基于慢性伤口登记数据库的伤口愈合结果早期预测。

Ruchir Srivastava, Ee Ping Ong, David Y Y Tan, Jingxian Zhang, Kyaw Kyar Toe, Priya Bishnoi, Yi Zhen Ng, Rosa Q Y So
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引用次数: 0

摘要

由于迟迟得不到适当的治疗,慢性伤口导致了许多不必要的截肢。为了加快及时治疗,本文提出了一种算法,利用逻辑回归分类器预测伤口是否会在指定时间内愈合。预测在三个时间点进行:从病人第一次到医疗机构就诊开始的一个月、三个月和六个月。该预测使用系统收集的慢性伤口登记册,完全基于患者首次就诊时收集的数据。该算法在三个时间点的预测结果的接收者工作特征曲线下面积(AUC)分别为 0.75、0.72 和 0.71。临床意义--使用所提出的预测模型,临床医生将能及早估计伤口愈合所需的时间,从而提供适当的治疗。我们希望这将确保及时治疗,减少不必要的截肢。
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Early Prediction of Wound Healing Outcome Based on Chronic Wound Registry Database.

Chronic wounds cause a number of unnecessary amputations due to a delay in proper treatment. To expedite timely treatment, this paper presents an algorithm which uses a logistic regression classifier to predict whether the wound will heal or not within a specified time. The prediction is made at three time-points: one month, three months, and six months from the first visit of the patient to the healthcare facility. This prediction is made using a systematically collected chronic wound registry and is based entirely on data collected during patients' first visit. The algorithm achieves an area under the receiver operating characteristic curve (AUC) of 0.75, 0.72, and 0.71 for the prediction at the three time-points, respectively.Clinical relevance- Using the proposed prediction model, the clinicians will have an early estimate of the time taken to heal thereby providing appropriate treatments. We hope this will ensure timely treatments and reduce the number of unnecessary amputations.

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