{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T14:46:41Z","timestamp":1786978001742,"version":"build-2736575974"},"reference-count":28,"publisher":"Wiley","issue":"19","license":[{"start":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T00:00:00Z","timestamp":1757462400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100020872","name":"Tainan Municipal An-Nan Hospital","doi-asserted-by":"publisher","award":["ANHRF112\u201034"],"award-info":[{"award-number":["ANHRF112\u201034"]}],"id":[{"id":"10.13039\/501100020872","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Clinical Laboratory Analysis"],"published-print":{"date-parts":[[2025,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Improving efficiency and reducing turnaround time are crucial in clinical laboratories. While automated analyzers such as the Beckman Coulter DxH 900 streamline workflow, subtle abnormalities like blasts and immature granulocytes (IGs) may be missed, especially in the absence of WBC\u2010related suspect messages. This study evaluated whether integrating cell population data (CPD) with instrument messages could enhance detection accuracy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A total of 587 blood samples were analyzed and classified with (Group A) or without (Group N) WBC\u2010related suspect messages. Manual slide review (MSR) and digital morphology (DM) served as reference standards. CPD parameters were evaluated using receiver operating characteristic (ROC) analysis and Youden's index to establish optimal detection rules.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Among the 587 samples, 55.3% were in Group A and 44.7% in Group N, with Group A showing significantly lower red blood cell, hemoglobin, and platelet counts (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001). The DxH 900 flagged 37.7% and 55.4% of samples with blast\u2010 and IG\u2010related messages, respectively. However, it failed to detect blasts in 20.6% of cases confirmed by MSR and 21.3% by DM, and missed IGs in 16.2% of MSR\u2010confirmed and 18.7% of DM\u2010confirmed positive samples. CPD parameters (e.g., SD_V_NE, MN_V_NE) identified additional true positives, with area under the curve (AUC) values &gt;\u20090.9. Integrating CPD rules with WBC\u2010related suspect messages improved sensitivity\/specificity to 91.9%\/99.0% for blasts and 91.5%\/96.7% for IGs, using MSR as the reference standard.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Integrating CPD parameters with WBC\u2010related suspect messages provides a sensitive, automated secondary screening strategy that reduces false negatives and enhances hematologic diagnostics.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jcla.70099","type":"journal-article","created":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T12:33:46Z","timestamp":1757507626000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Integrating Cell Population Data With Hematology Analyzer Messages for Improved Detection of Immature White Blood Cells and Laboratory Efficiency"],"prefix":"10.1002","volume":"39","author":[{"given":"Lin\u2010Chen","family":"Hsu","sequence":"first","affiliation":[{"name":"Department of Laboratory Medicine An Nan Hospital, China Medical University  Tainan Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tsung\u2010Han","family":"Tsai","sequence":"additional","affiliation":[{"name":"Department of Laboratory Medicine An Nan Hospital, China Medical University  Tainan Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu\u2010Hua","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Laboratory Medicine An Nan Hospital, China Medical University  Tainan Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kai\u2010Yun","family":"Lu","sequence":"additional","affiliation":[{"name":"Scientific Division MedTri Company Limited  Taipei Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9048-6363","authenticated-orcid":false,"given":"Wen\u2010Chun","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Nursing National Tainan Junior College of Nursing  Tainan Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,9,10]]},"reference":[{"key":"e_1_2_12_2_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMra043442"},{"key":"e_1_2_12_3_1","doi-asserted-by":"publisher","DOI":"10.1111\/ijlh.14103"},{"key":"e_1_2_12_4_1","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics11101756"},{"key":"e_1_2_12_5_1","doi-asserted-by":"publisher","DOI":"10.3343\/alm.2013.33.1.1"},{"key":"e_1_2_12_6_1","doi-asserted-by":"publisher","DOI":"10.3343\/alm.2022.42.5.515"},{"key":"e_1_2_12_7_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1751-553X.2011.01306.x"},{"key":"e_1_2_12_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cll.2024.04.001"},{"key":"e_1_2_12_9_1","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2172-14-8"},{"key":"e_1_2_12_10_1","doi-asserted-by":"publisher","DOI":"10.1093\/ajcp\/aqw035"},{"key":"e_1_2_12_11_1","doi-asserted-by":"publisher","DOI":"10.1111\/ijlh.13368"},{"key":"e_1_2_12_12_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-61247-0"},{"key":"e_1_2_12_13_1","doi-asserted-by":"publisher","DOI":"10.21037\/atm-19-3173"},{"key":"e_1_2_12_14_1","doi-asserted-by":"publisher","DOI":"10.1182\/blood-2020-142498"},{"key":"e_1_2_12_15_1","doi-asserted-by":"publisher","DOI":"10.1515\/cclm-2023-0932"},{"key":"e_1_2_12_16_1","doi-asserted-by":"crossref","unstructured":"E.Urrechaga O.B\u00f3veda U.Aguirre S.Garc\u0131'a andE.Pulido \u201cNeutrophil Cell Population Data Biomarkers for Acute Bacterial Infection \u201d2018.","DOI":"10.33309\/2639-8893.010106"},{"key":"e_1_2_12_17_1","doi-asserted-by":"publisher","DOI":"10.1515\/cclm-2022-0713"},{"key":"e_1_2_12_18_1","doi-asserted-by":"publisher","DOI":"10.1177\/08850666221127185"},{"key":"e_1_2_12_19_1","doi-asserted-by":"publisher","DOI":"10.1111\/ijlh.13312"},{"key":"e_1_2_12_20_1","doi-asserted-by":"publisher","DOI":"10.1111\/ijlh.13448"},{"key":"e_1_2_12_21_1","doi-asserted-by":"publisher","DOI":"10.1097\/JTO.0b013e3181ec173d"},{"issue":"4","key":"e_1_2_12_22_1","first-page":"203","article-title":"Measures of Diagnostic Accuracy: Basic Definitions","volume":"19","author":"Simundic A. 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