PURPOSE: We examined the prevalence of known facial features of Marfan syndrome (MFS)-dolicocephaly, malar hypoplasia, enophthalmos, retrognathia, and down-slanting palpebral fissures-and the diagnostic utility (sensitivity, specificity, accuracy, predictive values, and likelihood ratios) of using them for screening and diagnosis. METHODS: Frontal and lateral photographs of 76 subjects with MFS (average age 18.3 years) and of 76 age- and gender-matched controls were obtained, randomized, and compiled into an online survey. Three physicians experienced with MFS rated each photograph for the presence of each feature and indicated whether each photograph triggered a suspicion for MFS. Eight non-expert orthopaedic surgeons reviewed a subset of those photographs and indicated if each triggered a suspicion for MFS. Half of the non-experts then received a brief diagnosis instructional sheet, and all non-experts were retested. The results were compared using Chi-square tests and t-tests with a significance level of P < 0.05. RESULTS: Using facial features alone, the accuracy of experienced physicians in identifying individuals with MFS was 73%. Facial features had a 54% sensitivity, a 91% specificity, an 86% positive predictive value (PPV), a 67% negative predictive value (NPV), a 6.9% positive likelihood ratio (PLR), and a 50% negative likelihood ratio (NLR) for MFS. There was no significant difference in the diagnostic accuracy between non-experts receiving and not receiving instructions. CONCLUSIONS: Facial features are more specific than sensitive for MFS. Therefore, the recognition of facial features of MFS can be used as an initial screening tool, but facial features do not have a high sensitivity for MFS.
PURPOSE: We examined the prevalence of known facial features of Marfan syndrome (MFS)-dolicocephaly, malar hypoplasia, enophthalmos, retrognathia, and down-slanting palpebral fissures-and the diagnostic utility (sensitivity, specificity, accuracy, predictive values, and likelihood ratios) of using them for screening and diagnosis. METHODS: Frontal and lateral photographs of 76 subjects with MFS (average age 18.3 years) and of 76 age- and gender-matched controls were obtained, randomized, and compiled into an online survey. Three physicians experienced with MFS rated each photograph for the presence of each feature and indicated whether each photograph triggered a suspicion for MFS. Eight non-expert orthopaedic surgeons reviewed a subset of those photographs and indicated if each triggered a suspicion for MFS. Half of the non-experts then received a brief diagnosis instructional sheet, and all non-experts were retested. The results were compared using Chi-square tests and t-tests with a significance level of P < 0.05. RESULTS: Using facial features alone, the accuracy of experienced physicians in identifying individuals with MFS was 73%. Facial features had a 54% sensitivity, a 91% specificity, an 86% positive predictive value (PPV), a 67% negative predictive value (NPV), a 6.9% positive likelihood ratio (PLR), and a 50% negative likelihood ratio (NLR) for MFS. There was no significant difference in the diagnostic accuracy between non-experts receiving and not receiving instructions. CONCLUSIONS: Facial features are more specific than sensitive for MFS. Therefore, the recognition of facial features of MFS can be used as an initial screening tool, but facial features do not have a high sensitivity for MFS.
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