The Stat Profile® Prime Plus Analyzer System is indicated for use by healthcare professionals in clinical laboratory settings for quantitative determination of glucose, creatinine, and blood urea nitrogen in heparinized arterial and venous whole blood. Glucose measurements are used in the diagnosis and treatment of carbohydrate metabolism disturbances including diabetes mellitus, neonatal hypoglycemia, and idiopathic hypoglycemia, and of pancreatic islet cell tumor. Creatinine measurements are used in the diagnosis and treatment of certain renal conditions and for monitoring adequacy of dialysis. Blood urea nitrogen (BUN) measurements are used in the diagnosis and treatment of certain renal and metabolic diseases.
Device Story
Stat Profile Prime Plus Analyzer is a benchtop blood chemistry analyzer for hospital laboratory use. It accepts lithium heparinized arterial and venous whole blood samples (135 µL) from syringes, open tubes, or small cups. The device utilizes modular sensor cartridges (Primary and Auxiliary) to measure Glucose, Creatinine, and BUN. Glucose and Creatinine are measured via enzymatic amperometric sensors (platinum anode at 0.70V); BUN is measured via an ammonium ion-selective electrode using the Nernst equation. The system includes an onboard Quality Management System (QMS) for continuous monitoring. Results are displayed on a 10.1-inch color touch screen and can be printed via an integrated thermal printer. The device aids clinicians in diagnosing and treating renal conditions, metabolic diseases, and carbohydrate metabolism disturbances. It is designed for low-maintenance operation in clinical settings.
Clinical Evidence
Bench testing only. Performance verification included method comparison studies against the predicate analyzer, within-run and run-to-run precision studies (20 replicates per run), linearity testing across the analytical measurement range, and interference screening per CLSI EP7-A2. Results demonstrated good correlation, linearity, and precision meeting all pre-defined acceptance criteria.
Technological Characteristics
Materials: TPE tubing (Pharmed BPT). Sensing: Amperometric (glucose, creatinine) and potentiometric (BUN) sensors. Energy: Electrical. Form factor: Benchtop analyzer with 10.1" WXGA touch screen. Connectivity: Integrated 1D/2D barcode scanner. Software: Embedded firmware for sensor configuration and data processing. Traceability: NIST SRM 967a (creatinine), 912a (urea), 917a (glucose).
Indications for Use
Indicated for healthcare professionals in clinical laboratory settings for quantitative determination of glucose, creatinine, and BUN in heparinized arterial and venous whole blood. Not for point-of-care use.
Regulatory Classification
Identification
A glucose test system is a device intended to measure glucose quantitatively in blood and other body fluids. 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.
Special Controls
*Classification.* Class II (special controls). The device, when it is solely intended for use as a drink to test glucose tolerance, is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 862.9.
Predicate Devices
Stat Profile pHOx Ultra Analyzer System (k110648)
Submission Summary (Full Text)
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1
# 510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION DECISION SUMMARY ASSAY ONLY TEMPLATE
A. 510(k) Number:
k180340
B. Purpose for Submission:
New device
C. Measurand:
Glucose, blood urea nitrogen, creatinine
D. Type of Test:
Glucose and Creatinine - quantitative, enzyme/amperometric
BUN - quantitative, enzymatic potentiometric
E. Applicant:
Nova Biomedical Corporation
F. Proprietary and Established Names:
Stat Profile® Prime Plus Analyzer System
G. Regulatory Information:
| Regulation section | Classification | Product code | Panel |
| --- | --- | --- | --- |
| 21CFR§862.1345 Glucose test system | Class II | CGA | Chemistry (75) |
| 21CFR§862.1770 Urea nitrogen test system | | CDS | |
| 21CFR§862.1225 Creatinine test system | | CGL | |
H. Intended Use:
1. Intended use(s):
See Indication(s) for Use below
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2. Indication(s) for use:
The Stat Profile® Prime Plus Analyzer System is indicated for use by healthcare professionals in clinical laboratory settings for quantitative determination of glucose, creatinine, and blood urea nitrogen in heparinized arterial and venous whole blood.
Glucose measurements are used in the diagnosis and treatment of carbohydrate metabolism disturbances including diabetes mellitus, neonatal hypoglycemia, and idiopathic hypoglycemia, and of pancreatic islet cell tumor.
Creatinine measurements are used in the diagnosis and treatment of certain renal conditions and for monitoring adequacy of dialysis.
Blood urea nitrogen (BUN) measurements are used in the diagnosis and treatment of certain renal and metabolic diseases.
3. Special conditions for use statement(s):
Not for point-of-care use.
4. Special instrument requirements:
Stat Profile® Prime Plus Analyzer
I. Device Description:
The Stat Profile® Prime Plus Analyzer System consists of the analyzer, sensor cartridges, calibrator packs, auto-cartridge quality control packs (internal controls), ampiled quality control materials (external controls) and thermal paper for an onboard printer. Optionally, it provides for reading of barcode labels (such as operator badges and data sheets).
The Stat Profile® Prime Plus Analyzer has slots to accommodate two sensor cartridges (Primary and Auxiliary). The analyzer will determine the configuration of the system by detecting which sensor cards are installed. The reporting of CO-Oximeter parameters (or not reporting them) will also be determined by the selection of the Sensor Cards:
Primary Sensor Card Port: There are two options for the primary sensor card:
- Primary Sensor Card 1 shall enable and report glucose in addition to other select analytes.
- Primary Sensor Card 2 shall enable and report glucose in addition to other select analytes.
Auxiliary Sensor Card Port:
The reporting of Creatinine and BUN parameters (or not reporting them) is determined by the selection of the Auxiliary Sensor Card:
- Auxiliary Sensor Card 1 enables Creatinine and BUN parameters
- Auxiliary Sensor Card 2 is a "dummy" sensor card, and will not report any parameters.
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J. Substantial Equivalence Information:
1. Predicate device name(s):
Stat Profile pHOx Ultra Analyzer System
2. Predicate 510(k) number(s):
k110648
3. Comparison with predicate:
| Item | Candidate Device
Stat Profile PRIME Plus
Analyzer System
(k180340) | Predicate Device
Stat Profile pHOx Ultra
Analyzer System
(k110648) |
| --- | --- | --- |
| Indications for Use | For the quantitative determination of glucose, creatinine and blood urea nitrogen, in heparinized arterial and venous whole blood. | Same |
| Menu | Fully configurable test menu based on available sensors. | Same |
| Bar Code Scanner | Internal Integrated 1D/2D | Same |
| Printer | 2" Roll, Thermal Transfer | Same |
| Pump | Peristaltic Pump w/ Pressure Plate, TPE Tubing (Pharmed BPT). | Same |
| Analog Board | Precision low level analog front end with amperometric and potentiometric amplifiers, air detector circuitry and temperature control circuitry. | Same |
| Measuring Principle | Glucose - Enzyme sensor | Same |
| | BUN - Enzyme sensor | Same |
| | Creatinine - Impedance sensor | Same |
| Measuring Range | Glucose, 15.0 – 500.0 mg/dL | Same |
| | BUN, 3.0 – 100.0 mg/dL | Same |
| | Creatinine, 0.2 – 12.0 mg/dL | 0.2 – 20.0 mg/dL |
3
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| Item | Candidate Device Stat Profile PRIME Plus Analyzer System (k180340) | Predicate Device Stat Profile pHOx Ultra Analyzer System (k110648) |
| --- | --- | --- |
| Sample Types | Lithium heparin arterial and venous whole blood from syringes, open tubes, and small cups. | Sodium or lithium heparinized whole blood, serum, or plasma samples from syringes, open tubes, small cups, and capillary tubes. |
| Sample Volume | 135μL | 60-200μL (dependent on panel selected) |
| Touch Screen | 10.1” WXGA 1280 x 800 color touch screen | 12.1" LCD, 1024x768 pixel, Resistive Touch |
# K. Standard/Guidance Document Referenced (if applicable):
Not applicable.
# L. Test Principle:
Glucose: Glucose measurement is based on the level of $\mathrm{H}_2\mathrm{O}_2$ produced during the enzymatic reaction between glucose and oxygen molecules in the presence of the glucose oxidase enzyme. At a constant potential of 0.70 volts, electroactive $\mathrm{H}_2\mathrm{O}_2$ is oxidized at the surface of the platinum anode. The current generated by the flow of electrons at the surface of the platinum electrode is proportional to the glucose concentration of the sample.
BUN: The Prime Plus Analyzer uses urease, which has been chemically bonded to a membrane, to catalyze the conversion of urea present in the sample to ammonia and $\mathrm{CO}_{2}$ . At the pH of the sample, ammonia converts predominantly to the ammonium ion. An ammonium ion selective electrode is used to detect the ammonium formed by the above reactions. This measurement is then related to the concentration of urea present in the original sample via the Nernst equation.
Creatinine: The Prime Plus Creatinine sensor uses 3 enzymes. These 3 enzymes catalyze the conversion of Creatinine, ultimately forming formaldehyde, glycine, and hydrogen peroxide. At a constant potential of 0.70 volts, electroactive $\mathrm{H}_2\mathrm{O}_2$ is oxidized at the surface of the platinum anode. The current generated by the flow of electrons at the surface of the platinum electrode is proportional to the Creatinine concentration of the sample.
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M. Performance Characteristics (if/when applicable):
1. Analytical performance:
a. Precision/Reproducibility:
Within-Run Precision:
Within-run precision testing was performed using quality control (QC) and whole blood samples from syringe analyzed in one run, with 20 replicates per run on one day. Samples were run on three analyzers. The results of one representative analyzer are shown below:
Within-run precision results using internal QC samples:
| Parameter | n = 20 | Internal Control Level 1 | Internal Control Level 2 |
| --- | --- | --- | --- |
| Glucose (mg/dL) | Mean | 86 | 297 |
| | SD | 0.6 | 3.7 |
| | CV% | 0.7 | 1.2 |
| BUN (mg/dL) | Mean | 16.5 | 47.5 |
| | SD | 0.1 | 0.2 |
| | CV% | 0.4 | 0.4 |
| Creatinine (mg/dL) | Mean | 0.8 | 6.7 |
| | SD | 0.0 | 0.2 |
| | CV% | 1.3 | 2.3 |
Within-run precision results using external QC samples:
| Parameter | n = 20 | External Control Level 1 | External Control Level 2 |
| --- | --- | --- | --- |
| Glucose (mg/dL) | Mean | 77 | 313 |
| | SD | 1.1 | 2.9 |
| | CV% | 1.4 | 0.9 |
| BUN (mg/dL) | Mean | 16.0 | 51.2 |
| | SD | 0.5 | 0.3 |
| | CV% | 2.9 | 0.6 |
| Creatinine (mg/dL) | Mean | 1.1 | 7.4 |
| | SD | 0.1 | 0.0 |
| | CV% | 5.6 | 0.6 |
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Within-run precision results using whole blood samples:
| Glucose (mg/dL) (n=20) | | | |
| --- | --- | --- | --- |
| Sample | Mean | SD | %CV |
| Sample 1 | 16 | 0.7 | 4.4 |
| Sample 2 | 72 | 1.8 | 2.5 |
| Sample 3 | 110 | 2.0 | 1.9 |
| Sample 4 | 159 | 4.7 | 2.9 |
| Sample 5 | 188 | 5.0 | 2.6 |
| Sample 6 | 360 | 10.8 | 3.0 |
| BUN (mg/dL) (n=20) | | | |
| --- | --- | --- | --- |
| Sample | Mean | SD | %CV |
| Sample 1 | 11 | 0.1 | 0.7 |
| Sample 2 | 14.8 | 0.3 | 2.3 |
| Sample 3 | 20.4 | 0.5 | 2.3 |
| Sample 4 | 24.8 | 0.4 | 1.5 |
| Sample 5 | 75.2 | 0.9 | 1.2 |
| Creatinine (mg/dL) (n=20) | | | |
| --- | --- | --- | --- |
| Sample | Mean | SD | %CV |
| Sample 1 | 0.4 | 0.04 | 11.8 |
| Sample 2 | 0.5 | 0.0 | 9.2 |
| Sample 3 | 0.7 | 0.1 | 17.8 |
| Sample 4 | 3.4 | 0.08 | 2.2 |
| Sample 5 | 9.2 | 0.16 | 1.8 |
Run-to-Run Precision:
To assess run-to-run precision using QC samples, each sample was tested in duplicate per run, 2 runs per day, 3 analyzers performed over 20 days. The summary results for the three analyte test systems are shown below:
Run-to-Run precision using internal QC samples:
| Glucose (mg/dL) | | | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Sample | Pooled Mean | N | Within run SD | Within run % CV | Total imprecision SD | Total imprecision % CV |
| QC 1 | 87 | 240 | 0.8 | 0.9 | | 0.2 |
| QC 2 | 116.5 | 240 | 0.2 | 0.2 | 0.3 | 0.3 |
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| BUN (mg/dL) | | | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Sample | Pooled Mean | N | Within run SD | Within run % CV | Total imprecision SD | Total imprecision % CV |
| QC 1 | 16.8 | 240 | 0.1 | 0.4 | 0.5 | 2.7 |
| QC 2 | 48.7 | 240 | 0.4 | 0.7 | 1.7 | 3.6 |
| Creatinine (mg/dL) | | | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Sample | Pooled Mean | N | Within run SD | Within run % CV | Total imprecision SD | Total imprecision % CV |
| QC 1 | 0.8 | 240 | 0.0 | 1.2 | 0.0 | 4.9 |
| QC 2 | 6.7 | 240 | 0.1 | 0.9 | 0.3 | 4.9 |
Run-to-Run imprecision using whole blood samples:
To assess run-to-run precision using whole blood, triplicate analyses were performed on a single whole blood sample in ten separate runs during a single day. The systems were recalibrated before each triplicate run. Samples were analyzed on three analyzers. Representative summary results from one analyzer for the three analyte test systems are shown below:
| Parameter | n = 30 | Venous Blood 1 | Venous Blood 2 | Venous Blood 3 | Venous Blood 4 | Venous Blood 5 |
| --- | --- | --- | --- | --- | --- | --- |
| Glucose (mg/dL) | Mean | 26 | 79 | 103 | 207 | 378 |
| | SD | 1.5 | 2.6 | 2.7 | 5.1 | 8.9 |
| | CV% | 5.7 | 3.3 | 2.7 | 2.5 | 2.4 |
| BUN (mg/dL) | Mean | 3.9 | 11.7 | 25 | 73.2 | n/a |
| | SD | 0.1 | 0.3 | 0.3 | 1.3 | |
| | CV% | 2.0 | 2.1 | 1.1 | 1.8 | |
| Creatinine (mg/dL) | Mean | 0.3 | 0.5 | 1.3 | 9.2 | n/a |
| | SD | 0.06 | 0.0 | 0.12 | 0.34 | |
| | CV% | 18.2 | 4.4 | 9.0 | 3.7 | |
b. Linearity/assay reportable range:
Linearity studies on the Stat Profile® Prime Plus analyzer were conducted to establish and verify the analytical measurement range for each test system. The studies were performed on three analyzers using Li-heparinized venous whole blood for Glucose, BUN and creatinine. Low and high concentration pools were mixed and serial dilution samples (N=10 or 11) were prepared and tested in triplicate. The results from each candidate analyzer for each parameter were compared to the average duplicate results from the comparative method on the Stat Profile pHOx Ultra analyzer. All three analyzers yielded similar results. The results of the least squares linear regression analysis from one representative analyzer are summarized below.
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| Analyte | Claimed measurement range | Concentration range tested | Slope | Intercept | r |
| --- | --- | --- | --- | --- | --- |
| Glucose (mg/dL) | 15.0 – 500.0 | 2.0 – 519.0 | 1.0292 | -3.8879 | 0.9988 |
| BUN (mg/dL) | 3.0 – 100.0 | 1.2 – 110.5 | 1.0173 | -2.3235 | 0.9971 |
| Creatinine (mg/dL) | 0.2 – 12.0 | 0.1 – 12.5 | 1.0356 | -0.0497 | 0.9985 |
The results of the linearity study support the claimed measuring ranges as described in the table above.
c. Traceability, Stability, Expected values (controls, calibrators, or methods):
The traceability of the parameters measured by Stat Profile Prime Plus Analyzer are traceable to NIST reference standards. These are listed below:
Creatinine Test: It is traceable to NIST SRM 967a creatinine.
BUN Test: It is traceable to NIST SRM 912a urea.
Glucose Test: It is traceable to NIST SRM 917a D-glucose.
d. Detection limit:
The sponsor performed a study to evaluate the limit of blank (LoB), limit of detection (LoD) and limit of quantification (LoQ) for glucose, BUN and creatinine using altered whole blood samples. Study samples were prepared from heparinized venous whole blood samples. All prepared samples were measured on the reference analyzer to confirm target values.
Results from the detection limit study are summarized below:
| Analyte (mg/dL) | LoB | LoD | TE | LoQ | Acceptance Criteria for TE (<=) | Claimed Measurement Range |
| --- | --- | --- | --- | --- | --- | --- |
| Glucose | 4.0 | 5.0 | 3.0 | 12.0 | 6.0 | 15.0 - 500 |
| BUN | 0.5 | 0.7 | 1.2 | 2.4 | 1.3 | 3.0 – 100.0 |
| Creatinine | 0.09 | 0.11 | 0.08 | 0.12 | 0.56 | 0.2 - 12.0 |
Refer to the linearity study section M.2.b. above for measuring range claims for glucose, BUN and creatinine.
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# e. Analytical specificity:
An interference study was performed using whole blood collected in lithium heparin vacutainers. The potential interfering substances were tested at two analyte concentrations. If interference was identified, then a dose response study was performed to determine the concentration where the interfering substance may alter the results.
The sponsor defined interference as a specified bias or %bias from the test concentration as shown in the following table.
| Analyte | Interference Bias Specification |
| --- | --- |
| Glucose | ± 10.0 % |
| BUN | ± 10.0 % |
| Creatinine | ± 0.2 mg/dL or ± 10.0 % * |
* difference or percent, whichever is greater.
The sponsor determined that the following substances did not cause interference at the concentrations listed below:
Glucose
| Substance | Highest concentration tested that did not cause significant interference |
| --- | --- |
| Acetaminophen | 20 mg/dL |
| Acetoacetate | 2 mmol/L |
| N-acetylcysteine | 10.2 mmol/L |
| Acetylsalicylic Acid | 3.62 mmol/L |
| Ammonium Chloride | 107 μmol/L |
| Ascorbic Acid | 50 mg/dL |
| Benzalkonium Chloride | 10 mg/L |
| Bilirubin | 342 μmol/L |
| Dobutamine | 2 mg/dL |
| Dopamine Hydrochloride | 5.87 μmol/L |
| EDTA | 3 mmol/L |
| Ethanol | 86.8 mmol/L |
| Fluoride | 105 μmol /L |
| D-Galactose | 1 mmol/L |
| Glucosamine | 30 μmol/L |
| Glutathione | 3 mmol/L |
| Glycolic Acid | 1 mmol/L |
| Hemoglobin | 2 g/L |
| Sodium Heparin | 100 IU/mL |
| β-Hydroxybutyrate | 2 mmol/L |
| Hydroxyurea | 0.2 mg/dL |
{9}
| Substance | Highest concentration tested that did not cause significant interference |
| --- | --- |
| Ibuprofen | 2.4 mmol/L |
| Intralipid | 1.0% |
| Lithium Lactate | 6.6 mmol/L |
| Lactic Acid | 12 mmol/L |
| Maltose | 13 mmol/L |
| Mannose | 1 mmol/L |
| Pyruvate | 309 μmol/L |
| Salicylic Acid | 4.34 mmol/L |
| Sodium Citrate | 12 mmol/L |
| Sodium Oxalate | 125 mg/dL |
| Thiocyanate | 3.4 mmol/L |
| Urea | 43 mmol/L |
| Uric Acid | 1.4 mmol/L |
| Xylose | 25 mg/dL |
BUN
| Substance | Highest concentration tested that did not cause significant interference |
| --- | --- |
| Acetaminophen | 20 mg/dL |
| Acetoacetate | 2 mmol/L |
| Acetylsalicylic Acid | 3.62 mmol/L |
| Ammonium Chloride | 107 μmol/L |
| Ascorbic Acid | 50 mg/dL |
| N-acetylcysteine | 10.2 mmol/L |
| Benzalkonium Chloride | 10 mg/L |
| Bilirubin | 342 μmol/L |
| Chlorpromazine HCl | 0.2 mmol/L |
| Sodium Citrate | 12 mmol/L |
| Creatine | 5 mg/dL |
| Dopamine Hydrochloride | 5.87 μmol/L |
| EDTA | 3 mmol/L |
| Ethanol | 86.8 mmol/L |
| Glucose | 1000 mg/dL |
| Glutathione | 3 mmol/L |
| Glycolic Acid | 1 mmol/L |
| Sodium Heparin | 100 IU/mL |
| High Hct | 63% |
| β-Hydroxybutyrate | 2 mmol/L |
| Hydroxyurea | 0.8 mg/dL |
| Ibuprofen | 2.4 mmol/L |
| Intralipid | 1.0% |
| Lactic Acid | 12 mmol/L |
| Lithium Lactate | 6.6 mmol/L |
| Lactic Acids | 12 mmol/L |
| Maltose | 13 mmol/L |
| Mannose | 1 mmol/L |
| Pyruvate | 309 μmol/L |
| Salicylic Acid | 4.34 mmol/L |
| Sodium Citrate | 12 mmol/L |
| Sodium Oxalate | 125 mg/dL |
| Thiocyanate | 3.4 mmol/L |
| Urea | 43 mmol/L |
| Uric Acid | 1.4 mmol/L |
| Xylose | 25 mg/dL |
{10}
11
| Substance | Highest concentration tested that did not cause significant interference |
| --- | --- |
| Low Hct | 22% |
| Low pH | 6.8 |
| Nithiodote | 5.12 g/dL |
| Paracentamol-4-acetamidopenol | 2 mmol/L |
| Pyruvate | 309 μmol/L |
| Salicylic Acid | 4.34 mmol/L |
| Thiocyanate | 6.8 mmol/L |
| Uric Acid | 1.4 mmol/L |
## Creatinine
| Substance | Highest concentration tested that did not cause significant interference |
| --- | --- |
| Acetaminophen | 20 mg/dL |
| Acetoacetate | 2 mmol/L |
| Acetylsalicylic Acid | 3.62 mmol/L |
| Ascorbic Acid | 50 mg/dL |
| N-acetylcysteine | 10.2 mmol/L |
| Bilirubin | 342 μmol/L |
| Sodium Bromide | 37.5 mmol/L |
| Chlorpromazine HCl | 0.2 mmol/L |
| Sodium Citrate | 12 mmol/L |
| Creatine | 5 mg/dL |
| Dopamine Hydrochloride | 5.87 μmol/L |
| EDTA | 3 mmol/L |
| Ethanol | 86.8 mmol/L |
| Fluoride | 105 μmol/L |
| Glucose | 1000 mg/dL |
| Glycolic Acid | 1 mmol/L |
| Sodium Heparin | 100 IU/mL |
| High Hct | 64% |
| High Protein | 60 g/L |
| β-Hydroxybutyrate | 2 mmol/L |
| Hydroxyurea | 0.06 mg/dL |
| Ibuprofen | 2.4 mmol/L |
| Intralipid | 1.0% |
| Sodium Iodide | 2.99 mmol/L |
| Lithium Lactate | 6.6 mmol/L |
| Lactic Acid | 12 mmol/L |
| Low Hct | 26% |
| Low pH | 6.8 |
| Paracentamol-4-acetamidopenol | 2 mmol/L |
{11}
| Substance | Highest concentration tested that did not cause significant interference |
| --- | --- |
| acetamidopenol | |
| Proline | 0.5 mmol/L |
| Pyruvate | 309 μmol/L |
| Salicylic Acid | 4.34 mmol/L |
| Thiocyanate | 1.7 mmol/L |
| Urea | 43 mmol/L |
| Uric Acid | 1.4 mmol/L |
The sponsor lists the following interferents in the labeling:
| Parameter | Interferent | Interference Observed at Concentrations Above: |
| --- | --- | --- |
| Glucose | Hydroxyurea | 0.2 mg/dL |
| | Oxalate | 125 mg/dL |
| | Thiocyanate | 3.4 mmol/L |
| Creatinine | Hydroxyurea | 0.06 mg/dL |
| | Thiocyanate | 1.7 mmol/L |
f. Assay cut-off:
Not applicable.
# 2. Comparison studies:
a. Method comparison with predicate device:
A minimum of 200 lithium heparinized arterial and venous whole blood specimens from hospital patients were analyzed in syringe format in singlet on three Stat Profile® Prime Plus analyzers and two pHOx Ultra analyzers for each parameter. In order to cover the hard to find sample range, venous whole blood specimens from consenting donors were spiked or diluted to cover the analytical measurement ranges for all three analytes, glucose, BUN and creatinine. The singlet result from each test analyzer was compared to the average of the results from each comparative method. Representative summary result from one analyzer for the three analyte tests are listed in the below table.
| Analyte | N | Sample concentration range | Slope | Intercept | r |
| --- | --- | --- | --- | --- | --- |
| Glucose (mg/dL) | 224 | 23 – 479 | 0.9860 | 2.1406 | 0.9932 |
| BUN (mg/dL) | 209 | 2.0 – 98.0 | 0.9993 | 0.2195 | 0.9968 |
| Creatinine (mg/dL) | 216 | 0.4 – 11.0 | 0.9643 | 0.0222 | 0.9888 |
{12}
b. Matrix comparison:
Not applicable. For use with lithium heparinized whole blood only.
3. Clinical studies:
a. Clinical Sensitivity:
Not applicable.
b. Clinical specificity:
Not applicable.
c. Other clinical supportive data (when a. and b. are not applicable):
Not applicable.
4. Clinical cut-off:
Not applicable.
5. Expected values/Reference range:
Reference ranges for glucose, BUN and creatinine are cited from the literature.
Glucose: 65 – 95 mg/dL
BUN: 7 – 18 mg/dL
Creatinine: Female: 0.6 – 1.1 mg/dL and Male: 0.7 – 1.3 mg/dL
References cited:
Statland, Bernard, “Clinical Decision Levels for Lab Tests,” Medical Economics Books, 1987.
Burtis, Carl A. and Ashwood, Edward R., ed. 1994. Tietz Textbook of Clinical Chemistry, W. B. Saunders Co. Philadelphia, PA.
Tietz, Norbert W., ed. 1983. Clinical Guide to Laboratory Tests, W. B. Saunders Co., Philadelphia, PA.
N. Proposed Labeling:
The labeling is sufficient and it satisfies the requirements of 21 CFR Parts 801 and 809, as applicable.
O. Conclusion:
The submitted information in this premarket notification is complete and supports a substantial equivalence decision.
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Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.