Search Results

The Urodynamic Analysis Module is a software program that has been designed to analyze pressure, volume and flow data recorded from the urological tract in pediatric and adult populations. The Urodynamic Analysis Module includes the following analyses: Uroflow analysis. Cystometry analysis, Pressure/flow voiding analysis, Urethral Pressure Profile. The program is to be used on a personal computer analyzing patient data in the hospital environment under supervision of a trained physiclan. The analyzed data can be viewed on the computer screen or printed out on a separate paper.

The Polygram Software for Windows (KD46322) was designed to record and handle/store physiological parameters. After a recording, the user is able to review the tracings on the computer screen and print the signal tracings or just parts of them. When reviewing the data on the computer screen, the user is able to mark certain segments and calculate certain parameters from the selected signal segments. These parameters include minimum and maximum values. length of selection. By adding the Urodynamic Analysis Module to the Polygram Software for Windows, the user can also have all the pressure, flow and volume data analyzed In terms of physiological properties, comparison with normal values, etc. The analyzed data can thereafter be viewed on screen or printed out on a separate paper. The analysis report includes sections such as patient demographics: interpretation and comment (for user to insert); procedure summary; Urodynamic tracing; analyses (as specified below); and physician signature section.

The provided text describes the Urodynamic Analysis Module, a software program for analyzing urological data. However, it does not contain any specific acceptance criteria or details of a study that proves the device meets such criteria.

The section titled "Performance Testing" indicates that "alpha testing in terms of integration testing has been performed and documented and beta testing in terms of hospital site testing has been done and documented." It further states that "It has been concluded that the alpha and beta testing has meet and passed the specified objectives and should therefore be released to the market."

This statement is a high-level summary and lacks the detailed information required to fill out the requested table and answer the specific questions.

Here's an explanation of why the requested information cannot be extracted from the provided text:

1. Table of Acceptance Criteria and Reported Device Performance: This information is entirely absent. There are no measurable criteria (e.g., accuracy percentages, error rates, precision targets) or reported numerical performance data.
2. Sample Size Used for Test Set and Data Provenance: The document mentions "beta testing in terms of hospital site testing," suggesting real-world data was used. However, it does not specify the sample size (number of patients, number of cases), the country of origin, or whether the study was retrospective or prospective.
3. Number of Experts Used to Establish Ground Truth and Qualifications: This information is not provided. We don't know who established the "specified objectives" mentioned or how the ground truth for the testing was determined.
4. Adjudication Method: Not mentioned.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study: Not mentioned. There is no indication of human reader comparisons, with or without AI assistance, or any effect size.
6. Standalone Performance Study: The document describes the software's analytical capabilities but doesn't detail a standalone performance study with specific metrics, only generalized "alpha and beta testing."
7. Type of Ground Truth Used: The document doesn't specify how ground truth was established for the "specified objectives."
8. Sample Size for Training Set: Not applicable as the text describes a system that analyzes data, not one that uses machine learning models that require a training set in the conventional sense. The "training" here would likely refer to the software's development and internal validation, not a machine learning training phase.
9. How Ground Truth for Training Set was Established: Not applicable for the same reason as point 8.

In summary, the provided 510(k) summary focuses on describing the device's functionality and its equivalence to an older DOS-based version. It only offers a very general statement about performance testing, without the specific details required for a robust analysis of acceptance criteria and proven performance.

Ask a specific question about this device