Shiga S, Furukawa T, Koyanagi I, Yamagishi M, Yoshida Y, Takahashi T, Kannagi R, Mori T
Central Clinical Laboratory, Kyoto University School of Medicine, Japan.
Am J Hematol. 1997 Feb;54(2):108-17. doi: 10.1002/(sici)1096-8652(199702)54:2<108::aid-ajh3>3.0.co;2-0.
To establish a simple computer program for the laboratory diagnosis of anemia and related diseases, multivariate analyses were applied to the results of routine hematological laboratory tests obtained from 48 patients and 51 healthy volunteers. The patients studied were limited to those who had not been treated hematologically by the time of their first visit to our hospital, and their first data obtained in our laboratory were analyzed. Final diagnoses were aplastic anemia (AA) in 21, myelodysplastic syndrome (MDS) in 14, iron deficiency anemia (IDA) in 3, polycytemia vera (PV)in 3, and idiopathic thrombocytopenic purpura (ITP) in 7. Eight parameters, WBC, RBC, Hb, Ht, MCV, MCH, MCHC, and PLT, were transformed to normal distribution and then applied to principal component analysis to evaluate their independence. Very close relationships were observed between Ht and Hb, and between MCV and MCH. One each of these pairs was selected by discriminant analysis and two sets, RBC, MCH, Hb, PLT, and WBC, and RBC, MCV, Ht, PLT, and WBC, were obtained. Two canonical components gave good discrimination of these five diseases and also of normal subjects. When disease prediction was made using this analysis, 37 of 48 patients (77.1%) were predicted correctly, and furthermore, when two disease predictions were allowed, all patients were diagnosed properly. Some overlaps were observed in this two-dimensional coordinate system, especially of AA and MDS, and also with normal subjects. To improve the system further, the additional parameters of age and sex were added to construct a three-dimensional analysis which resulted in much clearer discrimination. The whole procedure described is being developed with subjects who are not taking medication. Subsequently, the general application of this analytical procedure should be limited to only those not on medications. In conclusion, this is in essence a demonstration project; however, this trial of laboratory diagnosis using routine hematological laboratory results appears to be promising. Further extension of the study by increasing numbers of patients and disorders studied, including secondary anemias, will allow the design of diagnostic software for use with personal computers at the sites of primary care.
为建立一个用于贫血及相关疾病实验室诊断的简单计算机程序，对48例患者和51名健康志愿者的常规血液学实验室检查结果进行了多变量分析。所研究的患者仅限于首次来我院就诊时未接受血液学治疗的患者，并对他们在我院实验室获得的首次数据进行了分析。最终诊断为再生障碍性贫血（AA）21例、骨髓增生异常综合征（MDS）14例、缺铁性贫血（IDA）3例、真性红细胞增多症（PV）3例、特发性血小板减少性紫癜（ITP）7例。将白细胞（WBC）、红细胞（RBC）、血红蛋白（Hb）、血细胞比容（Ht）、平均红细胞体积（MCV）、平均红细胞血红蛋白含量（MCH）、平均红细胞血红蛋白浓度（MCHC）和血小板（PLT）这8个参数转换为正态分布，然后应用主成分分析来评估它们的独立性。观察到Ht与Hb之间以及MCV与MCH之间存在非常密切的关系。通过判别分析从每组中各选择一个，得到两组参数，即红细胞、平均红细胞血红蛋白含量、血红蛋白、血小板和白细胞，以及红细胞、平均红细胞体积、血细胞比容、血小板和白细胞。两个典型成分对这五种疾病以及正常受试者都有很好的区分能力。当使用这种分析进行疾病预测时，48例患者中有37例（77.1%）被正确预测，此外，当允许进行两种疾病预测时，所有患者都得到了正确诊断。在这个二维坐标系中观察到一些重叠，特别是再生障碍性贫血和骨髓增生异常综合征之间，以及与正常受试者之间。为了进一步改进该系统，增加了年龄和性别的附加参数以构建三维分析，结果区分更加清晰。所描述的整个程序正在未服药的受试者中开展。随后，这种分析程序的普遍应用应仅限于未服药的人群。总之，这本质上是一个示范项目；然而，这项使用常规血液学实验室结果进行实验室诊断的试验似乎很有前景。通过增加研究的患者数量和疾病种类（包括继发性贫血）进一步扩展该研究，将能够设计出供基层医疗单位个人计算机使用的诊断软件。
