Survey of Primary Care Physicians Perception on Diagnosis and Management of Congestive Heart Failure in Lagos, Nigeria.

Purpose: To evaluate the perception of primary care physicians on diagnosis and management of congestive cardiac failure in Lagos, Nigeria Method: A slightly modified questionnaire used in the Euro-F study was distributed to primary care physicians in randomly selected hospitals in randomly selected local government in the Lagos metropolis. Result: Response rate to the questionnaire was 50%. There was poor (25%) record keeping of heart failure patients among the group. The commonest symptoms used by the primary care physicians for diagnosis were pedal swelling (74%). The favored signs were pedal oedema (62%) and basal crepitations (39%). There was poor knowledge of symptoms when these were categorized using the Framingham criteria. Only 32% knew two major criteria and less than 50% knew three minor criteria. Majority of the diagnosis of heart failure was based on symptoms and signs, (62.91± 29.57), with minimal reliance on investigation, (12.58± 20.75). Commonest investigations performed were electrocardiogram, (75%) and chest X-ray (91%). The use of echocardiography was quite low in this study (16%). There was poor knowledge regarding ACE-inhibitor use, (32.82± 37.54) and adequate doses. The knowledge about the beneficial effects of ACE inhibitors on symptom relief (37%) and reduction in mortality (42%) was poor. The knowledge about the use of b-blockers in heart failure was also poor. Majority of the physicians favoured use of diuretics and cardiac glycosides. They had correct knowledge about their effects on symptom relief, diuretics, (80%) and cardiac glycosides (72%). They wrongly asserted that mortality is reduced with diuretics, (61%) and cardiac glycosides (65%). Conclusion: There is poor knowledge among the primary care physicians as regards diagnosis and the management of congestive cardiac failure. Continuing medical education is therefore of paramount importance for these physicians in view of the importance of this disease entity and rapid emergence of new information in all aspects of heart failure. Keywords: Primary care Physicians, Diagnosis, Management, Heart failure.NQJHM Vol. 14 (2) 2004: pp. 130-13

Blood Pressure, Heart Rate, Cardiovascular Reflexes and Electrocardiographic changes in some Hypertensive Nigerians

The effects of hypertension on resting and reflex cardiovascular function were investigated in this study. Blood pressure, heart rate and electrocardiogram were recorded in male and female control subjects and hypertensive Nigerian patients. Blood pressure was measured, using the sphygmomanometer/auscultatory method. Heart rate was determined from palpating the radial pulse or from the resting electrocardiograph. The systolic and diastolic blood pressures were high in the hypertensive patient (160.90 ± 2.06 mmHg and 110.8 ± 1.95 mmHg respectively compared with control subjects (119.3 ± 2.05 and 73.58 ± 1.09mmHg; P<0.01). Pulse pressure and mean arterial pressures were also higher in the hypertensive patients. Heart rate was higher in the hypertensive compared to the control groups (86.93 ±+ 2.83 cf 71 ± 1.35 beats per minute, P<0.01). ECG analysis showed that the intervals were lower in the controls than in the hypertensive group except for PR intervals (0.21 ± 0.01 cf 0.23 ± 0.01 sec). The amplitude of the waves was also lower in the control group than the hypertensive group. Cardiovascular response to exercise assessed from the post-exercise recovery graph showed that the aggregate recovery (6min after) was lower in the hypertensive subjects (22% cf 28%, p<0.05) than in controls. This suggests that the baroreflex sensitivity was higher in the control than in the hypertensive subjects. Results from this study suggest that in hypertension there may be increased heart rate, altered electrocardiograph readings indicating ventricular hypertrophy and delay in ventricular conduction. In hypertension baroreflex sensitivity may be reduced

Orlistat vs Placebo in the Inhibition of Dietary Fat in Obese Adult Nigerian Volunteers

Objective: To compare the efficacy and safety of orlistat (120mg tid) versus placebo in the inhibition of dietary fat absorption in healthy adult Nigerian volunteers. Method: This was a double blind randomised cross-over study, with each arm of the cross-over lasting 4 weeks with a one week placebo run-in period before and in-between treatment. Four males and 16 females, with a mean BMI of 35.1 and a mean age of 40.08 years, participated in the study. Prior to allocation to treatment, subjects were given placebo for a 7-day period, while receiving a moderate hypocaloric supporting diet as prescribed for each individual by the dietician. During this period, a 72-hour faeces was collected from each subject for estimation of baseline faecal fat excretion. Additionally blood and urine samples were collected for evaluation of plasma lipid profile, haemogram, blood chemistry and urinalysis. Subjects were assigned to treatment according to their enrolment number i. e. subject no. 1 received treatment labelled DBN 1. Each subject was given a weekly pack of medication as specified in the label. The subjects took one capsule three times a day with the prescribed diet. At the end of each week of treatment, subjects were required to submit 24-hr faeces for faecal fat estimation. Blood samples were collected at week 5 and week 10 for haematological profile, lipid profile, blood chemistry and liver function tests. At each weekly clinical visit, subjects were questioned closely on the incidence of any adverse event, they also discussed their diet with the dietician. At the end of the study the emergency code envelopes were opened and the subjects were assigned into groups according to the treatment sequence, the sequence Placebo/ Orlistat were assigned group 1 and Orlistat/ Placebo group 2. Results: The difference in faecal fat excretion with orlistat compared to placebo was significant (

Integration of estimated glomerular filtration rate biomarker in image-based cardiovascular disease/stroke risk calculator: A South Asian-Indian diabetes cohort with moderate chronic kidney disease

Background: Recently, a 10-year image-based integrated calculator (called AtheroEdge Composite Risk Score-AECRS1.0) was developed which combines conventional cardiovascular risk factors (CCVRF) with image phenotypes derived from carotid ultrasound (CUS). Such calculators did not include chronic kidney disease (CKD)-based biomarker called estimated glomerular filtration rate (eGFR). The novelty of this study is to design and develop an advanced integrated version called-AECRS2.0 that combines eGFR with image phenotypes to compute the composite risk score. Furthermore, AECRS2.0 was benchmarked against QRISK3 which considers eGFR for risk assessment. Methods: The method consists of three major steps: 1) five, current CUS image phenotypes (CUSIP) measurements using AtheroEdge system (AtheroPoint, CA, USA) consisting of: average carotid intima-media thickness (cIMTave), maximum cIMT (cIMTmax), minimum cIMT (cIMTmin), variability in cIMT (cIMTV), and total plaque area (TPA); 2) five, 10-year CUSIP measurements by combining these current five CUSIP with 11 CCVRF (age, ethnicity, gender, body mass index, systolic blood pressure, smoking, carotid artery type, hemoglobin, low-density lipoprotein cholesterol, total cholesterol, and eGFR); 3) AECRS2.0 risk score computation and its comparison to QRISK3 using area-under-the-curve (AUC). Results: South Asian-Indian 339 patients were retrospectively analyzed by acquiring their left/right common carotid arteries (678 CUS, mean age: 54.25±9.84 years; 75.22% males; 93.51% diabetic with HbA1c ≥6.5%; and mean eGFR 73.84±20.91 mL/min/1.73m2). The proposed AECRS2.0 reported higher AUC (AUC=0.89, P&lt;0.001) compared to QRISK3 (AUC=0.51, P&lt;0.001) by ~74% in CKD patients. Conclusions: An integrated calculator AECRS2.0 can be used to assess the 10-year CVD/stroke risk in patients suffering from CKD. AECRS2.0 was much superior to QRISK3

Integration of estimated glomerular filtration rate biomarker in image-based cardiovascular disease/stroke risk calculator: A South Asian-Indian diabetes cohort with moderate chronic kidney disease

Background: Recently, a 10-year image-based integrated calculator (called AtheroEdge Composite Risk Score-AECRS1.0) was developed which combines conventional cardiovascular risk factors (CCVRF) with image phenotypes derived from carotid ultrasound (CUS). Such calculators did not include chronic kidney disease (CKD)-based biomarker called estimated glomerular filtration rate (eGFR). The novelty of this study is to design and develop an advanced integrated version called-AECRS2.0 that combines eGFR with image phenotypes to compute the composite risk score. Furthermore, AECRS2.0 was benchmarked against QRISK3 which considers eGFR for risk assessment. Methods: The method consists of three major steps: 1) five, current CUS image phenotypes (CUSIP) measurements using AtheroEdge system (AtheroPoint, CA, USA) consisting of: average carotid intima-media thickness (cIMTave), maximum cIMT (cIMTmax), minimum cIMT (cIMTmin), variability in cIMT (cIMTV), and total plaque area (TPA); 2) five, 10-year CUSIP measurements by combining these current five CUSIP with 11 CCVRF (age, ethnicity, gender, body mass index, systolic blood pressure, smoking, carotid artery type, hemoglobin, low-density lipoprotein cholesterol, total cholesterol, and eGFR); 3) AECRS2.0 risk score computation and its comparison to QRISK3 using area-under-the-curve (AUC). Results: South Asian-Indian 339 patients were retrospectively analyzed by acquiring their left/right common carotid arteries (678 CUS, mean age: 54.25±9.84 years; 75.22% males; 93.51% diabetic with HbA1c ≥6.5%; and mean eGFR 73.84±20.91 mL/min/1.73m2). The proposed AECRS2.0 reported higher AUC (AUC=0.89, P&amp;lt;0.001) compared to QRISK3 (AUC=0.51, P&amp;lt;0.001) by ~74% in CKD patients. Conclusions: An integrated calculator AECRS2.0 can be used to assess the 10-year CVD/stroke risk in patients suffering from CKD. AECRS2.0 was much superior to QRISK3. © 2020 EDIZIONI MINERVA MEDICA

Morphological Carotid Plaque Area Is Associated With Glomerular Filtration Rate: A Study of South Asian Indian Patients With Diabetes and Chronic Kidney Disease

We evaluated the association between automatically measured carotid total plaque area (TPA) and the estimated glomerular filtration rate (eGFR), a biomarker of chronic kidney disease (CKD). Automated average carotid intima–media thickness (cIMTave) and TPA measurements in carotid ultrasound (CUS) were performed using AtheroEdge (AtheroPoint). Pearson correlation coefficient (CC) was then computed between the TPA and eGFR for (1) males versus females, (2) diabetic versus nondiabetic patients, and (3) between the left and right carotid artery. Overall, 339 South Asian Indian patients with either type 2 diabetes mellitus (T2DM) or CKD, or hypertension (stage 1 or stage 2) were retrospectively analyzed by acquiring cIMTave and TPA measurements of their left and right common carotid arteries (CCA; total CUS: 678, mean age: 54.2 ± 9.8 years; 75.2% males; 93.5% with T2DM). The CC between TPA and eGFR for different scenarios were (1) for males and females −0.25 (P &lt;.001) and −0.35 (P &lt;.001), respectively; (2) for T2DM and non-T2DM −0.26 (P &lt;.001) and −0.49 (P =.02), respectively, and (3) for left and right CCA −0.25 (P &lt;.001) and −0.23 (P &lt;.001), respectively. Automated TPA is an equally reliable biomarker compared with cIMTave for patients with CKD (with or without T2DM) with subclinical atherosclerosis

Differences between familial and sporadic dilated cardiomyopathy: ESC EORP Cardiomyopathy & Myocarditis registry

Aims: Dilated cardiomyopathy (DCM) is a complex disease where genetics interplay with extrinsic factors. This study aims to compare the phenotype, management, and outcome of familial DCM (FDCM) and non-familial (sporadic) DCM (SDCM) across Europe. Methods and results: Patients with DCM that were enrolled in the prospective ESC EORP Cardiomyopathy & Myocarditis Registry were included. Baseline characteristics, genetic testing, genetic yield, and outcome were analysed comparing FDCM and SDCM; 1260 adult patients were studied (238 FDCM, 707 SDCM, and 315 not disclosed). Patients with FDCM were younger (P\ua0<\ua00.01), had less severe disease phenotype at presentation (P\ua0<\ua00.02), more favourable baseline cardiovascular risk profiles (P\ua0 64\ua00.007), and less medication use (P\ua0 64\ua00.042). Outcome at 1\ua0year was similar and predicted by NYHA class (HR 0.45; 95% CI [0.25\u20130.81]) and LVEF per % decrease (HR 1.05; 95% CI [1.02\u20131.08]. Throughout Europe, patients with FDCM received more genetic testing (47% vs. 8%, P\ua0<\ua00.01) and had higher genetic yield (55% vs. 22%, P\ua0<\ua00.01). Conclusions: We observed that FDCM and SDCM have significant differences at baseline but similar short-term prognosis. Whether modification of associated cardiovascular risk factors provide opportunities for treatment remains to be investigated. Our results also show a prevalent role of genetics in FDCM and a non-marginal yield in SDCM although genetic testing is largely neglected in SDCM. Limited genetic testing and heterogeneity in panels provides a scaffold for improvement of guideline adherence

Palm tocotrienol-rich fraction reduced plasma homocysteine and heart oxidative stress in rats fed with a high-methionine diet

Oxidative stress contributes to cardiovascular diseases. We aimed to study the effects of palm tocotrienol-rich fraction (TRF) on plasma homocysteine and cardiac oxidative stress in rats fed with a high-methionine diet. Forty-two male Wistar rats were divided into six groups. The first group was the control. Groups 2-6 were fed 1 % methionine diet for 10 weeks. From week 6 onward, folate (8 mg/kg diet) or palm TRF (30, 60 and 150 mg/kg diet) was added into the diet of groups 3, 4, 5 and 6. The rats were then killed. Palm TRF at 150 mg/kg and folate supplementation prevented the increase in plasma total homocysteine (4.14 ± 0.33 and 4.30 ± 0.26 vs 5.49 ± 0.25 mmol/L, p < 0.05) induced by a high-methionine diet. The increased heart thiobarbituric acid reactive substance in rats fed with high-methionine diet was also prevented by the supplementations of palm TRF (60 and 150 mg/kg) and folate. The high-methionine group had a lower glutathione peroxidase activity (49 ± 3 vs 69 ± 4 pmol/mg protein/min) than the control group. This reduction was reversed by palm TRF at 60 and 150 mg/kg diet (p < 0.05), but not by folate. Catalase and superoxide dismutase activities were unaffected by both methionine and vitamin supplementations. In conclusion, palm TRF was comparable to folate in reducing high-methionine diet-induced hyperhomocysteinemia and oxidative stress in the rats' hearts. However, palm TRF was more effective than folate in preserving the heart glutathione peroxidase enzyme activity

COVID-19 pathways for brain and heart injury in comorbidity patients: A role of medical imaging and artificial intelligence-based COVID severity classification: A review

Artificial intelligence (AI) has penetrated the field of medicine, particularly the field of radiology. Since its emergence, the highly virulent coronavirus disease 2019 (COVID-19) has infected over 10 million people, leading to over 500,000 deaths as of July 1st, 2020. Since the outbreak began, almost 28,000 articles about COVID-19 have been published (https://pubmed.ncbi.nlm.nih.gov); however, few have explored the role of imaging and artificial intelligence in COVID-19 patients—specifically, those with comorbidities. This paper begins by presenting the four pathways that can lead to heart and brain injuries following a COVID-19 infection. Our survey also offers insights into the role that imaging can play in the treatment of comorbid patients, based on probabilities derived from COVID-19 symptom statistics. Such symptoms include myocardial injury, hypoxia, plaque rupture, arrhythmias, venous thromboembolism, coronary thrombosis, encephalitis, ischemia, inflammation, and lung injury. At its core, this study considers the role of image-based AI, which can be used to characterize the tissues of a COVID-19 patient and classify the severity of their infection. Image-based AI is more important than ever as the pandemic surges and countries worldwide grapple with limited medical resources for detection and diagnosis

A narrative review on characterization of acute respiratory distress syndrome in COVID-19-infected lungs using artificial intelligence

COVID-19 has infected 77.4 million people worldwide and has caused 1.7 million fatalities as of December 21, 2020. The primary cause of death due to COVID-19 is Acute Respiratory Distress Syndrome (ARDS). According to the World Health Organization (WHO), people who are at least 60 years old or have comorbidities that have primarily been targeted are at the highest risk from SARS-CoV-2. Medical imaging provides a non-invasive, touch-free, and relatively safer alternative tool for diagnosis during the current ongoing pandemic. Artificial intelligence (AI) scientists are developing several intelligent computer-aided diagnosis (CAD) tools in multiple imaging modalities, i.e., lung computed tomography (CT), chest X-rays, and lung ultrasounds. These AI tools assist the pulmonary and critical care clinicians through (a) faster detection of the presence of a virus, (b) classifying pneumonia types, and (c) measuring the severity of viral damage in COVID-19-infected patients. Thus, it is of the utmost importance to fully understand the requirements of for a fast and successful, and timely lung scans analysis. This narrative review first presents the pathological layout of the lungs in the COVID-19 scenario, followed by understanding and then explains the comorbid statistical distributions in the ARDS framework. The novelty of this review is the approach to classifying the AI models as per the by school of thought (SoTs), exhibiting based on segregation of techniques and their characteristics. The study also discusses the identification of AI models and its extension from non-ARDS lungs (pre-COVID-19) to ARDS lungs (post-COVID-19). Furthermore, it also presents AI workflow considerations of for medical imaging modalities in the COVID-19 framework. Finally, clinical AI design considerations will be discussed. We conclude that the design of the current existing AI models can be improved by considering comorbidity as an independent factor. Furthermore, ARDS post-processing clinical systems must involve include (i) the clinical validation and verification of AI-models, (ii) reliability and stability criteria, and (iii) easily adaptable, and (iv) generalization assessments of AI systems for their use in pulmonary, critical care, and radiological settings