WO2008036649A2 - Système et procédé permettant de diagnostiquer une pathologie chez un patient - Google Patents
Système et procédé permettant de diagnostiquer une pathologie chez un patient Download PDFInfo
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- WO2008036649A2 WO2008036649A2 PCT/US2007/078754 US2007078754W WO2008036649A2 WO 2008036649 A2 WO2008036649 A2 WO 2008036649A2 US 2007078754 W US2007078754 W US 2007078754W WO 2008036649 A2 WO2008036649 A2 WO 2008036649A2
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- patient
- data
- waveform
- condition
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Classifications
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B7/00—Instruments for auscultation
- A61B7/02—Stethoscopes
- A61B7/04—Electric stethoscopes
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4821—Determining level or depth of anaesthesia
Definitions
- the disclosed subject matter relates to a technique for diagnosing a condition of a patient.
- Various techniques for evaluating the status of a patient can be performed based on vital signs data. For example, the evaluation of patient sound information, such as heart sounds and their associated waveforms, has always been an important part of medical diagnosis. However, professionals in the medical field have not utilized this information as a basic patient monitoring technique in lieu of technically advanced pulse and blood pressure monitors, which are now the standard of care in most ORs, Recovery rooms, or ICUs.
- the disclosed subject matter samples data relating to physical characteristics of the patient, deriving parameters of a waveform from the data, comparing the parameters of the waveform with reference data, obtains the condition of the patient based upon the comparison, and provides an output relating to the condition of the patient.
- the sampled data relating to the physical characteristics of the patient can include heart sounds. That data can be sampled at distinct time intervals or distinct milestones. The distinct milestones can include a resting state, a first dosage state, a high dosage state, or an anesthetized state.
- the reference data can include a database of the physical characteristics of a population of patients, prior condition of the patient, and prior waveform of the patient.
- Identifying parameters associated with the waveform can include identifying the heart rate of the patient, the amplitude of the waveform, the peak-to- peak spacing of the waveform, and identifying individual heart sounds, such as the Sl, S2, S3, and S4 sounds.
- the disclosed subject matter also provides a system for diagnosing a condition of a patient.
- the system includes an apparatus for sampling data relating to physical characteristics of the patient, a processor arranged and configured to derive parameters of a waveform from the data, to compare the parameters of the waveform with reference data, and to obtain a condition of the patient based upon the comparison, and an output device for providing the condition of the patient.
- FIG. 1 is a diagram illustrating a method implemented in accordance with some embodiments of the disclosed subject matter
- FIG. 2 shows the original files for one patient given resting, induced, and then high dose sevoforane;
- FIG. 3 is the tracings of the patient in FIG. 1 once filtered for artifacts and amplified.
- FIG. 4 is a block diagram of system in accordance with some embodiments of the disclosed subject matter. While the disclosed subject matter will now be described in detail with reference to the Figures, it is done so in connection with the illustrative embodiments.
- Systems and methods of diagnosing a condition of a patient are provided.
- the disclosed subject matter samples data relating to physical characteristics of the patient, derives parameters of a waveform from the data, comparing the parameters of the waveform with reference data, obtains the condition of the patient based upon the comparison, and provides an output relating to the condition of the patient.
- FIG. 1 is a diagram illustrating a method implemented in accordance with some embodiments of the disclosed subject matter.
- Data relating to physical characteristics of the patient are sampled at step 101.
- the sampled data relating to the physical characteristics of the patient can include heart sounds. That data can be sampled at distinct time intervals or distinct milestones.
- the distinct milestones can include a resting state, a first dosage state, a high dosage state, or an anesthetized state.
- the parameters of a waveform from the data can be derived at step 102. Identifying parameters associated with the waveform can include identifying the heart rate of the patient, the amplitude of the waveform, the peak-to-peak spacing of the waveform, and identifying individual heart sounds, such as the Sl , S2, S3, and S4 sounds.
- the parameters of the waveform can be compared with reference data at step 103.
- the reference data can include a database of the physical characteristics of a population of patients, prior condition of the patient, and prior waveform of the patient.
- the condition of the patient based upon the comparison can be obtained at step 104.
- the condition of the patient can include a normal state, a bad state, or an impossible state.
- the condition of the patient can also include changes in the
- NY02:596797.1 3 state of the patent such as an improving state or a worsening state.
- the condition of the patient can include states based on time, such as a previous state, an actual state, and an expected state.
- An output relating to the condition of the patient can be provided at step 105.
- the output can be in the form of a graphic or text indicating the condition of the patient. Additionally, the output can be a sound indicating that the condition of the patient is worsening or is in a bad or impossible state.
- the waveform data is heart sounds.
- Sl or First Heart Sound is made by the closing of the mitral and tricuspid valves.
- S2 or Second Heart Sound is made by the closing of the aortic and pulmonary valves.
- S3 or Third heart Sound is made by rapid ventricular filling when mitral and tricuspid open. This sound is typically considered normal in children and adolescents and can be heard at the Apex.
- S4 or Fourth Heart Sound is made by the Rapid ventricular filling that occurs in atrial systole, and is heard in late diastole. An S4 can clearly be heard at Erb's point. This sound is normally found in very elderly adults but it can also be heard in young children.
- S3 is a normal variant, while the S4 is not.
- S3 is considered abnormal in the young adults.
- the S4 is a normal variant after exercise and heart stress.
- Erb's point is considered a favorable location to find a right heart S4
- the apex of the heart is the location for the left S4.
- the left heart S4 is considered the normal variant, while the right is not.
- causes of a right S4 include, e.g., an augmented atrial contraction which increases filling during low ventricular compliance states, exercise and heightened cardiac output, and during positive pressure ventilation with a concordant increase in right ventricular afterload.
- NY02:596797.1 4 recorded before and after induction, and in the intensive care unit (ICU) post surgery.
- ICU intensive care unit
- Erb ' s point appeared to be useful to judge heart sounds and changes, followed by the apex and then the right sternum boarder. Similarities and differences between pediatric and adult patients before and after they were anesthetized were studied. While there were differences in anesthetic technique, inhalation versus intravenous, the decreases in after-load and concurrent increase in cardiac output was found to reveal an S3, S4, augmentation or diminution in the recorded heart sounds. It was also possible the institution of positive pressure ventilation may induce auditory changes that could be captured by our recordings. Similarities and differences in adult and pediatric patients given a high dose of anesthesia were also studied.
- the heart sounds were recorded with the stethoscope. After the sounds were recorded, they were transferred to a Windows computer via a USB infrared adapter. The Littmann Sound Analysis Software was used to determine if the recording was acceptable. If the recording was acceptable, it would be saved in the database.
- Wave Pad a wave evaluation application
- the application can amplify the sounds, eliminate background noise, etc. until a desired consistency was achieved.
- the original file was used in the evaluation of intensity, amplitude and time and inter- patient correlation.
- FIG. 2 shows the original files for one patient given resting 22, induced 24, and then high dose 26 sevoforane.
- the heartbeat of a child is heard more clearly when recorded than for an adult.
- the difference in the thickness of the chest wall in children and adults is a possible explanation.
- Pediatric patients and adults have a similar pattern of heart sounds when induced with anesthesia. This appears true for inhalation inductions, propofol, and versed fentanyl inductions.
- the appearance of the S4 occurred whether or not the patient was placed on positive pressure ventilation or not.
- FIG. 3 is the tracings of the same patient once filtered for artifacts and amplified. While the pattern of heart sounds that occur during induction is still prominent, the clarity for clinical testing as stated above with attendings and residents can easily be done.
- a computer program is used to execute a digital algorithm that detects first and second heart sounds, defines the systole and diastole, and characterizes the systolic murmur.
- Heart sounds were recorded in 300 children with a cardiac murmur, using an electronic stethoscope.
- a digital algorithm was developed for detection of first and second heart sounds. R-waves and T-waves in the electrocardiography were used as references for detection. The sound signal analysis was carried out using the short-time Fourier transform.
- the first heart sound detection rate, with reference to the R- wave was 100% within 0.05-0.2R-R interval.
- the second heart sound detection rate between the end of the T- wave and the 0.6R-R interval was 97%.
- the systolic and diastolic phases of the cardiac cycle could be identified. Because of the overlap between heart sounds and murmur a systolic segment between the first and second heart sounds (20-70%) was selected for murmur analysis. The maximum intensity of the systolic murmur, its average frequency, and the mean spectral power were quantified. The frequency at the point with the highest sound intensity in the spectrum and its time from the first heart sound, the highest frequency, and frequency
- FIG. 4 is a block diagram of system in accordance with some embodiments of the disclosed subject matter.
- the system includes an apparatus for sampling data relating to physical characteristics of the patient, a processor arranged and configured to derive parameters of a waveform from the data, to compare the parameters of the waveform with reference data, and to obtain a condition of the patient based upon the comparison, and an output device for providing the condition of the patient.
- the system diagnoses the condition of the patient based on the heart sounds of the patient.
- a stethoscope at 403 can be applied to the chest of a patient at 402 such that sounds from the heart at 401 of the patient can be sampled.
- the apparatus for sampling data relating to physical characteristics of the patient can include a stethoscope.
- An example of a stethoscope includes the Littmann 4100 Series Electronic stethoscope.
- the digitizer at 404 which can be connected to the stethoscope at 403, can covert the signal received by the stethoscope at 403 into a digital signal.
- the digitizer at 404 can be connected to a processor at 405 and the digital signal can be sent to the processor at 405.
- the processor at 405 is arranged and configured to derive parameters of a waveform from the digital signal, to compare the parameters of the waveform with reference data, and to obtain a condition of the patient based upon the comparison.
- the processor at 405 can be implemented as a computer microchip, a stand alone computer or collection of networks computing or any device suitable for processing.
- the disclosed subject matter can be implemented in Perl, C, or other suitable programming language.
- Software such as the Littmann Sound Analysis Software can be used to record the heart sounds, and Wave Pad, another application, can be used to edit and evaluate the heart sounds.
- the processor 405 may be distributed over a network in some embodiments.
- the processor may include a client and remote server on a wired or wireless network.
- the database at 406 is provided, which may be accessed by the processor at 405.
- the database can store data relating to the physical characteristics
- the data stored in the database at 406 can be used to compare the parameters of the waveform of the patient.
- An inference monitor as described in U.S. Application No. 10/795,724, may be used to identify and/or classify abnormal patients by scanning a patient's records for relevant data, such as heart sounds data, and applying one or more inference rules.
- the inference monitor may also scan data relating to a population of patients.
- the inference monitor identifies and/or classifies abnormal events that occurred at or about certain milestones in the therapeutic treatment.
- a "milestone” or “milestone event” refers herein to a distinguishable event in the course of a patient ' s treatment. It is understood that various types of milestones may be either predefined or user-defined, based on the type of treatment being offered. For instance, with regard to heart sounds, the milestones may be critical periods during surgery, such as resting (prior to anesthesia), anesthetization (at a first level of anesthesia) or highly anesthetized (at a second, higher level of anesthesia), etc.
- the inference engine may apply the inference rule or rules to patient data that have been collected within a predefined window, such as a 20-minute window, before and/or after any one or more of the milestones.
- the inference engine may also identify abnormal events in light of milestones, such as demographic data (e.g., the patient ' s age, gender, weight, etc.) and clinical data (e.g., the patient's vital signs, relevant allergic reactions, medications, prosthetics, preexisting medical conditions, relevant diagnoses, type of procedure suggested), and in light of the data, such as the time interval of the events (e.g., between start and stop times) and the drugs that were administered during the operation.
- demographic data e.g., the patient 's age, gender, weight, etc.
- clinical data e.g., the patient's vital signs, relevant allergic reactions, medications, prosthetics, preexisting medical conditions, relevant diagnoses, type of procedure suggested
- the time interval of the events e.g., between start and stop times
- Inferences identifying events indicative of the severity of a patient's condition include, without limitation, duration of treatment, the type of procedure, demographics, etc.
- Various techniques may be used to identify abnormal events from a patient's data.
- the system applies one or more inference rules that identify abnormal events based on a scoring system for inferring a patient's clinical status based on abnormal event thresholds for the scores.
- the scoring system includes a plurality of independent scoring schemes, which include at least one scoring scheme applicable prior to a milestone, and at least one scoring scheme applicable after the milestone.
- a single threshold, common to the plurality of scoring schemes, may be applied to infer the patient's clinical status; a plurality of thresholds, corresponding to each of the plurality of schemes, may also be applied.
- a scoring system may comprise a first scoring scheme for identifying from patient data at least one abnormal event occurring prior to at least one milestone event, and a second scoring scheme for identifying from patient data at least one abnormal event occurring after the at least one milestone event.
- a scoring system in accordance with some embodiment of the present invention is provided in U.S. Application No. 10/795,724, incorporated by reference hereinabove.
- the inference engine identifies abnormal events (i.e., the severity of the patient's condition) based, at least in part, on the milestone of the patient's treatment, the occurrence of heart sounds, the amplitude of the waveform, the peak-to-peak spacing, etc.
- the inference engine may take into account typical wave characteristics for the particular patient, and detect an improvement or worsening of their condition.
- the inference engine considers the wave characteristics for other patients in the patient pool having similar demographic characteristics, e.g., age, etc., as well as considerations relative to a milestone event, e.g., waveform characteristics just prior to a milestone event, just following a milestone event, etc.
- An output device can be used for providing the condition of the patient.
- Examples of output devices include a printer at 407 or a display at 408 for providing, e.g., a visual output of the patient's condition, or a speaker at 409 for providing, e.g., an audible alert.
- output may be incorporated into database 406, for providing additional data for the particular patient or the patient pool. The inference monitor can draw upon this data to provide improved information over time.
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- Heart & Thoracic Surgery (AREA)
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Abstract
La présente invention concerne des systèmes et des procédés permettant de diagnostiquer une pathologie chez un patient. L'invention comprend les opérations suivantes : accès à des données relatives à des caractéristiques physiques du patient; déduction de paramètres d'une représentation oscillographique à partir des données; comparaison des paramètres de la représentation oscillographique avec des données de référence; obtention de la pathologie du patient selon la comparaison; et mise à disposition de données de sortie relatives à la pathologie du patient.
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US84558506P | 2006-09-18 | 2006-09-18 | |
US60/845,585 | 2006-09-18 |
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WO2008036649A2 true WO2008036649A2 (fr) | 2008-03-27 |
WO2008036649A3 WO2008036649A3 (fr) | 2008-11-27 |
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Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8870791B2 (en) | 2006-03-23 | 2014-10-28 | Michael E. Sabatino | Apparatus for acquiring, processing and transmitting physiological sounds |
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US5687738A (en) * | 1995-07-03 | 1997-11-18 | The Regents Of The University Of Colorado | Apparatus and methods for analyzing heart sounds |
US6643548B1 (en) * | 2000-04-06 | 2003-11-04 | Pacesetter, Inc. | Implantable cardiac stimulation device for monitoring heart sounds to detect progression and regression of heart disease and method thereof |
US20040260188A1 (en) * | 2003-06-17 | 2004-12-23 | The General Hospital Corporation | Automated auscultation system |
US20050090755A1 (en) * | 2003-10-22 | 2005-04-28 | Guion Marie A. | Analysis of auscultatory sounds using single value decomposition |
US20050197865A1 (en) * | 2004-03-05 | 2005-09-08 | Desmond Jordan | Physiologic inference monitor |
US20060047213A1 (en) * | 2002-10-21 | 2006-03-02 | Noam Gavriely | Acoustic cardiac assessment |
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2007
- 2007-09-18 WO PCT/US2007/078754 patent/WO2008036649A2/fr active Application Filing
Patent Citations (6)
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US5687738A (en) * | 1995-07-03 | 1997-11-18 | The Regents Of The University Of Colorado | Apparatus and methods for analyzing heart sounds |
US6643548B1 (en) * | 2000-04-06 | 2003-11-04 | Pacesetter, Inc. | Implantable cardiac stimulation device for monitoring heart sounds to detect progression and regression of heart disease and method thereof |
US20060047213A1 (en) * | 2002-10-21 | 2006-03-02 | Noam Gavriely | Acoustic cardiac assessment |
US20040260188A1 (en) * | 2003-06-17 | 2004-12-23 | The General Hospital Corporation | Automated auscultation system |
US20050090755A1 (en) * | 2003-10-22 | 2005-04-28 | Guion Marie A. | Analysis of auscultatory sounds using single value decomposition |
US20050197865A1 (en) * | 2004-03-05 | 2005-09-08 | Desmond Jordan | Physiologic inference monitor |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
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US8870791B2 (en) | 2006-03-23 | 2014-10-28 | Michael E. Sabatino | Apparatus for acquiring, processing and transmitting physiological sounds |
US8920343B2 (en) | 2006-03-23 | 2014-12-30 | Michael Edward Sabatino | Apparatus for acquiring and processing of physiological auditory signals |
US11357471B2 (en) | 2006-03-23 | 2022-06-14 | Michael E. Sabatino | Acquiring and processing acoustic energy emitted by at least one organ in a biological system |
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WO2008036649A3 (fr) | 2008-11-27 |
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