Search Results

Ask a specific question about this device

The ReddyPort Elbow is intended to provide an interface for application of CPAP or bi-level therapy to the patient including while the patient is simultaneously undergoing another care procedure (e.g. oral care, suctioning, bronchoscopy) by hospital/institutional clinicians. The elbow is for single patient use in the hospital/institutional environment. The elbow is to be used on patients (> 40 lbs/ 18.2 kg) for whom CPAP or bi-level therapy has been prescribed. The elbow can be used with Philips Respironics AF541 masks and AF531 masks with the clip-style connection.

The ReddyPort Elbow is an NIV elbow that replaces the elements AF541 style masks and AF531 masks with a clip-style comection and provides oral access for clinicians to the patient's airway during CPAP and bi-level therapy. The ReddyPort Elbow is compatible with both Over the Nose (OTN) cushion ((S, M, L, XL sizes) and an Under the Nose (UTN) cushion (A, B, C sizes) configurations of the AF541 EE Mask and AF531 mask with clip-style connection. ReddyPort permanently replaces the conventional elbow on the mask and maintains positive pressure. This elbow allows for respiratory care procedures (e.g. oral care, suctioning, bronchoscopy) to be performed on a patient while the patient is receiving non-invasive ventilation. The elbow contains a duckbill valve that allows the patient's airway and that seals with similar leak rates to conventional NIV elbows. In addition, the elbow includes an anti-asphysia valve to ensure safety of the patient.

Here's an analysis of the provided FDA 510(k) summary regarding the ReddyPort Elbow, focusing on acceptance criteria and supporting studies.

Important Note: The provided document is a 510(k) summary for a medical device that interfaces with respiratory therapy equipment. It is not an AI/ML medical device. Therefore, many of the requested elements for AI/ML device studies (like sample size of test/training sets, expert ground truth, MRMC studies, etc.) are not applicable to this type of traditional medical device submission. This document focuses on the physical and functional equivalence to predicate devices through bench testing and biocompatibility testing, not on algorithmic performance.

I will address the applicable sections of your request based on the provided text.

Device Name: ReddyPort Elbow
Regulation Name: Continuous Ventilator (specifically an accessory/interface)
Regulatory Class: Class II
Product Code: MNS
Applicant: SMD Manufacturing LLC

1. Table of Acceptance Criteria and Reported Device Performance

The provided document doesn't present a formal table of "acceptance criteria" against "reported performance" in the way one might see for an AI/ML device (e.g., sensitivity, specificity thresholds). Instead, for this type of mechanical device, the acceptance criteria are generally implied by meeting the requirements of recognized standards (ISO 17510, ISO 5356-1) and demonstrating performance (e.g., leak rates, resistance to flow). The device is deemed acceptable if it meets these standards and is substantially equivalent to predicate devices.

However, based on the "Substantial Equivalence Comparison Table" (pages 4-5) and "Performance Testing" section (page 6), here's an attempt to structure the information in a table format, focusing on quantitative metrics where available:

Conclusion from section "Performance Testing": "The ReddyPort Elbow met all applicable requirements and acceptance criteria."

2. Sample Size Used for the Test Set and the Data Provenance

• Sample Size: Not applicable. For this type of device, "test set" refers to physical samples of the device undergoing bench testing, not a dataset of patient cases. The number of physical units tested is not specified but is assumed to be sufficient for engineering and regulatory standards (e.g., multiple units to ensure consistency and robustness, per standard requirements like ISO).
• Data Provenance: Not applicable. This is not clinical data. The data comes from bench testing performed by the manufacturer, likely in a controlled laboratory setting (e.g., specific to the manufacturing facility or a third-party testing lab). The document does not specify a country of origin for the testing, but it is for a US regulatory submission.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts

Not applicable. "Ground truth" in the context of an AI/ML device refers to a definitive 'correct answer' for a diagnostic task, often established by expert consensus or pathology results. For this mechanical device, the "truth" is established by physical measurement against engineering standards and specifications. Engineers and technicians, not medical experts as defined in the prompt, perform these tests.

4. Adjudication Method for the Test Set

Not applicable. Adjudication methods like 2+1 or 3+1 are used to resolve disagreements among multiple human readers in diagnostic tasks, which is characteristic of AI/ML performance studies. This device's evaluation is based on objective physical measurements via bench testing.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No. An MRMC study is relevant for evaluating the impact of AI on human diagnostic performance. This device is a mechanical accessory, not a diagnostic AI.

6. If a Standalone (i.e. algorithm only without human-in-the loop performance) Was Done

No. There is no algorithm or AI component in this device. The performance data presented (leak rates, resistance, dead space) is indeed "standalone" in the sense that it's the raw physical performance of the device without human interaction being assessed as part of the primary outcome, but this is standard bench testing, not AI standalone performance.

7. The Type of Ground Truth Used

The "ground truth" for this device's evaluation is defined by:

• Engineering Specifications and Design Requirements: What the device is designed to do.
• Recognized International Standards: Such as ISO 17510 (Medical devices -- Sleep apnoea breathing therapy Masks and application accessories) and ISO 5356-1 (Anaesthetic and respiratory equipment Conical connections). These standards specify acceptable ranges for performance characteristics like leak rates and resistance.
• Performance of Legally Marketed Predicate Devices: Especially the primary predicate (ReddyPort NIV Access Elbow, K171827) and reference devices (AF541 EE Full Face Mask, K150639; BRONCHOSCOPY ELBOW, K132168). The subject device must perform as well as or better than these predicates to prove substantial equivalence.

8. The Sample Size for the Training Set

Not applicable. This is a manufactured physical device, not an AI/ML model that requires training data.

9. How the Ground Truth for the Training Set Was Established

Not applicable. There is no training set for a mechanical device.

Summary of Acceptance and Proof for ReddyPort Elbow:

The ReddyPort Elbow's acceptance is based on demonstrating substantial equivalence to legally marketed predicate devices. This is proven through:

1. Bench Testing: As detailed in the table above, the device's physical performance characteristics (dead space, leak rates, resistance to flow) are measured and shown to be comparable to, and in some cases better than, the predicate devices, while meeting the requirements of relevant ISO standards. The document explicitly states: "The ReddyPort Elbow met all applicable requirements and acceptance criteria."
2. Biocompatibility Testing: The materials used in the device meet the requirements of ISO 10993 series and ISO 18562 series, indicating the device is biologically safe for its intended use and contact duration.
3. No Clinical Testing: The FDA determined that no clinical testing was required, implying that the bench testing and comparison to predicates provided sufficient evidence of safety and effectiveness for a 510(k) clearance.

In essence, the "study" proving the device meets acceptance criteria consists of these comprehensive engineering, performance, and biocompatibility tests conducted according to recognized standards, demonstrating the device's functional and safety equivalence to previously cleared devices.

Ask a specific question about this device

The BPAP System is a Bi-level PAP (Bi-level Positive Airway Pressure) device, which is intended to provide noninvasive ventilation for patients with Obstructive Sleep Apnea (OSA) or Respiratory Insufficiency. The integrated humidifier is indicated for the humidification and warming of air from the flow generator device. The device is intended for adult patients weighing more than 66lbs (30 kg) by prescription. The device is intended for single patient use in the home environment and multi-patient re-use in the hospital/institutional environment.

The proposed device is a non-invasive, continuous positive airway pressure ventilator, incorporating a heated respiratory humidifier. The device is intended to treat obstructive sleep apnea or respiratory insufficiency by delivering a flow of positive airway pressure at a level prescribed by a physician to splint open the airway and prevent airway collapse.

The proposed device is available in different models designed with different therapy modes and pressure ranges. The therapy modes are available in six types, which are CPAP, Spontaneous (S), Spontaneous/Timed (S/T), Timed (T), Auto CPAP and Auto S. The pressure range for the proposed devices is available in two types, which are 4-25cm H2O and 4-30 cm H2O.

Alarm module is incorporated in the device. The device will generate audio and visual alarm for any abnormal conditions. The proposed device is provided non-sterile, and not to be sterilized by the user prior to use. The proposed device can be reused by single patient and multi-patients

The provided text describes a 510(k) premarket notification for a BPAP System, stating that "No clinical study is included in this submission." Therefore, there is no information in the provided document about acceptance criteria, device performance, sample sizes for test and training sets, data provenance, expert ground truth establishment, adjudication methods, MRMC studies, or standalone performance. The document focuses on demonstrating substantial equivalence to predicate devices through non-clinical tests and feature comparison.

However, I can extract the non-clinical test conclusions and how they "prove the device meets acceptance criteria" in that context.

Here's a breakdown of what the document does provide:

Non-Clinical Test Data and Compliance

The document states that non-clinical tests were conducted to verify that the proposed device met all design specifications. The test results demonstrated compliance with various international standards, which serve as the "acceptance criteria" for these non-clinical aspects.

1. A table of acceptance criteria (standards) and the reported device performance (compliance):

Additionally, the device's specific technical performance attributes were compared to predicate devices, demonstrating substantial equivalence rather than meeting independent clinical acceptance criteria:

2. Sample size used for the test set and the data provenance:

No clinical study test set or data provenance is mentioned as "No clinical study is included in this submission." The "test set" in this context refers to the physical device prototypes undergoing non-clinical bench testing.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

Not applicable, as no clinical study or expert-driven ground truth establishment is described. The "ground truth" for non-clinical tests is based on engineering specifications and adherence to international standards.

4. Adjudication method for the test set:

Not applicable, as no clinical study is conducted.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done:

No. As explicitly stated: "No clinical study is included in this submission." Therefore, no MRMC study or effect size for human reader improvement with AI assistance was performed or reported here.

6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:

Not applicable. This is a physical medical device (BPAP system), not an AI algorithm. Its performance is inherent to the device itself, as demonstrated through non-clinical testing against standards.

7. The type of ground truth used:

For the non-clinical tests, the "ground truth" is defined by the requirements and specifications of the cited international standards (e.g., IEC 60601 series, ISO 80601 series, ISO 10993 series, ISO 18562 series) and the manufacturer's internal design specifications.

8. The sample size for the training set:

Not applicable, as "No clinical study is included in this submission." This is a hardware device cleared based on substantial equivalence, not a machine learning algorithm requiring a training set.

9. How the ground truth for the training set was established:

Not applicable for the same reason as above.

Ask a specific question about this device

The ReddyPort NIV Access Elbow is intended to provide an interface for application of CPAP or bi-level therapy. The elbow is for single patient use in the hospital/institutional environment. The elbow is to be used on patients 7 years or older (>40lbs/18.2kg) for whom CPAP or bi-level therapy has been prescribed.

Not Found

The provided text is a 510(k) premarket notification letter from the FDA to SMD Manufacturing, LLC, regarding the ReddyPort NIV Access Elbow. This document is a regulatory communication for a medical device and does not contain information about acceptance criteria, device performance studies, sample sizes, ground truth establishment, or expert qualifications for AI/algorithm-based devices.

Therefore, I cannot extract the requested information as it is not present in the provided text. The device described, the "ReddyPort NIV Access Elbow," is a physical medical device (an elbow interface for CPAP/bi-level therapy), not an AI or algorithm-based device that would typically undergo the kind of performance studies you're asking about with specific acceptance criteria, test sets, ground truth, and expert adjudication.

The letter confirms that the device is "substantially equivalent" to legally marketed predicate devices, which is a regulatory classification for certain medical devices, and outlines general controls and regulations it is subject to.

Ask a specific question about this device

The Juno VPAP ST-A is indicated to provide noninvasive ventilation for patients weighing more than 30lbs (13 kg) with respiratory insufficiency or obstructive sleep apnoea (OSA).

The iVAPS mode is indicated for patients weighing more than 66lbs (30 kg).

The Juno VPAP ST-A is intended for home and hospital use.

The humidifier is intended for single patient use in the home environment and re-use in a hospital/institutional environment.

The subject device Juno VPAP ST-A retains all the same hardware, technologies and manufacturing characteristics as previously cleared in K153061. The device is used in a wider breathing circuit which typically comprises patient tubing and a mask (patient interface) to deliver a prescribed positive airway pressure treatment to patients.

Some of the kev features of the device include an in-line power supply: fully integrated humidifier: alarms module; heater controller; colour LCD and simple controls for ease of use. The device also allows data transfer/connectivity via an integrated wireless module (When used in a hospital setting, remote changes may not be appropriate for certain patients, as these setting changes may not be communicated to all hospital personnel treating the patient. Hospital staff should liaise with the patient's regular care provider such that the desired therapy outcome is achieved).

Juno VPAP ST-A utilizes a Micro-processor controlled blower system that generates positive airway pressure (CPAP) between 4-20 cmHJO as required to maintain an "air splint" for effective treatment of OSA and (Bilevel) pressures between 3-30 cmH2O for the treatment respiratory insufficiency.

The therapy modes available in the Juno VPAP ST-A include CPAP, Spontaneous, Spontaneous/Timed, Timed, PAC and iVAPS. In this subject device now features an optional "AutoEPAP" function on iVAPS mode. AutoEPAP automatically adjusts EPAP pressure (within set values) in response to flow limitations of the upper airway.

Juno VPAP ST-A is intended to be used under the conditions and purposes indicated in the labelling provided with the product.

It is a prescription device, supplied non-sterile.

The document describes the Resmed Juno VPAP ST-A device (K161492), which is an update to a previously cleared device (K153061). The key change in the subject device is the addition of an optional "AutoEPAP" function to the iVAPS therapy mode.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are not explicitly stated as numerical targets in the provided text. Instead, suitability for market is based on demonstrating substantial equivalence to the predicate device (Juno VPAP ST-A, K153061) and demonstrating that the new AutoEPAP algorithm provides equivalent therapy to the fixed EPAP setting of the predicate.

The reported device performance is that the AutoEPAP iVAPS therapy mode was as efficacious as iVAPS with fixed EPAP in terms of several clinical metrics.

2. Sample Size Used for the Test Set and Data Provenance

• Sample size for the test set: Not explicitly stated. The document mentions "patients with respiratory insufficiency" but does not provide the number of participants.
• Data provenance: Not explicitly stated, but the study was a "clinical trial" which implies prospective data collection. The country of origin is not specified.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

This information is not provided in the document. As this is a study evaluating the clinical efficacy of a ventilator mode, the "ground truth" would be established by direct physiological measurements and clinical assessments rather than expert review of images or data.

4. Adjudication Method for the Test Set

This information is not provided in the document.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, If So, What Was the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

No, an MRMC study was not done. This device is a ventilator, not an AI-assisted diagnostic tool that would typically involve human readers interpreting data or images. The study focuses on the direct efficacy of the ventilator's automated function.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

Yes, the clinical trial described appears to be a standalone performance evaluation of the AutoEPAP iVAPS algorithm. It directly compares the efficacy of the new automated algorithm with the fixed EPAP mode, which also functions automatically (without real-time human intervention during therapy delivery).

7. The Type of Ground Truth Used

The ground truth was established using physiological measurements and clinical outcomes data such as:

• Apnea-Hypopnea Index (AHI)
• Oxygen Desaturation Index (ODI)
• Blood Oxygen Saturation (SPO2)
• Transcutaneous Carbon Dioxide (PtcCO2)
• Sleep Quality (presumably based on polysomnography or other clinical assessments)

8. The Sample Size for the Training Set

The document describes a clinical trial (double-blinded, randomized, crossover study) which evaluates the performance of the implemented algorithm. It does not mention a separate "training set" in the context of an AI/machine learning model development lifecycle. The AutoEPAP algorithm would have been developed and internally validated by the manufacturer, but the specific details of its training data (if any for a machine learning component) are not provided. The clinical trial serves as the validation or test set for the device's efficacy.

9. How the Ground Truth for the Training Set Was Established

As explained above, a "training set" in the machine learning sense is not explicitly discussed. For the clinical trial (validation data), the ground truth was established through direct physiological measurements and clinical assessments as listed in point 7.

Ask a specific question about this device

The VPAP ADAPT SV is intended to provide non-invasive ventilatory support to treat adult patients with obstructive sleep apnea (OSA) and Respiratory Insufficiency caused by central and/or mixed apneas and periodic breathing.

The VPAP TX is indicated for the treatment of patients weighing more than 66 lb (> 30 kg) with obstructive sleep apnea (OSA), respiratory insufficiency, central or mixed apneas, or periodic breathing. The VPAP TX is intended to be used in a clinical environment.

The S9 VPAP Tx is indicated for the treatment and titration of patients with obstructive sleep apnea (OSA), respiratory insufficiency, central or mixed apneas, or periodic breathing. CPAP, S, ST, T and PAC modes are indicated for patients weighing more than 30lb (13 kg); all other modes are indicated for patients weighing more than 66lb (30 kg). The S9 VPAP Tx is intended to be used in a clinical environment.

The VPAP Adapt SV is identical to the predicate device VPAP Adapt SV (K051364), using a blower based positive pressure system. The device platform is identical to the VPAP Adapt SV (K051364) and contains a blower (motorfan assembly), flow and pressure sensors, and processing electronics. The blower supplies pressurized air to the patient via a mask and air tubing. The VPAP Adapt SV is a non-invasive flow generator device designed to provide adaptive servo-ventilation therapy to stabilize a patient's ventilation. The device continually measures instantaneous ventilation, and calculates a target ventilation equal to 90% of the patient's recent average ventilation (time constant 100 seconds). It then adjusts the degree of support to servo-control the patient's ventilation to at least equal the target ventilation.

The VPAP Tx is identical to the predicate device VPAP Tx (K092186), using a blower based positive pressure system. The device platform is identical to the VPAP Tx (K092186) and contains a Micro- processor controlled blower system that generates airway pressures as required to maintain an "air splint" for effective treatment of OSA and/or respiratory insufficiency. The VPAP Tx system comprises the flow generator, patient interface) and optional humidifier.

The S9 VPAP Tx is identical to the predicate device S9 VPAP Tx (K123511), using a blower based positive pressure system. The device platform is identical to the S9 VPAP Tx (K092186) and contains a Micro- processor controlled blower system that generates airway pressures as required to maintain an "air splint" for effective treatment of OSA and/or respiratory insufficiency. The S9 VPAP Tx comprises the flow generator, patient interface) and optional humidifier.

This document is primarily a 510(k) summary for three ResMed devices (VPAP Adapt SV, VPAP Tx, and S9 VPAP Tx), indicating that the submission is for a labeling change to include a contraindication. It states that no further clinical testing was required to show substantial equivalence to the predicate devices because it was a labeling change only. Therefore, the document does not contain information about acceptance criteria or a study proving the device meets those criteria, as typically found in a performance study for a new device or software.

However, the contraindication is supported by a large-scale clinical study:

SERVE-HF Study Information (relevant to the contraindication):

• Study Design: Randomized, parallel, event-driven, international multicenter study.
• Sample Size: 1325 patients.
• Patient Population: Chronic, symptomatic heart failure (NYHA 2-4) with reduced left ventricular ejection fraction (LVEF ≤ 45%) and moderate to severe predominant central sleep apnea.
• Intervention: Addition of ASV (Adaptive Servo-Ventilation) to guideline-based medical management.
• Outcome Investigated: Effects on survival and cardiovascular outcomes.
• Finding: The addition of ASV did not improve outcomes and showed an increased risk of cardiovascular mortality despite effective control of central sleep apnea. This finding supports the need for a contraindication rather than demonstrating the device's performance against specific acceptance criteria for its intended use outside of this specific high-risk patient group.

Given the nature of the submission (a labeling change based on a clinical trial that identified a contraindication), the following points from your request cannot be directly extracted from the provided text for the device's performance meeting acceptance criteria:

1. A table of acceptance criteria and the reported device performance: Not available, as no new performance study was conducted. The tables provided compare characteristics of the new device to the predicate, stating they are "Equivalent," which is about substantial equivalence, not acceptance criteria performance.
2. Sample size used for the test set and the data provenance: For the contraindication study (SERVE-HF), the sample size was 1325 patients, from an international multicenter study. Data provenance for the device's original clearance is not detailed here.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable for this submission's context, as it's a labeling change based on a large clinical trial, not a performance study compared to expert ground truth for a diagnostic AI.
4. Adjudication method: Not applicable here.
5. If a multi reader multi case (MRMC) comparative effectiveness study was done: Not applicable.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): For the SERVE-HF study, the "ground truth" was clinical outcomes data (survival and cardiovascular mortality).
8. The sample size for the training set: Not applicable, as this is a device and a labeling change, not an AI/ML algorithm development with a training set.
9. How the ground truth for the training set was established: Not applicable.

Summary in relation to your request:

The document describes a labeling change for three continuous ventilators (VPAP Adapt SV, VPAP Tx, S9 VPAP Tx). This change is to add a contraindication for ASV therapy in patients with chronic, symptomatic heart failure (NYHA 2-4) with reduced left ventricular ejection fraction (LVEF ≤ 45%) and moderate to severe predominant central sleep apnea.

This contraindication is directly supported by findings from the SERVE-HF study, a large-scale, randomized, parallel, event-driven, international multicenter study involving 1325 patients. The study found that adding ASV to guideline-based medical management in this specific patient population did not improve outcomes and led to an increased risk of cardiovascular mortality. The "ground truth" for the SERVE-HF study was clinical outcomes data (survival and cardiovascular outcomes).

The document explicitly states that no further clinical testing was required for this 510(k) submission because it was only a labeling change, and the device itself (its operating principle, technology, manufacturing process) remains substantially equivalent to its respective predicate devices (K051364, K092186, K123511). Therefore, there are no new acceptance criteria or device performance data against them presented in this document for the device's efficacy in its cleared indications.

Ask a specific question about this device

The Juno VPAP ST-A is indicated to provide noninvasive ventilation for patients weighing more than 30lbs (13 kg) with respiratory insufficiency or obstructive sleep apnoea (OSA).

The iVAPS mode is indicated for patients weighing more than 66lbs (30 kg).

The Juno VPAP ST-A is intended for home and hospital use.

The humidifier is intended for single patient use in the home environment and re-use in a hospital/institutional environment.

The Juno VPAP ST-A System is a positive pressure device which design is based on the previously cleared ResMed S9 WANDA VPAP ST (K140159) platform. The device is used in a wider breathing circuit which typically comprises patient tubing and a mask (patient interface) to deliver the prescribed positive pressure treatment to patients.

Some of the key features of the platform include: in-line power supply; fully integrated humidifier; heater controller; colour LCD and simple controls for ease of use. An integrated wireless module for data transfer/connectivity is also included (note: Remote changes in a hospital setting may not be appropriate, as these setting changes may not be communicated to all hospital personnel treating the patient. Hospital staff should liaise with the patient's reqular care provider such that the desired therapy outcome is achieved).

Juno VPAP ST-A contains a Micro-processor controlled blower system that generates positive airway pressure (CPAP) between 4-20 cmHyO as required to maintain an "air splint" for effective treatment of OSA and (Bilevel) pressures between 3-30 cmH2O for the treatment respiratory insufficiency.

The device also incorporates an Alarm function as a fully integrated module.

The therapy modes available in the Juno VPAP ST-A come from the predicate ResMed S9 VPAP ST-A (K113288). These include CPAP, Spontaneous, Spontaneous/Timed, Timed, PAC and iVAPS.

Juno VPAP ST-A is intended to be used under the conditions and purposes indicated in the labelling provided with the product.

It is a prescription device, supplied non-sterile.

The provided text does not contain detailed acceptance criteria or a study proving that the device meets these criteria in the manner you've requested (e.g., performance metrics, sample sizes, expert ground truth).

The document is a 510(k) summary for a medical device (Juno VPAP ST-A), which focuses on demonstrating substantial equivalence to a predicate device (ResMed S9 VPAP ST-A K113288), rather than presenting a detailed clinical study with performance metrics against pre-defined acceptance criteria.

The "Non Clinical data submitted" section (page 8) mentions "Bench test data is presented to demonstrate that the new device meets its published specifications and back-to-back testing shows substantial equivalence to the predicate device S9 VPAP ST-A (K113288)." It further states, "All bench tests confirmed that the product met the predetermined acceptance criteria. this included Pressure, Flow, Pressure Support, Trigger and Cycling, Hypopnea and Apnea tests against the predicate devices using common protocols for both devices."

However, this section does not provide specific numerical acceptance criteria values or the reported device performance against those criteria. It also doesn't describe an AI/ML-based device that would typically involve a "test set" with ground truth established by experts, MRMC studies, or standalone algorithm performance.

Therefore, most of the requested information cannot be extracted from this document, as it pertains to a different type of device assessment (bench testing for substantial equivalence of a continuous ventilator) than what your questions imply (e.g., an AI/ML diagnostic device).

Here's what can be inferred or stated based on the document's content, and what cannot:

1. A table of acceptance criteria and the reported device performance:

• Cannot provide. The document states that bench tests confirmed the product met "predetermined acceptance criteria" for parameters like pressure, flow, pressure support, trigger and cycling, hypopnea, and apnea tests. However, the specific numerical acceptance criteria (e.g., "pressure within +/- X cmH2O") and the actual performance results are not detailed in this summary.

2. Sample sized used for the test set and the data provenance:

• Cannot provide. The document refers to "bench tests" and "back-to-back testing" against a predicate device. This is not a "test set" in the context of clinical data for an AI/ML device. There are no details on sample size, data provenance, or whether the data was retrospective or prospective, as this was not a clinical study involving patients for direct performance evaluation against ground truth.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not applicable. This device is a continuous ventilator, and its performance was evaluated through engineering bench tests, not clinical evaluation against expert-adjudicated ground truth as would be done for a diagnostic AI/ML system.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

• Not applicable. No expert adjudication was described.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

• Not applicable. This is not an AI-assisted diagnostic device, so an MRMC study comparing human readers with and without AI assistance was not performed.

6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:

• Not applicable. This is a hardware medical device (ventilator) with integrated software/firmware, not a standalone diagnostic algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):

• Implied ground truth for bench testing: Engineering specifications and performance of the predicate device (S9 VPAP ST-A (K113288)). This is a "technical" ground truth, not a "clinical" one. The document states: "this included Pressure, Flow, Pressure Support, Trigger and Cycling, Hypopnea and Apnea tests against the predicate devices using common protocols for both devices."

8. The sample size for the training set:

• Not applicable. This document is for a hardware device, not an AI/ML model that undergoes a training phase with a specific dataset.

9. How the ground truth for the training set was established:

• Not applicable. See point 8.

In summary: The provided 510(k) summary focuses on demonstrating substantial equivalence through bench testing against a predicate device's specifications and performance, rather than clinical study results of an AI/ML device against expert-established ground truth. Therefore, very little of the information typically sought for AI/ML device evaluation is available in this document.

Ask a specific question about this device

EasyCare Online is a web based solution for healthcare specialists intended to:
• assist in the diagnosis of sleep disordered breathing in adult patients through analysis of data recorded by an EasyCare Online compatible home sleep test device.
• transfer and display, usage and therapeutic information that has been transmitted remotely from the patient's therapy device located in the home. It is intended to support the standard follow-up care of patients that have been prescribed a compatible ResMed therapy device for the treatment of obstructive sleep apnea or respiratory insufficiency. EasyCare Online also provides remote settings capabilities

EasyCare Online is a web application that can transfer, store, manage and display usage and therapy data from (ResMed compatible flow generators) and diagnostic data from (ResMed compatible sleep study devices). The data is transferred from the device either wirelessly through a communications module, or with the aid of an SD card and internet technology, to a central database and then displayed on the clinician's/DME's computer, through a web based application such as internet Explorer.

EasyCare Online is used to monitor and optimize the therapy of patients diagnosed with sleep apnea or respiratory insufficiency, who are using a ResMed therapy device or home sleep test study device. The application enables patient usage data to be shared across several different user groups for the primary purpose of monitoring patient compliance and home sleep studies. Clinical users. Home Medical Equipment (DME) providers and other healthcare specialists can access data with ResMed approved user accounts. Also, clinical users and DMEs are able to address any clinical issues in a timely manner and provide the necessary patient support, including the modification of device settings. EasyCare Online supports physicians in the diagnosis Sleep Disordered Breathing, by reviewing home sleep test results via their web browser or download the clinical data to their PC for further analysis.

Here's an analysis of the provided text regarding the acceptance criteria and study for the EasyCare Online device:

This 510(k) submission is for an expanded intended use of an existing device (EasyCare Online, K123557) by integrating functionality from another predicate device (ApneaLink Plus, K083575). Therefore, the "study" primarily focuses on demonstrating that the new integration does not negatively impact the existing functionality and accurately displays data from the newly integrated device. It does not involve a traditional clinical study for the diagnostic accuracy of the device itself.

Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly derived from the comparison to the predicate devices and the successful completion of non-clinical testing. The "reported device performance" is essentially the successful completion of verification activities.

Study Details

1. A table of acceptance criteria and the reported device performance:
Provided above.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

• Test Set Sample Size: "Three patient breathing pattern scripts" were used for the side-by-side testing.
• Data Provenance: Not explicitly stated. The scripts likely represent simulated or standardized data rather than individual patient data from a specific country or collected prospectively/retrospectively in a clinical setting.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

• This submission does not involve human expert adjudication of diagnostic outcomes. The "ground truth" for the side-by-side testing was the output of the predicate ApneaLink Plus PC software. The study's goal was to ensure the modified EasyCare Online replicated this known output accurately. Therefore, no external experts were used to establish ground truth in the traditional sense of a clinical diagnostic study.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

• None (in the context of human adjudication). The "adjudication" was a direct comparison of output data between the modified device and the predicate device's software.

5. If a multi-reader, multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

• No. This was not an MRMC study. The device is a data management and display system, not a diagnostic AI system intended for direct human assistance in interpretation in the way a typical diagnostic image analysis AI would be.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

• Yes, in spirit. The core of the "testing" was comparing the data processing and display capabilities of the modified EasyCare Online (algorithm/software only) against the known output of the predicate ApneaLink Plus PC software (also algorithm/software only). The "standalone" performance here refers to the software's ability to process and present data identically to an established, cleared device.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

• The "ground truth" for the side-by-side testing was the output of the predicate ApneaLink Plus PC software (K083575). This means the existing, cleared device's performance served as the benchmark for accuracy for the data processing and display component. This is often referred to as "reference standard" or "comparator device" in such equivalence studies.

8. The sample size for the training set:

• Not applicable / Not explicitly stated. This submission does not describe the development of a novel algorithm that requires a "training set" in the machine learning sense. The changes primarily involved integrating existing functionalities and ensuring data integrity.

9. How the ground truth for the training set was established:

• Not applicable. As no training set for a novel algorithm was described, this question is not relevant to this submission. The "ground truth" for the device's expanded functionality was anchored to the performance of its predicate devices.

Ask a specific question about this device

The S9 VPAP Tx is indicated for the treatment and titration of patients with obstructive sleep apnea (OSA), respiratory insufficiency, central or mixed apneas, or periodic breathing. CPAP, S, ST, T and PAC modes are indicated for patients weighing more than 30lb (13 kg); all other modes are indicated for patients weighing more than 66lb (30 kg).

The S9 VPAP Tx is intended to be used in a clinical environment.

The S9 VPAP Tx is similar to the predicate devices VPAP ST-A (K113288), VPAP ST (K102513), S9 VPAP Adapt (K113801) and S8 Aspen (K091947).

The S9 VPAP Tx provides CPAP, Auto-titrating, Bilevel, VAuto and ASV modes to treat OSA and/or respiratory insufficiency, central or mixed apneas or periodic breathing. This is achieved through the use of a micro-processor controlled blower system that generates airway pressures as required to maintain an "air splint" for effective treatment of OSA and/or respiratory insufficiency.

The S9 VPAP Tx system comprises the flow generator, patient tubing, mask (patient interface) and optional H5i humidifier.

The performance and functional characteristics of the S9 VPAP Tx includes all the clinician and user friendly features of the predicate devices, VPAP ST-A (K113288), VPAP ST (K102513), S9 VPAP Adapt (K113801) and S8 Aspen (K091947).

Here's an analysis of the ResMed S9 VPAP Tx 510(k) submission based on the provided text, focusing on the absence of information regarding "acceptance criteria" and a "study that proves the device meets the acceptance criteria" in the traditional sense of an AI/ML medical device submission.

The provided document is a 510(k) summary for the ResMed S9 VPAP Tx, a continuous ventilator. It does NOT describe an AI/ML device or any study that would typically be associated with performance criteria for an algorithmic diagnostic or prognostic tool. Instead, it describes a hardware medical device and its substantial equivalence to previously cleared predicate devices.

Therefore, many of the requested points, such as "acceptance criteria and reported device performance" related to an AI/ML algorithm, sample sizes for test sets, data provenance, expert ground truth, MRMC studies, or standalone algorithm performance, are not applicable to this submission.

The submission focuses on demonstrating compliance with recognized standards for medical electrical equipment and biocompatibility, as well as the substantial equivalence of the new device to existing predicate devices based on intended use, operating principle, technology, and manufacturing process.

Summary regarding Acceptance Criteria and Study for ResMed S9 VPAP Tx (K123511):

This 510(k) submission is for a continuous ventilator (S9 VPAP Tx), which is a hardware medical device, not an AI/ML device. As such, the concept of "acceptance criteria" and "study that proves the device meets the acceptance criteria" within the context of AI/ML performance (e.g., sensitivity, specificity, AUC) is not applicable to this submission.

The document states:

• "Design and Verification activities were performed on the S9 VPAP Tx as a result of the risk analysis and design requirements. All tests confirmed the product met the predetermined acceptance criteria."
• "The S9 VPAP Tx has been tested to appropriate FDA consensus standards and other applicable requirements passing all test protocols."

This indicates that internal design verification and validation activities were conducted based on engineering specifications and compliance with relevant safety and performance standards for hardware medical devices. These are not performance metrics for an AI algorithm.

Addressing the specific points based on the provided text, noting irrelevance where appropriate for an AI/ML context:

1. A table of acceptance criteria and the reported device performance

   • Not Applicable in an AI/ML context. The document does not provide a table of performance metrics (like sensitivity, specificity) for an AI/ML component. The "acceptance criteria" here refers to the passing of various engineering and safety standards.
   • Relevant information from document: The device was tested according to:
     • IEC 60601-1-2:2007 (Electromagnetic compatibility)
     • IEC 60601-1:2005 (General requirements for safety and essential performance)
     • IEC 60601-1-8:2006 (Alarm systems)
     • ISO 10993 series (Biocompatibility)
   • Reported Device Performance: The document states "All tests confirmed the product met the predetermined acceptance criteria" and "passing all test protocols." No specific numerical performance results (e.g., for pressure delivery accuracy, flow rates) are provided in this summary, as these would typically be detailed in the full submission, not the summary.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

   • Not Applicable. This device is a hardware ventilator. There is no "test set" of patient data for evaluating an AI/ML algorithm as described in the prompt. The testing involved bench testing of the physical device. The document states: "Clinical data for the S9 VPAP Tx is not required as the predicate devices have been subjected to clinical trial requirements or validated patient simulation models have been used during the bench testing phases." This refers to physical models or simulated patient conditions, not patient data for algorithm training/testing.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

   • Not Applicable. This is not an AI/ML device. Ground truth as typically understood for AI/ML validation (e.g., expert consensus on image interpretation) is not relevant here.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

   • Not Applicable. This is not an AI/ML device.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

   • Not Applicable. This is not an AI/ML device and therefore no MRMC study involving human readers and AI assistance was conducted or would be relevant.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

   • Not Applicable. This device is a hardware ventilator, not an algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

   • Not Applicable in an AI/ML context. The "ground truth" for this device's testing would be established by the functional specifications and performance standards (e.g., a pressure sensor correctly measures the output pressure, the device delivers a specified flow rate). The "validated patient simulation models" mentioned refer to physical or mathematical models representing patient physiology for bench testing, not clinical ground truth derived from patients for an AI.

8. The sample size for the training set

   • Not Applicable. This device does not have a "training set" in the context of AI/ML.

9. How the ground truth for the training set was established

   • Not Applicable. This device does not have a "training set" or associated ground truth in the context of AI/ML.

In conclusion, the ResMed S9 VPAP Tx 510(k) submission is for a conventional medical device (ventilator) and does not contain information pertinent to the performance criteria or studies typically associated with AI/ML-enabled devices. The "predetermined acceptance criteria" and "test protocols" refer to engineering and safety standards, not AI algorithm performance metrics.

Ask a specific question about this device

EasyCare Online transfers and displays to clinicians, usage and therapeutic information that has been transmitted remotely from the patient's flow generator located in the home. EasyCare Online also provides remote settings capabilities.

EasyCare Online is intended to support the standard follow-up care of patients that have been prescribed a compatible ResMed flow generator for the treatment of obstructive sleep apnea or respiratory insufficiency.

EasyCare Online is a web application that can transfer, store, manage and display usage and therapy data from ResMed flow generators. The data is transferred from the flow generators either wirelessly through a communications module or with the aid of an SD card, to a central database and then displayed in a clinician computer, through a web application.

EasyCare Online is used to monitor and optimize the therapy of patients diagnosed with sleep apnea or respiratory insufficiency, who are using a ResMed therapy device. The application enables patient usage data to be shared across several different user groups for the primary purpose of monitoring patient compliance. Clinical users, Home Medical Equipment (HME) providers and other healthcare specialists can access data to monitor patient compliance. Also, clinical users and HMEs are able to address any noncompliance issues in a timely manner and provide the necessary patient support, including the modification of device settings.

The provided text is a 510(k) summary for the EasyCare Online device. It describes the device, its intended use, and argues for its substantial equivalence to previously cleared predicate devices. However, it does not contain a detailed study proving the device meets specific acceptance criteria with performance metrics, sample sizes, or information about ground truth establishment.

The document states:
"Design and non-clinical verification activities were performed on EasyCare Online as a result of the risk analysis and design process. Verification testing included end-to-end testing to verify data transfer integrity between the flow generator and EasyCare Online. All tests confirmed the product met the predetermined acceptance criteria."

This statement indicates that verification testing occurred and acceptance criteria were met, but it does not provide the details requested in your prompt.

Therefore, I cannot populate the table or provide specific details about the study, as they are not present in the provided text.

Based on the available information, here's what can be inferred and what cannot be determined:

Acceptance Criteria and Device Performance

Study Information (Based on available text)

1. Sample size used for the test set and the data provenance: Not specified in the provided text. The testing mentioned is "end-to-end testing to verify data transfer integrity," which sounds like functional verification rather than a clinical study with patient data.
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable/not specified. The testing described focuses on data transfer integrity, not diagnostic or therapeutic accuracy that would require expert-established ground truth on patient data.
3. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable/not specified.
4. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance: No. EasyCare Online is a data transfer and display system for clinicians, not an AI diagnostic or assistive tool that would involve human readers or MRMC studies.
5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: The "end-to-end testing to verify data transfer integrity" can be considered a standalone functional test, but it does not evaluate "performance" in the sense of clinical accuracy or decision-making.
6. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable. The "ground truth" for verifying data transfer integrity would likely involve comparing transmitted data against source data, rather than clinical ground truth.
7. The sample size for the training set: Not applicable. The device is a data management and display system, not a machine learning model that requires a training set.
8. How the ground truth for the training set was established: Not applicable.

Summary of what the document implies about the "study":

The "study" was primarily functional verification and non-clinical testing to ensure data transfer integrity and compatibility with new flow generator models. It was not a clinical effectiveness study assessing diagnostic accuracy or therapeutic outcomes, nor did it involve the use of AI algorithms on patient data that would necessitate the detailed ground truth and expert validation methods you've inquired about. The device is described as a system for transferring and displaying patient usage and therapeutic information, rather than a device making automated clinical decisions.

Ask a specific question about this device