{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T14:26:05Z","timestamp":1787840765980,"version":"build-2784847793"},"reference-count":15,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"10","license":[{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-sa\/4.0"}],"content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,10]]},"abstract":"<jats:title>\n                    A\n                    <jats:sc>BSTRACT<\/jats:sc>\n                  <\/jats:title>\n                  <jats:sec>\n                    <jats:title>Introduction:<\/jats:title>\n                    <jats:p>Acute leukaemia is a rapidly progressive haematopoietic disorder affecting bone marrow, leading to excessive production of immature blast cells. Acute myeloid leukaemia (AML) in adults accounts for 80\u201390% of cases of acute leukaemia. Acute lymphoblastic leukaemia (ALL), common in childhood, comprises 12% of all leukaemia. Immunophenotyping using flow cytometry is crucial for classifying leukaemia into AML and acute lymphoblastic leukaemia (ALL) subtypes, aiding in accurate diagnosis and treatment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective:<\/jats:title>\n                    <jats:p>The aim of the study was to analyze the different immunophenotypic patterns in paediatric leukaemia by flow cytometry.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and Methods:<\/jats:title>\n                    <jats:p>This prospective observational study included 54 diagnosed cases of paediatric acute leukaemia on bone marrow studies. Furthermore, it is classified by multiparametric flowcytometry.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>Among 54 cases, 30 (56%) were ALL and 24 (44%) were AML. Among ALL cases, 21 (70%) were B ALL and 9 (30%) were T ALL. The most common symptoms were fever (91%) and fatigue (96%). Immunophenotyping showed B ALL cases expressing CD10 (86%), CD19 (81%), and CD79a (81%), while T ALL cases predominantly expressed sCD3 (66%), CD5 (89%), and CD7 (89%). AML cases exhibited CD13 (83%), CD33 (88%), and cMPO (88%).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>Flow cytometry is a highly accurate tool for differentiating leukaemia subtypes. Immunophenotyping plays a crucial role in diagnosis, classification, and treatment planning for Paediatric leukaemia.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.4103\/jfmpc.jfmpc_372_25","type":"journal-article","created":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T13:02:51Z","timestamp":1761742971000},"page":"4356-4361","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":0,"title":["Immunophenotypic patterns in paediatric acute leukaemia: A flowcytometry-based prospective observational study in tribal dominant state, Jharkhand"],"prefix":"10.4103","volume":"14","author":[{"given":"Rashmi","family":"Rati","sequence":"first","affiliation":[{"name":"Department of Pathology, Rajendra Institute of Medical Sciences, Ranchi, Jharkhand, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arvind","family":"Kumar","sequence":"additional","affiliation":[{"name":"Department of Pathology, Rajendra 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