Cardiovascular risk assessment in patients with rheumatoid arthritis using carotid ultrasound B-mode imaging

Rheumatoid arthritis (RA) is a systemic chronic inflammatory disease that affects synovial joints and has various extra-articular manifestations, including atherosclerotic cardiovascular disease (CVD). Patients with RA experience a higher risk of CVD, leading to increased morbidity and mortality. Inflammation is a common phenomenon in RA and CVD. The pathophysiological association between these diseases is still not clear, and, thus, the risk assessment and detection of CVD in such patients is of clinical importance. Recently, artificial intelligence (AI) has gained prominence in advancing healthcare and, therefore, may further help to investigate the RA-CVD association. There are three aims of this review: (1) to summarize the three pathophysiological pathways that link RA to CVD; (2) to identify several traditional and carotid ultrasound image-based CVD risk calculators useful for RA patients, and (3) to understand the role of artificial intelligence in CVD risk assessment in RA patients. Our search strategy involves extensively searches in PubMed and Web of Science databases using search terms associated with CVD risk assessment in RA patients. A total of 120 peer-reviewed articles were screened for this review. We conclude that (a) two of the three pathways directly affect the atherosclerotic process, leading to heart injury, (b) carotid ultrasound image-based calculators have shown superior performance compared with conventional calculators, and (c) AI-based technologies in CVD risk assessment in RA patients are aggressively being adapted for routine practice of RA patients.

Cardiovascular/stroke risk predictive calculators: a comparison between statistical and machine learning models

Background

Statistically derived cardiovascular risk calculators (CVRC) that use conventional risk factors, generally underestimate or overestimate the risk of cardiovascular disease (CVD) or stroke events primarily due to lack of integration of plaque burden. This study investigates the role of machine learning (ML)-based CVD/stroke risk calculators (CVRC_ML) and compares against statistically derived CVRC (CVRC_Stat) based on (I) conventional factors or (II) combined conventional with plaque burden (integrated factors).

Methods

The proposed study is divided into 3 parts: (I) statistical calculator: initially, the 10-year CVD/stroke risk was computed using 13 types of CVRC_Stat (without and with plaque burden) and binary risk stratification of the patients was performed using the predefined thresholds and risk classes; (II) ML calculator: using the same risk factors (without and with plaque burden), as adopted in 13 different CVRC_Stat, the patients were again risk-stratified using CVRC_ML based on support vector machine (SVM) and finally; (III) both types of calculators were evaluated using AUC based on ROC analysis, which was computed using combination of predicted class and endpoint equivalent to CVD/stroke events.

Results

An Institutional Review Board approved 202 patients (156 males and 46 females) of Japanese ethnicity were recruited for this study with a mean age of 69±11 years. The AUC for 13 different types of CVRC_Stat calculators were: AECRS2.0 (AUC 0.83, P<0.001), QRISK3 (AUC 0.72, P<0.001), WHO (AUC 0.70, P<0.001), ASCVD (AUC 0.67, P<0.001), FRS_cardio (AUC 0.67, P<0.01), FRS_stroke (AUC 0.64, P<0.001), MSRC (AUC 0.63, P=0.03), UKPDS56 (AUC 0.63, P<0.001), NIPPON (AUC 0.63, P<0.001), PROCAM (AUC 0.59, P<0.001), RRS (AUC 0.57, P<0.001), UKPDS60 (AUC 0.53, P<0.001), and SCORE (AUC 0.45, P<0.001), while the AUC for the CVRC_ML with integrated risk factors (AUC 0.88, P<0.001), a 42% increase in performance. The overall risk-stratification accuracy for the CVRC_ML with integrated risk factors was 92.52% which was higher compared all the other CVRC_Stat.

Conclusions

ML-based CVD/stroke risk calculator provided a higher predictive ability of 10-year CVD/stroke compared to the 13 different types of statistically derived risk calculators including integrated model AECRS 2.0.

Ultrasound-based stroke/cardiovascular risk stratification using Framingham Risk Score and ASCVD Risk Score based on "Integrated Vascular Age" instead of "Chronological Age": a multi-ethnic study of Asian Indian, Caucasian, and Japanese cohorts

Background

Vascular age (VA) has recently emerged for CVD risk assessment and can either be computed using conventional risk factors (CRF) or by using carotid intima-media thickness (cIMT) derived from carotid ultrasound (CUS). This study investigates a novel method of integrating both CRF and cIMT for estimating VA [so-called integrated VA (IVA)]. Further, the study analyzes and compares CVD/stroke risk using the Framingham Risk Score (FRS)-based risk calculator when adapting IVA against VA.

Methods

The system follows a four-step process: (I) VA using cIMT based using linear-regression (LR) model and its coefficients; (II) VA prediction using ten CRF using a multivariate linear regression (MLR)-based model with gender adjustment; (III) coefficients from the LR-based model and MLR-based model are combined using a linear model to predict the final IVA; (IV) the final step consists of FRS-based risk stratification with IVA as inputs and benchmarked against FRS using conventional method of CA. Area-under-the-curve (AUC) is computed using IVA and benchmarked against CA while taking the response variable as a standardized combination of cIMT and glycated hemoglobin.

Results

The study recruited 648 patients, 202 were Japanese, 314 were Asian Indian, and 132 were Caucasians. Both left and right common carotid arteries (CCA) of all the population were scanned, thus a total of 1,287 ultrasound scans. The 10-year FRS using IVA reported higher AUC (AUC =0.78) compared with 10-year FRS using CA (AUC =0.66) by ~18%.

Conclusions

IVA is an efficient biomarker for risk stratifications for patients in routine practice.

Does the Carotid Bulb Offer a Better 10-Year CVD/Stroke Risk Assessment Compared to the Common Carotid Artery? A 1516 Ultrasound Scan Study

The objectives of this study are to (1) examine the "10-year cardiovascular risk" in the common carotid artery (CCA) versus carotid bulb using an integrated calculator called "AtheroEdge Composite Risk Score 2.0" (AECRS2.0) and (2) evaluate the performance of AECRS2.0 against "conventional cardiovascular risk calculators." These objectives are met by measuring (1) image-based phenotypes and AECRS2.0 score computation and (2) performance evaluation of AECRS2.0 against 12 conventional cardiovascular risk calculators. The Asian-Indian cohort (n = 379) with type 2 diabetes mellitus (T2DM), chronic kidney disease (CKD), or hypertension were retrospectively analyzed by acquiring the 1516 carotid ultrasound scans (mean age: 55 ± 10.1 years, 67% males, ∼92% with T2DM, ∼83% with CKD [stage 1-5], and 87.5% with hypertension [stage 1-2]). The carotid bulb showed a higher 10-year cardiovascular risk compared to the CCA by 18% (P < .0001). Patients with T2DM and/or CKD also followed a similar trend. The carotid bulb demonstrated a superior risk assessment compared to CCA in patients with T2DM and/or CKD by showing: (1) ∼13% better than CCA (0.93 vs 0.82, P = .0001) and (2) ∼29% better compared with 12 types of risk conventional calculators (0.93 vs 0.72, P = .06).

Cardiovascular/stroke risk prevention: A new machine learning framework integrating carotid ultrasound image-based phenotypes and its harmonics with conventional risk factors

MOTIVATION

Machine learning (ML)-based stroke risk stratification systems have typically focused on conventional risk factors (CRF) (AtheroRisk-conventional). Besides CRF, carotid ultrasound image phenotypes (CUSIP) have shown to be powerful phenotypes risk stratification. This is the first ML study of its kind that integrates CUSIP and CRF for risk stratification (AtheroRisk-integrated) and compares against AtheroRisk-conventional.

METHODS

Two types of ML-based setups called (i) AtheroRisk-integrated and (ii) AtheroRisk-conventional were developed using random forest (RF) classifiers. AtheroRisk-conventional uses a feature set of 13 CRF such as age, gender, hemoglobin A1c, fasting blood sugar, low-density lipoprotein, and high-density lipoprotein (HDL) cholesterol, total cholesterol (TC), a ratio of TC and HDL, hypertension, smoking, family history, triglyceride, and ultrasound-based carotid plaque score. AtheroRisk-integrated system uses the feature set of 38 features with a combination of 13 CRF and 25 CUSIP features (6 types of current CUSIP, 6 types of 10-year CUSIP, 12 types of quadratic CUSIP (harmonics), and age-adjusted grayscale median). Logistic regression approach was used to select the significant features on which the RF classifier was trained. The performance of both ML systems was evaluated by area-under-the-curve (AUC) statistics computed using a leave-one-out cross-validation protocol.

RESULTS

Left and right common carotid arteries of 202 Japanese patients were retrospectively examined to obtain 404 ultrasound scans. RF classifier showed higher improvement in AUC (~57%) for leave-one-out cross-validation protocol. Using RF classifier, AUC statistics for AtheroRisk-integrated system was higher (AUC = 0.99,p-value<0.001) compared to AtheroRisk-conventional (AUC = 0.63,p-value<0.001).

CONCLUSION

The AtheroRisk-integrated ML system outperforms the AtheroRisk-conventional ML system using RF classifier.

P956Improved quality of life and symptomatic atrial fibrillation reduction in patients treated with a standardized ablation index workflow

Background/Introduction

The use of a standardized ‘CLOSE’ ablation workflow for pulmonary vein isolation (PVI), with defined inter-tag distance (ITD) with targeted ablation index (AI) values, has been shown in single centre reports to result in good outcomes. The effect of this approach on patients’ quality of life (QoL) has not been studied.

Purpose

To evaluate the effects of paroxysmal atrial fibrillation (PAF) ablation by the CLOSE workflow on QoL and symptomatic AF reduction in the multicenter VISTAX study.

Methods

329 patients with PAF (61.5% male, 61.3 ± 10.1 year) were treated at 17 European centres by point-by-point radiofrequency ablation using the CLOSE protocol to achieve PVI.  An ITD ≤6mm and AI values of ≥400 on the posterior wall and ≥550 on the anterior wall were targeted. The AI value on the posterior wall was lowered as per investigator discretion in case of safety concerns. Patients were monitored for atrial arrhythmia recurrences via weekly and symptom-activated transtelephonic monitoring (TTM), for 12 months post procedure. Patients completed an Atrial Fibrillation Effect on Quality-of-life (AFEQT) questionnaire at their baseline and 12-month follow up visits.

Results

Majority (83.3% [274/329]) of patients experienced freedom from symptomatic atrial recurrence through 12 months. Of the 70 documented recurrences, 34 (49%) were documented by trans-telephonic monitoring only. All domains captured on the AFEQT questionnaire showed improvement with the overall score improving by 25.7, which exceeded the threshold of clinically meaningful improvement (±5) (Table). Patient reported most improvements in PAF control and symptoms relieved. The overall AFEQT score improvement was seen both in patients with or without documented atrial arrhythmia recurrence, with improvement by 21.5 and 26.8, respectively.

Conclusion

PAF ablation using a standardized CLOSE workflow resulted in consistent improvements in QoL. The improved QoL was observed regardless of atrial arrhythmia recurrence likely reflecting the low residual arrhythmia burden in patients with documented recurrence identified only on TTM.

AFEQT Scores Through 12 Months AFEQT Domain Baseline 12 Months Change from Baseline* Daily Activities 59.2 85.3 26.0 Treatment Concerns 62.2 88.1 26.0 Controlling PAF 50.2 87.8 37.5 Symptoms 63.7 89.0 25.1 Symptoms Relieved 52.0 88.4 36.3 Overall AFEQT Score 61.3 87.2 25.7 *only includes patients who completed both baseline and 12 month AFEQT questionnaire

1242The flexibility, ease of using, and leaving curve of a standardized ablation index workflow for catheter ablation of paroxysmal atrial fibrillation

Background/Introduction

The ‘CLOSE’ protocol, incorporating standardized ablation index (AI) targets in conjunction with defined inter-tag distance (ITD) has been shown to improve the acute and long-term success of pulmonary vein isolation (PVI) when treating paroxysmal atrial fibrillation (PAF). The reproducibility and learning curve for this protocol has not been studied.

Purpose

To assess the acute and long-term efficacy of CLOSE PVI across multiple operators (n = 37) in the 17-centre European study ‘VISTAX’.

Methods

329 patients with PAF (61.8% male, 61.3 ± 10.1 years) underwent PVI according to the CLOSE protocol, with target AI values for each lesion of ≥400 on the posterior wall and ≥550 on the anterior wall, and target ITD of ≤6mm. Each 3-dimensional electroanatomic map was evaluated at a core lab where adherence to each of these criteria was assessed. 281/329 patients (85.1%) fulfilled all standardized workflow requirements and were adjudicated as having their PVI per-protocol (PP). First pass PVI and acute effectiveness (adenosine-proof first pass PVI at 30-minute challenge) were recorded. Clinical effectiveness was assessed as freedom from atrial arrhythmia recurrence through 12 months recorded via transtelephonic monitoring (weekly and symptomatically), in addition to holter and electrocardiogram monitoring during 3,6,12 month follow up visits. Learning curve analysis was evaluated on all investigators.

Results

First pass PVI rates were similar in the overall (86%) and PP cohorts (85%), as was acute effectiveness (82% in both cohorts). Freedom from atrial arrhythmia at 12 months too was identical for both cohorts (79%). Total procedure time and total ablation time decreased by an average 8 minutes and 10 minutes respectively after the first procedure and then showed further steady decreases over the number of ablations performed by the investigator (Figure).  The procedural efficiencies and clinical success were reproducible across different centers. No significant deviations were found from individual sites.

Conclusion

The standardized CLOSE workflow is reproducible across centres, and is ‘forgiving’ without impacting on high efficacy of almost 80%. The learning curve is short, suggesting that the excellent clinical results can be replicated widely and easily.

Abstract Figure. Learning Curves- Procedure & Ablation

1138 OSA In A Patient With PFO, Is It The “Perfect Storm” For A Stroke? A Case Series Of 3 Patients With Stroke At Young Age, Due To PFO And Comorbid OSA

Introduction

Approximately 25% of all strokes are cryptogenic in nature, and about 50% of all young patients with cryptogenic stroke are found to have patent foramen ovale (PFO), which is known to be the most common cause of right-to-left shunting (RTLS). Studies have shown a 2.2-fold increase in right-to-left shunt in patients with OSA and PFO, compared to patients with PFO alone. Hence, increasing the risk of cardio-embolic stroke in such patients. We present a case series of 3 patients with PFO that had embolic stroke at a young age and were found to have comorbid OSA, the likely exacerbating factor of a RTLS.

Methods

A 38-year old female, a 59-year old male, and a 27-year old female presented with stroke-like symptoms without clear vascular pathology. Upon further work-up, all were found to have PFO with RTLS. Subsequently, these patients were referred for sleep evaluation, and each one was found to severe REM-related OSA with prominent oxygen desaturations. All three patients were started on PAP therapy for control of their OSA. Two out of the 3 patients opted for PFO closure, and the 3rd patient opted for anti-platelet therapy alone. He has had no recurrence of TIA/stroke after 12 years so far.

Results

These cases illustrate a correlation between right-to-left shunting and severe REM-related OSA, through possible elevation of right-sided pressure due to nocturnal desaturations/hypoxemia. Hence, it is worth consideration that the increased right-sided pressure induced by apneic events in sleep may be a potential exacerbating factor in producing stroke-like symptoms sooner in patients with PFO than in patients with PFO who are without OSA.

Conclusion

It may be beneficial to assess young patients with stroke due to PFO, for comorbid OSA as a cause of the RTLS. This would help to prevent recurrent stroke in such patients and improve quality of life.

Support

No financial support.

1270 Wobbly Knees: Cataplexy Or Seizure? A Case Report

Introduction

Cataplexy (associated with narcolepsy) is difficult to differentiate from conditions such as seizure, syncope or TIA, but using validated clinical tools can help. We report a case that was mistakenly diagnosed as cataplexy, delaying diagnosis and treatment of his underlying seizures.

Report of Case

A 42 years old male presented with “freezing spells” described as spontaneous episodes of weakness in his knees. He may stagger and drop objects but had never fallen. He denies loss of consciousness. Post-ictally, he takes a moment to readjust his body and returns to baseline. There was no warning or aura before the episodes. These spells initially occurred 1-2 times/year in 2002, then progressed to 1/month by 2006 and then increased to 15 times/day in Jan 2019, lasting 5-10 seconds at a time. He became hesitant to drive. He was evaluated by a pulmonologist/sleep specialist. PSG showed Mild OSA but MSLT wasn’t suggestive of Narcolepsy. He was prescribed CPAP but stopped after 6 months since it didn’t improve his symptoms. He was prescribed Venlafaxine to treat presumptive Cataplexy, without any benefit. Eventually, he was referred to neurology/sleep clinic. Cataplexy questionnaire was administered and was negative: specifically, there were no emotional triggers of his episodes, such as hearing a joke, laughing or crying. Due to the stereotyped nature of his spells, he was referred to epilepsy specialist. He underwent 72 hours video EEG monitoring which showed that his clinical episodes were associated with EEG abnormality, suggestive of frontal lobe epilepsy. He was placed on Keppra and Oxcarbazepine. On follow up visit, he reported improvement in seizure frequency from 10-20/day to 1-2/day.

Conclusion

A validated1 clinical Tool such as Stanford Cataplexy questionnaire helps in differentiation of Cataplexy from other forms of transient muscle weakness. It can prevent 15 years delay in diagnosis and treatment of patients, or use of unnecessary medication.

0809 A Randomized Double-blind, Placebo Controlled Trial With Cross-over, To Assess The Efficacy Of Correcting Vitamin D Deficiency In Improving The Symptoms Of Restless Legs Syndrome (RLS)

Introduction

Recent studies have shown an association of low Vitamin D levels and severity of RLS symptoms. However, effect of treatment of Vit D deficiency on RLS symptoms was not reported, nor were other exacerbating factors for RLS such as iron deficiency or OSA addressed in prior studies, but have been addressed in our study.

Methods

This is an ongoing study at the JFKMC Sleep Clinic. Eligible Patients with RLS include those with vitamin D 25,hydroxy deficiency (&lt;20 ng/ml), or insufficiency (&lt;30 ng/ml). Such patients will be enrolled in the study after comorbid conditions like iron deficiency and OSA have been adequately corrected. Randomization of the patients will be done by the JFK pharmacy so the patient and provider are blinded to the substance. Substance A or B could be either Vitamin D3 Capsule 50,000 IU, or placebo. Each patient takes A for 6 weeks and then crosses over to B for 6 weeks. Weekly iRLS questionnaires will be collected. Actiwatch Device, to assess activity count per minute, will be worn on the ankle at night for one week time periods: at baseline, at end of 6 weeks of taking A and then at the end of 6 weeks of taking B. Vitamin D levels will also be assessed after each course of supplementation and correlated with subjective and objective findings.

Results

Between July 7, 2019 to current, 50 consecutive patients seen in sleep clinic with RLS were assessed for vitamin D levels. Ages ranged from 23-86 years. 27 patients were female (54%). Two patients met inclusion criteria and have started their 13-week study.

Conclusion

This study will help to establish the role of Vitamin D deficiency as a risk factor for RLS, independent of ferritin levels, and comorbid OSA, in affected individuals. This may help to discover a potentially treatable form of RLS.

Support

No financial support.

1149 A Pilot Quality Improvement (QI) Study To Assess Whether Bilevel Positive Airway Pressure (bipap) Support In Acute Ischemic Stroke Patients With Sleep Disordered Breathing, Can Improve Neurological Recovery During Acute Stroke Care

Introduction

Obstructive sleep apnea (OSA) has been associated with adverse outcomes in patients with stroke. While data is limited, it suggests that treatment of OSA may improve neurological recovery. With this quality improvement (QI) project, we aim to develop an interprofessional-team workflow process for screening and correction of OSA in acute ischemic stroke, with the goal to improve outcomes of neurological recovery.

Methods

This is an ongoing study to screen all eligible patients admitted to JFK Medical Center stroke unit, with MRI-proven Supratentorial acute ischemic stroke. The patients are screened using an overnight Pulse Oximetry test. A 3% oxygen desaturation index (ODI) of ≥10/hr or 4% ODI of ≥ 5/hr is considered at high risk for OSA. Such Patients will receive nocturnal Auto-adjusting BIPAP therapy during their acute care stay, for up to 5 days, for at least 4 hours per night. Eligible Patients who refused BiPAP therapy or were non-compliant will be considered as a controls. Baseline NIH stroke scale (NIHSS), and bilateral MCA mean flow velocity (MFV) in the morning, by transcranial doppler (TCD) will be assessed at baseline for cases and controls, and after BiPAP therapy, for the case group. The two groups of patients will also be compared in terms of Modified Rankin Scale at time of discharge and at phone follow-up after 6 weeks.

Results

Between Oct 17th, 2019 to current, 15 patients were admitted to the stroke unit with MRI confirmed stroke. Ages ranged from 34 - 88 years (average age 66.5 years). 8 patients (60%) were female. Of those, 6 patients consented to being screened for OSA. Of these, 1 had 4%ODI &gt;5/hr, and therefore received treatment with BIPAP. However, compliance was &lt; 4 hrs on 2 consecutive nights.

Conclusion

This is ongoing QI project and results will be available after few more months of continued recruitment.

Support

Auto-adjusting BIPAP machines were provided by RESMED.

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<0.001) compared to QRISK3 (AUC=0.51, P<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.

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 < .001) and -0.35 (P < .001), respectively; (2) for T2DM and non-T2DM -0.26 (P < .001) and -0.49 (P = .02), respectively, and (3) for left and right CCA -0.25 (P < .001) and -0.23 (P < .001), respectively. Automated TPA is an equally reliable biomarker compared with cIMTave for patients with CKD (with or without T2DM) with subclinical atherosclerosis.

Low-cost preventive screening using carotid ultrasound in patients with diabetes

Diabetes and atherosclerosis are the predominant causes of stroke and cardiovascular disease (CVD) both in low- and high-income countries. This is due to the lack of appropriate medical care or high medical costs. Low-cost 10-year preventive screening can be used for deciding an effective therapy to reduce the effects of atherosclerosis in diabetes patients. American College of Cardiology (ACC)/American Heart Association (AHA) recommended the use of 10-year risk calculators, before advising therapy. Conventional risk calculators are suboptimal in certain groups of patients because their stratification depends on (a) current blood biomarkers and (b) clinical phenotypes, such as age, hypertension, ethnicity, and sex. The focus of this review is on risk assessment using innovative composite risk scores that use conventional blood biomarkers combined with vascular image-based phenotypes. AtheroEdge™ tool is beneficial for low-moderate to high-moderate and low-risk to high-risk patients for the current and 10-year risk assessment that outperforms conventional risk calculators. The preventive screening tool that combines the image-based phenotypes with conventional risk factors can improve the 10-year cardiovascular/stroke risk assessment.

Global perspective on carotid intima-media thickness and plaque: should the current measurement guidelines be revisited?

Carotid intima-media thickness (cIMT) and carotid plaque (CP) currently act as risk predictors for CVD/Stroke risk assessment. Over 2000 articles have been published that cover either use cIMT/CP or alterations of cIMT/CP and additional image-based phenotypes to associate cIMT related markers with CVD/Stroke risk. These articles have shown variable results, which likely reflect a lack of standardization in the tools for measurement, risk stratification, and risk assessment. Guidelines for cIMT/CP measurement are influenced by major factors like the atherosclerosis disease itself, conventional risk factors, 10-year measurement tools, types of CVD/Stroke risk calculators, incomplete validation of measurement tools, and the fast pace of computer technology advancements. This review discusses the following major points: 1) the American Society of Echocardiography and Mannheim guidelines for cIMT/CP measurements; 2) forces that influence the guidelines; and 3) calculators for risk stratification and assessment under the influence of advanced intelligence methods. The review also presents the knowledge-based learning strategies such as machine and deep learning which may play a future role in CVD/stroke risk assessment. We conclude that both machine learning and non-machine learning strategies will flourish for current and 10-year CVD/Stroke risk prediction as long as they integrate image-based phenotypes with conventional risk factors.

A low-cost machine learning-based cardiovascular/stroke risk assessment system: integration of conventional factors with image phenotypes

Background

Most cardiovascular (CV)/stroke risk calculators using the integration of carotid ultrasound image-based phenotypes (CUSIP) with conventional risk factors (CRF) have shown improved risk stratification compared with either method. However such approaches have not yet leveraged the potential of machine learning (ML). Most intelligent ML strategies use follow-ups for the endpoints but are costly and time-intensive. We introduce an integrated ML system using stenosis as an endpoint for training and determine whether such a system can lead to superior performance compared with the conventional ML system.

Methods

The ML-based algorithm consists of an offline and online system. The offline system extracts 47 features which comprised of 13 CRF and 34 CUSIP. Principal component analysis (PCA) was used to select the most significant features. These offline features were then trained using the event-equivalent gold standard (consisting of percentage stenosis) using a random forest (RF) classifier framework to generate training coefficients. The online system then transforms the PCA-based test features using offline trained coefficients to predict the risk labels on test subjects. The above ML system determines the area under the curve (AUC) using a 10-fold cross-validation paradigm. The above system so-called "AtheroRisk-Integrated" was compared against "AtheroRisk-Conventional", where only 13 CRF were considered in a feature set.

Results

Left and right common carotid arteries of 202 Japanese patients (Toho University, Japan) were retrospectively examined to obtain 395 ultrasound scans. AtheroRisk-Integrated system [AUC =0.80, P<0.0001, 95% confidence interval (CI): 0.77 to 0.84] showed an improvement of ~18% against AtheroRisk-Conventional ML (AUC =0.68, P<0.0001, 95% CI: 0.64 to 0.72).

Conclusions

ML-based integrated model with the event-equivalent gold standard as percentage stenosis is powerful and offers low cost and high performance CV/stroke risk assessment.

A Special Report on Changing Trends in Preventive Stroke/Cardiovascular Risk Assessment Via B-Mode Ultrasonography

PURPOSE OF REVIEW

Cardiovascular disease (CVD) and stroke risk assessment have been largely based on the success of traditional statistically derived risk calculators such as Pooled Cohort Risk Score or Framingham Risk Score. However, over the last decade, automated computational paradigms such as machine learning (ML) and deep learning (DL) techniques have penetrated into a variety of medical domains including CVD/stroke risk assessment. This review is mainly focused on the changing trends in CVD/stroke risk assessment and its stratification from statistical-based models to ML-based paradigms using non-invasive carotid ultrasonography.

RECENT FINDINGS

In this review, ML-based strategies are categorized into two types: non-image (or conventional ML-based) and image-based (or integrated ML-based). The success of conventional (non-image-based) ML-based algorithms lies in the different data-driven patterns or features which are used to train the ML systems. Typically these features are the patients' demographics, serum biomarkers, and multiple clinical parameters. The integrated (image-based) ML-based algorithms integrate the features derived from the ultrasound scans of the arterial walls (such as morphological measurements) with conventional risk factors in ML frameworks. Even though the review covers ML-based system designs for carotid and coronary ultrasonography, the main focus of the review is on CVD/stroke risk scores based on carotid ultrasound. There are two key conclusions from this review: (i) fusion of image-based features with conventional cardiovascular risk factors can lead to more accurate CVD/stroke risk stratification; (ii) the ability to handle multiple sources of information in big data framework using artificial intelligence-based paradigms (such as ML and DL) is likely to be the future in preventive CVD/stroke risk assessment.

Impaired decision-making and time perception in individuals with stroke: Behavioral and neural correlates

Several studies have demonstrated that stroke subjects present impairment of functions related to decision-making and timing, involving the information processing in the neural circuits of the cerebellum in association with the prefrontal cortex. This review is aimed to identify the gaps, and demonstrate a better understanding of decision-making and timing functions in the patients with stroke. Electronic literature database was searched and the findings of relevant studies were used to explore the mechanisms of decision-making and timing in patients with stroke, as well as the circuit connections in timing mediated by prefrontal cortex and cerebellum. A literature review was conducted with 65 studies that synthesized findings on decision-making and time perception in individuals with stroke. Types of neurobiological modalities in this study included: Relationships among decision-making, time perception, related cognitive aspects (such as discrimination tasks, verbal estimation, bisection tasks, time production and motor reproduction), and motor control. We demonstrate that the timing processes are important for the performance in cognitive tasks and that the cerebellum and prefrontal cortex are involved in decision-making and time perception. In the context, the decision-making is impaired in stroke patients has a great impact on executive functions, and this seems to be important in determining neurobiological aspects relevant to the time interval interpretation.

Ranking of stroke and cardiovascular risk factors for an optimal risk calculator design: Logistic regression approach

PURPOSE

Conventional cardiovascular risk factors (CCVRFs) and carotid ultrasound image-based phenotypes (CUSIP) are independently associated with long-term risk of cardiovascular (CV) disease. In this study, 26 cardiovascular risk (CVR) factors which consisted of a combination of CCVRFs and CUSIP together were ranked. Further, an optimal risk calculator using AtheroEdge composite risk score (AECRS1.0) was designed and benchmarked against seven conventional CV risk (CVR) calculators.

METHODS

Two types of ranking were performed: (i) ranking of 26 CVR factors and (ii) ranking of eight types of 10-year risk calculators. In the first case, multivariate logistic regression was used to compute the odds ratio (OR) and in the second, receiver operating characteristic curves were used to evaluate the performance of eight types of CVR calculators using SPSS23.0 and MEDCALC12.0 with validation against STATA15.0.

RESULTS

The left and right common carotid arteries (CCA) of 202 Japanese patients were examined to obtain 404 ultrasound scans. CUSIP ranked in the top 50% of the 26 covariates. Intima-media thickness variability (IMTV) and IMTV_10yr were the most influential carotid phenotypes for left CCA (OR = 250, P < 0.0001 and OR = 207, P < 0.0001 respectively) and right CCA (OR = 1614, P < 0.0001 and OR = 626, P < 0.0001 respectively). However, for the mean CCA, AECRS1.0 and AECRS1.0_10yr reported the most highly significant OR among all the CVR factors (OR = 1.073, P < 0.0001 and OR = 1.104, P < 0.0001). AECRS1.0_10yr also reported highest area-under-the-curve (AUC = 0.904, P < 0.0001) compared to seven types of conventional calculators. Age and glycated haemoglobin reported highest OR (1.96, P < 0.0001 and 1.05, P = 0.012) among all other CCVRFs.

CONCLUSION

AECRS1.0_10yr demonstrated the best performance due to presence of CUSIP and ranked at the first place with highest AUC.

Comparative evaluation of Myolaxin and EM LA cream for attenuation of venous cannulation pain: A prospective, randomised, double blind study

We evaluated the efficacy of topical Myolaxin (capsaican ointment, Geno, Mumbai) ointment over EMLA (eutectic mixture of lignocaine, prilocaine; Neon, Goa) cream for attenuating venous cannulation pain in this prospective, randomised, double blind study. Sixty adult patients undergoing elective laparoscopic cholecystectomy were randomly assigned into two equal groups. Group I (EMLA) received EMLA cream, whereas Group II (Myolaxin) received Myolaxin ointment. For both groups the cream was applied at the venous cannulation site (dorsum of the non-dominant hand) one hour prior to venous cannulation and was covered with an occlusive dressing. Following venous cannulation patients were asked if they felt pain during venous cannulation. If the answer was yes, they were asked to rate the severity of venous cannulation pain using a Visual Analogue Scale (VAS) of O-10. The incidence of venous cannulation pain was similar between groups: in the EMLA group 65% (18/28) compared to 67% (20/30) in the Myolaxin group (P=0.19). The severity of pain (median VAS with inter quartile range) was also similar between the groups: in the EMLA group 1.5 (3) compared to 1.5 (2) in the Myolaxin group (P=0.46). As the topical application of Myolaxin ointment is cheaper than EMLA and has similar efficacy, it may be a suitable alternative for reducing the incidence and severity of venous cannulation pain.

Pain during Injection of Propofol: The Effect of Prior Administration of Ephedrine

Propofol causes pain on intravenous injection in 28 to 90% of patients. A number of techniques have been tried to minimize propofol-induced pain, with variable results. In a randomized, double-blind, placebo-controlled trial, we compared the efficacy of ephedrine 30 μg/kg pretreatment to lignocaine 40 mg for prevention of propofol-induced pain. Ninety-three adult patients, ASA 1 and 2, undergoing elective laparoscopic cholecystectomy were randomly assigned to three groups of 31 each. Group 1 received normal saline, group 2 received lignocaine 2% (40 mg) and group 3 received 30 μg/kg ephedrine. All pretreatment drugs were made up to 2 ml. Pain at the time of propofol injection was assessed on a four-point scale: 0=no pain, 1=mild pain, 2=moderate pain, and 3=severe pain. Twenty-seven patients (87%) of ephedrine pretreatment patients had pain during intravenous injection of propofol as compared to 24 (77%) in the normal saline group. In the lignocaine group, propofol-induced pain was observed in only 13 (42%) when compared with other study groups (P<0.05). Pretreatment with ephedrine 30 μg/kg did not attenuate pain associated with intravenous injection of propofol, nor did it improve haemodynamic stability during induction. However, pretreatment with 2% lignocaine (40 mg) was effective in attenuating propofol-associated pain.

Nonlinear model for the carotid artery disease 10-year risk prediction by fusing conventional cardiovascular factors to carotid ultrasound image phenotypes: A Japanese diabetes cohort study

MOTIVATION

This study presents a novel nonlinear model which can predict 10-year carotid ultrasound image-based phenotypes by fusing nine traditional cardiovascular risk factors (ethnicity, gender, age, artery type, body mass index, hemoglobin A1c, hypertension, low-density lipoprotein, and smoking) with five types of carotid automated image phenotypes (three types of carotid intima-media thickness (IMT), wall variability, and total plaque area).

METHODOLOGY

Two-step process was adapted: First, five baseline carotid image-based phenotypes were automatically measured using AtheroEdge^™ (AtheroPoint^™ , CA, USA) system by two operators (novice and experienced) and an expert. Second, based on the annual progression rates of cIMT due to nine traditional cardiovascular risk factors, a novel nonlinear model was adapted for 10-year predictions of carotid phenotypes.

RESULTS

Institute review board (IRB) approved 204 Japanese patients' left/right common carotid artery (407 ultrasound scans) was collected with a mean age of 69 ± 11 years. Age and hemoglobin were reported to have a high influence on the 10-year carotid phenotypes. Mean correlation coefficient (CC) between 10-year carotid image-based phenotype and age was improved by 39.35% in males and 25.38% in females. The area under the curves for the 10-year measurements of five phenotypes IMT_ave10yr , IMT_max10yr , IMT_min10yr , IMTV_10yr , and TPA_10yr were 0.96, 0.94, 0.90, 1.0, and 1.0. Inter-operator variability between two operators showed significant CC (P < 0.0001).

CONCLUSIONS

A nonlinear model was developed and validated by fusing nine conventional CV risk factors with current carotid image-based phenotypes for predicting the 10-year carotid ultrasound image-based phenotypes which may be used risk assessment.

Performance evaluation of 10-year ultrasound image-based stroke/cardiovascular (CV) risk calculator by comparing against ten conventional CV risk calculators: A diabetic study

MOTIVATION

AtheroEdge Composite Risk Score (AECRS1.0_10yr) is an integrated stroke/cardiovascular risk calculator that was recently developed and computes the 10-year risk of carotid image phenotypes by integrating conventional cardiovascular risk factors (CCVRFs). It is therefore important to understand how closely AECRS1.0_10yr is associated with the ten other currently available conventional cardiovascular risk calculators (CCVRCs).

METHODS

The Institutional Review Board of Toho University approved the examination of the left/right common carotid arteries of 202 Japanese patients. Step 1 consists of measurement of AECRS1.0_10yr, given current image phenotypes and CCVRFs. Step 2 consists of computing the risk score using ten different CCVRCs given CCVR factors: QRISK3, Framingham Risk Score (FRS), United Kingdom Prospective Diabetes Study (UKPDS) 56, UKPDS60, Reynolds Risk Score (RRS), Pooled cohort Risk Score (PCRS or ASCVD), Systematic Coronary Risk Evaluation (SCORE), Prospective Cardiovascular Munster Study (PROCAM) calculator, NIPPON, and World Health Organization (WHO) risk. Step 3 consists of computing the closeness factor between AECRS1.0_10yr and ten CCVRCs using cumulative ranking index derived using eight different statistically derived metrics.

RESULTS

AECRS1.0_10yr reported the highest area-under-the-curve (0.927;P < 0.001) among all the risk calculators. The top three CCVRCs closest to AECRS1.0_10yr were QRISK3, FRS, and UKPDS60 with cumulative ranking scores of 2.1, 3.0, and 3.8, respectively.

CONCLUSION

AECRS1.0_10yr produced the largest AUC due to the integration of image-based phenotypes with CCVR factors, and ranked at first place with the highest AUC. Cumulative ranking of ten CCVRCs demonstrated that QRISK3 was the closest calculator to AECRS1.0_10yr, which is also consistent with the industry trend.

Lower eyelid excursion: A functional and cosmetically relevant parameter in the treatment of lower eyelid retraction

The purpose of this study was to assess and quantify lower lid excursion following repair of lower lid retraction. In this retrospective cohort study, a case review of patients who had undergone ear cartilage grafting for lower lid retraction was undertaken. Surgical correction involved the placement of autologous cartilage between the tarsal plate and lower lid retractors. Measurements taken preoperatively and postoperatively were the marginal reflex 2 (MRD2) and the lower scleral show (LSS). The lower lid excursion on downgaze (LLE) was measured only postoperatively with a comparison made between operated eyes and control eyes. Thirteen eyelids of 10 patients were included in the study. Preoperatively, MRD-2 ranged from 4 to 8 mm (6.5 ± 1.5 mm) - mean ± SD. Postoperatively, MRD-2 ranged from 4 to 6 mm (5.1 ± 0.7 mm). The difference in mean MRD2 was statistically significant (p < 0.05). Preoperatively, LSS ranged from 0 to 5 mm (2.5 ± 1.6 mm). Postoperatively, LSS ranged from 0-1 mm (0.1 ± 0.3 mm). The difference in mean LSS was statistically significant (p < 0.01). Postoperatively, all lower eyelids achieved movement on downgaze. On the operated eyes, the eyelid excursion ranged from 2 to 5 mm (3.1 ± 1.0 mm) on downgaze. On the nonoperated (control) eyes (where the operations were not performed bilaterally), the eyelid excursion ranged from 1 to 4 mm (2.8 ± 1.2 mm). There was no statistically significant difference in the lid excursion of operated and nonoperated eyes (p > 0.05). It is possible to correct lower lid retraction in both primary and secondary positions of gaze if an appropriate surgical technique is employed.

Jet outflow and open field line measurements on the C-2W advanced beam-driven field-reversed configuration plasma experiment

Accurate operation and high performance of the open field line plasma surrounding the field reversed configuration is crucial to achieving the goals of successful temperature ramp up and confinement improvement on C-2W. Knowledge and control of the open field line plasma requires extensive diagnostic efforts. A suite of diagnostics, which consists of microwave interferometry, dispersive spectroscopy, and spatial heterodyne spectroscopy, is being developed to measure electron density, ion temperature, and particle outflow velocity at various locations along the open magnetic field lines. A detailed overview of these diagnostics is presented.

Development of a Z eff diagnostic using visible and near-infrared bremsstrahlung light for the C-2W field-reversed configuration plasma

In C-2W, an elevated impurity concentration can lead to significant degradation of plasma performance and energy losses through radiation. To gauge plasma contamination from impurities, the effective ion charge (Z _eff) can be determined from measurements of bremsstrahlung continuum radiation over a small spectral range free from line radiation. To this end, a diagnostic system including visible and near-infrared bremsstrahlung detectors was deployed in C-2W to measure time-dependent radial distributions of Z _eff. The system is complemented by an array of survey spectrometers which enable full-range spectroscopic measurements of impurity emission lines from the vacuum ultraviolet to the near infrared, providing a good picture of the plasma composition. Here, the design scheme for this integrated diagnostic system is presented and discussed.

Effect of Hemodialysis on Corrected QT Interval and QTc Dispersion

Hemodialysis patients are at higher risk of cardiovascular disease due to traditional and dialysis-related risk factors. Our aim was to study the effects of hemodialysis on the corrected QT interval (QTc) and QTc dispersion in chronic kidney disease (CKD) without clinically manifest heart disease. Two hundred cases of CKD on chronic intermittent hemodialysis of >3 months' duration were included in the study. Twelve-lead electrocardiography and samples for serum creatinine, potassium, calcium, and magnesium were taken before and after dialysis. The mean age of patients was 52.4 ± 17 years with male-to-female ratio of 3:1. QTc interval and QTc dispersion were prolonged in 47% and 59% before and 50% and 89% of patients after hemodialysis, respectively. The mean values of QTc were 433.4 ± 36.9 ms before and 451.4 ± 39.6 ms after hemodialysis (p = 0.001) and the mean values of QTc dispersion were 60.5 ± 19.3 ms before and 81.5 ± 24.4 ms after hemodialysis (p = 0.001). Similar pattern was observed in all etiological groups of CKD, except for QTc dispersion in malignancy-related CKD (p = 0.216). After hemodialysis, there was a significant fall in the mean values of serum potassium (p = 0.001), rise in serum calcium (p = 0.001), and no change in magnesium (p = 0.424). Patients with post hemodialysis QTc dispersion >74 ms had significantly low mean values of serum potassium and calcium as compared to <74 ms group. Large numbers of hemodialysis patients have a prolonged QTc interval and QTc dispersion with a significant increase in the mean values after hemodialysis. There is a significant fall in serum potassium and rise in serum calcium after dialysis.

Echolucency-based phenotype in carotid atherosclerosis disease for risk stratification of diabetes patients

AIM

The study investigated the association of carotid ultrasound echolucent plaque-based biomarker with HbA1c, measured as age-adjusted grayscale median (AAGSM) as a function of chronological age, total plaque area, and conventional grayscale median (GSM_conv).

METHODS

Two stages were developed: (a) automated measurement of carotid parameters such as total plaque area (TPA); (b) computing the AAGSM as a function of GSM_conv, age, and TPA. Intra-operator (novice and experienced) analysis was conducted.

RESULTS

IRB approved, 204 patients' left/right CCA (408 images) ultrasound scans were collected: mean age: 69 ± 11 years; mean HbA1c: 6.12 ± 1.47%. A moderate inverse correlation was observed between AAGSM and HbA1c (CC of -0.13, P = 0.01), compared to GSM (CC of -0.06, P = 0.24). The RCCA and LCCA showed CC of -0.18, P < 0.01 and -0.08; P < 0.24. Female and males showed CC of -0.29, P < 0.01 and -0.10, P = 0.09. Using the threshold for AAGSM and HbA1c as: low-risk (AAGSM > 100; HbA1c < 5.7%), moderate-risk (40 < AAGSM < 100; 5.7% < HbA1c < 6.5%) and high-risk (AAGSM < 40; HbA1c > 6.5%), the area under the curve showed a better performance of AAGSM over GSM_conv. A paired t-test between operators and expert (P < 0.0001); inter-operator CC of 0.85 (P < 0.0001).

CONCLUSIONS

Echolucent plaque in patients with diabetes can be more accurately characterized for risk stratification using AAGSM compared to GSM_conv.

A Survey on Coronary Atherosclerotic Plaque Tissue Characterization in Intravascular Optical Coherence Tomography

PURPOSE OF REVIEW

Atherosclerotic plaque deposition within the coronary vessel wall leads to arterial stenosis and severe catastrophic events over time. Identification of these atherosclerotic plaque components is essential to pre-estimate the risk of cardiovascular disease (CVD) and stratify them as a high or low risk. The characterization and quantification of coronary plaque components are not only vital but also a challenging task which can be possible using high-resolution imaging techniques.

RECENT FINDING

Atherosclerotic plaque components such as thin cap fibroatheroma (TCFA), fibrous cap, macrophage infiltration, large necrotic core, and thrombus are the microstructural plaque components that can be detected with only high-resolution imaging modalities such as intravascular ultrasound (IVUS) and optical coherence tomography (OCT). Light-based OCT provides better visualization of plaque tissue layers of coronary vessel walls as compared to IVUS. Three dominant paradigms have been identified to characterize atherosclerotic plaque components based on optical attenuation coefficients, machine learning algorithms, and deep learning techniques. This review (condensation of 126 papers after downloading 150 articles) presents a detailed comparison among various methodologies utilized for plaque tissue characterization, classification, and arterial measurements in OCT. Furthermore, this review presents the different ways to predict and stratify the risk associated with the CVD based on plaque characterization and measurements in OCT. Moreover, this review discovers three different paradigms for plaque characterization and their pros and cons. Among all of the techniques, a combination of machine learning and deep learning techniques is a best possible solution that provides improved OCT-based risk stratification.