Quantifying Esophageal Hydrogen Ion Exposure using a novel pH-impedance metric improves prediction of PPI response compared with conventional acid exposure time in GERD
Mentore Ribolsi, Lorenzo Marchetti, Chiara Catamo, Laura Galdi, Marco Distefano, Michele CicalaBackground:
Acid exposure time (AET) is the reference metric quantifying esophageal acid burden, yet patients with pathological AET may fail to respond to PPI therapy. Given the logarithmic nature of pH, AET does not account for the exponential increase in hydrogen ion (H + ) concentration at lower pH values.
Aim:
To quantify acid burden using total integrated acidity exposure (TIAE), a dose-based metric integrating H + load over time, and to assess whether TIAE improves prediction of PPI response compared with conventional AET.
Methods:
Impedance-pH data were retrospectively evaluated. TIAE was calculated by integrating H + concentration (10 -pH ) at 1-second resolution across all acid reflux episodes. Diagnostic performance for PPI response was assessed using ROC analysis, multivariable logistic regression and decision curve analysis (DCA).
Results:
Among 174 patients (97 PPI responders, 77 non-responders), responders exhibited higher TIAE than non-responders and controls (p<0.0001). TIAE showed superior discrimination for PPI response compared with AET (AUC 0.78 vs 0.64). In multivariable models, TIAE independently predicted response both as a dichotomized and continuous variable, whereas continuous AET was not independently associated. TIAE correlated more strongly with MNBI than AET (ρ=-0.49 vs -0.26). DCA demonstrated greater net clinical benefit for models incorporating TIAE across clinically relevant threshold probabilities. In patients with inconclusive AET (4-6%), TIAE accurately segregated responders from non-responders. Very low pH (pH<2) greatly affected TIAE value and showed the strongest association with treatment response.
Conclusions:
Quantifying H + load provides a physiologically grounded assessment of esophageal acid burden and improves prediction of PPI response.