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The Wiener Laboratory enzyme-linked Immunosorbent assay (ELISA) recombinante V. 3.0 test system is a manual and automated instrument assay for the qualitative detection of total antibodies (IgG and IgM) to Trypanosoma cruzi in human serum and plasma (EDTA, heparin, or Citrate) using recombinant antigens of T. cruzi. Reactive results are presumptive evidence of present or past infection with Trypanosoma cruzi.

In this qualitative technique for the detection of antibodies anti-T. Cruzi, the sample is diluted in the wells in which recombinant antigens starting from specific proteins from the epimastigote and trypomastigote stages of the T. cruzi corresponding to highly conserved zones are immobilized. These antigens are proteins with aminoacid sequences repeated in tandem. SAPA (shed acute phase antigen) antigens detect antibodies in 93% of the patients' sera during the acute phase of the infection. It comes from the trypomastigote-bloodstream form of the parasite; #1, #2 and #30 antigens detect antibodies in chronic patients; #13 and #36 specially detect antibodies in sera both from acute and chronic patients.
If the sample contains Chagas' antibodies, they bind to the antigens bound to the support. The unbound antigens and antibodies are removed by washing, after which anti-human immunoglobulin antibodies conjugated to peroxidase are added. If a reaction was produced in the first step of the process, the conjugate is bound. After a new washing step and the addition of a chromogenic substrate and stopping reagent, specimens containing antibodies to T. cruzi produce a color reaction which can be read with a standard ELISA plate reader.

Here's an analysis of the provided text to extract information about acceptance criteria and the study that proves the device meets them:

Device Name: Chagatest ELISA recombinante v.3.0 (also referred to as Wiener lab Chagatest ELISA rec. v.3.0)

Intended Use: Qualitative detection of antibodies to Trypanosoma cruzi (causative agent of Chagas' disease) in human serum and plasma. Useful in establishing prior exposure to T. cruzi and as an aid in diagnosis.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state pre-defined acceptance criteria in a dedicated section. However, it presents "Performance Characteristics" including "Relative Sensitivity," "Relative Specificity," and "Relative Agreement," with specified confidence intervals. It also highlights an overall relative sensitivity of 97.9% and relative specificity of 97.8% (after resolution of discordant samples) or 97.9% and 97.8% (before resolution of discordant samples) from a combined analysis of multiple sites.

Given the context of a 510(k) summary seeking substantial equivalence, implicit acceptance criteria would likely involve demonstrating high relative sensitivity and specificity that are comparable to or better than predicate devices and meet general diagnostic accuracy expectations for such assays. While not explicitly stated as "acceptance criteria," the reported performance values are what would be used by the FDA to determine substantial equivalence.

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

The test set consisted of multiple studies performed at different sites. The total sample size and data provenance are:

Total combined sample size for comparative effectiveness/performance studies appears to be over 5000 specimens across various studies. All data appears to be retrospective based on the nature of the studies (testing existing specimens, panels, or comparing against established methods). The countries of origin include Argentina, Mexico, Chile, and Brazil, with some studies also including low-risk individuals from the U.S.

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

The document does not explicitly state the number or specific qualifications of individual experts. However, it describes that ground truth was established using:

• Comparison methods: Predicate devices (MERIDIAN Premier™ Chagas' IgG ELISA, ABBOTT Chagas Antibody EIA) were used as primary comparators.
• Confirmatory/Reference tests: Radio Immuno Precipitation Assay (RIPA), Indirect Hemagglutination Assay (IHA), Immunofluorescence Assay (IFA), and xenodiagnosis were used as reference methods, particularly for resolving discordant results or establishing the status of selected panels.
• Clinical context: Specimens were often from "patients with confirmed Chagas' disease by xenodiagnosis, IHA and IFA," "blood donors," or "patients from an endemic area."
• The reference tests (IHA, IFA, RIPA, xenodiagnosis) are typically performed and interpreted by experienced laboratory personnel or medical professionals.

4. Adjudication Method for the Test Set

Adjudication methods are described for discordant results:

• Discordant results between the Wiener lab ELISA and predicate devices were often adjudicated using reference methods like RIPA, IHA, and/or IFA.
  • For example: "Out of 5 specimens with discordant results, all 5 were reactive by Wiener lab ELISA and a RIPA, but non-reactive by Meridian." (Section 1.2)
  • "Of the 12 specimens with discordant results... 6 specimens were reactive by Wiener lab Chagatest ELISA rec.v.3.0 and non-reactive by Abbott Chagas Antibody EIA. Out of those 6 specimens, 3 were reactive by IFA." (Section 1.3)
  • "7 specimens were reactive by Wiener lab ELISA, reactive by IHA / IFA / RIPA and/or Meridian ELISA and non-reactive by Abbott ELISA." (Section 1.5a)

The specific process for how these reference results were used to adjudicate a final ground truth (e.g., majority vote, hierarchy of tests) is not explicitly detailed but implied that the consensus or superior reference test determined the final status.

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

No, an MRMC comparative effectiveness study was not explicitly described. This is an in vitro diagnostic device for laboratory use, and its performance is typically assessed by comparing its numerical output (e.g., signal/cut-off ratio) to a threshold and then to gold standard/reference methods, rather than human readers interpreting images or data for diagnosis. The studies focused on comparing the device's diagnostic accuracy (sensitivity, specificity, agreement) to other assays and established reference methods.

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

Yes, the studies reported are standalone performance evaluations of the Wiener lab Chagatest ELISA recombinante v.3.0. The "algorithm" here refers to the ELISA assay itself, which generates quantitative results (absorbance, s/c ratio) that are then interpreted against a predefined cutoff. The performance metrics (relative sensitivity, specificity, agreement) measure the device's accuracy in identifying positive or negative samples independently, without direct human intervention in the interpretation of each test result beyond comparing it to the cutoff. The studies compare the device's output to other test systems.

7. The Type of Ground Truth Used

The ground truth for the test sets was established using a combination of:

• Expert Consensus/Reference Methods: Primarily through established serological tests like Indirect Hemagglutination Assay (IHA), Immunofluorescence Assay (IFA), Radio Immuno Precipitation Assay (RIPA), and in some cases, previous ELISA results from other reference systems.
• Pathology/Outcomes Data (Indirectly): Xenodiagnosis, a biological method for detecting T. cruzi infection, was used for some "confirmed Chagas' disease" cases (e.g., Section 2.3, 2.11, 5). This can be considered a strong indicator of true infection.
• Clinical context: Patients from endemic areas and those with confirmed Chagas' disease were used to ensure the presence of antibodies, while low-risk individuals were used for specificity studies.

Therefore, the ground truth is a composite ground truth, derived from multiple established diagnostic methods and clinical confirmation strategies.

8. The Sample Size for the Training Set

The document does not specify a separate "training set" or "validation set" in the context of machine learning model development. This is an ELISA kit, which is a biochemical assay, not a machine learning algorithm that requires a training phase. The "studies" described are performance evaluations against established predicate devices and reference methods using various clinical samples. The "training" data for such a kit would implicitly be the data used during its development and optimization, which is not detailed here. The studies provided demonstrate the device's performance on various patient populations, which serves as a clinical validation.

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

As noted above, this is an ELISA assay, not a machine learning model, so the concept of a "training set" ground truth in the AI context does not directly apply. The establishment of ground truth for the samples used in the performance evaluations (analogous to a test set in ML) is described in point 7 (composite ground truth from various reference methods and clinical confirmation).

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For the quantitative calibration of WIENER LAB's clinical chemistry procedures. Calibrador A plus is a device intended for medical purposes for use in a test system to establish points of reference that are used in the determination of values in the measurement of substances in human specimens.

Calibrador A plus consists of Ivophilized human serum containing the compounds usually determined in clinical chemistry laboratories in the appropriate concentrations to ensure optimum calibration of clinical chemistry procedures. Such concentrations are lot-specific and are provided in product insert.

The provided text describes a 510(k) submission for a medical device called "Wiener lab. Calibrador A Plus". This is a multi-analyte calibrator and the submission focuses on demonstrating substantial equivalence to a predicate device, the ROCHE Calibrator for Automated systems (C.f.a.s.).

Here's an analysis of the requested information, based on the provided text:

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

The document does not explicitly state "acceptance criteria" or provide performance metrics in the format of a table as typically seen for diagnostic device performance (e.g., sensitivity, specificity, accuracy, precision). Instead, the submission relies on demonstrating substantial equivalence to a predicate device.

The "performance" is implicitly demonstrated through the similarities between the Wiener lab. Calibrador A Plus and the ROCHE C.f.a.s. in terms of:

• Intended Use: Both are for the calibration of clinical chemistry procedures.
• Format: Both are lyophilized pooled human sera with added constituents.
• Constituent Analytes: Both calibrate for the same set of 16 specific analytes (Albumin, Direct bilirubin, Total bilirubin, Calcium, Cholesterol, Creatinine, HDL Cholesterol, Glucose, Iron, Magnesium, Phosphorus, Total proteins, Triglycerides, Uric acid, Urea). The ROCHE device additionally calibrates for broader categories of "Enzymes" and "Electrolytes", which are not explicitly listed for the Wiener lab. calibrator.
• Stability: The ROCHE device's stability is described (stable in refrigerator until expiration, reconstituted for 8 hours at room temp, 2 days refrigerated or 1 month frozen), but the Wiener lab. calibrator's stability information is not provided in the comparison table.
• Levels: ROCHE C.f.a.s. is a "Single Level" calibrator, and this detail is not provided for the Wiener lab. calibrator in the comparison table.

The "acceptance criterion" in this context is that the device is "substantially equivalent" to the predicate device in its intended use, form, and composition for the listed analytes. The "reported device performance" is the statement that "Above mentioned data show substantial equivalency to the predicate device."

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 describe any specific "test set" of samples or data used for an independent performance evaluation. This submission is focused on demonstrating substantial equivalence through a comparison of product characteristics and intended use, rather than presenting results from a clinical or analytical performance study with a test set. Therefore, information on sample size, data provenance, retrospective/prospective nature, and country of origin is not applicable or not provided.

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)

Since there is no described "test set" for performance evaluation, there is no mention of experts or their qualifications used to establish ground truth for such a set. Establishing ground truth typically applies to diagnostic device performance studies, which are not detailed here.

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

As no "test set" with a performance evaluation is described, adjudication methods are not applicable and not mentioned in this document.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

No MRMC study was done. This device is a calibrator, not a diagnostic imaging device with human readers or AI assistance. Therefore, this section is not applicable.

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

No standalone algorithm performance study was done. This device is a multi-analyte calibrator, not an algorithm. Therefore, this section is not applicable.

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

Since no performance study with a test set is described, no specific "ground truth" establishment method (expert consensus, pathology, outcomes data, etc.) is mentioned. The "ground truth" in this context is the established performance and characteristics of the predicate device, to which the new device is being compared for substantial equivalence.

8. The sample size for the training set

The document does not describe a "training set" as this is a calibrator and not a machine learning or AI-based device that would require training data.

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

As there is no described "training set," the method for establishing its ground truth is not applicable and not mentioned.

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The WIENER LAB. Colinesterasa AA test system is a quantitative in vitro diagnostic device intended to be used in the quantitative determination of cholinesterase (an enzyme that catalyzes the hydrolysis of acetylcholine to choline) in human specimens, on both manual and automated systems. There are two principal types of cholinesterase in human tissues. True cholinesterase is present at nerve endings and in erythrocytes (red blood cells) but is not present in plasma. Pseudo cholinesterase is present in plasma and liver but is not present in erythrocytes. Measurements obtained by this device are used in the diagnosis and treatment of cholinesterase inhibition disorders (e.g., insecticide poisoning and succinylcholine poisoning).

Kinetic Method. The principle is based on the following reaction system: Cholinesterase Butyrylthiocholine + H2O -> Thiocholine + Butyrate Thiocholine + DTNB -> 2-Nitro-5-Mercapto-benzoate The cholinesterase activity is determined by measuring the rate of absorbance change at 405 nm. DTNB: 5,5'-Dithiobis-2-Nitrobenzoic Acid. ChE: serum or plasma cholinesterase.

Here's a breakdown of the acceptance criteria and study information for the "Wiener lab. Colinesterasa AA" device, based on the provided text:

Device: Wiener lab. Colinesterasa AA (Cholinesterase test system)
Predicate Device: SIGMA DIAGNOSTICS Cholinesterase (BTC) (Cat. 421-10)

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are not explicitly stated as separate targets, but rather are implied by direct comparison to the predicate device. The study's goal was to demonstrate "substantial equivalence" to the predicate, meaning the performance of the Wiener lab. Colinesterasa AA device should be comparable to or better than the SIGMA DIAGNOSTICS Cholinesterase (BTC) system.

Note on Acceptance Criteria: The document explicitly states the objective is to demonstrate "substantial equivalence" to the predicate device. Therefore, the "acceptance criteria" are implied to be achieving comparable or improved performance across the listed metrics. The reported device performance generally demonstrates better performance (e.g., higher linearity, lower CVs for precision) than the predicate device, which supports the claim of substantial equivalence.

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

The document does not explicitly state the sample size for the test set used to generate the reported performance data (linearity, precision, expected values).

The data provenance is not explicitly stated. However, given that "Wiener Laboratorios S.A.I.C." is located in Rosario, Argentina, it is reasonable to infer that the studies were likely conducted in Argentina or involved samples from that region. The study type (retrospective or prospective) is not mentioned.

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

This information is not applicable to this type of in vitro diagnostic device for chemical analysis. Ground truth for enzyme activity measurements is established through the analytical performance of the device (e.g., linearity, precision, accuracy against known standards or validated methods), not through expert consensus on qualitative interpretation. The "ground truth" here is the actual cholinesterase activity in the samples, measured by the device and compared for consistency and accuracy.

4. Adjudication Method for the Test Set

Adjudication methods (e.g., 2+1, 3+1) are typically used for qualitative or interpretive assessments (e.g., diagnostic imaging, pathology slides) where there might be inter-reader variability. This is not applicable to the quantitative measurement of an enzyme activity by an in vitro diagnostic device.

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 is not applicable. The device is an in vitro diagnostic for quantitative chemical analysis, not an AI-powered diagnostic imaging or qualitative assessment tool that involves human readers or AI assistance.

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

This is not applicable in the context of an "algorithm only" device as typically understood for AI or image analysis. The "Wiener lab. Colinesterasa AA" system is a chemical reagent-based assay. Its performance is inherent to the chemical reactions and subsequent spectrophotometric measurement, whether operated manually or on an automated system. Its operation is analogous to a standalone diagnostic test in that the result is directly generated by the system, requiring human intervention primarily for sample handling, instrument setup, and interpretation of the numerical result against reference ranges.

7. The Type of Ground Truth Used

The ground truth used for performance validation (linearity, precision, expected values) would typically be:

• For Linearity: Known concentrations of cholinesterase, or samples whose concentrations have been established by a gold-standard reference method.
• For Precision: Repeated measurements on control materials or patient samples where consistent readings are expected.
• For Expected Values: Data collected from a statistically significant healthy population (reference ranges) as well as patient populations with known cholinesterase inhibition disorders. The provided "Expected values" table serves as a reference range established through clinical studies.

8. The Sample Size for the Training Set

This is not applicable as the device is a chemical reagent-based analytical system, not a machine learning model that requires a "training set" in the conventional sense. The "training" for such a system involves formulation optimization and calibration, which doesn't typically involve a "training set" of patient data as understood in AI/ML.

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

This is not applicable for the reasons stated in point 8.

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The "Wiener lab. Bilirrubina directa AA" test system is a quantitative in vitro diagnostic device intended to be used in the determination of direct bilirubin in human sera and heparinized plasmas on both manual and automated systems. Measurements of the levels of bilirubin, and organic compound formed during the normal and abnormal destruction of red blood cells, are used in the diagnosis and treatment of liver. hemolytic, hematological, and metabolic disorders, including hepatitis and gall bladder block.

Direct bilirubin is measured using a stable dichlorophenyldiazonium salt (DPD) to form a red azocompound in an acid solution, with maximal O.D. at 546 nm. The amount of direct bilirubin is determined by measuring the absorbance of this pigment.

The provided text describes a 510(k) summary for the "WIENER LAB. BILIRRUBINA DIRECTA AA" test system, which is a quantitative in vitro diagnostic device for determining direct bilirubin in human sera and heparinized plasmas. The summary claims substantial equivalence to a predicate device, the DMA Direct Bilirubin Plus test system.

The document does not describe an acceptance criteria study in the way one would typically find for a medical device that uses algorithms or AI. This is a traditional in vitro diagnostic device (IVD) based on chemical reactions and spectrophotometric measurements, not an AI/ML powered device. Therefore, many of the requested categories in the prompt are not applicable.

However, I can extract the performance characteristics that serve as the "acceptance criteria" for chemical assays, by comparing them to a predicate device for demonstrating substantial equivalence. The "study" proving the device meets these criteria is an internal validation performed by Wiener Laboratorios S.A.I.C. for submission to the FDA.

Here is the information based on the provided text, with explanations for non-applicable categories:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly defined by claiming substantial equivalence to the predicate device (DMA Direct Bilirubin Plus test system). The "reported device performance" are the values for the Wiener Lab. system.

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The "Wiener lab. CK-MB DS UV unitest" test system is a quantitative in vitro diagnostic device intended to measure the activity of the MB isoenzyme of creatine phosphokinase in plasma and serum. Measurements of creatine phosphokinase and its isoenzymes are used in the diagnosis and treatment of myocardial infarction and muscle diseases such as progressive, Duchenne-type muscular dystrophy.

Not Found

I am sorry, but the provided text does not contain the detailed study information, acceptance criteria, or device performance metrics needed to answer your request. The document is a 510(k) clearance letter from the FDA for a device called "Weiner lab. CK-MB DS UV unitest," which is a creatine phosphokinase/creatine kinase or isoenzymes test system.

While it mentions the device's intended use and substantial equivalence to a predicate device, it does not include:

• A table of acceptance criteria and reported device performance.
• Details about specific studies, such as sample sizes, data provenance, ground truth establishment, or expert qualifications.
• Information regarding MRMC comparative effectiveness studies or standalone algorithm performance.

The letter is primarily a regulatory communication indicating that the device has met the requirements for market clearance, not a technical report detailing performance study results.

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The Wiener lab. Uricostat enzimático AA Líquida. test system is a quantitative in vitro diagnostic device intended to be used in the determination of uric acid in human sera and heparinized plasmas on both manual and automated systems. Measurements of serum uric acid, are used in the diagnosis and treatment of numerous renal and metabolic disorders, including renal failure, gout, leukemia, psoriasis, starvation or other wasting conditions and of patients under treatment with cytotoxic drugs.

End point method. The principle is based on the following reaction system: UOD Uric Acid + 2 H2O + O2- -> Allantoin + H2O2 + CO2 POD 2 H2O2 + 4-AP + 3,5-SDH ------------------------------------------------------------------------------------------------------------------------------------------------------ The amount of uric acid is determined by measuring the absorbance of this pigment. UOD: Uricase; POD: Peroxidase; 4-AP: 4-Aminophenazone; 3,5-DHS: 3,5-dichlorohydroxybenzenesulfonic acid, sodium salt.

The provided document describes the Wiener lab. Uricostat enzimático AA Líquida, an in vitro diagnostic device for determining uric acid levels. The document primarily focuses on establishing substantial equivalence to a predicate device rather than providing a detailed study demonstrating device performance in the context of clinical acceptance criteria typical for AI/ML-based medical devices.

Therefore, the requested information elements related to AI/ML device testing (such as ground truth, expert adjudication, MRMC studies, training set details) are not applicable or available in this document. The information provided outlines the analytical performance of the device.

Here's an analysis based on the available information:

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

The document serves as a 510(k) summary, which establishes substantial equivalence to a predicate device. The performance claims are primarily based on equivalence to the predicate and analytical performance. Explicit "acceptance criteria" for clinical utility in the context of a new AI/ML device are not stated, but rather, performance metrics compared to the predicate device are presented.

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 the sample size used for the precision and linearity studies, nor does it provide details on the provenance of the samples (e.g., country of origin, retrospective or prospective). This information is typically found in detailed validation reports, not in a 510(k) summary focused on substantial equivalence.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Not applicable. This device is a quantitative in vitro diagnostic test for measuring uric acid, not an AI/ML device requiring expert interpretation of complex data for ground truth establishment. Its performance is evaluated against reference methods or established analytical standards.

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

Not applicable, as this is not an AI/ML device requiring human adjudication of ground truth.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

Not applicable. This device is an analytical test that measures a biochemical parameter, not a system that assists human readers in interpreting images or data.

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

This refers to the inherent performance of the Uricostat enzimático AA Líquida test system itself. The precision and linearity data represent the standalone analytical performance of the device without human intervention in the result generation (though human operators would perform the assay).

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

For an in vitro diagnostic device like this, "ground truth" would typically refer to:

• Reference materials: Control sera with known concentrations of uric acid.
• Reference methods: Comparison with a gold standard analytical method for uric acid measurement.
• Known concentrations: Spiking samples with known amounts of uric acid for linearity studies.

The document implicitly uses these types of "ground truth" for its analytical performance claims (e.g., "Normal Control," "Abnormal Control," "Normal Level Serum," "High Level Serum" for precision, and implied known concentrations for linearity).

8. The sample size for the training set

Not applicable. This is not an AI/ML device that requires a training set in that context. The development of the reagents and assay would have involved optimization, but not "training data" in the machine learning sense.

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

Not applicable. As above, this is not an AI/ML device.

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The WIENER LAB. GOT (AST) UV AA Líquida test system is a quantitative in vitro diagnostic device intended to be used in the quantitative determination of aspartate amino transferase (AST or GOT) in human serum and plasma on both manual and automated systems. Aspartate amino transferase measurements are used in the diagnosis and treatment of certain types of liver and heart diseases.

Kinetic Method. The principle is based on the following reaction system: GOT (AST) L-aspartate + 2-oxoglutarate → Oxaloacetate + L-glutamate MDH Oxalacetate + NADH + H + → L-Malate + NAD + The rate of disappearance of NADH and the resulting decrease in absorbance at 340 nm is directly proportional to the activity of GOT (AST). AST or GOT: Aspartate Aminotransferase. MDH: Malate Dehydrogenase. NADH: Nicotinamide-Adenine Dinucleotide (Reduced) NAD + : Nicotinamide-Adenine Dinucleotide. H + : Proton.

The provided document describes the "Wiener lab. GOT (AST) UV AA Líquida" test system, a quantitative in vitro diagnostic device for determining aspartate aminotransferase (AST or GOT) in human serum and plasma. The device's performance is compared to a predicate device, "Wiener lab. GOT (AST) UV," to establish substantial equivalence.

Here's an analysis of the acceptance criteria and the study proving the device meets them:

1. Acceptance Criteria and Reported Device Performance:

The document primarily focuses on demonstrating substantial equivalence to a predicate device by comparing key performance characteristics. The "acceptance criteria" are implicitly set by matching or improving upon the performance of the predicate device.

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

The document does not explicitly state the sample sizes used for the precision and linearity studies. It only provides the results (e.g., CV values and linearity range). The provenance of the data (e.g., country of origin, retrospective or prospective) is also not specified.

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

This information is not applicable in this context. This device is a quantitative diagnostic assay, not an imaging or interpretive diagnostic tool that requires expert human interpretation to establish ground truth for testing. The "ground truth" for linearity and precision studies would be derived from the known concentrations or activities of reference materials, or statistical analysis of repeated measurements, not expert consensus on individual cases.

4. Adjudication Method for the Test Set:

This is not applicable for the type of device and studies presented. Adjudication methods (like 2+1, 3+1) are typically used in studies involving subjective interpretation of medical images or other data where consensus among experts is needed.

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 is not applicable. The device is an in vitro diagnostic assay, not an AI-assisted diagnostic tool that involves human readers.

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

This is not applicable in the sense of an "algorithm only" performance. The device is a chemical reagent system. Its performance (precision, linearity) is inherently "standalone" in the context of the assay itself, as it measures a biochemical parameter directly. There is no human interpretative "loop" in the direct performance of the assay.

7. The Type of Ground Truth Used:

For linearity, the ground truth would be based on known concentrations or activities of control materials or serially diluted samples.
For precision, the ground truth is established statistically by repeated measurements on stable control materials or patient samples to assess the reproducibility of the assay.

8. The Sample Size for the Training Set:

The document does not specify a training set in the context of machine learning or AI. For a traditional in vitro diagnostic assay like this, there isn't a "training set" in that sense. The assay's parameters (reagent concentrations, reaction conditions) are developed through chemical and biochemical optimization, often involving many experiments, but not a formally defined "training set" of patient data as would be found in AI/ML development.

9. How the Ground Truth for the Training Set was Established:

As there is no "training set" in the context of AI/ML for this device, this question is not applicable. The "ground truth" for the development of reagent formulations and assay conditions would be based on established biochemical principles, analytical chemistry standards, and experimental results aimed at optimizing the reaction kinetics and stability.

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The "Wiener lab. Bilirrubina Total AA" test system is a quantitative in vitro diagnostic device intended to be used in the quantitative determination of total bilirubin in human sera and heparinized plasmas on both manual and automated systems. Measurements of the levels of bilirubin, an organic compound formed during the normal and abnormal destruction of red blood cells, are used in the diagnosis and treatment of liver, hemolytic, hematological, and metabolic disorders, including hepatitis and gall bladder block.

Total bilirubin (both conjugated and free) is measured using a stable dichlorophenyl diazonium salt (DPD) to form an azobilirubin compound with maximal O.D. at 546 nm. Surfactants are used as reaction accelerators. The amount of bilirubin is determined by measuring the absorbance of this pigment.

The provided document describes the predicate device and the new device being submitted for 510(k) clearance, the Wiener lab. BILIRRUBINA TOTAL AA test system. It focuses on establishing substantial equivalence to the predicate device through a comparison of their features and performance characteristics, particularly related to analytical performance (precision, linearity, expected values).

However, the document does not contain information about:

• Specific acceptance criteria used in a study to prove the device meets these criteria. Instead, it presents performance characteristics and compares them to the predicate.
• A dedicated study design with a test set, training set, ground truth establishment, or expert involvement as would be typical for AI/ML-based device evaluation.
• Multi-reader multi-case (MRMC) comparative effectiveness studies.
• Standalone algorithm performance.

The information provided is typical for an IVD (In Vitro Diagnostic) device submission where the focus is on analytical performance characteristics rather than clinical diagnostic accuracy based on image analysis or human interpretation.

Therefore, many of the requested fields cannot be filled from the given text.

Here's a breakdown of what can be extracted and what cannot:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly state "acceptance criteria" but presents performance data for the new device and compares it to the predicate. The "acceptance" is implied by the concluding statement of substantial equivalence.

2. Sample size used for the test set and the data provenance:
This information is not provided in the document. The precision data (within-run and run-to-run) would have been generated using a laboratory test, but the specific sample sizes for these tests are not mentioned. There is no information about the country of origin or if the data was retrospective or prospective.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
Not applicable. This is an IVD device, and the "ground truth" for analytical performance (precision, linearity) would be based on reference methods or spiked samples, not expert interpretation.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
Not applicable. As above, this concept applies to human interpretation of diagnostic results, not the analytical performance of an IVD reagent.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:
No. This is not an AI-assisted diagnostic device.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
Not applicable. This is an IVD reagent kit; its performance is standalone in the sense that it produces a quantitative value, but there's no "algorithm" in the context of AI/ML.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):
For precision, the ground truth would be the known concentration of bilirubin in control samples as measured by a reference method or validated assays. For expected values, it would be based on large-scale population studies.

8. The sample size for the training set:
Not applicable. There is no "training set" in the context of AI/ML for this type of IVD device. The methods are chemical reactions, not learned algorithms.

9. How the ground truth for the training set was established:
Not applicable. See above.

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The "Wiener lab. Ca-Color Arsenazo III AA" test system is a quantitative in vitro diagnostic device intended to be used in the quantitative determination of calcium in human sera, heparinized plasmas and urine on both manual and automated systems. Measurements of calcium are used in the diagnosis and treatment of parathyroid diseases, a variety of bone diseases, chronic renal diseases and tetany (intermittent muscular contractions or spasms).

Calcium reacts with Arsenazo III, yielding a blue colored complex, which is photocolorimetrically measured at 650 nm. 8-hydroxyquinoline is added to remove magnesium interference.

The provided text describes the Wiener Lab. CA-COLOR ARSENAZO III AA test system, a device for quantitative determination of calcium in human sera, heparinized plasmas, and urine. The document is a 510(k) summary, which aims to establish substantial equivalence to a predicate device.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text, while noting the limitations in the available information:

1. Table of Acceptance Criteria and Reported Device Performance

The document compares the new device (CA-COLOR ARSENAZO III AA) with a predicate device (CA-COLOR AA) across several performance characteristics. While direct "acceptance criteria" are not explicitly stated as numerical thresholds for the new device, the comparison to the predicate device serves as the basis for demonstrating substantial equivalence, implying that performance similar to the predicate is acceptable.

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

The document provides precision data (Within-run and Run-to-run) for both Normal and High levels in Serum and Urine. However, it does not specify the sample size (number of replicates or samples) used for generating these precision values, nor does it specify the data provenance (country of origin, retrospective or prospective). This information is a significant omission from the provided summary regarding the study details.

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

This information is not applicable in the context of this diagnostic device. The "ground truth" for a calcium test system is established by the actual calcium concentration in the samples, determined by a reference method (which is not explicitly defined here but is implicit in the quantitative nature of the test). There are no human "experts" establishing ground truth in the sense of image interpretation or clinical diagnosis for this type of test.

4. Adjudication Method for the Test Set

This is not applicable for this type of quantitative diagnostic test. Adjudication methods (like 2+1, 3+1) are typically used in studies involving subjective assessments, such as expert review of medical images, where there might be disagreement among reviewers. For a quantitative chemical assay, the comparison would be against a reference method or known concentrations.

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 is not applicable. An MRMC study and the concept of "human readers improving with AI assistance" are relevant for AI-powered diagnostic tools, especially in radiology or pathology. This document describes a chemical assay kit for calcium determination, which does not involve human interpretation aided by AI.

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

This is not explicitly stated or applicable in the AI-centric sense. The device itself (reagents) is the "algorithm" in this context; its performance is measured directly. The document provides performance characteristics of the device itself (precision). While the test can be used on "manual and automated systems," the performance metrics provided reflect the kit's inherent analytical performance, which is a standalone assessment of the reagents' capability.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

The ground truth for evaluating the performance of a calcium test system would be the actual calcium concentration in the test samples. This is typically determined by:

• Reference materials/calibrators with known calcium concentrations: Used for linearity and calibration verification.
• Split samples analyzed by a well-established, often more precise, reference method (e.g., atomic absorption spectrophotometry or another validated clinical chemistry analyzer): Used for accuracy/bias assessment against patient samples.

The document does not explicitly state which ground truth method was used, but it's implied through the reporting of linearity and precision, which rely on having known or well-characterized samples.

8. The Sample Size for the Training Set

This is not applicable in the traditional sense of machine learning/AI models. The device is a chemical reagent system, not a software algorithm that undergoes a "training phase" on a dataset. The development of such a kit involves chemical formulation and optimization, followed by validation studies.

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

This is not applicable for the same reasons as #8. There is no training set or ground truth establishment in an AI context. The "development" of the product involves optimizing reagent concentrations and reaction conditions to achieve desired analytical performance, which is then validated.

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