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The Cystatin C assay is an in vitro diagnostic test used in the quantitative immunoturbidimetric determination of cystatin C in human serum and plasma on the Alinity c system.

Measurement of cystatin C aids in the diagnosis and treatment of renal diseases.

For laboratory professional use only.

The Cystatin C assay is an automated clinical chemistry assay.

Cystatin C is a particle-enhanced turbidimetric immunoassay (PETIA) developed to accurately and reproducibly measure cystatin C levels in serum and plasma. Latex particles coated with anti-human cystatin C antibody agglutinate when mixed with sample containing human cystatin C. The change in absorbance due to agglutination of the reaction mixture is proportional to the quantity of human cystatin C in the sample.

The provided text is a 510(k) clearance letter for an in vitro diagnostic test (Cystatin C assay), not an AI/ML-driven medical device. Therefore, the information requested for AI/ML device studies (such as MRMC studies, expert adjudication, training set ground truth, etc.) is not applicable to this document.

However, I can extract and present the performance acceptance criteria and reported device performance from the provided document, even though they relate to a traditional laboratory assay rather than an AI/ML model.

Here's an interpretation based on the provided text for a traditional in vitro diagnostic device:

Based on the provided FDA 510(k) clearance letter for the Cystatin C Test System, the device is a quantitative immunoturbidimetric assay for the determination of cystatin C in human serum and plasma. The performance of this device was demonstrated through various nonclinical studies.

1. Table of Acceptance Criteria and Reported Device Performance

For in vitro diagnostic tests like the Cystatin C assay, "acceptance criteria" are typically defined by ranges or thresholds for performance characteristics such as precision, accuracy (bias), linearity, and limits of detection. The document describes the reported performance measured during the studies, and implicitly, these figures met the internal acceptance criteria set by the manufacturer (and approved by the FDA for clearance).

Here's a summary of the reported device performance:

Study Details (Relevant to IVD, not AI/ML)

The following points are addressed as much as possible for an in vitro diagnostic device, noting where the requested AI/ML specific information is not applicable.

2. Sample sizes used for the test set and the data provenance:

   • Precision/Reproducibility:
     • Within-Laboratory Precision: 80 replicates per sample/control (2 replicates/day for 20 days) for 2 controls and 4 human serum panels.
     • Reproducibility: 240 replicates per sample/control (4 replicates, twice/day for 5 days at 3 sites) for 2 controls and 3 human serum panels.
   • Accuracy (Bias): Not specified as a separate sample size, but involved testing across 2 reagent lots and 2 calibrator lots.
   • Linearity: Not specified as a number of distinct samples, but assessed over a range of concentrations.
   • Lower Limits of Measurement (LoB, LoD, LoQ): ≥ 60 replicates of zero-analyte samples for LoB, and ≥ 60 replicates of low-analyte level samples for LoD/LoQ.
   • Analytical Specificity (Interference): Each substance tested at 2 analyte levels.
   • Method Comparison: 161 serum samples.
   • Matrix Comparison: Not specified as a specific number, but evaluated across various tube types.
   • High Dose Hook: Not specified as a specific number of samples, but tested up to 40.00 mg/L.
   • Expected Values (Reference Interval): 250 apparently healthy individuals (105 females, 145 males) with eGFR > 80, aged 18 to 69 years.

   Data Provenance: The document does not explicitly state the country of origin for the clinical samples. The studies are described as "nonclinical performance" studies, meaning they evaluate the analytical performance of the assay itself, rather than diagnostic accuracy in a clinical setting with patient outcomes. These are typically prospective studies conducted in a controlled lab environment.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Not applicable for this in vitro diagnostic device. Ground truth for analytical performance studies of IVDs is established by the known concentration of analytes in reference materials, calibrators, and characterized control samples, or by comparison to a well-established reference or predicate method. It does not involve expert readers or their consensus.

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

   • Not applicable for this in vitro diagnostic device. Adjudication methods are relevant for subjective image-based assessments or clinical diagnoses where human interpretation varies. This product is a quantitative chemical assay.

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 for this in vitro diagnostic device. MRMC studies are for evaluating the impact of AI on human reader performance, typically in radiology or similar interpretive fields. This device performs automated measurements.

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

   • Analogous concept applies. The performance data presented (precision, accuracy, linearity, limits of detection, etc.) are the standalone performance of the assay on the Alinity c system. It demonstrates the device's ability to measure Cystatin C without human interpretation of the analytical signal.

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

   • For the analytical performance studies, the ground truth was established by:
     • Certified reference materials: Specifically, ERM-DA471/IFCC for assay standardization and accuracy validation.
     • Preparation of known concentrations: Through spiking or dilution of samples to evaluate linearity and limits of measurement.
     • Comparison to a validated comparator assay: For method comparison (Cystatin C on Alinity c vs a Comparator Cystatin C assay).
     • Characterized control materials: For precision and reproducibility studies.
     • Established healthy population studies: For determining the reference interval.

8. The sample size for the training set:

   • Not applicable in the AI/ML sense. This is a traditional chemical assay, not an AI/ML model that undergoes a "training" phase with data. The assay's parameters are developed through conventional analytical chemistry principles and validated through the nonclinical performance studies detailed.
   • Development would involve formulation and optimization studies, but not "training data" in the AI sense.

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

   • Not applicable for this in vitro diagnostic device. As noted above, there is no "training set" in the AI/ML context for a traditional immunoturbidimetric assay. The "ground truth" for developing such an assay would be based on fundamental chemical principles, known concentrations of analytes, and established analytical chemistry standards.

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The Atellica® CH Creatinine_3 (Crea3) assay is for in vitro diagnostic use in the quantitative determination of creatinine in human serum, plasma (lithium heparin, dipotassium EDTA, and sodium heparin), and urine using the Atellica® CH Analyzer. Such measurements are used in the diagnosis and treatment of renal diseases, and in monitoring renal dialysis.

The Atellica CH Crea3 assay is based on the reaction of picrate with creatinine in an alkaline medium to produce a red chromophore creatinine picrate complex. The rate of complex formation is measured at 505/571 nm and is proportional to the creatinine concentration. The Atellica CH Crea3 assay is a modification of the Jaffe method, using rate blanking and intercept correction. Rate blanking is used to minimize bilirubin interference. Also, because non-specific serum/plasma protein interactions with this reagent have been found to produce a positive bias of approximately 0.3 mg/dL (26.5 µmol/L), serum/plasma measurements are automatically corrected by subtracting 0.3 mg/dL (26.5 µmol/L) from each result.

The provided text describes the performance characteristics and studies for the Atellica® CH Creatinine_3 (Crea3) assay, a new in vitro diagnostic device for quantitative determination of creatinine. It compares this new device to a predicate device, the Atellica® CH Creatinine_2 (Crea_2) assay.

Here's an analysis of the acceptance criteria and the study proving the device meets them, based on the provided text:

Important Note: The document focuses on establishing substantial equivalence for an in vitro diagnostic (IVD) test, which primarily relies on analytical performance characteristics rather than clinical outcome studies or multi-reader multi-case (MRMC) comparative effectiveness studies typically seen with imaging AI devices. Therefore, some of your requested information (like number of experts for ground truth, adjudication methods, MRMC studies, and training set details for an AI model) are not directly applicable or provided in this type of submission.

Acceptance Criteria and Reported Device Performance

The acceptance criteria for this device are established through various analytical performance studies, primarily comparing it to a legally marketed predicate device (Atellica® CH Creatinine_2). The acceptance criteria are implicitly defined by the successful demonstration of equivalence or meeting pre-defined performance goals for each characteristic.

Here's a table summarizing the acceptance criteria (inferred from the "designed to have" or "determined in accordance with" statements and the reported results meeting these) and the reported device performance:

• Serum 1 (0.38 mg/dL): Repeatability SD 0.006, CV 1.6%; Within-Lab SD 0.012, CV 3.2%
• Serum 2 (0.73 mg/dL): Repeatability SD 0.023, CV 3.2%; Within-Lab SD 0.029, CV 4.0%
• Serum 3 (0.73 mg/dL): Repeatability SD 0.006, CV 0.8%; Within-Lab SD 0.019, CV 2.6%
• Serum 4 (1.18 mg/dL): Repeatability SD 0.007, CV 0.6%; Within-Lab SD 0.019, CV 1.6%
• Serum QC 1 (1.85 mg/dL): Repeatability SD 0.007, CV 0.4%; Within-Lab SD 0.024, CV 1.3%
• Serum QC 2 (6.21 mg/dL): Repeatability SD 0.011, CV 0.2%; Within-Lab SD 0.067, CV 1.1%
• Serum 5 (17.39 mg/dL): Repeatability SD 0.035, CV 0.2%; Within-Lab SD 0.189, CV 1.1%
• Serum 6 (28.54 mg/dL): Repeatability SD 0.056, CV 0.2%; Within-Lab SD 0.317, CV 1.1%
  Urine Samples (n=80 each):
• Urine 1 (56.74 mg/dL): Repeatability SD 0.102, CV 0.2%; Within-Lab SD 0.746, CV 1.3%
• Urine 2 (135.80 mg/dL): Repeatability SD 0.206, CV 0.2%; Within-Lab SD 1.601, CV 1.2%
• Urine QC 1 (195.79 mg/dL): Repeatability SD 0.253, CV 0.1%; Within-Lab SD 2.376, CV 1.2%
  (All results demonstrate low CVs, indicating good precision). |
  | Reproducibility | Determined in accordance with CLSI Document EP05-A3 (implies meeting specific statistical targets for variability components across different days, lots, and instruments). | Serum Samples (n=225 each): Overall CV (%) for reproducibility ranges from 1.0% to 5.0%.
  Urine Samples (n=225 each): Overall CV (%) for reproducibility ranges from 1.4% to 1.6%.
  (All results demonstrate good reproducibility across conditions). |
  | Assay Comparison | Serum: Correlation coefficient $\ge$ 0.950 and slope of 1.00 ± 0.05, compared to predicate (Atellica CH Creatinine 2), using Weighted Deming regression.
  Urine: Correlation coefficient $\ge$ 0.950 and slope of 0.000 ± 3.00, compared to predicate (Atellica CH Creatinine 2), using Weighted Deming regression. | Serum (n=151): Regression equation y = 1.00x - 0.04 mg/dL, correlation coefficient (r) = 1.000. Sample range 0.44 to 28.64 mg/dL.
  Urine (n=113): Regression equation y = 1.00x + 0.14 mg/dL, correlation coefficient (r) = 1.000. Sample range 12.60 to 237.06 mg/dL.
  (Both serum and urine results meet the acceptance criteria for correlation and slope). |
  | Specimen Equivalence | Determined using Weighted Deming regression (implicitly, the regression line should demonstrate equivalence, i.e., close to y=x, with high correlation coefficient). | Sodium Heparin (n=50): y = 1.00x + 0.00 mg/dL, r=0.999.
  Lithium Heparin (n=50): y = 0.99x + 0.06 mg/dL, r=0.999.
  Dipotassium EDTA (n=50): y = 0.98x + 0.04 mg/dL, r=0.998.
  (All demonstrate strong equivalence to serum reference). |
  | Interferences (HIL) | $\le$ 10% interference from hemoglobin, bilirubin, and lipemia. Bias > 10% or 0.15 mg/dL (whichever is greater for serum/plasma) is considered interference. | Reported biases for Hemoglobin (1000 mg/dL), Conjugated Bilirubin (40-45 mg/dL), Unconjugated Bilirubin (45-60 mg/dL), and Lipemia (2250-3000 mg/dL) are all within the ±10% or ±0.15 mg/dL threshold for the tested analyte concentrations, demonstrating acceptable interference profiles. |
  | Interfering Substances | Bias $\le$ 10% or ±0.15 mg/dL for Serum/plasma samples. Bias $\le$ 10% for Urine samples (for listed substances). | Most tested substances (e.g., Acetaminophen, Ascorbic Acid, etc.) show negligible bias, meeting the criteria.

Substances showing bias beyond acceptance criteria for Serum:

• Cefoxitin: Significant interference (e.g., 243.6% and 947.9% bias at high concentrations).
• Cephalothin: Shows significant bias (e.g., 44.0% bias at 180 mg/dL).
• Glucose: Shows bias beyond 10% at higher concentrations (e.g., 11.5% at 500 mg/dL and 22.5% at 1000 mg/dL).
• Total Protein: Shows bias beyond 0.15 mg/dL at 15 g/dL (0.45 mg/dL).
• Acetohexamide: Shows bias beyond 10% at 2.0 mg/dL (10.4%).
• Hydroxocobalamin (Cyanokit): Shows significant bias (e.g., 14.5% and 49.3% at higher concentrations).

Substances showing bias beyond acceptance criteria for Urine:

• Cefoxitin: Shows bias beyond 10% at higher concentrations (e.g., 11.3% and 15.4%).
  (The document explicitly lists these substances under "Interference beyond ±10% for Serum" and "Interference beyond ±10% for Urine," indicating that they failed the non-interference criteria at the tested concentrations. This is typical for IVD submissions, where known interferences are identified for labeling purposes). |
  | Standardization | The assay shall be traceable to the reference material SRM967, from the National Institute of Standards and Technology (NIST). | Statement confirms the assay is traceable to NIST SRM967. |

Study Details:

1. Sample Size and Data Provenance:

   • Test Set Sample Sizes:
     • Detection Capability: Not explicitly stated as "sample size" but data points obtained according to CLSI EP17-A2.
     • Precision: 80 data points per serum/urine sample type (duplicate runs for 20 days, 2 runs/day).
     • Reproducibility: 225 data points per serum/urine sample type (n=5 in 1 run for 5 days using 3 instruments and 3 reagent lots).
     • Assay Comparison: 151 serum samples and 113 urine samples.
     • Specimen Equivalence: 50 samples for each plasma type (Sodium Heparin, Lithium Heparin, Dipotassium EDTA) compared to serum.
     • Interference (HIL & Non-Interfering Substances): Not explicitly stated as a total sample size, but experiments are designed to test specific analyte concentrations with and without interferents, following CLSI EP07-ED3.
   • Data Provenance: Not explicitly stated in terms of country of origin. Given the manufacturer (Siemens Healthcare Diagnostics Inc. in Tarrytown, New York, USA) and FDA submission, it's highly probable the studies were conducted in the US or in compliance with US regulatory standards. The studies described are retrospective in the sense that they use pre-collected or prepared samples to assess the analytical performance of the device under controlled conditions, not prospective in tracking patient outcomes in a clinical trial.

2. Number of experts used to establish the ground truth for the test set and qualifications of those experts:

   • For an in vitro diagnostic (IVD) device measuring a quantitative analyte like creatinine, "ground truth" is typically established by reference methods or established laboratory standards and calibrators, not by human expert consensus or labeling of medical images.
   • The "ground truth" for creatinine concentration in this context is based on traceable reference materials (NIST SRM 967) and established laboratory measurement principles, and the performance is compared against a legally marketed predicate device.
   • Therefore, this question (relevant for AI/imaging devices) does not directly apply to this type of IVD submission.

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

   • Not applicable. Adjudication methods are typically used in clinical trials or image labeling pipelines where there's human interpretation involved and a need to resolve disagreements among multiple readers; this is an analytical performance study of an IVD assay.

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/imaging device. It's an in vitro diagnostic assay.

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

   • This is an automated IVD assay performed on the Atellica® CH Analyzer. Its intended use is quantitative determination of creatinine. Therefore, the performance described (precision, accuracy, interference, etc.) is its standalone performance without a human in the loop for the analytical measurement itself, though a human still interacts with the instrument and interprets the results in a clinical context.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • The primary "ground truth" for the Atellica® CH Creatinine_3 assay's performance is traceability to NIST SRM 967 (a certified reference material for creatinine) and comparison to a legally marketed predicate device (Atellica® CH Creatinine_2) using method comparison validated against CLSI guidelines. This is a form of analytical reference standard and comparative performance to an established method.

7. The sample size for the training set:

   • This device is an analytical chemistry assay, not a machine learning/AI algorithm that requires a "training set" in the computational sense. The "development" or "optimization" of the assay would involve various experimental data, but it's not codified as a "training set" for an algorithm.

8. How the ground truth for the training set was established:

   • Not applicable, as there is no "training set" in the AI/ML context for this type of device. The assay development would rely on scientific principles of analytical chemistry, reagent formulation, and instrument calibration against known standards.

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The Nova Allegro urine albumin creatinine ratio (UACR) Assay is intended for the quantitative determination of albumin, creatinine, and the albumin/creatinine ratio (UACR) in human urine. The measurement of urine albumin, creatinine, and albumin/creatinine ratio aids in the early diagnosis of nephropathy.

The Nova Allegro Analyzer is intended for in vitro diagnostic use in clinical laboratory and near-patient testing (point-of-care) settings for the quantitative determination of Nova Allegro Assays using Nova Allegro Test Cartridges.

Nova Allegro UACR Assay: The Nova Allegro UACR Assay is a completely automated assay for the determination of albumin and creatinine in human urine. The results are used to calculate the UACR (Urine Albumin to Creatinine Ratio). Nova Allegro UACR Test Cartridges are the key element a user interacts with to determine the albumin and creatinine levels in a human urine sample. The main components of the Test Cartridge are the Capillary, the reaction chamber, and the barcode label.

Nova Allegro Analyzer: The Nova Allegro Analyzer is a compact, point-of-care analyzer that features a clinically important menu of measured and calculated tests. All tests are measured with disposable, ready-to-use cartridges. The analyzer supports multiple wavelengths that are used to measure the assay of interest. The analyzer consists of the following key systems/components that the user interacts with:

• Two analytical bays where the single use test cartridges are analyzed
• Color Touchscreen Display
• Barcode Scanner
• Printer
• Data Export Options
• Ethernet Connection
• USB Port

The provided text is a 510(k) Summary for the Nova Allegro UACR Assay and Analyzer. It details the device's performance testing results. According to the prompt's request, I will extract relevant information to describe the acceptance criteria and the study proving the device meets these criteria.

It's important to note that this document describes a medical device, specifically an in-vitro diagnostic test, not an AI/ML-based device. Therefore, many of the requested fields related to AI/ML specific quality evaluation criteria, such as "number of experts used to establish ground truth," "adjudication method," "MRMC study," "effect size of human readers improving with AI," "standalone performance," and details about training sets/ground truth for training, are not applicable in this context. The study performed is a performance validation of a diagnostic assay, comparing its results to a comparative method (CM), not a reader study.

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

Device: Nova Allegro UACR Assay, Nova Allegro Analyzer
Indications for Use: The Nova Allegro urine albumin creatinine ratio (UACR) Assay is intended for the quantitative determination of albumin, creatinine, and the albumin/creatinine ratio (UACR) in human urine. The measurement of urine albumin, creatinine, and albumin/creatinine ratio aids in the early diagnosis of nephropathy. The Nova Allegro Analyzer is intended for in vitro diagnostic use in clinical laboratory and near-patient testing (point-of-care) settings for the quantitative determination of Nova Allegro Assays using Nova Allegro Test Cartridges.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are generally implied by the successful conclusion of each test and the statement that the data "meets the acceptance criteria" or "demonstrated no significant interference." Specific quantitative acceptance criteria are sometimes stated (e.g.,

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The UC-1800 Automatic Urine Analyzer is automated instrument which is intended for professional, in vitro diagnostic use only.

Depending on the reagent strips being used, the instruments perform semi-quantitative detection of the following analytes in urine: ascorbic acid, microalbumin, leukocytes, creatinine, ketone, urobilinogen, bilirubin, glucose, protein, specific gravity, blood and pH in urine and for qualitative determination of nitrite in urine hydrometer (optional) can determine the color and turbidity of urine. Test results may provide information regarding the status of carbohydrate metabolism, kidney and liver function, acid-base balance and bacteriuria.

The URIT 11FA urine reagent strips provide semi-quantitative tests for ascorbic acid, leukocytes, setone, urobilinogen, bilirubin, glucose, protein, specific gravity, blood and pH in urine and for qualitative determination of nitrite in urine. The URIT 11FA urine reagent strips are for use with the UC-1800 Automatic Urine Analyzer and are for professional, in vitro diagnostic use only. Test results may provide information regarding the status of carbohydrate metabolism, kidney and liver function, acid-base balance and bacteriuria.

The URIT 12FA urine reagent strips provide semi-quantitative tests for microalbumin, leukocytes, creatinine, ketone, urobilinogen, bilirubin, glucose, protein, specific gravity, blood and pH in urine and for qualitative determination of nitrite in urine. The URIT 12FA urine reagent strips are for use with the UC-1800 Automatic Urine Analyzer and are for professional, in vitro diagnostic use only. Test results may provide information regarding the status of carbohydrate metabolism, kidney and liver function, acid-base balance and bacteriuria.

UC-1800 Automatic Urine Analyzer is characterized by fully automated and simple operation. All you need to do is to set test strips and samples, press the START key, and the rest of operations are fully automated with UC-1800, which can measure samples continuously. For each measurement, the instrument automatically performs a series of operation: sample transmitting, sample aspirating, sample dropping, rinsing strip feeding and color identifying, etc. The instrument is used in conjunction with a serial of URIT urine test strips for measuring 15 parameters. Measure results are printed through either built-in printer or external printer.

Urine Reagent Strips is used to determine the components to be measured in urine by dry chemistry method together with urine analyzer. Various components to be tested in the urine can result in changes to the colors of corresponding reagent blocks on the Urine Reagent Strips. The depth of reaction color is proportional to the corresponding component to be tested in the urine. Qualitative and semi-quantitative detection can be conducted to the contents of the corresponding detected components. As a reagent for the determination of multiple components in human urine and the most basic test item for clinical urine routine test), it is suitable for the screening test or auxiliary diagnosis for clinical diagnosis, without the specificity for diseases or indications, and urine dry chemistry test is a screening test and cannot be used as a single diagnostic method.

The provided document describes the URIT UC-1800 Automatic Urine Analyzer and its associated reagent strips (URIT 11FA and 12FA Urine Reagent Strips). The information below summarizes the acceptance criteria and the studies performed to demonstrate the device meets these criteria.

1. Table of Acceptance Criteria and Reported Device Performance

The document presents the performance in terms of "Exact agreement" and "± 1 color block" agreement with expected values or between the proposed device and predicate devices. For most analytes, the criteria seem to be high exact agreement and 100% agreement within ±1 color block. Specific thresholds for acceptance were not explicitly stated as global criteria but are implied by the "Qualified" conclusions for individual tests. The comparison to predicates also uses agreement rates.

Below is a summary of the reported device performance from the "Precision / Reproducibility" section (Tables 8, 9, 10, 11) for repeatability and "Comparison Studies" section (Tables a.1, a.2, a.3) for agreement with predicate devices. Given the extensive number of analytes and concentration levels, key representative results are presented.

a. Repeatability (Within-Run Precision)
Reported as "Exact agreement" and "± 1 color block". All tests for all expected values show 100% agreement for "± 1 color block". Exact agreement varies slightly, but most are 100% or very close.

b. Reproducibility (Between-Run Precision)
Reported as "Exact agreement" and "± 1 color block". All tests for all expected values show 100% agreement for "± 1 color block". Exact agreement varies slightly, but most are 100% or very close.

c. Comparison with Predicate Devices

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

• Repeatability (within-run) & Reproducibility (between-run):

  • Sample Size:
    • Repeatability: 60 measurements per concentration level per analyte (20 replicates x 3 instruments).
    • Reproducibility: 120 measurements per concentration level per analyte (20 days x 2 runs/day x 1 time/run in 3 sites, with 1 instrument/site, 3 operators).
  • Data Provenance: The document does not explicitly state the country of origin or if the data was retrospective or prospective. It refers to "negative urines and spiked urines of known concentrations." This suggests controlled laboratory-prepared samples rather than direct patient samples.

• Linearity/Assay Reportable Range:

  • Sample Size: 63 measurements per concentration level per analyte (reference solutions tested 21 times on 3 UC-1800 machines with 3 lots of reagent strips).
  • Data Provenance: Laboratory-prepared reference solutions, not clinical samples.

• Analytical Sensitivity: No sample sizes mentioned, values are stated directly.

• Critical Value: No sample sizes mentioned, values are stated directly.

• Analytical Specificity (Interference, pH, Color, Specific Gravity):

  • Sample Size: For interference studies, samples were tested 5 times on 2 UC-1800 machines with 2 batch numbers of 11FA and 12FA reagent strips. This totals 20 measurements per condition (5 tests x 2 machines x 2 strips).
  • Data Provenance: Laboratory-prepared urine samples (negative samples prepared and spiked with interfering substances or adjusted for pH/color/SG).

• Comparison Studies with Predicate Devices (Clinical Samples):

  • Uritest-500B (K082811): 1000 clinical urine samples.
  • Mission® U120 Ultra Urine Analyzer (K142391): 979 clinical urine samples.
  • AUTION MAX AX-4030 Urinalysis System (K093098):
    • Color: 1365 clinical urine samples.
    • Turbidity: 1000 clinical urine samples.
  • Data Provenance: The document explicitly states "clinical urine samples were collected." The country of origin is not specified but given the submitter's address (China), it is highly likely that these clinical samples were collected in China and were retrospective as the study compares against existing predicate devices.

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

The document does not mention the use of experts to establish a "ground truth" for the test set in the traditional sense of medical image interpretation or clinical diagnosis. For chemical analyzers, the "ground truth" (or reference standard) is typically established by:

• Known concentrations: For repeatability, reproducibility, linearity, and analytical sensitivity, samples are prepared with known concentrations of the analytes.
• Reference methods: For the analytical specificity and comparison studies, the predicate devices themselves or established reference methods (e.g., 2,6-Dichlorophenolindophenol Titration Method for Ascorbic Acid, Lange method for Ketone, etc. as specified in Table 35 "Traceability") serve as the reference for comparison.

Therefore, the concept of "number of experts" and their "qualifications" for ground truth establishment, as typically applied in AI/ML performance evaluation (e.g., for image interpretation), is not directly applicable here. The ground truth is analytical and based on laboratory standards and established measurement techniques.

4. Adjudication Method for the Test Set

Not applicable in the context of this analytical device. As explained above, the "ground truth" refers to known concentrations or results from predicate/reference methods. There isn't a subjective interpretation by multiple experts that would require an adjudication method like 2+1 or 3+1.

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 automated urine analyzer, not an AI/ML-driven diagnostic aid for human readers. It performs measurements to provide semi-quantitative results for various urine analytes. Therefore, there is no human-in-the-loop performance or comparison of human reader improvement with or without AI assistance.

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

Yes, the studies presented are all standalone performance evaluations of the device (UC-1800 Automatic Urine Analyzer with URIT 11FA/12FA Urine Reagent Strips) without human intervention in the measurement process. The device operates automatically to detect and report analyte levels. The comparison studies demonstrate its performance against existing predicate (standalone) analyzers.

7. The Type of Ground Truth Used

The ground truth used in the studies includes:

• Known Concentrations: For analytical performance studies such as precision (repeatability and reproducibility), linearity, analytical sensitivity, and analytical specificity (interference testing), samples were prepared with known, precisely measured concentrations of the target analytes or interfering substances.
• Predicate Device Measurements: For method comparison studies, the results obtained from the established predicate devices (Uritest-500B Urine Analyzer, Mission® U120 Ultra Urine Analyzer, and AUTION MAX AX-4030 Urinalysis System) served as the reference standard for comparison. These predicate devices also operate based on defined analytical principles.
• Reference Methods: Table 35 details the "Reference Method" used for traceability for each analyte (e.g., 2,6-Dichlorophenolindophenol Titration Method for Ascorbic Acid, Glucose Oxidase Method for Glucose, Acidometer measurement for pH, etc.). This indicates fundamental analytical standards are the basis for the stated detection ranges and performance.

8. The Sample Size for the Training Set

The document does not explicitly mention a "training set" in the context of machine learning. The UC-1800 Automatic Urine Analyzer uses reflectance photometry and other physical principles (refractometer for specific gravity, light-scattering for turbidity, light-transmission for color) to generate results, not an AI algorithm that learns from a dataset in the conventional sense. The "training" of such a system typically involves calibrating optical sensors and algorithms to known standards, which is part of the engineering design and quality control processes.

If interpretation of "training set" refers to the data used for the initial development and calibration of the device's measurement algorithms:

• No specific sample size for a "training set" for an AI model is reported because the device does not employ machine learning that requires a distinct "training set" and "test set" in the typical AI/ML development lifecycle.
• The system is calibrated using URIT urine control materials and calibration test strips (Table 9, "Calibration").

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

As noted above, the device does not use an AI/ML model with a "training set" in the common understanding. The system's operational parameters and calibration are established using:

• Reference materials and calibrators: The device is calibrated using "URIT urine control materials and calibration test strips" (Table 9, "Calibration"). These control materials and calibration strips would have their values established using highly accurate reference methods or certified reference materials, ensuring traceability to scientific standards (as indicated in Table 35 "Traceability").
• Chemical principles: The underlying "ground truth" for the device's internal algorithms (i.e., how they convert optical signals to analyte concentrations) is based on established chemical reactions and physical measurement principles (e.g., reflectance photometry, refractometry, light scattering, dye-binding, enzymatic reactions). The "ground truth" for developing and fine-tuning these algorithms would be derived from rigorous scientific validation against these known chemical and physical properties.

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The Minuteful - kidney test is an in-vitro diagnostic, home-use urine analysis test system for the semi-quantitative measurement of albumin and creatinine in urine, as well as the presentation of their ratio, the albumin-creatinine ratio (ACR). The system consists of a smartphone application, proprietary Color-Board and an ACR Reagent Strip. The system is available for prescription-use only and is intended for people at risk of kidney disease. Results are used in conjunction with clinical evaluation as an aid in the assessment of kidney health.

The Minuteful - kidney test is comprised of a kit and a smartphone application. It is intended for the semi-quantitative measurement of albumin and creatinine in urine, as well as the presentation of their ratio, the albumin-creatinine ratio (ACR). The Minuteful - kidney test is intended for prescription-use only, as a home-use device to aid in the assessment of kidney health. The results can be used together with clinical evaluation to guide patient care. The device's kit includes a urine receptacle, an ACR Reagent Strip, an absorbing (i.e. "blotting") pad, a proprietary Color-Board and a user manual. The device also consists of an easy-to-use smartphone application, image recognition algorithms, and a physician compendium. The software component of the Minuteful - kidney test consists of both an application (app) and a backend server. Both components encompass different computer vision and machine learning algorithmic components, performing the image analysis activities. The app instructs the user how to accurately administer the test. The Image Validation Transfer System (IVTS) component of the Minuteful - kidney test enables its usage across a wide range of smartphone types and operating systems, essentially making the test platform agnostic.

The provided text describes the Minuteful-kidney test (K222921) and its substantial equivalence to a predicate device (K210069). However, it specifically states that "The rest of the analytical performance studies are still relevant for the modified version of the Minuteful - kidney test, and their summary is available in the predicate device documentation (K210069)." This means the detailed acceptance criteria and the comprehensive study demonstrating the device meets those criteria are not present in this document but are referenced as being in the predicate device's documentation.

Therefore, I can report on the studies performed for K222921 to assert its substantial equivalence, but I cannot provide a table of acceptance criteria and reported device performance from this document for the overall device functionality as those details are in K210069. Nor can I provide information regarding sample sizes for test sets, expert qualifications, adjudication methods, MRMC studies, standalone performance, or ground truth details for K222921's overall performance since those are tied to the K210069 submission.

The studies described in K222921 (the current device) are focused on demonstrating that changes made to the device in K222921 do not negatively impact performance, thus maintaining substantial equivalence to its predicate.

Here's an analysis based solely on the provided text for K222921, noting the limitations:

Acceptance Criteria and Device Performance (Limited to K222921 changes):

Since the comprehensive performance data is referenced in K210069, the "acceptance criteria" discussed here are implicitly related to demonstrating that the modifications in K222921 (e.g., multilingual support, software enhancements) do not degrade the performance previously established for K210069. The studies conducted for K222921 focused on the robustness of the Image Validation Transfer System (IVTS) and the analytical limits of detection.

Study Details (for K222921 specific enhancements):

1. Sample size used for the test set and the data provenance:

   • Limit of Detection (LoD): The document does not specify the sample size for the LoD study for K222921. It mentions the study was designed and executed according to CLSI document EP17-A2.
   • Illumination, Physical, Shadow, Blurriness, Misplaced Urine Stick, Dirty Color-Board Studies: The document refers to "Tested smartphones" and "different conditions," but specific numerical sample sizes (e.g., number of images, tests, or smartphones) are not provided. The data provenance is implied to be laboratory-controlled since these are experimental conditions, but no explicit country of origin or retrospective/prospective nature is stated for these new studies. The overall device is intended for home use, so these validations mimic adverse home conditions.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • This information is not provided in the K222921 document. These types of analytical studies typically rely on reference methods or scientifically established standards rather than expert consensus. For the clinical performance, the document refers to the predicate device K210069, where such details would likely be found if applicable.

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

   • Not applicable/Not provided for these specific analytical studies. The assessment of whether performance was "not impacted" would likely come from statistical analysis against pre-defined thresholds.

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:

   • No MRMC or comparative effectiveness study involving human readers with and without AI assistance is mentioned in the K222921 submission. This device is an in-vitro diagnostic home-use test system where the smartphone app performs the measurement, rather than assisting a human in interpreting diagnostic images. Thus, the concept of "human readers improve with AI" in a traditional MRMC sense does not directly apply to this device's function.

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

   • The core of the described studies (LoD, Illumination, Physical, Shadow, Blurriness, Misplaced Urine Stick, Dirty Color-Board) are indeed standalone performance tests of the device's algorithmic capability to accurately read the test strip under various challenging conditions encountered in a home setting. The device is described as having "image recognition algorithms" and performing "image analysis activities."

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • For the analytical studies described (LoD, Illumination, etc.), the ground truth would be based on controlled experimental conditions and potentially quantitative reference measurements (e.g., known concentrations for LoD, controlled lighting conditions). The document does not specify the exact methods for establishing this ground truth but implies scientific rigor (e.g., "in accordance with guidance provided by the Clinical and Laboratory Standards Institute (CLSI) document EP17-A2"). For the clinical performance aspects, the document refers to K210069.

7. The sample size for the training set:

   • Not provided in the K222921 document. Training set details would typically be part of the initial K210069 submission for the machine learning algorithms.

8. How the ground truth for the training set was established:

   • Not provided in the K222921 document. This information would be found in the K210069 submission, likely involving laboratory-controlled tests with known analyte concentrations and reference methods for accurate measurement.

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The GEM Premier ChemSTAT is a portable critical care system for use by health care professionals to rapidly analyze lithium heparinized whole blood samples at the point of health care delivery in a clinical setting and in a central laboratory. The instrument provides quantitative measurements of sodium (Na+), Potassium (K+), Ionized Calcium (Ca++), Chloride (Cl-), Glucose (Glu), Lactate (Lac), Hematocrit (Hct), Creatinine (Crea), Blood Urea Nitrogen (BUN), Total Carbon Dioxide (tCO2), pH, and partial pressure of carbon dioxide (pCO2) from arterial and venous heparinized whole blood. These parameters, along with derived parameters, aid in the diagnosis of a patient's acid/base status, electrolyte and metabolite balance.

Electrolytes in the human body have multiple roles. Nearly all metabolic processes depend on or vary with electrolytes:

· Sodium (Na+) measurements are used in the diagnosis and treatment of aldosteronism, diabetes insipidus, adrenal hypertension, Addison's disease, dehydration, inappropriate antidiuretic secretion, or other diseases involving electrolyte imbalance.

· Potassium (K+) measurements are used to monitor electrolyte balance in the diagnosis and treatment of disease conditions characterized by low or high blood potassium levels.

· Ionized calcium (Ca++) measurements are used in the diagnosis and treatment of parathyroid disease, a variety of bone diseases, chronic renal disease and tetany. · Chloride (Cl-) measurements are used in the diagnosis and treatment of electrolyte and metabolic disorders, such as cystic fibrosis and diabetic acidosis.

· Glucose (Glu) measurement is used in the diagnosis, monitoring and treatment of carbohydrate metabolism disturbances including diabetes mellitus, neonatal hypoglycemia, idiopathic hypoglycemia, and of pancreatic islet cell carcinoma.

· Lactate (Lac) measurement is used to evaluate the acid-base status of patients suspected of having lactic acidosis, to monitor tissue hypoxia and strenuous physical exertion, and in the diagnosis of hyperlactatemia.

· Hematocrit (Hct) measurements in whole blood of the packed red cell volume of a blood sample are used to distinguish normal from abnormal states, such as anemia and erythrocytosis (an increase in the number of red cells).

· Creatinine (Crea) measurements are used in the diagnosis and treatment of renal diseases and in monitoring renal dialysis.

· Blood Urea Nitrogen (BUN) or urea measurements are used for the diagnosis, monitoring, and treatment of certain renal and metabolic diseases.

· Total carbon dioxide/tCO2 (also referred to as bicarbonate/HCO3-) is used in the diagnosis, monitoring, and treatment of numerous potentially serious disorders associated with changes in body acid-base balance.

· pH and pCO2 measurements in whole blood are used in the diagnosis and treatment of life-threatening acid-base disturbances.

The GEM Premier ChemSTAT system provides fast, accurate, quantitative measurements of Sodium (Na"), Potassium (K*), Ionized Calcium (Ca*), Chloride (Cl·), Glucose (Glu), Lactate (Lac), Hematocrit (Hct), Creatinine (Crea), Blood Urea Nitrogen (BUN), Total Carbon Dioxide (tCO2), pH, and partial pressure of carbon dioxide (pCO2) from arterial and venous lithium heparinized whole blood.

The provided text describes a Special 510(k) submission for an upgrade to the operating system of the GEM Premier ChemSTAT device. The device itself is an in vitro diagnostic (IVD) system for quantitative measurements of various blood parameters. The submission focuses on the software upgrade rather than a change in the device's fundamental function or performance.

Therefore, the "acceptance criteria" and "reported device performance" in this context refer to the successful verification and validation of the software upgrade and the continued adherence to the established performance of the unmodified device, as the indications for use and performance claims remain unchanged. The study proving this essentially consists of the software verification and validation activities.

Here's the information extracted from the document, tailored to the context of a software upgrade:

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a software upgrade with no changes to the performance claims of the device, the general acceptance criteria are that the upgraded software performs as intended without adversely affecting the device's established performance specifications. The reported device performance is that these criteria were met.

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

The document does not specify a "test set sample size" or "data provenance" in the traditional sense for evaluating diagnostic performance. The focus is on software verification and validation. Therefore, the "sample" for testing the software functionality would be the various test cases and scenarios designed to validate the operating system upgrade and its interaction with the GEM Premier ChemSTAT application software.

The document states: "Performance data is limited to Software Verification and Validation as the scope of this Special 510(k) is specific to an operating system upgrade from Fedora 17 Linux to WindRiver LTS 18 Linux."

Further details on the specific number of test cases, the nature of the data (e.g., simulated, actual runs on the device), or its origin are not provided in this summary.

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)

This information is not applicable to a software operating system upgrade as described. "Ground truth" in the context of expert consensus is typically relevant for diagnostic performance studies where human interpretation or a gold standard reference is needed (e.g., pathology for an imaging device). Here, the "ground truth" is the proper functioning of the software and its integration with the hardware, which is evaluated through engineering and software testing.

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

This information is not applicable for a software operating system upgrade. Adjudication methods like 2+1 or 3+1 are used in clinical studies to resolve discrepancies in expert interpretation of diagnostic results. Software verification and validation typically rely on predefined test outcomes and engineering assessments.

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

This information is not applicable. An MRMC comparative effectiveness study is used to evaluate the impact of an AI algorithm on human reader performance, usually for diagnostic tasks. This submission is for a software operating system upgrade for an existing IVD device, not for a new AI algorithm.

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

The concept of "standalone performance" in the context of an algorithm's diagnostic capability (like an AI algorithm) is not directly applicable here. The device itself (GEM Premier ChemSTAT) operates to provide quantitative measurements. The software upgrade ensures the continued, correct operation of the device. The verification and validation activities demonstrate that the upgraded software performs its functions correctly as part of the overall device system.

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

For this software upgrade, the "ground truth" is the expected behavior and functionality of the software and the device. This is established through:

• Functional specifications: The software is expected to perform according to its design specifications.
• Risk analysis: The software should not introduce new risks or fail to mitigate existing ones.
• Cybersecurity standards: The software should meet cybersecurity requirements.
• Established device performance: The software upgrade should not negatively impact the established analytical and clinical performance of the GEM Premier ChemSTAT device (which relies on the physical and chemical principles of its measurements).

The document explicitly states that the changes "do not introduce...changes to labeled performance claims." This implies that the performance of the device (e.g., accuracy, precision of Na+, K+, Glu measurements) remains the same as previously cleared, and the software upgrade was validated not to alter these.

8. The sample size for the training set

This information is not applicable. Training sets are used for machine learning models. This submission describes a conventional software operating system upgrade (Fedora 17 Linux to WindRiver LTS 18 Linux) for an existing IVD device, not the development or retraining of a machine learning algorithm.

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

This information is not applicable, as there is no training set for a machine learning model; it is a software operating system upgrade.

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The Minuteful - kidney test is an in-vitro diagnostic, home-use urine analysis test system for the semi-quantitative measurement of albumin and creatinine in urine, as well as the presentation of their ratio, the albumin-creatinine ratio (ACR). The system consists of a smartphone application, proprietary Color-Board and an ACR Reagent Strip. The system is available for prescription-use only and is intended for people at risk of kidney disease. Results are intended to be used in conjunction with clinical evaluation as an aid in the assessment of kidney health.

The Minuteful - kidney test is comprised of a kit and a smartphone application. It is intended for the semi-quantitative measurement of albumin and creatinine in urine, as well as the presentation of their ratio, the albumin-creatinine ratio (ACR). The Minuteful - kidney test is intended for prescription-use only, as a home-use device to aid in the assessment of kidney health. The results can be used together with clinical evaluation to guide patient care. The device is provided as a kit that comprises a urine receptacle, an ACR Reagent Strip, an absorbing (i.e. "blotting") pad, a proprietary Color-Board and a user manual. The device also consists of an easy-to-use smartphone application, image recognition algorithms, and a physician compendium. The software component of the Minuteful - kidney test consists of both an application (app) and a backend server. Both components encompass different computer vision and machine learning algorithmic components, performing the image analysis activities. The app instructs the user how to accurately administer the test. The Image Validation Transfer System (IVTS) component of the Minuteful - kidney test enables its usage across a wide range of smartphone types and operating systems, essentially making the test platform agnostic.

Here's a breakdown of the acceptance criteria and study information for the Healthy.io Minuteful - kidney test (K210069), based on the provided document:

Acceptance Criteria and Device Performance for Minuteful - kidney test (K210069)

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document implies acceptance criteria by reporting performance results against the predicate device that demonstrate substantial equivalence.

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

• Sample Size: More than 450 subjects were recruited for the clinical trials.
• Data Provenance: The document does not explicitly state the country of origin. The study was a prospective clinical trial, as subjects were "recruited" and tasks were "completed" within the context of the study.

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

The ground truth was established by comparing the Minuteful - kidney test results to those obtained from a professional user performing the test on the URISCAN Optima Urine Analyzer (predicate device).

• Number of Experts: Not explicitly stated as a count of individual professionals, but referred to as "a professional user." It's implied that this
  professional operated the predicate device.
• Qualifications: "Professional user" suggests trained laboratory or healthcare personnel familiar with operating the URISCAN Optima Urine Analyzer and interpreting its results. Specific credentials (e.g., medical technologist, clinical laboratory scientist, years of experience) are not provided.

4. Adjudication Method for the Test Set

The adjudication method involved a 2-part comparison:

1. A lay user (subject in the clinical trial) performed the test using the Minuteful - kidney test app.
2. A professional user (operating the predicate device, URISCAN Optima Urine Analyzer) then performed the test on the same urine sample.

The professional user was blinded to the results of the lay user until after they had completed their test. This can be considered a form of adjudication where the predicate device's result, as read by a professional, serves as the comparison benchmark. There was no explicit multi-expert consensus or 2+1/3+1 method described for establishing a single "ground truth" independent of the comparison devices; rather, the predicate device's output was the reference.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study was not explicitly done in the sense of comparing multiple human readers with and without AI assistance on the same cases. The study compared a lay user with the AI-powered device to a professional user with a predicate device. It was a method comparison study to show substantial equivalence, not a study evaluating human reader improvement with AI assistance.

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

The clinical performance study involved a lay user interacting with the smartphone application and performing the test steps guided by the app. While the app uses "image recognition algorithms" and "machine learning algorithmic components," it is not a purely standalone algorithm-only performance assessment in the sense of a laboratory-based algorithm evaluation without human interaction for image capture and strip preparation. However, the analytical performance testing (Precision, Interference, Limit of Detection, Linearity, Stability) would represent the closest to "standalone" algorithm performance testing, as these evaluate the device's technical capabilities in a controlled environment. The linearity study, showing 100% exact match for every level of albumin, creatinine, and ACR, is a strong indicator of the core algorithm's accuracy at different concentrations.

7. The Type of Ground Truth Used

The ground truth was established by comparison to a legally marketed predicate device (URISCAN Optima Urine Analyzer) operated by a professional user. This is a form of reference standard comparison where the predicate device's output serves as the truth.

8. The Sample Size for the Training Set

The document does not provide information regarding the sample size for the training set used for the device's algorithms.

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

The document does not provide information on how the ground truth was established for the training set of the device's algorithms. It only describes the ground truth for the clinical performance (test set) comparison.

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The Creatinine2 assay is used for the quantitation of creatinine in human serum, plasma, or urine on the ARCHITECT c System.

The Creatinine2 assay is to be used as an aid in the diagnosis and treatment of renal diseases, in monitoring renal dialysis, and as a calculation basis for measuring other urine analytes.

The Creatinine2 assay is an automated clinical chemistry assay. At an alkaline pH, creatinine in the sample reacts with picric acid to form a creatinine-picrate complex that absorbs at 500 nm. The rate of increase in absorbance is directly proportional to the concentration of creatinine in the sample.

The provided document describes the Abbott Creatinine2 assay, an in vitro diagnostic device, and its performance relative to a predicate device. The information needed to answer the request is primarily found in Section 5: 510(k) Summary (Summary of Safety and Effectiveness), specifically subsections VIII (Summary of Nonclinical Performance) and VII (Comparison of Technological Characteristics).

Here's the breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" as a separate, pre-defined column. Instead, it presents the results of various performance studies. The "Reported Device Performance" below is extracted directly from the study results presented in the document. The comparable predicate device values are included for context where available.

Creatinine2 Assay - Performance Summary

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

The document describes several nonclinical laboratory studies.

• Precision (Within-Laboratory): For both Serum/Plasma and Urine, the studies tested 80 replicates per sample type for each of the two controls and three human panels (5 samples total). This was done in duplicate, twice per day, on 20 days. The provenance of the human panels (e.g., country of origin, retrospective/prospective) is not specified, but they are referred to as "human serum panels" and "human urine panels." This data is ex vivo laboratory testing.
• Accuracy: No specific sample size of "patient samples" is given. The study was performed using "material standardized to the Certified Reference Material NIST SRM 967a" for serum/plasma and "material standardized to the Certified Reference Material NIST SRM 914a" for urine.
• Lower Limits of Measurement (LoB, LoD, LoQ): n ≥ 60 replicates for zero-analyte and low-analyte level samples for LoB/LoD, and for low-analyte level samples for LoQ.
• Linearity: The sample size for linearity is not explicitly stated in terms of number of unique samples, but it covers the analytical measuring interval by spiking and dilution.
• Method Comparison:
  • Serum: 128 samples
  • Urine: 129 samples
    The provenance of these clinical samples (e.g., country of origin, retrospective or prospective) is not explicitly stated.
• Interference: "Each substance was tested at 2 levels of the analyte." No specific sample size (n) for the number of replicates per interference test is given beyond this, nor is the provenance of the base samples used.
• Tube Type: "Samples were collected from a minimum of 40 donors." The provenance is not explicitly stated.

The studies described are nonclinical laboratory studies, primarily involving analytical performance evaluation rather than clinical patient studies.

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

This information is not applicable (N/A) to this specific device (Creatinine2 assay). The device is an in vitro diagnostic for quantitative measurement of creatinine, not an imaging device or a device requiring expert interpretation of complex clinical data to establish ground truth for its performance evaluation (e.g., a diagnosis of a disease from imaging). The "ground truth" for its analytical accuracy is typically established against certified reference materials (NIST SRM 967a for serum/plasma and NIST SRM 914a for urine) or reference methods, not by human experts adjudicating cases for a test set.

4. Adjudication Method for the Test Set

This information is not applicable (N/A) for the same reasons as #3. Clinical adjudication by multiple experts (like 2+1, 3+1) is typically used for devices that rely on human interpretation of outputs (e.g., medical images, pathology slides) where consensus or expert opinion defines the ground truth for diagnostic accuracy. This device measures a biochemical analyte.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study was not done. This type of study is relevant for medical devices where human readers or interpreters are part of the diagnostic workflow, such as imaging-based AI tools. The Creatinine2 assay is an automated clinical chemistry assay that directly measures creatinine levels in biological samples and does not involve human image interpretation or a "human-in-the-loop" effectiveness study as typically understood in the context of MRMC studies.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

The Creatinine2 assay is a standalone (algorithm only) device in the sense that it performs a quantitative measurement without a human-in-the-loop for interpreting the output of the device to arrive at the creatinine value. The performance metrics described (precision, accuracy, linearity, lower limits of measurement, interference, method comparison) are all tests of the device's performance directly, independent of human interpretation or assistance in generating the result.

7. The Type of Ground Truth Used

The ground truth for the performance evaluation of the Creatinine2 assay was primarily established using:

• Certified Reference Materials: NIST SRM 967a for serum/plasma and NIST SRM 914a for urine were used for accuracy studies.
• Predicate Device/Reference Method: The Creatinine assay (K083809; List No. 3L81) was used as a comparator for the method comparison study to assess substantial equivalence.
• Defined Standards/Controls: For precision and lower limits of measurement, studies used control materials and low-analyte level samples with known or established concentrations to determine repeatability, detection, and quantitation limits.

8. The Sample Size for the Training Set

This information is not applicable (N/A). The Creatinine2 assay is a chemical assay, not a machine learning or AI-based device that requires a "training set" in the computational sense. Its performance is based on the chemical reaction and analytical methods described.

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

This information is not applicable (N/A) for the same reasons as #8.

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The Atellica® CH Enzymatic Creatinine 3 (ECre3) assay is for in vitro diagnostic use in the quantitative determination of creatinine in human serum, plasma (lithium heparin and dipotassium EDTA), and urine using the Atellica® CH Analyzer. Such measurements are used in the diagnosis and treatment of renal diseases and in monitoring renal dialysis.

The Atellica CH ECre3 assay measures the concentration of creatinine through a series of coupled enzymatic reactions and is based upon the method developed by Masaru and Mitsutaka. The Atellica CH ECre3 assay uses a series of coupled enzymatic reactions. In a "pretreatment" reaction, endogenous creatine and sarcosine are removed from a test sample by creatinase and sarcosine oxidase. The level of creatinine in a test sample is then determined through coupled enzymatic reactions. First, creatinine is enzymatically converted by creatininase into creatine. Creatine is then enzymatically converted to sarcosine by creatinase. This is followed by the oxidation of sarcosine by sarcosine oxidase to produce hydrogen peroxide. In the presence of peroxidase, the hydrogen peroxide allows for the oxidative condensation of 4-aminoantipyrine and N-ethyl-N-(3-methylphenyl)-N'-succinyl-ethylenediamine to produce a reddish purple quinone pigment. The absorbance of this quinone pigment is measured as an endpoint reaction at 545/694 nm.

This document describes the performance of the Atellica® CH Enzymatic Creatinine 3 (ECre3) assay, a new in vitro diagnostic device for quantitative determination of creatinine. The information provided is for a 510(k) Premarket Notification to the FDA, demonstrating substantial equivalence to a predicate device. Therefore, the "acceptance criteria" here refers to the performance thresholds that the new device must meet to show it functions as intended and is comparable to the predicate device. The "study" refers to the analytical performance validation studies conducted.

Here's the breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance & 2. Sample Sizes and Data Provenance

Since this is an in vitro diagnostic (IVD) device, the "acceptance criteria" are typically defined as performance specifications that demonstrate the device's analytical accuracy, precision, linearity, and freedom from interferences. These are not clinical acceptance criteria in the sense of diagnostic accuracy to a specific disease state, but rather analytical performance metrics. The document compares the new device (candidate) to a predicate device and established standards.

Data Provenance (General): The document does not explicitly state the country of origin for the patient samples used in method comparison or specimen equivalency studies. It also does not specify if the studies were retrospective or prospective, though for IVD analytical performance, they are typically prospective analytical studies using characterized samples (pooled, spiked, or real patient samples collected for the study).

Regarding items 3-9 for this IVD document:

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• For an IVD device like this, "ground truth" for analytical performance studies is established by reference methods (e.g., Isotope Dilution Mass Spectrometry - IDMS, as seen in the assay comparison) or against a legally marketed predicate device (ADVIA Chemistry ECRE_2 assay). It is not established by human experts (like radiologists reading images) for diagnostic accuracy or consensus in the typical sense for medical imaging or clinical decision support AI. The "experts" would be the metrologists or lab professionals validating the reference methods according to CLSI guidelines.

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

• Not applicable in the context of an IVD analytical performance study. Adjudication methods are relevant for subjective interpretations, like radiology image reads or pathological diagnoses, where human variability exists and a consensus "ground truth" needs to be established. Here, the "truth" is quantitative measurement by reference methods.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

• Not applicable. MRMC studies are used to assess the comparative effectiveness of different diagnostic methods (often involving human readers and AI) where subjectivity and reader variability are factors. This submission is for an in vitro diagnostic assay, which provides quantitative values, not an imaging-based AI or a system that aids human interpretation in a subjective setting.

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

• This is inherently a "standalone" device in the sense that it is an automated laboratory assay. Its performance is measured directly (algorithm only) against reference methods or the predicate, as presented in the analytical performance section. There isn't a "human-in-the-loop" component in its operation or interpretation beyond the lab professional running the analyzer and reviewing results.

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

• The ground truth for this device's performance evaluation is established by:
  • Reference Methods: Specifically, Isotope Dilution Mass Spectrometry (IDMS) for creatinine measurements, which is a highly accurate and precise chromatographic-mass spectrometric method. This is considered the "gold standard" for creatinine measurement.
  • Comparison to a Legally Marketed Predicate Device: The ADVIA® Chemistry Enzymatic Creatinine_2 (ECRE_2) assay. The performance against the predicate is used to demonstrate "substantial equivalence."
  • Internal analytical validation: Using controlled samples (e.g., spiked samples, control materials) for precision, linearity, interference studies, where the "ground truth" is the known concentration or expected behavior of the sample.

8. The sample size for the training set:

• This document describes the validation of the device's performance, not its development or "training." For an IVD assay (like a chemical reagent and analyzer system), there isn't a "training set" in the machine learning sense. The assay is based on established enzymatic reaction principles, not on learned patterns from a "training set" of data. Therefore, this concept is not applicable here.

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

• Not applicable, as there is no "training set" for this type of IVD device. The assay's chemical reactions and measurement principles are intrinsically defined, not learned from data.

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Medicon Hellas Albumin: Reagent for the quantitative measurement of albumin in serum. Albumin measurements are used in the diagnosis and treatment of numerous diseases involving primarily the liver or kidneys.

Medicon Hellas Calcium: Reagent for the quantitative measurement of calcium in serum or urine. Calcium measurements are used in the diagnosis and treatment of parathyroid disease, a variety of bone diseases, chronic renal disease and tetany (intermittent muscular contractions or spasms).

Medicon Hellas Creatinine: Reagent for the quantitative measurement of creatinine in serum and urine. Creatinine measurements are used in the diagnosis and treatment of renal diseases and in monitoring renal dialysis.

Medicon Hellas Glucose: Reagent for the quantitative measurement of glucose in serum and urine. Glucose measurements are used in the diagnosis and treatment of carbohydrate metabolism disorders including diabetes mellitus, neonatal hypoglycemia, and idiopathic hypoglycemia, and of pancreatic islet cell carcinoma.

Medicon Hellas Direct Bilirubin; Reagent for the quantitative measurement of direct bilirubin (conjugated) in serum. Measurements of the level of direct bilirubin is used in the diagnosis and treatment of liver, hemolytic, hematological, and metabolic disorders, including hepatitis and gall blader block.

Medicon Hellas Total Bilirubin: Reagent for the quantitative measurements of total bilirubin in serum. Measurements of the levels of total bilirubin is used in the diagnosis and treatment of liver. hemolytic hematological, and metabolic disorders, including hepatitis and gall bladder block.

Medicon Hellas Urea Nitrogen: Reagent is for the quantitative measurement of urea nitrogen in serum and urine. Measurements are used in the diagnosis and treatment of certain renal and metabolic diseases.

The Medicon Hellas Albumin, Medicon Hellas Calcium, Medicon Hellas Creatinine, Medicon Hellas Glucose, Medicon Hellas Direct Bilirubin, Medicon Hellas Total Bilirubin, and Medicon Hellas Urea Nitrogen are reagents for use with Diatron Pictus 500 Clinical Chemistry Analyzers. They are test systems for the quantitative measurement of albumin, calcium, creatinine, glucose, direct and total bilirubin, and urea nitrogen in human serum and urine where clinically applicable. The methods employed are photometric, utilizing reactions between the sample and reagents to produce a colored chromophore or a change in absorbance that is proportional to the concentration of the analyte. The analyzer photometer reads the absorbances at time intervals dictated by the method application stored in the analyzer memory, and the change in absorbance is calculated automatically.

The provided text describes the performance of several Medicon Hellas assays (Albumin, Calcium, Creatinine, Glucose, Direct Bilirubin, Total Bilirubin, and Urea Nitrogen) when run on the Diatron Pictus 500 Clinical Chemistry Analyzer, demonstrating their substantial equivalence to predicate devices (Beckman Coulter AU reagents on AU2700 analyzer, and Abbott Architect Direct Bilirubin on Architect c8000 analyzer).

Here's an analysis of the provided information, structured to address your specific points regarding acceptance criteria and study details:

1. A Table of Acceptance Criteria and the Reported Device Performance:

The document doesn't explicitly state "acceptance criteria" in a single, overarching table with pass/fail remarks. Instead, it describes each performance characteristic and then presents the results. The "Summary" sections for each study type imply that the results met the pre-defined acceptance criteria for demonstrating substantial equivalence. For instance, for accuracy, it states "Accuracy studies completed on at least three lots of each candidate reagent confirm that Medicon albumin... are substantially equivalent to the related predicate devices." This implies that the statistical analyses (Deming regression, R2, slope, intercept) fell within acceptable ranges. Similarly, for precision, it states "All lots passed acceptance criteria for each applicable sample type at each level."

Since explicit acceptance criteria are not presented, they are inferred from the demonstrated performance and the statement that the devices "passed acceptance criteria" or "met statistical acceptance criteria." Below is a table summarizing the reported device performance for each analyte. The "Acceptance Criteria" column will reflect the general statements of success or the implied ranges from the results themselves, as explicit numerical targets for individual tests are not given.

Implied Acceptance Criteria and Reported Device Performance

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