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个体患者肾功能变化率模型:基于常规收集数据的纵向模型

Modeling Rate of Change in Renal Function for Individual Patients: A Longitudinal Model Based on Routinely Collected Data
课程网址: http://videolectures.net/nipsworkshops2011_poh_patients/  
主讲教师: Norman Poh
开课单位: 萨里大学
开课时间: 2012-06-23
课程语种: 英语
中文简介:
人群数据表明,随着患者年龄的增长,估计的肾小球滤过率(eGFR)稳步下降。然而,这几乎没有考虑到个体患者的波动;许多患者超过了变化水平,这将导致转诊到专科护理。在这项研究中,我们开发了一种以年龄和表皮生长因子受体为协变量来估计肾功能变化率的算法。生成的图表使临床医生能够查看这种变化是否在正常范围内的概率。为了实现这一目标,我们使用了一个常规的临床数据库——慢性肾脏疾病质量改善(QICKD)试验数据库——其中18476名符合条件的患者已经被确定。这里的关键创新是使用回归模型来平滑底层数据,这使得eGFR测量对患者和时间都具有依赖性。我们方法的一个显著优点是考虑了生物测量中的每日波动。这使得临床医生能够揭示以前被忽视或忽视的趋势。作为一种可能的应用,我们绘制了eGFR变化率随年龄和eGFR水平变化的分布图。这些数据也以视频形式在线呈现在。其中一个关键的发现是,在不同年龄和不同肾功能水平的患者中,表皮生长因子受体的变化率存在显著差异。因此,在人群水平上整理数据会对个体患者水平的趋势产生不利影响。这就需要在患者层面上对速率变化进行建模。尽管如此,我们的时间和耐心强制的估计仍然足够敏感,可以检测出人口水平上的微小变化。考虑到按年龄组和eGFR值对患者进行分类的传统方法(如当前实践的那样)可能无法检测到这种微小的变化,这是一个重大的改进。
课程简介: Population data suggest that there is a steady decline in estimated glomerular filtration rate (eGFR) as patients get older. However this takes little account of individual patient fluctuation; with many patients exceeding levels of change which should lead to referral to specialist care. In this study, we develop an algorithm to estimate the rate of change in renal function with age and eGFR as covariates. The produced chart enables clinicians to look up the probability that this change was within the normal range. To achieve this, we used a routine clinical database – the Quality Improvement in Chronic Kidney Disease (QICKD) trial database – in which 18,476 eligible patients have been identified. The key innovation here is the use of a regression model to smooth the underlying data, which enforces the dependency of the eGFR measurement on both the patient and time. A significant advantage of our approach is that daily fluctuation in the biological measurement is taken into account. This allows a clinician to reveal trends previously dismissed or ignored. As a possible application, we produced a plot of distribution of the rate of change in eGFR as a function of age and each level of eGFR. These data are also presented as a video online at: . One the key findings is the presence of considerable variance of the rate of change in eGFR across patients at all ages and levels of renal function. Consequently, collating the data at the population level can adversely impact on the trend at the individual patient level. This points to the need for modeling the rate change at the patient level. Despite this, our time- and patient-enforced estimate is still sensitive enough to detect the minute change at the population level. This represents a significant improvement considering that the conventional approach that bins the patient by age group and eGFR value, as currently practiced, may not be able to detect such a minute change.
关 键 词: 肾小球滤过率; 慢性肾脏病; 肾功能
课程来源: 视频讲座网
数据采集: 2020-12-21:yxd
最后编审: 2021-12-20:liyy
阅读次数: 50