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The Reza Band® UES Assist Device is indicated for patients 18 years and older to reduce the symptoms of larvngopharyngeal reflux (LPR) disease by reducing the regurgitation of stomach contents from passing through the upper esophageal sphincter. The device is worn by the patient when sleeping.

The Reza Band® UES Assist Device (Reza Band) (Figure 1) is a non-invasive, non-sterile device worn by the patient and is designed to provide a set pressure (20-30 mm Hg) on the cricoid cartilage, which increases the luminal pressure within the upper esophageal sphincter (UES). The patient wears the Reza Band after being fit by the physician (Figure 2).

The Reza Band has 5 main components:

• Frame
• Cushion
• Comfort Band
• Clasp
• Comfort Dial

The Reza Band® External Manometer (External Manometer) is a hand-held device and is connected to the Reza Band® Pressure Sensor (Pressure Sensor). It is used by the treating physician, is powered by a AAA battery and displays the pressure being applied to the cricoid cartilage region by the Reza Band in millimeters of Mercury (mm Hg) as the Reza Band® is being fitted (Figure 3).

The Pressure Sensor connected to the External Manometer is regulated as a miniature pressure transducer (21 CFR Part 890.1615) which is Class I exempt. The Pressure Sensor and the External Manometer were assessed to ensure that the Reza Band® was accurately applying the specified pressure.

The Reza Band® Upper Esophageal Sphincter (UES) Assist Device did not undergo a study that assessed its performance against specific, pre-defined acceptance criteria with a quantifiable metric (e.g., accuracy, sensitivity, specificity). Instead, the studies focused on demonstrating the safety and effectiveness of the device.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

As mentioned, there isn't a direct table of "acceptance criteria" where a specific quantitative metric (like accuracy or AUC) is listed alongside a target value and then the device's performance against that target for a classification task. The studies provided focus on demonstrating safety and symptomatic improvement.

Bench Test Acceptance Criteria and Results (from Table 2):

Clinical Study Effectiveness Endpoint (from Study #1):

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

• Study #1 (Clinical Effectiveness Study):

  • Sample Size:
    • Enrolled: 95 patients
    • Analyzed for Effectiveness: 89 patients (who wore the device for at least 2 weeks and provided one post-baseline RSI assessment). 6 subjects discontinued and were excluded from this specific effectiveness analysis, but a worst-case sensitivity analysis confirmed no impact on treatment effect.
  • Data Provenance: Prospective, multi-center (5 investigational sites). Country of origin is not explicitly stated, but implicitly US given the FDA submission context.

• Study #2 (Safety of Intentionally Displaced Device):

  • Sample Size: 20 subjects
  • Data Provenance: Prospective. Country of origin not explicitly stated, but implicitly US given the FDA submission context.

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

This information is not explicitly provided in the document for either study.

• Study #1: The primary effectiveness endpoint, Reflux Symptom Index (RSI), is a "validated nine-item, patient-administered outcome questionnaire." This suggests the ground truth for effectiveness is based on patient-reported outcomes, rather than expert assessment of the RSI score itself. Clinical diagnosis of LPR was made by healthcare professionals, but the evaluation of effectiveness relied on the patient-completed RSI.
• Study #2: Ground truth for safety was established by direct physiological measurements (heart rate, blood pressure, cardiac rhythm, IOP). These are objective measurements, not requiring expert consensus for ground truth establishment in the dataset.

4. Adjudication Method for the Test Set

Not applicable to these studies as the primary endpoints are either patient-reported (RSI) or direct physiological measurements, not requiring expert adjudication of a "test set" in the context of diagnostic performance.

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 comparative effectiveness study was not done. This device is not an AI/diagnostic imaging device, so this type of study is not relevant.

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

Not applicable. The Reza Band is a physical medical device, not an algorithm. Its performance is tied to its physical application and effect on the patient.

7. The Type of Ground Truth Used

• Study #1 (Effectiveness): Patient-reported outcomes (Reflux Symptom Index - RSI). The RSI is a validated questionnaire.
• Study #2 (Safety in Displaced Position): Objective physiological measurements (heart rate, blood pressure, cardiac rhythm, intraocular pressure).

8. The Sample Size for the Training Set

Not applicable. The Reza Band is a physical medical device. It does not utilize machine learning or AI models that require a "training set" in the conventional sense. The "training" of the device itself refers to its design, testing, and refinement, not an algorithmic training process.

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

Not applicable, as there is no "training set" for an AI algorithm.

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The intended use of the Sonic Palpometer is to assess patient sensitivity to tactile stimulus by providing quantification of fingertip pressure, for tactile response procedures and freatments that use digital palpation.

The Palpometer is a simple device that combines the fine motor and sensory attributes of manual examination with the precision measurements made with pressure gauges. By measuring the amount of pressure between the device and a soft tissue, the Palpometer standardizes pain response by controlling the pressure of the examiner's palpating finger. The Palpometer consists of a thin sensor, positioned on the palpating portion of the examiner's finger. The sensor changes its electrical resistance caused by varying the pressure exercised by the examining finger. The Palpometer beeps in a different tone as you pass through each programmable pressure threshold (of which there are five).

The Palpometer is a device designed to quantify fingertip pressure during digital palpation to assess patient sensitivity to tactile stimuli. The provided documentation (K060125) describes the device and references several studies to demonstrate its equivalence and performance relative to conventional pain measurement methods.

Here's an analysis of the acceptance criteria and the studies mentioned:

1. Table of Acceptance Criteria and the Reported Device Performance

The submission does not explicitly state formal "acceptance criteria" with specific quantitative thresholds that the device must meet for approval. Instead, it presents a summary of "Substantial Equivalence Data" by comparing the Palpometer's performance with established methods of pain measurement found in published literature. The reported performance focuses on correlations, reliability, and differences in statistical significance.

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

The document references several published research papers and abstracts rather than a single dedicated test set for the FDA submission. Therefore, the sample sizes and data provenance vary across the cited studies:

• Atkins, C. J. et al. (1992): "An electronic method for measuring joint tenderness in rheumatoid arthritis."
  • Sample Size: Not specified in the provided summary, would require consulting the original paper.
  • Data Provenance: Not specified in the provided summary (likely prospective, clinical study as typical for such research).
• Bendtsen, L., Jensen, R., Jensen, N.K. and Olesen, J.R. (1995): "Pressure controlled palpation: A new technique which increases the reliability of manual palpation."
  • Sample Size: Not specified in the provided summary, would require consulting the original paper.
  • Data Provenance: Not specified in the provided summary (likely prospective, clinical study).
• Bennet, R., Atkins, C.J., Zielinski, A., and Makosinski, A. (1996): "A miniaturized pain-measuring device called an electronic Palpometer worn on the examiner's finger links a pressure gauge to conventional manual palpation."
  • Sample Size: Not specified in the provided summary, would require consulting the original abstract/paper.
  • Data Provenance: Collaborative study between University of Victoria (Canada) and Oregon Health Sciences University (USA). Likely prospective.
• Bendsten, L., Norregaard, J., Jensen, R., Olesen, J. (1997): "Evidence of qualitatively altered nociception in patients with fibromyalgia."
  • Sample Size: Not specified in the provided summary, would require consulting the original paper.
  • Data Provenance: Not specified in the provided summary (likely prospective, clinical study).
• Neufeld, J.D., Holroyd, K.A., and Lipchik, G.L. (2000): "Dynamic assessment of abnormalities in central pain transmission and modulation in tension-type headache sufferers."
  • Sample Size: Not specified in the provided summary, would require consulting the original paper.
  • Data Provenance: Not specified in the provided summary (likely prospective, clinical study).
• Bendtsen, L., Jensen, R., Jensen, N.K. and Olesen, J.R. (1994): "Muscle palpation with controlled finger pressure: New equipment for the study of tender myofascial tissues."
  • Sample Size: Not specified in the provided summary, would require consulting the original paper.
  • Data Provenance: Not specified in the provided summary (likely prospective, clinical study).
• Puttick, M.P.E., et al. (1995): "Reliability and reproducibility of fibromyalgic tenderness: measurement by electronic and mechanical dolorimeters."
  • Sample Size: Not specified in the provided summary, would require consulting the original paper.
  • Data Provenance: Not specified in the provided summary (likely prospective, clinical study).
• Atkins, C.J., and Zielinski, A. (1997): "Comment on Article by Puttick, M.P.E., et al."
  • Sample Size: N/A (commentary on a previous study).
  • Data Provenance: N/A (commentary).

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

The concept of "ground truth" in these studies is primarily clinical observation and assessment by human examiners, often involving measurement techniques (conventional palpation, other dolorimeters, VAS scores). The studies focus on comparing the Palpometer's measurements to these human-derived "ground truths" or benchmarks.

• The studies often involve "observers" or "examiners" (e.g., "two different observers" in Bendtsen et al. 1995).
• The qualifications of these experts are not explicitly stated in the summary, but they are implied to be medical professionals (e.g., those experienced in rheumatoid arthritis, headache, or fibromyalgia assessment) contributing to clinical research published in medical journals. Without access to the full papers, specific qualifications (e.g., "radiologist with 10 years of experience") cannot be determined.

4. Adjudication Method for the Test Set

The provided summaries of the studies do not explicitly detail adjudication methods for disagreements between observers.

• Bendtsen et al. (1995) does note that "the sum of tenderness scores recorded by two different observers using conventional palpation differed significantly (P=0.0003) where results did not differ using pressure controlled palpation (P=0.89)." This implies a comparison of agreement rather than a formal adjudication process to resolve discrepancies, likely using statistical methods.
• Other studies focus on correlations and reliability metrics, which inherently account for agreement/disagreement without necessarily requiring a separate adjudication step to define a single "ground truth."

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, a MRMC comparative effectiveness study was not done in the context of an AI-assisted interpretation versus unassisted human interpretation.
• The Palpometer itself is a diagnostic tool that standardizes the human act of palpation, providing objective pressure measurements. It is not an AI algorithm that assists in interpretation of medical images or data.
• The studies instead compare the Palpometer-assisted palpation method to conventional manual palpation or other dolorimeters.
  • Effect Size Example: In Atkins et al. (1992), the Palpometer reduced intraobserver error from 0.2 (conventional) to 0.12, and increased the correlation coefficient from 0.62 to 0.78. This indicates an improvement in objective measurement and reliability when using the device compared to unassisted manual palpation.

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

• Not applicable. The Palpometer is a human-in-the-loop device. It is designed to be worn on an examiner's finger to quantify the pressure they apply during palpation. It does not operate as a standalone algorithm without human interaction. Its function is to enhance and standardize the human examination process.

7. The Type of Ground Truth Used

The "ground truth" in these studies is primarily established through:

• Expert Clinical Assessment / Conventional Measurements: This includes traditional manual palpation scores, tender joint scores, tender point scores, and Visual Analog Scale (VAS) scores for pain.
• Other Standardized Measurement Devices: Comparisons are made to other dolorimeters and algometers (e.g., Pressore Monitor, micro-emed-system, Dynatron 2000, Somedic pressure algometer, Chatillon dolorimeter). These devices are themselves established as tools for quantifying pressure or pain thresholds.
• Physiological Relationships: For example, the discovery of a "linear relationship between pressure and pain in a double logarithmic plot" (Bendsten et al., 1997) serves as a biological ground truth expectation against which the device's measurements are validated.

8. The Sample Size for the Training Set

• Not applicable / Not explicitly defined. The Palpometer is a hardware device with an embedded microprocessor and programmed thresholds. It does not appear to use machine learning or AI that would require a "training set" in the conventional sense for an algorithm.
• The "programming" of its five pressure thresholds would likely be based on engineering specifications and potentially clinical input, but not iterative learning from a large "training set" of data.

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

• Not applicable. As explained above, there is no conventional machine learning "training set" for an algorithm. The device's operational parameters (e.g., pressure thresholds for different tones) would be established through engineering design, calibration against known physical pressures, and potentially clinical validation relating these pressure levels to clinically relevant palpation forces.

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