Towards an Algorithm-Based Tailored Treatment of Acute Neonatal Hyperammonemia.
Sunny ElootJonathan De RudderPatrick VerlooEvelyn DhontRaes AnnWim Van BiesenSnauwaert EvelienPublished in: Toxins (2021)
Acute neonatal hyperammonemia is associated with poor neurological outcomes and high mortality. We developed, based on kinetic modeling, a user-friendly and widely applicable algorithm to tailor the treatment of acute neonatal hyperammonemia. A single compartmental model was calibrated assuming a distribution volume equal to the patient's total body water (V), as calculated using Wells' formula, and dialyzer clearance as derived from the measured ammonia time-concentration curves during 11 dialysis sessions in four patients (3.2 ± 0.4 kg). Based on these kinetic simulations, dialysis protocols could be derived for clinical use with different body weights, start concentrations, dialysis machines/dialyzers and dialysis settings (e.g., blood flow QB). By a single measurement of ammonia concentration at the dialyzer inlet and outlet, dialyzer clearance (K) can be calculated as K = QB∙[(Cinlet - Coutlet)/Cinlet]. The time (T) needed to decrease the ammonia concentration from a predialysis start concentration Cstart to a desired target concentration Ctarget is then equal to T = (-V/K)∙LN(Ctarget/Cstart). By implementing these formulae in a simple spreadsheet, medical staff can draw an institution-specific flowchart for patient-tailored treatment of hyperammonemia.
Keyphrases
- end stage renal disease
- chronic kidney disease
- peritoneal dialysis
- liver failure
- blood flow
- machine learning
- healthcare
- respiratory failure
- case report
- room temperature
- newly diagnosed
- deep learning
- type diabetes
- skeletal muscle
- aortic dissection
- metabolic syndrome
- quality improvement
- human milk
- preterm infants
- brain injury
- anaerobic digestion
- cardiovascular events
- patient reported