The peculiarity of the proposed model is the possibility it offers to perform a real-time simulation enabling quantitative appraisal of hematochemical quantities whose direct measurement is prohibitive. These will be beneficial to dialysis therapy planning, reducing intradialysis complications and improving patients' quality of life.
Intra-Dialysis Hypotension (IDH) is one of the main hemodialysis related complications, occurring in 25-30% of the sessions. The factors involved in the onset of hypotension in patients undergoing dialysis are due both to clinical conditions (e.g. presence of vascular or cardiac diseases, neuropathology, anemia) and treatment settings such as temperature of the dialysate, sodium concentration, buffer composition, ultrafiltration rate, etc. The patient's peculiar reaction to the treatment implies difficulties in preventing IDH episodes. This work explores the possibility to use a multivariate analysis of clinical data to quantify the risk to develop IDH at the beginning of each session. The study is framed in the DialysIS project (Dialysis therapy between Italy and Switzerland) funded by INTERREG-Italy-Switzerland and Co-funded by European Union. Data referring to a total of 516 sessions performed on 70 adult patients undergoing dialysis treatment (50 patients enrolled at A. Manzoni Hospital Lecco, Italy and 20 patients at Regional Hospital of Lugano, Switzerland) were collected. Clinical prescriptions, hydration status, dialysis machine data and hematochemical data were recorded and stored in a unique flexible structured MySQL® database. A statistical analysis was performed to find the potential risk factor related to IDH onset. IDH episodes were automatically detected during the monitored sessions, according to the literature criteria. Patients suffering from IDH in 2 or more sessions were classified as Hypotension Prone (HP), the others as Hypotension Resistant (HR). Initial values of potassium concentration [K+], systolic (SBP) and diastolic (DBP) blood pressure, and weight gain (ΔW) from the end of the previous treatment result to be statistically different between the HP and HR groups. A new index, J, was defined as a weighted patient-specific combination of these parameters and calculated for each session of each patient. The weight of the index coefficients can be dynamically adjourned based on the longitudinal analysis of [K+], SBP, DBP, and ΔW.
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