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The Hem-Avert® Perianal Stabilizer provides counter-pressure to the anus during vaginal childbirth. This counter-pressure force, applied at 8-10 cm of dilation, is intended to help reduce the likelihood of cesarean delivery. Additionally, this counter-pressure force helps prevent the occurrence of external hemorrhoids during vaginal childbirth.

This is a single use, disposable, sterile device. The Hem-Avert Perianal Stabilizer (Hem-Avert) consists of three components:

• 1. Rigid polymer base manufactured from a polycarbonate
• 2. Centrally located cushioning pad composed of a laminate of polyester non- woven tape and polyethylene foam tape
• 3. Two lateral hook and loop adhesive strips (with liners) which provide the tension required to keep the device firmly in place during delivery.

This request pertains to the HEM-AVERT® PERIANAL STABILIZER, a medical device, and not an AI/ML device. Therefore, typical acceptance criteria and study designs relevant to AI/ML devices (e.g., ground truth established by experts, MRMC studies, standalone performance) are not applicable in their usual form.

However, I can extract the relevant acceptance criteria (special controls and risks to health) and how the device's performance was proven through clinical studies, focusing on the reduction of cesarean delivery, sterility, and biocompatibility.

Here's a summary of the acceptance criteria and the study results, rephrased to fit the structure where applicable, with explanations for non-applicability for certain AI/ML-specific questions:

Acceptance Criteria and Reported Device Performance for HEM-AVERT® PERIANAL STABILIZER

1. Table of Acceptance Criteria and the Reported Device Performance

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

• This device is not an AI/ML diagnostic, so the concept of a "test set" for algorithm evaluation isn't directly applicable. Instead, there were two clinical studies (human participant trials) evaluating the device's effectiveness and safety.

  • Niagara Falls Memorial Medical Center Study (Primary Effectiveness Data):

    • Sample Size: 102 patients initially enrolled, 98 patients included in analysis (50 in device arm, 48 in control arm).
    • Data Provenance: Prospective, randomized, single-site clinical study. The country of origin is not explicitly stated but implied to be the US (based on FDA submission and standard practices for such studies).

  • Dignity Health Clinical Study (Supportive Effectiveness Data):

    • Sample Size:
      • Baseline Retrospective Chart Review: 521 subjects.
      • Observational Study Period: 799 consecutive patients delivered, 790 with complete data. 500 met inclusion criteria, resulting in 227 subjects in the Hem-Avert group and 273 subjects in the control arm.
    • Data Provenance: Single-site, observational study (phased introduction). It included a baseline retrospective chart review followed by a prospective observational period. Country of origin not explicitly stated but implied to be the US.

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

• This question is not applicable as the device is not an AI/ML system that requires "ground truth" derived from expert interpretation of data like images or signals.
• The outcomes measured (e.g., cesarean delivery, adverse events, perineal lacerations) are clinical endpoints determined by medical professionals (obstetricians, nurses) as part of standard medical practice during labor and delivery, and recorded in patient charts. The "ground truth" is the clinical outcome itself, as documented.

4. Adjudication Method for the Test Set

• Not applicable for a medical device clinical trial in the same way it would be for an AI/ML diagnostic where expert disagreement needs reconciliation.
• Clinical outcomes were recorded as per standard medical practice and study protocols. For the Niagara Falls study, it was a randomized controlled trial, and outcomes were objectively recorded. For the Dignity Health study, it was an observational study with data extracted from electronic health records. Any adjudication would have been part of the clinical study design for recording adverse events or primary endpoints, not for resolving disagreements in "ground truth interpretation" of an AI output.

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 a physical medical device, not an AI/ML diagnostic system. There are no "human readers" or "AI assistance" in the context of this device. The studies directly measure the clinical outcome in patients using the device versus a control group.

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

• Not applicable. This is a physical medical device. It does not involve an "algorithm only" or "human-in-the-loop performance." The device is intended for direct application by a healthcare professional.

7. The Type of Ground Truth Used

• Not applicable in the context of AI/ML "ground truth" (e.g., expert consensus on an image).
• The "ground truth" for the clinical studies was the actual clinical outcome as per best medical practice and documentation, such as:
  • Occurrence/non-occurrence of cesarean delivery.
  • Occurrence/type of adverse events (e.g., fetal bradycardia, hemorrhoids, perineal lacerations).
  • Duration of labor stages.
  • As assessed and documented by treating physicians and medical staff.

8. The Sample Size for the Training Set

• Not applicable. This is a physical medical device and does not have a "training set" in the context of AI/ML model development.

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

• Not applicable, as there is no AI/ML training set.

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