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PREVENA 125 and PREVENA PLUS 125 Therapy Units manage the environment of closed surgical incisions and remove fluid away from the surgical incision via the application of -125mmHg continuous negative pressure. When used with legally marketed compatible dressings, PREVENA 125 and PREVENA PLUS 125 Therapy Units are intended to aid in reducing the incidence of seroma and, in patients at high risk for post-operative infections, aid in reducing the incidence of superficial surgical site infection in Class I and Class II wounds.

The PREVENA 125 and PREVENA PLUS 125 Therapy Units ("PREVENA pumps") are singleuse, compact and portable powered suction pumps. The therapy units are packaged with compatible sterile canisters (45 ml for PREVENA 125 or 150 ml for PREVENA PLUS 125) and sterile tubing set. The therapy units can be used with compatible, legally marketed wound dressings classified under 21 CFR 878.4780, such as the PEEL & PLACE dressing and the CUSTOMIZABLE dressing, which, when combined are referred to as the PREVENA Incision Management Systems ("PREVENA systems"). The PREVENA Incision Management Systems deliver a pre-set, continuous negative pressure of 125 mmHz to the incision site. The systems are intended to be applied to incision sites immediately after surgery for a minimum of 2 days up to a maximum of 7 days depending on the surgeon's preference. The therapy units can be used up to 192 hours, after which they will automatically shut off.

The provided text describes the regulatory evaluation of the PREVENA 125 and PREVENA PLUS 125 Therapy Units, focusing on clinical evidence from a systematic literature review and meta-analyses rather than a single, dedicated device performance study with specific acceptance criteria that would typically be seen for AI/ML devices. Therefore, a direct table of "acceptance criteria and reported device performance" as one might expect for a diagnostic AI/ML device is not explicitly present in the document.

However, based on the meta-analysis results and the FDA's granted indications for use, we can infer the "acceptance criteria" were met by demonstrating a favorable trend in reducing SSI and seroma, particularly in specific subgroups. The study essentially is the meta-analysis of existing clinical data.

Here's an interpretation of the information provided, structured to address your points, with explanations where direct parallels to AI/ML device criteria are not exact due to the nature of this submission (a device for wound therapy, not an AI/ML diagnostic).

Inferred Acceptance Criteria and Reported Device Performance (Based on Meta-Analysis Conclusion)

While explicit numerical acceptance criteria for a single study were not provided, the FDA's granting of the De Novo request signifies that the overall body of evidence from the meta-analysis met the regulatory standard for demonstrating safety and effectiveness for the specified indications. The "acceptance" was based on a "small but consistent trend" and "greater absolute percentage reduction" in specific high-risk populations.

• For Superficial Incisional SSI (all wounds analyzed for depth): OR of 0.19 (95% CI: 0.08, 0.46), showing a significant reduction. (5 studies)
• For Class I wounds: OR of 0.36 (95% CI: 0.24, 0.55) for overall SSI, consistent reduction. (11 studies)
• For Class II wounds: OR of 0.27 (95% CI: 0.11, 0.68) for overall SSI, consistent reduction. (3 studies)
• For high-risk patients (overall SSI): OR of 0.40 (95% CI: 0.27, 0.62). Greater absolute percentage reduction observed (5.5% in treatment vs. 12.9% in control vs. 4.2% vs. 5.8% in overall). (9 studies) |
  | Device demonstrates acceptable safety profile. | Similar Safety Profile to Conventional Dressings: No significant differences in Adverse Events (AEs) or Serious Adverse Events (SAEs) between PREVENA and control groups in the 3 studies that reported this data. Post-market data (7 years, hundreds of thousands of units shipped) consistent with anticipated AEs (skin irritation, blisters, pain, etc.), and no device-related SAEs. |
  | Non-clinical performance (pressure maintenance, exudate removal, alarms). | Device capable of maintaining -125±25 mmHg, removing simulated wound fluid, and alarms function as intended under worst-case scenarios. |
  | Usability demonstrated. | Usability testing showed intended users can operate the device (reviewed from prior 510(k) K141017). |

Study Details:

1. Sample sizes used for the test set and the data provenance:

   • Test Set Sample Size:
     • For SSI meta-analysis: 20 prospective studies, total of up to 6,403 evaluable patients (1,367 in PREVENA group, 5,036 in control group).
     • For Seroma meta-analysis: 7 prospective studies, total of 952 evaluable patients (366 in PREVENA group, 586 in control group).
   • Data Provenance: The data comes from a systematic literature review and meta-analyses of published and unpublished prospective clinical studies. The geographic origin of these individual studies is not explicitly stated but implied to be global as it's a literature search. The studies are prospective. Seven articles identified as retrospective were removed to minimize bias.

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

   • Study Selection/Ground Truth Establishment:
     • Study Selection: Six (6) independent reviewers performed the initial study selection. A subset of two (2) independent reviewers assessed abstracts and manuscripts for inclusion/exclusion criteria. When discordance was identified, these two reviewers deliberated until a consensus was reached.
     • Characteristic Extraction: At least two additional independent reviewers extracted study characteristics.
     • Wound Classification (Ground Truth for Subgroup Analysis): CDC wound classification was assigned to each study by "two individuals with appropriate medical and clinical trials background."
   • Qualifications: The specific qualifications (e.g., number of years of experience, board certification) of these reviewers/experts are not detailed beyond "independent reviewers" and "individuals with appropriate medical and clinical trials background."

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

   • Study Selection: "When discordance was identified, the two reviewers deliberated until a consensus was reached." This suggests a consensus-based adjudication among the two reviewers, rather than a third expert "tie-breaker" (2+1).
   • Wound Classification: "a CDC wound classification was assigned by two individuals with appropriate medical and clinical trials background." It is implied a consensus or adjudication method was used if there was disagreement, but not explicitly stated.

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, an MRMC study was NOT done. This submission is for a medical device (a wound therapy unit), not an AI/ML diagnostic or assistive technology for human readers. The study is a meta-analysis of clinical trials comparing the device to conventional wound dressings. Therefore, the concept of "human readers improving with AI assistance" is not applicable here.

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

   • Not applicable. This is a physical wound therapy device, not a standalone algorithm. Its performance is evaluated in a clinical context on patients.

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

   • The "ground truth" for effectiveness (reduction in SSI and seroma) was the clinical outcomes data reported directly by the individual prospective studies included in the meta-analysis. These outcomes were typically assessed by the clinical investigators of each respective study.

7. The sample size for the training set:

   • Not applicable. This is a device, not an AI/ML model that requires a training set. The "training data" in a broader sense would be all the accumulated medical knowledge and device design iterations that led to the PREVENA system. The studies reviewed form the evidence base for its effectiveness, not a training set for an algorithm.

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

   • Not applicable. As stated above, there is no AI/ML training set in this context.

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The Prevena Incision Management System is intended to manage the environment of surgical incisions that continue to drain following sutured or stapled closed by maintaining a closed environment and removing exudate via the application of negative pressure wound therapy.

Negative pressure wound therapy system

The provided document is a 510(k) premarket notification for a medical device (Prevena Incision Management System). It does not describe a study involving an AI/Machine Learning device or outline particular acceptance criteria usually associated with such devices (e.g., sensitivity, specificity, AUC). Instead, it discusses the substantial equivalence of the device to a predicate device, focusing on functional and safety aspects for a medical device.

Therefore, I cannot extract the acceptance criteria, study details, sample sizes, expert qualifications, adjudication methods, MRMC study results, standalone performance, or ground truth information relevant to an AI/ML device from the provided text.

The document primarily focuses on:

• Device Description and Indications for Use: The Prevena Incision Management System manages surgical incisions by maintaining a closed environment and removing exudate via negative pressure wound therapy.
• Comparison to Predicate Device: The current device is substantially equivalent to a previously cleared Prevena Incision Management System (K121883). The core technology (negative pressure wound therapy) and primary components are the same.
• Technological Differences: Minor changes were made to the software to reduce "nuisance alerts" related to the Leak Alert and Low Battery Alert mute times and a slight increase in the air leak threshold.
• Non-Clinical Testing: Bench tests were conducted to confirm the therapy unit delivers negative pressure within specifications, software verification and validation, and battery life testing.
• Clinical Testing: No clinical tests were deemed necessary for substantial equivalence. However, usability testing was conducted with patient users to assess the impact of labeling changes due to software modifications, and all usability goals were met.

In summary, this document is for a traditional medical device demonstrating substantial equivalence, not an AI/ML device.

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The ciSNaP® Closed Incision System is indicated for patients who would benefit from wound management via the application of negative pressure, particularly as the device may promote wound healing through the removal of small amounts of exudate from surgical incisions that continue to drain following sutured or stapled closure.

The ciSNaP® Closed Incision System ("ciSNaP System") is a new addition to Spiracur Inc.'s ("Spiracur") family of negative pressure wound management devices. The ciSNaP System is a portable, non-powered, disposable Negative Pressure Wound Therapy ("NPWT") system that is intended for wound management through the removal of small amounts of exudate from surgically closed incisions. The ciSNaP System utilizes the concept of forced expansion of volume to produce negative pressure at the closed incision. The ciSNaP System can be applied in the sterile field. The ciSNaP System has no electrically powered parts and is disposable after use. Additionally, it is capable of delivering negative pressure wound therapy at a near-constant pressure level over several days without any required adjustments by the patient or clinician. The dressing component of the ciSNaP System incorporates an antimicrobial interface.

The provided text describes the acceptance criteria and the study that proves the device meets the acceptance criteria for the ciSNaP® Closed Incision System.

Here's the breakdown of the information requested:

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

4.3 for MRSA
4.5 for VRE
4.4 for Escherichia coli
4.1 for Pseudomonas aeruginosa
4.3 for Klebsiella pneumoniae
4.3 for Candida albicans
3.2 for Aspergillus brasiliensis |
| Antimicrobial Log Reduction (Day 3) | >4.4 for Staphylococcus aureus
4.3 for MRSA
4.6 for VRE
4.4 for Escherichia coli
4.1 for Pseudomonas aeruginosa
4.2 for Klebsiella pneumoniae
4.2 for Candida albicans
3.2 for Aspergillus brasiliensis |
| Antimicrobial Log Reduction (Day 7) | >4.1 for Staphylococcus aureus
4.2 for MRSA
4.6 for VRE
4.3 for Escherichia coli
4.4 for Pseudomonas aeruginosa
4.4 for Klebsiella pneumoniae
4.1 for Candida albicans
3.6 for Aspergillus brasiliensis |
| Equivalence to predicate devices (intended use and technology) | Nonclinical performance test results demonstrate the ciSNaP System performs equivalently to predicate devices and is as safe and effective. |
| No new issues of safety or effectiveness | Differences in technological characteristics do not raise any new issues of safety and effectiveness. |

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

The provided text does not specify sample sizes for human subjects or clinical data in the "test set" as the studies described are nonclinical, bench testing. The antimicrobial log reduction tests were conducted on "samples of the silverplated skin interface layer" and "silverplated samples" (of the ciSNaP® Controlled Tension Relief Layer). The exact number of samples tested for each organism or time point is not provided.

The provenance (country of origin, retrospective/prospective) is not applicable or provided as these are in vitro laboratory tests.

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 information is not applicable to the provided document. The studies described are nonclinical, bench tests, and in vitro antimicrobial log reduction tests. These types of tests do not typically involve human experts establishing ground truth in the way a clinical study or imaging study would. The 'ground truth' for these tests would be the measured physical, chemical, or biological properties and performance against established standards (e.g., ISO 10993-1 for biocompatibility, or microbial counts for antimicrobial efficacy).

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

This information is not applicable to the provided document. As mentioned above, the studies are nonclinical bench tests and in vitro antimicrobial tests, which do not typically involve adjudication methods for human interpretation.

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 MRMC comparative effectiveness study was done. The document solely describes nonclinical bench testing and in vitro antimicrobial tests. There is no mention of human readers, AI assistance, or clinical comparative effectiveness studies.

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

This is not applicable. The device is a physical medical device (negative pressure wound therapy system), not an AI algorithm. Therefore, "standalone" performance in the context of an algorithm is not relevant. The in vitro antimicrobial tests represent the standalone performance of the silver-plated material's antimicrobial properties.

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

The ground truth for the nonclinical tests was based on:

• Design specifications and verification testing: For appropriate design characteristics.
• ISO 10993-1 standards: For biocompatibility.
• Product specifications: For packaging and shelf life.
• Measured silver ion availability: For ion release rate.
• Microbial counts of control samples: For antimicrobial log reduction tests (comparing silver-plated samples to unplated controls).

8. The sample size for the training set

This information is not applicable. The document describes nonclinical testing and does not mention any machine learning or AI models with training sets.

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

This information is not applicable, as there is no mention of a training set for machine learning or AI models.

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