ECG Criteria for Left Ventricular Hypertrophy in Hypertensive Black Africans: Insights from the CoArtHA Trial

ECG Criteria for Left Ventricular Hypertrophy in Hypertensive Black Africans: Insights from the CoArtHA Trial | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search ECG Criteria for Left Ventricular Hypertrophy in Hypertensive Black Africans: Insights from the CoArtHA Trial View ORCID Profile Annina Vischer , Valeriya Nemtsova , Blaise Lukau , Martin Rohacek , Jonathan Macko , Johanna Oehri , Herry Mapesi , Fiona Vanobberghen , Andrew Katende , Ravi Gupta , Herieth Ismael Wilson , Alain Amstutz , Josephine Muhairwe , Elizabeth Senkoro , Theonestina Byakuzana , Geofrey Mbunda , Jamali Siru , Winfrid Gingo , Niklaus Daniel Labhardt , Maja Weisser , View ORCID Profile Thilo Burkard doi: https://doi.org/10.1101/2025.07.31.25332550 Annina Vischer 1 Medical Outpatient Department and Hypertension Centre, ESH Hypertension Centre of Excellence, University Hospital Basel , Basel, Switzerland 5 University of Basel , Basel, Switzerland MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Annina Vischer Valeriya Nemtsova 1 Medical Outpatient Department and Hypertension Centre, ESH Hypertension Centre of Excellence, University Hospital Basel , Basel, Switzerland MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Blaise Lukau 2 SolidarMed, Partnerships for Health , Maseru, Lesotho MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Martin Rohacek 3 Ifakara Health Institute, Ifakara branch , Ifakara, United Republic of Tanzania 4 Swiss Tropical and Public Health Institute , Allschwil, Switzerland 5 University of Basel , Basel, Switzerland 6 St. Francis Regional Referral Hospital , Ifakara, United Republic of Tanzania MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jonathan Macko 1 Medical Outpatient Department and Hypertension Centre, ESH Hypertension Centre of Excellence, University Hospital Basel , Basel, Switzerland BSc Find this author on Google Scholar Find this author on PubMed Search for this author on this site Johanna Oehri 1 Medical Outpatient Department and Hypertension Centre, ESH Hypertension Centre of Excellence, University Hospital Basel , Basel, Switzerland 4 Swiss Tropical and Public Health Institute , Allschwil, Switzerland 5 University of Basel , Basel, Switzerland MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Herry Mapesi 3 Ifakara Health Institute, Ifakara branch , Ifakara, United Republic of Tanzania 4 Swiss Tropical and Public Health Institute , Allschwil, Switzerland 5 University of Basel , Basel, Switzerland PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Fiona Vanobberghen 4 Swiss Tropical and Public Health Institute , Allschwil, Switzerland 5 University of Basel , Basel, Switzerland PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Andrew Katende 3 Ifakara Health Institute, Ifakara branch , Ifakara, United Republic of Tanzania 6 St. Francis Regional Referral Hospital , Ifakara, United Republic of Tanzania MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ravi Gupta 7 SolidarMed, Partnerships for Health , Maseru, Lesotho MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Herieth Ismael Wilson 3 Ifakara Health Institute, Ifakara branch , Ifakara, United Republic of Tanzania MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Alain Amstutz 8 Division of Clinical Epidemiology, Department of Clinical Research; University Hospital Basel , Basel, Switzerland 9 Oslo Centre for Biostatistics and Epidemiology, Oslo University Hospital , Oslo, Norway 10 Bristol Medical School, University of Bristol , Bristol, United Kingdom PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Josephine Muhairwe 7 SolidarMed, Partnerships for Health , Maseru, Lesotho 11 Agency for Development , Washington, DC, US MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Elizabeth Senkoro 3 Ifakara Health Institute, Ifakara branch , Ifakara, United Republic of Tanzania MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Theonestina Byakuzana 3 Ifakara Health Institute, Ifakara branch , Ifakara, United Republic of Tanzania Bsc Find this author on Google Scholar Find this author on PubMed Search for this author on this site Geofrey Mbunda 3 Ifakara Health Institute, Ifakara branch , Ifakara, United Republic of Tanzania Dip Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jamali Siru 3 Ifakara Health Institute, Ifakara branch , Ifakara, United Republic of Tanzania Dip Find this author on Google Scholar Find this author on PubMed Search for this author on this site Winfrid Gingo 6 St. Francis Regional Referral Hospital , Ifakara, United Republic of Tanzania MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Niklaus Daniel Labhardt 4 Swiss Tropical and Public Health Institute , Allschwil, Switzerland 5 University of Basel , Basel, Switzerland 7 SolidarMed, Partnerships for Health , Maseru, Lesotho 8 Division of Clinical Epidemiology, Department of Clinical Research; University Hospital Basel , Basel, Switzerland 12 Division of Infectious Diseases, University Hospital Basel , Basel, Switzerland MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Maja Weisser 3 Ifakara Health Institute, Ifakara branch , Ifakara, United Republic of Tanzania 4 Swiss Tropical and Public Health Institute , Allschwil, Switzerland 5 University of Basel , Basel, Switzerland 12 Division of Infectious Diseases, University Hospital Basel , Basel, Switzerland MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Thilo Burkard 1 Medical Outpatient Department and Hypertension Centre, ESH Hypertension Centre of Excellence, University Hospital Basel , Basel, Switzerland 5 University of Basel , Basel, Switzerland 13 , Department of Cardiology, University Hospital Basel , Basel, Switzerland MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Thilo Burkard For correspondence: Thilo.Burkard{at}usb.ch Abstract Full Text Info/History Metrics Data/Code Preview PDF Abstract Background Electrocardiographic (ECG) criteria for detecting left ventricular hypertrophy (LVH) were derived largely from non-African populations. Whether these indices accurately identify LVH in African adults with untreated hypertension remains uncertain. Objective To evaluate the diagnostic accuracy of established ECG-LVH criteria compared with echocardiographic left ventricular mass index (LVMI) in Black African adults with untreated, uncomplicated hypertension enrolled in the CoArtHA trial. Methods In this subanalysis, we included participants from rural Tanzania and Lesotho who underwent baseline 12-lead ECG and focused transthoracic echocardiography (fTTE). LVH was defined as LVMI > 95 g/m² in women and > 115 g/m² in men. Diagnostic performance of multiple ECG-LVH criteria was assessed using Spearman correlation, sensitivity, specificity, and area under the receiver-operating characteristic curve (AUC). Results Echocardiographic LVH was present in 56 participants (5%). Among continuous ECG indices, the Cornell voltage product adjusted by + 0.8 mV in women showed the highest correlation with LVMI (rho = 0.373, p < 0.001) and achieved the best overall discrimination (AUC = 0.719). Standard cut-offs provided a specificity of 79.5% and sensitivity of 64.3%, whereas an adapted cut-off of 277.8 mV*ms increased specificity above 90%. Other indices, including MESA- and Sokolow-Lyon-based criteria, showed limited accuracy. Conclusions In this large cohort of hypertensive Black African adults, the Cornell voltage product (with + 0.8 mV adjustment for women) demonstrated the best diagnostic performance for detecting LVH compared with echocardiography. These results highlight the need to verify the diagnostic validity of established ECG criteria in African populations and support their pragmatic use to guide cardiovascular risk stratification in low-resource settings. Trial registration Clinicaltrials.gov NCT04129840 . Registered on 17 October 2019 ( https://www.clinicaltrials.gov/ ). INTRODUCTION Left ventricular hypertrophy (LVH) is a recognized complication of hypertension and associated with a worse prognosis, independent of ethnicity( 1 ). While cardiac magnetic resonance (CMR) is considered the reference method for assessing LV mass, its availability in low-resource settings is limited. Transthoracic echocardiography (TTE) remains the preferred modality in clinical practice, yet even this is often inaccessible in rural regions of sub-Saharan Africa ( 2 , 3 ). In contrast, electrocardiography (ECG) is inexpensive and widely available, but its diagnostic accuracy for LVH varies considerably ( 4 – 6 ). Most ECG-LVH criteria were developed in predominantly Caucasian populations, with limited validation among African adults ( 7 , 8 ). Only few studies have evaluated the suitability of the ECG criteria for LVH assessment in adult black African populations ( 5 , 9 ). In the MESA (the Multi-Ethnic Study of Atherosclerosis) study, the MESA ECG-LVH index was the best at diagnosing LVH in the subgroup of African Americans when compared to CMR ( 10 ). The CoArtHA trial (Identifying the most effective Treatment Strategies to Control Arterial Hypertension in sub-Saharan Africa) enrolled treatment-naïve adults with uncomplicated hypertension in Tanzania and Lesotho ( 11 , 12 ). Using this unique dataset, we assessed the diagnostic performance of numerous established ECG-LVH criteria against focused echocardiographic (fTTE) LV mass index (LVMI) and explored optimal cut-off values for this population. METHODS Study design and population The CoArtHA trial was an investigator-initiated, open-label, randomized controlled trial conducted in rural Tanzania and Lesotho to compare three antihypertensive treatment strategies. Detailed methods and eligibility criteria have been published previously ( 11 , 12 ). In brief, Black African adults (≥18 years) with untreated, uncomplicated hypertension were enrolled. Key exclusion criteria were symptomatic hypertension, recent cardiovascular events, severe comorbidities, pregnancy, or inability to attend follow-up. This subanalysis included all participants with interpretable baseline ECG and fTTE. All participants gave written informed consent for the collection, storage and use of clinical data and sample specimens for research purposes within the CoArtHA trial. The study protocol of the CoArtHA trial was approved by the Institutional review board of the Ifakara Health Institute, the National Health Research Ethics Committee in Tanzania, the Tanzania Medicines and Medical Devices Authority, the National Health Research and Ethics Committee and Ministry of Health of Lesotho, as well as the Ethics committee of Northwest and Central Switzerland ( 11 , 12 ). This was an exploratory analysis of the CoArtHA trial using fTTE and ECG data from baseline investigations. Patients for whom ECG or fTTE data were not available or of insufficient quality, were excluded ( Figure 2 ). Download figure Open in new tab Figure 1: Graphical abstract Download figure Open in new tab Figure 2: Study flow chart and selection of participants. Legend: fTTE - focused echocardiography, ECG-electrocardiography Study procedures Blood pressure measurement Blood pressure was measured according to ESC/ESH 2018 guidelines using an automated device (Omron M6 Comfort, HEM-7321-E). Hypertension was defined as systolic ≥ 140 mmHg and/or diastolic ≥ 90 mmHg. The average of the last two of three measurements was used for analysis.( 13 , 14 ). Electrocardiography A 12-lead ECG was recorded at baseline using a Schiller AT-1 electrocardiogram machine at 10 mm/mV calibration and at a speed of 25 mm/s.. All ECGs were printed out including an automated matrix analysis of times and amplitudes and were verified by trained investigators under cardiologist supervision. We compared several established ECG-LVH indices with definitions and thresholds summarized in Table 1 ). Parameters were analyzed as both dichotomous and continuous variables to evaluate correlation and discriminative ability versus echocardiographic LVH as appropriate. View this table: View inline View popup Table 1: Characteristics of electrocardiographic indexes used in this study Focused transthoracic echocardiography Focused echocardiography (fTTE) was performed at baseline by trained study personnel using standardized acquisition protocols and centrally reviewed under the supervision of board certified cardiologists supported by an automated FDA-approved deep-learning workflow (Us2.ai, Singapore) ( 26 , 27 ). LVM, LVM indexed by BSA and relative wall thickness (RWT) were calculated according to guideline recommendations (LVM defined as 0.8x 1.04x [(IVS + LVID + PWT)^3-LVID^3] + 0.6 grams, where IVS is interventricular septum diastole (unit mm), LVID is left ventricular end-diastolic diameter (units mm), and PWT is posterior wall diastole (units mm)( 28 ). LVH was defined as LVMI >95g/m 2 in women, >115g/m 2 in men ( 2 ). Statistics For testing the normality of distribution, a Shapiro-Wilk test was used. Normal distribution was defined as a p-value ≥0.05. Continuous data were reported as median (interquartile range), categorical data as n (% of total). Differences between groups were calculated using a Wilcoxon signed rank test for continuous data and using a chi-square test for categorical data. Testing of ECG parameters Correlations were calculated with the spearman method using the ggpubr-package ( 29 ). Correlations were ranked from (0.01-0.19) indicating no or negligible relationship, to (≥ 0.70) indicating a very strong relationship ( Table S1 )( 30 ). For accuracy analyses, specificity as (true negative) / (true negative + false positive), sensitivity as (true positive) / (true positive + false negative) was calculated. The negative predictive value (NPV) was calculated as (true negative) / (true negative + false negative). The positive predictive value (PPV) was calculated as (true positive) / (true positive + false positive). The accuracy was calculated as (true positive + true negative) / N. Receiver operating characteristics (ROC) curves were plotted and area under the curves (AUCs) were calculated using the pROC package( 31 ),( 32 ). Discriminative property was graded: AUC of 0.5 suggested no discrimination, 0.7 to 0.8 was considered acceptable, 0.8 to 0.9 was considered excellent, and more than 0.9 was considered outstanding( 32 ). All calculations were completed by using R ( 33 ). Selection of the best ECG-parameters to improve cut-off values The four best parameters were then selected according to their AUC for further evaluation regarding improved cut-off values for this cohort. Furthermore, the general MESA ECG-LVH index, as the best ECG-LVH parameter for African Americans in the Mesa Study was used( 10 ). For each of the parameters test characteristics were calculated for the standard threshold, 90% and 95% accuracy, 90% and 95% sensitivity, 90% and 95% specificity and the highest Youden index (J), being defined as the point in the AUC curve with the farthest distance to the diagonal line; calculated as highest value (J) =sensitivity+specificity−1. Discriminative performance for the new cutoffs of each of the parameters were calculated using the pROC package ( 31 ). RESULTS Characteristics of the Patient Cohort Of 1 268 CoArtHA participants, 1 125 (49% from Tanzania, 51% from Lesotho) had evaluable ECG and echocardiography data ( Figure 2 ). Median age was 53.4 (IQR:44.6-64.4) years, 28% were male, and 38% were HIV positive. LVH by echocardiography was identified in 56 participants (5%). Participants with LVH were older, more often female, more often with a history of hypertension and had higher systolic and diastolic blood pressure, and body mass index compared with those without LVH ( Table 2 ). View this table: View inline View popup Table 2: Baseline demographic and clinical characteristics of the study sample, overall and regarding subgroups with echocardiographic signs for LVH Prevalence of LVH ECG markers The overall prevalence of positive ECG markers according to the presence of echocardiographic signs for LVH is shown in Table 3 . The highest prevalence of positive ECG LVH markers was observed with the general MESA ECG-LVH criterion (633/1125 [56.3%]) participants), the ethnicity- and gender-specific MESA ECG-LVH criterion (566/1125 [50.3%]) participants) and Sokolow-Lyon voltage index (390/1125 [34.7%]) participants. There were no significant differences in the prevalence of positive values of these criteria, as well as for the Framingham-adjusted Cornell voltage index, and Minnesota Code 3.3, between the group of patients fTTE - LVH and the patients without fTTE-LVH (p>0.05). View this table: View inline View popup Table 3. Prevalence of positive ECG markers in the entire cohort, as well as separated for the group with echocardiographic signs of LVH and those without Characteristics of ECG parameters Median values of the continuous ECG criteria in the group of participants with fTTE-LVH were significantly higher than in the group without fTTE-LVH, except for the General and male specific MESA ECG-LVH criterion and the male and female specific Framingham-adjusted Cornell voltage ( Table S2 ). Correlations between LVMI and ECG-LVH criteria Continuous LVH ECG criteria were compared with continuous LVMI to determine the degree of correlation between these methods and to evaluate the extent to which ECG parameters can serve as markers for echocardiographic changes ( Figure S1 ). Significant, weak to moderate, positive correlations were found between continuous LVMI and all ECG indices, with the highest correlations observed for unadjusted Cornell voltage product, Cornell voltage criteria, 0.6mV adjusted Cornell voltage product and R amplitude aVL (rho = 0.373, rho = 0.327, rho = 0.324 and rho = 0.304, respectively; p < 0.001 for all). The MESA ECG-LVH criteria showed a significant positive but very weak correlation with LVMI (rho = 0.179, p < 0.001). Diagnostic performance of ECG-LVH criteria Sensitivity, specificity, positive (PPV) and negative (NPV) predictive values and the AUC for LVH were calculated for each ECG criterion with recommended standard cut-off values in comparison to echocardiographic signs of LVH ( Table 4 ). View this table: View inline View popup Table 4: Performance of standard ECG LVH criteria in overall study population Using standard cut-offs, the Cornell voltage product (adjusted + 0.8 mV for women) achieved the highest AUC (0.719) with sensitivity 64% and specificity 80%, followed by the 0.6 mV-adjusted (AUC 0.690) and unadjusted (AUC 0.651) versions. Strain pattern and unadjusted Cornell voltage product yielded the highest specificity (> 90%) but lower sensitivity. MESA-derived criteria showed poor discrimination (AUC 0.517). Analysis of continuous ECG parameters to identify most promising ECG parameter as an indicator for LVH Detection The ROC plot in Figure 3 provides a comparative analysis of the diagnostic performance of the studied ECG criteria as continuous values with regard to the presence of LVH to see if an improvement of the cut-off values would be possible. Among the indexes investigated, compared to the ‘neutral’ AUC value of 0.5, the Cornell voltage product adjusted with 0.8mV and 0.6mV (women), the unadjusted Cornell voltage product, and the R wave amplitude in aVL had the highest AUC values (0.765, 0.761, 0.738, and 0.708, respectively) with an acceptable discriminative property ( 32 ). The MESA ECG-LVH index showed the lowest AUC of the tested parameters (0.577). Download figure Open in new tab Figure 3. ROC plot with area under the curve (AUC) for continuous electrocardiography (ECG) parameters. Legend: ECG-electrocardiography, LVH-left ventricular hypertrophy, MESA-the Multi-Ethnic Study of Atherosclerosis Alternative cut off values for selected ECG parameters Based on the previous results, we selected the three best criteria for further evaluation: Cornell voltage criteria, Cornell voltage product, and R amplitude aVL, as well as the MESA ECG-LVH index. We analysed both standard and optimized thresholds for these ECG LVH criteria to identify the most clinically applicable thresholds ( Table S3 , Figure S2 ). Considering the limited number of men diagnosed with fTTE-LVH in our cohort, we evaluated novel thresholds for the Cornell voltage criteria without sex-specific adjustments. Figure S2 illustrates the discriminative performance of each parameter using both traditional cut-off values and thresholds optimized for maximal Youden’s index. It also reports the AUCs corresponding to cut-offs that achieve sensitivity, specificity, or accuracy greater than 90% and 95%, respectively ( Table S3 ). Highest AUC (0.719) was calculated for the traditional cut-off of the Cornell voltage product adjusted with 0.8 mV (women). Figure 4 summarizes the best test and cut-off values for highest Youden index/AUC, sensitivity >90% and specificity >90% for the Cornell voltage product adjusted with 0.8 mV (women), despite AUC for sensitivity >90% was numerically higher for the unadjusted Cornell voltage product (0.599 vs. 0.620). Download figure Open in new tab Figure 4. Discriminative performance of the Cornell voltage product adjusted with 0.8 mV (women) at the highest Youden index/AUC derived cut-offs and sensitivity >90% and specificity >90% cut-offs DISCUSSION This sub-analysis of the CoArtHA trial provides several important insights into the diagnostic utility of ECG criteria for left ventricular hypertrophy (LVH) among hypertensive Black African adults. First, LVH ECG indices showed a weak to moderate correlation with echocardiographic LV mass index (LVMI), with the Cornell voltage product and its female-adjusted version performing best. Second, appliying traditional cut-off values yielded highest discriminative properties for the Cornell voltage product with 0.8 mV adjustment for women at a cut-off of 243.6 mVms, followed by the cuf-off of 244 mVms. Third, the limited sensitivity of ECG in diagnosing LVH highlights the need for tests with higher sensitivity and acceptable specificity. Rodrigues et al e.g. proposed lowering sex-specific thresholds for the Cornell voltage criteria to improve sensitivity ( 34 ). The CoArtHa study also aimed to enhance ECG criteria for LVH in African populations, supporting ethnic-specific thresholds. The Youden index is commonly used to identify optimal cut-off values, minimizing both false positives and negatives ( 35 ). Within our cohort novel cut-off values only have better discriminative properties than standard cut-offs, when high sensitivities or specifities are aimed for. Interestingly, the highest AUC for the detection of LVH was reached at the best Youden Index with the Cornell voltage product with adjustment of 0.8 mV for women at the cut-off of 243.6 mVms, showing a sensitivity of 64.3% and specificity of 79.6%. ECG criteria for LVH were originally designed to reach a specificity as high as 90% to 95%, which in our cohort was achieved only by the unadjusted Cornell voltage product and Strain pattern at standard cut-offs, with the latter having a lower sensitivity of 21% compared to 37.5% ( 36 ). An adapted best threshold for > 90% specificity could be using the Cornell voltage product adjusted with 0.8 mV for women at >277 mVms with a sensitivity of 42.9%. Regarding Cornell voltage criteria best Youden index at 2.25 mV showed higher AUC values and improved sensitivity to 53.6%, while maintaining specificity at a level of 79.4%. Further studies are needed to confirm the clinical usefulness of these thresholds for diagnosing LVH in Black African hypertensive patients. Collectively, these findings demonstrate that standard ECG criteria especially the Cornell voltage product with a 0.8 mV adjustment for women remain applicable but may require minor threshold adjustments when used in African populations with untreated hypertension. Several aspects of the present study deserve to be mentioned The weak to moderate correlations between ECG-LVH indices and echocardiographic LV mass index observed in our study are consistent with prior reports from both African and non-African cohorts.( 5 , 6 , 9 , 34 , 36 – 38 ) Our findings of variable but overall low-to-moderate sensitivity (0.15–0.59) combined with higher specificity (0.44–0.97) are consistent with previous studies in African adults with hypertension, which have repeatedly reported that standard ECG criteria for LVH show limited sensitivity but good specificity ( 5 , 9 , 36 , 39 , 40 ). In a study conducted in Nigeria in 90 subjects evaluating four ECG criteria, Cornell criterion and Sokolow-Lyon criterion showed a lower accuracy than our results, but the defined cut off for LVH in TTE was >125/m 2 for both sexes which is higher than the recommended gender-specific cutoff values we used ( 9 ). In a subgroup of 120 African American participants of the LIFE study, Sokolow-Lyon overestimated and Cornell voltage criteria underestimated the presence of LVH relative to white participants compared to TTE, in terms of sensitivity and specificity – but not in terms of overall test performance in ROC curve analysis ( 41 ). In line with our results, Cornell voltage product had the highest numerical AUC value of 0.665 in the LIFE study ( 41 ). Interestingly and in contrast to a study by Jain et al, comparing ECG parameter to cardiac MRI in several ethnicities within the MESA study and deriving the MESA ECG-LVH criteria, the general MESA ECG-LVH and the ethnicity- and gender-specific MESA ECG-LVH criterion had a low specificity and sensitivity in our cohort.( 10 ) Within the MESA cohort and when applying ethnicity and gender specific cut-offs, specificity and sensitivity for the participants of African American descent was 90% and 37-39%, respectively with an ROC AUC of 0.64.In addition to the geographical differences of the trials namely United States versus sub saharan Africa, there were also differences between the cohorts with a 50% proportion of males and a higher prevalence of MRI-LVH of 11% in the MESA study. Additionally participants were older and had an higher BMI. Another reason for the discrepancy may be the differences between MRI and TTE, but again in the MESA study, the agreement for LVH between the imaging modalities ranged from 77-98% with a kappa coefficient from 0.1-0.76( 42 ). To our knowledge, the MESA criteria had not been externally validated. Generally, in the CoArtHa study three particular ECG criteria (Cornell voltage сriteria, Cornell voltage product (especially with adjustment), and R amplitude aVL) had better discriminative properties and were more sensitive than other criteria. This aligns with other studies in different ethnic populations that demonstrated that the Cornell-based criteria had superior diagnostic performance compared to Sokolov-Lyon, and other criteria ( 34 , 40 , 43 , 44 ). Regarding the prognostic value, presence of LVH is an important marker for mortality, especially in African American patients, making screening of this condition even more relevant( 41 , 45 , 46 ). This is true not only for LVH diagnosed by TTE or MRI but also for LVH detected by ECG criteria in different settings, even though the prevalence of LVH by ECG is higher than by imaging. For example, within the LIFE study, regression of LVH defined by Cornell voltage criteria, Sokolov-Lyon voltage criteria or ECG Strain pattern was associated with an improved cardiovascular outcome independent of BP reduction ( 47 ). Additionally, presence of these markers at baseline or development of new Strain pattern over time were predictors of cardiovascular events ( 47 ). Moreover, in a meta-analysis conducted by Zhigang You et al, Cornell voltage criteria had a stronger predictive value for cardiovascular risk than the Sokolov-Lyon index and Cornell voltage product in general populations, without studies coming from the African continent. ( 48 ). Of note, there is evidence that the information from TTE and ECG may complement each other, with, however, a higher impact of the TTE diagnosis. A study by Seko and colleagues evaluated the prognostic relevance of presence and absence of LVH in TTE and ECG by using Cornell product in hospitalized asian participants. When considering the resulting four possible patterns of TTE/ECG, namely +/+, +/-, -/+ and -/-, the hazard ratio for major adverse cardiovascular events over 3 years was 1.63 (1.16-2.28), 1.68 (1.23-2.30) and 1.09 (0.85-1.41) compared to patients no evidence of LVH( 49 ). Therefore, ECG remains a useful tool for risk stratification in hypertension not only in countries where poor technical provision and costs may limit the use of echocardiography. Therefore, it may be clinically feasible to use ECG with tailored cutoff values to identify a group of patients at lower risk for LVH and deprioritise them for further imaging. Our study has several limitations. Firstly, in our cohort of treatment-naïve adults with hypertension, the prevalence of fTTE LVH was 5%, resulting in 56 participants with LVH only. The low number, together with the overrepresentation of female participants within the study as well as within those with an echocardiographically confirmed LVH, makes it difficult to generalize the results, especially to men, speaking for the need of a validation in other cohorts in Africa. Secondly, the prevalence of echocardiographic LVH in hypertension varies based on LVM indexation and cut-off values. Adebiyi et al. examined different echocardiographic thresholds in 457 hypertensive native Africans, finding LVH prevalence ranged from 30.9% to 56.0%( 37 , 50 ). The highest was with LVM indexed to height²·□ (49.2 g/ht²·□ in men, 46.7 g/ht²·□ in women), and the lowest with BSA indexation (125 g/m² for both sexes)( 50 ). This aligns with studies in southwestern Nigeria and the MAVI (MAssa Ventricolare sinistra nel soggetto Iperteso) study, which used a higher LVMI cut-off (>125 g/m²) and reported LVH prevalence of 32.2% and 27.2%, respectively( 6 , 9 ). Our analysis applies the American Society of Echocardiography definition (>115 g/m² in men, >95 g/m² in women), widely used in clinical practice and linked to adverse cardiovascular outcomes( 28 ). Thirdly, the fTTE in our study were not performed by fully trained cardiologists, but by doctors and nurses after a short-time training, possibly resulting in differences when compared to board certified cardiologists or cardiac sonographer. However, analyses of echocardiographies were done in a central site with the support of an artificial intelligence algorithm and interpretation of cardiologists. This approach was used also in a population-based survey by our group and has been proven to be feasible( 27 , 51 ). Additionally there is evidence that TTE image quality has limited influence on the reliability and performance of LVM assessment, when compared to cMRI( 42 ). Finally, we could not analyse a correlation of ECG parameter with outcomes such as morbidity or mortality. In conclusion, in this population of treatment-naïve Black Africans with uncomplicated and untreated hypertension in rural Africa, the Cornell voltage product with adjustment of 0.8 mV for women had the best diagnostic properties when compared to alternative LVH ECG criteria, with a moderate association with left ventricular myocardial mass measured by focused echocardiography, indexed to body surface area and should be the preferred ECG parameter when full or point-of-care echocardiography is not available. We found, that application of standard cut-offs are in line with best Youden Index. Specificity can be increased to 90% using a cut-off value of 277 mVms. Implementing ECG and using the best performing criteria in routine clinical care may contribute to improve the diagnosis of LVH at screening stage and may allow to identify a group of patients at lower or higher risk for hypertension-mediated cardiac damage to de-or prioritize for further echocardiography. However, given the rapid advancements in imaging technology, the increasing integration of artificial intelligence (AI) and a more comprehensive and dynamic assessment of cardiac function by fTTE, it is plausible that ECG may be gradually supplanted by fTTE in the coming years. Nonetheless, continued refinement of ECG-LVH criteria and AI-based diagnostic approaches may further enhance the utility of ECG as an accessible screening tool in resource-limited settings. Data Availability The datasets used for the current study are available from the corresponding author on reasonable request. Sources of Funding This trial was funded by the Swiss National Science Foundation (grant 32003B185263/1). Additional funding for focused echocardiography analysis was granted by the Cardiovascular Research Foundation Basel Disclosures PD Annina Salome Vischer has received personal fees from Bristol Myers Squibb, Amarin, Servier, Medtronic, Vifor, NovoNordisk, AstraZeneca outside the submitted work. Dr Mapesi reported being employed by Roche outside the submitted work. Prof Rohacek reported receiving grants from Else Kröner Fresenius Foundation outside the submitted work. Prof Labhardt reported receiving travel support from Gilead Sciences and ViiV outside the submitted work. PD Burkard reported receiving grants from Swiss National Science Foundation, Cardiovascular Research Foundation Basel, AstraZeneca, Daiichi Sankyo, Medtronic, Roche Diagnostics, Novartis, Novo Nordisk, Collabree, and Preventicus and lecture and/or travel fees paid to institution from Servier, Medtronic, Sanofi, Novartis, and Daiichi Sankyo outside the submitted work. Prof Weisser reported receiving grants from the Swiss National Science Foundation for implementation and conduct of the study and travel grants for conference attendance from MSD and Gilead. Dr. Oehri reported funds from Goldschmidt-Jacobsen Stiftung outside the submitted work. No other disclosures were reported. Supplementary Material View this table: View inline View popup Download powerpoint Table S1. Interpretation Table of Spearman Rank-Order Correlation Coefficients ( 30 ) View this table: View inline View popup Table S2: Median values (IQR) for different continuous ECG parameters overall and in participants with and without echocardiographic LVH View this table: View inline View popup Table S3: Diagnostic performance of selected ECG LVH criteria at different cut-off values Download figure Open in new tab Figure S1. Scatter plots showing correlation between continuous ECG parameters and LV mass index from TTE parameters. Panel A: Cornell voltage criteria; Panel B: unadjusted Cornell voltage product; Panel C: Cornell voltage product, adjusted for women 0.6 mV; Panel D: Cornell voltage product, adjusted for women 0.8 mV; Panel E: R amplitude in lead aVL; Panel F: General MESA ECG-LVH; Panel G: Sokolow-Lyon voltage; Panel H: Sokolow-Lyon product; Panel I: Framingham-adjusted Cornell voltage Download figure Open in new tab Figure S2: Comparison of AUCs for traditional vs. Youden-index-derived cut-offs, and AUCs at sensitivity, specificity, or accuracy levels exceeding 90% and 95%. Acknowledgments The authors thank all investigators, staff, and participants of the CoArtHA study for their valuable contributions. Footnotes Revised manuscript. Revised abstract. Change of the author order (first and second) during the revision process. Both keep the contributed equally status. References 1. ↵ Havranek EP , Froshaug DB , Emserman CD , Hanratty R , Krantz MJ , Masoudi FA , et al. Left ventricular hypertrophy and cardiovascular mortality by race and ethnicity . Am J Med . 2008 ; 121 ( 10 ): 870 – 5 . OpenUrl CrossRef PubMed Web of Science 2. ↵ Mancia G , Kreutz R , Brunstrom M , Burnier M , Grassi G , Januszewicz A , et al. 2023 ESH Guidelines for the management of arterial hypertension The Task Force for the management of arterial hypertension of the European Society of Hypertension Endorsed by the International Society of Hypertension (ISH) and the European Renal Association (ERA) . J Hypertens . 2023 . 3. ↵ McEvoy JW , McCarthy CP , Bruno RM , Brouwers S , Canavan MD , Ceconi C , et al. 2024 ESC Guidelines for the management of elevated blood pressure and hypertension . Eur Heart J . 2024 ; 45 ( 38 ): 3912 – 4018 . OpenUrl CrossRef PubMed 4. ↵ Chapman JN , Mayet J , Chang CL , Foale RA , Thom SA , Poulter NR . Ethnic differences in the identification of left ventricular hypertrophy in the hypertensive patient . Am J Hypertens . 1999 ; 12 ( 5 ): 437 – 42 . OpenUrl CrossRef PubMed 5. ↵ Jingi AM , Noubiap JJ , Kamdem P , Kingue S . Determinants and improvement of electrocardiographic diagnosis of left ventricular hypertrophy in a black African population . PLoS One . 2014 ; 9 ( 5 ): e96783 . OpenUrl PubMed 6. ↵ Verdecchia P , Dovellini EV , Gorini M , Gozzelino G , Lucci D , Milletich A , et al. Comparison of electrocardiographic criteria for diagnosis of left ventricular hypertrophy in hypertension: the MAVI study . Ital Heart J . 2000 ; 1 ( 3 ): 207 – 15 . OpenUrl PubMed 7. ↵ Sokolow M , Lyon TP . The ventricular complex in left ventricular hypertrophy as obtained by unipolar precordial and limb leads . Am Heart J . 1949 ; 37 ( 2 ): 161 – 86 . OpenUrl CrossRef PubMed Web of Science 8. ↵ Romhilt DW , Estes EH , Jr . . A point-score system for the ECG diagnosis of left ventricular hypertrophy . Am Heart J . 1968 ; 75 ( 6 ): 752 – 8 . OpenUrl CrossRef PubMed Web of Science 9. ↵ Ogunlade O , Akintomide AO . Assessment of voltage criteria for left ventricular hypertrophy in adult hypertensives in south-western Nigeria . J Cardiovasc Dis Res . 2013 ; 4 ( 1 ): 44 – 6 . OpenUrl PubMed 10. ↵ Jain A , Tandri H , Dalal D , Chahal H , Soliman EZ , Prineas RJ , et al. Diagnostic and prognostic utility of electrocardiography for left ventricular hypertrophy defined by magnetic resonance imaging in relationship to ethnicity: the Multi-Ethnic Study of Atherosclerosis (MESA) . Am Heart J . 2010 ; 159 ( 4 ): 652 – 8 . OpenUrl CrossRef PubMed Web of Science 11. ↵ Mapesi H , Gupta R , Wilson HI , Lukau B , Amstutz A , Lyimo A , et al. The coArtHA trial-identifying the most effective treatment strategies to control arterial hypertension in sub-Saharan Africa: study protocol for a randomized controlled trial . Trials . 2021 ; 22 ( 1 ): 77 . OpenUrl PubMed 12. ↵ Mapesi H , Rohacek M , Vanobberghen F , Gupta R , Wilson HI , Lukau B , et al. Treatment Strategies to Control Blood Pressure in People With Hypertension in Tanzania and Lesotho: A Randomized Clinical Trial . JAMA Cardiol . 2025 . 13. ↵ Williams B , Mancia G , Spiering W , Agabiti Rosei E , Azizi M , Burnier M , et al. 2018 ESC/ESH Guidelines for the management of arterial hypertension . Eur Heart J . 2018 ; 39 ( 33 ): 3021 – 104 . OpenUrl CrossRef PubMed 14. ↵ Belghazi J , El Feghali RN , Moussalem T , Rejdych M , Asmar RG . Validation of four automatic devices for self-measurement of blood pressure according to the International Protocol of the European Society of Hypertension . Vasc Health Risk Manag . 2007 ; 3 ( 4 ): 389 – 400 . OpenUrl PubMed 15. Alchaghouri S , Wong KY , Perry RA , Ramsdale DR , Somauroo JD , Pyatt JR . QT peak prolongation is not associated with left ventricular hypertrophy in teenage professional football players . Ann Noninvasive Electrocardiol . 2007 ; 12 ( 2 ): 104 – 10 . OpenUrl PubMed 16. Alfakih K , Walters K , Jones T , Ridgway J , Hall AS , Sivananthan M . New gender-specific partition values for ECG criteria of left ventricular hypertrophy: recalibration against cardiac MRI . Hypertension . 2004 ; 44 ( 2 ): 175 – 9 . OpenUrl CrossRef 17. Molloy TJ , Okin PM , Devereux RB , Kligfield P . Electrocardiographic detection of left ventricular hypertrophy by the simple QRS voltage-duration product . J Am Coll Cardiol . 1992 ; 20 ( 5 ): 1180 – 6 . OpenUrl FREE Full Text 18. Rautaharju PM , Park LP , Chaitman BR , Rautaharju F , Zhang Z-M . The novacode criteria for classification of ECG abnormalities and their clinically significant progression and regression . Journal of Electrocardiology . 1998 ; 31 ( 3 ): 157 – 87 . OpenUrl PubMed Web of Science 19. Levy D , Labib SB , Anderson KM , Christiansen JC , Kannel WB , Castelli WP . Determinants of sensitivity and specificity of electrocardiographic criteria for left ventricular hypertrophy . Circulation . 1990 ; 81 ( 3 ): 815 – 20 . OpenUrl Abstract / FREE Full Text 20. Mancia G , Fagard R , Narkiewicz K , Redon J , Zanchetti A , Bohm M , et al. 2013 ESH/ESC guidelines for the management of arterial hypertension: the Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC) . Eur Heart J . 2013 ; 34 ( 28 ): 2159 – 219 . OpenUrl CrossRef PubMed Web of Science 21. Sparapani R , Dabbouseh NM , Gutterman D , Zhang J , Chen H , Bluemke DA , et al. Detection of Left Ventricular Hypertrophy Using Bayesian Additive Regression Trees: The MESA . J Am Heart Assoc . 2019 ; 8 ( 5 ): e009959 . OpenUrl PubMed 22. Norman JE , Jr ., Levy D , Campbell G , Bailey JJ . Improved detection of echocardiographic left ventricular hypertrophy using a new electrocardiographic algorithm . J Am Coll Cardiol . 1993 ; 21 ( 7 ): 1680 – 6 . OpenUrl FREE Full Text 23. Prineas RJ , Crow RS , Zhang Z-M . The Minnesota Code Manual of Electrocardiographic Findings 2010 . 24. Inoue YY , Soliman EZ , Yoneyama K , Ambale-Venkatesh B , Wu CO , Sparapani R , et al. Electrocardiographic Strain Pattern Is Associated With Left Ventricular Concentric Remodeling, Scar, and Mortality Over 10 Years: The Multi-Ethnic Study of Atherosclerosis . J Am Heart Assoc . 2017 ; 6 ( 9 ). 25. Okin PM , Oikarinen L , Viitasalo M , Toivonen L , Kjeldsen SE , Nieminen MS , et al. Prognostic Value of Changes in the Electrocardiographic Strain Pattern During Antihypertensive Treatment The Losartan Intervention for End-Point Reduction in Hypertension Study (LIFE) . Circulation . 2009 ; 119 ( 14 ): 1883 – 91 . OpenUrl Abstract / FREE Full Text 26. ↵ Tromp J , Bauer D , Claggett BL , Frost M , Iversen MB , Prasad N , et al. A formal validation of a deep learning-based automated workflow for the interpretation of the echocardiogram . Nat Commun . 2022 ; 13 ( 1 ): 6776 . OpenUrl PubMed 27. ↵ Firima E , Gonzalez L , Manthabiseng M , Bane M , Lukau B , Leigh B , et al. Implementing focused echocardiography and AI-supported analysis in a population-based survey in Lesotho: implications for community-based cardiovascular disease care models . Hypertens Res . 2024 ; 47 ( 3 ): 708 – 13 . OpenUrl PubMed 28. ↵ Lang RM , Badano LP , Mor-Avi V , Afilalo J , Armstrong A , Ernande L , et al. Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging . J Am Soc Echocardiogr . 2015 ; 28 ( 1 ): 1 – 39 e14. OpenUrl CrossRef PubMed 29. ↵ Kassambara A . ggpubr: ‘ggplot2’ Based Publication Ready Plots . R package version 0.6.0 ed2023 . 30. ↵ Leclezio L , Jansen A , Whittemore VH , de Vries PJ . Pilot validation of the tuberous sclerosis-associated neuropsychiatric disorders (TAND) checklist . Pediatr Neurol . 2015 ; 52 ( 1 ): 16 – 24 . OpenUrl CrossRef PubMed 31. ↵ Robin X , Turck N , Hainard A , Tiberti N , Lisacek F , Sanchez JC , et al. pROC: an open-source package for R and S+ to analyze and compare ROC curves . BMC Bioinformatics . 2011 ; 12 : 77 . 32. ↵ Mandrekar JN . Receiver operating characteristic curve in diagnostic test assessment . J Thorac Oncol . 2010 ; 5 ( 9 ): 1315 – 6 . OpenUrl CrossRef PubMed 33. ↵ Team RC . R: A Language and Environment for Statistical Computing . R Foundation for Statistical Computing. Vienna, Austria 2024 . 34. ↵ Rodrigues SL , D’Angelo L , Pereira AC , Krieger JE , Mill JG . Revision of the Sokolow-Lyon-Rappaport and cornell voltage criteria for left ventricular hypertrophy . Arq Bras Cardiol . 2008 ; 90 ( 1 ): 46 – 53 . OpenUrl PubMed 35. ↵ Hajian-Tilaki K . The choice of methods in determining the optimal cut-off value for quantitative diagnostic test evaluation . Stat Methods Med Res . 2018 ; 27 ( 8 ): 2374 – 83 . OpenUrl CrossRef PubMed 36. ↵ Jaggy C , Perret F , Bovet P , van Melle G , Zerkiebel N , Madeleine G , et al. Performance of classic electrocardiographic criteria for left ventricular hypertrophy in an African population . Hypertension . 2000 ; 36 ( 1 ): 54 – 61 . OpenUrl 37. ↵ Dada A , Adebiyi AA , Aje A , Oladapo OO , Falase AO . Standard electrocardiographic criteria for left ventricular hypertrophy in Nigerian hypertensives . Ethnic Dis . 2005 ; 15 ( 4 ): 578 – 84 . OpenUrl PubMed 38. ↵ Schillaci G , Verdecchia P , Borgioni C , Ciucci A , Guerrieri M , Zampi I , et al. Improved electrocardiographic diagnosis of left ventricular hypertrophy . Am J Cardiol . 1994 ; 74 ( 7 ): 714 – 9 . OpenUrl CrossRef PubMed Web of Science 39. ↵ Bombelli M , Vanoli J , Cuspidi C , Dell’Oro R , Facchetti R , Mancia G , et al. Comparison of electrocardiographic versus echocardiographic detection of left ventricular mass changes over time and evaluation of new onset left ventricular hypertrophy . J Clin Hypertens (Greenwich ). 2023 ; 25 ( 4 ): 343 – 9 . OpenUrl PubMed 40. ↵ Abiodun OO , Anya T , Adekanmbi VT . Electrocardiographic Abnormalities in Nigerian Hypertensives With Echocardiographic Left Ventricular Hypertrophy . Cureus . 2024 ; 16 ( 5 ): e60170 . OpenUrl 41. ↵ Okin PM , Wright JT , Nieminen MS , Jern S , Taylor AL , Phillips R , et al. Ethnic differences in electrocardiographic criteria for left ventricular hypertrophy: the LIFE study. Losartan Intervention For Endpoint . Am J Hypertens . 2002 ; 15 ( 8 ): 663 – 71 . OpenUrl CrossRef PubMed 42. ↵ Armstrong AC , Gjesdal O , Almeida A , Nacif M , Wu C , Bluemke DA , et al. Left ventricular mass and hypertrophy by echocardiography and cardiac magnetic resonance: the multi-ethnic study of atherosclerosis . Echocardiography . 2014 ; 31 ( 1 ): 12 – 20 . OpenUrl CrossRef PubMed 43. ↵ Ricciardi D , Vetta G , Nenna A , Picarelli F , Creta A , Segreti A , et al. Current diagnostic ECG criteria for left ventricular hypertrophy: is it time to change paradigm in the analysis of data? J Cardiovasc Med (Hagerstown ). 2020 ; 21 ( 2 ): 128 – 33 . OpenUrl PubMed 44. ↵ Park JK , Shin JH , Kim SH , Lim YH , Kim KS , Kim SG , et al. A comparison of cornell and sokolow-lyon electrocardiographic criteria for left ventricular hypertrophy in korean patients . Korean Circ J . 2012 ; 42 ( 9 ): 606 – 13 . OpenUrl PubMed 45. ↵ Levy D , Garrison RJ , Savage DD , Kannel WB , Castelli WP . Prognostic implications of echocardiographically determined left ventricular mass in the Framingham Heart Study . N Engl J Med . 1990 ; 322 ( 22 ): 1561 – 6 . OpenUrl CrossRef PubMed Web of Science 46. ↵ Koren MJ , Devereux RB , Casale PN , Savage DD , Laragh JH . Relation of left ventricular mass and geometry to morbidity and mortality in uncomplicated essential hypertension . Ann Intern Med . 1991 ; 114 ( 5 ): 345 – 52 . OpenUrl CrossRef PubMed Web of Science 47. ↵ Bang CN , Devereux RB , Okin PM . Regression of electrocardiographic left ventricular hypertrophy or strain is associated with lower incidence of cardiovascular morbidity and mortality in hypertensive patients independent of blood pressure reduction - A LIFE review . J Electrocardiol . 2014 ; 47 ( 5 ): 630 – 5 . OpenUrl CrossRef PubMed 48. ↵ You Z , He T , Ding Y , Yang L , Jiang X , Huang L . Predictive value of electrocardiographic left ventricular hypertrophy in the general population: A meta-analysis . J Electrocardiol . 2020 ; 62 : 14 – 9 . OpenUrl PubMed 49. ↵ Seko Y , Kato T , Yamaji Y , Haruna Y , Nakane E , Haruna T , et al. Discrepancy between left ventricular hypertrophy by echocardiography and electrocardiographic hypertrophy: clinical characteristics and outcomes . Open Heart . 2021 ; 8 ( 2 ). 50. ↵ Adebiyi AA , Ogah OS , Aje A , Ojji DB , Adebayo AK , Oladapo OO , et al. Echocardiographic partition values and prevalence of left ventricular hypertrophy in hypertensive Nigerians . BMC Med Imaging . 2006 ; 6 : 10 . 51. ↵ Firima E , Gonzalez L , Khan MA , Manthabiseng M , Sematle MP , Bane M , et al. High Rates of Undiagnosed Target Organ Damage Among Adults with Elevated Blood Pressure or Diabetes Mellitus in a Community-Based Survey in Lesotho . J Epidemiol Glob Health . 2023 ; 13 ( 4 ): 857 – 69 . OpenUrl PubMed View the discussion thread. Back to top Previous Next Posted November 10, 2025. Download PDF Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following ECG Criteria for Left Ventricular Hypertrophy in Hypertensive Black Africans: Insights from the CoArtHA Trial Message Subject (Your Name) has forwarded a page to you from medRxiv Message Body (Your Name) thought you would like to see this page from the medRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share ECG Criteria for Left Ventricular Hypertrophy in Hypertensive Black Africans: Insights from the CoArtHA Trial Annina Vischer , Valeriya Nemtsova , Blaise Lukau , Martin Rohacek , Jonathan Macko , Johanna Oehri , Herry Mapesi , Fiona Vanobberghen , Andrew Katende , Ravi Gupta , Herieth Ismael Wilson , Alain Amstutz , Josephine Muhairwe , Elizabeth Senkoro , Theonestina Byakuzana , Geofrey Mbunda , Jamali Siru , Winfrid Gingo , Niklaus Daniel Labhardt , Maja Weisser , Thilo Burkard medRxiv 2025.07.31.25332550; doi: https://doi.org/10.1101/2025.07.31.25332550 Share This Article: Copy Citation Tools ECG Criteria for Left Ventricular Hypertrophy in Hypertensive Black Africans: Insights from the CoArtHA Trial Annina Vischer , Valeriya Nemtsova , Blaise Lukau , Martin Rohacek , Jonathan Macko , Johanna Oehri , Herry Mapesi , Fiona Vanobberghen , Andrew Katende , Ravi Gupta , Herieth Ismael Wilson , Alain Amstutz , Josephine Muhairwe , Elizabeth Senkoro , Theonestina Byakuzana , Geofrey Mbunda , Jamali Siru , Winfrid Gingo , Niklaus Daniel Labhardt , Maja Weisser , Thilo Burkard medRxiv 2025.07.31.25332550; doi: https://doi.org/10.1101/2025.07.31.25332550 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Cardiovascular Medicine Subject Areas All Articles Addiction Medicine (567) Allergy and Immunology (863) Anesthesia (297) Cardiovascular Medicine (4411) Dentistry and Oral Medicine (443) Dermatology (380) Emergency Medicine (606) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1505) Epidemiology (15205) Forensic Medicine (30) Gastroenterology (1119) Genetic and Genomic Medicine (6574) Geriatric Medicine (666) Health Economics (994) Health Informatics (4511) Health Policy (1365) Health Systems and Quality Improvement (1608) Hematology (537) HIV/AIDS (1263) Infectious Diseases (except HIV/AIDS) (15903) Intensive Care and Critical Care Medicine (1103) Medical Education (620) Medical Ethics (144) Nephrology (666) Neurology (6573) Nursing (345) Nutrition (998) Obstetrics and Gynecology (1139) Occupational and Environmental Health (954) Oncology (3319) Ophthalmology (968) Orthopedics (369) Otolaryngology (420) Pain Medicine (435) Palliative Medicine (129) Pathology (662) Pediatrics (1689) Pharmacology and Therapeutics (691) Primary Care Research (710) Psychiatry and Clinical Psychology (5422) Public and Global Health (9205) Radiology and Imaging (2191) Rehabilitation Medicine and Physical Therapy (1367) Respiratory Medicine (1191) Rheumatology (593) Sexual and Reproductive Health (709) Sports Medicine (529) Surgery (709) Toxicology (99) Transplantation (288) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'9fe954300ce358f4',t:'MTc3OTI1OTAwNQ=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();