The Utility of Novel pH-Impedance Monitoring Parameters (PSPW Index and MNBI) in Pediatric Gastroesophageal Reflux Disease Phenotypes-A Systematic Review.
Radu Samuel PopDorin FarcăuLăcrămioara Eliza ChiperiDan Lucian DumitrașcuPublished in: Journal of clinical medicine (2024)
Background/Objectives : Researchers have proposed two novel impedance-pH parameters, mean nocturnal baseline impedance (MNBI) and the post-reflux swallow-induced peristaltic wave (PSPW) index, to enhance the diagnosis of gastroesophageal reflux disease (GERD) and enable better predictions of the effectiveness of anti-reflux therapies. This systematic review aims to synthesize the available evidence on the utility of the PSPW index and MNBI as diagnostic tools for pediatric GERD. Methods : A systematic search of studies reporting PSPW index and MNBI values in patients with GERD was performed in PubMed, Embase, Clarivate, Scopus, Cochrane and Google Scholar databases from their beginning until April 2024. The following terms were used: GERD , children , pediatric , PSPW and MNBI . Results : Eight studies were included, describing 479 patients ranging from 2 months to 17 years old over an 8-year period in 12 pediatric centers. Four studies demonstrated that children with pathological acid exposure have a significantly lower MNBI, with a good discriminatory ability to diagnose GERD. The PSPW index showed lower values in patients with reflux hypersensitivity (RH) compared to those with functional heartburn (FH). Conclusions : Patients with pathological acid exposure tend to exhibit lower MNBI and PSPW index values compared to those with normal acid exposure. MNBI and the PSPW index show promise as diagnostic tools in distinguishing between different GERD phenotypes. Further research is needed to establish standardized diagnostic criteria and optimize the clinical applicability in GERD diagnosis and management.
Keyphrases
- gastroesophageal reflux disease
- systematic review
- young adults
- randomized controlled trial
- end stage renal disease
- chronic kidney disease
- emergency department
- machine learning
- obstructive sleep apnea
- ejection fraction
- blood pressure
- computed tomography
- oxidative stress
- physical activity
- magnetic resonance
- drug induced
- deep learning
- adverse drug
- sleep apnea