Method and device to monitor patients with kidney disease

• US 10,506,933 B2
• Filed: 12/11/2017
• Issued: 12/17/2019
• Est. Priority Date: 04/29/2011
• Status: Active Grant

• Current Assignee: Mozarc Medical US LLC
• Original Assignee: Medtronic Incorporated (Medtronic Plc)
• Inventors: Soykan, Orhan, Manda, VenKatesh R., Gerber, Martin T., Hobot, Christopher M., Ruetz, Linda L., Schu, Carl
• Primary Examiner(s): Bass, Dirk R
• Application Number:
  US15/837,388
• Publication Number:
  US 20180098704A1
• Time in Patent Office: 736 Days
• Field of Search: 600483, 600515, 600546
• CPC Class Codes: A61B 2560/0223 of calibration, e.g. protocols for calibrating sensors
• CPC Class Codes: A61B 5/0031 Implanted circuitry
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/0537 Measuring body composition by impedance, e.g. tissue hydration or fat content
• CPC Class Codes: A61B 5/14503 invasive, e.g. introduced into the body by a catheter or needle or using implanted sensors A61B5/1459, A61B5/1464, A61B5/1473, A61B5/1482, A61B5/14865 take precedence
• CPC Class Codes: A61B 5/14539 for measuring pH
• CPC Class Codes: A61B 5/14546 for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• CPC Class Codes: A61B 5/201 Assessing renal or kidney functions
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/389 Electromyography [EMG]
• CPC Class Codes: A61B 5/4836 Diagnosis combined with treatment in closed-loop systems or methods A61B5/0036 takes precedence
• CPC Class Codes: A61B 5/6866 Extracorporeal blood circuits, e.g. dialysis circuits
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61M 1/14 Dialysis systems; Artificial kidneys; Blood oxygenators semi-permeable membranes characterised by the material, manufacturing processes therefor B01D71/00 ; Reciprocating systems for treatment of body fluids, e.g. single needle systems for hemofiltration or pheresis
• CPC Class Codes: A61M 1/1601 Control or regulation
• CPC Class Codes: A61M 1/3609 Physical characteristics of the blood, e.g. haematocrit, urea
• CPC Class Codes: A61M 2205/18 with alarm
• CPC Class Codes: A61M 2205/3523 using telemetric means
• CPC Class Codes: A61M 2205/52 with memories providing a history of measured variating parameters of apparatus or patient
• CPC Class Codes: A61M 2205/70 with testing or calibration facilities
• CPC Class Codes: A61M 2230/20 : Blood composition characteristics
• CPC Class Codes: A61M 2230/207 : hematocrit
• CPC Class Codes: A61M 2230/208 : pH-value
• CPC Class Codes: A61M 2230/30 : Blood pressure A61M2230/04 takes precedence
• CPC Class Codes: B01D 2321/12 : Use of permeate
• CPC Class Codes: B01D 2321/40 : Automatic control of cleaning processes
• CPC Class Codes: B01D 61/243 : Dialysis
• CPC Class Codes: B01D 61/32 : Controlling or regulating
• CPC Class Codes: B01D 65/02 : Membrane cleaning or sterilisation ; Membrane regeneration
• CPC Class Codes: G16H 50/30 : for calculating health indices; for individual health risk assessment

Abstract

A medical monitoring device for monitoring electrical signals from the body of a subject is described. The medical monitoring device monitors electrical signals originating from a cardiac cycle of the subject and associates each cardiac cycle with a time index. The medical monitoring device applies a forward computational procedure to generate a risk score indicative of hyperkalemia, hypokalemia or arrhythmia of the subject. The medical monitoring device can adjust the forward computational procedure based upon clinical data obtained from the subject.

Claims

1. A method performed by a processor comprising:

connecting at least one electrocardiogram sensor to a subject to receive one or more electrocardiogram features;

applying an electrocardiogram algorithm to the one or more electrocardiogram features to obtain an indicator for serum potassium concentration of the subject, wherein the electrocardiogram algorithm includes one or more of the following operational rules;

i) the output on the serum potassium concentration being a function of the R-wave amplitude;

ii) the output on the serum potassium concentration being a function of the T-wave amplitude;

iii) the output on the serum potassium concentration being a function of the T/R ratio; and

iv) the output on the serum potassium concentration being a function of the T-wave flatness;

applying a forward computational procedure to the output to generate a risk score; and

issuing an alert indicating a condition of hyperkalemia, hypokalemia or arrhythmia of the subject based on the risk score;

wherein the electrocardiogram sensor includes one or more electrocardiogram electrodes for receiving one or more electrocardiogram features from the subject, the one or more electrocardiogram features including T-wave amplitude, R-wave amplitude, T-slope, ratio of Twave amplitude to R-wave amplitude (T/R ratio), and T-wave flatness; and

wherein the processor applies further comprising an electrocardiogram algorithm for producing the output on the serum potassium concentration in the subject based on the value of the one or more electrocardiogram features, wherein the electrocardiogram algorithm is programmed into a computer readable medium and includes one or more of the following operational rules;

i) the output on the serum potassium concentration being a function of the R-wave amplitude;

ii) the output on the serum potassium concentration being a function of the Twave amplitude;

iii) the output on the serum potassium concentration being a function of the T/R ratio; and

iv) the output on the serum potassium concentration being a function of the T-wave flatness.

2. The method of claim 1, wherein the processor adjusts the forward computational procedure for future use according to an error signal based on the risk score and actual patient outcome.

3. The method of claim 2, wherein the processor applies the same forward computational procedure in response to the error signal being zero.

4. The method of claim 1, wherein the processor produces an output of the serum potassium concentration based on a value of the one or more electrocardiogram features.