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首页> 外文期刊>Malaria research and treatment >Analysis of Haematological Parameters as Predictors of Malaria Infection Using a Logistic Regression Model: A Case Study of a Hospital in the Ashanti Region of Ghana
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Analysis of Haematological Parameters as Predictors of Malaria Infection Using a Logistic Regression Model: A Case Study of a Hospital in the Ashanti Region of Ghana

机译：血液学参数分析逻辑回归模型的疟疾感染预测因子 - 以加纳亚散蒂地区医院为例

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摘要

Malaria is the leading cause of morbidity in Ghana representing 40-60% of outpatient hospital attendance with about 10% ending up on admission. Microscopic examination of peripheral blood film remains the most preferred and reliable method for malaria diagnosis worldwide. But the level of skills required for microscopic examination of peripheral blood film is often lacking in Ghana. This study looked at determining the extent to which haematological parameters and demographic characteristics of patients could be used to predict malaria infection using logistic regression. The overall prevalence of malaria in the study area was determined to be 25.96%; nonetheless, 45.30% of children between the ages of 5 and 14 tested positive. The binary logistic model developed for this study identified age, haemoglobin, platelet, and lymphocyte as the most significant predictors. The sensitivity and specificity of the model were 77.4% and 75.7%, respectively, with a PPV and NPV of 52.72% and 90.51%, respectively. Similar to RDT this logistic model when used will reduce the waiting time and improve the diagnosis of malaria.
机译：疟疾是加纳的发病率的主要原因，占门诊院出席的40-60％，最终收取约10％。外周血膜的显微镜检查仍然是全球疟疾诊断最优选和可靠的方法。但是，加纳往往缺乏外周血血膜微观检查所需的技能水平。这项研究看着确定患者的血液学参数和人口统计学特性的程度可用于使用逻辑回归来预测疟疾感染。研究区疟疾的总体患病率确定为25.96％;尽管如此，45.30％的儿童在5和14岁之间测试了阳性。为该研究开发的二元物流模型确定了年龄，血红蛋白，血小板和淋巴细胞作为最重要的预测因子。该模型的敏感性和特异性分别为77.4％和75.7％，PPV和NPV分别为52.72％和90.51％。与RDT类似于此逻辑模型，当使用时会降低等待时间并改善疟疾的诊断。

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