K112755 · Diatron U.S., Inc. · GKZ · Mar 27, 2012 · Hematology
Device Facts
Record ID
K112755
Device Name
ABACUS 5
Applicant
Diatron U.S., Inc.
Product Code
GKZ · Hematology
Decision Date
Mar 27, 2012
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 864.5220
Device Class
Class 2
Attributes
Pediatric
Indications for Use
The Diatron Abacus 5 System is a quantitative multi-parameter automated hematology analyzer designed for in-vitro-diagnostic use in clinical laboratories for enumeration of the following parameters in K3EDTA anti-coagulated venous whole blood samples: WBC, LYM%, LYM#, MON%, MON#, NEU%, NEU#, EOS%, EOS#, BAS%, BAS#, RBC, HGB, HCT, MCV, MCH, MCHC, RDWcv, RDWsd, PLT, and MPV. The Diatron Abacus 5 is indicated for use to identify patients with hematologic parameters within and outside of established reference ranges.
Device Story
Abacus 5 is a fully automated hematology analyzer for clinical laboratory use. It processes K3EDTA venous whole blood samples via manual or optional autosampler (up to 100 tubes). Measurement technologies include impedance (WBC, RBC, PLT), photometry (HGB), and laser-based flow cytometry (5-part WBC differential). The system features a touch screen interface, internal database for 100,000 records, and LIS connectivity via Ethernet/HL7. It provides quantitative results, scatter diagrams, and histograms. Flags and alerts assist clinicians in identifying abnormal hematologic parameters. The device aids in patient screening and monitoring by providing rapid, precise blood cell counts.
Clinical Evidence
Clinical performance evaluated via method comparison against the predicate (Cell-Dyn 3700) using 828 patient samples across three sites (ages >1 month to >80 years). Accuracy demonstrated high correlation (r > 0.90 for most parameters). Distributional flagging sensitivity was 90.0% and specificity was 83.6% compared to manual microscopy (n=210). Precision/reproducibility studies (n=240 replicates per control level) showed within-device CVs generally <7%. Linearity (r² > 0.95) and carryover (≤1.0%) met specifications.
Technological Characteristics
Bench-top hematology analyzer; volumetric impedance (WBC, RBC, PLT); photometric (HGB); optical light scattering/diffraction (5-part differential). Connectivity via USB for printers. Software supports 100,000 record storage. Calibration via commercial calibrator; QC via CBC-3K controls. Operates on K3EDTA venous whole blood.
Indications for Use
Indicated for use in clinical laboratories to perform quantitative multi-parameter hematology analysis on K3EDTA anti-coagulated venous whole blood samples from patients of all ages (from >1 month to >80 years) to identify hematologic parameters within or outside established reference ranges.
Regulatory Classification
Identification
An automated differential cell counter is a device used to identify one or more of the formed elements of the blood. The device may also have the capability to flag, count, or classify immature or abnormal hematopoietic cells of the blood, bone marrow, or other body fluids. These devices may combine an electronic particle counting method, optical method, or a flow cytometric method utilizing monoclonal CD (cluster designation) markers. The device includes accessory CD markers.
Special Controls
*Classification.* Class II (special controls). The special control for this device is the FDA document entitled “Class II Special Controls Guidance Document: Premarket Notifications for Automated Differential Cell Counters for Immature or Abnormal Blood Cells; Final Guidance for Industry and FDA.”
Predicate Devices
Abbott Cell-Dyn 3700 (k991605)
Submission Summary (Full Text)
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# 510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION DECISION SUMMARY
A. 510(k) Number:
k112755
B. Purpose for Submission:
New device
C. Manufacturer and Instrument Name:
Diatron US Inc., Abacus 5
D. Type of Test or Tests Performed:
Quantitative test for WBC, NEU%, NEU#, LYM%, LYM#, MON%, MON#, EOS%, EOS#, BAS%, BAS#, RBC, HGB, HCT, MCV, MCH, MCHC, RDWcv, RDWsd, PLT, and MPV parameters.
E. System Descriptions:
1. Device Description:
The Abacus 5 is a fully automated bench-top hematology analyzer featuring a color touch screen display with a user interface capable of reporting 21 hematology parameters including CBC with a five-part WBC differential. The analyzer is supplied with specialized reagents including Diluent, Lyse, Diff and Cleaner. An optional Autosampler is available for automated processing of up to 100 sample tubes for increased laboratory efficiency. The main analyzer, data module, and display station are housed as a single unit. The Abacus 5 analyzer’s software system supports the use of commonly used external printers via USB connections.
2. Principles of Operation:
The Abacus 5 analyzer uses volumetric impedance to determine the cellular concentrations and volume distributions of WBC, RBC, and PLT. The HGB concentration is determined by photometric measurement of light absorbance. Optical measurement of light scattering and diffraction is used to determine the five-part leukocyte differential parameters. The MCV and RDW values are derived from statistical analysis of the RBC histogram. The HCT, MCH, and MCHC are calculated values. The MPV value is derived from statistical analysis of the PLT histogram.
3. Modes of Operation:
The Abacus 5 operates in both open and closed sample tube mode.
4. Specimen Identification:
The sample ID can be entered by the operator from a keyboard or hand held barcode reader for a manually processed specimen. For automatically processed specimens, the sample ID can be read from a sample tube barcode or entered into a list for one of the automatic processing list modes.
5. Specimen Sampling and Handling:
Manually presented whole blood K₃EDTA sample tubes must be mixed properly prior to specimen analysis. Sample tubes are placed into a tube adapter inserted
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on the sample rotor for closed vial or open vial single tube manual sample processing. A minimum of 30 minutes should elapse between collection of the blood sample and analysis on the Abacus 5 to ensure that the interaction of blood and anticoagulant has fully stabilized.
6. Calibration:
The Abacus 5 analyzer calibration process consists of running a commercial calibrator material multiple times. The calibration procedure ends when three or seven accepted calibration replicates are completed. The known calibrator parameter values and the average values of multiple runs are used to calculate calibration factors. Diatron recommends performing calibration at installation, when indicated by quality control, after major maintenance or service, and at periodic time intervals as directed by laboratory regulatory agencies.
7. Quality Control:
Diatron recommends the use of CBC-3K controls from R&D Systems to verify performance of the Abacus 5. Perform quality control at intervals established by the laboratory or as required by laboratory accreditation, licensing, or regulatory agencies.
8. Software:
FDA has reviewed applicant’s Hazard Analysis and Software Development processes for this line of product types:
Yes ☐ X or No ☐
F. Regulatory Information:
1. Regulation section:
21 CFR § 864.5220, Automated differential cell counter
2. Classification:
Class II
3. Product code:
GKZ, Counter, differential cell
4. Panel:
Hematology (81)
G. Intended Use:
1. Indication(s) for Use:
The Diatron Abacus 5 System is a quantitative multi-parameter automated hematology analyzer designed for in-vitro-diagnostic use in clinical laboratories for enumeration of the following parameters in K₃EDTA anti-coagulated venous whole blood samples: WBC, LYM%, LYM#, MON%, MON#, NEU%, NEU#, EOS%, EOS#, BAS%, BAS#, RBC, HGB, HCT, MCV, MCH, MCHC, RDWcv, RDWsd, PLT, and MPV. The Diatron Abacus 5 is indicated for use to identify patients with hematologic parameters within and outside of established reference ranges.
2. Special Conditions for Use Statement(s):
For Prescription Use Only
H. Substantial Equivalence Information:
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1. Predicate Device Name(s) and 510(k) numbers:
Abbott Cell-Dyn 3700 (k991605)
2. Comparison with Predicate Device:
| Similarities | | |
| --- | --- | --- |
| Item | Device | Predicate |
| | Abacus 5 | Cell-Dyn 3700 |
| Intended Use | The Diatron Abacus 5 System is a quantitative multi-parameter automated hematology analyzer designed for in-vitro-diagnostic use in clinical laboratories for enumeration of the following parameters in K3EDTA anti-coagulated venous whole blood samples: WBC, LYM%/#, MON%/#, NEU%/#, EOS%/#, BAS%/#, RBC, HGB, HCT, MCV, MCH, MCHC, RDW, PLT, MPV | The CELL-DYN 3700 System is a automated, multi-parameter hematology analyzer intended to classify the following formed elements of EDTA anticoagulated blood: WBC, NEU%/#, LYM%/#, MONO%/#, EOS%/#, BASO%/#, RBC, HGB, HCT, MCV, MCH, MCHC, RDW, PLT, MPV |
| Sampling Mechanisms | Manual sampling (open tube mode) Closed vial mode Autosampler cap piercing | Same |
| Sample ID | Manual and barcode | Same |
| Methodology | WBC Differential-Optical RBC, PLT- Impedance HGB - Photometric MCV- Derived | Same |
| Parameters | WBC, LYM%/#, MON%/#, NEU%/#, EOS%/#, BAS%/#, RBC, HGB, HCT, MCV, MCH, MCHC, RDWcv, RDWsd, PLT, MPV. | Same except RDWsd |
| QC data | Maintains QC files; generated Levey-Jennings charts | Same |
| Flags/Alerts | Provides dispersional data alerts, suspect parameter messages and suspect population flags to assist in data review. | Same |
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| Differences | | |
| --- | --- | --- |
| Item | Device | Predicate |
| | Abacus 5 | Cell-Dyn 3700 |
| Methodology | WBC- impedance | WBC- simultaneous optical and impedance |
| Parameter (reticulocytes) | Not performed | RETIC#/% , IRF |
| Throughput | 60 samples/hr. | 90 samples/hr. |
| Sample Aspiration Volume | Open Mode: 110μL Closed Vial Mode: 110μL Autosampling: 110μL | Open Mode: 130μL Closed Vial Mode: 240μL Autosampling: 355μL |
| Sample Type | K3EDTA anticoagulated venous whole blood | K3and K2EDTA anticoagulated venous whole blood |
| Reagents | Diatro Dil-5P Diluent, Diatro Lyse-5P, Diatro Diff-5P, Diatro Hypocleaner CC | Diluent, CN-Free Lyse Reagent, Enzymatic Cleaner, Detergent Sheath Reagent, Reticulocyte Reagent |
| Calibrator, and Controls | R&D Systems CBC-3K®, R&D Systems CBC CAL Plus | CELL-DYN 26 Plus Control, CELL-DYN HemCal Plus Calibrator |
| Data Storage | 100,000 record storage capacity | 10,000 record storage capacity |
# I. Special Control/Guidance Document Referenced (if applicable):
CLSI EP05-A2 Evaluation of Precision Performance of Quantitative Measurement Methods; Approved Guideline-Second Edition
CLSI EP06-A, Evaluation of the Linearity of Quantitative Measurement Procedures: A Statistical Approach; Approved Guideline
CLSI EP07-A2 Interference Testing in Clinical Chemistry; Second Edition
CLSI EP09-A2, Method Comparison and Bias Estimation Using Patient Samples; Approved Guideline-Second Edition
CLSI EP17-A Protocols for the Determination of Limits of Detection and Limits of Quantitation; 1st Edition
CLSI H26-A2 Validation, Verification, and Quality Assurance of Automated Hematology Analyzers; 2nd Edition
CLSI C28-A3 Defining, Establishing, and Verifying Reference Intervals in the Clinical Laboratory; 3rd Edition
CLSI H20-A2 Reference Leukocyte (WBC) Differential Count (Proportional) and Evaluation of Instrumental Methods; 2nd Edition
# J. Performance Characteristics:
# 1. Analytical Performance:
# a. Accuracy:
Each parameter of the Abacus 5 was compared to the predicate analyzer Cell-Dyn 3700. A total of 828 samples were analyzed at three (3) sites, two in Hungary and one in the US. Patient demographics include age range from $>1$
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month to $>80$ years of age. Approximately, one-third $(n = 281)$ samples were normal and two-thirds $(n = 563)$ had one or more abnormal conditions. In addition, $47.5\%$ were male and $52.5\%$ were female. The correlation analysis was performed using the first valid replicate of the Abacus 5 against the first valid replicate of the Cell-Dyn 3700. Accuracy summary data analysis is provided in the tables below:
Site 1- Regression Results
| (n = 295) | | | | Intercept 95% CI | | | Slope 95% CI | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Parameter | Range | (r) | Intercept | Lower | Upper | Slope | Lower | Upper |
| WBC | 0.30-52.4 | 0.9994 | 0.0221 | -0.0555 | 0.0996 | 0.9956 | 0.9835 | 1.0077 |
| NEU% | 8.4-91.6 | 0.9915 | 0.9888 | -0.1620 | 2.1396 | 1.0123 | 0.9943 | 1.0303 |
| LYM% | 3.9-88.0 | 0.9934 | -0.1398 | -0.5329 | 0.2532 | 0.9867 | 0.9718 | 1.0016 |
| MON% | 0.0-13.8 | 0.9218 | -0.5901 | -0.9555 | -0.2247 | 0.9708 | 0.9165 | 1.0251 |
| EOS% | 0.0-12.2 | 0.9662 | 0.0594 | -0.0617 | 0.1805 | 0.9852 | 0.9267 | 1.0437 |
| BAS% | 0.0-2.7 | 0.4960 | -0.0431 | -0.1245 | 0.0383 | 0.9385 | 0.8603 | 1.0168 |
| RBC | 1.59-7.38 | 0.9088 | 0.0331 | -0.0048 | 0.0710 | 0.9958 | 0.9866 | 1.0050 |
| HGB | 4.8-21.3 | 0.9983 | 0.0716 | -0.0313 | 0.1744 | 1.0023 | 0.9943 | 1.0104 |
| MCV | 61-113 | 0.9947 | 0.1371 | -0.9124 | 1.1867 | 0.9990 | 0.9877 | 1.0102 |
| RDWcv | 12.6-29.6 | 0.9828 | -0.1139 | -0.5485 | 0.3206 | 1.0055 | 0.9787 | 1.0323 |
| PLT | 19-1095 | 0.9971 | -0.8223 | -3.0071 | 1.3625 | 1.0143 | 1.0064 | 1.0223 |
| MPV | 3.0-12.7 | 0.9548 | -0.9445 | -1.3741 | -0.5149 | 1.1102 | 1.0566 | 1.1638 |
Site 2- Regression Results
| (n =295) | | | | Intercept 95% CI | | | Slope 95% CI | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Parameter | Range | (r) | Intercept | Lower | Upper | Slope | Lower | Upper |
| WBC | 0.11-87.0 | 0.9987 | 0.1430 | 0.0218 | 0.2642 | 0.9674 | 0.9519 | 0.9828 |
| NEU% | 0.40-93.7 | 0.9924 | 1.8630 | 0.5963 | 3.1296 | 0.9957 | 0.9755 | 1.0160 |
| LYM% | 2.3-86.1 | 0.9932 | 0.2191 | -0.2648 | 0.7030 | 0.9626 | 0.9438 | 0.9814 |
| MON% | 0.9-25.6 | 0.8531 | -0.6116 | -1.3303 | 0.1072 | 1.0110 | 0.9173 | 1.1047 |
| EOS% | 0.0-13.0 | 0.9349 | -0.0791 | -0.1898 | 0.0317 | 1.0152 | 0.9536 | 1.0767 |
| BAS% | 0.0-4.9 | 0.6136 | -0.5237 | -0.9532 | -0.0942 | 1.3386 | 0.8424 | 1.8349 |
| RBC | 1.49-7.99 | 0.9358 | 0.0366 | -0.0106 | 0.0837 | 0.9852 | 0.9740 | 0.9965 |
| HGB | 3.8-23.9 | 0.9966 | -0.2970 | -0.4611 | -0.1328 | 1.0374 | 1.0236 | 1.0511 |
| MCV | 61-106 | 0.9771 | -8.2639 | -10.7298 | -5.7980 | 1.0960 | 1.0676 | 1.1243 |
| RDWcv | 11.8-35.9 | 0.8645 | -2.7534 | -5.2632 | -0.2436 | 1.2337 | 1.0584 | 1.4090 |
| PLT | 7-1154 | 0.9741 | -6.9212 | -14.6317 | 0.7894 | 1.0674 | 1.0317 | 1.1032 |
| MPV | 3.0-14.3 | 0.7219 | -2.5373 | -5.0791 | 0.0046 | 1.2490 | 0.9550 | 1.5429 |
Site 3- Regression Results
| (n =238) | | | | Intercept 95% CI | | | Slope 95% CI | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Parameter | Range | (r) | Intercept | Lower | Upper | Slope | Lower | Upper |
| WBC | 0.85-88.6 | 0.9974 | -0.0731 | -0.6645 | 0.5182 | 0.9928 | 0.9224 | 1.0633 |
| NEU% | 2.0-96.4 | 0.9912 | 0.3192 | -1.4153 | 2.0538 | 1.0102 | 0.9844 | 1.0360 |
| LYM% | 1.7-96.7 | 0.9876 | 0.9019 | 0.1517 | 1.6522 | 0.9510 | 0.9197 | 0.9823 |
| MON% | 0.5-22.2 | 0.7952 | -0.4382 | -1.6670 | 0.7905 | 0.9997 | 0.8169 | 1.1825 |
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| (n =238) | | | | Intercept 95% CI | | | Slope 95% CI | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Parameter | Range | (r) | Intercept | Lower | Upper | Slope | Lower | Upper |
| EOS% | 0.0-10.7 | 0.9200 | -0.0729 | -0.2168 | 0.0711 | 0.9730 | 0.8682 | 1.0778 |
| BAS% | 0.0-7.6 | 0.5366 | -0.4982 | -1.1825 | 0.1860 | 1.5717 | 0.5926 | 2.5508 |
| RBC | 1.84-7.39 | 0.9355 | 0.0017 | -0.0549 | 0.0584 | 0.9928 | 0.9793 | 1.0063 |
| HGB | 3.0-22.5 | 0.9972 | -0.2427 | -0.3888 | -0.0966 | 1.0273 | 1.0148 | 1.0397 |
| MCV | 66-109 | 0.9846 | 0.8628 | -1.2881 | 3.0136 | 0.9895 | 0.9649 | 1.0141 |
| RDWcv | 12.5-23.9 | 0.9189 | 0.4077 | -1.3426 | 2.1581 | 0.9914 | 0.8753 | 1.1075 |
| PLT | 9-916 | 0.9814 | 3.0983 | -4.1731 | 10.3696 | 1.0285 | 0.9941 | 1.0629 |
| MPV | 3.1-16.6 | 0.6783 | -0.8755 | -2.9770 | 1.2261 | 1.0587 | 0.8673 | 1.2501 |
The ability of the Abacus 5 to flag abnormal samples was evaluated per CLSI H20-A2 in comparison with the reference method (Manual Microscopy). A total of 210 samples were analyzed on the Abacus 5 in combination with manual differential reviews. The WBC distributional flagging statistical analysis data are summarized in the tables below:
Distributional Results: 2 x 2 Table and Figures of Merit
| | Abacus 5 | | |
| --- | --- | --- | --- |
| | | Positive (Abnormal) | Negative (Normal) |
| Manual Microscopy | Positive (Abnormal) | 63 | 7 |
| | Negative (Normal) | 23 | 117 |
| Agreement | 85.7% |
| --- | --- |
| Sensitivity | 90.0% |
| Specificity | 83.6% |
b. Precision/Reproducibility:
The Abacus 5 repeatability evaluation was conducted using 22 human blood samples and three levels of control. The samples were selectively chosen to span the analytical measuring range and to be close to clinical decision points on two Abacus 5 instruments. A minimum of 15 and a maximum of 21 replicates were run for each sample.
The following tables represent reproducibility and intermediate precision using commercial controls. Two replicates of low, normal, and high control samples were run twice per day at three different sites for 20 working days. The data from three instruments was analyzed to determine the overall mean and precision for between-site, between-day, within-day, and within-device.
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| Low Control | WBC | RBC | HGB | MCV | RDWcv | PLT | MPV |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Mean (n = 240) | 3.1 | 2.19 | 5.5 | 83.0 | 17.4 | 95.2 | 8.4 |
| Between-Site SD | 0.043 | 0.028 | 0.005 | 0.911 | 0.690 | 1.573 | 0.762 |
| Between-Day SD | 0.020 | 0.000 | 0.052 | 0.295 | 0.126 | 3.714 | 0.229 |
| Within-Day SD | 0.020 | 0.024 | 0.000 | 0.383 | 0.000 | 3.011 | 0.250 |
| Within-Device SD | 0.064 | 0.033 | 0.101 | 0.641 | 0.305 | 6.698 | 0.569 |
| Within-Device CV | 2.06% | 1.49% | 1.83% | 0.77% | 1.75% | 7.0% | 6.79% |
| Low Control | NEU% | LYM% | MON% | EOS% | BAS% |
| --- | --- | --- | --- | --- | --- |
| Mean (n = 240) | 48.4 | 44.8 | 5.2 | 1.6 | 0.121 |
| Between-Site SD | 1.319 | 0.375 | 1.497 | 0.202 | 0.020 |
| Between-Day SD | 0.521 | 0.107 | 0.417 | 0.085 | 0.009 |
| Within-Day SD | 0.731 | 0.000 | 0.635 | 0.130 | 0.019 |
| Within-Device SD | 1.466 | 1.073 | 1.003 | 0.295 | 0.038 |
| Normal Control | WBC | RBC | HGB | MCV | RDWcv | PLT | MPV |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Mean (n = 240) | 7.9 | 4.63 | 13.0 | 96.4 | 15.3 | 269 | 8.9 |
| Between-Site SD | 0.071 | 0.051 | 0.102 | 1.331 | 0.611 | 4.654 | 0.429 |
| Between-Day SD | 0.059 | 0.031 | 0.067 | 0.351 | 0.076 | 7.454 | 0.385 |
| Within-Day SD | 0.045 | 0.022 | 0.000 | 0.638 | 0.082 | 6.541 | 0.172 |
| Within-Device SD | 0.128 | 0.061 | 0.169 | 0.837 | 0.243 | 12.450 | 0.540 |
| Within-Device CV | 1.62% | 1.32% | 1.30% | 0.87% | 1.59% | 4.6% | 6.05% |
| Normal Control | NEU% | LYM% | MON% | EOS% | BAS% |
| --- | --- | --- | --- | --- | --- |
| Mean (n = 240) | 65.2 | 27.3 | 2.9 | 4.4 | 0.123 |
| Between-Site SD | 0.768 | 0.385 | 0.773 | 0.368 | 0.027 |
| Between-Day SD | 0.353 | 0.172 | 0.347 | 0.050 | 0.019 |
| Within-Day SD | 0.501 | 0.000 | 0.327 | 0.191 | 0.014 |
| Within-Device SD | 0.897 | 0.647 | 0.565 | 0.362 | 0.036 |
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| High Control | WBC | RBC | HGB | MCV | RDWcv | PLT | MPV |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Mean (n = 240) | 24.1 | 5.16 | 16.4 | 101.7 | 15.1 | 501.5 | 8.9 |
| Between-Site SD | 0.325 | 0.058 | 0.120 | 1.183 | 0.389 | 1.257 | 0.345 |
| Between-Day SD | 0.166 | 0.029 | 0.090 | 0.365 | 0.030 | 5.458 | 0.104 |
| Within-Day SD | 0.177 | 0.025 | 0.068 | 0.475 | 0.122 | 5.042 | 0.117 |
| Within-Device SD | 0.354 | 0.060 | 0.168 | 0.806 | 0.262 | 11.783 | 0.258 |
| Within-Device CV | 1.47% | 1.16% | 1.02% | 0.79% | 1.74% | 2.4% | 2.91% |
| High Control | NEU% | LYM% | MON% | EOS% | BAS% |
| --- | --- | --- | --- | --- | --- |
| Mean (n = 240) | 69.9 | 23.4 | 3.7 | 2.7 | 0.177 |
| Between-Site SD | 1.394 | 0.557 | 1.453 | 0.450 | 0.041 |
| Between-Day SD | 0.276 | 0.134 | 0.213 | 0.086 | 0.000 |
| Within-Day SD | 0.459 | 0.167 | 0.408 | 0.102 | 0.016 |
| Within-Device SD | 0.816 | 0.403 | 0.739 | 0.209 | 0.029 |
# c. Linearity:
The analytical measuring range (AMR) was established by analyzing dilutions made from manipulated whole human blood or from commercial linearity kit material. In order to demonstrate that each parameter is within the claimed performance, a minimum of 9 proportional dilutions spanning the reportable range were run in triplicate on two Abacus 5 analyzers. The high concentration sample is diluted with low concentration sample to create seven intermediate proportional dilutions. All of the eight linearity runs produced coefficients of determination $(\mathrm{r}^2) > 0.95$ for each measurand. The following parameters are linear within the stated AMR:
| Measurand | Units | AMR |
| --- | --- | --- |
| WBC | 103/μL | 0.21 – 100.0 |
| HGB | g/dL | 1.1 – 22.2 |
| RBC | 106/μL | 0.36 – 7.19 |
| PLT | 103/μL | 16 – 1000 |
# d. Carryover:
Carryover was determined using three Abacus 5 analyzers by running whole blood specimens with high target values (HTV) of WBC, RBC, HGB, and PLT. Each specimen was run in triplicate followed by three aspirations of whole blood specimens with low target values (LTV). Carryover % was
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calculated by using the following equation: % Carryover = (LTV1 - LTV3) / (HTV1 - LTV3) x 100. The maximum carryover for WBC, RBC, HGB, and PLT are 1.00%, 0.50%, 0.80%, and 1.00% respectively. The upper 95% confidence intervals (CI) of the carryover point estimates for each parameter tested are shown in the following table:
| Abacus 5 | Upper 95% CI | | | |
| --- | --- | --- | --- | --- |
| | WBC | RBC | HGB | PLT |
| Analyzer #1 | 0.043% | 0.10% | 0.46% | 0.30% |
| Analyzer #2 | 0.017% | 0.04% | 0.23% | 0.63% |
| Analyzer #3 | 0.017% | 0.07% | 0.68% | 0.51% |
# e. Interfering Substances:
Test samples are created by adding interfering substances to normal samples such as bilirubin and lipids based on CLSI EP07-A2. Other evaluations were made by finding naturally occurring human blood samples with potential interferences such as high WBC, platelet abnormalities and NRBCs. A bias of $5\%$ or more was considered clinically significant in the directly measured parameters. Two Abacus 5 instruments were used in the evaluation of interfering substances. Measurands were not impacted by bilirubin up to 30 mg/dL. The following parameters were affected by interference from NRBC, PLT clumps/large PLT, increased WBC, and lipids (see table below):
| Parameter | Interference |
| --- | --- |
| WBC | >5 NRBCs/100 WBCs, PLT clumps/large PLTs |
| RBC | WBC Count >75.0 x103/μL |
| MCV | WBC Count >75.0 x103/μL |
| PLT | PLT clumps/large PLTs |
| Hemoglobin | WBC count >75.0 x103/μL, Lipids >280 mg/dL |
| Differential | >5 NRBCs/100 WBCs, PLT clumps/large PLTs |
# f. Background Counts:
Daily Start-up background counts were performed on the Abacus 5 and were verified by each site against the specifications. Start-up background specifications were achieved before data collection. The Abacus 5 background specifications are as follows:
| Measurand | Background Concentration Limits |
| --- | --- |
| WBC | ≤ 0.20 |
| RBC | ≤ 0.05 |
| HGB | ≤ 1.0 |
| PLT | ≤15 |
2. Other Supportive Instrument Performance Data Not Covered Above: Studies were conducted to support claims and attributes for whole blood sampling. They were designed to evaluate the following:
a. Sample stability:
{9}
The parameters selected for this evaluation are the directly measured parameters (WBC, RBC, HGB, PLT), the optically measured parameters (NEU%, LYM%, MON%, EOS%, BAS%) and the derived parameters (MCV, RDWcv, MPV). A total of 10 normal and six abnormal $\mathrm{K}_3$ EDTA anticoagulated human whole blood samples were analyzed on two Abacus 5 instruments at 0.5 hours after venipuncture and at various time intervals thereafter. The averages of the parameters at each time point were compared to the baseline averages. The results support sample stability at room temperature $(20 - 23^{\circ}\mathrm{C})$ of 7 hours.
# b. Comparison of open and closed vial sampling:
A minimum of $31\mathrm{K}_3$ EDTA anticoagulated human blood samples spanning the reportable range were used in the study. The specimens were run in closed vial cap pierce mode (selected as the reference as per CLSI H26-A2) and compared to the open vial mode and to the Autosampler automatic processing mode. The testing demonstrated that the Abacus 5 will process specimens using open and closed mode sampling in the same manner.
# c. Reference ranges:
Evaluation of reference ranges for the Abacus 5 instrument was conducted using a data set of 240 normal human whole blood samples collected at the US site. Of these 240 samples, 120 were from female patients and 120 were from male patients. The manufacturer recommends each laboratory establish its own reference range.
| Parameter | Units | Lower limit | Upper limit |
| --- | --- | --- | --- |
| WBC | 103/μL | 4.50 | 10.37 |
| LYM | % | 14.76 | 45.40 |
| MON | % | 2.91 | 12.1 |
| NEU | % | 42.90 | 78.10 |
| EOS | % | 0.10 | 7.00 |
| BAS | % | 0.15 | 1.60 |
| LYM | 103/μL | 1.08 | 3.17 |
| MON | 103/μL | 0.20 | 0.91 |
| NEU | 103/μL | 2.43 | 7.42 |
| EOS | 103/μL | 0.01 | 0.53 |
| BAS | 103/μL | 0.01 | 0.13 |
| RBC | 106/μL | F-3.86 M-3.91 | F-5.18 M-5.62 |
| HGB | g/dL | F-11.8 M-12.0 | F-15.1 M-16.9 |
| HCT | % | F-35.5 M-36.2 | F-46.5 M-48.0 |
| MCV | fl | 81.6 | 97.7 |
| MCH | pg | 26.8 | 33.8 |
| MCHC | g/dL | 31.1 | 35.5 |
| RDWcv | % | 12.8 | 16.8 |
{10}
| Parameter | Units | Lower limit | Upper limit |
| --- | --- | --- | --- |
| PLT | 103/μL | 151 | 361 |
| MPV | fL | 6.1 | 14.1 |
# d. Determination of lower limits of detection and quantitation:
The lower limit of detection (LLoD) and the lower limit of quantitation (LLoQ) of WBC and PLT were quantified as per CLSI H26-A2 section 5.8. To determine LLoD, 12 blank runs were collected daily over five days (total 60 blank runs) on two instruments using alternating operators. The values of WBC and PLT for these blank runs are analyzed to determine the LLoD. Once the LLoD is calculated, five low level specimens are run over a period of five days. One specimen was run each day using alternating operators. Twelve replicates per specimen were collected for a total of 60 replicates. The CVs of each dilution of WBC and PLT were analyzed to determine the LLoQ of each.
| Item | WBC | PLT |
| --- | --- | --- |
| LLoD | 0.0748 | 5.6138 |
| LLoQ | 0.18 | 15.07 |
# K. Proposed Labeling:
The labeling is sufficient and it satisfies the requirements of 21 CFR Part 809.10.
# L. Conclusion:
The submitted information in this premarket notification is complete and supports a substantial equivalence decision.
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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.