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HemosIL D-Dimer HS 500 is an automated latex enhanced immunoassay for the quantitative determination of D-Dimer in human citrated plasma on the ACL TOP® Family and ACL TOP Family 50 Series Systems for use, in conjunction with a clinical pretest probability (PTP) assessment model to exclude venous thromboembolism (VTE) in outpatients suspected of deep venous thrombosis (DVT) and pulmonary embolism (PE). For in vitro diagnostic use.

The D-Dimer HS 500 Latex Reagent is a suspension of polystyrene latex particles of uniform size coated with the F(ab')2 fragment of a monoclonal antibody highly specific for the D-Dimer domain included in fibrin soluble derivatives. The use of the F(ab')2 fragment allows a more specific D-Dimer detection avoiding the interference of some endogenous factors like the Rheumatoid Factor. When a plasma containing D-Dimer is mixed with the Latex Reagent and the Reaction Buffer included in the HemosIL D-Dimer HS 500 kit, the coated latex particles agglutinate. The degree of agglutination is directly proportional to the concentration of D-Dimer in the sample and is determined by measuring the decrease of transmitted light caused by the aggregates (turbidimetric immunoassay).

The provided document is a 510(k) summary for the HemosIL D-Dimer HS 500 device. This particular submission (K172903) is a Special 510(k), meaning it's for modifications to an already cleared device (predicate K090264) and not for a de novo clearance. Special 510(k)s typically do not require new clinical studies to demonstrate device performance against acceptance criteria, as the performance claims are carried over from the predicate device.

The main purpose of K172903 is to add general information from peer-reviewed published literature to the Summary and Principle section of the HemosIL D-Dimer HS 500 insert sheet regarding the association of patient age with D-Dimer levels and to clarify that the device's performance has not been validated for age-adjusted cut-off values.

Therefore, many of the requested items regarding a new clinical study and ground truth establishment would not be applicable to this specific submission. However, I can extract the acceptance criteria and performance claims that apply to the predicate device and are carried over to this modified device.

Here's the breakdown based on the provided text:

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

Since this is a Special 510(k) for an insert sheet modification and not a new device, the acceptance criteria and reported performance are implicitly the same as the predicate (K090264). The document explicitly states "No change to labeled performance claims, including no change to the assay cut-off."

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

This information is not provided in this Special 510(k) summary (K172903) because no new clinical test set was used or presented for this particular submission. The performance claims are based on the predicate device (K090264). To obtain this information, one would need to refer to the 510(k) summary for K090264.

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 provided in this Special 510(k) summary (K172903) as no new clinical test set (requiring expert ground truth) was used for this submission. This type of detail would be found in the original 510(k) for the predicate device (K090264) which established the clinical performance.

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

This information is not provided in this Special 510(k) summary (K172903) as no new clinical test set requiring adjudication was used for this submission. This type of detail would be found in the original 510(k) for the predicate device (K090264).

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 device is an in vitro diagnostic for D-Dimer measurement, not an imaging device typically analyzed by human readers in the context of MRMC studies or AI assistance in reading. Therefore, an MRMC comparative effectiveness study, as described, is not applicable.

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

The HemosIL D-Dimer HS 500 is an automated immunoassay for quantitative determination. Its performance is inherently "standalone" in the sense that it provides a quantitative result based on the immunoassay reaction, without direct human cognitive input in interpreting the raw signal for the D-Dimer concentration. The result is then used in conjunction with a clinical pretest probability (PTP) assessment model by a clinician. The validation of its quantitative accuracy would have been performed during the original clearance (K090264).

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

For an in vitro diagnostic device like a D-Dimer assay, the ground truth for performance measures like linearity, detection limit, and cut-off would typically be established by:

• Reference methods/calibrators: For analytical performance (linearity, detection limit), certified reference materials or highly accurate reference methods would be used.
• Clinical outcomes/diagnosis: For the diagnostic performance (sensitivity, specificity, NPV for VTE exclusion), the ground truth for DVT/PE would be established through definitive diagnostic imaging (e.g., ultrasound, CTPA, ventilation-perfusion scan) or other established clinical diagnostic criteria for the patient cohort recruited for the original predicate study (K090264).

This specific Special 510(k) (K172903) does not provide these details as it relies on the predicate (K090264).

8. The sample size for the training set

This information is not provided in this Special 510(k) summary (K172903). For an immunoassay, the concept of a "training set" in the context of machine learning (as often implied by this question) is not directly applicable. However, method development and optimization would involve numerous samples, with calibration curves and reagents being "trained" or optimized during the development phase of the original predicate device (K090264), but described in terms of analytical validation rather than a machine learning 'training set'.

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

As above, while not a "training set" in the common AI sense, the ground truth for optimizing assay parameters and establishing analytical performance (for the original predicate K090264) would have been established using reference standards or established, validated methods. Clinical training data, if any, for setting the original cut-off would have involved patients with confirmed (or ruled out) DVT/PE, as validated by definitive diagnostic tests. This information is not within this K172903 document.

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