(110 days)
The AusculThing ACC software is a decision-support SW for the healthcare provider (the user) in the evaluation of patient heart sounds. The ACC is used to record, display, and analyze acoustic signals of the heart recorded by means of an electronic stethoscope. It is intended for use on adult and pediatric patients. The automated analysis will categorize heart sounds as either "abnormal" if any heart murmur of any intensity is identified in any position across the precordium, or "normal" if either no murmurs or benign murmurs are identified. ACC is indicated for use in a setting where auscultation would typically be performed by a healthcare provider. It is not intended as a sole means of diagnosis. The heart sound interpretation offered by the software is only significant when used in conjunction with physician over-read and including all other relevant patient data. The device is intended for Rx use only. The AusculThing ACC shall be used together with Thinklabs One electronic stethoscope.
AusculThing ACC is a decision support SW that collects heart sounds from adult and pediatric patients. The ACC software receives the data using a Thinklabs One electronic stethoscope. The SW is running on a mobile device, where the electronic stethoscope is connected to. The SW guides the user how relevant heart sound recordings should be obtained from different parts of the body. After recording, the ACC analyzes the recordings in conjunction automatically using an AI -based algorithm, which is trained using a proprietary echocardiogram validated high-quality data database. The basic functionality of the ACC SW is to give a user an instant, automated, analysis of the patient under evaluation and differentiate between normal and pathological sounds. For the abnormal heart sounds, the ACC delivers information on suspected murmurs. The ACC software is a SW that allows a user to upload heart sounds/phonocardiogram (PCG) data to the device for analysis and visualization. The AusculThing ACC Mobile App runs on a mobile device. The app permits the electronic recording of heart sound signals via a compatible electronic stethoscope (Thinklabs One). The app also permits visual and acoustic playback of heart sounds in the mobile device. After analysis, results are returned to the user in the App. The Murmur detection algorithm is based on a neural network model that uses heart sounds to detect the presence of pathological heart sounds. The user can utilize the heart sound analysis results and the acoustic and visual representation of the heart sound recordings as decision support data in their decision-making process regarding the presence and type of a heart murmur.
The AusculThing ACC device claims substantial equivalence to the predicate device, eMurmur ID (K181988), for its performance in detecting abnormal heart sounds.
1. Table of Acceptance Criteria and Reported Device Performance
The acceptance criteria for the AusculThing ACC are based on demonstrating non-inferiority to the predicate device, eMurmur ID, in terms of sensitivity, specificity, and accuracy.
| Metric | Acceptance Criteria (Non-inferior to eMurmur ID) | AusculThing ACC Performance | eMurmur ID Performance (Predicate) |
|---|---|---|---|
| Sensitivity | At least 85.0% | 90.5% (82.3%-95.1%) | 85.0% (72.9%-92.5%) |
| Specificity | At least 86.7% | 96.0% (86.3%-98.9%) | 86.7% (74.9%-93.7%) |
| Accuracy | At least 85.8% | 92.5% (86.7%-95.9%) | 85.8% (78.0%-91.3%) |
The reported performance of the AusculThing ACC (Sensitivity 90.5%, Specificity 96.0%, Accuracy 92.5%) exceeds the performance metrics of the predicate device, eMurmur ID, thereby demonstrating non-inferiority.
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size: The test set comprised 133 patients, from whom a total of 519 heart sound recordings were captured.
- 84 patients were below 18 years of age.
- 49 patients were above 18 years of age.
- 84 patients had a confirmed heart defect.
- Data Provenance: All data was collected in a clinical study conducted in Finland across various hospitals:
- Children:
- Kuopio University Hospital (Puijo Hospital)
- Oulu University Hospital
- Adults:
- Hospital district of Helsinki and Uusimaa (Lohja Hospital)
- Hospital district of Helsinki and Uusimaa (Hyvinkää Hospital)
The study was conducted in accordance with GCP/ISO14155, indicating a prospective and ethically sound approach to data collection.
- Children:
3. Number of Experts Used to Establish Ground Truth and Qualifications
- Number of Experts: Not explicitly stated as a number, but the ground truth was established by cardiologists.
- Qualifications: The heart sound recordings were obtained by a cardiologist, and an echocardiogram was conducted by a cardiologist on all patients to establish the golden standard for diagnosis. This implies highly qualified medical professionals experienced in cardiovascular diagnosis.
4. Adjudication Method for the Test Set
The document does not explicitly state an adjudication method (e.g., 2+1, 3+1). It states that an echocardiogram was conducted by a cardiologist on all patients to establish the "golden standard for diagnosis," suggesting that the cardiologist's echocardiogram interpretation served as the definitive ground truth for each case. This implies a single-expert gold standard based on the cardiologist's assessment and the echocardiogram.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- A MRMC comparative effectiveness study was not explicitly conducted or reported in this summary. The comparison is between the standalone performance of the AusculThing ACC algorithm and the reported performance of the predicate device's algorithm, not the improvement of human readers with AI assistance.
6. Standalone (Algorithm Only) Performance
- Yes, a standalone performance study was conducted. The reported sensitivity, specificity, and accuracy values (90.5%, 96.0%, 92.5%) are for the AusculThing ACC algorithm itself, without a human-in-the-loop component for the performance evaluation presented. The device is intended as "decision support SW" and "not intended as a sole means of diagnosis," with interpretation significant "in conjunction with physician over-read," but the reported performance metrics are for the algorithm's direct classification output.
7. Type of Ground Truth Used
- The ground truth used was expert consensus combined with pathology/diagnostic imaging. Specifically, a cardiologist performed an echocardiogram on all patients, which was then used to establish the "golden standard for diagnosis" against which the algorithm's performance was compared.
8. Sample Size for the Training Set
- The document states that the AI-based algorithm was "trained using a proprietary echocardiogram validated high-quality data database." However, the sample size for this training set is not provided in the given text.
9. How the Ground Truth for the Training Set Was Established
- The ground truth for the training set was established using a "proprietary echocardiogram validated high-quality data database." This implies that the training data also had ground truth labels derived from echocardiogram interpretations, likely by cardiologists, similar to how the ground truth for the test set was established. However, specific details about the process for the training set are not provided beyond this general statement.
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Image /page/0/Picture/0 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). On the left, there is a symbol representing the Department of Health & Human Services - USA. To the right of the symbol, there is the FDA logo in blue, with the words "U.S. FOOD & DRUG" stacked on top of the word "ADMINISTRATION".
July 12, 2023
AusculThing Oy Jani Virtanen Process owner, Regulatory and Quality Affairs Ruusutorpanpuisto 4 A 15 Espoo, 02600 Finland
Re: K230823
Trade/Device Name: AusculThing ACC Regulation Number: 21 CFR 870.1875 Regulation Name: Stethoscope Regulatory Class: Class II Product Code: DQD, DQC Dated: June 12, 2023 Received: June 12, 2023
Dear Jani Virtanen:
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies.
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You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR 803) for devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatoryinformation/postmarketing-safety-reporting-combination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,
Hetal B. Patel -S
for
Robert Kazmierski Acting Assistant Director Division of Cardiac Electrophysiology, Diagnostics and Monitoring Devices Office of Cardiovascular Devices Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
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Indications for Use
510(k) Number (if known)
Device Name
Indications for Use (Describe)
| Prescription Use (Part 21 CFR 801 Subpart D) | |
|---|---|
| Over-The-Counter Use (21 CFR 801 Subpart C) |
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Image /page/3/Picture/1 description: The image contains the logo for AusculThing. The logo consists of a stylized blue icon on the left and the name "AusculThing" in gray text on the right. Below the name is the tagline "Reinventing auscultation" in a smaller font, also in gray.
5. 510(k) Summary
Submitter information
| Name: | AusculThing Ltd. |
|---|---|
| Address: | Ruusutorpanpuisto 4 A 1502600 Espoo, Finland |
| Phone: | +358 50 3801 134 |
| Contact person: | Jani Virtanen, D.Sc.Regulatory and Quality Affairs, Process Owner |
| Submission date: | 15 March 2023 |
Device information
| Trade name: | AusculThing ACC | ||
|---|---|---|---|
| Common name: | Decision support SW, Computer Aided Auscultation, Heart Sound Analyzer | ||
| Classification name: | Electronic Stethoscope, Phonocardiograph | ||
| Regulation number: | 21 CFR 870.1875, 870.2390 | ||
| Product code: | DQD, DQC | ||
| Classification panel: | Cardiology | ||
| Predicate devices | |||
| Primary predicate: | K181988 | Emurmur ID |
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Image /page/4/Picture/1 description: The image contains the logo for AusculThing. The logo consists of a stylized graphic to the left of the company name. The graphic is a blue geometric shape that resembles a network or interconnected nodes. To the right of the graphic is the company name "AusculThing" in a dark gray sans-serif font, with the tagline "Reinventing auscultation" in a lighter gray font below the name.
5.1 Device Description
AusculThing ACC is a decision support SW that collects heart sounds from adult and pediatric The ACC software receives the data using a Thinklabs One electronic patients. stethoscope. The SW is running on a mobile device, where the electronic stethoscope is connected to. The SW guides the user how relevant heart sound recordings should be obtained from different parts of the body. After recording, the ACC analyzes the recordings in conjunction automatically using an AI -based algorithm, which is trained using a proprietary echocardiogram validated high-quality data database. An image below shows the basic architecture of the use environment for the ACC.
Image /page/4/Figure/4 description: The image shows an electronic stethoscope connected to a mobile device with ACC. The mobile device displays a waveform and an image of a chest with several points marked on it. The image also mentions BT/USB/WIFI connection for software updates and a database consisting of clinically validated pediatric heart sounds.
Image 5.1. Basic structure of the ACC use environment.
The basic functionality of the ACC SW is to give a user an instant, automated, analysis of the patient under evaluation and differentiate between normal and pathological sounds. For the abnormal heart sounds, the ACC delivers information on suspected murmurs.
The ACC software is a SW that allows a user to upload heart sounds/phonocardiogram (PCG) data to the device for analysis and visualization. The AusculThing ACC Mobile App runs on a mobile device. The app permits the electronic recording of heart sound signals via a compatible electronic stethoscope (Thinklabs One). The app also permits visual and acoustic playback of heart sounds in the mobile device. After analysis, results are returned to the user in the App. The Murmur detection algorithm is based on a neural network model that uses heart sounds to detect the presence of pathological heart sounds.
The user can utilize the heart sound analysis results and the acoustic and visual representation of the heart sound recordings as decision support data in their decision-making process regarding the presence and type of a heart murmur.
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Image /page/5/Picture/1 description: The image contains the logo for AusculThing. The logo consists of a stylized blue icon to the left, resembling interconnected lines, followed by the name "AusculThing" in a dark gray sans-serif font. Below the name, there is a tagline that reads "Reinventing auscultation" in a lighter gray, smaller font.
5.2 Intended use
The AusculThing ACC software is a decision-support SW for the healthcare provider (the user) in the evaluation of patient heart sounds. The ACC is used to record, display, and analyze acoustic signals of the heart recorded by means of an electronic stethoscope. It is intended for use on adult and pediatric patients. The automated analysis will categorize heart sounds as either "abnormal" if any heart murmur of any intensity is identified in any position across the precordium, or "normal" if either no murmurs or benign murmurs are identified. ACC is indicated for use in a setting where auscultation would typically be performed by a healthcare provider. It is not intended as a sole means of diagnosis. The heart sound interpretation offered by the software is only significant when used in conjunction with physician over-read and including all other relevant patient data. The device is intended for Rx use only. The AusculThing ACC shall be used together with Thinklabs One electronic stethoscope.
5.3 Technological characteristics
AusculThing ACC has technological characteristics that are comparable to the predicate device:
-
Both systems host a heart sound analysis algorithm.
-
Both systems provide the user with a mobile app, which is used to record heart sounds and patient information. Both systems perform an analysis to the data and display the analysis results to the user.
-
Both systems require an FDA-cleared off-the-shelf electronic stethoscope for the acquisition of the heart sounds.
-
Both devices provide similar heart sound analysis output and similar additional supporting information to the user.
The predicate device in this 510(k) Premarket Notification submission is eMurMur ID (K181988) which function and indication are substantially equivalent for the Ausculthing ACC software. On a table below is presented the technical characteristics of the ACC software and eMurMur ID.
The ACC does not raise different questions of safety or effectiveness in comparison to the predicates. While some of the predicate devices feature additional technological capabilities (e.g., the predicate device additional parameters on heart sound), this does not raise different questions of safety or effectiveness because in all cases the subject device features are a subset of those cleared predicate devices.
| ACC | Emurmur ID | |
|---|---|---|
| Device type | Software only | Software only |
| Physiological input | Heart sounds | Heart sounds |
| Classificationproduct code | DQD, DQC | DQD, DQC |
| 510(k) number | K230823 | K181988 |
| Patient population | Adult and pediatric | Adult and pediatric |
| Intended/useIndications for Use | The AusculThing ACC software is adecision-support SW for the healthcareprovider (the user) in the evaluation ofpatient heart sounds. The ACC is usedto record, display, and analyze acousticsignals of the heart recorded by meansof an electronic stethoscope. It isintended for use on adult and pediatricpatients. The automated analysis willcategorize heart sounds as either"abnormal" if any heart murmur of anyintensity is identified in any positionacross the precordium, or "normal" ifeither no murmurs or benign murmursare identified. ACC is indicated for usein a setting where auscultation wouldtypically be performed by a healthcareprovider. It is not intended as a solemeans of diagnosis. The heart soundinterpretation offered by the software isonly significant when used inconjunction with physician over-readand including all other relevant patientdata. The device is intended for Rx useonly. The AusculThing ACC shall beused together with Thinklabs Oneelectronic stethoscope. | The eMurmur ID software system is adecision support device for the healthcareprovider (the user) in the evaluation ofpatient heart sounds. eMurmur ID is usedto record, display, analyze, and store theacoustic signal of the heart, recorded bymeans of an electronic stethoscope. Theautomated analysis will identify specificheart sounds that may be present,including S1, S2, physiological heartmurmurs, pathological heart murmursand absence of a heart murmur.eMurmur ID is indicated for use in asetting where auscultation wouldtypically be performed by a healthcareprovider. It is not intended as a solemeans of diagnosis. The heart soundinterpretations offered by eMurmur IDare only significant when considered inconjunction with healthcare providerover-read and including all other relevantpatient data. |
| Prescribed | Prescription only | Prescription only |
| User interface | App (iOS/Android) for recording heartsounds, performing analysis ofrecordings locally on the device andpresenting the analysis results. | App for recording heart sounds, sendinganalysis requests and receiving analysisresults. Web portal for reviewing andediting user and patient data. |
| Murmur detection | Yes (Classification) | Yes (Classification) |
| Acquires and recordsheart sounds | Yes - acoustic signal of heart by meansof electronic stethoscope and mobileapp | Yes - acoustic signal of heart bymeans of electronic stethoscope andmobile app |
| Analyzes heartsounds | Yes - distinguishes between normaland pathological heart murmurs | Yes – distinguishes betweennormal/physiological and pathologicalheart murmurs |
| Intended user | Healthcare provider licensed or | Healthcare provider licensed or |
| authorized to perform auscultation | authorized to perform auscultation | |
| Backend | The mobile device analyzes the dataand communicates with the othercomponents of AusculThing ACC.Results from the analysis can be sharedvia email. | Server analyzes (algorithm) and stores(database) patient-related data andcommunicates with the other componentsof eMurmur ID. The interface to the othercomponents is a REST/JSON web API. |
| Safety features | No protected health information isstored on the user's devices. User hasauthentication on the app and themobile device. | Encrypted internet traffic, data stored inthe database on the backend is encrypted,data in the database is duplicated toanother database in a different datacenter,no protected health information is storedon the user's devices, user needs toauthenticate, user can only accessauthorized data. |
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Image /page/6/Picture/1 description: The image contains the logo for AusculThing. The logo consists of a stylized graphic to the left of the company name. Below the company name is the tagline "Reinventing auscultation."
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Image /page/7/Picture/1 description: The image contains the logo for AusculThing. The logo consists of a blue abstract graphic to the left of the company name. The company name is in two lines, with "AusculThing" on the top line in a dark gray font and "Reinventing auscultation" on the bottom line in a lighter gray font.
5.4 Performance data - Non-clinical Testing
Performance data included software verification and validation testing, no performance data under non-clinical testing have been included.
5.5 Performance data - Clinical Testing
The algorithm in this submission has been validated using proprietary data captured with the ACC. A total of 519 recordings were captured from a study population consisting of 133 patients. Of the population 84 were below 18 years of age and 49 were above. Out of the 133 patients 84 had a confirmed heart defect. All data was collected in a clinical study in accordance with GCP/ISO14155.
In the table below the content (age distribution, gender, diagnoses and auscultation findings) of the validation data is described. Some of the patients have multiple diagnoses.
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Image /page/8/Picture/0 description: The image contains the logo for AusculThing. The logo consists of a stylized blue icon to the left of the company name, "AusculThing," which is in a dark gray sans-serif font. Below the name is the tagline "Reinventing auscultation" in a lighter gray, smaller font.
| R01.0 : Benign murmur | Q21.0 : Ventricular Septal Defect | Q21.10 : Atrial Septal Defect | Q21.11 : Patent foramen ovale | Q23.0 : Stenosis congenita valva e aorta | Q23.11 : Valvae aortae biscupidalis | Q22.1 : Stenosis congenita valva pulmonalis (inc. ToF) | Q25.1 : Coarctation of the aorta | Q25.0 : Patent ductus arteriosus | Q23.10 : Insufficientia congenita valvae aortae | Q22.2 : Insufficientia congenita valvae pulmonalis | Q23.3 : Insufficientia congenita valvae mitralis | Q25.7 : Stenosis pulmonalis | Q35.0: Stenosis valvae aortae | Q37.0 : Stenosis valvae pulmonalis | Q34.2: Stenosis valvae mitralis | Q35.1 : Insufficientia valvae aortae | Q37.1 : Insufficientia valvae pulmonalis | Q34.0 : Insufficientia valvae mitralis | Q36.1 : Insufficientia valvae tricuspidalis | Normal (no murmur nor heart defect) | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Age group | 0 - 1 months | 0 | 6 | 3 | 0 | 0 | 0 | 1 | 1 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
| 1 - 6 months | 6 | 3 | 4 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | |
| 6 - 12 months | 3 | 2 | 2 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 1 - 4 years | 5 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | |
| 4 - 12 years | 9 | 4 | 0 | 0 | 6 | 2 | 2 | 3 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 7 | |
| 12 -18 years | 3 | 1 | 0 | 0 | 2 | 1 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | |
| 18 - 55 years | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | |
| 55 -80 years | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 20 | 0 | 0 | 3 | 0 | 5 | 3 | 1 | |
| >80 years | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | |
| Sex | Male | 16 | 5 | 1 | 0 | 6 | 3 | 3 | 2 | 0 | 2 | 0 | 0 | 2 | 22 | 0 | 0 | 4 | 0 | 8 | 3 | 9 |
| Female | 18 | 9 | 0 | 0 | 3 | 1 | 3 | 1 | 6 | 0 | 0 | 0 | 1 | 12 | 0 | 0 | 1 | 0 | 0 | 0 | 7 | |
| Systolic findings | 24 | 14 | 1 | 0 | 9 | 4 | 6 | 3 | 6 | 2 | 0 | 0 | 3 | 33 | 0 | 0 | 5 | 0 | 8 | 3 | 1 | |
| Diastolic finding | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| Systolic gradus | 1 | 13 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2 | 10 | 4 | 1 | 0 | 1 | 2 | 2 | 2 | 1 | 0 | 0 | 0 | 1 | 7 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | |
| 3 | 0 | 6 | 0 | 0 | 3 | 2 | 3 | 1 | 1 | 1 | 0 | 0 | 2 | 11 | 0 | 0 | 2 | 0 | 4 | 1 | 0 | |
| 4 | 0 | 2 | 0 | 0 | 4 | 0 | 1 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 6 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| Diastolic gradus | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| Punctum Maximum | A | 4 | 0 | 0 | 0 | 6 | 2 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 8 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
| B | 4 | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 3 | 0 | 0 | 0 | 3 | 15 | 0 | 0 | 3 | 0 | 2 | 2 | 0 | |
| C | 8 | 13 | 0 | 0 | 2 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 7 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| D | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 1 | 0 | 6 | 0 | 0 | |
| Unspecified | 14 | 1 | 1 | 0 | 1 | 1 | 1 | 2 | 2 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 1 | 16 |
Heart sounds were recorded from all patients either by a cardiologist. An echocardiogram was conducted by a cardiologist on all patients to establish the golden standard for diagnosis to which the algorithm performance was compared. The table below shows the amount of recordings made in each hospitals.
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Image /page/9/Picture/1 description: The image contains the logo for AusculThing. The logo consists of a stylized graphic to the left of the company name. The graphic is a blue geometric shape. To the right of the graphic is the company name "AusculThing" in a dark gray font, with the tagline "Reinventing auscultation" in a smaller, lighter gray font below it.
| Population | Hospital District | Hospital | Audio recordingsobtained by | Patient count |
|---|---|---|---|---|
| Children | Kuopio UniversityHospital | Puijo Hospital | Cardiologist | 14 |
| Children | Oulu UniversityHospital | Oulu UniversityHospital | Cardiologist | 70 |
| Adults | Hospital district ofHelsinki andUusimaa | Lohja Hospital | Cardiologist | 20 |
| Adults | Hospital district ofHelsinki andUusimaa | Hyvinkää Hospital | Cardiologist | 29 |
The obtained accuracy, sensitivity and specificity were compared to the predicate device performance metrics as provided in the predicate device 510k summary (K181988) and are shown in the following table:
| ACC | eMurmur ID | |
|---|---|---|
| Sensitivity | 90.5% (82.3%-95.1%) | 85.0% (72.9%-92.5%) |
| Specificity | 96.0% (86.3%-98.9%) | 86.7% (74.9%-93.7%) |
| Accuracy | 92.5% (86.7%-95.9%) | 85.8% (78.0%-91.3%) |
The results from the study demonstrate that ACC does not perform worse than the predicate device in the given test setting.
Conclusions
The ACC Analysis Software is as safe and effective as the predicate device. Performance data demonstrate that the AusculThing ACC software performs in a manner that is comparable to the reference device, meeting the criteria that it be at least non-inferior. The ACC Analysis Software has the same intended use and similar indications, technological characteristics, and principles of operation as its predicate device. The minor technological differences between AusculThing ACC and its predicate device raise no new questions of safety or effectiveness when used as labeled. Thus, the ACC Analysis Software is substantially equivalent.
§ 870.1875 Stethoscope.
(a)
Manual stethoscope —(1)Identification. A manual stethoscope is a mechanical device used to project the sounds associated with the heart, arteries, and veins and other internal organs.(2)
Classification. Class I (general controls). The device is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 870.9.(b)
Electronic stethoscope —(1)Identification. An electronic stethoscope is an electrically amplified device used to project the sounds associated with the heart, arteries, and veins and other internal organs.(2)
Classification. Class II (special controls). The device, when it is a lung sound monitor, is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 870.9.