Prognostic value of exercise capacity in incident diabetes: a country with high prevalence of diabetes.

BACKGROUND: Diabetes Mellitus (DM) is a fast-growing health problem that imposes an enormous economic burden. Several studies demonstrated the association between physical inactivity and predicting the incidence of diabetes. However, these prediction models have limited validation locally. Therefore, we aim to explore the predictive value of exercise capacity in the incidence of diabetes within a high diabetes prevalence population. METHODOLOGY: A retrospective cohort study including consecutive patients free of diabetes who underwent clinically indicated treadmill stress testing. Diabetic patients at baseline or patients younger than 18 years of age were excluded. Incident diabetes was defined as an established clinical diagnosis post-exercise testing date. The predictive value of exercise capacity was examined using Harrell's c-index, net reclassification index (NRI), and integrated discrimination index (IDI). RESULTS: A total of 8,722 participants (mean age 46 ± 12 years, 66.3% were men) were free of diabetes at baseline. Over a median follow-up period of 5.24 (2.17-8.78) years, there were 2,280 (≈ 26%) new cases of diabetes. In a multivariate model adjusted for conventional risk factors, we found a 12% reduction in the risk of incident diabetes for each METs achieved (HR, 0.9; 95% CI, 0.88-0.92; P < 0.001). Using Cox regression, exercise capacity improved the prediction ability beyond the conventional risk factors (AUC = 0.62 to 0.66 and c-index = 0.62 to 0.68). CONCLUSION: Exercise capacity improved the overall predictability of diabetes. Patients with reduced exercise capacity are at high risk for developing incidence diabetes. Improvement of both physical activity and functional capacity represents a preventive measure for the general population.

Prevalence and predictors of frailty in a high-income developing country: A cross-sectional study.

Background: Frailty is a state of vulnerability and a decreased physiological response to stressors. As the population ages, the prevalence of frailty is expected to increase. Thus, identifying tools and resources that efficiently predict frailty among the Saudi population is important. We aimed to describe the prevalence and predictors of frailty among Saudi patients referred for cardiac stress testing with nuclear imaging. Methods: We included 876 patients (mean age 60.3 ± 11 years, women 48%) who underwent clinically indicated cardiac nuclear stress testing between January and October 2016. Fried Clinical Frailty Scale was used to assess frailty. Patients were considered frail if they had a score of four or higher. Multivariate adjusted logistic regression models were used to determine the independent predictors of elderly frail patients. Results: In this cohort, the median age of the included patients was 61 years, and the prevalence of frailty was 40%. The frail patients were older, more frequently women, and had a higher body mass index. Additionally, frailty was associated with a higher prevalence of cardiovascular risk factors: hypertension (85% vs. 70%) and diabetes (75% vs. 60%). In a fully adjusted logistic regression model, women, hypertension, and obesity (BMI ≥ 30 kg/m2) were independent predictors of elderly frail patients. Conclusions: With the aging of the Saudi population, frailty prevalence is expected to increase. Elderly, obesity, hypertension, and female gender are risk factors of frailty. Interventions to reduce frailty should be focused on this high-risk population.

Incremental prognostic value of SPECT-MPI in chronic kidney disease: A reclassification analysis.

BACKGROUND: Traditional cardiovascular (CV) risk factors have limited predictive value of CV mortality in patients with chronic kidney disease (CKD, creatinine clearance less than 60 mL/minute per 1.73 m2). The aim of this study was to evaluate incremental and independent prognostic value of single-photon emission computerized tomography-myocardial perfusion imaging (SPECT-MPI) across continuum of renal function. METHODS: We retrospectively studied 11,518 (mean age, 65 ± 12 years; 52% were men) patients referred for a clinical indication of SPECT-MPI between April 2004 and May 2009. Primary end point was composite of cardiac death and non-fatal myocardial infarction (CD/MI). We examined the relationship of total perfusion defect (TPD) and CD/MI in multiple Cox regression models for CV risk factors and GFR. The incremental predictive value of TPD was examined using Harrell's c-index, net reclassification index (NRI), and integrated discrimination index (IDI). RESULTS: Over a median follow-up of 5 years (25th to 75th percentiles, 3.0-6.5 years), 1,692 (14.5%) patients experienced CD/MI (740 MI and 1,182 CD). In a multivariable model adjusted for traditional CV risk factors and GFR, the presence of a perfusion defect was independently associated with increased risk of CD/MI (HR = 2.10; 95% CI 1.81, 2.43, p < .001). Using Cox regression, TPD improved the discriminatory ability beyond traditional CV risk factors and GFR [from AUC = 0.725, (95% CI 0.712-0.738) to 0.784, (95% CI 0.772-0.796), p < .0001]. Furthermore, TPD improves risk stratification of CKD patients over and above traditional CV risk factors and GFR [NRI = 14%, 95% CI (12%-16%, p < .001) and relative IDI = 60%, 95% CI (51%, 66%, p < .001)]. CONCLUSIONS: Across the spectrum of renal function, SPECT-MPI perfusion defects independently and incrementally reclassified patients for their risk of CD/MI, beyond traditional CV risk factors.

Cardiorespiratory fitness and incident heart failure: The Henry Ford ExercIse Testing (FIT) Project.

BACKGROUND: Prior studies have demonstrated cardiorespiratory fitness (CRF) to be a strong marker of cardiovascular health. However, there are limited data investigating the association between CRF and risk of progression to heart failure (HF). The purpose of this study was to determine the relationship between CRF and incident HF. METHODS: We included 66,329 patients (53.8% men, mean age 55 years) free of HF who underwent exercise treadmill stress testing at Henry Ford Health Systems between 1991 and 2009. Incident HF was determined using International Classification of Diseases, Ninth Revision codes from electronic medical records or administrative claim files. Cox proportional hazards models were performed to determine the association between CRF and incident HF. RESULTS: A total of 4,652 patients developed HF after a median follow-up duration of 6.8 (±3) years. Patients with incident HF were older (63 vs 54 years, P<.001) and had higher prevalence of known coronary artery disease (42.3% vs 11%, P<.001). Peak metabolic equivalents (METs) of task were 6.3 (±2.9) and 9.1 (±3) in the HF and non-HF groups, respectively. After adjustment for potential confounders, patients able to achieve ≥12 METs had an 81% lower risk of incident HF compared with those achieving <6 METs (hazard ratio 0.19 [95% CI 0.14-0.29], P for trend < .001). Each 1 MET achieved was associated with a 16% lower risk (hazard ratio 0.84 [95% CI 0.82-0.86], P<.001) of incident HF. CONCLUSIONS: Our analysis demonstrates that higher level of fitness is associated with a lower incidence of HF independent of HF risk factors.

The role of myocardial viability in contemporary cardiac practice.

Ischemic heart disease (IHD) remains the single most common cause of death worldwide. Ischemic cardiomyopathy is a major sequel of coronary artery disease. The economic health burden of IHD is substantial. In patients with old myocardial infarction (OMI), the extent of viable myocardium (VM) directly affects the short- and long-term outcome. There is a considerable collection of observational data showing substantial improvement in patients with significant left ventricular dysfunction when the need for revascularization is guided by preoperative assessment of viability and hibernation. However, a major challenge for present cardiovascular imaging is to identify better ways to assess viable but inadequately perfused myocardium and thus optimize selection of patients for coronary revascularization. Several non-invasive techniques have been developed to detect signs of viability. Hence, our aim is to provide the reader a state-of-the art review for the assessment of myocardial viability.

Comparison of machine learning techniques to predict all-cause mortality using fitness data: the Henry ford exercIse testing (FIT) project.

BACKGROUND: Prior studies have demonstrated that cardiorespiratory fitness (CRF) is a strong marker of cardiovascular health. Machine learning (ML) can enhance the prediction of outcomes through classification techniques that classify the data into predetermined categories. The aim of this study is to present an evaluation and comparison of how machine learning techniques can be applied on medical records of cardiorespiratory fitness and how the various techniques differ in terms of capabilities of predicting medical outcomes (e.g. mortality). METHODS: We use data of 34,212 patients free of known coronary artery disease or heart failure who underwent clinician-referred exercise treadmill stress testing at Henry Ford Health Systems Between 1991 and 2009 and had a complete 10-year follow-up. Seven machine learning classification techniques were evaluated: Decision Tree (DT), Support Vector Machine (SVM), Artificial Neural Networks (ANN), Naïve Bayesian Classifier (BC), Bayesian Network (BN), K-Nearest Neighbor (KNN) and Random Forest (RF). In order to handle the imbalanced dataset used, the Synthetic Minority Over-Sampling Technique (SMOTE) is used. RESULTS: Two set of experiments have been conducted with and without the SMOTE sampling technique. On average over different evaluation metrics, SVM Classifier has shown the lowest performance while other models like BN, BC and DT performed better. The RF classifier has shown the best performance (AUC = 0.97) among all models trained using the SMOTE sampling. CONCLUSIONS: The results show that various ML techniques can significantly vary in terms of its performance for the different evaluation metrics. It is also not necessarily that the more complex the ML model, the more prediction accuracy can be achieved. The prediction performance of all models trained with SMOTE is much better than the performance of models trained without SMOTE. The study shows the potential of machine learning methods for predicting all-cause mortality using cardiorespiratory fitness data.

Predictors of delayed pre-hospital presentation among patients with ST-segment elevation myocardial infarction.

BACKGROUND: Early treatment of ST elevation myocardial infarction (STEMI) is essential to improve survival of these patients. However, not all patients present early enough to receive optimal treatment especially in third world countries. Social factors affecting early vs. late treatment have not been studied, particularly in the Middle East. Thus, the aim of this study was to determine the social factors associated with delayed presentation of STEMI patients. METHODS: All patients with STEMI presenting to King Abdulaziz Cardiac Center (KACC) between October 2013 and July 2014 were approached. After obtaining consent, patients were interviewed regarding their psychosocial circumstances using a standardized questionnaire. Their medical charts were also reviewed for further clinical data. Patients were divided according to their symptom-to-door time into early ( ≤ 6h) and late (>6h) presentation and group comparisons were conducted. RESULTS: A total of 79 patients were enrolled, of which 24 patients (30%) presented late. Patients with increased symptom-to-door time had higher prevalence of diabetes (40% vs. 79.2%, p = 0.001), hypertension (43.6% vs. 70.8%, p = 0.023), and dyslipidemia (23.6% vs. 54.2%, p = 0.009). Most of the late presenters did not undergo primary coronary intervention (72.7% vs. 47.8%, P = 0.034) and had less prior information about myocardial infarction (43.6% vs. 25%, P = 0.023). Late presenters were more often illiterates and lived most often far away from the hospital. Using multivariate logistic regression; dyslipidemia was the only independent predictor for the late hospital presentation for STEMI patients. CONCLUSION: One third of patients with STEMI present more than six hours after symptom onset; these patients have a higher prevalence of coronary risk factors and less information about STEMI. Programs should be designed to educate patients and the general public about the symptoms of STEMI and the necessary action to be taken if a heart attack is suspected.

Noninvasive Ventilation in Critically Ill Patients With Severe Acute Respiratory Infections.

BACKGROUND: The objective of this study was to evaluate the association between noninvasive ventilation (NIV) compared with invasive ventilation and mortality in subjects with severe acute respiratory infection. METHODS: This was a retrospective multi-center study of subjects with severe acute respiratory infection treated with ventilatory support between September 2012 and June 2018. We compared the 90-d mortality of subjects managed initially with NIV (NIV group) with those managed with invasive ventilation only (invasive ventilation group), adjusting by propensity score. RESULTS: Of 383 subjects, 189 (49%) were in the NIV group and 194 (51%) were in the invasive ventilation group. Of the subjects initially treated with NIV, 117 (62%) were eventually intubated. Crude 90-d mortality was lower in the NIV group versus the invasive ventilation group (42 [22.2%] vs 77 [39.7%]; P < .001). After propensity score adjustment, NIV was associated with lower 90-d mortality than invasive ventilation (odds ratio 0.54, 95% CI 0.38-0.76; P < .001). The association of NIV with mortality compared with invasive ventilation was not different across the studied subgroups. CONCLUSIONS: In subjects with severe acute respiratory infection and acute respiratory failure, NIV was commonly used. NIV was associated with a lower 90-d mortality. The observed high failure rate suggests the need for further research to optimize patient selection and facilitate early recognition of NIV failure.

Outcomes of patients admitted to the intensive care unit with community-acquired pneumonia in a tertiary care center in Riyadh, Saudi Arabia.

BACKGROUND: Community-acquired pneumonia (CAP) is a leading cause of intensive care unit (ICU) morbidity and mortality. Despite extensive international epidemiological and clinical studies to improve those patients' outcomes, local statistics in Saudi Arabia are limited. The objective of this study is to describe the clinical characteristics and outcomes of patients admitted to the ICU with the diagnosis of CAP reflecting the experience of a tertiary center over an 18-year period. METHODS: A retrospective cohort study included all consecutive adult ICU patients diagnosed with CAP between 1999 and 2017. Baseline demographics, patients' risk factors, and initial admission laboratory investigations were compared between survivors and nonsurvivors. A multivariate regression model was used to predict mortality. RESULTS: During the study period, there were 3438 patients admitted to the ICU with CAP (median age 67 [Quartile 1, 3 (Q1, Q3) 51, 76] years) and 54.4% were males, of whom 1007 (29.2%) died. The survivors compared with nonsurvivors were younger (65 vs. 70 years), less likely to have chronic liver disease (2.4% vs. 10.5%), chronic renal failure (8.1% vs. 14.4%), and be immunocompromised (10.2% vs. 18.2%), and less frequently required mechanical ventilation or vasopressors (46.2% vs. 80.5% and 29.6% vs. 55.9%, respectively). Acute Physiology and Chronic Health Evaluation (APACHE) II score was significantly higher among nonsurvivors (median score 26 vs. 20) with a longer duration of mechanical ventilation and ICU stay. Using a multivariate regression model, age, APACHE II score, bilirubin level, vasopressors, and mechanical ventilation were significantly associated with increased mortality, while diabetes was associated with lower mortality. CONCLUSION: Around one-third of patients admitted to the ICU with CAP died. Mortality was significantly associated with age, APACHE II score, vasopressor use, and mechanical ventilation. A comprehensive national registry is needed to enhance epidemiological data and to guide initiatives for improving CAP patients' outcomes.

Association of Twitter Metrics and Cardiology and Heart Surgery National Hospital Rankings.

Since 1990, the U.S. News and World Report (USNWR) has been publishing rankings of US adult and children's hospitals. The aim of this study was to analyze the association between hospital Twitter metrics and the 2020 USNWR hospital cardiology and heart surgery ranking. We collected data on the cardiology and heart surgery overall ranking score and expert opinion. Twitter metrics were obtained on October 20, 2020, and included time on Twitter, number of followers, accounts being followed, total tweets, reach score (difference between followers and followed), and annual tweet rate (total tweets divided by time on Twitter). The final cohort consisted of 463 hospitals (48 of which were top-ranking hospitals). A significant positive relation was observed with Twitter metrics and hospital ranking. On multivariable regression after adjusting for time on Twitter, the overall score was independently associated with annual tweet rate and reach score (ß=12.45% and ß=0.34% for each 1,000 tweets per year and 10,000 reach score accounts; P<.001). Similarly, expert opinion was independently associated with annual tweet rate and reach score (ß=0.025% and ß=0.002% for each 1000 tweets per year and 10,000 reach score accounts; P<.001). Our results emphasize how hospital leaders may leverage social media platforms as an important medium to disseminate accomplishments and increase their visibility and reputation, potentially translating to higher USNWR ranking.

Prognostic Value of Cardiorespiratory Fitness in Patients with Chronic Kidney Disease: The FIT (Henry Ford Exercise Testing) Project.

PURPOSE: We conducted this study to investigate the association of cardiorespiratory fitness and all-cause mortality among patients with chronic kidney disease. METHODS: We studied a retrospective cohort of patients from the Henry Ford Health System who underwent clinically indicated exercise stress testing with baseline cardiorespiratory fitness and estimated glomerular filtration rate measurement. Cardiorespiratory fitness was expressed as metabolic equivalents of task, and kidney function was categorized into stages according to estimated glomerular filtration rate. Multivariable-adjusted Cox proportional hazard models were used to examine the association between metabolic equivalents of task and all-cause mortality among patients with chronic kidney disease stages 3-5. Discrimination of mortality was assessed using receiver operating characteristic curves, while reclassification was evaluated using net reclassification index (NRI). RESULTS: Among 50,121 participants, the mean age was 55 ± 12.6 years; 47.5% were women, 64.5% were white, and 6877 (13.7%) participants had chronic kidney disease stage 3-5. Over a median follow-up of 6.7 years, 6308 participants died (12.6%). Each 1-unit higher metabolic equivalents of task was associated with a significant 15% reduction in all-cause mortality (hazard ratio 0.85; 95% confidence interval [CI], 0.84-0.87). Metabolic equivalents of task improved discriminatory ability of mortality prediction when added to traditional risk factors and estimated glomerular filtration rate (area under the curve 0.7996; 95% CI, 0.789-0.810 vs 0.759; 95% CI, 0.748-0.770, respectively; P < .001). The addition of metabolic equivalents of task to traditional risk factors resulted in significant reclassification (6% for events, 5% for non-events: NRI = 0.13, P < .001). CONCLUSIONS: Cardiorespiratory fitness improves mortality risk prediction among patients with chronic kidney disease. Cardiorespiratory fitness provides incremental prognostic information when added to traditional risk factors and may help guide treatment options among patients with renal dysfunction.

30-year follow-up of an unoperated left atrial myxoma: a case report.

BACKGROUND: Cardiac myxomas are the most common benign primary cardiac tumours. The natural history of left cardiac myxomas is thought to be of slowly growing tumours. Cardiac myxomas are a heterogeneous group with a variable growth rate. They present usually with stroke, valve obstruction, or non-specific symptoms. Surgical resection is the effective treatment. CASE SUMMARY: This case report describes a 56-year-old hypertensive and dyslipidaemic female, when she was admitted in January 1990, complaining of loss of appetite, aches, pains, and palpitations. Her workup included a transthoracic echocardiography and transoesophageal echocardiography, which showed a left atrial mass attached to the inter-atrial septum, highly suggestive of left atrial myxoma. She was referred for surgical removal of the left atrial mass. However, she was reluctant to undergo surgery as she felt better. The patient was followed-up for almost 30 years with the left atrial mass confirmed as left atrial myxoma by cardiac magnetic resonance imaging. The left atrial mass became smaller in size and more calcified. DISCUSSION: Cardiac myxomas are a group of heterogeneous tumours, thought to be slowly growing. The growth rate of cardiac myxomas prior to diagnosis is not well known, as the vast majority is treated with surgical resection immediately after diagnosis. Our case showed the natural progression of an unoperated smooth-surfaced left atrial myxoma followed-up for almost 30 years, which slowly became smaller and more calcified.

Native valve fungal endocarditis caused by Aspergillus fumigatus: management dilemma.

Fungal endocarditis (FE) accounts for ~50% of the mortality rate associated with predisposing host conditions. Despite optimal therapeutic strategies, the survival rate remains low. FE is mostly caused by Candida albicans and Aspergillus fumigatus. Previous valvular surgery is the most essential risk factor for Aspergillus endocarditis, which observed in 40-50% of cases. However, native valve FE caused by Aspergillus is uncommon, with only a few reported cases. We hereby report a case of native valve FE caused by A. fumigatus with complications following Wegener's disease and prostate cancer. The patient survived after successful management with the combination of surgical and medical therapy. Aspergillus endocarditis is a rare and fatal fungal infection. Despite difficulties in diagnosis and treatment, medical intervention with antifungal therapy and immediate surgical intervention are essential to achieve desirable outcomes.

Predictors of in-hospital length of stay among cardiac patients: A machine learning approach.

OBJECTIVE: The In-hospital length of stay (LOS) is expected to increase as cardiovascular diseases complexity increases and the population ages. This will affect healthcare systems especially with the current situation of decreased bed capacity and increasing costs. Therefore, accurately predicting LOS would have a positive impact on healthcare metrics. The aim of this study is to develop a machine learning-based model approach for predicting in-hospital LOS for cardiac patients. DESIGN: Using electronic medical records, we retrospectively extracted all records of patients' visits that were admitted under adult cardiology service. Admission diagnosis and primary treating physician were reviewed to verify selection criteria. A predictive machine learning-based model approach was applied to incorporate simple baseline health data at admission time to predict LOS. Patients were divided into three groups based on their LOS: short (<3 days), intermediate (3-5 days) and long (>5 days). Information gain algorithm was utilized to select the most relevant attributes. Only attributes with information gain of more than zero were used in model building. Four different machine learning techniques were evaluated and their diagnostic accuracy measures were compared. SETTING: The dataset of this study included adult patients who were admitted between 2008 and 2016 in King Abdulaziz Cardiac Center (KACC). The center is located in King Abdulaziz Medical City Complex in Riyadh, the capital of Saudi Arabia. PARTICIPANTS (DATASET): A total of 16,414 consecutive inpatient visits for 12,769 unique patients (mean age of 58.8 ±â€¯16 years of which 68.2% were males) between 2008 and 2016 were included. The study cohort had a high prevalence of cardiovascular risk factors (hypertension 56%, diabetes 56%, dyslipidemia 52%, obesity 33% and smoking 24%). The most common admitting diagnosis was acute coronary syndrome (36%). RESULTS: The variables with highest impact on the prediction of in-hospital LOS were on admission heart rate, on admission systolic and diastolic blood pressure, age and insurance status (eligibility). Using machine learning models; Random Forest (RF) model outperformed among all other models (sensitivity (0.80), accuracy (0.80), and AUROC (0.94)). CONCLUSION: We showed that machine learning methods provide accurate prediction of LOS for cardiac patients. This is can be used in clinical bed management and resources allocation.

Predictors of Coronary Artery Disease Progression among High-risk Patients with Recurrent Symptoms.

BACKGROUND: Despite the availability of new potent medical therapies, the rate of progression of angiographic coronary artery disease (CAD) is not well described. The aim of this analysis is to describe the rate and predictors of progression of CAD among patients with recurrent symptoms. MATERIALS AND METHODS: We reviewed 259 patients (mean age 61 ± 11 years, 70% males) who underwent two coronary angiograms between 2008 and 2013. Progressive CAD was defined as obstructive CAD in a previously disease-free segment or new obstruction in a previously nonobstructive segment. Patients who had coronary artery bypass surgery between these two angiograms were excluded from the analysis. Multivariate logistic regression was used to determine the independent predictors of progression of CAD. RESULTS: The included cohort had a high prevalence of coronary risk factors; hypertension (71%), diabetes (69%), and dyslipidemia (75%). Despite adequate medical therapy, more than half of the patients (61%) had CAD progression. Using multivariate logistic regression, a drop in the left ventricular ejection fraction (LVEF) by more than 5% was the predictor of CAD progression (adjusted odds ratio 5.8, P = 0.042, 95% confidence interval 1.1-31.2). CONCLUSION: Among high-risk patients with recurrent symptoms, the short-term rate of progression of CAD is high. A drop in LVEF >5% is a predictor of CAD progression. Further studies are needed to determine the prognostic value of CAD progression in the era of potent medical therapy.

Prognostic value of exercise capacity among patients with treated depression: The Henry Ford Exercise Testing (FIT) Project.

BACKGROUND: Exercise capacity is associated with survival in the general population. Whether this applies to patients with treated depression is not clear. HYPOTHESIS: High exercise capacity remains associated with lower risk of all-cause mortality (ACM) and nonfatal myocardial infraction (MI) among patients with treated depression. METHODS: We included 5128 patients on antidepressant medications who completed a clinically indicated exercise stress test between 1991 and 2009. Patients were followed for a median duration of 9.4 years for ACM and 4.5 years for MI. Exercise capacity was estimated in metabolic equivalents of tasks (METs). Cox proportional hazards regression models were used. RESULTS: Patients with treated depression who achieved ≥12 METs (vs those achieving <6 METs) were younger (age 46 ± 9 vs 61 ± 12 years), more often male (60% vs 23%), less often black (10% vs 27%), and less likely to be hypertensive (51% vs 86%), have DM (9% vs 38%), or be obese (11% vs 36%) or dyslipidemic (45% vs 54%). In the fully adjusted Cox proportional hazard regression model, exercise capacity was associated with a lower ACM (HR per 1-MET increase in exercise capacity: 0.82, 95% CI: 0.79-0.85, P < 0.001) and nonfatal MI (HR: 0.92, 95% CI: 0.87-0.97, P = 0.004). CONCLUSIONS: Exercise capacity had an inverse association with both ACM and nonfatal MI in patients with treated depression, independent of cardiovascular risk factors. These results highlight the potential impact of assessing exercise capacity to identify risk, as well as promoting an active lifestyle among treated depression patients.

Multimodality Imaging of Pericardial Diseases.

OPINION STATEMENT: Pericardial diseases have changed their epidemiology in the past few years. With the aging population and decreasing incidence of communicable diseases, the causes of pericardial diseases have significantly changed from infectious and malignant to postradiation and cardiac surgery causes. Despite that, pericardial diseases remain difficult to diagnose. The accurate and timely diagnosis of these diseases is essential to avoid the late sequela of pericardial constriction and pericardial cirrhosis. Echocardiography remains the first test of choice for the assessment of patients with suspected pericardial diseases. Most patients with acute pericarditis have a self-limiting course and do not need further imaging. However, in the era of multimodality imaging, other modalities, namely, computed tomography (CT) and magnetic resonance imaging (CMR), are often utilized in complex cases. These two modalities provide a wide-open view of the pericardium and adjacent structures. They have high resolution to assess pericardial calcification, a hallmark of many diseases especially tuberculous constrictive pericarditis. CMR is also unique in its ability to assess pericardial late gadolinium enhancement (LGE) and edema. These have been recently suggested to be very important in the progression from acute pericarditis to constrictive pericarditis. In addition, they provide prognostic value to assess which patients are at high risk of developing heart failure and resource utilization. Thus, in the current era, patients with suspected complex pericardial diseases will need a multimodality approach rather than a single modality approach.

Low-dose attenuation correction in diagnosis of non-alcoholic fatty liver disease.

BACKGROUND: Non-enhanced computed tomography (CT) is a valuable modality in the diagnosis of non-alcoholic fatty liver disease (NAFLD). However, it is not clear if low-dose CT attenuation correction (CTAC) scans have the same accuracy to diagnose NAFLD. Our aim is to evaluate the diagnostic accuracy of low-dose CTAC in the diagnosis of NAFLD using non-enhanced CT as a gold standard. METHODS: A total of 864 patients who underwent a clinically indicated hybrid nuclear imaging scanning between May 2011 and April 2014 were included in the study. Diagnosis of fatty liver was established if an absolute liver attenuation was <40 Hounsfield units and/or a liver-to-spleen ratio was <1.1. The diagnostic accuracy parameters were calculated to detect NAFLD by low-dose CTAC using unenhanced CT as a gold standard. RESULTS: The prevalence of fatty liver by diagnostic CT and low-dose attenuation correction were 9.9 and 12.9% (using liver attenuation <40HU and liver-to-spleen ratio <1.1), respectively, with 32.9 and 34.9% (using absolute liver attenuation or ratio-to-spleen criteria), correspondingly. Low-dose CTAC had sensitivity (81.3%), specificity (94.0%), positive predictive value (60.2%), and negative predictive value (97.8%) using both diagnostic criteria. Using either of the diagnostic criteria resulted in sensitivity (76.8%), specificity (83.5%), PPV (66.3%), and NPV (89.5%). CONCLUSION: Low-dose CT could be used as a tool to rule out the presence of fatty liver if neither liver attenuation of less than 40 HU nor liver-to-spleen below 1.1 is present.

Cardiovascular risk factors burden in Saudi Arabia: The Africa Middle East Cardiovascular Epidemiological (ACE) study.

BACKGROUND: Limited data exist on the epidemiology of cardiovascular risk factors in Saudi Arabia, particularly in relation to the differences between Saudi nationals and expatriates in Saudi Arabia. The aim of this analysis was to describe the current prevalence of cardiovascular risk factors among patients attending general practice clinics across Saudi Arabia. METHODS: In this cross-sectional epidemiological analysis of the Africa Middle East Cardiovascular Epidemiological (ACE) study, the prevalence of cardiovascular risk factors (hypertension, diabetes, dyslipidemia, obesity, smoking, abdominal obesity) was evaluated in adults attending primary care clinics in Saudi Arabia. Group comparisons were made between patients of Saudi ethnicity (SA nationals) and patients who were not of Saudi ethnicity (expatriates). RESULTS: A total of 550 participants were enrolled from different clinics across Saudi Arabia [aged (mean ± standard deviation) 43 ± 11 years; 71% male]. Nearly half of the study cohort (49.8%) had more than three cardiovascular risk factors. Dyslipidemia was the most prevalent risk factor (68.6%). The prevalence of hypertension (47.5%) and dyslipidemia (75.5%) was higher among expatriates when compared with SA nationals (31.4% vs. 55.1%, p = 0.0003 vs. p < 0.0001, respectively). Conversely, obesity (52.6% vs. 41.0%; p = 0.008) and abdominal obesity (65.5% vs. 52.2%; p = 0.0028) were higher among SA nationals vs. expatriates. CONCLUSION: Modifiable cardiovascular risk factors are highly prevalent in SA nationals and expatriates. Programmed community-based screening is needed for all cardiovascular risk factors in Saudi Arabia. Improving primary care services to focus on risk factor control may ultimately decrease the incidence of coronary artery disease and improve overall quality of life. The ACE trial is registered under NCT01243138.

The impact of digoxin on mortality in patients with chronic systolic heart failure: A propensity-matched cohort study.

BACKGROUND: Prior Studies showed mixed results in association of digoxin use with all-cause mortality (ACM). The aim of this analysis is to identify the impact of digoxin use on ACM in a contemporary heart failure (HF) cohort treated with guideline based therapy. METHODS: We included 2298 consecutive patients seen in an HF clinic between 2000 and 2015. Patients were considered to be a digoxin user if he/she received digoxin at any point during the enrollment period in the HF clinic. Patients were matched based on digoxin utility using propensity matching in 2-3:1 fashion. The primary outcome was ACM. RESULT: Of 2298 patients, 325 digoxin users were matched with 750 non-digoxin users. The Matched cohort did not have differences among demographics and clinical variables except for worse HF symptomatology and increased prevalence of atrial fibrillation. Overall, the prevalence of the use of guideline suggested therapies was 96%. After a median follow-up duration of 4years (IQR 2-6years), digoxin use was associated with increased ACM (21.8% versus 12.9%, unadjusted HR=1.81; 95% CI=1.33 to 2.45; p=0.001). This association remained significant after adjusting for the propensity score, atrial fibrillation, ejection fraction, and New York HF Class (HR=1.74; 95% CI=1.20 to 2.38; p<0.0001). CONCLUSION: In this analysis of well-treated HF patients, digoxin was associated with increased ACM. Further randomized controlled trials are needed to determine whether digoxin therapy should be used in well-treated HF patients. Until then, routine use of digoxin in clinical practice should be discouraged.