Is analysis of lower esophageal sphincter vector volumes of value in diagnosing gastroesophageal reflux disease?
OBJECTIVE
With successful surgical treatment of gastroesophageal reflux disease (GERD), there is interest in understanding the anti-reflux barrier and its mechanisms of failure. To date, the potential use of vector volumes to predict the DeMeester score has not been adequately explored.


METHODS
627 patients in the referral database received esophageal manometry and ambulatory 24-hour pH monitoring. Study data included LES resting pressure (LESP), overall LES length (OL) and abdominal length (AL), total vector volume (TVV) and intrabdominal vector volume (IVV).


RESULTS
In cases where LESP, TVV or IVV were all below normal, there was an 81.4 % probability of a positive DeMeester score. In cases where all three were normal, there was an 86.9 % probability that the DeMeester score would be negative. Receiver-operating characteristics (ROC) for LESP, TVV and IVV were nearly identical and indicated no useful cut-off values. Logistic regression demonstrated that LESP and IVV had the strongest association with a positive DeMeester score; however, the regression formula was only 76.1 % accurate.


CONCLUSIONS
While the indices based on TVV, IVV and LESP are more sensitive and specific, respectively, than any single measurement, the measurement of vector volumes does not add significantly to the diagnosis of GERD.
Marsh
Robert E
RE
Department of Surgery, Creighton University School of Medicine, Omaha, NE 68131, USA.
Perdue
Christopher L
CL
Awad
Ziad T
ZT
Watson
Patrice
P
Selima
Mohamed
M
Davis
Richard E
RE
Filipi
Charles J
CJ
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D002675:Child, Preschool; D004943:Esophagogastric Junction / Q000473:pathology / Q000502:physiology*; D005260:Female; D005764:Gastroesophageal Reflux / Q000175:diagnosis*; D006801:Humans; D006863:Hydrogen-Ion Concentration; D008297:Male; D008365:Manometry; D008875:Middle Aged; D012372:ROC Curve; D012044:Regression Analysis