Cross-sectional comparison of cardiovascular risk scores in people with HIV.

Introduction: Cardiovascular disease (CVD) risk scores are used to estimate an individual’s risk of developing a disease or death from a cardiovascular event. Recently, the American College of Cardiology/American Heart Association (ACC/AHA) introduced the Pooled Cohort risk equations (ACC/AHA model). It is important to know how comparable CVD risk predictions are in low-middle income countries (LMIC). Hypothesis: ACC/AHA model has a poor concordance with any other CVD risk score. Methods: We used secondary data from two Peruvian, age and sex-matched, population-based studies across five geographical sites. The ACC/AHA model was compared to five other CVD risk prediction tools: two versions of the Framingham Risk Score (FRS-Lipids and FRS-BMI), Reynolds Risk Score (RRS), four versions of the Systematic Coronary Risk Evaluation (SCORE 1-4), World Health Organization risk chart (WHO), and Lancet Chronic Disease risk chart (LCD). We calculated predicted risk as a continuous variable and used Lin’s concordance correlation coefficient (CCC). We also compared the high predicted risk prevalence between all the scores using the cut-off levels suggested by each score’s guidelines. Results: We included 2183 subjects in the risk scores age range of 45-65 years (mean age 54.3 (SD±5.6) years). CCC agreement values found in this study were generally poor. The highest concordance was observed between the ACC/AHA model and the risk scores derived from the Framingham Study (40% with FRS-BMI and 44% with FRS-Lipids). ACC/AHA model depicted the highest proportion of people with predicted high-risk of 10-year CVD, at 29.0% (95%CI 26.9-31.0%) and the same tendency was observed in all study sites. Conclusions: In Peruvian population-based samples, agreement between ACC/AHA model and five other CVD risk scores was generally poor. There is an urgent need to use an appropriate risk score for CVD in LMIC. In an ideal scenario, it would be significant to have a proper CVD risk score for LMIC.

It is unclear how well currently available risk scores predict cardiovascular disease (CVD) risk in low-income and middle-income countries. We aim to compare the American College of Cardiology/American Heart Association (ACC/AHA) Pooled Cohort risk equations (ACC/AHA model) with 6 other CVD risk tools to assess the concordance of predicted CVD risk in a random sample from 5 geographically diverse Peruvian populations. We used data from 2 Peruvian, age and sex-matched, population-based studies across 5 geographical sites. The ACC/AHA model were compared with 6 other CVD risk prediction tools: laboratory Framingham risk score for CVD, non-laboratory Framingham risk score for CVD, Reynolds risk score, systematic coronary risk evaluation, World Health Organization risk charts, and the Lancet chronic diseases risk charts. Main outcome was in agreement with predicted CVD risk using Lin's concordance correlation coefficient. Two thousand one hundred and eighty-three subjects, mean age 54.3 (SD ± 5.6) years, were included in the analysis. Overall, we found poor agreement between different scores when compared with ACC/AHA model. When each of the risk scores was used with cut-offs specified in guidelines, ACC/AHA model depicted the highest proportion of people at high CVD risk predicted at 10 years, with a prevalence of 29.0% (95% confidence interval, 26.9-31.0%), whereas prevalence with World Health Organization risk charts was 0.6% (95% confidence interval, 0.2-8.6%). In conclusion, poor concordance between current CVD risk scores demonstrates the uncertainty of choosing any of them for public health and clinical interventions in Latin American populations. There is a need to improve the evidence base of risk scores for CVD in low-income and middle-income countries.

Background Automatic noninvasive oscillometric blood pressure (NIBP) devices measure mean arterial pressure (MAP); systolic and diastolic blood pressure (SBP, DBP) are algorithmically derived from MAP. The most invalid NIBP measure is SBP, yet stroke practitioners use it to manage blood pressure (BP) in accordance with thrombolysis guidelines. We determined agreement between SBP, DBP, and MAP measured manually and by NIBP in patients treated with alteplase. Methods A multisite prospective observational study of NIBP and manual BP agreement was conducted in patients treated with alteplase immediately after bolus and infusion initiation using methods established in guidelines for the assessment of device agreement. Dual auscultatory stethoscopes were used by 2 investigators to ensure agreement with each manual BP variable and MAP was calculated using the standard formula for manual BP measures. Data were analyzed using Bland–Altman analyses and Lin concordance correlation coefficient. Results A total of 7 hospitals participated, collecting 5 sets of manual/NIBP BPs in 95 patients treated with alteplase (475 paired measures). Range in limits of agreement were SBP: −28.91 to 21.41 mmHg with Lin's concordance correlation coefficient 0.8; DBP: −21.0 to 19.0 mmHg with Lin's concordance correlation coefficient 0.69; and MAP: −27.5 to 16.5 mmHg with Lin's concordance correlation coefficient 0.7. There was no difference in device agreement by BP device manufacturer brand. Differences in SBP, DBP, and MAP between NIBP and manual sphygmomanometry failed to reach guideline recommendations requiring 80% of measures to fall within a 5 mmHg difference and 95% of measures to fall within a 10 mmHg difference. Conclusion NIBP devices produce significantly different BP measures then manual sphygmomanometry auscultated BP. Because NIBP devices rely on the MAP and do not directly measure SBP and DBP, definition of what constitutes safe MAP boundaries in patients treated with alteplase should be determined when automatic BP measurement is used in clinical practice.

Objective. To examine the gender differences in the association of psychological distress with cardiovascular disease (CVD) risk scores using two different CVD risk assessment models. Design and setting. A cross-sectional, population-based study from 1997 to 1998 in Pieksämäki, Finland. Subjects. A population sample of 899 (399 male and 500 female) middle-aged subjects. Main outcome measures. The 10-year risk for CVD events was calculated using the European SCORE model and the Framingham CVD risk prediction model. Psychological distress was measured using the 12-item General Health Questionnaire (GHQ-12). Study subjects were allocated into three groups according to their global GHQ-12 -scores: 0 points, 1–2 points, and 3–12 points. Results. Psychological distress was associated with higher mean CVD risk scores in men. Men in the highest GHQ group (3–12 points) had significantly higher mean European CVD risk score (3.6 [SD 3.3]) compared with men in the lowest group (0 points) (2.5 [SD 2.6]), the difference being 1.1 (95% CI 0.4 to 1.9). The p-value for linearity between the three GHQ groups was 0.003. The Framingham CVD risk prediction model yielded similar results: 15.7 (SD 10.2) vs. 12.3 (SD 9.6), the difference 3.4 (95% CI 1.0 to 6.0) and p-value for linearity 0.008. No significant association was observed in women. Conclusion. A gender-specific association was found betwen psychological distress and cardiovascular risk scores. These results highlight the importance of identifying men with psychological distress when assessing CVD risk.

Extant data on the performance of cardiovascular disease (CVD) risk score models in people living with HIV have not been synthesized. To synthesize available data on the performance of the various CVD risk scores in people living with HIV. PubMed and Embase were searched from inception through January 31, 2021. Selected studies (1) were chosen based on cohort design, (2) included adults with a diagnosis of HIV, (3) assessed CVD outcomes, and (4) had available data on a minimum of 1 CVD risk score. Relevant data related to study characteristics, CVD outcome, and risk prediction models were extracted in duplicate. Measures of calibration and discrimination are presented in tables and qualitatively summarized. Additionally, where possible, estimates of discrimination and calibration measures were combined and stratified by type of risk model. Measures of calibration and discrimination. Nine unique observational studies involving 75 304 people (weighted average age, 42 years; 59 490 male individuals [79%]) living with HIV were included. In the studies reporting these data, 86% were receiving antiretroviral therapy and had a weighted average CD4+ count of 449 cells/μL. Included in the study were current smokers (50%), patients with diabetes (5%), and patients with hypertension (25%). Ten risk prediction scores (6 in the general population and 4 in the HIV-specific population) were analyzed. Most risk scores had a moderate performance in discrimination (C statistic: 0.7-0.8), without a significant difference in performance between the risk scores of the general and HIV-specific populations. One of the HIV-specific risk models (Data Collection on Adverse Effects of Anti-HIV Drugs Cohort 2016) and 2 of the general population risk models (Framingham Risk Score [FRS] and Pooled Cohort Equation [PCE] 10 year) had the highest performance in discrimination. In general, models tended to underpredict CVD risk, except for FRS and PCE 10-year scores, which were better calibrated. There was substantial heterogeneity across the studies, with only a few studies contributing data for each risk score. Results of this systematic review and meta-analysis suggest that general population and HIV-specific CVD risk models had comparable, moderate discrimination ability in people living with HIV, with a general tendency to underpredict risk. These results reinforce the current recommendations provided by the American College of Cardiology/American Heart Association guidelines to consider HIV as a risk-enhancing factor when estimating CVD risk.

Validation of lower limb segmental volumetry with hand-held, self-positioning three-dimensional laser scanner against water displacement.

To validate anthropometric equations in the current literature predicting body fat percentage (%BF) in the Greek population, to develop and validate two anthropometric equations estimating %BF, and to compare them with the retrieved equations. Anthropometric data from 642 Greek adults were incorporated. Dual-energy X-ray absorptiometry was used as reference method. The comparison with other equations was made using Bland-Altman analysis, intraclass correlation coefficient, and Lin's concordance correlation coefficient. Nine of the thirty-one retrieved equations had no statistically significant bias. However, all of them had wide limits of agreement (±8.3 to ±16%BF). The equations accrued were: BF% = -0.615-10.948 × sex + 0.321 × waist circumference + 0.502 × hips circumference-0.39 × forearm circumference - 19.768 × height (m) and BF% = -27.787-5.515 × sex-8.419 × height + 0.145 × waist circumference + 0.270 × hips circumference + 7.509 × log of thigh skinfold + 20.090 × log of sum of skinfolds (bicep + tricep + suprailiac + subscapular)-0.445 × forearm circumference. Bland-Altman's reliability analysis showed no significant bias of -0.058 and -0.148%BF and limits of agreement ±8.100 and ±6.056%BF; the intraclass correlation coefficient was 0.955 and 0.976; and Lin's concordance correlation coefficient was 0.914 and 0.951, respectively. Literature equations performed moderately on this study's population. Therefore, two equations were designed and validated. The first one was simple and easily applicable, with measures obtained from a measuring tape, and the second one more complicated yet more accurate and reliable. Both were found to be reliable for the assessment of body composition in the Greek population.

Objectives (1) To describe and compare cardiovascular and cardiometabolic disease risk scores using three existing risk calculators: Framingham Risk Score (FRS), American Heart Association (AHA) and Metabolic Syndrome Severity Score (MSSS) in Veterans with spinal cord injury and disorders (SCI/D); (2) To examine level of agreement between risk scores derived from three different risk scoring systems; and (3) To investigate whether the agreement among these methods is different for Veterans with Tetraplegia versus Paraplegia. Design Retrospective chart review. Methods Electronic medical records of 194 Veterans with SCI/D who were seen at the VAPAHCS SCI/D Center between August 2004 and June 2022 were reviewed. Cardiovascular disease (CVD) risk scores (FRS and AHA) along with a Metabolic Syndrome Severity Score (MSSS) were computed using web-based calculators. Results Moderate agreement between CVD risk scores (FRS and AHA) was observed; however, the agreement was poor between MSSS and both AHA and FRS. No differences were observed between the paraplegia and tetraplegia cohorts. From the AHA risk score, more than half the study population was found to be at high risk while less than half was considered high risk from the FRS and MSSS scores. Conclusions Given the moderate association between AHA and FRS scores along with considerable variation in risk predictors, CVD risk prediction assessment tools should be interpreted cautiously in the SCI population. SCI-related clinical biomarkers and other clinically relevant risk factors should be taken into consideration to optimize risk estimation in persons with SCI/D.

At present, automated analysis of high-resolution manometry (HRM) provides details of upper esophageal sphincter (UES) relaxation parameters. The aim of this study was to assess the accuracy of automatic analysis of UES relaxation parameters. One hundred and fifty three subjects (78 males, mean age 68.6 years, range 26-97) underwent HRM. UES relaxation parameters were interpreted twice, once visually (V) by two experts and once automatically (AS) using the ManoView ESO analysis software. Agreement between the two analysis methods was assessed using Bland-Altman plots and Lin's concordance correlation coefficient (CCC). The agreement between V and AS analyses of basal UES pressure (CCC 0.996; 95% confidence interval (CI) 0.994-0.997) and residual UES pressure (CCC 0.918; 95% CI 0.895-0.936) was good to excellent. Agreement for time to UES relaxation nadir (CCC 0.208; 95% CI 0.068-0.339) and UES relaxation duration (CCC 0.286; 95% CI 0.148-0.413) between V and AS analyses was poor. There was moderate agreement for recovery time of UES relaxation (CCC 0.522; 95% CI 0.397-0.627) and peak pharyngeal pressure (CCC 0.695; 95% CI 0.605-0.767) between V and AS analysis. AS analysis was unreliable, especially regarding the time variables of UES relaxation. Due to the difference in the clinical interpretation of pharyngoesophageal dysfunction between V and AS analysis, the use of visual analysis is justified.

Multifrequency bioelectrical impedance devices such as the InBody 770 (IB770) offer faster measurements and lower costs compared with other body composition assessments. This study validated measures from IB770 against the deuterium oxide dilution technique (D2O) and DXA and compared a four-compartment (4C) model using total body water (TBW) derived from IB770 compared with D2O. A total of 55 adult females (mean ± SD, age: 21.1 ± 2.6 years) completed IB770 and DXA scans and the D2O protocol. Lin's concordance correlation coefficients (CCCs), Bland-Altman analyses, and other equivalence tests evaluated agreement between IB770 and the criterion for measures of fat mass (FM), fat-free mass (FFM), and TBW individually and as part of 4C models. There was substantial agreement between IB770 and D2O for TBW (MD = Mean Difference) (MD = 0.34 L, CCC = 0.98) and between the IB770 and DXA for FM (MD = -0.22 kg, CCC = 0.99). IB770 overestimated FFM compared with DXA (MD = 3.15 kg, CCC = 0.91). Both 4C models had almost perfect agreement for FM (CCC = 0.99), FFM (CCC = 0.99), and body fat percentage (CCC = 0.99). IB770 is valid for assessing TBW and can be used within the context of a 4C model in females.

Centers for Medicare and Medicaid Services (CMS) has proposed a rule change to redefine the metric by which organ procurement organizations (OPOs) are evaluated. The metric relies on Centers for Disease Control and Prevention (CDC) data on inpatient deaths from causes consistent with donation among patients <75 years of age. Concerns have been raised that this metric does not account for rates of ventilation, and prevalence of cancer and severe sepsis, without objective data to substantiate or refute such concerns. We estimated OPO-level donation rates using CDC data, and used Agency for Healthcare Research and Quality/Healthcare Cost and Utilization Project data from 43 State Inpatient Databases to calculate "adjusted" donation rates. The CMS metric and the ventilation-adjusted CMS metric were highly concordant in absolute terms (Spearman and Pearson correlation coefficients ≥0.95). In the Bland-Altman plot, 100% (48/48) of paired values (standard deviations [SDs] of the CMS and "ventilation adjusted" metrics) were within 1.96 SDs of the mean difference, with near-perfect correlation in Passing and Bablok regression (Lin's concordance correlation coefficient: 0.97). The CMS metric and the ventilation/cancer/sepsis-adjusted metric were highly concordant in absolute terms (Spearman and Pearson correlation coefficients ≥0.94). In the Bland-Altman plot, 97.9% (47/48) of paired values (SDs of the CMS and "ventilation/cancer/sepsis adjusted" metrics) were within 1.96 SDs of the mean difference, with near-perfect correlation in the Passing and Bablok regression (Lin's concordance correlation coefficient: 0.97). These conclusions should provide CMS, and the transplant community, with comfort that the proposed CMS metric using CDC inpatient death data as a tool to compare OPO is not compromised by its lack of inclusion of ventilation or other comorbidity data.

Endovenous Radiofrequency Ablation (Venefit Procedure): Impact of Different Energy Rates on Great Saphenous Vein Shrinkage

Histological validation of dark-blood LGE quantification methods in rat myocardial infarction models: A 3.0T CMR study.

The utility and validity of cardiovascular diseases (CVD) risk scores are not well studied in sub-Saharan Africa. We compared and correlated CVD risk scores with carotid intima media thickness (c-IMT) among HIV-infected and uninfected people in Uganda. We first calculated CVD risk using the (1) Framingham laboratory-based score; (2) Framingham nonlaboratory score (FRS-BMI); (3) Reynolds risk score; (4) American College of Cardiology and American Heart Association score; and (5) the Data collection on Adverse Effects of Anti-HIV Drugs score. We then compared absolute risk scores and risk categories across each score using Pearson correlation and kappa statistics, respectively. Finally, we fit linear regression models to estimate the strength of association between each risk score and c-IMT. Of 205 participants, half were females and median age was 49 years [interquartile range (IQR) 46-53]. Median CD4 count was 430 cells/mm (IQR 334-546), with median 7 years of antiretroviral therapy exposure (IQR 6.4-7.5). HIV-uninfected participants had a higher median systolic blood pressure (121 vs. 110 mm Hg), prevalent current smokers (18% vs. 4%, P = 0.001), higher median CVD risk scores (P < 0.003), and greater c-IMT (0.68 vs. 0.63, P = 0.003). Overall, FRS-BMI was highly correlated with other risk scores (all rho >0.80). In linear regression models, we found significant correlations between increasing CVD risk and higher c-IMT (P < 0.01 in all models). In this cross-sectional study from Uganda, the FRS-BMI correlated well with standard risk scores and c-IMT. HIV-uninfected individuals had higher risk scores than HIV-infected individuals, and the difference seemed to be driven by modifiable factors.

To assess the utility of cardiovascular disease (CVD) risk scores compared to age or years since menopause for prediction of CVD events in the WHI clinical trials. Briefly, in the randomized clinical trial 27,347 postmenopausal women age 50 to 79 years entered from 1993 to 1998. Women with a uterus (16,608) were randomized to receive daily oral conjugated equine estrogen (CEE) (0.625 mg) plus medroxyprogesterone acetate (2.5 mg) (5.7 years or placebo), while women with a hysterectomy (10,739) were randomized to receive daily oral CEE (0.625 mg) alone or placebo (7.2 y). CVD risk scores were assessed at baseline and CVD events were adjudicated throughout the follow-up period to the end of the main study phase and to the end of cumulative follow-up. The median follow-up time after the start of the randomized clinical trial to the end of the main study phase was 8.2 years. The median follow-up time to the end of cumulative follow-up was 17.6 years. We compared The American Heart Association/American College of Cardiology (AHA/ACC) and Framingham Heart Study risk scores to age or years since menopause all obtained at baseline to predict subsequent CVD events. The absolute event rates, hazard ratios, and C-statistics (Uno Concordance from Cox proportional models) were compared. Overall, the hazard ratios for CVD events were highest with calculated CVD scores calculated at trial onset both at the end of the main study (ranging from 2.02 to 10.8 for Q2-Q5, compared to Q1) and at cumulative follow-up (ranging from 1.76 to 8.86 for Q2-Q5, compared to Q1). While older age and years since menopause at baseline were also associated with higher CVD event rates, better risk prediction was accomplished by using CVD risk scores. The Framingham Heart Study BMI score had the highest C-statistic at the end of the main study (0.711) and after 17.6 years through the end of follow-up (0.689). CVD risk scores can help identify postmenopausal women at higher risk for CVD beyond age or time since menopause. Risk scoring that better estimates vascular aging may facilitate CVD risk prevention. When performed prior to initiation of menopausal hormone therapy, scores can better inform HT risk/benefit discussions.