Banbeta Akalu, Seyoum Dinberu, Belachew Tefera, Birlie Belay, Getachew Yehenew
Department of Statistics, College of Natural Science, Jimma University, Jimma, Ethiopia.
Department of Population and Family Health, College of Public Health and Medical Science, Jimma University, Jimma, Ethiopia.
Arch Public Health. 2015 Jan 1;73(1):6. doi: 10.1186/2049-3258-73-6. eCollection 2015.
In developing countries about 3.5% of children aged 0-5 years are victims of severe acute malnutrition (SAM). Once the morbidity has developed the cure process takes variable period depending on various factors. Knowledge of time-to-cure from SAM will enable health care providers to plan resources and monitor the progress of cases with SAM. The current analysis presents modeling time-to-cure from SAM starting from the day of diagnosis in Wolisso St. Luke Catholic hospital, southwest Ethiopia.
With the aim of coming up with appropriate survival (time-to-event) model that describes the SAM dataset, various parametric clustered time-to-event (frailty) models were compared. Frailty model, which is an extension of the proportional hazards Cox survival model, was used to analyze time-to-cure from SAM. Kebeles (villages) of the children were considered as the clustering variable in all the models. We used exponential, weibull and log-logistic as baseline hazard functions and the gamma as well as inverse Gaussian for the frailty distributions and then based on AIC criteria, all models were compared for their performance.
The median time-to-cure from SAM cases was 14 days with the maximum of 63 days of which about 83% were cured. The log-logistic model with inverse Gaussian frailty has the minimum AIC value among the models compared. The clustering effect was significant in modeling time-to-cure from SAM. The results showed that age of a child and co-infection were the determinant prognostic factors for SAM, but sex of the child and the type of malnutrition were not significant.
The log-logistic with inverse Gaussian frailty model described the SAM dataset better than other distributions used in this study. There is heterogeneity between the kebeles in the time-to-cure from SAM, indicating that one needs to account for this clustering variable using appropriate clustered time-to-event frailty models.
在发展中国家，约3.5%的0至5岁儿童患有重度急性营养不良（SAM）。一旦发病，治愈过程会因各种因素而持续不同的时间。了解SAM的治愈时间将有助于医疗保健提供者规划资源并监测SAM病例的进展。当前分析呈现了埃塞俄比亚西南部沃利索圣卢克天主教医院自诊断之日起对SAM治愈时间的建模。
为了得出描述SAM数据集的合适生存（事件发生时间）模型，比较了各种参数化聚类事件发生时间（脆弱性）模型。脆弱性模型是比例风险Cox生存模型的扩展，用于分析SAM的治愈时间。在所有模型中，将儿童所在的凯贝勒（村庄）视为聚类变量。我们使用指数分布、威布尔分布和对数逻辑斯蒂分布作为基线风险函数，以及伽马分布和逆高斯分布作为脆弱性分布，然后根据AIC标准比较所有模型的性能。
SAM病例的中位治愈时间为14天，最长为63天，其中约83%的病例被治愈。在所比较的模型中，具有逆高斯脆弱性的对数逻辑斯蒂模型的AIC值最小。聚类效应在SAM治愈时间建模中具有显著性。结果表明，儿童年龄和合并感染是SAM的决定性预后因素，但儿童性别和营养不良类型不显著。
具有逆高斯脆弱性的对数逻辑斯蒂模型比本研究中使用的其他分布能更好地描述SAM数据集。SAM治愈时间在各凯贝勒之间存在异质性，这表明需要使用适当的聚类事件发生时间脆弱性模型来考虑这一聚类变量。
