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Circulation. 1997;96:1863-1873

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(Circulation. 1997;96:1863-1873.)
© 1997 American Heart Association, Inc.

Articles

Distribution and Categorization of Echocardiographic Measurements in Relation to Reference Limits

The Framingham Heart Study: Formulation of a Height- and Sex-Specific Classification and Its Prospective Validation

Ramachandran S. Vasan, MD; Martin G. Larson, ScD; Daniel Levy, MD; Jane C. Evans, MPH; ; Emelia J. Benjamin, MD, ScM

From the National Heart, Lung, and Blood Institute's Framingham (Mass) Heart Study (all authors); the Divisions of Cardiology and Clinical Epidemiology, Beth Israel Hospital, Harvard Medical School, Boston, Mass (D.L.); the Cardiology Section (E.J.B.) and Department of Preventive Medicine and Epidemiology (R.S.V., M.G.L., D.L., E.J.B.), Boston (Mass) University School of Medicine; and the National Heart, Lung, and Blood Institute, Bethesda, Md (D.L.).

Correspondence to Emelia J. Benjamin. MD, ScM, Framingham Heart Study, 5 Thurber St, Framingham, MA 01701. E-mail emelia{at}fram.nhlbi.nih.gov


*    Abstract
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 *Abstract
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 down arrowResults
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Background Despite widespread categorization of echocardiographic measurements, there are no standardized guidelines for partitioning values exceeding reference limits.

Methods and Results We used regression analyses to develop sex- and height-specific reference limits for cardiac M-mode measurements (left ventricular [LV] mass, LV wall thickness, and LV and left atrial dimensions) in a healthy reference sample (n=1099) from the Framingham Heart Study. We then examined the distribution of measurements in a broad sample (n=4957) and classified the measurements according to increasing deviation from the height- and sex-specific reference limits and the 95th, 98th, and 99th percentile values for the broad sample (categories 0 through 4, respectively). To validate the categorization scheme, we used multivariable proportional-hazards regression to assess the relations of LV mass and LV wall thickness categories to risk of cardiovascular events and the relations of left atrial size to risk of atrial fibrillation. During a mean follow-up period of 7.7 years, 587 subjects developed new cardiovascular disease events, and 166 subjects developed new-onset atrial fibrillation. After adjustment for known risk factors, there was a 1.2- and 1.3-fold risk of cardiovascular disease events per category of LV wall thickness and LV mass, respectively, and a 1.6-fold risk of atrial fibrillation per category of left atrial size.

Conclusions Using a large community-based study sample, we propose a classification scheme that provides a standardized and validated framework for partitioning echocardiographic measurements. If adopted, the categorization scheme should promote uniformity in describing measurements among echocardiographic laboratories and enhance the comprehensibility of measurements to clinicians.


Key Words: echocardiography • cardiovascular diseases • ventricles • atrium • follow-up studies


*    Introduction
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 up arrowAbstract
 *Introduction
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 down arrowDiscussion
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Reference values, often referred to as the "upper limits of normal," have been proposed for echocardiographic dimensions of cardiac chambers.1 2 3 4 5 6 7 8 9 10 The current practice in echocardiographic laboratories across the world is to categorize echocardiographic measurements as normal or into mild, moderate, or severe degrees of abnormality. For instance, the expressions "moderate concentric left ventricular hypertrophy" and "severe left atrial enlargement" are used widely to describe quantitative abnormalities of these cardiac structures. Despite the widespread use of such descriptive terms, there are no standardized guidelines in the echocardiographic literature regarding cut points for partitioning values exceeding reference limits. Furthermore, the current clinical practice of categorizing values exceeding reference limits is highly variable between and within institutions, neither height- nor sex-specific, and inadequately substantiated by scientific data.

The choice of cut points for classifying echocardiographic values (or any other quantitative clinical measurement) on an ordinal scale should be based on the distribution of these observations in relation to reference limits in a randomly selected noninstitutionalized sample of the general population.11 Such a classification system may be useful for descriptive purposes, for prognostication, and for the prevention and treatment of diseases.12 Previous publications from the Framingham Heart Study have evaluated the relations of echocardiographic variables as continuous measures to cardiovascular disease events. The objectives of the present investigation were twofold: (1) to develop a classification system of echocardiographic values exceeding reference limits in a community-based study sample and (2) to prospectively examine the utility of our categorization approach for predicting clinically important events during follow-up.


*    Methods
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 up arrowAbstract
 up arrowIntroduction
 *Methods
down arrowResults
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Study Sample
The selection criteria and study design of the FHS (both original and offspring study cohorts) have been detailed extensively.13 14 Original subjects of the FHS who participated in the 16th biennial examination (1979 through 1981) and subjects of the Framingham Offspring Study who participated in the second offspring examination (1979 through 1983) constituted the study sample. The FHS examination has been approved by the Boston Medical Center Institutional Review Board, and all subjects gave informed consent before the examinations.

Of 6216 subjects who attended the index examinations, 1259 subjects (20.3%) with inadequate M-mode echocardiograms were excluded from the present investigation. The study sample included two groups. The larger group, called the broad sample, included all 4957 who had adequate M-mode echocardiograms. A healthy subgroup of 1099 subjects, henceforth called the reference sample, was selected from the broad sample to formulate reference limits. The reference sample included subjects between the ages of 20 and 45 years who were not obese (body mass index between 19 and 26 kg/m2), who were of average height (1.5 to 1.9 m in men and 1.4 to 1.8 m in women), and who were free of cardiovascular disease, hypertension,15 AF, diabetes mellitus, and cardiac medication use.

Echocardiographic Methods
All subjects underwent routine M-mode echocardiography. In >90% of subjects, two-dimensional guided M-mode echocardiograms were obtained from the left parasternal window.16 All measurements were made according to the American Society of Echocardiography guidelines.17 Three measurements were averaged for each value. The following echocardiographic variables were studied in the present investigation: LA dimensions, LV mass, LV wall thickness, and LV end-diastolic and end-systolic internal dimensions. LV mass was calculated thus: LV mass=0.8[1.04(LVIDD+IVST+PWT)3-(LVIDD)3]+0.6, where LVIDD represents LV end-diastolic internal dimension and IVST and PWT indicate the end-diastolic thicknesses of the interventricular septum and LV posterior wall, respectively.18 End-diastolic LV wall thickness was calculated as IVST+PWT.

Analysis and Statistical Methods
Development of Classification for Values Exceeding Reference Limits
All analyses were sex-specific. Height was used for indexation of echocardiographic variables because the use of body surface area may inappropriately mask obesity-related alterations in cardiac structure.19 20 21 22 For each echocardiographic variable Y, logarithmic regression analyses were performed using the reference sample with height as the predictor variable, thus: log Y=ß0+ß1 log(height)+E, where ß0 is the Y-axis intercept, ß1 is the slope, and E is an error term. The predicted value of Y was calculated as Yp=exp[ß0+ß1 log(height)]. The 95th percentile value of Y was calculated for the reference sample as Y95=Yxexp(1.645xroot mean square error). The values of Y95 represent the sex- and height-specific reference limits for the variable. Reference limits (regression coefficients and the values of [height]k, k being sex-specific and echocardiographic variable–specific) for LV wall thickness, LV internal dimensions, and LV mass have been published previously.19 20 The distribution of the ratio of the raw observation divided by the value predicted for height and sex, ie, Y/Yp, in the broad sample was studied. The sex- and height-specific 95th, 98th, and 99th percentile values of the echocardiographic variable in the broad sample were determined subsequently from the corresponding percentiles of the ratio. We classified values of each echocardiographic variable into the following five categories based on sex- and height-specific percentiles (indicating increasing deviation from the reference limits): category 0 (reference limits), value <=95th percentile of the reference sample; category 1, 95th percentile of reference sample<value<=95th percentile of broad sample; category 2, 95th percentile of broad sample<value<=98th percentile of broad sample; category 3, 98th percentile of broad sample<value<=99th percentile of broad sample; and category 4, value >99th percentile of broad sample.

Relations of Categories of Echocardiographic Variables to Clinical Outcomes
To assess the validity and prognostic significance of the proposed classification scheme, we evaluated the risk of adverse clinical outcomes among subjects in the five proposed categories of each echocardiographic variable (as defined at the baseline examination) during a follow-up period of up to 11 years. Category 0 served as the reference group with which the other categories were compared. The a priori hypothesis was that an increase in risk of adverse clinical events would be observed across the five categories of each echocardiographic variable. Analyses relating to categories of LV mass, LV wall thickness and LA dimensions are presented here. The relations of LV mass and LV wall thickness to the incidence of cardiovascular disease events and of LA dimensions to the incidence of new-onset AF were examined with sex-stratified Cox regression,23 adjusted for known risk factors for these outcomes. The end points were selected a priori on the basis of previous studies reporting an association of increasing LV mass24 25 26 27 28 29 and LV wall thickness25 27 with risk of cardiovascular events and of increasing LA size with risk of AF.30 31 All study subjects were under periodic surveillance for development of cardiovascular disease events with the aid of medical history, hospitalization records, and communication with personal physicians. All suspected new cardiovascular events were reviewed by a panel of three investigators who evaluated all pertinent available medical records. Cardiovascular disease events included coronary heart disease (angina pectoris, coronary insufficiency, myocardial infarction, and sudden or nonsudden death attributable to coronary heart disease), congestive heart failure, cerebrovascular disease (stroke or transient ischemic attack), and intermittent claudication. Criteria for these events have been detailed previously.32 A diagnosis of AF on follow-up was made on the basis of documentation of AF or flutter on ECGs obtained from the FHS examination, hospital records, or private physician records. For examining the impact of LA size categories on risk of AF, we excluded subjects with AF at or before baseline (n=82).

Adjustment for Covariates
For multivariable analyses examining cardiovascular events as the outcome, hazard ratios were adjusted for the following covariates: sex, age (years), diastolic blood pressure (mm Hg), pulse pressure (mm Hg), the ratio of total to HDL cholesterol, body mass index (weight in kg/[height in m]2), and the following dichotomous variables: hypertension, smoking, diabetes mellitus, and prior cardiovascular disease.24 The covariates included in the multivariable models evaluating AF as the outcome event included age (years), hypertension status, diabetes mellitus, ECG LV hypertrophy, valve disease, and prior cardiovascular disease.33 Hypertension was defined according to the JNC-V criteria as a systolic blood pressure value >=140 mm Hg, a diastolic blood pressure value >=90 mm Hg,15 or current drug treatment for hypertension. Valve disease was defined as the presence of a diastolic murmur or a systolic murmur (grade 3/6 or more) on precordial auscultation at baseline. Criteria for other risk factors have been detailed previously.34 Only subjects with complete information regarding the covariates were included for the proportional-hazards analyses.

Choice of Statistical Models
We investigated whether the risk of adverse events differed among categories of echocardiographic variables using the several multivariable statistical models: models incorporating clinical variables only; multicategory models, in which risk of adverse outcome in each category was compared with that associated with category 0; trend models, in which we investigated whether there was a stepwise increase in risk of adverse outcome from one category to the next higher one; and threshold models, in which we tested whether there was a particular category above which there was increased risk of adverse outcomes (eg, risk of adverse events in subjects in categories 0 and 1 versus risk in subjects in categories 2, 3, and 4).

To explore the impact of sex on the risks associated with the echocardiographic categories, we performed secondary analyses incorporating interaction terms. All analyses were performed with the SAS System (SAS Institute Inc) procedures REG35 and PHREG36 on a SUNsparc 2 workstation; a two-sided value of P<.05 assessed statistical significance.


*    Results
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 up arrowAbstract
 up arrowIntroduction
 up arrowMethods
 *Results
down arrowDiscussion
 down arrowReferences
 
Study Sample
The characteristics of the study subjects are summarized in Table 1Down. Compared with the reference sample, subjects in the broad sample were older, heavier, and had higher blood pressure, body mass index, and mean values for the echocardiographic measurements studied. In the broad sample, the prevalence of cardiovascular disease was as follows: hypertension, 33.1%; coronary disease, 6.7%; congestive heart failure, 0.9%; and AF, 1.7%. These conditions were grounds for exclusion from the reference sample.


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  		Table 1. Clinical and Echocardiographic Characteristics of Study Samples

Classification of Values Exceeding Reference Limits
In general, we noted a significant relation between height and echocardiographic variables in both sexes. The distributions of the ratio of observed to sex- and height-predicted values were examined for each echocardiographic variable; the FigureDown displays the distribution of this ratio for LA dimension, LV mass, LV wall thickness, and LV end-diastolic dimension. Approximately one quarter of men and one third of women exceeded reference limits for LV wall thickness, LV mass, and LA dimension. Eleven percent of men and 9% of women exceeded reference limits for LV end-diastolic dimension. Tables 2Down and 3Down provide the sex- and height-specific cut points for the five proposed categories of each echocardiographic variable derived from the percentiles of the ratio of observed to sex- and height-predicted values in the reference (category 0) and broad (categories 1 through 4) samples.



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  		Figure 1. Distribution and categorization of echocardiographic variables in the broad sample of 4957 subjects based on deviation from height- and sex-specific reference limits. Categories were based on relations of 95th, 98th, and 99th percentile values of observed/predicted value for given height and sex in broad sample to reference limits. Reference limits were based on 95th percentile values in a healthy reference sample. Values for 22% of men and 29% of women exceeded reference limits for LA dimensions; values for 17% of men and 24% of women exceeded reference limits but were <95th percentile for broad sample. About 23% of men and 28% of women in broad sample exceeded reference limits for LV mass; LV mass values for 18% of men and 23% of women exceeded reference limits (height- and sex-specific) but were within 95th percentile of values for broad sample. Values for 26% of men and 36% of women exceeded reference limits for LV wall thickness; values for 21% of men and 31% of women were intermediate between reference limits and 95th percentile of values for broad sample. Values for 11% of men and 9% of women exceeded reference limits for LV end-diastolic internal dimensions (LVIDed); values for 5% of men and 4% of women were between reference limits and 95th percentile for broad sample. For LV end-systolic internal dimensions, distribution of male subjects was 2058, 53, 66, 23, and 23 for categories 0, 1, 2, 3, and 4, respectively; distribution of female subjects was 2545, 51, 83, 27, and 28 for categories 0, 1, 2, 3, and 4, respectively (not shown).


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  		Table 2. Cut Points for Categorization of Echocardiographic LA Size, LV Mass, Wall Thickness, and LV Diameter in Women


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  		Table 3. Cut Points for Categorization of Echocardiographic LA Size, LV Mass, Wall Thickness, and LV Diameter in Men

Relation of Category of Echocardiographic Variable to Clinical Outcome
Unadjusted Event Rates According to Category of Variable
Three subjects were lost to follow-up. During follow-up of the remaining 4954 subjects (mean age, 7.7 years; range, 0.4 to 11 years), 587 subjects experienced a new cardiovascular event; 55 of these new events were fatal. There were 166 subjects with new-onset AF among the 4872 subjects free of AF at baseline. Crude rates for new events increased across categories of LV mass, LV wall thickness, and LA size (Tables 4 through 6DownDownDown). Among men and women with a measurement of LV mass or LV wall thickness suggestive of extreme deviation from reference limits (category 4), >60% developed new cardiovascular disease events on follow-up; in comparison, <10% of the subjects in category 0 experienced a new event. Categories of LV mass or LV wall thickness between these two extremes (categories 1 through 3) had intermediate rates of new cardiovascular disease events. For categories of LA dimension, AF rates rose in stepwise fashion; >60% of subjects in category 4 developed AF, compared with 2% of subjects in category 0.


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  		Table 4. Relations of Categories of LV Mass to Incidence of New Cardiovascular Disease Events: Results of Cox Proportional-Hazards Models


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  		Table 5. Relations of Categories of LV Wall Thickness to Incidence of New Cardiovascular Disease Events: Results of Cox Proportional-Hazards Models


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  		Table 6. Relations of Categories of LA Dimension to Incidence of AF: Results of Cox Proportional-Hazards Models

Multivariable Analyses
Irrespective of the choice of the statistical model, a significant risk gradient for adverse events was evident across the categories of LV mass, LV wall thickness, and LA dimensions for both sexes after adjustment for other known risk factors. In general, trend models were roughly comparable to the five category models in terms of risk prediction but incorporated fewer variables (ie, were more parsimonious). The threshold models were inferior to the trend and five category models but were better than multivariable models that included only clinical predictors (data not shown). The results of the trend and five-category models are shown in Tables 4 through 6UpUpUp. There was a 1.2- to 1.3-fold increase in hazard for new cardiovascular disease events per increase in category of LV wall thickness and LV mass, respectively (trend model). There was a 1.6-fold increase in hazard of AF per increase in category of LA dimension (trend model); a 4.4-fold hazard was seen for subjects in the highest category of LA dimension compared with those in the lowest category. There were no significant sex differences in the risks associated with LV mass and LV wall thickness categories (probability values for the respective interaction terms were .29 and .68). There was a 29% greater risk for AF across LA size categories in women than in men (P=.08).


*    Discussion
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 up arrowAbstract
 up arrowIntroduction
 up arrowMethods
 up arrowResults
 *Discussion
down arrowReferences
 
Need for Classifying Echocardiographic Values in Relation to Reference Limits
Because of the plethora of tests in medicine, raw values of clinical measurements often are poorly comprehended by nonspecialists. Understandably, nonspecialists frequently cannot recall cut points for abnormality, much less retain a sense of how far an abnormal value has strayed from normal.37 Clinical chemists have tried to resolve this dilemma by presenting any observed value in relation to its reference limits.38 Classification of abnormal clinical measurements on an ordinal scale, ie, within reference limits and with increasing degrees of deviation from reference limits, is an attractive option because clinicians tend to think in terms of categories when they interpret quantitative clinical data.39 Besides making clinical data more comprehensible to nonspecialists, classification also renders the available information more manageable.40

When standards for categorization of laboratory tests are absent, clinicians set their own informal criteria for converting noncategorical data into categorical information. This was well illustrated by a study addressing the interpretation of objective measures by physicians; the larger the physician's own set of reference values was, the greater was the leniency in the interpretation of such data.41 We searched the literature for cut points for classifying echocardiographic values exceeding the reference limits but failed to find standardized guidelines. Despite the routine use of descriptive categories in echocardiography laboratories, there is little scientific literature to support such practice.

Development and Validation of Our Classification
There is no universally accepted method for categorizing continuous variables.42 43 44 In the present investigation, we developed a classification system for echocardiographic reference limits that attempted to meet two broad objectives: standardization of echocardiographic interpretation and clinical sensibility.39 To achieve the latter goal, we sought to develop a classification system that was straightforward, user-friendly, evidence based, and based on appropriate physiological variables. Because echocardiographic measurements are dependent on sex as well as on body size,19 20 45 echocardiographic variables should be classified with reference to sex and to anthropometric measurements. We chose height as a physiological obesity-independent determinant of echocardiographic measurements. Although age is an important determinant of cardiac dimensions,21 46 47 we avoided formulating age-dependent cut points because of uncertainty in distinguishing the physiological from the pathological effects of aging on the heart.48

By examining the distribution of values in a broad study sample that included healthy and diseased individuals, we developed a classification in which each echocardiographic variable could be partitioned into four categories based on increasing degrees of deviation from reference limits (category 0). The present investigation suggested that echocardiographic measurements exceeding height- and sex-specific reference limits were associated with an adverse prognosis; furthermore, the greater the extent of deviation, the worse the prognosis. Results of trend models indicated a stepwise increase in hazard per category increase in LV mass (1.3-fold risk of cardiovascular disease events), LV wall thickness (1.2-fold risk of cardiovascular events), and LA size (1.6-fold risk of AF). The adverse impact associated with values in categories 1 through 4 (compared with category 0) was evident in both sexes, persisted in multivariable analyses adjusting for the impact of other known risk factors, and was generally consistent within the various statistical models explored.

Strengths and Limitations
Any classification may be justified on the basis of its peremptory assignment, its consensual validation, or external documentation.40 Peremptory assignment is desirable when data have no inherent meaning (eg, zip codes). A consensual approach involves establishing a standard by common agreement of experts in the field. External documentation (validation by application) requires providing independent evidence that justifies the creation of the proposed categories. We chose the latter method because we believe that it was unbiased and scientifically more rigorous. Furthermore, the ability of any classification system to predict risk of adverse events considerably enhances its utility to the clinician. The longitudinal design of the FHS facilitated such prospective validation.

To the best of our knowledge, except for LV mass,49 the present investigation is the first systematic attempt at classifying echocardiographic values exceeding reference limits. The a priori definition of cut points based on the distribution of the echocardiographic measurements instead of post hoc generation based on clinical outcome events is an additional strength of our study.44 The large, community-based study sample used for deriving our reference limits and for developing and validating our classification approach makes the present investigation unique. In comparison, previous reports of echocardiographic reference limits1 2 3 4 5 6 7 8 9 10 have been based on percentile estimates drawn from cross-sectional samples of smaller numbers of healthy subjects. Previous investigations from the FHS19 50 and elsewhere1 2 3 4 5 6 7 8 9 10 have not subdivided the values exceeding reference limits for practical use by clinicians.

The exclusion of subjects without satisfactory echocardiograms (who are generally sicker) may have resulted in the lowering of thresholds for abnormal values. The use of M-mode measurements presents other potential limitations. Cardiac disease may result in distorted LV geometry with the possibility of underestimating or overestimating LV mass.51 Furthermore, M-mode technology (transducer sensitivity, etc) has changed over the past two decades because the echocardiograms were performed. In addition, categories based on M-mode measurements may not be generalizable to two-dimensional echocardiographic measurements. Nonetheless, previous investigations have found reasonable agreement between measurements made by the two techniques.6 52 Finally, it is possible for a patient to shift between categories simply on the basis of limitations in the reproducibility of echocardiographic measurements.53

Because the generation and validation of our classification are based on ambulatory subjects, its prognostic relevance in hospitalized subjects is unknown. A related potential limitation is that in addition to age, the cut points are largely dependent on the prevalent pattern and severity of cardiac disease in the study participants. For instance, cut points for varying degrees of LV hypertrophy and LV dilatation obtained from our study sample may differ substantially from those obtained from subjects in hypertension and heart failure clinics, respectively. Nonetheless, it is heartening to note that the prevalence of cardiovascular disease in our study sample was consistent with that observed in the general US population.54 Furthermore, although we have demonstrated significant prognostic value of this categorization scheme, the therapeutic implications of our classification, if any, are unknown. Last, given the largely white racial composition of the Framingham sample, readers should exercise caution in extrapolating the study results to other racial groups.

Clinical Implications
Scrutiny of our cut points reveals that there are some challenges to currently used thresholds for quantitative echocardiographic abnormalities. For example, a sum of septal and posterior LV wall thicknesses of 20 mm is regarded as normal by most clinicians. Nonetheless, we would classify this value as above reference limits in a woman or in a short man; such a value for wall thickness (category 1) is associated with a 1.2-fold risk of cardiovascular disease events compared with values within reference limits. These observations underscore the weaknesses inherent in the use of traditional reference limits that establish an arbitrary dichotomous threshold (mean±2 SD or 95th percentile) without providing insights into risks associated with various levels of the echocardiographic variable.

By classifying echocardiographic values on an ordinal scale reflecting an increasing hazard for morbid events across categories, we have reported a framework that will promote greater consistency in echocardiographic interpretation and will provide prognostic information. Such a standardized classification is particularly important in an era when the nonspecialist not only orders echocardiograms but also is expected to interpret and act on the results of the studies.


*    Selected Abbreviations and Acronyms
 
AF = atrial fibrillation
FHS = Framingham Heart Study
LA = left atrial
LV = left ventricular


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  		Table 2A. Continued


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  		Table 3A. Continued


*    Acknowledgments
 
This work was supported in part by NIH/NHLBI contract NOI-HC-38038 and NINDS grant 2-ROI-NS-17950-11. Dr Vasan's research fellowship was made possible by a grant from Merck & Co Inc.

Received December 9, 1996; revision received March 25, 1997; accepted April 26, 1997.


*    References
up arrowTop
 up arrowAbstract
 up arrowIntroduction
 up arrowMethods
 up arrowResults
 up arrowDiscussion
 *References
 

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