Search Results

The Nikomed USA electrosurgical grounding pad (sold under various commercial names through repackagers and resellers) is indicated for use with electrosurgical generators for cutting and coagulation.

The Nikopad Electrosurgical Grounding Pad is a flexible, conductive adhesive electrosurgical grounding pad with integrated 3 meter transparent cable and standard US 2-female connector. The conductive area is 143 sq cm and the adhesive area is 242 sq cm. Units are packaged individually and typically sold 25 pieces to a box.

This document describes a 510(k) submission for the Nikomed Electrosurgical Grounding Pad. However, the provided text does not contain detailed acceptance criteria or a study design with specific performance metrics (like sensitivity, specificity, AUC, etc.) that are typically associated with AI/ML device evaluations.

The submission is for a medical device that appears to be a passive electrosurgical grounding pad, not an AI/ML-driven diagnostic or therapeutic device. The "SUMMARY of TESTING" section only mentions biocompatibility testing.

Therefore, many of the requested items (e.g., acceptance criteria for diagnostic performance, sample size for test set, number of experts for ground truth, MRMC studies, standalone performance) are not applicable or cannot be extracted from this particular document.

Here's an attempt to answer the questions based on the provided text, highlighting where information is missing or not applicable:

Description of Acceptance Criteria and Study for Nikomed Electrosurgical Grounding Pad

This 510(k) submission is for a traditional medical device (an electrosurgical grounding pad), not an AI/ML diagnostic or therapeutic device. Consequently, the "acceptance criteria" and "study" described herein are primarily focused on safety, fundamental device function, and substantial equivalence to a predicate device, rather than performance metrics typically associated with AI/ML.

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

Given the nature of the device (an electrosurgical grounding pad), the "acceptance criteria" appear to be related to safety and material compatibility rather than diagnostic performance.

Ask a specific question about this device

The MPC Model 7000 External Temporary Pacemaker System is indicated for temporary (1-10 days typical) ventricular cardiac pacing in a controlled clinical environment.

The MPC Model 7000 External Temporary Pacemaker System is a battery powered, single chamber external pacemaker. It consists of two major components: the MPC Model 3000 Programmer and the MPC Model 1000 Pulse Generator. The System also includes an MPC Model 5003 Patient Arm/Leg Strap used to secure the Pulse Generator to either the patient's arm or leg. An MPC Model 5002 Programmer Holder to store the Programmer on a wall is also available.

The MPC Model 3000 Programmer transmits the pulse programming data selected by the physician for patient therapy to the MPC Model 1000 Pulse Generator by infrared telemetry.

The MPC Model 1000 Pulse Generator and the MPC Model 3000 Programmer are re-usable. The MPC Model 1000 Pulse Generator and the MPC Model 3000 Programmer are designed so that they may be disinfected between patient use. The MPC Model 5003 Patient Arm/Leg Strap is disposable and labeled for single-use only.

{
  "1. A table of acceptance criteria and the reported device performance": {
    "Acceptance Criteria": [
      "No new issues of safety when compared to the predicate device (Pace EV 4542 External Pacemaker)",
      "Operate safely and to specification in an environment with potential electromagnetic challenges",
      "Pass radiated emissions test",
      "Pass Drop Test",
      "Pass Ship Test",
      "Software validated and tested",
      "Cleaning and disinfection validated for MPC Model 1000 Pulse Generator and MPC Model 3000 Programmer",
      "MPC Model 5003 Patient Arm/Leg Strap determined to be biocompatible and non-cytotoxic"
    ],
    "Reported Device Performance": [
      "Tests show that differences due to the ergonomic design features do not introduce different safety issues. Extensive qualification and validation conducted. MPC 7000 significantly enhances patient safety considerations.",
      "Extensive Electromagnetic Compatibility (EMC), Electromagnetic Interference (EMI), and Safety testing was conducted. The MPC Model 7000 External Temporary Pacemaker passed these EMC/EMI/Safety and Defibrillation Tests.",
      "The MPC Model 7000 External Temporary Pacemaker System was tested for radiated emissions and passed this test.",
      "The MPC Model 7000 External Temporary Pacemaker System was Drop Tested and passed this test.",
      "The MPC Model 7000 External Temporary Pacemaker System was Ship Tested and passed this test.",
      "The MPC Model 7000 External Temporary Pacemaker System's software has been validated and tested.",
      "Cleaning and disinfection described in the Instructions for Use have been validated for the MPC Model 1000 Pulse Generator and MPC Model 3000 Programmer.",
      "The MPC Model 5003 Patient Arm/Leg Strap has been tested and determined to be biocompatible and non-cytotoxic."
    ]
  },
  "2. Sample sized used for the test set and the data provenance": "Not specified in the provided text. The testing appears to be primarily laboratory-based and engineering validation, not clinical trials with human subjects for the 'test set' in the traditional sense of a diagnostic device. The 'test set' here refers to the device and its components undergoing various engineering validations.",
  "3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts": "Not applicable. The study involves engineering and safety testing against established standards and predicate device performance, not expert-derived ground truth for diagnostic accuracy.",
  "4. Adjudication method for the test set": "Not applicable, as the evaluation is based on engineering and safety test results rather than expert adjudication of clinical outcomes or interpretations.",
  "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 device is an external temporary pacemaker, not an AI-assisted diagnostic tool. No human reader studies with or without AI assistance are mentioned.",
  "6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done": "Not applicable. This is a medical device (pacemaker), not an algorithm or AI system for standalone performance evaluation.",
  "7. The type of ground truth used": "Engineering specifications, safety standards, and performance characteristics of the predicate device (Pace Medical, Inc. Model EV 4542 External Pulse Generator). For biocompatibility, standard biological testing methods were used.",
  "8. The sample size for the training set": "Not applicable. This device is an external temporary pacemaker, not an AI system that requires a 'training set'. The 'extensive qualification and validation' likely refers to engineering testing of multiple device units, but this is not a 'training set' in the AI sense.",
  "9. How the ground truth for the training set was established": "Not applicable, as there is no 'training set' for this medical device."
}

Ask a specific question about this device

The Stratasys FDM MedModeler is indicated as an image processing accessory, used to create three dimensional models from 3D surface representation data or 2D contour data as a diagnostic tool, as a pre-operative planning tool, and to enhance communication with patients, other professionals or students.

The Stratasys FDM MedModeler produces anatomical models for use in a variety of medical applications using CT and MRI imaging data. The four main parts of the FDM system, as displayed in Figure 1 (previous page) are 1) the QuickSlice Software, 2) FDM Hardware, 3) Modeling Materials and a 4) Computer Workstation.

Here's an analysis of the provided text regarding the Stratasys FDM® MedModeler System, focusing on acceptance criteria and study details:

This device is not an AI/ML powered device. It is a system for creating physical 3D models from imaging data. Therefore, many of the typical questions related to AI/ML device studies (like MRMC studies, standalone algorithm performance, number of experts for ground truth, and training set details) are not applicable or described in the provided 510(k) summary. The summary focuses on the safety and performance of the model generation process itself, rather than diagnostic accuracy.

Acceptance Criteria and Reported Device Performance

The provided 510(k) summary is very limited regarding specific, quantifiable acceptance criteria typical for diagnostic accuracy studies. The criteria are broadly defined around the system's intended function.

Study Details (Where Applicable)

Given the nature of the device (a 3D modeling system rather than a diagnostic AI), many of these categories are not explicitly addressed in the provided summary.

1. Sample size used for the test set and the data provenance: Not explicitly stated. The summary mentions "CAD, CT and MRI image modeling" data but does not specify the number of cases or their origin.
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable or not specified. The "ground truth" here would relate to the geometric accuracy and usability of the physical models compared to the original imaging data. There's no mention of expert radiologists or similar medical professionals evaluating model accuracy in the way they would evaluate diagnostic images.
3. Adjudication method for the test set: Not applicable or 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: Not applicable. This is not an AI diagnostic device for human readers.
5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable in the context of typical AI diagnostic devices. The performance of the FDM MedModeler system itself (the "algorithm only," if you consider the software and hardware combined) was assessed based on its ability to produce "satisfactory models" per the model generation report.
6. The type of ground truth used: The ground truth appears to be the original 2D contour or 3D surface representation data from CT/MRI, against which the generated 3D physical models were compared for "satisfactory" replication and adherence to "system requirements."
7. The sample size for the training set: Not applicable. This is not a machine learning device that uses a "training set" in the conventional sense. The "training" here would be the development and calibration of the system itself.
8. How the ground truth for the training set was established: Not applicable.

Ask a specific question about this device

ACU-CLENS™ Cleaning Accessory is indicated for use with recommended contact lens cleaning solutions for cleaning soft (hydrophilic) and rigid gas permeable contact lenses in accordance with directions for use in the solution labeling. The device ands in cleaning by minimizing hand contact with lenses.

ACU-CLENS™ Cleaning Accessory for Contact Lens Cleaning is a method of cleaning contact lenses that mimics the figure-eight hand-in-palm motion. The ACU-CLENS™ Cleaning Accessory can be used with hard (gas permeable) and soft (hydrophilic) lenses. ACU-CLENSTM Cleaning Accessory features a durable plastic case and disposable foam pads for use with professionally recommended daily cleaning solutions. The hinge mounted base and cover contain right and left lens receptacles and four mounting posts which secures the disposable pad to the base. The cover provides a motion plate, cleaning head domes and a hinged latch to secure the disposable pad to the cleaning head domes. Daily cleaning solution (recommended by an eye care professional or physician) is applied to the disposable pad secured to the cleaning head domes and the right and left receptacle and the lenses are placed on the disposable pad above the right and left receptacle. After closing the case the motion plate on the cover is moved in a figure-8 motion to create the scrubbing effect necessary to clean both top and bottom of each lens simultaneously. Lenses should be thoroughly disinfected using solution recommended by physicians or eye-care professionals. The disposable pad should be removed and the Cleaning Case disinfected after each use.

This document describes a 510(k) summary for the ACU-CLENS™ Cleaning Accessory, a device for cleaning contact lenses. It focuses on demonstrating substantial equivalence to a predicate device. The information provided is insufficient to answer most of the questions related to sophisticated acceptance criteria, quantitative performance evaluations, and detailed study methodologies typically associated with modern medical device clearances, especially software-driven AI algorithms.

The 510(k) is from 1996, and the device is a mechanical cleaning accessory, not an AI or software-driven diagnostic tool. Therefore, many of the requested details (like AI effect size, training data, expert ground truth for specific metrics) are not applicable or not provided in this type of submission for this kind of device.

However, I can extract what is available and explain why other information is missing.

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

Based on the provided text, the acceptance criteria are primarily related to safety, non-toxicity, non-irritation, and effectiveness in cleaning contact lenses. The performance is described qualitatively and visually.

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

• Sample Size: Not specified. The text mentions "The CLENSER Corporation has tested lenses with the ACU-CLENS™ Cleaning Accessory," but provides no numerical count of lenses or tests performed.
• Data Provenance: Not specified. Given the company is in Minnesota, USA, it's highly likely the testing was conducted in the USA, but this is not explicitly stated. The study type (retrospective/prospective) is not mentioned, but it would have been a prospective lab study to generate the SEM photographs.

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. The ground truth for cleaning effectiveness appears to be based on visual inspection via Scanning Electron Microscope (SEM) photographs. While SEM analysis requires expertise, the number and specific qualifications of the evaluators are not mentioned, nor would they typically be for this type of device and submission.

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

Not applicable. This type of adjudication method is usually associated with human-expert review of diagnostic findings, often in medical imaging or pathology. The primary evidence for this device is physical testing (cytotoxicity, irritation, cleaning effectiveness via SEM).

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 mechanical contact lens cleaning accessory, not an AI-assisted diagnostic tool for human readers. Therefore, an MRMC study and AI-related effect sizes are irrelevant to this submission.

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

Not applicable. This is a mechanical device, not an algorithm.

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

The ground truth for cleaning effectiveness was based on Scanning Electron Microscope (SEM) photographs. For biocompatibility, it was based on cytotoxicity and eye irritation testing (standardized in-vitro and/or in-vivo tests to assess material biological response).

8. The sample size for the training set

Not applicable. This device does not use a "training set" in the context of machine learning or AI.

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

Not applicable. No training set was used.

Ask a specific question about this device