AU619288B2 - Creation of Inventions and Patents with Artificial Intelligence

AU619288B2 – Cardiac death probability determining device
– Google Patents

AU619288B2 – Cardiac death probability determining device
– Google Patents
Cardiac death probability determining device

Download PDF
Info

Publication number
AU619288B2

AU619288B2
AU34218/89A
AU3421889A
AU619288B2
AU 619288 B2
AU619288 B2
AU 619288B2
AU 34218/89 A
AU34218/89 A
AU 34218/89A
AU 3421889 A
AU3421889 A
AU 3421889A
AU 619288 B2
AU619288 B2
AU 619288B2
Authority
AU
Australia
Prior art keywords
patient
cardiovascular
risk
output
mortality
Prior art date
1988-03-25
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)

Ceased

Application number
AU34218/89A
Other versions

AU3421889A
(en

Inventor
Harry P. Selker
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)

New England Medical Center Hospitals Inc

Original Assignee
New England Medical Center Hospitals Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
1988-03-25
Filing date
1989-03-27
Publication date
1992-01-23

1989-03-27
Application filed by New England Medical Center Hospitals Inc
filed
Critical
New England Medical Center Hospitals Inc

1989-10-16
Publication of AU3421889A
publication
Critical
patent/AU3421889A/en

1992-01-23
Application granted
granted
Critical

1992-01-23
Publication of AU619288B2
publication
Critical
patent/AU619288B2/en

2009-03-27
Anticipated expiration
legal-status
Critical

Status
Ceased
legal-status
Critical
Current

Links

Espacenet

Global Dossier

Discuss

Classifications

A—HUMAN NECESSITIES

A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE

A61B—DIAGNOSIS; SURGERY; IDENTIFICATION

A61B5/00—Measuring for diagnostic purposes; Identification of persons

A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof

A61B5/316—Modalities, i.e. specific diagnostic methods

A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]

A61B5/346—Analysis of electrocardiograms

A61B5/349—Detecting specific parameters of the electrocardiograph cycle

G—PHYSICS

G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS

G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA

G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics

G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment

G—PHYSICS

G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS

G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR

G16Z99/00—Subject matter not provided for in other main groups of this subclass

Abstract

A device for determining the probability of death in cardiovascular patients including an electrocardiograph adapted to deliver a signal in the form of an electrical waveform containing information about the condition of the patient’s heart; a waveform recognition and measurement device adapted to analyze the waveform and generate output based on the analysis; and a computer adapted to receive the output and calculate a numerical value representing the probability based on the output. Also provided is a method for assessing cardiovascular mortality risk at a health care facility or provider using this device.

Description

OPI DATE 16/10/89 APPLN- ID S34218 89 PCp AOJP DATE 09/11/89 PCT NUMBER PCT/US89/01258 INTERNATIONAL APPLICATIO 6 BLjH 9 UA2 R PBNT COOPERATION TREATY (PCT) (51) International Patent Classification 4 (11) International Publication Number: WO 89/09022 A61B 5/04 Al (43) International Publication Date: 5 October 1989 (05.10.89) (21) Irternational Application Number: PCT/US89/01258 (81) Designated States: AT (European patent), AU, BB, BE (European patent), BF (OAPI patent), BG, BJ (OAPI (22) International Filing Date: 27 March 1989 (27.03,89) patent), BR, CF (OAPI patent), CG (OAPI patent), CH (European patent), CM (OAPI patent), DE (European patent), DK, FI, FR (European patent), GA (31) Priority Application Number: 173,220 (OAPI patent), GB (European patent), HU, IT (European patent), JP, KP, KR, LK, LU (European pa- (32) Priority Date: 25 March 1988 (25.03,88) tent), MC, MG, ML (OAPI patent), MR (OAPI patent), MW, NL (European patent), NO, RO, SD, SE (33) Priority Country: US (European patent), SN (OAPI patent), SU, TD (OAPI patent), TG (OAPI patent).
(71) Applicant: NEW ENGLAND MEDICAL CENTER HOSPITALS, INC. [US/US]; 750 Washington Street, Published Boston, MA 02111 With international search report.
(72) Inventor: SELKER, Harry, 26 Pine Tree Road, Wellesley, MA 02181 (US).
(74) Agent: CLARK, Paul, Fish Richardson, One Financial Center, Suite 2500, Boston, MA 02111-2658
(US).
(54) Title: CARDIAC DEATH PROBABILITY DETERMINING DEVICE (57) Abstract (PATIENT A device for determining the probabil.
ity of death of a cardiovascular patient in- cludes an electrocardiograph (10) adapted to ELECTROCARDIOGRAPH deliver a signal in the form of an electrical waveform C ntaining information about the WAVE FORM condition o, the patient’s heart; a waveform 12 recognition and measurement device (14) adapted to analyse the waveform and gen- FEATURE RECOGNITION 2 eraLe output based on the analysis; and a AND MEASUREMENT computer (18) adapted to receive the output “DEVICE D INPUT and calculate a numerical value representing 1DEVICE the probability based on the output. Also provided is a method for assessing cardiovascular mortality risk at a health care facili- 1- BINARY DATA ty or provider using this device.
la3′- DEATH RISK
ESTIMATOR
%CHANCE OF DEATH
PHYSICIAN
DATA STORAGE 24 PCT/US89/01258 WO 89/09022 -1- Cardiac Death Probability Determining Device–.
Background of the Invention The invention relates to an electrocardiograph device that determines a patient’s probability of death from cardiovascular disease.
In the United States, approximately 1.5 million patients per year enter emergency rooms (ERs) with symptoms suggesting acute cardiac disease, and one third of them are subsequently admitted to Coronary Care Units (CCUs). A physician must decide whether triage options other than the CCU intermediate care units, ward beds, observation units, or home care under close supervision) may be more appropriate. In addition to the patient’s condition, to the extent it can be accurately assessed, other factors to be considered include the scarcity of facilities, continually i increasing costs, and the new stricter cost containment ‘i strategies diagnostic related groups (DRGs)).
ii 20 Such decisions are difficult because they require an accurate, reliable determination of a patient’s true level of risk, and such determinations are themselves difficult to make.
Hospitals currently release mortality data the fraction of patients who die per year) that are not adjusted in accordance with differences in their respective patient populations. If such data are to be used as metrics of quality of medical care, these data should be calibrated in order to facilitate fair comparisons between hospitals having different patient populations.
In Pozen et al. (1984), New England J. Med., Vol. 310, pp. 1273-78, a hand-held calculator is programmed to provide the emergency room physician with 7 c 1 I WO 89/09022 PCr/US89/01258 2 a patient’s calculated likelihood of having acute ischemia (a type of heart attack). It uses a logistic regression function with coefficients derived by stepwise regression analysis. Its use depends on the physician’s interpretation of the patient’s electrocardiogram (ECG).
Electrocardiographs exist that imitate physician judgment by using feature recognition algorithms in conjunction with a rule based computer program to provide a quali’ative diagnosis of a patient’s condition.
Other electrocardiographs exist that use feature recognition data and feature measurements as inputs to a logistic regression formula to provide a quantitative measure of the possibility of ischemia.
The probability of ischemia is not the same as the probability of death, because there are other causes of acute and dangerous cardiac conditions. For example, a patient with new or unstable angina pectoris has approximately a 5 percent chance of dying, whereas a patient with a Killip Class IV myocardial infarction has an approximately 80 percent chance of death, This is important because it is the probability of death, not the probability of ischemia, that is critical to a Summary In general the invention features a device for determining the probability of acute episode death in cardiovascular patients that includes ai electrocardiograph adapted to deliver a signal in the form of an electrical waveform containing information about the condition of the patient’s heart, a waveform recognition and measurement device adapted to analyze the waveform and generate output based on the analysis, -3and a computer adapted to receive the output and calculate a numerical val.r representing the probability based on the output.
More specifically the invention provides a device for determining the probability of imminent death of a patient from cardiovascular disease comprising: an electrocardiograph adapted to deliver a signal in the form of an electrical waveform containing information about the condition of said patient’s heart; a waveform recognition and measurement device adapted to analyse said waveform and generate output based on said analysis; and a computer adapted to receive said output and calculate a numerical value representing said probability based on said output.
In preferred embodiments, the cardiovascular patient is primarily at risk for 15 mortality due to acute myocardial infarction, or heart failure.
Another general feature of the invention is a method for assessing cardiovascular mortality risk at a health care facility or provider that includes the steps of providing the device of the invention to the health care facility or provider, using 20 the device to calculate an individual predicted cardiovascular mortality risk of a patient at the health care facility or provider, repeating this last step for a large number of the patients, and using the individual predicted cardiovascular mortality risks to calculate a collective predicted cardiovascular mortality rate, and adjusting the collective observed cardiovascular mortality rate for the facility or provider using the i 25 collective predicted cardiovascular mortality rate to yield a summary statistic represening the overall mortality risk at the facility or provider, or the risk adjusted mortality rate at the facility or provider, More specifically the invention provides a meihod for the assessment of cardiovascular mortality risk at a health care facility or provider comprising the steps providing the device of claim 1 to said health care facility or provider; 911107,gcp!,102,34218.c,3 3a using said device to calculate an individual predicted cardiovascular mortality risk of a patient at said health care facility or provider; repeating step for a plurality of said patients, and using said individual predicted cardiovascular mortality risks to calculate a collective predicted cardiovascular mortality risk; and adjusting the collective observed cardiovascular mortality rate for said facility or provider using said collective predicted cardiovascular mortality risk to yield a summary statistic representing the overall mortality risk at said facility or provider, or the risk adjusted mortality rate at said facility or provider.
*In preferred embodiments, the individual predicted cardiovascular mortality risks conform substantially to a normal distribution, and may be characterised by a mean, called the collective predicted cardiovascular mortality rate, and a variance, and 15 wherein the adjusted collective cardiovascular mortality rate is calulated by dividing the collective observed cardiovascular mortality rate by the collective predicted cardiovascular mortality rate, and multiplying the ratio so formed by a reference mortality rate, which may be a national statistic, or may be a regional or a S n e e 911 107,cpdaLl02,34218.c,4 WO 89/09022 PCT/US89/01258 4local statistic.
The invention allows fair comparisons between hospitals having different patient populations.
The invention facilitates clinicians’ positive involvement by its ease of use, and by providing measures of risk that are sufficiently accurate, reliable, and immediate to be of value in the real-time clinical setting. The immediacy of the assessment allows the accurate capture of a patient’s true presenting mortality risk, not a risk thac was assessed after a 24-hour or longer delay, as is the current predominant practice, during which time increased severity might in fact be due to poor quality care.
The invention helps to avoid the need for inappropriate high-technology or special tests, Thus, the patient is spared the added risk and expense of such tests.
The invention maintains objective assessment regardless of whether the patient is admitted to intensive care or to a ward bed, or is not admitted at all.
The entire assessment of mortality risk-adjustment can be done without ever looking at actual medical records. The required data, and the risk-adjusted individual predicted cardiovascular mortality rate, could be obtained directly from the electrocardiograph of the invention. Thus, the speed of capture, reliability, and accuracy of the data are all improved, while the cost of data capture is significantly reduced.
Other advantages and features will become apparent from the following description of the preferred embodiment, and from the claim.
.WO 89/09022 PCT/US89/01258 5 Description of the Preferred Embodiment We first briefly describe the drawings.
Fig. 1 is a schematic diagram of the electrocardiograph of the invention.
Fig. 2 is a logistic regression formula.
Fig. 3 is a table of logistic regression variables, coefficients and values for the prediction of mortality from myocardial infarction.
Fig. 4 is a table of logistic regression variables, coefficients and values for the prediction of mortality from congestive heart failure.
Structure Referring to Fig. 1, a computer assisted electrocardiograph (ECG) (available, from Hewlett Packard Corp.) 10 monitors a patient’s cardiac activiLy. There are twelve electrodes attachcd to the patient, each monitoring a different portion of the heart. The ECG 10 sends twelve corresponding signals via a lead 12 to a feature recognition and measurement device 14 that decides whether particular critical features are present in each ECG signal presence or absence of a Q-wave), and measures the magnitude of other critical features extent of ST-segment depression). These data are digitally encoded in a signal that is received by an additional feature of ECG modified to act as a death risk estimator 18. The death risk estimator 18 is a microcomputer that has been programmed to use the information produced by the feature recognition and measurement device 14, and using a logistic regression formula as in Fig. 2, calculates the quantitative probability value that reflects the likelihood of dying.
Referring to Fig. 2, the logistic regression formula is of the form P 100 1 where WO 89/09022 PCT/US89/01258 6 y b E bix i where P is a cardiovascular patient’s probability of dying expressed as a value ranging from 0.0 to 100.0, e is the base of the natural log; b 0 is a constant; b. is a regression coefficient or weight corresponding to each clinical variable; and x i is set equal to one if the corresponding clinical variable condition is present, and zero otherwise.
Referring to Figs. 3 and 4, variables x i have been computed using stepwise regression analysis of reference population data using the SAS institute’s LOGIST logistic regression computer program. (See Walker et al., (1967), Biometrika, Vol. 54, pp. 167-79; and N.C. Cary (1983), SUGI supplement library user’s guide, SAS Institute, pp. 181-202.) The death risk estimator 18 also prompts the physician for vital signs, such as heart rate and blood pressure, and basic clinical data, such as age and patient complaints. The physician uses a patient data input device 22 to provide this information to the computer.
The ECG waveform, the values xi computed by the feature recognition and measurement device 14, and the calculated probability of death P, are stored in a database maintained by a data storage unit 24. This data storage unit may then be polled remotely using I telecommunications by a central computer for the purpose of compiling mortality statistics of a large population.
Use There are two applications of the invention: 1) as a clinical tool to be used by physicians and other health care providers in administering care to individual patients, a:,id 2) as a way to collect data on groups of patients to assess the medical care of a .WO 89/09022 PCT/US89/01258 7provider, provider group or institution, for purposes such as quality assessment, cr reimbursement.
In a clinical setting, the electrocardiograph of the invention is used to provide the physician with the patient’s risk of dying. This information is used as an aid in the triage decision making process. This information would be usel to supplement a physician’s or other clinician’s judgment, and other available diagnostic information patient’s symptoms, physical exam and lab data, including the electrocardiogram itself). For example, in an emergency j room setting, a patient with a low probability P would be admitted to a ward bed, or not hospitalized.
In addition to aiding in triage decisions, the invention may also help to determine treatment options, To use the invention for the second i application, data must first be collected, including Ieach cardiovascular patient’s risk of dying, which can be expressed as a single numerical value P. These values are combined by averaging to yield a collective predicted cardiovascular mortality rate. The collective observed cardiovascular mortality rate is calculated by dividing the total number of those who have died in a health care facility or provider by the total number of those patients who enter the facility or provider with cardiac complaints. To calculate the adjusted collective mortality rate, the ratio of the observed cardiovascular mortality rate to the predicted cardiovascular mortality rate is multiplied by a i 30 reference mortality rate, This reference mortality rate |i may be a national statistic, or one of a more local or regional nature. The adjusted collective mortality rate of a facility or health care provider an HMO) may then be compared fairly with similarly computed risk r I I c–~1 WO 89/09022 PCT/US89/01258 8 values from other facilities or health care providers with different patient populations.
Other modifications and variations will occur to those ski ;ed in the art that are nevertheless within the spirit and scope of the invention as claimed.
j

Claims (24)

1. A device for determining the probability of imminent death of a patient from cardiovascular disease comprising: an electrocardiograph adapted to deliver a signal in the form of an electrical waveform containing information about the condition of said patient’s heart; a waveform recognition and measurement device adapted to analyse said waveform and generate output based on said analysis; and a computer adapted to receive said output and calculate a numerical value representing said probability based on said output,

2. The device of claim 1, wherein said cardiovascular patient is primarily at risk for mortality due to acute myocardial infarction.

3, The device of claim 1, wherein said cardiovascular patient is primarily at risk for mortality due to congestive heart failure.

4. The device of claim 1, wherein the computer uses a regression formula to 20 compute the probability from said output.

The device of claim 4, wherein the regression formula is of the form: P=A[1-(1+e 1 Yb~bO4E,.L b, Xj where A h 1~ -4t A is a positive number; e equals the base of the natural log; i is an integer index; b, is a constant; 01 107,.gcpda.1J02,34218.,d r’ i U”P 10 *r 4 4,. 4 Sa 9 a 9 9*Cr 9 99 for i where 1-is-n, represent “linical variables, at least some of which are determined by said output; bi is regression coefficient corresponding to the i’ clinical variable; and n is a positive integer representing the number of clinical variables used in the regression equation.

6. The device of claim 4 wherein the coefficients of the regression formula are derived from a reference population using stepwise regression analysis.

7, The device of claim 1 wherein the output includes information relating to the patient’s ECG ST-segment.

8. The device of claim 7 wherein the output indicates whether the patient’s ECG ST-segment is elevated.

9. The device of claim 7 wherein the output indicates whether the patient’s ECG St-segment is depressed.

10, The device of claui 1 wherein the output includes information relating to the patient’s ECG T-waves.

11. The device of claim 10 wherein the output indicates whether the patient’s ECG T-waves are elevated.

12. The device of claim 10 wherein the output indicates whether the patient’s ECG T-waves are depressed,

13. The device of claim 1 wherein the output includes Information relating to the patient’s ECG Q-waves. Ac NA,

14, The device of claim 1 wherein the computer is adapted to also receive inputs relating to basic clinical data for the patient and to use said inputs along with said 911107,gcpdai02,34218,c,10 i -11- outputs to calculate the numerical value representing said probability.

The device of claim 14 wherein the basic clinical data inputs include the patient’s age.

16. The device of claim 1 wherein the computer is adapted to also receive inputs relating to certain of the patient’s vital signs and to use ;,aid inputs along with said outputs to calculate the numerical value representing said probability.

17. The device of claim 16 wherein the inputs relating to certain of the patient’s vital signs include the patient’s heart rate.

,18. The device of claim 16 wherein the inputs relating to certain of the patient’s vital signs include the patient’s blood pressure.

19, A method for the assessment of cardiovascular mortality risk at a health care facility or provider comprising the steps of: providing the device of claim 1 to said health care facility or provider; using said device to calculate an individual predicted cardiovascular 20 mortality risk of a patient at said health care facility or provider; repeating step for a plurality of said patients, and using said individual predicted cardiovascular mortality risks to calculate a collective predicted cardiovascular mortality risk; and adjusting the collective observed cardiovascular mortality rate for said I 25 facility or provider using said collective predicted cardiovascular mortality risk to yield a summary statistic representing the overall mortality risk at said facility or provider, or the risk adjusted mortality rate at said facility or provider.

20. The method of claim 19 veherein said individual prtdicted cardiovascular mortality risks conform substantially to a normal distribution, and may be characterised by a mean, called said collective predicted cardiovascular mortality risk, 911107,gcpd”i.102,3421 8.c,II 12- and a variance, and wherein said adjusted collective cardiovascular mortality rate is calculated by dividing said collective observed cardiovascular mortality risk by said collective predicted cardiovascular mortality risk, and multiplying the ratio so formed by a reference mortality rate.

21. The method of claim 20, wherein said reference mortality rate is a national statistic.

22. The method of claim 20, wherein said reference mortality rate is a regional or local statistic.

23. A device for determining the probability of imminent death of a patient substantially as hereinbefore described with reference to the accompanying drawings. 15

24. A method for the assessment of cardiovascular mortality risk at a health care facility substantially as hereinbefore described with reference to the accompanying drawings. o* 9 DATED this 7th day of November, 1991 NEW ENGLAND MEDICAL CENTER HOSPITALS, INC. By its Patent Attorneys DAVIES COLLISON CAVE
911107.gcpdat. 143421 x, 12

AU34218/89A
1988-03-25
1989-03-27
Cardiac death probability determining device

Ceased

AU619288B2
(en)

Applications Claiming Priority (2)

Application Number
Priority Date
Filing Date
Title

US173220

1988-03-25

US07/173,220

US4957115A
(en)

1988-03-25
1988-03-25
Device for determining the probability of death of cardiac patients

Publications (2)

Publication Number
Publication Date

AU3421889A

AU3421889A
(en)

1989-10-16

AU619288B2
true

AU619288B2
(en)

1992-01-23

Family
ID=22631031
Family Applications (1)

Application Number
Title
Priority Date
Filing Date

AU34218/89A
Ceased

AU619288B2
(en)

1988-03-25
1989-03-27
Cardiac death probability determining device

Country Status (9)

Country
Link

US
(1)

US4957115A
(en)

EP
(1)

EP0370085B1
(en)

JP
(1)

JPH02504232A
(en)

CN
(1)

CN1021793C
(en)

AT
(1)

ATE140601T1
(en)

AU
(1)

AU619288B2
(en)

CA
(1)

CA1323431C
(en)

DE
(1)

DE68926877T2
(en)

WO
(1)

WO1989009022A1
(en)

Families Citing this family (72)

* Cited by examiner, † Cited by third party

Publication number
Priority date
Publication date
Assignee
Title

US5276612A
(en)

1990-09-21
1994-01-04
New England Medical Center Hospitals, Inc.
Risk management system for use with cardiac patients

US5277188A
(en)

1991-06-26
1994-01-11
New England Medical Center Hospitals, Inc.
Clinical information reporting system

US5594637A
(en)

1993-05-26
1997-01-14
Base Ten Systems, Inc.
System and method for assessing medical risk

US5423323A
(en)

1993-08-30
1995-06-13
Rocky Mountain Research, Inc.
System for calculating compliance and cardiac hemodynamic parameters

US5724983A
(en)

1994-08-01
1998-03-10
New England Center Hospitals, Inc.
Continuous monitoring using a predictive instrument

US5501229A
(en)

1994-08-01
1996-03-26
New England Medical Center Hospital
Continuous monitoring using a predictive instrument

AU5530996A
(en)

1995-03-31
1996-10-16
Michael W. Cox
System and method of generating prognosis reports for corona ry health management

US5778345A
(en)

1996-01-16
1998-07-07
Mccartney; Michael J.
Health data processing system

US5792066A
(en)

1997-01-09
1998-08-11
Hewlett-Packard Company
Method and system for detecting acute myocardial infarction

US6061657A
(en)

1998-02-18
2000-05-09
Iameter, Incorporated
Techniques for estimating charges of delivering healthcare services that take complicating factors into account

US6175752B1
(en)

1998-04-30
2001-01-16
Therasense, Inc.
Analyte monitoring device and methods of use

US8346337B2
(en)

1998-04-30
2013-01-01
Abbott Diabetes Care Inc.
Analyte monitoring device and methods of use

US8974386B2
(en)

1998-04-30
2015-03-10
Abbott Diabetes Care Inc.
Analyte monitoring device and methods of use

US8480580B2
(en)

1998-04-30
2013-07-09
Abbott Diabetes Care Inc.
Analyte monitoring device and methods of use

US8688188B2
(en)

1998-04-30
2014-04-01
Abbott Diabetes Care Inc.
Analyte monitoring device and methods of use

US6949816B2
(en)

2003-04-21
2005-09-27
Motorola, Inc.
Semiconductor component having first surface area for electrically coupling to a semiconductor chip and second surface area for electrically coupling to a substrate, and method of manufacturing same

US8465425B2
(en)

1998-04-30
2013-06-18
Abbott Diabetes Care Inc.
Analyte monitoring device and methods of use

US9066695B2
(en)

1998-04-30
2015-06-30
Abbott Diabetes Care Inc.
Analyte monitoring device and methods of use

US6067466A
(en)

1998-11-18
2000-05-23
New England Medical Center Hospitals, Inc.
Diagnostic tool using a predictive instrument

US6454707B1
(en)

1999-03-08
2002-09-24
Samuel W. Casscells, III
Method and apparatus for predicting mortality in congestive heart failure patients

GB2352815A
(en)

1999-05-01
2001-02-07
Keith Henderson Cameron
Automatic health or care risk assessment

US6339720B1
(en)

1999-09-20
2002-01-15
Fernando Anzellini
Early warning apparatus for acute Myocardial Infarction in the first six hours of pain

US7127290B2
(en)

1999-10-01
2006-10-24
Cardiac Pacemakers, Inc.
Cardiac rhythm management systems and methods predicting congestive heart failure status

US7076437B1
(en)

1999-10-29
2006-07-11
Victor Levy
Process for consumer-directed diagnostic and health care information

DE19963246A1
(en)

1999-12-17
2001-06-21
Biotronik Mess & Therapieg

Device for detecting the circulatory effects of extrasystoles

US6665559B2
(en)

2000-10-06
2003-12-16
Ge Medical Systems Information Technologies, Inc.
Method and apparatus for perioperative assessment of cardiovascular risk

US6560471B1
(en)

2001-01-02
2003-05-06
Therasense, Inc.
Analyte monitoring device and methods of use

US6532381B2
(en)

2001-01-11
2003-03-11
Ge Medical Systems Information Technologies, Inc.
Patient monitor for determining a probability that a patient has acute cardiac ischemia

AU2002309528A1
(en)

2001-04-02
2002-10-15
Therasense, Inc.
Blood glucose tracking apparatus and methods

US20030032871A1
(en)

2001-07-18
2003-02-13
New England Medical Center Hospitals, Inc.
Adjustable coefficients to customize predictive instruments

WO2004061420A2
(en)

2002-12-31
2004-07-22
Therasense, Inc.
Continuous glucose monitoring system and methods of use

US7013176B2
(en)

2003-01-28
2006-03-14
Cardiac Pacemakers, Inc.
Method and apparatus for setting pacing parameters in cardiac resynchronization therapy

US7587287B2
(en)

2003-04-04
2009-09-08
Abbott Diabetes Care Inc.
Method and system for transferring analyte test data

US8066639B2
(en)

2003-06-10
2011-11-29
Abbott Diabetes Care Inc.
Glucose measuring device for use in personal area network

EP1718198A4
(en)

2004-02-17
2008-06-04
Therasense Inc
Method and system for providing data communication in continuous glucose monitoring and management system

US20050197544A1
(en)

2004-02-24
2005-09-08
Bernstein Steven L.
System and method for indexing emergency department crowding

US7415304B2
(en)

2004-04-15
2008-08-19
Ge Medical Systems Information Technologies, Inc.
System and method for correlating implant and non-implant data

US20050234354A1
(en)

2004-04-15
2005-10-20
Rowlandson G I
System and method for assessing a patient’s risk of sudden cardiac death

US7272435B2
(en)

2004-04-15
2007-09-18
Ge Medical Information Technologies, Inc.
System and method for sudden cardiac death prediction

US7162294B2
(en)

2004-04-15
2007-01-09
Ge Medical Systems Information Technologies, Inc.
System and method for correlating sleep apnea and sudden cardiac death

DE102004033614A1
(en)

2004-07-12
2006-02-09
Emedics Gmbh

Apparatus and method for estimating an occurrence probability of a health disorder

DE102004056092A1
(en)

2004-11-21
2006-06-01
Axel Dr. Stachon
Determining probability of death in patients, especially in intensive care, involves using a blood sample analyser to measure a range of standard values and a computer to calculate a numerical probability from the data

US8112240B2
(en)

2005-04-29
2012-02-07
Abbott Diabetes Care Inc.
Method and apparatus for providing leak detection in data monitoring and management systems

JP2008546117A
(en)

2005-06-08
2008-12-18
カーディナルヘルス３０３インコーポレイテッド

System and method for dynamic quantification of disease prognosis

US7766829B2
(en)

2005-11-04
2010-08-03
Abbott Diabetes Care Inc.
Method and system for providing basal profile modification in analyte monitoring and management systems

US7620438B2
(en)

2006-03-31
2009-11-17
Abbott Diabetes Care Inc.
Method and system for powering an electronic device

US8226891B2
(en)

2006-03-31
2012-07-24
Abbott Diabetes Care Inc.
Analyte monitoring devices and methods therefor

US20080071157A1
(en)

2006-06-07
2008-03-20
Abbott Diabetes Care, Inc.
Analyte monitoring system and method

US8930203B2
(en)

2007-02-18
2015-01-06
Abbott Diabetes Care Inc.
Multi-function analyte test device and methods therefor

US8732188B2
(en)

2007-02-18
2014-05-20
Abbott Diabetes Care Inc.
Method and system for providing contextual based medication dosage determination

US8123686B2
(en)

2007-03-01
2012-02-28
Abbott Diabetes Care Inc.
Method and apparatus for providing rolling data in communication systems

US8665091B2
(en)

2007-05-08
2014-03-04
Abbott Diabetes Care Inc.
Method and device for determining elapsed sensor life

US7928850B2
(en)

2007-05-08
2011-04-19
Abbott Diabetes Care Inc.
Analyte monitoring system and methods

US8456301B2
(en)

2007-05-08
2013-06-04
Abbott Diabetes Care Inc.
Analyte monitoring system and methods

US8461985B2
(en)

2007-05-08
2013-06-11
Abbott Diabetes Care Inc.
Analyte monitoring system and methods

US9883799B2
(en)

2008-10-16
2018-02-06
Fresenius Medical Care Holdings, Inc.
Method of identifying when a patient undergoing hemodialysis is at increased risk of death

US8103456B2
(en)

2009-01-29
2012-01-24
Abbott Diabetes Care Inc.
Method and device for early signal attenuation detection using blood glucose measurements

WO2010127050A1
(en)

2009-04-28
2010-11-04
Abbott Diabetes Care Inc.
Error detection in critical repeating data in a wireless sensor system

WO2010138856A1
(en)

2009-05-29
2010-12-02
Abbott Diabetes Care Inc.
Medical device antenna systems having external antenna configurations

WO2011026147A1
(en)

2009-08-31
2011-03-03
Abbott Diabetes Care Inc.
Analyte signal processing device and methods

WO2011026148A1
(en)

2009-08-31
2011-03-03
Abbott Diabetes Care Inc.
Analyte monitoring system and methods for managing power and noise

WO2011041469A1
(en)

2009-09-29
2011-04-07
Abbott Diabetes Care Inc.
Method and apparatus for providing notification function in analyte monitoring systems

JP6159250B2
(en)

2010-03-15
2017-07-05
シンガポールヘルスサービシーズピーティーイーリミテッド

System control method and program for predicting patient survival

EP2561457B1
(en)

2010-04-23
2018-11-14
Fresenius Medical Care Holdings, Inc.
System and method of identifying when a patient undergoing hemodialysis is at increased risk of death by a logistic regression model

US10203321B2
(en)

2010-12-02
2019-02-12
Fresenius Medical Care Holdings, Inc.
Method of identifying when a patient undergoing hemodialysis is at increased risk of death

JP6072021B2
(en)

2011-06-24
2017-02-01
コーニンクレッカフィリップスエヌヴェＫｏｎｉｎｋｌｉｊｋｅＰｈｉｌｉｐｓＮ．Ｖ．

Evaluation system and evaluation method

AU2012335830B2
(en)

2011-11-07
2017-05-04
Abbott Diabetes Care Inc.
Analyte monitoring device and methods

US9968306B2
(en)

2012-09-17
2018-05-15
Abbott Diabetes Care Inc.
Methods and apparatuses for providing adverse condition notification with enhanced wireless communication range in analyte monitoring systems

US9775533B2
(en)

2013-03-08
2017-10-03
Singapore Health Services Pte Ltd
System and method of determining a risk score for triage

EP2786704B1
(en)

2013-04-02
2016-10-05
Georg Schmidt
Device and method for assessing mortality risk of a cardiac patient

US9946843B2
(en)

2013-11-13
2018-04-17
Koninklijke Philips N.V.
Clinical decision support system based triage decision making

CN108072618A
(en)

2017-12-19
2018-05-25
中国医学科学院阜外医院
The forecasting system of mortality risk after a kind of heart infarction

Citations (3)

* Cited by examiner, † Cited by third party

Publication number
Priority date
Publication date
Assignee
Title

US4679144A
(en)

1984-08-21
1987-07-07

Q-Med, Inc.

Cardiac signal real time monitor and method of analysis

US4680708A
(en)

1984-03-20
1987-07-14

Washington University

Method and apparatus for analyzing electrocardiographic signals

AU7677787A
(en)

1983-02-14
1987-11-12

Arrhythmia Research Technology Inc.

System and method for predicting ventricular tachycardia

Family Cites Families (3)

* Cited by examiner, † Cited by third party

Publication number
Priority date
Publication date
Assignee
Title

US3608545A
(en)

1968-11-25
1971-09-28
Medical Engineering Research C
Heart rate monitor

JPS5255284A
(en)

1975-10-31
1977-05-06
Fujitsu Ltd
Controlling method for recording in automatic analyzing system of electrocardiogram

US4230125A
(en)

1979-07-09
1980-10-28
Schneider Daniel E
Method and apparatus for effecting the prospective forewarning diagnosis of sudden brain death and heart death and other brain-heart-body growth maladies such as schizophrenia and cancer and the like

1988

1988-03-25
US
US07/173,220
patent/US4957115A/en
not_active
Expired – Lifetime

1989

1989-03-23
CA
CA000594737A
patent/CA1323431C/en
not_active
Expired – Lifetime

1989-03-23
CN
CN89103187A
patent/CN1021793C/en
not_active
Expired – Fee Related

1989-03-27
DE
DE68926877T
patent/DE68926877T2/en
not_active
Expired – Fee Related

1989-03-27
WO
PCT/US1989/001258
patent/WO1989009022A1/en
active
IP Right Grant

1989-03-27
AT
AT89904665T
patent/ATE140601T1/en
not_active
IP Right Cessation

1989-03-27
EP
EP89904665A
patent/EP0370085B1/en
not_active
Expired – Lifetime

1989-03-27
AU
AU34218/89A
patent/AU619288B2/en
not_active
Ceased

1989-03-27
JP
JP1504338A
patent/JPH02504232A/en
active
Pending

Patent Citations (3)

* Cited by examiner, † Cited by third party

Publication number
Priority date
Publication date
Assignee
Title

AU7677787A
(en)

1983-02-14
1987-11-12
Arrhythmia Research Technology Inc.
System and method for predicting ventricular tachycardia

US4680708A
(en)

1984-03-20
1987-07-14
Washington University
Method and apparatus for analyzing electrocardiographic signals

US4679144A
(en)

1984-08-21
1987-07-07
Q-Med, Inc.
Cardiac signal real time monitor and method of analysis

Also Published As

Publication number
Publication date

CA1323431C
(en)

1993-10-19

US4957115A
(en)

1990-09-18

ATE140601T1
(en)

1996-08-15

CN1021793C
(en)

1993-08-18

EP0370085A4
(en)

1990-12-05

EP0370085A1
(en)

1990-05-30

DE68926877T2
(en)

1996-11-28

DE68926877D1
(en)

1996-08-29

WO1989009022A1
(en)

1989-10-05

AU3421889A
(en)

1989-10-16

CN1038583A
(en)

1990-01-10

JPH02504232A
(en)

1990-12-06

EP0370085B1
(en)

1996-07-24

Contact information