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The extriCARE® 1000 NPWT System is intended to generate negative pressure to remove wound exudates, infectious material, and tissue debris from the wound bed.

The extriCARE® 1000 NPWT System is intended for use in wounds with low to moderate levels of exudate. Appropriate wound types include:

• Chronic wounds
• Acute wounds
• · Traumatic wounds
• · Subacute and dehisced wounds
• · Partial-thickness burns
• · Ulcer wounds (such as diabetic or pressure)
• · Flaps and grafts
• · Closed surgical incisions

The extriCARE 1000 NPWT System is intended for use in healthcare facilities.

The extriCARE 1000 Negative Pressure Wound Therapy (NPWT) system consists of a portable, battery-powered pump unit intended to generate vacuum pressure to remove low to moderate level of wound exudates, infectious material, and tissue debris from the wound bed. Three preset vacuum pressures can be selected by the user - 80, 100, and 125mmHg. The extriCARE 1000 is packaged and provided with the following components:

• 1. extriCARE 1000 Negative Pressure Wound Therapy Pump
• 2. extriCARE 1000 50cc Collection Canister

The extriCARE 1000 Negative Pressure Wound Therapy (NPWT) Pump accessory that is included in this 510(k) applications and will be commercialized separately is the extriCARE 1000 50cc Collection Canister (additional cannister replacements).

The provided document describes the extriCARE® 1000 Negative Pressure Wound Therapy System and its substantial equivalence to predicate devices, rather than a study with specific acceptance criteria, performance metrics, and a dedicated test set as typically found in AI/ML performance evaluations.

Therefore, many of the requested fields cannot be directly extracted from the provided text because the document does not detail a clinical or performance study in the way a medical device utilizing AI/ML would. The document focuses on regulatory clearance for a physical medical device (a negative pressure wound therapy system) based on its technological characteristics, intended use, and non-clinical testing demonstrating safety and performance.

However, I can extract information related to the non-clinical testing performed and the general claims of performance the device makes.

Here's the closest possible interpretation of your request based on the provided text:

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

The document categorizes "non-clinical testing" as proof of meeting internal standards and regulations and having performance characteristics substantially equivalent to predicate devices. Specific quantitative acceptance criteria are not explicitly stated as numerical targets, but the "Results" कॉलम indicates success.

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

This information is not provided in the document. The non-clinical tests described are likely laboratory-based and do not involve "test sets" in the context of patient data for AI/ML evaluation.

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

This information is not applicable/provided. The evaluation is for a physical medical device, not an AI/ML algorithm requiring expert ground truth in the traditional sense.

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

This information is not applicable/provided. Adjudication methods are typically relevant for human review of AI/ML outputs, which is not the subject of this 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

This information is not applicable/provided. This document concerns a standalone medical device (Negative Pressure Wound Therapy System), not an AI-assisted diagnostic tool that would involve human readers.

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

The document mentions "Software Verification and Validation" for the device's proprietary algorithm, stating it was completed and had no unresolved anomalies. The software was determined to be of a "moderate" level of concern. While this confirms standalone software performance was evaluated, it's not in the context of an AI/ML diagnostic algorithm making predictions requiring human review. It pertains to the control software of the NPWT pump.

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

For the functional performance testing and electrical safety/EMC testing, the "ground truth" would be established by engineering standards, regulatory requirements (e.g., IEC standards), and internal specifications for the device's operation. For the software verification and validation, the ground truth would be the software requirements specifications and expected behavior to ensure the device operates safely and effectively. This is not "ground truth" in the clinical sense of pathology or expert consensus on a medical finding.

8. The sample size for the training set

This information is not applicable/provided. This device is not described as involving an AI/ML model that is trained on a dataset. The software mentioned is control software, not a learning algorithm.

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

This information is not applicable/provided. As above, there is no mention of a training set or AI/ML model development.

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