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Archives of internal medicine 2004-Jan

Accuracy of ultrasonography in predicting celiac disease.

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Mirella Fraquelli
Agostino Colli
Alice Colucci
Maria Teresa Bardella
Cristina Trovato
Roberta Pometta
Michela Pagliarulo
Dario Conte

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Resumo

BACKGROUND

Various ultrasonographic (US) signs have been reported in overt celiac disease (CD). The aim of this study was to investigate the diagnostic accuracy of 6 US parameters in predicting CD.

METHODS

One hundred sixty-two consecutive patients with chronic diarrhea (n=105), iron deficiency anemia (n=25), or dyspepsia (n=32) underwent anti-endomysial IgA antibody determination and duodenal biopsy. Moreover, US evaluation of 6 parameters (ie, fasting gallbladder volume, transverse diameter of small bowel loops, thickness of the small bowel wall, pattern of peristalsis, presence of free abdominal fluid, and diameter of the mesenteric lymph nodes) was done by 2 operators blind to the serological and histological findings. The pretest probability of CD was estimated to be between 5% and 10%. The percentage of agreement between US and histologic findings, the sensitivity, specificity, positive and negative likelihood ratios, and the posttest probability for positive and negative results were calculated.

RESULTS

Celiac disease was diagnosed in 12 patients (7.4%). An increased gallbladder volume, the presence of free fluid in the abdominal cavity, and enlarged mesenteric lymph nodes showed a specificity of 96%, 96%, and 97%, respectively (95% confidence intervals [CIs], 92%-99%, 93%-99%, and 95%-99%), whereas the presence of dilated small bowel loops with increased fluid content and increased peristalsis had a sensitivity of 92% and 83%, respectively (95% CIs, 76%-100% and 62%-100%). Eleven (92%) of the 12 patients with celiac disease and 35 (23%) of the 150 patients who did not have the disease had at least 1 US sign (P=.001); all of the US signs were concomitantly present in 4 patients with CD (33%) and 1 patient without CD (0.6%) (P=.001).

CONCLUSIONS

Ultrasonographic evaluation can accurately predict CD but its place in the diagnostic algorithm depends upon the probability of the disease in the considered population.

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