Composite carotid intima-media thickness as a risk predictor of coronary heart disease in a selected population in Sri Lanka.

BACKGROUND: Segment-specific variations of carotid intima-media thickness (CIMT) have not been assessed in South Asian populations. The purpose of this study was to determine if segment-specific CIMTs or a composite-CIMT score is a better risk predictor of coronary heart disease in South Asian populations.
METHODS: A comparative prospective study was conducted from November 2019 to October 2020 in a hospital in Colombo, Sri Lanka. Based on pre-defined inclusion and exclusion criteria, cases (having a diagnosis of Coronary Heart Disease (CHD), n = 338) and controls (non-CHD group, n = 356) were recruited. Ultrasound examination of the common carotid (CCA), the carotid bulb (CB) and the internal carotid segments (ICA) of the carotid vessels was conducted by a radiologist, and CIMTs were measured. A composite-CIMT score defined as the average value of all six segments of the left and right sides was derived.
RESULTS: 694 participants were enrolled (male n = 399, 57.5%). The mean (±SD) age of the study sample was 60.2 (±9.86) years. There were variations in segment-specific values between the left and right vessels. The mean composite-CIMT value of the CHD group was significantly higher than that of the non-CHD group. A composite-CIMT score of 0.758 had a sensitivity of 98.4% and a specificity of 64.6% in distinguishing CHD from non-CHD groups (Area under the curve (AUC): 0.926).
CONCLUSIONS: Carotid artery segment-specific CIMT variations were present in this population. The composite CIMT score is better than segment-specific CIMTs in predicting CHD and may be used to predict CHD in this population.

Introduction

Coronary heart disease (CHD) and stroke have been identified as the most common cardiovascular disease (CVD) that causes the highest mortality globally [1]. The considerably higher impact of morbidity and mortality due to CHD and stroke is seen in low- and middle-income countries compared to the developed world [1]. Higher mortality, mainly of sudden deaths, and poor prognosis inevitably make early identification of the “high-risk CHD population” a priority [2]. Primary prevention is a significant component of public health that plays a pivotal role in identifying at-risk CHD populations. Many tools have been identified, developed, and effectively used to screen at-risk populations and assess individual risk of CHD [3]. Measuring carotid artery intima-media thickness (CIMT) is one such method [4]. The CIMT and its predictability of CHD are still arguable among the scientific community. Variation of the CIMT measurement sites, lack of uniform imaging protocols and different cutoff values are some reasons for this ambiguity [5, 6]. Various combinations of CIMT values of carotid segments have been used to predict CHD [7, 8]. Up to date, the majority of research has been conducted on Western populations in the United States and European countries. There are considerably few studies on CIMT among Asians [9].

There is a scarcity of data on carotid intima-media thickness (CIMT) measured adhering to Mannheim Consensus and American Society of Echocardiography guidelines in the South East Asian region. The segment-specific variation and the importance of the composite CIMT score in coronary heart disease risk prediction in the region remain unclear. We assessed segment-specific CIMT variations and the potential of using the composite CIMT score for risk prediction of coronary heart diseases in a South Asian population in Sri Lanka.

Methodology

Study design

This comparative study was carried out among participants recruited prospectively at a private hospital in Colombo, Sri Lanka.

Study population

The study population comprised participants aged 40 to 74 years who underwent regular health check-ups after assessment of traditional cardiovascular risk factors at the health screening centre (n = 476) and those who underwent elective/emergency coronary angiography and coronary interventions (PTCA or CABG) following the diagnosis of Acute Coronary Syndrome(ACS) (unstable angina, non-ST-elevation myocardial infarction/ST-elevation myocardial infarction) (n = 295) at the hospital within the last one month. The study population was divided into two; cases of CHD and controls (non-CHD group). 476 participants who attended the health screening centre were screened for CHD (Fig 1) and 65 participants were diagnosed as having CHD based on the criteria given below. The rest of the participants (n = 356) were considered as the non-CHD group. Of the 295 participants who underwent elective/emergency coronary angiography and coronary interventions (PTCA or CABG) during the last one month that comprised the CHD group, 22 were excluded as they did not satisfy inclusion and exclusion criteria given below. The remaining 273 CHD group subjects were added to the 65 identified through the health screening centre to give a total of 338 participants in the CHD group (Fig 1). A person with more than one of the following was considered as a case of coronary heart disease: suggestive medical history having angina type chest pain, significant ECG changes suggestive of an acute coronary syndrome, positive treadmill test, echocardiographic evidence (wall hypokinesia) and positive test results of Troponin I and T. Any person with a history of stroke/TIA, malignancy, who had undergone carotid endarterectomy, history of connective tissue disease, history suggestive or diagnosis of, acute coronary syndrome and signs of an ongoing infection was excluded from the control group.

Fig 1

Flow chart of study participants recruitment.

Data collection

Based on an extensive literature review and discussions with experts, an interviewer-administered questionnaire was developed following the STEPS manual of WHO. The questionnaire was developed in English and translated into Sinhala and Tamil; the translations were back-translated into English by two independent translators. The back translations were compared with the original English version, and slight modifications were made. The translated questionnaires were pre-tested among 10 participants not included in the study, and minor revisions were done to improve the understanding and flow of questions. Two data collectors with a medical background were recruited and given a 5-day training, including a mock data collection session on how to extract data from past records. The questionnaire was used to obtain details on demographic and socioeconomic characteristics, past medical/surgical history, clinical characteristics, results of relevant biochemical investigations and anthropometric measurements. Age was calculated in years.

Anthropometric measurements

Height was measured using a stadiometer. The participants were requested to remove their shoes, any headgear before taking the measurement. The participants stood with their back to the wall and looked directly forward (straight ahead without tilting their head upwards) keeping the eyes at the same level as the ears; the backs of their feet, calves, buttocks, upper back and the back of their head were all be in contact with the wall directly underneath the drop-down measuring device. The drop-down measuring device was brought down until it rested gently on the top of the participants head. Height was measured once to the nearest 0.5cm [10].

Bodyweight was measured using an electronic digital weighing scale that was calibrated before each session using known weights placed on a firm flat surface. Each participant was asked to remove any ‘heavy’ items from their pockets (key’s, wallets, etc.) and remove any heavy clothing or apparel items (jackets, shoes, etc.). The participant was asked to step on the scale looking straight ahead until requested to step off. Body weight was measured once to the nearest 100g [10].

Body Mass Index (BMI) was calculated as the body weight (kg) divided by the squared height in metres (m2) [10].

Waist circumference was measured at the midpoint between the lower margin of the last palpable rib and the top of the iliac crest (hip bone) using a stretch‐resistant tape that provided a constant 100 g tension. The tape was placed horizontally across the back and front of the participant parallel to the floor and the measurement taken at the end of a normal expiration and with the arms relaxed at the sides. The waist and hip circumferences were measured once to the nearest 0.1 cm [10].

Hip circumference was measured once around the buttocks’ widest portion, with the tape parallel to the floor to the nearest 0.1 cm [10].

The waist-hip-ratio was calculated by dividing waist circumference measurement by the hip circumference measurement [10].

Biochemical studies

Blood samples were drawn from the anterior cubital vein after overnight fasting of at least 12 hours for biochemical assays after obtaining informed consent. 5ml of venous blood was drawn from each subject under aseptic conditions using a TERUMO sterile, non-toxic, non-pyrogenic syringe with a 23 G 11/4” disposable needle by trained phlebotomists. The blood samples were transferred to vacutainers, where serum was automatically separated. The vacutainers were handed over to the laboratory at Nawaloka Hospital immediately. The following investigations were carried out. Fasting Blood Sugar (FBS), Lipid Profile and Full Blood Count (FBC).

Ultrasound measurements of CIMT

All the participants underwent a carotid Doppler scan free of charge. The same consultant radiologist performed all the carotid Doppler scans using a 7.5-MHz linear probe ultrasound imaging system. A Sonoscape S50 Trolley mount colour Doppler ultrasound system [Yi Zhe building, Yu Quan Road, Shen Zhen, 518051, China] was used. Digital image acquisition and storage were made using DICOM 3.0 (Digital Imaging and Communications in Medicine), which has a footprint of 4cm, a display depth of 4cm and a frame rate of 256 /second. IMT was measured on a two-dimensional (2D) grey-scale image. CIMT measurements were obtained from1) the far wall in a 1cm segment in the distal common carotid arteries (CCA) [1cm proximal to the dilatation of the CB]; 2) 1 cm in the carotid bulb (CB) [1 cm proximal to the flow divider]; and 3) 1 cm in the proximal internal carotid arteries (ICA) [immediately distal to the flow divider] of both the right and left arteries in 3 different projections (anterior, lateral, and posterior).CIMT measurements were obtained in segments where a plaque was not identified. A plaque was defined as a focal structure that encroaches into the arterial lumen of at least 0.5 mm or 50% of the surrounding IMT value or demonstrates a thickness >1.5 mm as measured from the media-adventitia interface to the intima-lumen interface based on the Mannheim Carotid Intima-Media Thickness and Plaque Consensus [11]. Measurements were obtained in the frames concordant with the ECG R-wave [12]. The R-wave in the electrocardiogram represents the end-diastolic moment where the thickest CIMT can be obtained [13, 14]. The measures considered in these analyses were mean and maximal IMT of the CCA, CB, and ICA and all carotid arteries (ACA) segments (CCA, CB and ICA) assessed in the left and right carotid arteries. The mean carotid IMT was defined as the average of right and left IMT measures observed in the right and left CA segments as described by Grau et al. (2012) [15]. Similarly, the composite CIMT score (mean ACA IMT) was defined as the average of all intima-media thickness measurements (IMT) in the three right and left segments of the carotid artery (CCA, CB, and ICA);[Ʃ (left / right CCA+ left / right CB+ left/right ICA)/6]. All findings were stored on the hard disk of the sonographer’s computer and then sent to the core laboratory for anonymous image analysis.

Assessment of quality index for CIMT measurements

CIMT was measured automatically. The Structural Similarity (SSIM) index was used to compare the image quality obtained by the consultant radiologist with the sample image generated by the machine. The SSIM values range between 0 and 1, 1 referring to a perfect match between the radiologist’s image and the manufacturer’s image. A sample of 51 from the CHD group and a sample of 50 from the non-CHD group were randomly selected for quality index assessment. SSIM values were obtained for all three segments of the carotid arteries (CCA, CB and ICA) on both sides. In the non-CHD group the SSIM coefficient of variation ranged from 1.2% to 1.7%; in the CHD group, the SSIM coefficient of variation ranged from 1.4% to 1.8%.

A schematic representation of the measurement of CIMT is given Fig 2.

Fig 2

Anatomical, histological and ultrasound view of carotid artery segments and CIMT measurement.

(Created with BioRender.com).

Data analysis

Data were entered into Microsoft EXCEL worksheets (version 2007, Microsoft Corp., Seattle, Washington) and checked manually and corrected where necessary. Descriptive statistics were derived and expressed as measures of central tendency and frequency. Independent sample t-tests were used to compare mean scores of age, height, weight, Body mass index (BMI), waist and hip circumferences, waist-hip ratio, CIMTs and biochemical investigations that were normally distributed among CHD and /non-CHD groups. Non-parametric tests were used for the analysis of non-normal data (Kruskal-Wallis test and Mann-Whitney U test). The segment-specific CIMT values were compared using one way ANOVA. ROC analysis was used for the comparison of CIMT cut-off values which predict coronary heart disease in the CCA, the CB, the ICA and the composite CIMT score. Multiple linear regression analysis was used to identify predictors for the composite CIMT score. Data were analysed using Statistical Package for Social Sciences version 20 (SPSS) (SPSS 20.0, Chicago, Illinois, USA) and STATA version 16 (16.0, Texas, USA). Statistical significance was considered if the p-value was<0.05.

Ethics approval

Ethical approval for the study was obtained from the Ethics Review Committee of the Faculty of Medicine, University of Kelaniya (Reference number: P/118/06/2019). Permission to conduct the study was obtained from the Nawaloka Hospital PLC management. All participants provided informed written consent for their data to be included in the study. All results were given to participants. None of the participants had to pay for ultrasonography or additional tests that were done outside the routine tests that were carried out.

Results

There were 694 participants comprising 338 cases and 356 controls, with the majority being male (n = 399, 57.5%). The mean age (±SD) of the study sample was 60.2 (±9.86) years, the ages ranging from 40 to 75 years. The profile of the study population is shown in Table 1. The CHD group was significantly older than the non-CHD group (61.77±9.43 years vs 58.71±10.04 years; P = 0.0001) (Table 1). Significantly higher proportions of smokers (95/144, 65.97%), alcohol consumers (134/200, 67.0%), diabetics (156/205, 76.09%), hypertensives (115/162, 70.98%) and those having dyslipidemia (163/219, 74.43%) were in the CHD group (P = 0.0001). The mean (±SD) body mass index (BMI) and waist-hip ratio (WHR) was significantly higher in the CHD group than in the non-CHD group (BMI; 71.20±6.27Kg/m2 in CHD vs68.24±5.74Kg/m2 in non-CHD group: WHR; CHD vs non-CHD: 0.89±0.06 vs 0.83±0.08, P = 0.0001) (Table 1).

Table 1

Profile of the study population.

Variable	CHD group	Non-CHD group	Total sample	Statistical test
	(N = 338)	(N = 356)	(N = 694)	(P-value)
Demographic factors
Age (Years), Mean±SD	61.77±9.43	58.71±10.04	60.2±9.86	0.0001a
Male, N (%)	212 (62.7)	187 (52.5)	399 (57.5)	0.006b
Traditional Risk factors
Smoker1, N (%)	95 (28.1)	49 (13.8)	144 (20.7)	<0.0001b
Alcohol consumer2, N (%)	134 (39.6)	66 (18.5)	200 (28.8)	<0.0001b
Diabetes3, N (%)	156 (46.2)	49 (13.8)	205 (29.5)	<0.0001b
Hypertension4, N (%)	115 (34.5)	47 (13.2)	162 (23.3)	<0.0001b
Dyslipidemia5, N (%)	163 (48.2)	56 (15.7)	219 (31.6)	<0.0001b
Anthropometric measurements
Bodyweight (Kg), Mean±SD	71.20±6.27	68.24±5.74	69.68±6.18	0.001a
Height (m), Mean±SD	1.59±0.07	1.61±0.07	1.59±0.07	0.011a
BMI [Kg/m2], Mean±SD	28.36±3.92	26.68±3.51	27.50±3.80	0.0001a
Waist-Hip ratio, Male, Mean±SD	0.89±0.07	0.83±0.07	0.86±0.08	0.0001a
Waist-Hip ratio, Female. Mean±SD	0.89±0.06	0.83±0.08	0.85±0.07	0.0001a
Biochemical factors
Fasting Blood Sugar (mg/dl) Mean±SD	119.33±29.83	100.86±21.02	109.86±27.28	0.001a
Total cholesterol (mg/dl), Mean±SD	216.90±29.68	187.58±25.53	201.86±31.26	0.001a
HDL (mg/dl), Mean±SD	40.26±4.17	47.09±9.33	43.77±8.04	0.001a
LDL (mg/dl), Mean±SD	122.46±19.91	113.65±27.94	117.94±24.74	0.001a
Triglycerides(mg/dl),Mean±SD	187.38±49.85	142.08±26.81	164.14±45.72	0.001a
Haemoglobin (g/dl), Mean±SD	11.59±1.41	11.65±1.40	11.62±1.40	0.557a
Neutrophil (%), Median (IQ 25%-75%)	65.50(54–79.25)	64.00(54–71.45)	65.00(54–75.67)	0.004c
Lymphocyte (%),Mean±SD	29.52±17.03	29.68±14.15	29.60±17.03	0.884a
Neutrophil/Lymphocyte ratio [NLR], Mean±SD	4.10±4.64	2.83±2.02	3.45±3.07	0.001a
Vital signs on admission or the day of the interview
Systolic blood pressure(mmHg),Mean±SD	138.02±11.73	130.24±12.29	134.03±12.62	0.0001a
Diastolic blood pressure(mmHg), Mean±SD	83.40±6.79	77.35±6.19	80.30±7.16	0.0001a
Heart rate(per/min), Mean±SD	76.50±5.33	71.32±4.41	73.84±5.52	0.0001a

Note: Smoking1: Smoking tobacco products for 12 months or more. (Male: 2–10 Daily; Female: 1 [16]). Alcohol consumer: Consume alcohol, standard drink for past 12months or more. A drink /3 to 4 days per week. (Source: WHO STEPS surveillance manual, 2017). Diabetes: Previously diagnosed or a fasting glucose concentration of more than 7mmol/L (126mg/dL). Hypertension: Previously diagnosed or raised blood pressure SBP >140mmHg and DBP>90mmHg or last two weeks on medication. Dyslipidaemia: Total cholesterol <190mg/dL and/or HDL >40mg/dL (Men) and >50(Female) and / or Triglyceride >150mg/dL. (Source: WHO STEPS surveillance manual, 2017). CKD: Chronic Kidney Disease. BMI: Body Mass Index.

aIndependent sample t-test

b comparison of two proportions z-test

cMann-Whitney U test.

Table 2 shows the variation of segment-specific mean CIMT values in CHD and non-CHD groups. There were statistically significant differences in CIMT values between the different segments on both the left and right sides in the CHD and the non-CHD groups (Table 2). The highest average CIMT was reported in the CCA in the non-CHD group (0.73±0.15mm) and the CB in the CHD group (0.89±0.10mm). The lowest average of CIMT was in the ICA of both groups (CHD group: 0.85±0.07mm and non-CHD group: 0.70±0.11mm). There were significant differences in the mean left, right, average, and composite CIMT values between CHD and non-CHD groups (Student t-test; P<0.05 for all). The left-sided CIMT values were higher than the right side in all three segments.

Table 2

Variation of segment-specific mean CIMT values in CHD and non-CHD groups.

Segment	CHD group	P-value1	Non CHD group	P-value1	All	P-value1
	Mean±SD (mm)		Mean±SD (mm)		Mean±SD (mm)
Left CCA	0.86±0.13a	F = 13.18,df = 2, P<0.0001	0.77±0.15a	F = 3.39,df = 2, P = 0.03	0.80±0.16a	F = 3.18,df = 2, P = 0.04
CB	0.92±0.15b		0.73±0.19b		0.82±0.20b
ICA	0.87±0.11a		0.72±0.16b		0.80±0.15a
Right CCA	0.87±0.09a	F = 14.56,df = 2, P<0.0001	0.71±0.10a	F = 10.34,df = 2, P<0.0001	0.79±0.12a	F = 12.70,df = 2, P<0.0001
CB	0.86±0.09a		0.68±0.11b		0.77±0.14a
ICA	0.83±0.10b		0.67±0.12b		0.75±0.13b
Average CCA	0.86±0.13a	F = 10.65,df = 2, P<0.0001	0.73±0.15a	F = 4.71,df = 2,	0.80±0.16a	F = 3.78, df = 2, P = 0.02
CB	0.89±0.10b		0.71±0.12b	P = 0.009	0.79±0.15a
ICA	0.85±0.07a		0.70±0.11b		0.77±0.12b
Composite CIMT score	0.87±0.08	N/A	0.72±0.09	N/A	0.79±0.12	N/A

CCA: Common Carotid Artery. CB: Carotid Blub. ICA: Internal Carotid artery.CHD: Coronary Heart Disease.

1p-value from ANOVA (Post Hoc; Tukey HSD) comparing different segments of the carotid arteries separately by side and group.

The mean CIMT values of left, right, average and composite were compared between CHD and non-CHD groups (Student t-test), P<0.05).

The composite CIMT score is defined as the average value of all six segments of the left and right sides.[Ʃ (left / right CCA+ left / right CB+ left/right ICA)/6]

a, b Means having a superscript with the same letter are similar

Fig 3 shows the receiver operator characteristics (ROC) curves for predicting coronary heart disease in CCA, CB, ICA and composite CIMT score. The curve of the composite-CIMT score had the highest area under the curve (AUC: 0.926, 95% CI of AUC: 0.908–0.944) in comparison to the average CIMT values of CCA,CB and ICA. The composite CIMT score cut-off value of 0.758 had a sensitivity of 98.4% and specificity of 64.6% in distinguishing CHD and non-CHD groups (Table 3).

Fig 3

Comparison of areas under the curve (AUC) of receiver operating curves predicting coronary heart disease using the common carotid artery (CCA), carotid bulb (CB), internal carotid artery (ICA) and the composite carotid intima media thickness (CIMT) score.

Table 3

The cutoff CIMT values for segments and composite score predicting coronary heart disease risk.

Site	Cut-off value of IMT[mm]	AUC	95% CI of AUC	SE	Sensitivity	Specificity	PPV	NPV	Youden’s J statistic
CCA	0.77	0.86	0.83–0.88	0.02	82.83	75.82	80.52	74.61	0.58
CB	0.77	0.89	0.87–0.92	0.01	90.82	75.01	88.21	71.02	0.65
ICA	0.72	0.87	0.85–0.89	0.01	96.73	61.21	92.12	59.11	0.57
Composite CIMT score	0.76	0.93	0.91–0.94	0.01	98.41	64.62	91.71	66.31	0.64

IMT: Intima media thickness. CCA: Common Carotid Artery. CB: Carotid Blub. ICA: Internal Carotid artery.ACA: All carotid artery (Composite score)[Composite CIMT score = Ʃ (left / right CCA+ left / right CB+ left/right ICA)/6]. PPV: Positive predictive value: NPV: Negative predictive value. AUC: Area under the curve. SE: Standard error.

Age, having diabetes, systolic blood pressure, diastolic blood pressure, waist-hip ratio>0.9, Low Density Lipoprotein (LDL) level and Total Cholesterol (TC) were significant predictors of the composite score. An increase in High Density Lipoprotein (HDL) by one unit decreased the composite score by 0.004mm (Table 4).

Table 4

Summary of multiple linear regression analysis using the composite CIMT score as the dependent variable.

Variable	Regression coefficient	Std. error	p-value	95% confidence interval of the regression coefficient
Composite CIMT score (R2 = 0.467)
Age	0.002	0.000	<0.0001	0.002 to 0.003
Diabetes(Yes = 1)	0.048	0.008	<0.0001	0.035 to 0.066
Waist-Hip ratio>0.9	0.025	0.008	0.002	0.009 to 0.040
Systolic blood pressure(mmHg)	0.002	0.001	0.001	0.001 to 0.003
Diastolic blood pressure(mmHg)	0.003	0.001	0.001	0.002 to 0.004
HDL(mg/dl)	-0.004	0.001	0.001	-0.004 to -0.003
LDL(mg/dl)	0.001	0.001	0.004	0.000 to 0.001
TC(mg/dl)	0.001	0.001	0.001	0.000 to 0.001
Intercept	0.099

HDL: High-density lipoprotein, LDL: Low-density lipoprotein, TC: Total cholesterol

Composite CIMT score = Ʃ (left / right CCA+ left / right CB+ left/right ICA)/6

Discussion

The objectives of this study were to assess the variation of segment-specific CIMT values and the ability of the composite CIMT score in risk prediction of coronary heart disease in a South Asian population resident in Sri Lanka. The unique feature of this study is the use of the Mannheim Carotid Intima-Media Thickness protocol in measuring CIMT which was a limitation in most studies, especially in those conducted in South East Asian countries. Evidence was scarce demonstrating the ability of the CIMT-composite score predicting CHD in Asia and South East Asia.

This study shows variations in segment specific mean CIMT values in both CHD and non-CHD groups. There were also segmental differences in CIMT values between the left and right sides. A previous study reported that participants between 35 to 65 years of age had significantly thicker left-sided CIMT values as compared to the right side [17]. Ghosa and the team reported that the right-sided CIMT values are higher in diabetics (DM) and pre-diabetics compared to non-diabetics [18].

Literature suggests that the right-sided CIMT values correlate better with haemodynamic parameters, while the left-sided CIMT values correlate with biochemical indices [17]. Segment- and side-wise CIMT differences may be due to cardiovascular risk factors. In men, the differences are due to: alcohol use (at the bifurcation); physical activity (common and internal carotid arteries); BMI (all segments); diabetes (at the bifurcation and in the internal carotid artery); hypertension (in the internal carotid artery); and HDL-cholesterol (in the common carotid artery and at the bifurcation) [6]. In women the differences are due to: smoking (at the bifurcation), hypertension (in the common carotid artery), total and LDL cholesterol (at the bifurcation and in the internal carotid artery), and hs-CRP (in the common and internal carotid arteries) [6]. Although in this study the highest average CIMT was in the CCA in the non-CHD group and in the CB in the CHD group, Lara reported that highest CIMT value was in the carotid bulb, followed by CCA, and the lowest in the ICA [5].

A majority of research on CIMT and its CHD prediction ability has been conducted in the US and in European countries. There were very few studies in East Asia that included CIMT in risk prediction of an asymptomatic general population [9, 19]. Literature highlights that using CIMT cut-off values for risk prediction obtained from western populations may not be appropriate for Asians [20]. Ravani and colleagues reported that CIMT values are strongly affected by age, sex and population. It has been suggested that country-specific IMT cut-offs are needed before clinical application of CIMT values as a screening tool to predict individual cardiovascular risk [21]. In this study, CIMT values of 0.775mm for CCA and CB, 0.725 for CB and 0.758mm for the composite score may be used for risk prediction of CHD among healthy subjects; the composite score gave the best risk prediction of CHD. In an Indian population, the mean CIMT was shown to be an independent predictor of coronary artery disease (CAD) along with diabetes, waist-hip ratio, and smoking. However, CIMT was not related to the severity and complexity of the CAD as assessed by the Gensini score and Syntax score [19]. We have demonstrated segment specific CIMT variation and that the best potential cutoff values to discriminate CHD and non-CHD groups in a Sri Lankan population are obtained using the composite CIMT score.

Among French subjects without conventional cardiovascular risk factors, the mean common carotid artery intima-media thickness was 0.712 ± 0.122 mm in men and 0.682 ± 0.105 mm in women [22]. Studies conducted in Poland (2 studies) (n = 277, cut-off CIMT value—0.933mm; n = 412, cutoff CIMT value—0.76mm) [23, 24], in USA (n = 150,cut-off CIMT value -0.9mm) [25], Italy (n = 446,cut off CIMT value -0.80mm) [26], Canada (n = 217, cut-off CIMT value -0.82mm) [27], and Ireland (n = 35, cut-off CIMT value -0.9mm) [28] have reported different cut-off CIMT values to predict CHD risk. A Nigerian study, reported that a mean CIMT of 0.72 ± 0.15 mm and 0.76 ± 0.14 mm for the right and left sides, respectively, and a range of 0.5 to 0.9mm among non-hypertensive patients to be considered as cut-off points [29].

Age, diabetes, systolic blood pressure, diastolic blood pressure, waist-hip ratio, LDL and TC were significant risk predictors of the composite score after adjusting for each other; HDL was a protective factor. Different studies have shown that traditional cardiovascular risk factors such as age [30]; sex, race, smoking, alcohol consumption [31]; lack of exercise, high blood pressure [32]; dyslipidemia [33, 34]; poor dietary patterns, risk-lowering drug therapy [35-37]; glycemic status, hyperuricemia, obesity-related anthropometric parameters, obesity and obesity-related diseases [38] affect CIMT of the CCA, the CB and the ICA. These risk factors are similar to the ones we report for the CIMT composite score for the first time. As the CIMT composite score is an average of all segments of the Carotid artery, the risk factors are likely to be similar. A recent study revealed that more than 60% of CIMT cases were not explained by demographic and conventional cardiovascular risk factors [39]. Having a single CIMT cut-off value for risk prediction of CHD makes clinical application easier.

Limitations

The selected sample was confined to one private hospital in Sri Lanka and the results may not be generalizable as private health care is affordable mainly to the upper social classes. However, given the fact that the burden of NCDs is disproportionately higher in the lower social classes among persons living in low and lower middle income countries, we surmise that these values may be taken as a baseline in such groups as well. Non-traditional risk factors such as heredity and specific genotypic, immunological diseases; and effects of inflammatory cytokines, haematological parameters and infectious disease on the composite CIMT score need to be studied in a larger study.

Conclusions

There were segment-specific CIMT variations within as well as between CHD and non-CHD groups in this Sri Lankan population. The derived composite CIMT score shows the highest prediction ability of CHD and may be used to screen for CHD.

Transfer Alert

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25 May 2022

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Additional Editor Comments:

Specific issues were raised by reviewers to improve clarify. The population studied in this report is indeed under evaluated in the literature, which is a strength.

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Reviewers' comments:

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Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

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Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

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Reviewer #1: No

Reviewer #2: Yes

**********

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Reviewer #1: No

Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: This is a prospective study to evaluate correlation between segmental versus composite IMT and the occurance of CHD and the threshold for such an association. Globally the article is well understood.

Concern: in 11 months period authors claim that they have recruited 694 participants. This is 63 particiopants per month, this is 2 patients per day including week-ends (it seems impossible for me for a single center), recruitment chart flow figure is absent and is highly appreciated to clarify this issue.

A study published in February 2022 by Verma et al. https://www.sciencedirect.com/science/article/abs/pii/S0214916821001649 included south asian patients in India. How is this study different?

US measurements : should specify the technique, is it manual? If yes how many measurements per segment were done to increase reliability and what is the coefficient of variation. Is it semi automatic or automatic? if yes, what is the quality index used and the coefficient of variation for the measurements. How many operators? authors mention just one : what about inter observer variability reproductibility study? Did the authors do intra-observer reproductibility studies even if it were for a small proportion of the studied population?

Age, height, weight, BMI, waist and hip circumferences and waist-hip ratio are not mentionned in methods section nor is there mention of how they were measured, which medical device and the nearest decimal to which the meassurements were performed? Formula of BMI is lacking, although known, it should be mentioned. From the description of the methods section one cannot replicate the study which is the purpose of this section of the manuscript.

Pearson's correlation coefficients could be done to evaluate correlations between CIMT and CHD. I understand that the objective is to compare segmental IMT versus the composite IMT but such analysis would be of added value.

Results section lacks mention of the regression analysis which are seen just in the tables. Need to re write this section clearly.

Line 131, Mannheim recommendations mention linear probe, authors mention an annular probe, explanation? A figure showing an example of IMT measured on an ultrasound image would be appreciated.

Line 160 : abbreviation at first appearance for BMI

Lines 176-177 which normative reference tables were used?

Line 249 : what do authors mean by enter method?

Table 2 round up values to 2 decimals. Same for table 3 and table 4.

Table 4 : what does constant in the last line of the table refer to? This table is not clear. Explanation of the ACA R2 needed (first line) is lacking.

Reviewer #2: Title:

Composite carotid intima-media thickness as a risk predictor of coronary heart disease in a selected population in Sri Lanka.

This is a prospective one-center study comparing models of use of carotid CIMT for the prediction of coronary heart disease. Separate CIMT measurements (CCA, ICA, or carotid bulb), as well as a composite CIMT (average value of all six segments of the left and right sides) are compared. 694 participants were enrolled in the study. There were variations in segment-specific values. ROC curve analyses show a better AUC for composite CIMT than for segment-specific methods.

This study is interesting, globally well-organized. It addresses an important issue: validation of CIMT values in a specific population, under-represented in the literature (Sri Lanka). The manuscript is well written.

Here are some more specific comments.

Introduction:

“The considerable impact of morbidity and mortality due to CHD and stroke is seen in low- and middle-income countries compared to the developed world [1].” Is this a superior impact ? Please rephrase.

“Up to date, the majority of research has been conducted on Western populations in the United

States and European countries. There are considerably few studies on CIMT among Asians”: Important issue

Methodology:

Definition of cases and controls is clear

“Core lab with anonymous reading” : this means blind reading ? Please describe blind to what parameters: to the adjudication of cases and controls, to medical history, symptoms ?

In the abstract, the composite score is clearly defined as: “A composite-CIMT score defined as the average value of all six segments of the left and right sides was derived. “ I do not find this clear definition in the main text.

Results:

p13 line 211 “The lowest average of CIMT was in the ICA of both groups.” Please give the value, as in the prior sentence.

The composite score is labelled as composite score, ACA or composite-CIMT score. Please use a consistent labelling.

Discussion:

“Studies conducted in Poland (n=277, cut-off CIMT value - 0.933mm; n=412, cutoff 292 CIMT value - 0.76mm) [20] ». Why is there 2 cut-off values, but only one reference ?

**********

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Reviewer #1: No

Reviewer #2: No

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30 Jun 2022

Guy Cloutier, Ph.D.

Academic Editor

PLOS ONE

30th June 2022

Dear Editor,

We would like to thank the reviewers for the comments given in the Review Form of our manuscript: “Composite carotid intima-media thickness as a risk predictor of coronary heart disease in a selected population in Sri Lanka.” (PONE-D-22-12162). We hereby sincerely address the specific reviewer comments and queries. (Highlighted red colour in the revised manuscript: marked-up copy).

Thank you

Yours Sincerely

Dr.Visula Abeysuriya

Department of Public Health, Faculty of Medicine,

University of Kelaniya, P.O. Box 6, Ragama, Sri Lanka.

Responses to reviewer comments.

Responses to reviewer comments

Reviewer 1:

Comment

1. “Concern: in 11 months period authors claim that they have recruited 694 participants. This is 63 participants per month, this is 2 patients per day including week-ends (it seems impossible for me for a single center), recruitment chart flow figure is absent and is highly appreciated to clarify this issue.”

Response

Our study was conducted in the largest private hospital(Tertiary care centre) of Sri Lanka. It has a bed capacity of nearly 475. The total number of admissions (Including cardiac) per year is about 25,000. It has an OPD coverage of nearly 450,000 patients (all categories) per year. Our hospital has two angiogram laboratories which normally perform around 250 to 300 coronary angiograms and 70 odd PCIs per month. It has capacity of perform nearly 50 to 60 CABG surgeries per month. Our hospital also has a medical screening centre which screens nearly 750 to 800 patients per month. During our study we allocated a consultant radiologist for neck carotid imaging and CIMT measurement and trained two medical officers and four trained assistants for data collection. The morning session started at 8am and finished at 12noon. The afternoon session was from 1.30pm to 5.30pm. Data were collected during both sessions (included administration of the questionnaire, taking anthropometric measurements, drawing blood for biochemical studies and CIMT measurements) from about 4 participants. It took nearly one and half hours to complete data collection on each participant.

Flow chart of participant recruitment is included in the methodology section.

Comment

2. “A study published in February 2022 by Verma et al. https://www.sciencedirect.com/science/article/abs/pii/S0214916821001649 included south asian patients in India. How is this study different?”

Response

In the Indian population, the mean CIMT was shown to be an independently associated with coronary artery disease (CAD) along with diabetes, waist-hip ratio, and smoking. However, CIMT was not related to the severity and complexity of the CAD as assessed by the Gensini score and Syntax score. We have demonstrated segment specific CIMT variation and that best potential cut-off values to discriminate CHD and non-CHD groups in a Sri Lankan population are obtained using the composite CIMT score. (Line numbers 341 to 346)

Comment

3. “US measurements: should specify the technique, is it manual? If yes how many measurements per segment were done to increase reliability and what is the coefficient of variation. Is it semi automatic or automatic? if yes, what is the quality index used and the coefficient of variation for the measurements. How many operators? authors mention just one : what about inter observer variability reproducibility study? Did the authors do intra-observer reproducibility studies even if it were for a small proportion of the studied population?”

Response

CIMT was measured automatically. The Structural Similarity (SSIM) index was used as a quality index to compare the image quality obtained by the consultant radiologist with the sample image provided by the machine. The SSIM values range between 0 to 1, 1 referring to a perfect match between the radiologist’s image and the manufacturer’s image. A sample of 51 from the CHD group and a sample of 50 from the non-CHD group were randomly selected for quality index assessment. SSIM values were obtained for all three segments of the carotid arteries (CCA, CB and ICA) on both sides. In the non-CHD group the SSIM coefficient of variation ranged from 1.2% to 1.7%; in the CHD group, the SSIM coefficient of variation ranged from 1.4% to 1.8 %.( Line numbers 191 to 199)

Only one consultant radiologist had performed all the carotid imaging and CIMT measurements of the participants. Therefore, we have not assessed inter-observer reproducibility in this study.Intra-observer reliability was not assessed but the comparison with the image produced by the machine serves as a check on the radiologists assessment.

Comment

4. “Age, height, weight, BMI, waist and hip circumferences and waist-hip ratio are not mentioned in methods section nor is there mention of how they were measured, which medical device and the nearest decimal to which the measurements were performed? Formula of BMI is lacking, although known, it should be mentioned. From the description of the methods section one cannot replicate the study which is the purpose of this section of the manuscript.”

Response

Age was calculated in years.

Height was measured using a stadiometer. The participants were requested to remove their shoes, any headgear before taking the measurement. The participants stood with their back to the wall and looked directly forward (straight ahead without tilting their head upwards) keeping the eyes at the same level as the ears; the backs of their feet, calves, buttocks, upper back and the back of their head were all be in contact with the wall directly underneath the drop-down measuring device. The drop-down measuring device was brought down until it rested gently on the top of the participants head. Height was measured once to the nearest 0.5cm [10].

Bodyweight was measured using an electronic digital weighing scale that was calibrated before each session using known weights placed on a firm flat surface. Each participant was asked to remove any ‘heavy’ items from their pockets (key’s, wallets, etc.) and remove any heavy clothing or apparel items (jackets, shoes, etc.). The participant was asked to step on the scale looking straight ahead until requested to step off. Body weight was measured once to the nearest 100g. [10]

Body Mass Index (BMI) was calculated as the body weight (kg) divided by the squared height in metres (m2). [10]

Waist circumference was measured at the midpoint between the lower margin of the last palpable rib and the top of the iliac crest (hip bone) using a stretch‐resistant tape that provided a constant 100 g tension. The tape was placed horizontally across the back and front of the participant parallel to the floor and the measurement taken at the end of a normal expiration and with the arms relaxed at the sides. The waist and hip circumferences were measured once to the nearest 0.1 cm. [10]

Hip circumference was measured once around the buttocks' widest portion, with the tape parallel to the floor to the nearest 0.1 cm. [10]

The waist-hip-ratio was calculated by dividing waist circumference measurement by the hip circumference measurement. [10] (Line numbers 129 to 154)

Comment

5. “Pearson's correlation coefficients could be done to evaluate correlations between CIMT and CHD. I understand that the objective is to compare segmental IMT versus the composite IMT but such analysis would be of added value.”

Response

We have not calculated Pearson's correlation coefficient as CHD status was categorical. Hence we computedthe means for the CHD and non-CHD groups.

Comment

6. “Results section lacks mention of the regression analysis which are seen just in the tables. Need to re write this section clearly.”

Response

Section of regression analysis has been rewritten in the result section of the text.

“Age, having diabetes, systolic blood pressure, diastolic blood pressure, waist-hip ratio >0.9, Low Density Lipoprotein (LDL) level and Total Cholesterol (TC) were significant predictors of the composite score. An increase in High Density Lipoprotein (HDL) by one unit decreased the composite score by 0.004mm”. (Line numbers 295 to 298)

Comment

7. “Line 131, Mannheim recommendations mention linear probe, authors mention an annular probe, explanation? A figure showing an example of IMT measured on an ultrasound image would be appreciated.”

Response

This was an error; it has now been corrected. A Linear probe was used for the CIMT measurements. (Line number 165)

A figure (Figure 2)giving the schematic representation of the measurement of CIMT has been included. (Line number 199 to 201)

.

Comment

8. “Line 160: abbreviation at first appearance for BMI.”

Response

This was corrected (Line number 144).

Comment:

9. “Lines 176-177 which normative reference tables were used?”

Response

No nominative reference table was used. We have given actual values.

Comment

10. “Line 249: what do authors mean by enter method?”

Response

“Enter method “stands for regression with all variables in the model. It’s used in SPSS. We removed the word to prevent confusion. (Line number 300)

Comment

11. “Table 2 round up values to 2 decimals. Same for table 3 and table 4.”

Response:

Values of table 2 and 3 have been rounded up to two decimals.However, we did not round up values of table 4 as the differences in the values are seen only with more decimal places.

Comment

12. “Table 4: what does constant in the last line of the table refer to? This table is not clear. Explanation of the ACA R2 needed (first line) is lacking.”

Response:

The constant has been modified as the intercept. (Line number 301)

R2 was typograhical error. It should read as R2 which indicates the amount of variability in CIMT that is explained by the regression model.

Reviewer 2:

Comment

1. Introduction: “The considerable impact of morbidity and mortality due to CHD and stroke is seen in low- and middle-income countries compared to the developed world [1].” Is this a superior impact? Please rephrase.”

Response

The sentence has been rephrased. (Line numbers 68 to 70)

“The considerably higher impact of morbidity and mortality due to CHD and stroke is seen in low- and middle-income countries compared to the developed world.”

Comment

2. Methodology: “Core lab with anonymous reading”: this means blind reading? Please describe blind to what parameters: to the adjudication of cases and controls, to medical history, symptoms?”

Response

It was a mistake that we had written “Core lab with anonymous reading”. It was not done. The imagers were only stored in the laboratory.

Comment

3. Methodology: “In the abstract, the composite score is clearly defined as: “A composite-CIMT score defined as the average value of all six segments of the left and right sides was derived. “ I do not find this clear definition in the main text.”

Response

Definition of composite score was added to the methodology section. (Line numbers 185 to 187)

“The composite CIMT score (mean ACA IMT) was defined as the average of all intima-media thickness measurements (IMT) in the three right and left segments of the carotid artery (CCA, CB, and ICA);[Ʃ (left / right CCA+ left / right CB+ left/right ICA)/6].”

Comment

4. Results: “p13 line 211 “The lowest average of CIMT was in the ICA of both groups.” Please give the value, as in the prior sentence.”

Response

The values were added to the text.(Line numbers 258 to 259)

“The lowest average of CIMT was in the ICA of both groups (CHD group: 0.85±0.07mm and Non CHD group: 0.70±0.11mm).”

Comment

5. Results: “The composite score is labelled as composite score, ACA or composite-CIMT score. Please use a consistent labelling.”

Response

The composite score is labelled as “composite CIMT score”. Correction has been done in the text.

Comment

6. Discussion: “Studies conducted in Poland (n=277, cut-off CIMT value - 0.933mm; n=412, cut-off 292 CIMT value - 0.76mm) [20] ». Why is there 2 cut-off values, but only one reference?”

Response

There were two studies conducted in Poland. We have cited both studies.

Reference added to text. (Line numbers 349 to 350)

“Studies conducted in Poland (2 studies) (n=277, cut-off CIMT value - 0.933mm; n=412, cut-off CIMT value - 0.76mm) [21, 22]”.

Submitted filename: Response to Reviewers .docx

Click here for additional data file.

12 Jul 2022

Composite carotid intima-media thickness as a risk predictor of coronary heart disease in a selected population in Sri Lanka.

PONE-D-22-12162R1

Dear Dr. Abeysuriya,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Guy Cloutier, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Thank you for your responses. After reviewing your responses from all comments of both Reviewers and according to the positive decision of one of the Reviewers, I am happy to inform you on the acceptance of your paper.

Academic Editor

Guy Cloutier

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: Composite carotid intima-media thickness as a risk predictor of coronary heart disease

in a selected population in Sri Lanka.

This is a prospective one-center study comparing models of use of carotid CIMT for the prediction of coronary heart disease. Separate CIMT measurements (CCA, ICA, or carotid bulb), as well as a composite CIMT (average value of all six segments of the left and right sides) are compared. 694 participants were enrolled in the study. There were variations in segment-specific values. ROC curve analyses show a better AUC for composite CIMT than for segment-specific methods, for the association with CAD.

This study is interesting, globally well-organized. It addresses an important problem a validation CIMT values in a specific population, under-represented in the literature (Sri Lanka). The manuscript is well written.

All comments have been addressed.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

**********

4 Aug 2022

PONE-D-22-12162R1

Composite carotid intima-media thickness as a risk predictor of coronary heart disease in a selected population in Sri Lanka.

Dear Dr. Abeysuriya:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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