Natural course of coronary artery calcium progression in Asian population with an initial score of zero

Gender Differences in Subclinical Coronary Atherosclerosis in the Asian Population With a Coronary Artery Calcium Score of Zero

There is little evidence on whether gender difference influences the incidence of subclinical coronary atherosclerosis in Asian populations with a 0 score. In this study, we investigated the influence of age and gender on the extent of subclinical coronary atherosclerotic burden within a healthy Asian population with a 0 coronary artery calcium (CAC) score. A total of 934 participants (320 women and 614 men) from Taiwan's Han Chinese population with an initial CAC score of 0 were included in this study. They underwent 2 consecutive cardiac computed tomography scans over a clinical follow-up period of 4.35 ± 2.37 years. Clinical information and laboratory measurements were collected for analysis. Compared with the female group, the male group demonstrated significantly higher rates of subclinical CAC progression (27.4% vs 13.8%, p <0.001). Across the age group deciles (≤40, 41 to 50, 51 to 60, ≥61 years), the male group had a higher prevalence of subclinical CAC progression than the female group. For the subclinical CAC progression, the logistic regression model demonstrated that age, gender (male gender), cholesterol level, and follow-up period were statistically significant parameters. In conclusion, these findings support that a gender difference impacts the long-term natural course of subclinical coronary calcification conversion in women compared with men, suggesting that the gender-based effect on coronary CAC conversion plays an important role in subclinical coronary atherosclerosis risk stratification in personalized preventive medicine.

HDL-cholesterol concentration and its association with coronary artery calcification: a systematic review and meta-analysis

BACKGROUND

Coronary artery calcification (CAC) is a potential risk marker of coronary atherosclerosis that has high specificity and sensitivity. However, the association between high-density lipoprotein cholesterol (HDL-C) concentration and CAC incidence and progression is controversial.

METHODS

PubMed, Embase, Web of Science, and Scopus were systematically searched to identify relevant observational studies up to March 2023 and assessed the methodological quality using Newcastle-Ottawa Scale (NOS) scale. Random-effects meta-analysis was used to estimate pooled odds ratios (OR) and 95% confidence interval considering heterogeneity across studies.

RESULTS

Of the 2,411 records, 25 cross-sectional (n = 71,190) and 13 cohort (n = 25,442) studies were included in the systematic review. Ten cross-sectional and eight cohort studies were not eligible and were omitted from the meta-analysis. A total of 15 eligible cross-sectional studies (n = 33,913) were included in the meta-analysis and pooled results revealed no significant association between HDL-C and CAC > 0, CAC > 10, or CAC > 100 [pooled OR: 0.99 (0.97, 1.01)]. Meta-analysis of the 5 eligible prospective cohort studies (n = 10,721) revealed no significant protective effect of high HDL-C against CAC > 0 [pooled OR: 1.02 (0.93, 1.13)].

CONCLUSIONS

According to this analysis of observational studies, high HDL-C levels were not found to predict protection against CAC. These results suggest HDL quality rather than HDL quantity is important for certain aspects of atherogenesis and CAC.

REGISTRATION NUMBER

CRD42021292077.

Coronary CT angiography for preoperative evaluation of non-cardiac surgery in patients with thoracic tumors: preliminary exploratory analysis in a retrospective cohort

PURPOSE

Noninvasive coronary CT angiography (CCTA) was used to retrospectively analyze the characteristics of coronary artery disease (CAD) in patients with thoracic tumors and the impact of the results on clinical surgery decision-making, thus increasing the understanding of perioperative cardiac risk evaluation.

METHOD

A total of 779 patients (age 68.6 ± 6.6 years) with thoracic tumor (lung, esophageal, and mediastinal tumor) scheduled for non-cardiac surgery were retrospectively enrolled. Patients were divided into two groups: accepted or canceled surgery. Clinical data and CCTA results were compared between the two groups, and multivariate logistic regression analysis was performed to determine predictors of the events of cancellations of scheduled surgeries.

RESULTS

634 patients (81.4%) had non-significant CAD and 145 patients (18.6%) had significant CAD. Single‑, 2‑, and 3‑ vessel disease was found in 173 (22.2%), 93 (11.9%) and 50 (6.4%) patients, respectively. 500 (64.2%), 96 (12.3%), 96 (12.3%), 56 (7.2%) and 31 (4.0%) patients were rated as CACS 0, 1-99, 100-399, 400-999 and > 1000, respectively. Cancellations of scheduled procedures continue to increase based on the severity of the stenosis and the number of major coronary artery stenosis. The degree of stenosis and the number of vascular stenosis were independent predictors of cancelling scheduled surgery.

CONCLUSIONS

For patients with thoracic tumors scheduled for non-cardiac surgery, the results suggested by CCTA significantly influenced surgery planning and facilitated to reduce perioperative cardiovascular events.

Comparing the pooled cohort equations and coronary artery calcium scores in a symptomatic mixed Asian cohort

Background

The value of pooled cohort equations (PCE) as a predictor of major adverse cardiovascular events (MACE) is poorly established among symptomatic patients. Coronary artery calcium (CAC) assessment further improves risk prediction, but non-Western studies are lacking. This study aims to compare PCE and CAC scores within a symptomatic mixed Asian cohort, and to evaluate the incremental value of CAC in predicting MACE, as well as in subgroups based on statin use.

Methods

Consecutive patients with stable chest pain who underwent cardiac computed tomography were recruited. Logistic regression was performed to determine the association between risk factors and MACE. Cohort and statin-use subgroup comparisons were done for PCE against Agatston score in predicting MACE.

Results

Of 501 patients included, mean (SD) age was 53.7 (10.8) years, mean follow-up period was 4.64 (0.66) years, 43.5% were female, 48.3% used statins, and 50.0% had no CAC. MI occurred in 8 subjects while 9 subjects underwent revascularization. In the general cohort, age, presence of CAC, and ln(Volume) (OR = 1.05, 7.95, and 1.44, respectively) as well as age and PCE score for the CAC = 0 subgroup (OR = 1.16 and 2.24, respectively), were significantly associated with MACE. None of the risk factors were significantly associated with MACE in the CAC > 0 subgroup. Overall, the PCE, Agatston, and their combination obtained an area under the receiver operating characteristic curve (AUC) of 0.501, 0.662, and 0.661, respectively. Separately, the AUC of PCE, Agatston, and their combination for statin non-users were 0.679, 0.753, and 0.734, while that for statin-users were 0.585, 0.615, and 0.631, respectively. Only the performance of PCE alone was statistically significant (p = 0.025) when compared between statin-users (0.507) and non-users (0.783).

Conclusion

In a symptomatic mixed Asian cohort, age, presence of CAC, and ln(Volume) were independently associated with MACE for the overall subgroup, age and PCE score for the CAC = 0 subgroup, and no risk factor for the CAC > 0 subgroup. Whilst the PCE performance deteriorated in statin versus non-statin users, the Agatston score performed consistently in both groups.

Assessment of Calcium Score Cutoff Point for Clinically Significant Aortic Stenosis on Lung Cancer Screening Program Low-Dose Computed Tomography-A Cross-Sectional Analysis

Low-dose computed tomography (LDCT) is predominantly applied in lung cancer screening programs. Tobacco smoking is the main risk factor for developing lung cancer but is also common for cardiovascular diseases, including aortic stenosis (AS). Consequently, an increased prevalence of cardiovascular diseases is expected in lung cancer screenees. Therefore, initial aortic valve calcification evaluation should be additionally performed on LDCT. The aim of this study was to estimate a calcium score (CS) cutoff point for clinically significant AS diagnosis based on LDCT, confirmed by echocardiographic examination. The study included 6631 heavy smokers who participated in a lung cancer screening program (MOLTEST BIS). LDCTs were performed on all individuals and were additionally assessed for aortic valve calcification with the use of CS according to the Agatston method. Patients with CS ≥ 900 were referred for echocardiography to confirm the diagnosis of AS and to evaluate its severity. Of 6631 individuals, 54 met the inclusion criteria and underwent echocardiography for confirmation and assessment of AS. Based on that data, receiver operating characteristic (ROC) curves of CS were plotted, and cutoff points for clinically significant AS diagnosis were established: A CS of 1758 for at least moderate AS had 85.71% (CI 65.36-95.02%) sensitivity and 75.76% (CI 58.98-87.17%) specificity; a CS of 2665 for severe AS had 87.5% (CI 73.89-94.54%) sensitivity and 76.92% (CI 49.74-91.82%) specificity. This is the first study to assess possible CS cutoff points for diagnosing clinically significant AS detected by LDCT in lung cancer screening participants. LDCT with CS assessment could enable early detection of patients with clinically significant AS and therefore identify patients who require appropriate treatment.

Assessing Agreement When Agreement Is Hard to Assess-The Agatston Score for Coronary Calcification

Method comparison studies comprised simple scatterplots of paired measurements, a 45-degree line as benchmark, and correlation coefficients up to the advent of Bland-Altman analysis in the 1980s. The Agatston score for coronary calcification is based on computed tomography of the heart, and it originated in 1990. A peculiarity of the Agatston score is the often-observed skewed distribution in screening populations. As the Agatston score has manifested itself in preventive cardiology, it is of interest to investigate how reproducibility of the Agatston score has been established. This review is based on literature findings indexed in MEDLINE/PubMed before 20 November 2021. Out of 503 identified articles, 49 papers were included in this review. Sample sizes were highly variable (10-9761), the main focus comprised intra- and interrater as well as intra- and interscanner variability assessments. Simple analysis tools such as scatterplots and correlation coefficients were successively supplemented by first difference, later Bland-Altman plots; however, only very few publications were capable of deriving Limits of Agreement that fit the observed data visually in a convincing way. Moreover, several attempts have been made in the recent past to improve the analysis and reporting of method comparison studies. These warrant increased attention in the future.

Novel nomogram for predicting coronary vulnerable plaque risk in patients with coronary artery disease

Objective: To develop and validate a nomogram for predicting coronary vulnerable plaques (VPs) in coronary artery disease (CAD) patients. Methods: One hundred seventy-seven CAD patients were enrolled in the training group. Another 60 patients were included for validation. Based on the identified independent risk factors, a nomogram model was developed and then validated. Results: Type 2 diabetes, hypertension, neutrophil-to-lymphocyte ratio, low-density lipoprotein cholesterol, MCP-1 and MMP-9 were found to be independent risk factors for coronary VPs. Both internal and external validation showed this nomogram had satisfactory discrimination via receiver operating characteristic curves, calibration via calibration plots and clinical application values via decision curve analysis. Conclusion: The authors established a nomogram model predicting coronary VP risk in CAD patients with promising clinical application value.

Intraindividual evaluation of effects of image filter function on image quality in coronary computed tomography angiography

Objectives

To evaluate whether applying image filters (smooth 3D+ and edge-2) improves image quality in coronary CT angiography (CCTA).

Methods

Ninety patients (routine group) with suspected coronary artery diseases based on 16-cm wide coverage detector CT findings were retrospectively enrolled at a chest pain center from December 2019 to September 2021. Two image filters, smooth 3D+ and edge-2 available on the Advantage Workstation (AW) were subsequently applied to the images to generate the research group (SE group). Quantitative parameters, including CT value, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), image sharpness and image quality score, and diagnostic accuracy were compared between the two groups.

Results

A total of 900 segments from 270 coronary arteries in 90 patients were analyzed. SNR, CNR, and image sharpness for vessels and image quality scores in the SE group were significantly better than those in the routine group (all p < 0.001). The SE group showed a slightly higher negative predictive value (NPV) on the left anterior descending artery and right coronary artery (RCA) stenosis evaluations, as well as total NPV. The SE group also showed slightly higher sensitivity and accuracy than the routine group on RCA stenosis evaluation.

Conclusion

The use of an image filter combining smooth 3D+ and edge-2 on an AW could improve the image quality of CCTA and increase radiologists' diagnostic confidence.

Artificial Intelligence-Enabled ECG Algorithm for the Prediction of Coronary Artery Calcification

Coronary artery calcium (CAC), which can be measured in various types of computed tomography (CT) examinations, is a hallmark of coronary artery atherosclerosis. However, despite the clinical value of CAC scores in predicting cardiovascular events, routine measurement of CAC scores is limited due to high cost, radiation exposure, and lack of widespread availability. It would be of great clinical significance if CAC could be predicted by electrocardiograms (ECGs), which are cost-effective and routinely performed during various medical checkups. We aimed to develop binary classification artificial intelligence (AI) models that predict CAC using only ECGs as input. Moreover, we aimed to address the generalizability of our model in different environments by externally validating our model on a dataset from a different institution. Among adult patients, standard 12-lead ECGs were extracted if measured within 60 days before or after the CAC scores, and labeled with the corresponding CAC scores. We constructed deep convolutional neural network models based on residual networks using only the raw waveforms of the ECGs as input, predicting CAC at different levels, namely CAC score ≥100, ≥400 and ≥1,000. Our AI models performed well in predicting CAC in the training and internal validation dataset [area under the receiver operating characteristics curve (AUROC) 0.753 ± 0.009, 0.802 ± 0.027, and 0.835 ± 0.024 for the CAC score ≥100, ≥400, and ≥1,000 model, respectively]. Our models also performed well in the external validation dataset (AUROC 0.718, 0.777 and 0.803 for the CAC score ≥100, ≥400, and ≥1,000 model, respectively), indicating that our model can generalize well to different but plausibly related populations. Model performance in terms of AUROC increased in the order of CAC score ≥100, ≥400, and ≥1,000 model, indicating that higher CAC scores might be associated with more prominent structural changes of the heart detected by the model. With our AI models, a substantial proportion of previously unrecognized CAC can be afforded with a risk stratification of CAC, enabling initiation of prophylactic therapy, and reducing the adverse consequences related to ischemic heart disease.

Coronary Computed Tomography Angiography Analysis of Calcium Content to Identify Non-culprit Vulnerable Plaques in Patients With Acute Coronary Syndrome

Background

Aside from the culprit plaque, the presence of vulnerable plaques in patients with acute coronary syndrome (ACS) may be associated with future cardiac events. A link between calcification and plaque rupture has been previously described.

Aim

To assess whether analysis of the calcium component of coronary plaques using CT angiography, coronary computed tomographic angiography (CCTA) can help to detect additional vulnerable plaques in patients with non-ST elevation myocardial infarction (NSTEMI).

Materials And Methods

Cross sectional study of consecutive patients referred for NSTEMI from 30 July to 30 August 2018 with CCTA performed before coronary angiography with systematic optical coherence tomography (OCT) analysis of all coronary arteries within 24 h of clinical onset of NSTEMI. Three types of plaques were defined: culprit plaques defined by angiography (vulnerable culprit plaques–VCP) – plaques with a fibrous cap thickness < 65 microns or thrombus in OCT (vulnerable non-culprit plaque–VNCP) – plaques with a fibrous cap thickness ≥ 65 microns in OCT (stable plaque–SP).

Results

A total of 134 calcified plaques were identified in 29 patients (73% male, 59 ± 14 years) with 29(22%) VCP, 28(21%) VNCP and 77(57%) SP. Using CCTA analysis of the calcium component, factors associated with vulnerable plaques were longer calcification length, larger calcification volume, lower calcium mass, higher Agatston score plaque-specific (ASp), presence of spotty calcifications and an intimal position in the wall. In multivariate analysis, ASp, calcification length and spotty calcifications were independently associated to vulnerable plaques. There was no difference between VCP and VNCP.

Conclusions

CCTA analysis of calcium component of the plaque could help to identify additional vulnerable plaques in NSTEMI patients.

Artificial Intelligence Advancements in the Cardiovascular Imaging of Coronary Atherosclerosis

Coronary artery disease is a leading cause of death worldwide. There has been a myriad of advancements in the field of cardiovascular imaging to aid in diagnosis, treatment, and prevention of coronary artery disease. The application of artificial intelligence in medicine, particularly in cardiovascular medicine has erupted in the past decade. This article serves to highlight the highest yield articles within cardiovascular imaging with an emphasis on coronary CT angiography methods for % stenosis evaluation and atherosclerosis quantification for the general cardiologist. The paper finally discusses the evolving paradigm of implementation of artificial intelligence in real world practice.

Prevalence and significance of risk enhancing biomarkers in the United States population at intermediate risk for atherosclerotic disease: Risk Enhancing Factors in Intermediate Risk for ASCVD

BACKGROUND

Pooled cohort equations (PCEs) estimate 10-year risk for atherosclerotic cardiovascular disease (ASCVD) in US adults. One use is to guide statin eligibility. However, PCEs risk estimate is inaccurate in some US subpopulations.

OBJECTIVE

Recent cholesterol guidelines proposed addition of risk enhancing factors to improve risk assessment for selection of statin therapy. This study examines frequencies of several risk enhancing biomarkers in NHANES subjects at intermediate risk (7.5 -<20% 10-year risk for ASCVD) and considers how they may be used to better assess risk for individuals.

METHODS

Prevalence of the following biomarkers were determined; elevations in apolipoprotein B-containing lipoproteins, i.e., LDL cholesterol (LDL-C) (160-189 mg/dL), non-HDL-cholesterol (non-HDL-C) (190-219 mg/dL), or total apolipoprotein B (apoB) (≥ 130 mg/dL), serum triglyceride (≥175 mg/dL), hemoglobin A1c (5.7-6.4%), high sensitivity C-reactive protein (2-10 mg/L), and waist circumference ≥ 102 cm, and abnormal estimated glomerular filtration rate (15 - ≤ 60 mg/min/1.73 m²).

RESULTS

25% of NHANES population had intermediate risk. In this subpopulation, 85% had ≥ 1 biomarkers-similarly in women and men-with a third having ≥3 abnormal markers. Frequencies were not age-related, except in those 40-49 years, in whom > 40% had ≥3 abnormal biomarkers. It made little difference whether LDL-C, non-HDL-C or apoB was used as the atherogenic lipoprotein.

CONCLUSION

Three or more enhancing risk factors in intermediate risk subjects can complement PCE-estimated 10-year risk and guide the patient-provider discussion toward use of lipid-lowering medication. Future research is needed to integrate risk estimates by PCE and multiple risk enhancers.

Cholesterol Control for Subclinical Coronary Atherosclerosis in Subjects Without Indication for Statin Therapy

Low-risk individuals still experience adverse cardiac events. We sought to evaluate long-term cardiac events and predictors for subclinical coronary atherosclerosis in subjects without indication for statin therapy. We analyzed 3,272 individuals without indication for statin therapy who voluntarily underwent coronary computed tomography angiography as part of a general health examination. A cardiac event was defined as a composite of cardiac death, nonfatal myocardial infarction, unstable angina requiring hospitalization, or late coronary revascularization. The prevalence of normal coronary arteries, nonobstructive coronary artery disease (CAD) (diameter stenosis < 50%), and obstructive CAD (diameter stenosis ≥50%) was 2,338 (71.5%), 809 (24.7%), and 125 (3.8%), respectively. During the follow-up period (median 5.3 [interquartile range, 4.3-6.3] years), the 6-year event-free survival rates were 99.2%±0.2% in subjects with normal coronary arteries, 98.2%±0.6% in those with nonobstructive CAD, and 90.2%±2.7% in those with obstructive CAD (log-rank p < 0.001). Multivariable regression analysis showed that low-density lipoprotein cholesterol (LDL-C, odds ratio [OR]: 1.012; 95% confidence interval (CI): 1.005-1.019) and high-density lipoprotein cholesterol (HDL-C, OR: 0.968; 95% CI: 0.952-0.984) levels were associated with subclinical obstructive CAD, together with age (OR: 1.080; 95% CI: 1.040-1.121) and male sex (OR: 3.102; 95% CI: 1.866-5.155) (all p < 0.05). In conclusion, LDL-C and HDL-C are significantly associated with the presence of subclinical obstructive CAD with a worse prognosis in subjects without indication for statin therapy. These findings suggest that stricter control of LDL-C and HDL-C levels may be necessary for primary prevention even in a relatively low-risk population.

Use of Coronary Computed Tomography Angiography to Screen Hospital Employees with Cardiovascular Risk Factors

The objective of this study was to determine how coronary computed tomography angiography (CCTA) can be employed to detect coronary artery disease in hospital employees, enabling early treatment and minimizing damage. All employees of our hospital were assessed using the Framingham Risk Score. Those with a 10-year risk of myocardial infarction or death of >10% were offered CCTA; the Coronary Artery Disease Reporting and Data System (CAD-RADS) score was the outcome. A total of 3923 hospital employees were included, and the number who had received CCTA was 309. Among these 309, 31 (10.0%) had a CAD-RADS score of 3-5, with 10 of the 31 (32.3%) requiring further cardiac catheterization; 161 (52.1%) had a score of 1-2; and 117 (37.9%) had a score of 0. In the multivariate logistic regression, only age of ≥ 55 years (p < 0.05), hypertension (p < 0.05), and hyperlipidemia (p < 0.05) were discovered to be significant risk factors for a CAD-RADS score of 3-5. Thus, regular and adequate control of chronic diseases is critical for patients, and more studies are required to be confirmed if there are more significant risk factors.

Severe, but not mild to moderate, non-alcoholic fatty liver disease associated with increased risk of subclinical coronary atherosclerosis

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) is associated with high risk of cardiovascular disease. The prevalence is increasing to 45-65% in the general population with routine health check-up, and most subjects have the mild degree NAFLD in recent years. Moreover, there are no studies on the association between NAFLD severity and coronary atherosclerosis in the real-world setting by ultrasonography.

METHODS

The aim of this study was to determine the relationship between the severity of NAFLD and subclinical coronary atherosclerosis. Overall, 817 subjects meet criteria for NAFLD were enrolled in the retrospective cohort study (155 subjects were excluded). The severity of NAFLD was divided into the normal, mild, moderate and severe degree based on the finding of abdominal ultrasonography. The assessment of coronary atherosclerosis was based on CAC scan/coronary CT angiography finding in terms of CAC score ≧ 100, CAC score ≧ 400, CAD-RADS ≧ 3 and presence of vulnerable plaque(s).

RESULTS

A significant linear trend was observed between the severity of NAFLD and subclinical coronary atherosclerosis. Compared with the reference group (including normal, mild, and moderate NAFLD), severe degree NAFLD was the independently associated risk of subclinical coronary atherosclerosis in term of CAC score ≧ 100, CAC score ≧ 400, CAD-RADS ≧ 3 and presence of vulnerable plaque(s) based on binary logistic regression after adjustment for FRS score and body fat percentage.

CONCLUSIONS

Severe degree, but not mild to moderate, was associated with high risk of subclinical coronary atherosclerosis, independently of FRS score and body-fat percentage.

A LASSO-Derived Risk Model for Subclinical CAC Progression in Asian Population With an Initial Score of Zero

Background: This study is aimed at developing a prediction nomogram for subclinical coronary atherosclerosis in an Asian population with baseline zero score, and to compare its discriminatory ability with Framingham risk score (FRS) and atherosclerotic cardiovascular disease (ASCVD) models.

Methods: Clinical characteristics, physical examination, and laboratory profiles of 830 subjects were retrospectively reviewed. Subclinical coronary atherosclerosis in term of Coronary artery calcification (CAC) progression was the primary endpoint. A nomogram was established based on a least absolute shrinkage and selection operator (LASSO)-derived logistic model. The discrimination and calibration ability of this nomogram was evaluated by Hosmer–Lemeshow test and calibration curves in the training and validation cohort.

Results: Of the 830 subjects with baseline zero score with the average follow-up period of 4.55 ± 2.42 year in the study, these subjects were randomly placed into the training set or validation set at a ratio of 2.8:1. These study results showed in the 612 subjects with baseline zero score, 145 (23.69%) subjects developed CAC progression in the training cohort (N = 612), while in the validation cohort (N = 218), 51 (23.39%) subjects developed CAC progression. This LASSO-derived nomogram included the following 10 predictors: “sex,” age,” “hypertension,” “smoking habit,” “Gamma-Glutamyl Transferase (GGT),” “C-reactive protein (CRP),” “high-density lipoprotein cholesterol (HDL-C),” “cholesterol,” “waist circumference,” and “follow-up period.” Compared with the FRS and ASCVD models, this LASSO-derived nomogram had higher diagnostic performance and lower Akaike information criterion (AIC) and Bayesian information criterion (BIC) value. The discriminative ability, as determined by the area under receiver operating characteristic curve was 0.780 (95% confidence interval: 0.731–0.829) in the training cohort and 0.836 (95% confidence interval: 0.761–0.911) in the validation cohort. Moreover, satisfactory calibration was confirmed by Hosmer–Lemeshow test with P-values of 0.654 and 0.979 in the training cohort and validation cohort.

Conclusions: This validated nomogram provided a useful predictive value for subclinical coronary atherosclerosis in subjects with baseline zero score, and could provide clinicians and patients with the primary preventive strategies timely in individual-based preventive cardiology.