An anthropometric analysis of indices of severity in the unilateral cleft lip.
The aim of this study was to analyze the relationships among three key anthropometric parameters in the unilateral cleft lip to determine the correlations, if any, among these indices of severity. Using a standardized anthropometric documentation protocol, preoperative measurements of 125 unilateral cleft lips (103 complete and 22 incomplete) were performed under general anesthesia by a single surgeon at the time of primary lip repair at the age of 3 months. The following key measurements were analyzed statistically: (1) the philtral height difference (PHD) between the cleft and noncleft sides, (2) the nasal floor width difference (NFWD) between the cleft and noncleft sides, and (3) the cleft width (CW). The mean values of all three indices were greater in the complete group versus the incomplete group. These differences were statistically significant. Linear relationships were obtained between NFWD and GAP, between PHD and GAP, and between PHD and NFWD in the complete group. In contrast, the relationships between PHD and GAP, and between PHD and NFWD were nonlinear in the incomplete group. These findings suggest that there was a strong correlation between the transverse and vertical tissue deficiencies in the complete cleft lip. In incomplete clefts, however, this correlation did not exist. In other words, the incomplete cleft lip can be associated with a severely short philtrum even in the presence of a relatively mild transverse tissue deficit. Therefore, it is not necessarily easier to repair an incomplete cleft lip in terms of the correction of the vertical tissue deficiency.
Yeow
Vincent K L
VK
Department of Plastic Surgery, Singapore General Hospital, Singapore 0316. gplykl@sgh.gov.sg
Huang
Martin H S
MH
Lee
S T
ST
Fook Chong
Stephanie M C
SM
D002508:Cephalometry; D002971:Cleft Lip / Q000473:pathology*; D006801:Humans; D007223:Infant; D008046:Lip / Q000473:pathology; D009666:Nose / Q000473:pathology; D012720:Severity of Illness Index; D018709:Statistics, Nonparametric