metabolic diseases in COVID-19 and compared the incidences of the comorbidities in ICU/severe and non-ICU/severe patients was performed. Embase and PubMed were searched for relevant studies. A total of six studies with 1527 patients were included in this analysis. The proportions of hypertension, cardia-cerebrovascular disease and diabetes in patients with COVID-19 were 17.1%, 16.4% and 9.7%, respectively. The incidences of hypertension, cardia-cerebrovascular diseases and diabetes were about twofolds, threefolds and twofolds, respectively, higher in ICU/severe cases than in their non-ICU/severe counterparts. At least 8.0% patients with COVID-19 suffered the acute cardiac injury. The incidence of acute cardiac injury was about 13 folds higher in ICU/severe patients compared with the non-ICU/severe patients. Patients with previous cardiovascular metabolic diseases may face a greater risk of developing into the severe condition and the comorbidities can also greatly affect the prognosis of the COVID-19. On the other hand, COVID-19 can, in turn, aggravate the damage to the heart.

/pdf/prevalence-and-impact-of-cardiovascular-metabolic-diseases-47raewzpzq.pdf

Prevalence and impact of cardiovascular metabolic diseases on COVID-19 in China.

BACKGROUND Porokeratosis (PK) is a common autosomal dominant chronic progressive dyskeratosis with various clinical manifestations. Based on clinical manifestations, porokeratosis can be classified as porokeratosis of mibelli, disseminated superficial porokeratosis, disseminated superficial actinic porokeratosis, linear porokeratosis (LP), porokeratosis palmaris et plantaris disseminata, porokeratosis punctata, popular PK, hyperkeratosis PK, inflammatory PK, verrucous PK, and mixed types. We report a case of LP in a child and describe its dermoscopic findings. CASE SUMMARY Linear porokeratosis is a rare PK. The patient presented with unilateral keratinizing maculopapular rash of the foot in childhood. The patient underwent skin pathology and dermoscopy, and was treated with liquid nitrogen freezing and topical drugs. CONCLUSION From this case we take-away that LP is a rare disease, by the dermoscopic we can identify it.

https://doi.org/10.12998/wjcc.v10.i31.11585

Linear porokeratosis of the foot with dermoscopic manifestations: A case report

Abstract Background Drug-coated balloons (DCBs) are an up-and-coming tactic in treating in-stent restenosis and coronary artery small vessel disease, but their efficacy in treating acute myocardial infarction needs to be further explored. Methods A meta-analysis of 7 studies was conducted to make a comparison with the results of DCB and drug-eluting stent implantation after a median follow-up of 15 months. Results A total of 922 patients were included in this analysis in total, including 375 patients in the DCB group and 547 patients in the stent group. A total of 962 vascular diseases were manifested in the 2 groups. After 6 to 24 months of follow-up, there was no statistically significant difference with respect to major adverse cardiovascular events (odds ratio [OR]: 0.82; 95% confidence interval [CI]: 0.52–1.29; Z = 0.85; P = 0.39), cardiac death (OR: 0.92; 95% CI: 0.39–2.12; Z = 0.21; P = 0.84), target lesion revascularization (OR: 1.09; 95% CI: 0.53–2.25; Z = 0.24; P = 0.81), late lumen loss (MD: −0.05; 95% CI: −0.15 to 0.06; Z = 0.85; P = 0.40), or dual antiplatelet therapy (DAPT) (OR: 1.04; 95% CI: 0.53–2.05; Z = 0.11; P = 0.91) between the 2 groups. In the DCB group, persistent residual stenosis or C-F dissection occurrence necessitated that a total of 30 patients receive extra bailout implantations. The rate of bailout stenting was 11.8% (95% CI: 7.1–16). Moreover, the DCB group had a shorter DAPT duration compared with the stent group. Conclusion Drug-coated balloons with shorter DAPT durations may be as effective and safe as stent therapy in treating acute myocardial infarction.

Drug-coated balloons are not inferior to drug-coated stents in the treatment of acute myocardial infarction and shorten the duration of dual antiplatelet treatment

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Prevalence and impact of cardiovascular metabolic diseases on COVID-19 in China.

Linear porokeratosis of the foot with dermoscopic manifestations: A case report

Drug-coated balloons are not inferior to drug-coated stents in the treatment of acute myocardial infarction and shorten the duration of dual antiplatelet treatment