The EasyStat 300 is designed for clinical laboratory use, making quantitative measurements of Glucose (Glu) and Hematocrit % (Hct) in whole blood (arterial/venous) samples from Li-Heparinized Syringes or Capillary Tubes. This analyzer should only be used by trained technicians in clinical laboratories to aid in the diagnosis and treatment of patients with metabolite disturbances. Glucose (Glu) measurements are used in the diagnosis and treatment of carbohydrate metabolism disorders including diabetes mellitus, idiopathic hypoglycemia, and pancreatic inlet cell carcinoma. Hematocrit (Hct) measurements are used to measure red cell volume in blood. Abnormal states include anemia and erythrocytosis.
Device Story
EasyStat 300 is a bench-top analyzer for clinical laboratories; operated by trained technicians. Input: 175μL (syringe) or 100μL (capillary) of lithium heparinized whole blood. Principle: Amperometric glucose measurement via glucose oxidase (H₂O₂ production proportional to current); hematocrit quantification via electrical impedance corrected for sodium ion concentration. Device uses replaceable ISE cartridges and reagent modules with encoded calibration data. Output: Quantitative glucose and hematocrit values displayed to the clinician. Clinical utility: Aids diagnosis/treatment of metabolic disorders and red cell volume abnormalities. Benefits: Rapid, automated point-of-care-style analysis within a laboratory setting.
Clinical Evidence
No clinical trials performed. Evidence consists of analytical bench testing: precision (20-day single-site and 5-day multi-site studies), linearity (9-sample regression analysis), interference testing (endogenous/exogenous substances), and method comparison against predicate devices (RapidPoint 500 and EasyStat). Method comparison showed strong correlation (R² 0.872–0.999) across reported ranges.
Technological Characteristics
Bench-top analyzer; replaceable sensor cartridge and reagent module. Glucose sensing: amperometric (glucose oxidase). Hematocrit sensing: electrical impedance/conductivity. Sample volume: 100-175μL. Traceability: Glucose to NIST SRM-917c; Hct to internal conductivity standards. Connectivity: encoded reagent information read by analyzer. Standards: CLSI EP05-A3, EP07-A3, EP09c, EP17-A2, EP37 E1, EP32-R, EP25-Ed2; IEC 61010-1; ISO 17511:2020.
Indications for Use
Indicated for clinical laboratory use by trained technicians to measure Glucose and Hematocrit in arterial or venous Li-Heparinized whole blood to aid in diagnosing/treating carbohydrate metabolism disorders (e.g., diabetes, hypoglycemia, carcinoma) and red cell volume abnormalities (e.g., anemia, erythrocytosis).
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.
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FDA
U.S. FOOD & DRUG
ADMINISTRATION
# 510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION DECISION SUMMARY
ASSAY ONLY
## I Background Information:
A 510(k) Number
K220328
B Applicant
Medica Corporation
C Proprietary and Established Names
EasyStat 300
D Regulatory Information
| Product Code(s) | Classification | Regulation Section | Panel |
| --- | --- | --- | --- |
| CGA | Class II | 21 CFR 862.1345 - Glucose Test System | CH - Clinical Chemistry |
| GKF | Class II | 21 CFR 864.5600 - Automated hematocrit instrument | HE - Hematology |
## II Submission/Device Overview:
A Purpose for Submission:
New Device
B Measurand:
Glucose (Glu) and Hematocrit (Hct).
C Type of Test:
Glucose – quantitative, amperometric
Hematocrit – quantitative, electrical conductivity
Food and Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993-0002
www.fda.gov
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K220328 - Page 2 of 12
## III Intended Use/Indications for Use:
### A Intended Use(s):
See Indications for Use below.
### B Indication(s) for Use:
The EasyStat 300 is designed for clinical laboratory use, making quantitative measurements of Glucose (Glu) and Hematocrit % (Hct) in whole blood (arterial/venous) samples from Li-Heparinized Syringes or Capillary Tubes. This analyzer should only be used by trained technicians in clinical laboratories to aid in the diagnosis and treatment of patients with metabolite disturbances.
Glucose (Glu) measurements are used in the diagnosis and treatment of carbohydrate metabolism disorders including diabetes mellitus, idiopathic hypoglycemia, and pancreatic inlet cell carcinoma.
Hematocrit (Hct) measurements are used to measure red cell volume in blood. Abnormal states include anemia and erythrocytosis.
### C Special Conditions for Use Statement(s):
Rx - For Prescription Use Only
For in vitro diagnostic use only
### D Special Instrument Requirements:
EasyStat 300 Analyzer
## IV Device/System Characteristics:
### A Device Description
The candidate device is a small bench-top analyzer for use by health care professionals. The analyzer incorporates a replaceable EasyStat 300 ISE cartridge that is comprised of sensors for measurement of glucose (Glu) and hematocrit (Hct). The analyzer draws 175μL of human lithium heparinized venous or arterial whole blood samples when operated in syringe mode, and 100μL of human lithium heparinized venous or arterial whole blood samples when operated in capillary mode.
The analyzer incorporates a replaceable reagent module containing calibrating solutions (A2, B2, and C2) for the sensors. The reagent module contains encoded reagent information (calibration values and expiration date) which is read by the analyzer upon installation of the reagent module. Calibrations are performed automatically or on-demand by the user.
The EasyStat 300 Analyzer was also cleared for making quantitative measurements of pO2 (partial pressure of oxygen), pCO2 (partial pressure of carbon dioxide), and pH (hydrogen ion
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activity) in K211559 and K+ (potassium), Ca++ (ionized calcium), and Cl- (Chloride) in K220396.
## B Principle of Operation:
The EasyStat 300 uses biosensors incorporated in the Glu-Hct sensor cartridge for the measurement of glucose and hematocrit in patient's blood samples.
Glucose is measured amperometrically on the cartridge using electrodes that measure the change in current at the sensor surface. The sensor uses glucose oxidase to produce hydrogen peroxide (H₂O₂), and the electrons generated in the oxidation process produce an electrical current that is proportional to the glucose concentration in the sample.
Hematocrit is quantified by measuring the electrical impedance of a blood sample following calibration of the Hct sensor using two standard solutions. The Hct concentration obtained is corrected for the concentration of sodium ions.
## V Substantial Equivalence Information:
A Predicate Device Name(s):
GEM Premier ChemSTAT
B Predicate 510(k) Number(s):
K223090
C Comparison with Predicate(s):
| Device & Predicate Device(s): | K220328 | K223090 |
| --- | --- | --- |
| Device Trade Name | EasyStat 300 | GEM Premier ChemSTAT |
| General Device Characteristic Similarities | | |
| Intended Use/Indications For Use | For the measurement of Glucose (Glu) and Hematocrit % (Hct) | Same |
| Sample Type | arterial and venous lithium heparinized whole blood | Same |
| General Device Characteristic Differences | | |
| Use Environment | Clinical Laboratory | Clinical Laboratory and Point of Care |
| Analytes Measured | Glu and Hct | Sodium (Na+), Potassium (K+), Ionized Calcium (Ca++), Chloride (Cl-), Glucose |
K220328 - Page 3 of 12
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| Device & Predicate Device(s): | K220328 | K223090 |
| --- | --- | --- |
| | | (Glu), Lactate (Lac), Hematocrit (Hct), Creatinine (Crea), Blood Urea Nitrogen (BUN), Total Carbon Dioxide (tCO2), pH, and partial pressure of carbon dioxide (pCO2) |
VI Standards/Guidance Documents Referenced:
- CLSI EP05-A3 “Evaluation of Precision of Quantitative Measurement Procedures: Approved Guideline – 3rd Edition”
- CLSI EP07-A3 “Interference Testing in Clinical Chemistry: Approved Guideline – 3rd Edition”
- CLSI EP09c “Method Procedure Comparison and Bias Estimation Using Patient Samples – 3rd Edition”
- CLSI EP17-A2 “Evaluation of Detection Capability for Clinical Laboratory Measurement Procedures: Approved Guideline – 2nd Edition”
- CLSI EP37 E1 “Supplemental Tables for Interference Testing in Clinical Chemistry”
- IEC 61010-1 “Safety Requirement for Electrical Equipment for Measurement, Control, and Laboratory Use – Part 1: General Requirements”
- ISO 17511:2020 “In Vitro Diagnostic Medical Devices – Requirements for Establishing Metrological Traceability of Values Assigned to Calibrators, Trueness Control Materials, and Human Samples”
- CLSI EP32-R “Metrological Traceability and Its Implementation; A Report”
- CLSI EP25-Ed2 “Evaluation of Stability of In Vitro Medical Laboratory Test Reagents – 2nd Edition”
VII Performance Characteristics (if/when applicable):
A Analytical Performance:
1. Precision/Reproducibility:
The Precision of the EasyStat 300 was evaluated in two studies: a single-site, 20-day study using aqueous QC material and a multi-site, 5-day study using venous whole blood from donors. Each study was performed in both Syringe and Capillary mode.
Single-Site Study – 20-day with aqueous QC material
Three levels of aqueous QC material were assayed for Glucose and two levels of aqueous QC material were assayed for Hematocrit. Testing was performed using three EasyStat 300 analyzers and a single lot of cartridges. Each sample was measured in duplicate per run with two runs per day over twenty non-consecutive days, resulting in a total of 80 measurements
K220328 - Page 4 of 12
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per level. Data collected from each of the three analyzers were evaluated for Repeatability (within-run) and Within-Device precision and the results from one representative analyzer are summarized below:
Single Site 20-day Precision Summary
| Analytes | Mode | Level | Mean Value | N | Repeatability | | Within-Device | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | | | | | SD | %CV | SD | %CV |
| Glucose | Syringe | 1 | 325 | 80 | 4.14 | 1.3 | 6.48 | 2.0 |
| | | 2 | 91 | 80 | 1.54 | 1.7 | 1.98 | 2.2 |
| | | 3 | 46 | 80 | 0.97 | 2.1 | 1.38 | 3.0 |
| | Capillary | 1 | 295 | 80 | 6.62 | 2.2 | 9.69 | 3.3 |
| | | 2 | 86 | 80 | 2.49 | 2.9 | 2.75 | 3.2 |
| | | 3 | 43 | 80 | 2.02 | 4.7 | 2.32 | 5.4 |
| Hematocrit | Syringe | 1 | 27 | 80 | 0.32 | 1.2 | 0.45 | 1.7 |
| | | 2 | 47 | 80 | 0.25 | 0.5 | 0.49 | 1.0 |
| | Capillary | 1 | 26 | 80 | 0.70 | 2.8 | 0.75 | 2.9 |
| | | 2 | 44 | 80 | 0.40 | 0.9 | 0.52 | 1.2 |
Multi-Site Study - 5-day with venous whole blood
Three levels of venous whole blood were assayed for both Glucose and Hematocrit. Testing was performed by using three EasyStat 300 analyzers and three cartridge lots (one per instrument). Each sample was measured with five replicates per run, with one run per day over five consecutive days, resulting in a total of 25 measurements per level on each instrument. Data collected from each of the three analyzers were evaluated for Repeatability (Within-Run precision) and Within Laboratory precision. The results from one representative analyzer are summarized in the tables below:
Multi Site 5-day Precision Summary - Glucose
| Glu (Syringe Mode) | | | | | |
| --- | --- | --- | --- | --- | --- |
| Sample | Mean | Repeatability | | Within Laboratory | |
| | | SD | %CV | SD | %CV |
| 1 | 54.9 | 0.5 | 1.0% | 1.2 | 2.2% |
| 2 | 40.3 | 1.0 | 2.4% | 1.1 | 2.6% |
| 3 | 51.1 | 1.0 | 2.1% | 1.1 | 2.1% |
| 4 | 40.3 | 1.4 | 3.6% | 1.4 | 3.6% |
| 5 | 45.3 | 2.1 | 4.7% | 2.1 | 4.7% |
| 6 | 117.9 | 1.6 | 1.3% | 2.5 | 2.1% |
| 7 | 115.3 | 1.6 | 1.4% | 2.1 | 1.8% |
| 8 | 76.2 | 1.3 | 1.7% | 1.3 | 1.7% |
| 9 | 94.3 | 1.8 | 1.9% | 2.1 | 2.2% |
| 10 | 114.7 | 2.1 | 1.9% | 2.4 | 2.1% |
| 11 | 265.9 | 1.8 | 0.7% | 6.0 | 2.2% |
| 12 | 256.0 | 1.5 | 0.6% | 4.9 | 1.9% |
| 13 | 235.3 | 1.6 | 0.7% | 3.2 | 1.4% |
| 14 | 248.9 | 1.9 | 0.8% | 4.1 | 1.6% |
| Glu (Capillary Mode) | | | | | |
| --- | --- | --- | --- | --- | --- |
| Sample | Mean | Repeatability | | Within Laboratory | |
| | | SD | %CV | SD | %CV |
| 1 | 51.1 | 0.7 | 1.4% | 1.6 | 3.1% |
| 2 | 37.4 | 1.0 | 2.8% | 1.7 | 4.6% |
| 3 | 49.5 | 1.6 | 3.3% | 1.6 | 3.3% |
| 4 | 39.0 | 1.8 | 4.6% | 1.8 | 4.7% |
| 5 | 43.7 | 2.1 | 4.8% | 2.1 | 4.8% |
| 6 | 115.8 | 1.9 | 1.7% | 3.1 | 2.7% |
| 7 | 113.3 | 2.0 | 1.8% | 2.1 | 1.8% |
| 8 | 76.2 | 1.5 | 2.0% | 1.6 | 2.1% |
| 9 | 91.9 | 2.2 | 2.4% | 2.4 | 2.6% |
| 10 | 111.1 | 1.9 | 1.7% | 2.5 | 2.2% |
| 11 | 255.1 | 2.8 | 1.1% | 6.2 | 2.4% |
| 12 | 253.3 | 2.5 | 1.0% | 5.0 | 2.0% |
| 13 | 234.3 | 2.3 | 1.0% | 3.2 | 1.4% |
| 14 | 238.8 | 3.7 | 1.5% | 3.8 | 1.6% |
K220328 - Page 5 of 12
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Multi Site 5-day Precision Summary – Hematocrit
| Hct (Syringe Mode) | | | | | |
| --- | --- | --- | --- | --- | --- |
| Sample | Mean | Repeatability | | Within Laboratory | |
| | | SD | %CV | SD | %CV |
| 1 | 27.5 | 0.5 | 1.8% | 0.8 | 3.0% |
| 2 | 22.5 | 0.5 | 2.3% | 0.7 | 3.0% |
| 3 | 23.4 | 0.3 | 1.1% | 1.1 | 4.5% |
| 4 | 22.9 | 0.4 | 1.8% | 0.7 | 3.1% |
| 5 | 26.3 | 0.5 | 1.8% | 0.8 | 2.9% |
| 6 | 40.3 | 0.7 | 1.8% | 0.9 | 2.1% |
| 7 | 39.4 | 0.3 | 0.7% | 1.2 | 3.1% |
| 8 | 37.5 | 0.5 | 1.3% | 1.5 | 4.0% |
| 9 | 47.4 | 0.5 | 1.0% | 0.7 | 1.4% |
| 10 | 50.0 | 0.4 | 0.9% | 0.6 | 1.1% |
| 11 | 59.3 | 2.0 | 3.3% | 2.0 | 3.3% |
| 12 | 59.1 | 1.4 | 2.4% | 2.4 | 4.1% |
| 13 | 56.8 | 0.5 | 0.9% | 1.4 | 2.4% |
| 14 | 63.5 | 0.5 | 0.8% | 0.8 | 1.3% |
| 15 | 67.1 | 0.8 | 1.2% | 0.9 | 1.4% |
| Hct (Capillary Mode) | | | | | |
| --- | --- | --- | --- | --- | --- |
| Sample | Mean | Repeatability | | Within Laboratory | |
| | | SD | %CV | SD | %CV |
| 1 | 26.9 | 0.8 | 3.0% | 1.2 | 4.6% |
| 2 | 22.9 | 0.5 | 2.4% | 1.2 | 5.3% |
| 3 | 23.5 | 0.4 | 1.6% | 1.1 | 4.9% |
| 4 | 23.1 | 1.2 | 5.4% | 1.2 | 5.4% |
| 5 | 26.3 | 0.6 | 2.3% | 1.0 | 3.7% |
| 6 | 40.4 | 0.9 | 2.3% | 1.1 | 2.7% |
| 7 | 39.7 | 0.6 | 1.5% | 1.9 | 4.9% |
| 8 | 37.6 | 0.4 | 1.2% | 1.4 | 3.6% |
| 9 | 48.7 | 0.7 | 1.5% | 1.5 | 3.1% |
| 10 | 50.9 | 0.5 | 0.9% | 2.0 | 3.9% |
| 11 | 57.6 | 2.0 | 3.5% | 2.6 | 4.6% |
| 12 | 60.2 | 1.8 | 3.0% | 3.2 | 5.3% |
| 13 | 56.9 | 0.4 | 0.6% | 2.0 | 3.6% |
| 14 | 64.1 | 0.5 | 0.8% | 0.9 | 1.5% |
| 15 | 68.4 | 0.6 | 0.8% | 2.3 | 3.3% |
2. Linearity:
The linearity study was conducted using 9 samples covering the measuring range assayed in triplicate on each of three EasyStat 300 analyzers. The study was conducted in both syringe mode and capillary mode, using one lot of cartridges over one day. Native lithium heparin venous whole blood samples were spiked with D-glucose (for Glu) or packed red blood cells (for Hct) or diluted with plasma from the same donor. Regression analysis confirmed first order linearity for both glucose and hematocrit within the specified reportable ranges. The maximum % deviation from linearity noted was 9.1%. The summary analysis is included in the table below:
| Analyte | Claimed Range | Mode | Analyzer | Tested Range | Slope | Intercept | R2 | Max Deviation |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Glucose | 25-500 mg/dL | Syringe | 1 | 18-530 | 0.970 | -3.04 | 0.999 | -4.2% |
| | | | 2 | 19-558 | 1.014 | -3.13 | 0.999 | -3.7% |
| | | | 3 | 18-530 | 0.971 | -2.29 | 0.999 | -3.1% |
| | | Capillary | 1 | 18-536 | 0.969 | 0.56 | 0.999 | 0.8% |
| | | | 2 | 20-556 | 1.028 | -2.86 | 0.999 | -2.7% |
| | | | 3 | 20-544 | 1.001 | -3.18 | 0.999 | -3.6% |
| Hematocrit | 10-70% | Syringe | 1 | 8-77 | 1.007 | 0.82 | 0.999 | 6.4% |
| | | | 2 | 9-78 | 1.007 | 1.60 | 0.999 | 8.3% |
K220328 - Page 6 of 12
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K220328 - Page 7 of 12
| Analyte | Claimed Range | Mode | Analyzer | Tested Range | Slope | Intercept | R² | Max Deviation |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | | | 3 | 9-77 | 1.000 | 2.00 | 1.000 | 9.1% |
| | | Capillary | 1 | 6-74 | 0.974 | 0.37 | 0.999 | 2.7% |
| | | | 2 | 6-78 | 1.011 | 0.34 | 0.999 | 2.3% |
| | | | 3 | 6-78 | 1.000 | 0.78 | 0.999 | 4.8% |
# 3. Analytical Specificity/Interference:
Interference with endogenous and exogenous substance was evaluated using lithium heparin venous whole blood samples. Two levels of Glu (ranging from 26.4 to 346.4 mg/dL) and two levels of Hct (ranging from 18.2% to 48.4%) were tested with and without the potential interfering substances.
Bias was calculated as the difference between the average value with interferent and the average value without interferent. Interferents identified with a bias less than the total allowable error (TAE) were listed as non-interfering while those with bias greater than the TAE were listed with their calculated % bias.
| Analyte | TAE |
| --- | --- |
| Glucose | ± 6 mg/dL or 10% |
| Hematocrit | ± 4% or 10% |
The potential interferents that were tested are listed in the tables below, along with the highest concentration that each substance did not cause interference:
Glucose
| Interferent | Highest Concentration that did not cause interference |
| --- | --- |
| Acetaminophen | 8.0 mg/dL |
| Acetoacetate (Lithium) | 2 mmol/L |
| N-Acetylcysteine | 15 mg/dL |
| Albumin | 60 g/L |
| Ascorbic Acid | 0.298 mmol/L |
| Bilirubin (conjugated) | 20 mg/dL |
| Chloropromazine | 9 μmol/L |
| Citrate (Sodium) | 12.0 mmol/L |
| Creatinine | 15 mg/dL |
| Dobutamine | 0.121 mg/dL |
| Dopamine | 4.06 μmol/L |
| Ethanol | 130 mmol/L |
| Fluoride (Sodium) | 40 μmol/L |
| Flaxedil | 5 mg/dL |
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| Interferent | Highest Concentration that did not cause interference |
| --- | --- |
| Fructose | 1 mM |
| Galactose | 3.33 mmol |
| Glycolic Acid | 0.75 mmol/L |
| Hematocrit | 75% |
| Heparin (Sodium) | 330 U/dL |
| Hemoglobin | 22 gr/dL |
| B-Hydroxybutyrate | 2 mmol/L |
| Hydroxy Urea* | 0.12 mg/dL |
| Ibuprofen | 1.06 mmol/L |
| Isoniazid* | 2 mg/dL |
| Lactate | 10 mmol/L |
| Maltose | 10.3 mmol/L |
| Mannose | 20 mg/dL |
| pO2 | 74 mmHg |
| Pralidoxime Iodide | 40 μg/dL |
| Pyruvate (Sodium) | 5 mg/dL |
| Triglycerides (Intralipids) | 2% |
| Urea | 42.9 mmol/L |
| Xylose | 20 mg/dL |
*The following substances were shown to exhibit interference with glucose. For hydroxyurea, an interference was noted when tested at 3.08 mg/dL, resulting in a bias of up to 458% for glucose. For isoniazid, an interference was noted when tested at 3 mg/dL, resulting in a bias of up to 30% for glucose.
Hematocrit
| Interferent | Highest Concentration that did not cause interference |
| --- | --- |
| Acetaminophen | 15.6 mg/dL |
| Albumin | 60 g/L |
| Ammonium Chloride | 0.1 mM |
| Benzalkonium Chloride | 0.25 mg/dL |
| Bilirubin | 40 mg/dL |
| Bromide (Sodium) | 2.0 mM |
| Chloropromazine | 5 mg/dL |
| Epinephrine | 0.4 μM |
| Ethanol | 130 mmol/L |
| Fluoride (Sodium) | 0.1 mM |
| Fructose | 1 mM |
K220328 - Page 8 of 12
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| Interferent | Highest Concentration that did not cause interference |
| --- | --- |
| Galactose | 1 mM |
| Ibuprofen | 1.06 mmol/L |
| Intralipids | 2000 mg/dL |
| Iodide (Potassium) | 0.5 mM |
| Isoniazid | 0.4 μM |
| Mannose | 10 mg/dL |
| Perchlorate (Sodium) | 5.0 mg/dL |
| Platelets | 790 x 10^{6}/mL |
| Pralidoxime Iodide | 4 mg/dL |
| Salicylate (Sodium) | 12 mg/dL |
| Sodium Chloride | 193 mM |
| Thiocyanate (Potassium) | 1.0 mg/dL |
| White Blood Cells | 27 x 10^{6}/mL |
| Xylose | 20 mg/dL |
| Li-Heparin (anticoagulant) | 126 IU/mL |
4. Assay Reportable Range:
See section VII A.2, Linearity.
5. Traceability, Stability, Expected Values (Controls, Calibrators, or Methods):
Glucose is traceable to NIST SRM-917c. Hct traceability is performed using internally produced reference standards and is calculated using conductivity measurements.
6. Detection Limit:
**LoB/LoD**
For Glucose, the Limit of Blank (LoB) was evaluated using five pooled plasma samples. Once LoB was established, LoD was evaluated by spiking glucose into the plasma samples.
For Hematocrit, the LoB was evaluated using five pooled plasma samples that were prepared through centrifugation of blood samples. Once LoB was established, LoD was evaluated by spiking a small number of red blood cells into the plasma samples.
All studies were performed in both syringe and capillary mode and carried out on a single instrument with two reagent lots over three consecutive days. Five samples were run with four replicates per reagent lot, resulting in a total of 60 blank replicates per lot for LoB and 60 low level replicates per lot for LoD.
K220328 - Page 9 of 12
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K220328 - Page 10 of 12
# LoQ
For Glucose, the Limit of Quantitation (LoQ) was determined using four pooled plasma samples created by using ultrafiltration until the glucose concentrations were sufficiently low. The ultrafiltered plasma was then spiked with concentrated glucose to achieve glucose levels slightly above the LoD. Values were determined by first measuring on a RapidPoint 500 device.
For Hematocrit, the LoQ was determined using four pooled plasma samples that were prepared through centrifugation of blood samples. A small number of red blood cells were then spiked into the plasma to increase hematocrit level to slightly above the LoD. Values were determined by first measuring on an EasyStat pH, pCO₂, pO₂, Hct, NA⁺, K⁺, CA++ analyzer and then diluting the sample with plasma from the same donor.
Studies were performed in both syringe and capillary modes and carried out on a single instrument with two reagent lots over three consecutive days. Each day, the four samples were run with three replicates per reagent lot, resulting in a total of 36 low level sample replicates per lot.
The Detection Limit results are summarized in the tables below:
Limit of Blank, Detection, and Quantitation Summary
| Syringe | LoB | LoD | LoQ | LDL* Claim |
| --- | --- | --- | --- | --- |
| Glu (mg/dL) | 7.5 | 11.8 | 25 | 25 |
| Hct (%) | 4 | 5 | 8 | 10 |
| Capillary | LoB | LoD | LoQ | LDL* Claim |
| --- | --- | --- | --- | --- |
| Glu (mg/dL) | 9.5 | 14.3 | 22 | 25 |
| Hct (%) | 4 | 7 | 9 | 10 |
(*) LDL: Lowest Detection Limit
7. Assay Cut-Off:
Not Applicable.
B Comparison Studies:
1. Method Comparison with Predicate Device:
The Method Comparison study was conducted using lithium heparin venous and arterial whole blood collected from subjects across two sites. For Glucose, 243 unique samples were analyzed on both an EasyStat 300 candidate device and a Rapidpoint 500 predicate device. For Hematocrit, up to 198 unique samples were analyzed on both an EasyStat 300 candidate device and an EasyStat predicate device. Many of these samples were used to evaluate both Glu and Hct.
{10}
Data was obtained in both Syringe and Capillary modes on the EasyStat 300 analyzer and analysis was performed using the Weighted Deming method for linear regression.
| Analyte | Mode | N | Sample Range | Slope | Intercept | R² |
| --- | --- | --- | --- | --- | --- | --- |
| Glucose | Syringe | 198 | 42-494 mg/dL | 0.960 | -1.520 | 0.972 |
| | Capillary | 70 | 84-463 mg/dL | 0.9842 | 0.9685 | 0.976 |
| Hematocrit | Syringe | 242 | 16-62% | 1.098 | -2.653 | 0.872 |
| | Capillary | 71 | 14-64% | 0.9665 | 0.6540 | 0.972 |
2. Matrix Comparison:
Not Applicable.
C Clinical Studies:
1. Clinical Sensitivity:
Not Applicable.
2. Clinical Specificity:
Not Applicable.
3. Other Clinical Supportive Data (When 1. and 2. Are Not Applicable):
Not Applicable.
D Clinical Cut-Off:
Not Applicable.
E Expected Values/Reference Range:
Based on published literature, the sponsor included the following in the labeling:
Glucose: 70-105 mg/dL
Hematocrit: 35-50%
Sources:
1) Tietz Textbook of Clinical Chemistry and Molecular Diagnostics, 5th ed. Burtis C.A., Ashwood E.R., Bruns D.E., (WB Saunders Co, 2012).
K220328 - Page 11 of 12
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2) B.E. Statland, Clinical Decision Levels for Lab Tests (Oradell, NJ: Medical Economics Books, 1987).
## VIII Proposed Labeling:
The labeling supports the finding of substantial equivalence for this device.
## IX Conclusion:
The submitted information in this premarket notification is complete and supports a substantial equivalence decision.
K220328 - Page 12 of 12
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Learn the FDA Browser
Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
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.