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单个患者肾功能变化的建模率: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: 2012-01-23
课程语种: 英语
中文简介:
人口数据表明,随着患者年龄的增长,估计的肾小球滤过率(eGFR)会稳步下降。然而,这几乎没有考虑个体患者的波动;许多患者超过了变化水平,导致转诊到专科医生。在这项研究中,我们开发了一种算法来估计肾功能随年龄和eGFR变化的变化率作为协变量。生成的图表使临床医生能够查看这种变化在正常范围内的概率。为实现这一目标,我们使用了常规临床数据库 - 慢性肾病质量改进(QICKD)试验数据库 - 其中已鉴定了18,476名符合条件的患者。这里的关键创新是使用回归模型来平滑基础数据,这强化了eGFR测量对患者和时间的依赖性。我们的方法的一个显着优势是考虑到生物测量的每日波动。这允许临床医生揭示先前被忽视或忽略的趋势。作为一种可能的应用,我们制作了eGFR变化率分布随年龄和每个eGFR水平变化的图。这些数据也在线提供,一个关键的发现是所有年龄和肾功能水平的患者中eGFR的变化率存在相当大的变化。因此,在人口水平上整理数据会对个体患者的趋势产生不利影响。这表明需要对患者水平的速率变化进行建模。尽管如此,我们的时间和患者执行的估计仍然足够敏感,以检测人口水平的微小变化。这代表了显着的改进,考虑到当前实践中对患者分组和eGFR值进行分类的常规方法可能无法检测到微小的变化。
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 . 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: 肾功能; 协变量; 常规临床数据库
课程来源: 视频讲座网
最后编审: 2021-12-22:liyy
阅读次数: 69