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White blood cell count and insulin resistance in healthy nonsmoking men
Volume 127, Number 2 American Heart Journal
Jeppesen,
White blood cell count and insulin resistance in healthy nonsmoking men
and Facchini
459
Table 1. Simple correlation coefficients between blood cell count and other variables measured
white
Variables
Jorgen Lykke Jeppesen, MD, Pierre Maheux, MD, and Francesco Stefano Facchini, MD, PhD Stanford, Calif.
Several studies have shown that elevated leukocyte or white blood cell (WBC) count is an independent risk factor for cardiovascular disease.1-4 The pathogenetic link between WBC count and cardiovascular disease is unclear. An association exists between cigarette smoking and WBC count, but even after controlling for smoking WBC count is an independent predictor of cardiovascular disease. WBC count is associated with other cardiovascular risk factors,3,5-7 and the most consistent finding is a negative association between WBC count and high-density lipoprotein (HDL) cholesterol. In this context, it has been shown that HDL cholesterol is related to insulin resistance and hyperinsulinemia.8 Our study was initiated to define a potential relation between WBC count, insulin resistance, and the variables associated with this defect, such as glucose intolerance, hyperinsulinemia, hypertriglyceridemia, high blood pressure, and low-HDL cholesterol (syndrome X),g in a population of healthy men. Methods. The study was approved by Stanford Human Subjects Committee, and each subject gave written, informed consent before entering the study. One hundred two consecutive healthy men participated in our study with a mean age ( + SD) of 50 + 13 years and a mean body mass index (BMI) of 25.6 + 3.3 kg/m2. Each subject was considered normal on the basis of history, physical examination results, blood pressure < 160/90 mm Hg, hemogram, routine blood chemistry test, and a standard oral glucose tolerance test. None of the subjects reported smoking within the previous 3 years or were taking any medications known to affect carbohydrate or lipid metabolism and WBC count. None of the subjects reported any recent allergic or infectious disease. All experimental procedures were tolerated well. The experimental procedures and analytic methods have been described in detail elsewhere.lO In brief, after a 12-hour overnight fast, blood specimens were collected for determination of fasting plasma triglyceride, cholesterol, and lipoprotein concentrations. An oral glucose tolerance
From the Department
of Medicine,
Dr. Jeppesen was supported vaerd, Denmark.
Stanford
by a training
University grant
from
School Now
of Medicine. Nordisk,
Bags-
Reprint requests: Francesco S. Facchini, MD, PhD; Department of Medicine, St. Mary’s Hospital & Medical Center, 450 Stanyan St., San Francisco, CA 94117. AM HEART
J 1994;127:459-61
Copyright ‘c 1994 0002.8703/94/$1.00
by Mosby-Year Book, + .lO 4/4/51111
Inc.
Maheux,
r
p Value
Age
0.06
0.53
BMI
0.20 0.14
<0.05 0.16 0.08
Systolic blood pressure Diastolic blood pressure Glucose response Insulin response SSPG Triglyceride Cholesterol LDL cholesterol HDL cholesterol
0.18 0.29 0.37 0.36 0.14
0.11 0.16 -0.22
<0.005
test was performed, and the area under the insulin and glucose plasma concentration curves was calculated by the trapezoidal method and defined as insulin and glucose response. Insulin resistance was estimated by the insulin suppression test. Each subject received a continous intravenous infusion of somatostatin (5 Mg/min), insulin (25 mU/m’/min) and glucose (240 mg/m2/min). Steady-state plasma insulin (SSPI) concentration and steady-state plasma glucose (SSPG) concentration were measured at frequent intervals during the last 30 minutes of the infusion. Because SSPI concentrations are similar in all individuals, SSPG concentrations provide a measure of insulinmediated glucose disposal. The higher the SSPG concentration, the more insulin-resistant the individual. The WBC count was measured on a sample of fasting venous whole blood by automated standard procedures (Coulter Counter S-4, Coulter Electronics, Hialeah, Fla.). Blood pressure was measured by standard techniques, with phase V (disappearance of Korotkoff s sounds) as the criterion for diastolic blood pressure. Results. Results are expressed as mean +-SD and were analyzed by a commercial personal computer statistical software package (STATVIEW 512, Abacus Corp., Berkeley, Calif.). Correlation coefficients between each set of two variables were assessed among all demographic and metabolic variables by Pearson correlation analysis. Variables that were significantly correlated with WBC count were reanalyzed by multiple regression analysis to identify independent predictor variables of WBC count. The mean WBC count was 5.6 t 1.4 x log/L cells. The results in Table I show the simple correlation coefficients between WBC count and the other variables measured. It is apparent from these results that WBC was significantly correlated with BMI, glucose and insulin responses, insulin resistance (Fig. l), and HDL cholesterol. It should be noted that neither total cholesterol nor LDL cholesterol correlated with WBC count. The five variables significantly correlated with WBC count were reanalyzed by multiple regression analysis to identify independent predictor variables of WBC count.
460
Jeppesen,
Maheux,
and Facchini
American
WBC COUNT
AND INSULIN
February 1994 Heart Journal
RESISTANCE
12 l. i3 =
.
gl
0”
.
.
. .
. .
s
ii c
6-
E a 0
.
3-
.
l .
l.
.
r = 0.36
l
p< 0.001
tii 3 I
I
I
I
I
I
I
50
100
150
200
250
300
350
01 0
SSPG (mg/dL) Fig. 1. Relation plasma glucose).
Table II. Regression analysis
excluding Variable
SSPG BMI HDL cholesterol
Table III. Regression analysis
excluding Variable
response Insulin BMI HDL cholesterol
between
white
blood cell count and estimates
coefficients from multiple regression insulin and glucose responses Regression coeficients 0.24 0.07 -0.12
coefficients from multiple SSPG and glucose response Regression coefficients 0.27 0.05 -0.15
of insulin
Table IV. Regression analysis
excluding
p Value
Variable
0.04 0.55 0.24
Glucose response BMI HDL cholesterol
regression
p Value 0.01 0.65 0.12
Insulin response, glucose response, and SSPG are highly correlated and metabolically closely related. The simple correlation coefficients between SSPG and insulin and glucose responses were r = 0.72 and I = 0.55, respectively. For this reason the multiple regression analysis was performed omitting (1) insulin and glucose responses in the first model (Table II), (2) SSPG and glucose response in the second model (Table III); and (3) SSPG and insulin response in the third model (Table IV). It is apparent from the three tables that SSPG, insulin, and glucose responses
resistance
(SSPG, steady-state
coefficients from multiple SSPG and insulin response Regression coefficients 0.22 0.10 -0.19
regression
p Value 0.03 0.31 0.06
were the only variables significantly associated with WBC count, and that BMI had no independent relationship with WBC count. Finally, SSPG was significantly correlated with fasting plasma triglyceride (r = 0.61, p < 0.001) and HDL cholesterol concentrations (r = -0.35, p < 0.001). Comments. Our results suggest the existence of a relationship between WBC count and insulin resistance and some of the variables associated with this defect in a population of healthy, nonsmoking men. Insulin resistance accounted for about 14 5%of the variation in WBC count, thus explaining only a minor fraction of the variation in WBC count. However, it should be noted that our study population consisted of normotensive healthy men with normal oral glucose tolerance test. It could be speculated that if we had included patients with mild diabetes and hypertension in our study population a stronger association between WBC count and insulin resistance would appear. Indeed, a very powerful effect of WBC count on cardiovascular risk was shown in the Framingham Offspring Study where patients with hypertension and diabetes were included in the
Volume 127, Number 2 American Heart Journal
Vilacosta
analysis.3 In conclusion, (1) multiple reports have provided evidence that WBC count is an independent predictor of cardiovascular disease; (2) in epidemiologic studies WBC count is associated with an atherogenic lipid profile, but so far no studies have examined a potential relation to WBC count and insulin resistance in men; (3) our data indicate that WBC count is related to abnormalities in glucose and insulin metabolism that increase the risk of cardiovascular disease; and (4) we could postulate that also an elevated WBC count may be caused by pathologic processes primarily caused by syndrome X. REFERENCES 1.
2.
Ernst E, Hammerschmidt DE, Bagge U, Matrai A, Dormandy JA. Leucocytes and the risk of ischemic disease. JAMA 1987;257:2318-24. Ensrud K, Grimm RH. The white blood cell count and risk for
coronary heart disease. AM HEART j 1992;124:207-13. 3. Kannel WB, Anderson K, Wilson PWF. White blood cell count and cardiovascular disease. JAMA 1992;267:1253-6. 4. Yarnell JWG, Baker IA, Sweetnam PM, Bainton D, O’Brien JR, Whitehead PJ, Elwood PC. Fibrinogen, viscosity, and white blood cell count are major risk factors for ischemic heart disease. Circulation 1991;83:836-44. RJ, Abbott RD, Castelli WP. Factors 5. Wilson PWF, Garrison associated with lipoprotein cholesterol levels. Arteriosclerosis 1983;3:273-81. of white 6. Hansen LK, Grimm RH, Neaton JD. The relationship blood cell count to other cardiovascular risk factors. Int J Epidemiol 1990;19:881-8. 7. Friedman GD, Tekawa I, Grimm RH, Manolio T, Shannon SG, Sidney S. The leucocyte count: correlates and relationship to coronary risk factors. The Cardia study. Int J Epidemiol 1990;19:889-93. for an independent relation8. Laws A, Reaven GM. Evidence ship between insulin resistance and fasting plasma HDL-cholesterol, trigyceride and insulin concentrations. J Intern Med 1992;231:25-30. 9. Reaven GM. Role of insulin resistance in human disease. Diabetes 1988;37:1595-607. C, Jeppesen J, Reaven GM. 10. Facchini F, Chen Y, Clinkingbeard Insulin resistance, hyperinsulinemia, and dyslipidemia in nonobese individuals with a family history of hypertension. Am d Hypertens 1992;5:694-9.
Massive left atrial calcification: limitation of transesophageal echocardiography
A
Isidre Vilacosta, MD: Jorge Gomez, MD,b Carlos Almeria, MD,a Juan Antonio Castillo, MD,a Jose Albert0 San Roman, MD,B Jose Zamorano, MD, Maria Jesus Rollan, MD: I&s Vidal, MD,” and Luis Sanchez Harguindey, MDa Madrid, Spain
From the aDepartment of Cardiology, Hospital Universitario de San Carlos; and the bDepartment of Radiology, Hospital de la Princesa. Reprint requests: Isidre Vilacosta, MD, Serrano 46, 2’ izq. 28001 Madrid, Spain. AM HEART 3 1994;127:461-3 Copyright @ 1994 by Mosby-Year Book, Inc. 0002-8703/94/$1.00 + .lO 4/4/50681
et al.
461
Transesophagealechocardiography has becomean excellent technique for imaging the left atrium so that diagnosis of left atrial thrombus can be easily made.] The anatomic proximity of the esophagusto the left atrium allows its high ultrasonic resolution. We present a casein which a massiveleft atria1calcification madeimagingof the left atrium by transesophagealechocardiography impossible. Magnetic resonanceimaging correctly demonstrated the morphology and extent of the largeleft atria1thrombus. A 71-year-old womanwith rheumatic mitral stenosiswas admitted becauseof progressive dyspnea and asthenia. When she was 43 years of age, a mitral commissurotomy wasperformed. Eleven years later shehad a transient episodeof suddenlossof consciousness and left hemiplegia, and she remained in New York Heart Association functional classII until 6 months before admission.On admission she had mild tachypnea. Blood pressurewas 130/85 mm Hg and heart rate 80 beats/min. The breath sounds were diminishedin both lung bases,but no raleswerenoted on pulmonary auscultation. Examination of the heart revealed a singleand accentuated secondheart soundand a low-pitched diastolic murmur at the apex consistentwith mitral stenosis.The electrocardiogramdemonstratedatria1 fibrillation, and the chest roentgenogramrevealed enlargement of the left atrium and the right ventricle, mild pulmonary vascular redistribution, and massiveand curvilinear left atria1 calcification forming a shell around the circumferenceof the left atria1 chamber (Fig. 1). A two-dimensionalechocardiogramwith color Doppler flow imaging was performed by using a Toshiba SSH-16OA ultrasound system with a 2.5 MHz transducer. Doppler echocardiography suggestedseveremitral stenosis(mitral valve area 1.0 cm’). The left ventricle appearednormal, and the left atrium and the mitral valve were severely calcified. A left atria1 thrombus wassuspected,but the acoustic density of the atria1 wall prevented a better visualization of the left atrium, and a well-defined echo masswas not seen. A transesophagealechocardiogramwas performed with a 5 MHz transducer. The transesophagealprobe wasadvanced to a depth between 28 and 32 cm from the patient’s teeth, and the orientation landmark of the ascendingaorta and main pulmonary artery was reached. With further advancement of the probe, the echographicimagewaslost in spite of tilting, rotating, and angulating the esophageal probe. The left atrium, the aorta, and the left atria1 appendagecould not be visualized. When the transducer wasadvanced into the transgastric position (approximately 35to 40 cmfrom the incisors),the transgastric short-axis view wasdisplayed on the video screen.It wasassumedthat the large calcification of the left atria1 wall prevented us from visualizing the left atrium and the left atria1appendage, and the patient was referred for magnetic resonance imaging. This technique demonstrated the presenceof a thrombus localized in the atria1 appendageand on the roof and the posterior wall of the left atrium (Fig. 2); it spared the anterior and the most inferior portions of the atria1 chamber. Demonstration of atria1 wall calcification represents long-standing and extensive rheumatic mitral valve disease.Sometimesthe calcification is the result of a thrombus that is adherent to the atria1 endothelium.2 The
Jeppesen,
White blood cell count and insulin resistance in healthy nonsmoking men
and Facchini
459
Table 1. Simple correlation coefficients between blood cell count and other variables measured
white
Variables
Jorgen Lykke Jeppesen, MD, Pierre Maheux, MD, and Francesco Stefano Facchini, MD, PhD Stanford, Calif.
Several studies have shown that elevated leukocyte or white blood cell (WBC) count is an independent risk factor for cardiovascular disease.1-4 The pathogenetic link between WBC count and cardiovascular disease is unclear. An association exists between cigarette smoking and WBC count, but even after controlling for smoking WBC count is an independent predictor of cardiovascular disease. WBC count is associated with other cardiovascular risk factors,3,5-7 and the most consistent finding is a negative association between WBC count and high-density lipoprotein (HDL) cholesterol. In this context, it has been shown that HDL cholesterol is related to insulin resistance and hyperinsulinemia.8 Our study was initiated to define a potential relation between WBC count, insulin resistance, and the variables associated with this defect, such as glucose intolerance, hyperinsulinemia, hypertriglyceridemia, high blood pressure, and low-HDL cholesterol (syndrome X),g in a population of healthy men. Methods. The study was approved by Stanford Human Subjects Committee, and each subject gave written, informed consent before entering the study. One hundred two consecutive healthy men participated in our study with a mean age ( + SD) of 50 + 13 years and a mean body mass index (BMI) of 25.6 + 3.3 kg/m2. Each subject was considered normal on the basis of history, physical examination results, blood pressure < 160/90 mm Hg, hemogram, routine blood chemistry test, and a standard oral glucose tolerance test. None of the subjects reported smoking within the previous 3 years or were taking any medications known to affect carbohydrate or lipid metabolism and WBC count. None of the subjects reported any recent allergic or infectious disease. All experimental procedures were tolerated well. The experimental procedures and analytic methods have been described in detail elsewhere.lO In brief, after a 12-hour overnight fast, blood specimens were collected for determination of fasting plasma triglyceride, cholesterol, and lipoprotein concentrations. An oral glucose tolerance
From the Department
of Medicine,
Dr. Jeppesen was supported vaerd, Denmark.
Stanford
by a training
University grant
from
School Now
of Medicine. Nordisk,
Bags-
Reprint requests: Francesco S. Facchini, MD, PhD; Department of Medicine, St. Mary’s Hospital & Medical Center, 450 Stanyan St., San Francisco, CA 94117. AM HEART
J 1994;127:459-61
Copyright ‘c 1994 0002.8703/94/$1.00
by Mosby-Year Book, + .lO 4/4/51111
Inc.
Maheux,
r
p Value
Age
0.06
0.53
BMI
0.20 0.14
<0.05 0.16 0.08
Systolic blood pressure Diastolic blood pressure Glucose response Insulin response SSPG Triglyceride Cholesterol LDL cholesterol HDL cholesterol
0.18 0.29 0.37 0.36 0.14
0.11 0.16 -0.22
<0.005
test was performed, and the area under the insulin and glucose plasma concentration curves was calculated by the trapezoidal method and defined as insulin and glucose response. Insulin resistance was estimated by the insulin suppression test. Each subject received a continous intravenous infusion of somatostatin (5 Mg/min), insulin (25 mU/m’/min) and glucose (240 mg/m2/min). Steady-state plasma insulin (SSPI) concentration and steady-state plasma glucose (SSPG) concentration were measured at frequent intervals during the last 30 minutes of the infusion. Because SSPI concentrations are similar in all individuals, SSPG concentrations provide a measure of insulinmediated glucose disposal. The higher the SSPG concentration, the more insulin-resistant the individual. The WBC count was measured on a sample of fasting venous whole blood by automated standard procedures (Coulter Counter S-4, Coulter Electronics, Hialeah, Fla.). Blood pressure was measured by standard techniques, with phase V (disappearance of Korotkoff s sounds) as the criterion for diastolic blood pressure. Results. Results are expressed as mean +-SD and were analyzed by a commercial personal computer statistical software package (STATVIEW 512, Abacus Corp., Berkeley, Calif.). Correlation coefficients between each set of two variables were assessed among all demographic and metabolic variables by Pearson correlation analysis. Variables that were significantly correlated with WBC count were reanalyzed by multiple regression analysis to identify independent predictor variables of WBC count. The mean WBC count was 5.6 t 1.4 x log/L cells. The results in Table I show the simple correlation coefficients between WBC count and the other variables measured. It is apparent from these results that WBC was significantly correlated with BMI, glucose and insulin responses, insulin resistance (Fig. l), and HDL cholesterol. It should be noted that neither total cholesterol nor LDL cholesterol correlated with WBC count. The five variables significantly correlated with WBC count were reanalyzed by multiple regression analysis to identify independent predictor variables of WBC count.
460
Jeppesen,
Maheux,
and Facchini
American
WBC COUNT
AND INSULIN
February 1994 Heart Journal
RESISTANCE
12 l. i3 =
.
gl
0”
.
.
. .
. .
s
ii c
6-
E a 0
.
3-
.
l .
l.
.
r = 0.36
l
p< 0.001
tii 3 I
I
I
I
I
I
I
50
100
150
200
250
300
350
01 0
SSPG (mg/dL) Fig. 1. Relation plasma glucose).
Table II. Regression analysis
excluding Variable
SSPG BMI HDL cholesterol
Table III. Regression analysis
excluding Variable
response Insulin BMI HDL cholesterol
between
white
blood cell count and estimates
coefficients from multiple regression insulin and glucose responses Regression coeficients 0.24 0.07 -0.12
coefficients from multiple SSPG and glucose response Regression coefficients 0.27 0.05 -0.15
of insulin
Table IV. Regression analysis
excluding
p Value
Variable
0.04 0.55 0.24
Glucose response BMI HDL cholesterol
regression
p Value 0.01 0.65 0.12
Insulin response, glucose response, and SSPG are highly correlated and metabolically closely related. The simple correlation coefficients between SSPG and insulin and glucose responses were r = 0.72 and I = 0.55, respectively. For this reason the multiple regression analysis was performed omitting (1) insulin and glucose responses in the first model (Table II), (2) SSPG and glucose response in the second model (Table III); and (3) SSPG and insulin response in the third model (Table IV). It is apparent from the three tables that SSPG, insulin, and glucose responses
resistance
(SSPG, steady-state
coefficients from multiple SSPG and insulin response Regression coefficients 0.22 0.10 -0.19
regression
p Value 0.03 0.31 0.06
were the only variables significantly associated with WBC count, and that BMI had no independent relationship with WBC count. Finally, SSPG was significantly correlated with fasting plasma triglyceride (r = 0.61, p < 0.001) and HDL cholesterol concentrations (r = -0.35, p < 0.001). Comments. Our results suggest the existence of a relationship between WBC count and insulin resistance and some of the variables associated with this defect in a population of healthy, nonsmoking men. Insulin resistance accounted for about 14 5%of the variation in WBC count, thus explaining only a minor fraction of the variation in WBC count. However, it should be noted that our study population consisted of normotensive healthy men with normal oral glucose tolerance test. It could be speculated that if we had included patients with mild diabetes and hypertension in our study population a stronger association between WBC count and insulin resistance would appear. Indeed, a very powerful effect of WBC count on cardiovascular risk was shown in the Framingham Offspring Study where patients with hypertension and diabetes were included in the
Volume 127, Number 2 American Heart Journal
Vilacosta
analysis.3 In conclusion, (1) multiple reports have provided evidence that WBC count is an independent predictor of cardiovascular disease; (2) in epidemiologic studies WBC count is associated with an atherogenic lipid profile, but so far no studies have examined a potential relation to WBC count and insulin resistance in men; (3) our data indicate that WBC count is related to abnormalities in glucose and insulin metabolism that increase the risk of cardiovascular disease; and (4) we could postulate that also an elevated WBC count may be caused by pathologic processes primarily caused by syndrome X. REFERENCES 1.
2.
Ernst E, Hammerschmidt DE, Bagge U, Matrai A, Dormandy JA. Leucocytes and the risk of ischemic disease. JAMA 1987;257:2318-24. Ensrud K, Grimm RH. The white blood cell count and risk for
coronary heart disease. AM HEART j 1992;124:207-13. 3. Kannel WB, Anderson K, Wilson PWF. White blood cell count and cardiovascular disease. JAMA 1992;267:1253-6. 4. Yarnell JWG, Baker IA, Sweetnam PM, Bainton D, O’Brien JR, Whitehead PJ, Elwood PC. Fibrinogen, viscosity, and white blood cell count are major risk factors for ischemic heart disease. Circulation 1991;83:836-44. RJ, Abbott RD, Castelli WP. Factors 5. Wilson PWF, Garrison associated with lipoprotein cholesterol levels. Arteriosclerosis 1983;3:273-81. of white 6. Hansen LK, Grimm RH, Neaton JD. The relationship blood cell count to other cardiovascular risk factors. Int J Epidemiol 1990;19:881-8. 7. Friedman GD, Tekawa I, Grimm RH, Manolio T, Shannon SG, Sidney S. The leucocyte count: correlates and relationship to coronary risk factors. The Cardia study. Int J Epidemiol 1990;19:889-93. for an independent relation8. Laws A, Reaven GM. Evidence ship between insulin resistance and fasting plasma HDL-cholesterol, trigyceride and insulin concentrations. J Intern Med 1992;231:25-30. 9. Reaven GM. Role of insulin resistance in human disease. Diabetes 1988;37:1595-607. C, Jeppesen J, Reaven GM. 10. Facchini F, Chen Y, Clinkingbeard Insulin resistance, hyperinsulinemia, and dyslipidemia in nonobese individuals with a family history of hypertension. Am d Hypertens 1992;5:694-9.
Massive left atrial calcification: limitation of transesophageal echocardiography
A
Isidre Vilacosta, MD: Jorge Gomez, MD,b Carlos Almeria, MD,a Juan Antonio Castillo, MD,a Jose Albert0 San Roman, MD,B Jose Zamorano, MD, Maria Jesus Rollan, MD: I&s Vidal, MD,” and Luis Sanchez Harguindey, MDa Madrid, Spain
From the aDepartment of Cardiology, Hospital Universitario de San Carlos; and the bDepartment of Radiology, Hospital de la Princesa. Reprint requests: Isidre Vilacosta, MD, Serrano 46, 2’ izq. 28001 Madrid, Spain. AM HEART 3 1994;127:461-3 Copyright @ 1994 by Mosby-Year Book, Inc. 0002-8703/94/$1.00 + .lO 4/4/50681
et al.
461
Transesophagealechocardiography has becomean excellent technique for imaging the left atrium so that diagnosis of left atrial thrombus can be easily made.] The anatomic proximity of the esophagusto the left atrium allows its high ultrasonic resolution. We present a casein which a massiveleft atria1calcification madeimagingof the left atrium by transesophagealechocardiography impossible. Magnetic resonanceimaging correctly demonstrated the morphology and extent of the largeleft atria1thrombus. A 71-year-old womanwith rheumatic mitral stenosiswas admitted becauseof progressive dyspnea and asthenia. When she was 43 years of age, a mitral commissurotomy wasperformed. Eleven years later shehad a transient episodeof suddenlossof consciousness and left hemiplegia, and she remained in New York Heart Association functional classII until 6 months before admission.On admission she had mild tachypnea. Blood pressurewas 130/85 mm Hg and heart rate 80 beats/min. The breath sounds were diminishedin both lung bases,but no raleswerenoted on pulmonary auscultation. Examination of the heart revealed a singleand accentuated secondheart soundand a low-pitched diastolic murmur at the apex consistentwith mitral stenosis.The electrocardiogramdemonstratedatria1 fibrillation, and the chest roentgenogramrevealed enlargement of the left atrium and the right ventricle, mild pulmonary vascular redistribution, and massiveand curvilinear left atria1 calcification forming a shell around the circumferenceof the left atria1 chamber (Fig. 1). A two-dimensionalechocardiogramwith color Doppler flow imaging was performed by using a Toshiba SSH-16OA ultrasound system with a 2.5 MHz transducer. Doppler echocardiography suggestedseveremitral stenosis(mitral valve area 1.0 cm’). The left ventricle appearednormal, and the left atrium and the mitral valve were severely calcified. A left atria1 thrombus wassuspected,but the acoustic density of the atria1 wall prevented a better visualization of the left atrium, and a well-defined echo masswas not seen. A transesophagealechocardiogramwas performed with a 5 MHz transducer. The transesophagealprobe wasadvanced to a depth between 28 and 32 cm from the patient’s teeth, and the orientation landmark of the ascendingaorta and main pulmonary artery was reached. With further advancement of the probe, the echographicimagewaslost in spite of tilting, rotating, and angulating the esophageal probe. The left atrium, the aorta, and the left atria1 appendagecould not be visualized. When the transducer wasadvanced into the transgastric position (approximately 35to 40 cmfrom the incisors),the transgastric short-axis view wasdisplayed on the video screen.It wasassumedthat the large calcification of the left atria1 wall prevented us from visualizing the left atrium and the left atria1appendage, and the patient was referred for magnetic resonance imaging. This technique demonstrated the presenceof a thrombus localized in the atria1 appendageand on the roof and the posterior wall of the left atrium (Fig. 2); it spared the anterior and the most inferior portions of the atria1 chamber. Demonstration of atria1 wall calcification represents long-standing and extensive rheumatic mitral valve disease.Sometimesthe calcification is the result of a thrombus that is adherent to the atria1 endothelium.2 The