SYSTEM TO CONTROL PRE-ANALYTICAL VARIABLES IN PLATELET COUNT ESTIMATION IN HEMATOLOGY LABORATORIES

Abstract

The present invention provides a system to control pre-analytical variables in platelet count estimation in hematology laboratories. The system reduces pre-analytical errors in platelet count estimation by establishing standardized protocols for each step of sample collection, handling, and processing, ensuring that platelet samples are consistently managed across the laboratory. The algorithm addresses this by mandating specific guidelines for sample collection to prevent under-filling or overfilling of tubes, thorough mixing to prevent platelet aggregation, and timely processing of samples to maintain platelet integrity. Proper labeling and tracking are also emphasized, reducing the risk of sample misidentification or mishandling. Furthermore, the algorithm monitors conditions during sample transport and storage, ensuring that temperature and handling standards are met to avoid platelet degradation during transit.

Specification

Description:FIELD OF THE INVENTION
[001] The present invention relates to the field of medical science, and more particularly, the present invention relates to the system to control pre-analytical variables in platelet count estimation in hematology laboratories.
BACKGROUND FOR THE INVENTION:
[002] The following discussion of the background to the invention is intended to facilitate an understanding of the present invention. However, it should be appreciated that the discussion is not an acknowledgment or admission that any of the material referred to was published, known, or part of the common general knowledge in any jurisdiction as of the priority date of the application. The details provided herein the background if belongs to any publication is taken only as a reference for describing the problems, in general terminologies or principles or both of science and technology in the associated prior art.
[003] The invention addresses a critical issue in hematology laboratories: pre-analytical errors (PAEs), which are mistakes occurring before lab analysis, particularly in sample collection, handling, and processing. PAEs are a major challenge as they can significantly impact the accuracy of test results, leading to misdiagnosis or inappropriate treatment for patients. Common issues include sample mislabeling, improper tube filling, delayed processing, and inadequate mixing-all of which can alter sample integrity, especially for delicate measurements like platelet counts, where platelets may clump or degrade if handled improperly. While some laboratories attempt to mitigate these errors through manual quality checks or ad hoc staff training, these solutions are often inconsistent and lack systematic control.
[004] Applicant has conducted a worldwide patent application prior art search to elucidate novel and inventive features of the present invention:
- US Patent 5,998,171: "Method and Apparatus for Quality Control in Automated Hematology Analyzers". This patent addresses methods to improve quality control in hematology analyzers by incorporating pre-analytical checks and delta-check systems for reliable sample processing. It includes mechanisms for detecting discrepancies in white blood cell (WBC) and platelet counts and flagging potential errors. US Patent 6,475,188 - "Automated Hematology Analyzer with Cell Count Error Detection and Correction". This patent describes a system that monitors cell count errors caused by platelet clumping and large platelets affecting WBC counts, flagging results for manual review when abnormalities are detected. It provides an automated means to reduce errors specific to platelet counts.
- US Patent 7,786,007: "Quality Assurance System for Automated Hematology Analyzers". This patent focuses on a quality assurance system integrated into hematology analyzers to detect and mitigate pre-analytical and analytical errors. It discusses delta check methods for parameters like MCV and MCHC and a flagging mechanism for platelet abnormalities.
- EP Patent 2154982 A1: "Methods for Flagging Abnormal Samples in Hematology Analysis". This European patent discusses flagging algorithms designed for hematology analyzers to detect abnormalities in platelet size and count, such as giant platelets and platelet clumps, which can interfere with WBC and RBC counting channels. The system prompts manual review in response to flagged anomalies.
- WO Patent 2009094173 A2: "Method and System for Detecting Platelet Clumps in Hematology Analyzers". This World Intellectual Property Organization (WIPO) patent covers methods for detecting platelet clumping in automated systems. It includes algorithms for flagging abnormal platelet size distributions and assessing sample integrity, with special reference to impedance-based counting.
[005] In light of the foregoing, there is a need for the system to control pre-analytical variables in platelet count estimation in hematology laboratories that overcomes problems prevalent in the prior art. This invention introduces a comprehensive algorithm that standardizes every stage of the pre-analytical phase, providing a structured approach to control and reduce PAEs. The algorithm enforces proper collection techniques, handling protocols, and labeling procedures, minimizing risks like platelet clumping or sample degradation. Additionally, it incorporates quality indicators for continuous monitoring; allowing labs to track error rates and identify patterns that can be addressed in real time. By automating these controls and ensuring consistent adherence to best practices, this invention systematically reduces pre-analytical errors, improves test accuracy, and enhances patient care quality more effectively than manual or fragmented approaches.
OBJECTS OF THE INVENTION:
[006] Some of the objects of the present disclosure, which at least one embodiment herein satisfies, are as follows.
[007] The principal object of the present invention is to overcome the disadvantages of the prior art by providing a system to control pre-analytical variables in platelet count estimation in hematology laboratories.
[008] Another object of the present invention is to provide a system to control pre-analytical variables in platelet count estimation in hematology laboratories that introduces a comprehensive algorithm that standardizes every stage of the pre-analytical phase, providing a structured approach to control and reduce PAEs.
[009] Another object of the present invention is to provide a system to control pre-analytical variables in platelet count estimation in hematology laboratories that enforces proper collection techniques, handling protocols, and labeling procedures, minimizing risks like platelet clumping or sample degradation.
[010] Another object of the present invention is to provide a system to control pre-analytical variables in platelet count estimation in hematology laboratories that incorporates quality indicators for continuous monitoring; allowing labs to track error rates and identify patterns that can be addressed in real time. By automating these controls and ensuring consistent adherence to best practices, this invention systematically reduces pre-analytical errors, improves test accuracy, and enhances patient care quality more effectively than manual or fragmented approaches.
[011] Other objects and advantages of the present disclosure will be more apparent from the following description, which is not intended to limit the scope of the present disclosure.
SUMMARY OF THE INVENTION:
[012] The present invention provides a system to control pre-analytical variables in platelet count estimation in hematology laboratories.
[013] The system reduces pre-analytical errors in platelet count estimation by establishing standardized protocols for each step of sample collection, handling, and processing, ensuring that platelet samples are consistently managed across the laboratory. Errors in platelet counts can stem from issues like incorrect tube filling, delays in processing, or inadequate mixing, all of which can cause platelets to clump or degrade, leading to unreliable results. The algorithm addresses this by mandating specific guidelines for sample collection to prevent under-filling or overfilling of tubes, thorough mixing to prevent platelet aggregation, and timely processing of samples to maintain platelet integrity. Proper labeling and tracking are also emphasized, reducing the risk of sample misidentification or mishandling. Furthermore, the algorithm monitors conditions during sample transport and storage, ensuring that temperature and handling standards are met to avoid platelet degradation during transit. Training for lab staff is a crucial component, as it raises awareness about the delicate nature of platelets and teaches best practices to avoid disruption of counts. Lastly, quality indicators allow the lab to monitor error rates, identify recurring issues, and provide feedback to continually adjust and refine processes. Together, these measures help produce accurate platelet counts, improving data reliability for patient diagnoses and treatments.
[014] The novelty of this invention lies in its structured, automated approach to minimizing errors before laboratory testing even begins. Unlike traditional methods that rely heavily on manual checks or inconsistent procedures, this invention introduces a step-by-step algorithm that standardizes every part of the pre-analytical phase-from sample collection and handling to transport and storage. For example, a common issue in blood tests is that if a sample isn't mixed well, platelets can clump together, leading to a falsely low platelet count. With this invention, clear guidelines and protocols are enforced, ensuring that samples are always mixed correctly and handled promptly. Another key feature is its use of quality indicators to continuously monitor error patterns and provide immediate feedback, allowing for real-time adjustments that reduce errors over time.

BRIEF DESCRIPTION OF DRAWINGS:
[015] Reference will be made to embodiments of the invention, examples of which may be illustrated in accompanying figures. These figures are intended to be illustrative, not limiting. Although the invention is generally described in the context of these embodiments, it should be understood that it is not intended to limit the scope of the invention to these particular embodiments.
[016] No Figure.
DETAILED DESCRIPTION OF DRAWINGS:
[017] While the present invention is described herein by way of example using embodiments and illustrative drawings, those skilled in the art will recognize that the invention is not limited to the embodiments of drawing or drawings described and are not intended to represent the scale of the various components. Further, some components that may form a part of the invention may not be illustrated in certain figures, for ease of illustration, and such omissions do not limit the embodiments outlined in any way. It should be understood that the drawings and the detailed description thereto are not intended to limit the invention to the particular form disclosed, but on the contrary, the invention is to cover all modifications, equivalents, and alternatives falling within the scope of the present invention as defined by the appended claim.
[018] As used throughout this description, the word "may" is used in a permissive sense (i.e. meaning having the potential to), rather than the mandatory sense, (i.e. meaning must). Further, the words "a" or "an" mean "at least one" and the word "plurality" means "one or more" unless otherwise mentioned. Furthermore, the terminology and phraseology used herein are solely used for descriptive purposes and should not be construed as limiting in scope. Language such as "including," "comprising," "having," "containing," or "involving," and variations thereof, is intended to be broad and encompass the subject matter listed thereafter, equivalents, and additional subject matter not recited, and is not intended to exclude other additives, components, integers, or steps. Likewise, the term "comprising" is considered synonymous with the terms "including" or "containing" for applicable legal purposes. Any discussion of documents, acts, materials, devices, articles, and the like are included in the specification solely for the purpose of providing a context for the present invention. It is not suggested or represented that any or all these matters form part of the prior art base or were common general knowledge in the field relevant to the present invention.
[019] In this disclosure, whenever a composition or an element or a group of elements is preceded with the transitional phrase "comprising", it is understood that we also contemplate the same composition, element, or group of elements with transitional phrases "consisting of", "consisting", "selected from the group of consisting of, "including", or "is" preceding the recitation of the composition, element or group of elements and vice versa.
[020] The present invention is described hereinafter by various embodiments with reference to the accompanying drawing, wherein reference numerals used in the accompanying drawing correspond to the like elements throughout the description. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiment set forth herein. Rather, the embodiment is provided so that this disclosure will be thorough and complete and will fully convey the scope of the invention to those skilled in the art. In the following detailed description, numeric values and ranges are provided for various aspects of the implementations described. These values and ranges are to be treated as examples only and are not intended to limit the scope of the claims. In addition, several materials are identified as suitable for various facets of the implementations. These materials are to be treated as exemplary and are not intended to limit the scope of the invention.
[021] The present invention provides a system to control pre-analytical variables in platelet count estimation in hematology laboratories.
[022] The system reduces pre-analytical errors in platelet count estimation by establishing standardized protocols for each step of sample collection, handling, and processing, ensuring that platelet samples are consistently managed across the laboratory. Errors in platelet counts can stem from issues like incorrect tube filling, delays in processing, or inadequate mixing, all of which can cause platelets to clump or degrade, leading to unreliable results. The algorithm addresses this by mandating specific guidelines for sample collection to prevent under-filling or overfilling of tubes, thorough mixing to prevent platelet aggregation, and timely processing of samples to maintain platelet integrity. Proper labeling and tracking are also emphasized, reducing the risk of sample misidentification or mishandling. Furthermore, the algorithm monitors conditions during sample transport and storage, ensuring that temperature and handling standards are met to avoid platelet degradation during transit. Training for lab staff is a crucial component, as it raises awareness about the delicate nature of platelets and teaches best practices to avoid disruption of counts. Lastly, quality indicators allow the lab to monitor error rates, identify recurring issues, and provide feedback to continually adjust and refine processes. Together, these measures help produce accurate platelet counts, improving data reliability for patient diagnoses and treatments.
[023] The novelty of this invention lies in its structured, automated approach to minimizing errors before laboratory testing even begins. Unlike traditional methods that rely heavily on manual checks or inconsistent procedures, this invention introduces a step-by-step algorithm that standardizes every part of the pre-analytical phase-from sample collection and handling to transport and storage. For example, a common issue in blood tests is that if a sample isn't mixed well, platelets can clump together, leading to a falsely low platelet count. With this invention, clear guidelines and protocols are enforced, ensuring that samples are always mixed correctly and handled promptly. Another key feature is its use of quality indicators to continuously monitor error patterns and provide immediate feedback, allowing for real-time adjustments that reduce errors over time.
[024] This algorithm can be applied in any hematology laboratory, regardless of the analyzer type-a three-part, five-part, or seven-part analyzer using the impedance method (Wallace Coulter method) for platelet estimation. It provides a systematic approach for technologists to follow upon receiving samples in the lab, enabling accurate action in the absence of a pathologist. This is especially valuable in high-volume tertiary care settings, where thousands of samples are processed daily, and the risk of errors in reporting complete blood counts is elevated. Among these parameters, platelet count is particularly vulnerable to pre-analytical errors.
[025] The algorithm starts by verifying that each sample is properly labeled and correctly placed in the appropriate tube, rejecting any underfilled or overfilled samples. The technologist should also inspect for visible clots, as errors often begin at the sample collection stage, potentially due to incorrect collection methods or sample mismatches. Such discrepancies can be detected by comparing parameters like Mean Cell Volume (MCV), Mean Cell Hemoglobin (MCH), and Mean Cell Hemoglobin Concentration (MCHC) to previous counts, if available, allowing the technologist to identify mismatches without needing pathologist intervention.
[026] According to the College of American Pathologists (CAP) guidelines, delta checks are recommended to identify specimen mix-ups, focusing on parameters with minimal short-term biological variability. MCV and MCHC are the most stable in a 24-hour period, with MCV, for example, showing only a 0.5% diurnal variation. Even during acute blood loss, MCV and MCHC typically remain unchanged over the first 24 hours, making them reliable parameters for delta checks.
[027] In the impedance method, the WBC histogram ranges from 35 fL to 500 fL, assuming that particles within this range are WBCs. However, large platelets or platelet clumps can sometimes fall within this range, causing WBC interference. This may prompt the pathologist to review and adjust the platelet count accordingly. Similarly, if the Mean Platelet Volume (MPV) exceeds 10.5 fL, it indicates the potential presence of large platelets that the analyzer may have missed which could lead to a falsely low platelet count and requires a manual count.
[028] The platelet histogram, covering 2 fL to 30 fL, is assumed to reflect only platelets. However, fragmented red blood cells (RBCs) can sometimes be counted as platelets, leading to an artificially elevated count. Similarly, if large platelets are counted in the RBC or WBC channels, the platelet count may be underestimated. These instances necessitate manual verification.
[029] By addressing all these points, this algorithm helps ensure accurate platelet reporting, supporting high-quality results in the hematology lab.
- Advantages: The algorithm described above offers a more comprehensive and quality-focused approach than simply relying on the DxH 800 analyzer's automated platelet count and flagging system. While the DxH 800 uses electrical resistance to measure cells and flags abnormalities based on size (counting particles between 2-20 fL as platelets and flagging irregularities like giant platelets or clumps), it has limitations. Here's how the algorithm improves on this system:
- Enhanced Pre-Analytical Quality Control: The algorithm emphasizes meticulous pre-analytical checks (proper labeling, tube fill level, clot checks) that reduce the likelihood of errors before the sample even reaches the analyzer. By filtering out mislabeled, underfilled, or overfilled samples and visually inspecting for clots, the algorithm minimizes sources of error that the DxH 800 would otherwise encounter during processing.
- Improved Error Detection via Delta Checks: The algorithm employs delta checks for Mean Cell Volume (MCV), Mean Cell Hemoglobin (MCH), and Mean Cell Hemoglobin Concentration (MCHC) to catch mismatches between current and previous results. Since MCV and MCHC are stable over short periods, unusual variations are likely due to sample mislabeling or mix-ups rather than biological variability, a detail the analyzer alone cannot detect.
- Manual Review of Potentially Erroneous Counts: The DxH 800's flagging system prompts a review only when platelets fall outside the 2-20 fL range or if there's a noticeable platelet size irregularity, which could miss cases of large platelets or platelet clumps affecting WBC or RBC counts. The algorithm, on the other hand, provides a systematic approach for reviewing flagged samples, including checking Mean Platelet Volume (MPV) and manually verifying the platelet count if MPV is above 10.5 fL. This step helps identify cases where large platelets may be miscounted as WBCs or RBCs, reducing the chance of underreporting platelet counts.
- Cross-Checking Histograms for Enhanced Accuracy: By integrating WBC and platelet histogram checks, the algorithm detects anomalies such as WBC interference caused by large platelets or fragmented RBCs being misclassified as platelets. This added layer of cross-verification is absent in the analyzer's default flagging protocol, which only assesses cell types individually rather than in relation to the entire blood profile.
- Greater Assurance in High-Volume Labs: In high-throughput laboratories where thousands of samples are processed daily, a structured algorithm reduces dependence on automated flags alone. It provides clear, sequential steps for technologists to catch errors and inconsistencies early, maintaining quality and accuracy despite the heavy workload.
- In summary, the algorithm provides a more robust and error-proof system, addressing potential pre-analytical, analytical, and post-analytical issues that the DxH 800 might miss. It minimizes false counts and increases the reliability of platelet reporting by integrating checks that account for a wider range of potential variances in sample quality and processing.
[030] The disclosure has been described with reference to the accompanying embodiments herein and the various features and advantageous details thereof are explained with reference to the non-limiting embodiments in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein.
[031] The foregoing description of the specific embodiments so fully revealed the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the scope of the embodiments as described herein.
, Claims:1) A system for controlling pre-analytical variables in platelet count estimation in hematology laboratories; the system comprising:
- an electronic device comprising a processor; and
- a set of standardized protocols for sample collection, handling, and processing, configured to reduce errors arising from incorrect tube filling, delayed processing, or inadequate mixing of samples.
2) The system as claimed in claim 1, wherein the standardized protocols include specific guidelines for preventing under-filling or overfilling of tubes, enabling thorough mixing of blood samples to prevent platelet aggregation and clumping, thus maintaining platelet integrity.
3) The system as claimed in claim 1, wherein the system further comprising an automated algorithm that mandates labeling and tracking protocols, minimizing the risk of sample misidentification and mishandling, ensuring accurate processing and platelet count estimation.
4) The system as claimed in claim 1, wherein the system includes monitoring conditions during sample transport and storage to maintain temperature and handling standards, thereby preserving platelet stability and preventing degradation during transit.
5) The system as claimed in claim 1, wherein the system incorporates delta checks based on stable hematological parameters, including Mean Cell Volume (MCV), Mean Cell Hemoglobin (MCH), and Mean Cell Hemoglobin Concentration (MCHC), enabling detection of sample mismatches without requiring a pathologist's intervention.
6) The system as claimed in claim 1, wherein a manual review protocol is initiated for flagged samples, specifically verifying Mean Platelet Volume (MPV) when it exceeds 10.5 fL to identify large platelets, clumps, or potential interferences in platelet counts, enhancing overall accuracy.
7) The system as claimed in claim 1, wherein the system further comprising quality indicators to continuously monitor error rates and provide feedback, thereby enabling real-time adjustments to reduce errors and improve platelet count reliability in high-throughput laboratory settings.
8) A method for detecting and correcting platelet count inaccuracies in hematology analyzers, comprising steps of:
- verifying sample integrity, conducting pre-analytical quality checks;
- detecting abnormal platelet sizes; and
- prompting manual review if discrepancies exceed predetermined thresholds.
9) A method for quality control in hematology sample analysis utilizing delta checks for Mean Cell Volume (MCV) and Mean Cell Hemoglobin Concentration (MCHC) to identify sample mismatches, the method comprising:
- comparing current MCV and MCHC with previous results; and
- flagging samples with deviations beyond a predefined limit for manual review.

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