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510(k) Data Aggregation
(218 days)
The EasyRA EtOH reagent is intended for the quantitative measurement of Alcohol (EtOH) in human urine, using MEDICA's EasyRA Chemistry Analyzer in clinical laboratories. Alcohol measurements are used for the diagnosis and treatment of alcohol intoxication and poisoning.
The EasyCal Ethanol Calibrator is intended for in-vitro diagnostic use for the calibration of the ethyl alcohol assay on the EasyRA Chemistry Analyzer for the quantitative determination of ethyl alcohol in urine.
The EasyQC Ethanol quality control material is intended for in-vitro diagnostic use for the validation of the ethyl alcohol assay, which is used on the EasyRA Chemistry Analyzer for the quantitative determination of ethyl alcohol in urine.
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The provided text is a 510(k) premarket notification letter from the FDA to Medica Corporation regarding their Easy RA Ethyl Alcohol Reagent, Calibrator, and QC Material. It details the regulatory approval of the devices for "quantitative measurement of Alcohol (EtOH) in human urine" and states that "Alcohol measurements are used for the diagnosis and treatment of alcohol intoxication and poisoning."
However, this document does not contain information about specific acceptance criteria, study details, sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, or how ground truth was established for these devices. The letter primarily confirms that the device is substantially equivalent to legally marketed predicate devices and is subject to general controls provisions.
Therefore, I cannot fulfill your request for a description of the acceptance criteria and the study that proves the device meets them based on the provided text.
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(55 days)
The Bayer ADVIA IMS Ethanol (ETOH) assay is an in vitro diagnostic device intended to quantitatively measure ethanol concentration in human serum or plasma (Lithium Heparin). Measurement of ethanol is used in the diagnosis of ethanol (alcohol) toxicity and overdose.
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The Bayer ADVIA® IMS™ Ethanol assay is an in vitro diagnostic device intended to quantitatively measure ethanol concentration in human serum or plasma (Lithium Heparin). This assay is used in the diagnosis of ethanol (alcohol) toxicity and overdose.
1. Table of Acceptance Criteria and Reported Device Performance
| Performance Metric | Acceptance Criteria (Predicate Device TDx) | Reported Device Performance (ADVIA® IMS™ Ethanol) |
|---|---|---|
| Imprecision (Total CV%) | ||
| Level ~40 mg/dL | 5.9% | 5.3% (at 22.0 mg/dL) |
| Level ~100 mg/dL | 3.2% | 2.2% (at 88.9 mg/dL) |
| Level ~250 mg/dL | 3.2% | 1.8% (at 289.5 mg/dL) |
| Correlation (vs. Predicate TDx - Serum) | ||
| Regression Equation | Not explicitly stated, but high R-value expected | Y = 0.964x - 0.04 |
| Syx (mg/dL) | Not explicitly stated | 4.8 |
| R | Not explicitly stated, but close to 1 expected | 0.999 |
| Sample Range (mg/dL) | Not explicitly stated | 22.9 to 433.0 |
| Correlation (Plasma vs. Serum - ADVIA IMS) | ||
| Regression Equation | Not explicitly stated | Y = 1.005x - 1.75 |
| Syx (mg/dL) | Not explicitly stated | 2.99 |
| R | Not explicitly stated, but close to 1 expected | 1.000 |
| Sample Range (mg/dL) | Not explicitly stated | 10.0 to 516.2 |
| Interfering Substances | Minimal interference (< ~10% change) | |
| Bilirubin (unconjugated, 25 mg/dL) | Not explicitly stated | +1.2% (at 98.2 mg/dL Ethanol) |
| Bilirubin (conjugated, 25 mg/dL) | Not explicitly stated | +1.6% (at 98.3 mg/dL Ethanol) |
| Hemoglobin (1000 mg/dL) | Not explicitly stated | +2.7% (at 94.9 mg/dL Ethanol) |
| Lipids (Triglycerides, 1000 mg/dL) | Not explicitly stated | +2.0% (at 95.8 mg/dL Ethanol) |
| Analytical Range | Not explicitly stated | 0.7 to 500 mg/dL |
2. Sample Sizes Used for the Test Set and Data Provenance
- Correlation (Serum vs. Abbott/TDx): 54 samples (N=54)
- Correlation (Plasma vs. Serum using ADVIA IMS): 50 samples (N=50)
The document does not explicitly state the country of origin of the data or whether the study was retrospective or prospective. Given the context of a 510(k) submission for a diagnostic device, it is typically expected that studies are prospective or, if retrospective, well-controlled with banked samples.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications
Not applicable. This is an in vitro diagnostic device measuring a chemical analyte (ethanol concentration). The "ground truth" for such measurements is established by validated reference methods or predicate devices, not by expert interpretation.
4. Adjudication Method for the Test Set
Not applicable. As noted above, the "ground truth" is a quantitative measurement, not a subjective interpretation requiring adjudication.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No. This type of study (MRMC) is typically used for imaging-based diagnostic devices where human readers interpret images. For an in vitro diagnostic assay, the comparison is made against a predicate device or reference method's quantitative output.
6. Standalone Performance Study
Yes, in essence. The imprecision, interfering substances, and analytical range studies assess the algorithm's (or assay's) performance independently of human interpretation.
The correlation studies also demonstrate the standalone performance of the ADVIA IMS Ethanol assay in comparison to a predicate device and also for different sample types (plasma vs serum) using the ADVIA IMS system itself.
7. Type of Ground Truth Used
The ground truth for the performance studies was established by:
- Predicate Device Comparison: The Abbott/TDx system served as the comparison system for the serum correlation study.
- Internal Comparison: For the plasma versus serum correlation, the ADVIA IMS itself was used to compare ethanol levels in matched plasma and serum samples.
- Known Concentrations: For imprecision and interfering substances studies, known concentrations of ethanol and interfering substances would have been used.
8. Sample Size for the Training Set
The document does not specify a separate "training set" sample size. For an in vitro diagnostic assay, development and validation typically involve extensive internal testing before final performance studies are conducted. The provided data represents validation studies, not typically a "training set" in the machine learning sense. Statistical models or algorithms within such devices are generally based on established chemical principles rather than iterative machine learning from large datasets.
9. How the Ground Truth for the Training Set was Established
Not explicitly stated or applicable in the conventional machine learning sense. The "ground truth" for developing such a chemical assay would involve:
- Chemical Principles: The assay is based on known biochemical reactions for ethanol detection.
- Reference Materials: Using validated reference materials with known ethanol concentrations for calibration and quality control.
- Method Optimization: Through extensive laboratory experimentation and optimization, ensuring that the assay accurately measures ethanol across its intended range.
- Comparison to Established Methods: During development, the assay would be compared to existing, well-validated methods to ensure accuracy and precision.
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(51 days)
The Ethanol assay is used for the quantitative analysis of ethyl alcohol (ethanol) in human serum, plasma, or urine. The Ethanol assay should be exclusively used to detect ethanol and not other alcohols such as isopropanol or methanol. Reactivity with compounds structurally unrelated to ethanol has not been observed.
Ethanol is an in vitro diagnostic assay for the quantitative analysis of ethyl alcohol (ethanol) in human serum, plasma, or urine. The assay is based on an enzymatic reaction. Active enzyme converts NAD to NADH, resulting in an absorbance change that can be measured spectrophotometrically. The increase in absorbance at 340 nm is proportional to the concentration of alcohol in the specimen.
This submission describes the "Ethanol" assay, an in vitro diagnostic device for the quantitative analysis of ethyl alcohol in human serum, plasma, or urine. The study presented aims to demonstrate substantial equivalence to a predicate device, the Emit® II Plus Ethyl Alcohol assay (K993980).
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria (Predicate Performance) | Reported Device Performance (Ethanol Assay) |
|---|---|
| Correlation with Predicate Device (Emit® II Plus Ethyl Alcohol assay on SYVA 30R Analyzer) | Acceptable correlation demonstrated. |
| - Serum: Not explicitly stated as a numerical criterion, but the predicate's performance implies a high correlation is expected. | - Serum: Correlation coefficient = 0.996, slope = 1.00, Y-intercept = -1.87 mg/dL |
| - Urine: Not explicitly stated as a numerical criterion, but the predicate's performance implies a high correlation is expected. | - Urine: Correlation coefficient = 0.997, slope = 1.01, Y-intercept = -4.85 mg/dL |
| Precision (Implied from predicate or general assay expectations) | Precision studies conducted. |
| - Within-run Total %CV: Implied to be low for similar assays. | - Low control: 5.1% Total %CV |
| - Within-run Total %CV: Implied to be low for similar assays (e.g., around 1-5% for calibrators/controls). | - 100 mg/dL calibrator/control: 2.8% Total %CV |
| - Within-run Total %CV: Implied to be low for similar assays. | - High control: 1.7% Total %CV |
| Assay Range (Implied from predicate or general assay expectations) | 10 to 600 mg/dL |
| Limit of Quantitation (Sensitivity) (Implied from predicate or general assay expectations) | 5 mg/dL |
Note: The acceptance criteria are not explicitly defined as pass/fail thresholds in the provided text but are inferred from the need to demonstrate "substantially equivalent performance" to the predicate device. The presented performance characteristics are typical metrics for demonstrating equivalence in IVD assays.
2. Sample Size Used for the Test Set and Data Provenance
The document does not explicitly state the specific number of human serum or urine samples used in the comparative performance studies to generate the correlation data (correlation coefficients, slopes, and y-intercepts). It only mentions "Comparative performance studies were conducted." The data provenance (e.g., country of origin, retrospective or prospective) is also not specified.
For the precision studies, "three levels of control material" were used for the within-run study. The number of replicates for each level is not provided.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
This type of information is not applicable to this submission. The "Ethanol" assay is an in vitro diagnostic (IVD) test that quantifies a biomarker (ethyl alcohol concentration). The "ground truth" for such devices is typically established by comparing its performance to a reference method or another legally marketed device (the predicate device in this case), or by using known concentrations in control materials. It does not involve interpretation by human clinicians or experts for ground truth establishment in the same way an imaging or pathology device might require.
4. Adjudication Method for the Test Set
The concept of an "adjudication method" (e.g., 2+1, 3+1) is not applicable here. Adjudication is used to resolve discrepancies in independent interpretations by multiple experts, typically for qualitative or semi-quantitative diagnostic tests where human judgment is involved. For a quantitative IVD assay like the Ethanol assay, the comparison is directly between the numerical results of the new device and the predicate device (or known concentrations).
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size of Human Improvement
A Multi-Reader Multi-Case (MRMC) comparative effectiveness study is not applicable to this device. MRMC studies are used to evaluate the impact of an AI-powered diagnostic aid on human reader performance (e.g., radiologists interpreting images). The "Ethanol" assay is an automated in vitro diagnostic test for quantifying a biomarker and does not involve human interpretation in the diagnostic process beyond performing the test and reviewing results. Therefore, there is no "human reader improvement with AI vs without AI assistance" to measure.
6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done
The entire study presented is a standalone performance evaluation of the "Ethanol" assay. The device itself is an automated enzymatic assay. The performance characteristics (correlation, precision, range, sensitivity) are inherently "standalone" in that they describe the capability of the device itself to accurately measure ethanol concentration, without requiring active human interpretation of its diagnostic output (beyond standard laboratory procedures).
7. The Type of Ground Truth Used
The ground truth used for the comparative performance studies was the results obtained from the predicate device, the Emit® II Plus Ethyl Alcohol assay on the SYVA 30R Analyzer. For the precision studies, the ground truth was the known concentrations of the control materials (low control, 100 mg/dL calibrator/control, and high control).
8. The Sample Size for the Training Set
The document does not specify a training set sample size. This submission describes an in vitro diagnostic that uses an enzymatic reaction. This type of assay does not typically involve machine learning algorithms that require "training sets" in the conventional sense (i.e., large datasets used to train a model). Instead, it relies on established biochemical principles and calibration procedures.
9. How the Ground Truth for the Training Set Was Established
As noted above, this device does not utilize a training set in the machine learning context. The "ground truth" relevant to the development and calibration of such an enzymatic assay would historically involve:
- Known concentrations of analyte: Prepared standards and calibrators with precisely measured ethanol concentrations.
- Reference methods: Historical or established reference methods for measuring ethanol.
These elements would be used during the assay's development and manufacturing to establish its analytical performance characteristics and ensure it accurately measures ethanol. The specific details of how these were established are not provided in this 510(k) summary, as it is focused on demonstrating equivalence to the predicate, not the de novo development process.
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(60 days)
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(61 days)
For the quantitative determination of ethanol in serum. For IN VITRO diagnostic use.
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The provided document is a 510(k) premarket notification letter from the FDA regarding the "Ethanol-L3K Assay." This document does not contain information about acceptance criteria, device performance studies, sample sizes, ground truth establishment, or expert qualifications in the way you've requested for an AI/ML medical device.
The information you are asking for typically comes from the actual 510(k) submission document itself, or from a scientific publication detailing the device's validation. This FDA letter is merely the agency's response granting market clearance.
Therefore, I cannot fulfill your request for the specific details outlined as they are not present in the provided text.
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(162 days)
For the quantitative determination of ethanol in serum, plasma or urine. For IN VITRO diagnostic use.
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The provided text is a letter from the FDA regarding the 510(k) clearance of the "Ethanol-SL Assay" device. It does not contain any information about the acceptance criteria or a study proving the device meets those criteria, nor does it provide details about algorithm performance, sample sizes, expert qualifications, or ground truth establishment.
The letter is a regulatory document stating that the FDA has reviewed the submission and determined that the device is substantially equivalent to legally marketed predicate devices. It discusses regulatory classifications, general controls, and compliance requirements, but not the technical performance details of the device itself or any studies demonstrating its performance against specific acceptance criteria.
Therefore, I cannot fulfill your request for the specified information based on the provided text.
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