K090109 · Epocal, Inc. · CGA · Jun 24, 2009 · Clinical Chemistry
Device Facts
Record ID
K090109
Device Name
BLOOD GAS, ELECTROLYTE AND METABOLITE TEST CARD
Applicant
Epocal, Inc.
Product Code
CGA · Clinical Chemistry
Decision Date
Jun 24, 2009
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 862.1345
Device Class
Class 2
Attributes
Real-World Evidence
Real-World Evidence
Submission
Device
Sponsor
RWD Sources
RWE Use Summary
Key Tags
K090109 · Jun 24, 2009
BLOOD GAS, ELECTROLYTE AND METABOLITE TEST CARD
Epocal, Inc.
Patient whole blood samples collected in hospital field trials
Clinical method comparison studies were conducted at multiple hospital point-of-care (POC) sites to evaluate the performance of the EPOC Glucose test against the predicate device using patient-derived arterial, venous, and capillary blood samples.
Method comparison; Point-of-care; Clinical field trials; Patient samples
Clinical Evidence
Study Design
Population
Comparator
Key Endpoints
Method comparison field trials; Method comparison study
Hospital patients (capillary, arterial, and venous whole blood samples); Sample Size: 160; Number of Sites: Several hospitals
i-STAT Model 300
Glucose concentration measurement accuracy
Anticoagulant effect study; Method comparison study
Patient samples collected using heparinized and non-heparinized devices; Sample Size: 58; Number of Sites: Various POC sites of a hospital
i-STAT Model 300
Glucose concentration measurement accuracy
Arterial vs Venous comparison; Method comparison study
Patient samples (arterial and venous); Sample Size: 214; Number of Sites: Several hospitals and POC locations
i-STAT Model 300
Glucose concentration measurement accuracy
Indications for Use
The Glucose test, as part of the epoc Blood Analysis System is intended for use by trained medical professionals as an in vitro diagnostic device for the quantitative testing of samples of heparinized or un-anticoagulated arterial or venous whole blood in the laboratory or at the point of care in hospitals, nursing homes or other clinical care institutions. Glucose measurements from the epoc Blood Analysis System are used in the diagnosis and treatment of carbohydrate metabolism disorders including diabetes mellitus, idiopathic hypoglycemia, and pancreatic islet cell tumors.
Device Story
The epoc Blood Analysis System is a point-of-care diagnostic platform consisting of a handheld reader and a mobile computing device (epoc Host). It uses single-use test cards containing electrochemical sensor arrays. The glucose test adds a glucose oxidase-based amperometric sensor to the existing card panel. The user inserts a blood-filled card into the reader; the system automatically performs calibration, sample analysis, and data transmission to the Host. The Host displays and stores results. The device provides rapid quantitative glucose measurements to assist clinicians in diagnosing and managing metabolic disorders. It is designed for use by trained medical professionals in clinical environments.
Clinical Evidence
Bench testing only. Performance validated through precision studies (total CV 2.3% at 241.9 mg/dL), linearity (R²=0.9989, range 20-700 mg/dL), and method comparison against predicate devices (i-STAT, Hitachi) and reference methods. Comparison studies across 214 patient samples (arterial/venous) showed high correlation (slope 1.02, intercept -1.874, R²=0.997). Interference testing evaluated common anticoagulants and metabolites. Hematocrit effect was assessed across 30-62% range with no significant bias observed.
Technological Characteristics
The device uses an electrochemical glucose oxidase-based amperometric sensor. The test card is a unit-use, laminated foil sensor module with an on-board calibrator reservoir. The system operates at 37°C via a heater assembly. Connectivity is wireless (Bluetooth) between the Reader and the EPOC Host. The system is designed for point-of-care use. Software controls the automated test cycle, signal processing, and result calculation.
Indications for Use
Indicated for trained medical professionals to perform quantitative glucose testing on heparinized or un-anticoagulated arterial or venous whole blood. Used for diagnosis and treatment of carbohydrate metabolism disorders (diabetes mellitus, idiopathic hypoglycemia) and pancreatic islet cell tumors in clinical settings.
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
i-Stat Glucose Test using i-Stat Model 300 Portable Clinical Analyzer (K001387)
Reference Devices
ABL800 Flex Radiometer
Submission Summary (Full Text)
{0}
510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION
DECISION SUMMARY
ASSAY AND INSTRUMENT COMBINATION TEMPLATE
A. 510(k) Number:
k090109
B. Purpose for Submission:
Add new test to existing cleared system
C. Measurand:
Glucose
D. Type of Test:
Electrode technology
E. Applicant:
Epocal, Inc.
F. Proprietary and Established Names:
Blood Gas, Electrolyte And Metabolite Test Card
G. Regulatory Information:
1. Regulation section:
21CFR Sec.- 862.1345-Glucose test system.
2. Classification:
Class II
3. Product code:
CGA - Glucose Oxidase, Glucose
4. Panel:
Chemistry (75)
H. Intended Use:
1. Intended use(s):
See indications for use below
2. Indication(s) for use:
The Glucose test, as part of the epoc Blood Analysis System is intended for use by trained medical professionals as an in vitro diagnostic device for the quantitative testing of samples of heparinized or un-anticoagulated arterial or venous whole blood in the laboratory or at the point of care in hospitals, nursing homes or other clinical care institutions.
Glucose measurements from the epoc Blood Analysis System are used in the diagnosis and treatment of carbohydrate metabolism disorders including diabetes mellitus, idiopathic hypoglycemia, and pancreatic islet cell tumors.
{1}
3. Special conditions for use statement(s):
For prescription use
4. Special instrument requirements:
epoc Card Reader, epoc Host
I. Device Description:
The epoc glucose test is being added as an additional sensor to the existing single use test card that is used with the epoc Blood Analysis System. This test card is inserted into the epoc Reader and all analytical steps are performed automatically. Patient and user information may be entered into the mobile computing device (epoc Host) during the automated analysis cycle.
The epoc Blood Analysis System is an in vitro analytical system comprising a network of one or more epoc Readers designed to be used at the point of care (POC). The readers accept an epoc single use test card containing a group of sensors that perform diagnostic testing on whole blood. The blood test results are transmitted wirelessly to an epoc Host, which displays and stores the test results.
The epoc System is intended for use by trained medical professionals as an in vitro diagnostic device for the quantitative testing of samples of whole blood.
The test card panel configuration currently includes sensors for Sodium, Potassium, Ionized Calcium, pH, pCO2, pO2 and Hematocrit. This submission adds Glucose to this list of cleared tests.
To perform a blood test, a new test card is inserted into a card reader's card slot with white label face down. When fully inserted, the test card is automatically engaged in the reader.
Changes to the epoc Blood Analysis System required to introduce the Glucose test include:
- Developing a new Glucose sensor and adding it to the existing epoc test card, which was already designed to accommodate additional sensors;
- Modifications to the existing EpocHost software application to accommodate the new test;
- Labeling changes including indications for use for the Glucose test.
J. Substantial Equivalence Information:
1. Predicate device name(s):
i-STAT Model 300
2. Predicate 510(k) number(s):
k001387
2 of 13
{2}
3. Comparison with predicate:
| | epoc Blood Analysis System (Device) | i-STAT Model 300 – Predicate k001387 | |
| --- | --- | --- | --- |
| Intended use | The epoc Blood Analysis System is intended for use by trained medical professionals as an in vitro diagnostic device for the quantitative testing of samples of whole blood using the BGEM (Blood Gas Electrolyte Metabolite) test card panels. | The i-STAT Model 300 Portable Clinical Analyzer is intended to be used by trained medical professionals for use with i-STAT test cartridges and MediSense blood glucose test strips. i-STAT cartridges comprise a variety of clinical chemistry tests and test panels. | same |
| Where used | hospital | hospital | same |
| Measured parameters | Glucose, Sodium, Potassium, Ionized Calcium, pH, pCO2, pO2 and Hematocrit | Glucose and other various analytes such as Sodium, Potassium, Ionized Calcium, pH, pCO2, pO2 and Hematocrit | same |
| Sample type | Venous, arterial whole blood | Venous, arterial and capillary whole blood | same |
| Reportable range | Gluc 20 – 700 mg/dL | Gluc 20 – 700 mg/dL | same |
| Sample volume | 95-125 μL | 100 μL | same |
| Test card | Unit-use card with - on-board calibrator in sealed reservoir - an electrochemical multi-sensor array - port for sample introduction - fluid waste chamber | Unit-use cartridge with - on-board calibrator in sealed reservoir - an electrochemical multi-sensor array - port for sample introduction - fluid waste chamber | same |
| Test card storage | Room temperature until expiry date | Fridge storage until expiry date including max 2 weeks at room temperature | different |
| Sensor array | A laminated foil sensor module | A micro-fabricated chip-set | different |
| Tests/sensor components | Glu - glucose oxidase based amperometric peroxide detection | Glu - glucose oxidase based amperometric peroxide detection | same |
| Measurement temperature | 37°C | 37°C | same |
| Measurement sequence | Calibrate test card-introduce sample-measure | Introduce sample-calibrate test cartridge-measure | different |
| Measurement time | 30sec from sample introduction | 200 sec from sample introduction | different |
{3}
K. Standard/Guidance Document Referenced (if applicable):
| FDA Recognition No. | Standard | Title |
| --- | --- | --- |
| 5-4 | IEC 60601-1 | Medical Electrical Equipment - Part 1: General Requirements for Safety, 1988; Amendment 1, 1991-11, Amendment 2, 1995. (General) |
| 5-28 | IEC 60601-1-2:2001 | Medical Electrical Equipment - Part 1-2: General Requirements for Safety - Collateral Standard: Electromagnetic Compatibility - Requirements and Tests |
| 5-40 | ISO 14971 (2007)* | Medical devices - Application of risk management to medical devices |
| 7-100 | ISO 15197 (2003) | In vitro diagnostic test systems - Requirements for in vitro whole blood glucose monitoring systems intended for use by patients for self testing in management of diabetes mellitus, First Edition 2003-05-01, |
| 7-110 | CLSI EP05-A2 (2004) | Evaluation of Precision Performance of Clinical Chemistry Devices; Approved Guideline |
| 7-193 | CLSI EP06-A | Evaluation of the Linearity of Quantitative Measurement |
| 7-127 | CLSI EP07-A2 (2005) | Interference Testing in Clinical Chemistry; Approved Guideline |
| 7-92 | CLSI EP09-A2 (2002) | Method Comparison and Bias Estimation Using Patient Samples; Approved Guideline – Second Edition |
| 7-104 | CLSI H07-A3 (2000) | Procedure for Determining Packed Cell Volume by the Microhematocrit Method – Second Edition; Approved Standard – Third Edition |
| N/A | SW68 (2001)* | Medical device software – Software life cycle processes |
* Used as a guideline for the design and development of the device
| FDA Guidance Documents |
| --- |
| Points to Consider for Portable Blood Glucose Monitoring Devices Intended for Bedside Use in the Neonate Nursery |
| Review Criteria for Assessment of Portable Blood Glucose In Vitro Diagnostic Devices Using Glucose Oxidase |
| Total Product Life Cycle for Portable Invasive Blood Glucose Monitoring Systems |
L. Test Principle:
The glucose sensor comprises an immobilized enzyme first layer coated onto a gold electrode of the electrode module, with a diffusion barrier second layer.
The Epocal glucose electrode uses the enzyme glucose oxidase to convert glucose to hydrogen peroxide, and then uses an amperometric sensor to detect the enzymatically produced hydrogen peroxide. Peroxide detection is by redox mediated, horseradish peroxidase catalyzed, reduction on a gold electrode.
The enzyme layer immobilized on the electrode is further over-coated by a diffusion barrier layer whose composition and dimensions are selected to facilitate rapid transport of oxygen to the oxidase enzyme and assure that the enzymatic reaction rate
{4}
is regulated by the diffusion limited transport of glucose. The reduction current is proportional to the concentration of glucose in the test fluid.
## M. Performance Characteristics (if/when applicable):
### 1. Analytical performance:
#### a. Precision/Reproducibility:
Point-of-Care (POC) Precision was demonstrated at a total of 4 POC clinical sites utilizing typical POC operators and different locations. In two of the sites, listed below, each operator performed a precision study. This comprised the testing of twelve (12) epoc cards on six (6) readers using venous blood samples collected from volunteers in green top (dry Na Heparin) vacutainers.
| Site | User | N | Mean | SD | C.V. % |
| --- | --- | --- | --- | --- | --- |
| Level 1 | | | [mg/dL] | [mg/dL] | |
| Baystate Heme Onco | Phlebotomist | 10 | 42.8 | 1.9 | 4.4 |
| Baystate Heme Onco | Lab Operator | 12 | 43.2 | 1.8 | 4.2 |
| Baystate Main Lab | Lab Operator | 12 | 41.6 | 1.6 | 3.8 |
| Baystate Main Lab | Med Tech | 12 | 50 | 1.1 | 2.2 |
| Level 2 | | | | | |
| Huntsville Main Lab | Lab Operator | 11 | 242.8 | 6.6 | 2.7 |
| Huntsville Main Lab | Med Tech | 11 | 229 | 5.3 | 2.3 |
| Huntsville Main Lab | Lab Operator | 11 | 233.4 | 6.8 | 2.9 |
| Huntsville Main Lab | Phlebotomist | 12 | 228.5 | 7 | 3.1 |
Aqueous precision testing was conducted at an additional two POC sites in Huntsville Hospital, Huntsville, Alabama, at the Surgical/Trauma ICU (STICU) and Cardiac-Vascular Intensive Care Unit (CVICU). This study was conducted to demonstrate precision by operators who typically run patient samples at a point-of-care sites. The three QC levels were tested in each location by three different operators, with one operator per level of fluid per site, for a total of six different users: 4 Respiratory Therapists (RT), 1 nurse and 1 Certified Registered Nurse Practitioner (CRNP).
| | Low | | Mid | | High | |
| --- | --- | --- | --- | --- | --- | --- |
| | STICU | CVICU | STICU | CVICU | STICU | CVICU |
| N | 11 | 12 | 12 | 11 | 11 | 11 |
| Mean mg/dL | 48 | 46.6 | 109.7 | 106.8 | 258.9 | 256.9 |
| SD | 1.54 | 0.97 | 3.58 | 1.83 | 8.99 | 2.31 |
| %CV | 3.2 | 2.1 | 3.3 | 1.7 | 3.5 | 0.9 |
Studies were performed in-house to demonstrate the precision of the epoc glucose test. The table below shows the results of a twenty day precision study performed on 4 cartridge lots using aqueous controls at two levels L1 (213-277 mg/dL) and L3 (31-59 mg/dL). Each lot was tested for each level in
5 of 13
{5}
duplicate twice a day for 20 days.
| Glucose [mg/dL] | L1 | L3 |
| --- | --- | --- |
| N | 320 | 320 |
| Mean | 241.9 | 50.2 |
| \(S_{WR}\) | 4.72 | 1.1 |
| Within run CV% | 1.95% | 2.19% |
| \(S_{DD}\) | 2.86 | 0.43 |
| Day to day CV% | 1.18% | 0.09% |
| \(S_T\) | 5.52 | 1.18 |
| Total CV% | 2.30% | 2.30% |
Studies were performed in-house to demonstrate the precision of the epoc glucose sensor. The table below shows the results of a study conducted on whole blood samples prepared to five concentrations of glucose, using cards from four different lots and testing over 100 cards/blood sample on 50 different readers. The test was performed within $12\mathrm{min}$ for each sample.
| Fluid | Lot | n | avg | SD | %CV |
| --- | --- | --- | --- | --- | --- |
| 20 | 09072-8 | 4 | 25.4 | 1.2 | 4.8% |
| | 09096-7 | 24 | 22.1 | 1.2 | 5.2% |
| | 09097-7 | 29 | 22.7 | 1.0 | 4.6% |
| | 09098-7 | 45 | 22.4 | 1.0 | 4.4% |
| 20 Combined | | 102 | 22.5 | 1.2 | 5.4% |
| 120 | 09072-8 | 10 | 121.5 | 2.6 | 2.1% |
| | 09096-7 | 15 | 124.0 | 1.5 | 1.2% |
| | 09097-7 | 28 | 123.6 | 2.9 | 2.3% |
| | 09098-7 | 45 | 124.1 | 3.4 | 2.8% |
| 120 Combined | | 98 | 123.7 | 3.0 | 2.4% |
| 200 | 09072-8 | 8 | 210.0 | 2.6 | 1.2% |
| | 09096-7 | 19 | 216.5 | 7.0 | 3.2% |
| | 09097-7 | 31 | 214.3 | 6.9 | 3.2% |
| | 09098-7 | 43 | 217.9 | 10.2 | 4.7% |
| 200 Combined | | 101 | 215.9 | 8.5 | 3.9% |
| 300 | 09072-8 | 2 | 302.1 | 2.1 | 0.7% |
| | 09096-7 | 26 | 314.4 | 8.5 | 2.7% |
| | 09097-7 | 32 | 309.2 | 17.9 | 5.8% |
| | 09098-7 | 45 | 312.5 | 11.3 | 3.6% |
| 300 Combined | | 105 | 311.8 | 13.1 | 4.2% |
| 500 | 09072-8 | 4 | 529.7 | 23.8 | 4.5% |
| | 09096-7 | 25 | 554.2 | 14.6 | 2.6% |
| | 09097-7 | 30 | 544.8 | 17.1 | 3.1% |
| | 09098-7 | 44 | 548.9 | 17.8 | 3.2% |
| 500 Combined | | 103 | 548.3 | 17.6 | 3.2% |
{6}
# b. Linearity/assay reportable range:
The reportable range of the assay, 20 to $700\mathrm{mg / dL}$ is supported by the linearity study. This study was performed in-house using blood samples as per CLSI EP6-A recommendations for evaluation of linearity. A total of nine blood samples, with theoretical concentrations of 29, 83, 137, 212, 298, 406, 492, 578, $675\mathrm{mg / dL}$ were prepared from two pools of blood, which were evaluated by comparison with in-house reference instruments with traceability to NIST standards. Regression analysis was performed as per CLSI EP6-A. The summary is given in the table below.
| | Slope | Intercept | R2 | Range |
| --- | --- | --- | --- | --- |
| Glu [mg/dL] | 0.9996 | 0.64 | 0.9989 | 20-700 |
Another study was performed in-house on multiple whole blood samples with Glucose values spanning the reportable range. Three types of samples were considered, namely, normal hematocrit-normal venous blood pO2, normal hematocrit- hypoxic venous blood and elevated hematocrit-normal venous blood pO2. Linearity is reported versus two in-house standard whole blood glucose methods with traceability to NIST standards.
| Type of blood sample | Slope | Intercept | R2 | Test range | Units |
| --- | --- | --- | --- | --- | --- |
| 43% Hct, 30mmHg pO2 | 1.022 | -3.32 | 0.9997 | 20-700 | mg/dL |
| 62% Hct, 30mmHg pO2 | 1.018 | -4.04 | 0.9996 | 20-700 | mg/dL |
| 43% Hct, <20mmHg pO2 | 0.955 | 0.33 | 0.9995 | 20-700 | mg/dL |
# c. Traceability, Stability, Expected values (controls, calibrators, or methods):
The epoc System's test card comprises an on-board calibration material. This calibration fluid in the test card is prepared gravimetrically. Its concentration is measured for each batch with in house secondary reference instruments. Each reference instrument is calibrated with fluids having NIST traceable glucose concentrations and periodically verified using NIST SRM 965B serum based glucose solutions.
Stability is based on real time studies.
No controls available with assay. The manufacturer recommends using commercially available controls to comply with federal, state and local regulatory requirements that oversee the institution.
{7}
d. Detection limit:
The detection limit of 20 mg/dL for the epoc was verified by demonstrating acceptable precision near 20 mg/dL as described above. A study was conducted on whole blood samples at 20 ng/mL glucose using cards from four different lots and testing over 100 cards/blood sample on 50 different readers. The test was performed within 12 min for each sample. The observed %CV was ≤5.2%.
e. Analytical specificity:
Interference testing was performed in-house on the epoc glucose sensor. In each of these tests a whole blood specimen was aliquoted into two samples. The test sample was spiked by addition of interferent, while the control sample was spiked by the addition of the solvent of the interferent.
Anticoagulants:
- Citrate had no significant effect up to 15mM (441mg/dL), after which it decreases the glucose reading by -0.28%/mMCitrate, i.e. -0.01%/(mg/dLCitrate); therefore it is not recommended to use collection devices containing citrate as additive.
- Na fluoride had no significant effect up to 10mM (42mg/dL), after which it decreases the glucose reading by -0.1%/mMNaF, i.e. -0.024%/(mg/dLNaF); therefore it is not recommended to use collection devices containing Na fluoride as additive.
- Oxalate had no significant effect up to 20mM (128mg/dL), after which it decreases the glucose reading by -0.29%/mMOxalate, i.e. -0.045%/(mg/dLOxalate); therefore it is not recommended to use devices tubes containing oxalate as additive.
- Iodide had no significant effect up to 28μM (0.47mg/dLKI), after which it decreases the glucose reading by as much as (-0.16mg/dL)/μMI-, i.e. (-9.5mg/dL)/(mg/dLKI). Iodide concentrations higher than 0.4mMI- (6.7mMKI) will trigger iQC.
- Bromide had no significant effect up to 28mM (224mg/dLNaBr), after which it decreases the glucose reading by (-0.23 mg/dL)/mMBr, i.e. (-0.029mg/dL)/(mg/dLNaBr).
- N-acetyl cysteine had no significant effect up to 500μM (8mg/dL), after which it will trigger iQC.
- L-cysteine had no significant effect up to 750μM (9mg/dL), after which it will trigger iQC.
- Gallamine triethiodide (Flaxedil) had no significant effect up to 11μM (1mg/dL), after which it decreases the glucose reading by (-0.27mg/dL)/μMgallamine triethiodide, i.e. (-3mg/dL)/(mg/dLgallamine triethiodide).
- Thiocyanate had no significant effect up to 1mM (5.9mg/dLKSCN), after which it decreases the glucose reading with -1.7%/mMSCN, i.e. (-0.29mg/dL)/(mg/dLKSCN).
8 of 13
{8}
- Uric acid had no significant effect up to $700\mu \mathrm{M}$ (11.8mg/dL), after which it decreases the glucose reading by (-3.5mg/dL)/mMUric Acid, i.e. (-0.21mg/dL)/(mg/dLUric Acid).
- Mannose had no significant effect up to $3.5\mathrm{mM}$ (63mg/dL), after which it will increase the glucose reading by $+3.8\%/\mathrm{mM}$ Mannose, i.e. $(+0.21\%)/(mg/dL$ Mannose).
- Xylose had no significant effect up to $3\mathrm{mM}$ (45mg/dL), after which it will increase the glucose reading by $+7.5\%/\mathrm{mM}$ Xylose, i.e. $(+0.5\%)/(mg/dL$ Xylose).
# f. Assay cut-off:
Not Applicable
# 2. Comparison studies:
# a. Method comparison with predicate device:
The applicant evaluated the performance of the new epoc tests on patient specimens (capillary, arterial and venous) in clinical settings including at the point of care. The reference instrument was the predicate device, i.e. iSTAT Abbott Point of Care analyzers using CG8 cartridges and a Roche Hitachi analyzer. Comparison testing to the predicate device was performed in two locations: central lab and Hematology-Oncology-POC site. The testing was performed by a phlebotomist who was part of the POC-coordination staff.

i-STAT

Hitachi
| Device compared against i-STAT | | | | | | Device compared against Hitachi | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| N | slope | intercept | R | Range | | N | slope | intercept | R | Range | |
| 80 | 1.031 | -2.2 | 0.999 | 20 | 605.5 | 73 | 0.971 | -0.2 | 0.998 | 20 | 605.5 |
| Combined | | | | | |
| --- | --- | --- | --- | --- | --- |
| N | Slope | Intercept | R | Range | |
| 160 | 1.022 | -2.338 | 0.999 | 20 | 605.5 |
{9}
Additionally, the applicant evaluated the performance of the new epoc glucose sensor on patient specimens in clinical settings including at the point of care at Huntsville Hospital. Comparison testing to the predicate device was first performed in the laboratory and then thereafter in three non-lab locations: CVICU, Neurological Intensive Care Unit (NICU)-stroke and STICU. The method comparison study was conducted on 58 blood specimens against predicate device at point-of-care, in three different sites.
| N | slope | intercept | R2 | Range | |
| --- | --- | --- | --- | --- | --- |
| 58 | 1.006 | 0.7 | 0.993 | 65 | 268.5 |

# b. Matrix comparison:
# i. Effect of anticoagulant
The effect of anticoagulant was evaluated on patient samples that were collected using heparinized and non-heparinized collection devices. This study was performed at various POC sites of a hospital. The data was analyzed using EP9-2A methodology. The table below shows the method comparison summary versus the predicate device.
| Heparinized | | | | | |
| --- | --- | --- | --- | --- | --- |
| N | slope | intercept | R2 | Range | |
| 29 | 0.994 | 2 | 0.992 | 78 | 266.5 |
| Unheparinized | | | | | |
| 29 | 1.019 | -0.7 | 0.994 | 65 | 268.5 |
| Combined | | | | | |
| 58 | 1.006 | 0.7 | 0.993 | 65 | 268.5 |
{10}
ii. Venous versus arterial blood
Clinical data from method comparison studies performed in field trials at several hospitals and POC locations, on patient samples of whole blood, were analyzed separately as arterial and venous. The data was analyzed according to CLSI guideline EP09-2A. The table below shows the method comparison summary versus the predicate device.
| N | slope | intercept | R² | Range | |
| --- | --- | --- | --- | --- | --- |
| Arterial | | | | | |
| 100 | 0.991 | 1.89 | 0.995 | 26 | 355 |
| Venous | | | | | |
| 114 | 1.028 | -3.03 | 0.998 | 20 | 605.5 |
| Combined | | | | | |
| 214 | 1.02 | -1.874 | 0.997 | 20 | 605.5 |
iii. Effect of altitude
A method comparison study was performed at an altitude of over 2000m (~6600 ft) against ABL800 Flex Radiometer whole blood instrument. The data was analyzed using EP9-2A methodology. The table in figure 5.12 shows the method comparison summary.
| N | slope | intercept | R² | Range | |
| --- | --- | --- | --- | --- | --- |
| 26-100 mg/dL | | | | | |
| 39 | 0.986 | -1.9 | 0.975 | 26 | 97 |
| 100-300 mg/dL | | | | | |
| 26 | 1.009 | -4.1 | 0.985 | 100 | 290 |
| 300-631 mg/dL | | | | | |
| 16 | 1.032 | -5.9 | 0.978 | 301 | 631.5 |
| 26-631 mg/dL | | | | | |
| 81 | 1.031 | -6.12 | 0.998 | 26 | 631.5 |
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:
{11}
Non-diabetic patient glucose reference range is 74 – 100 mg/dL*
* Reference Ranges Table 56-1 in Tietz Textbook of Clinical Chemistry and Molecular Diagnostics- Fourth Edition, C.A. Burtis, E.R. Ashwood, and D.E. Burns eds., Elsevier Saunders, St.Louis, 2006.
N. Instrument Name:
epoc Blood Analysis System with BGEM Test Card (BGE Test Card plus Glucose)
O. System Descriptions:
1. Modes of Operation:
Single sample mode of operation for sample reader, Host Personal Digital Assistant (PDA) can link to up to seven readers and actively control up to 4 readers in the analysis mode.
2. Software:
FDA has reviewed applicant’s Hazard Analysis and software development processes for this line of product types:
Yes ☐ X or No ☐
The applicant has provided software documentation that supports good software life-cycle processes.
3. Specimen Identification:
Hand entry or Bar-Code
4. Specimen Sampling and Handling:
Single sample using syringe
5. Calibration:
Unitized calibrator fluid
6. Quality Control:
Internal Quality control and recommendation of commercially available external quality control material
P. Other Supportive Instrument Performance Characteristics Data Not Covered In The “Performance Characteristics” Section above:
Effect of Hematocrit
Hematocrit effect was evaluated in six glucose level blood linearity studies performed at four different hematocrit levels.
The hematocrit was evaluated by centrifugation using the micro-hematocrit method. The reference mean glucose concentration was computed from the average of at least two in house reference instruments with traceability to NIST standards. The percent bias for each sample tested was within 10% of the reference mean for each level and each level of glucose demonstrated acceptable precision and there was no correlation between the glucose result and the hematocrit.
The summary is presented in the Table below. Each sample was tested on 6 cards, i.e. duplicates from 3 different lots and each individual sample fell within 10% of the reference mean:
12 of 13
{12}
| Hct [PCV] | Glu level | Ref. mean [mg/dL] | epoc mean | Mean 95% conf | epoc | epoc bias | epoc bias |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | | | [mg/dL] | [mg/dL] | %CV | [mg/dL] | percent |
| 30 | 35 | 33.7 | 34.9 | 2.1 | 8.40% | 1.2 | 3.56% |
| 30 | 60 | 54.5 | 55.6 | 1 | 2.50% | 1.1 | 2.02% |
| 30 | 130 | 128.7 | 127.9 | 1.2 | 1.30% | -0.7 | -0.62% |
| 30 | 200 | 209.3 | 212.6 | 3.2 | 2.10% | 3.2 | 1.58% |
| 30 | 400 | 407.2 | 425.4 | 7.9 | 2.60% | 18.2 | 4.47% |
| 30 | 600 | 608.3 | 601.4 | 14.8 | 3.30% | -7 | -1.13% |
| 43 | 35 | 36.6 | 36 | 1.1 | 1.20% | -0.6 | -1.64% |
| 43 | 50 | 49.2 | 46.4 | 0.8 | 3.80% | -2.7 | -5.69% |
| 43 | 100 | 96.8 | 95.4 | 1.8 | 5.70% | -1.4 | -1.45% |
| 43 | 130 | 129.9 | 128.4 | 2.7 | 2.20% | -1.5 | -1.15% |
| 43 | 200 | 204.7 | 205.3 | 2 | 2.60% | 0.6 | 0.29% |
| 43 | 350 | 330.7 | 346.4 | 10.8 | 2.40% | 15.7 | 4.75% |
| 43 | 650 | 670.5 | 690.5 | 32.4 | 4.00% | 20 | 2.98% |
| 52 | 35 | 34 | 35.9 | 2.1 | 5.80% | 1.9 | 5.59% |
| 52 | 60 | 55.7 | 55.8 | 1 | 2.70% | 0.1 | 0.18% |
| 52 | 130 | 130.7 | 129.7 | 1.2 | 1.50% | -0.9 | -0.77% |
| 52 | 200 | 216 | 210.2 | 3.2 | 1.30% | -5.8 | -2.69% |
| 52 | 400 | 416.7 | 417.3 | 7.9 | 2.00% | 0.7 | 0.14% |
| 52 | 600 | 615.2 | 596.2 | 14.8 | 5.10% | -18.9 | -3.09% |
| 62 | 35 | 29.7 | 31.6 | 0.6 | 2.10% | 1.9 | 6.40% |
| 62 | 50 | 46.8 | 45.9 | 0.4 | 1.20% | -1 | -1.92% |
| 62 | 100 | 95.4 | 93.9 | 1.9 | 1.80% | -1.5 | -1.57% |
| 62 | 130 | 127.5 | 121.7 | 1.3 | 1.00% | -5.8 | -4.55% |
| 62 | 200 | 205.1 | 201.6 | 3.5 | 1.30% | -3.4 | -1.71% |
| 62 | 350 | 326 | 336 | 3.2 | 2.50% | 10 | 3.07% |
| 62 | 650 | 666 | 685.3 | 9.8 | 2.20% | 19.2 | 2.90% |
Table - Summary of Glucose Blood Linearity Results at Various Hct Levels
# Q. Proposed Labeling:
The labeling is sufficient and it satisfies the requirements of 21 CFR Part 809.10.
# R. Conclusion:
The submitted information in this premarket notification is complete and supports a substantial equivalence decision.
Predicate graph will load when search results are available.
Embedding visualization will load when search results are available.
PDF viewer will load when search results are available.
Loading panels...
Select an item from Submissions
Click any panel, subpart, regulation, product code, or device to see details here.
Section Matches
Results will appear here.
Product Code Matches
Results will appear here.
Special Control Matches
Results will appear here.
Loading collections...
Loading
My Alerts
You will receive email notifications based on the filters and frequency you set for each alert.
Sort by:
Create Alert
Search Filters
Agent Token
Create a read-only bearer token for Claude, ChatGPT, or other agents that can call HTTP APIs.
Copy this now. It will not be shown again.
Connected apps
Apps you authorized through browser sign-in. Disconnecting revokes their access immediately.
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.