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BCDE评估,一种用于分析自动血细胞计数及分类的微机程序。

Evaluation of BCDE, a microcomputer program to analyze automated blood counts and differentials.

作者信息

Bates J E, Bessman J D

出版信息

Am J Clin Pathol. 1987 Sep;88(3):314-23. doi: 10.1093/ajcp/88.3.314.

DOI:10.1093/ajcp/88.3.314
PMID:3307376
Abstract

A microcomputer program (BCDE) has been developed to analyze automated blood cell counts and differentials' similarity to normal values or to 36 disease categories. In 50 normal subjects, the analytic program listed the correct diagnosis as the first diagnosis in 49 cases (the only diagnosis in 44) and second of two diagnoses in one case. In 182 subjects with known hematologic disorders, the correct diagnosis was listed first in 134 and second or third in an additional 40. Subjects with iron deficiency, heterozygous thalassemia, immune thrombocytopenia, anemia of chronic disease, reactive thrombocytosis, acute infection, and chronic leukemia had the disorder identified as the most likely one by the analytic program with both sensitivity greater than 80% and specificity greater than 98%. Subjects with acute leukemia, folate deficiency, sickle cell anemia, cytotoxic chemotherapy, and chronic liver disease had the disorder identified as most likely by the program with a sensitivity less than 80%. In a different 11 cases with known hematologic status, a panel of 37 physicians identified the disorder(s) or normality only 72% of the time, whereas the analytic program listed the correct diagnosis first in 10 of 11 (91%). The analytic program appears useful for both triage of normal from abnormal data and for the initial differential analysis of abnormal data.

摘要

已开发出一种微机程序(BCDE),用于分析血细胞自动计数以及血细胞分类与正常值或36种疾病类别的相似性。在50名正常受试者中,分析程序在49例中将正确诊断列为首要诊断(44例为唯一诊断),在1例中列为两个诊断中的第二个。在182名已知血液系统疾病的受试者中,正确诊断在134例中列为首位,在另外40例中列为第二位或第三位。缺铁、杂合子地中海贫血、免疫性血小板减少症、慢性病贫血、反应性血小板增多症、急性感染和慢性白血病患者,分析程序将该疾病识别为最可能的疾病,敏感性均大于80%,特异性均大于98%。急性白血病、叶酸缺乏、镰状细胞贫血、细胞毒性化疗和慢性肝病患者,程序将该疾病识别为最可能的疾病,敏感性小于80%。在另外11例已知血液学状况的病例中,由37名医生组成的小组仅在72%的情况下识别出疾病或正常情况,而分析程序在11例中的10例(91%)中首先列出了正确诊断。该分析程序似乎既有助于区分正常数据与异常数据,也有助于对异常数据进行初步的鉴别分析。

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