MODELING IN ANTI CANCER DRUG DVMT PRECLINICAL STUDIES THOUGH CLINICAL TRIALS

通过临床试验进行抗癌药物 DVMT 临床前研究建模

• 批准号: 6611245
• 负责人: MERRILL J EGORIN
• 金额: $ 15.58万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-01 至 2003-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6611245
• 关键词: bioengineering /biomedical engineering; biomedical resource; gas; model design /development; respiratory system

We extended the work described in last year's progress report by attempting to find improved predictors of arousal from an array of variables derived from non-EEG-related measurements. We examined various other respiratory-based measures for correlation to arousal. The following were calculated on an epoch-to-epoch basis and compared to the visually-scored arousal index: (1) the average value of the fuzzy-based severity index, SI; (2) the standard deviation of SI; (3) average inspired tidal volume; (4) standard deviation of tidal volume; (5) the maximum breath-to-breath change in inspiratory peak flow; and (6) the ratio of the maximum tidal volume over the minimum tidal volume. These variables were computed from our database of 13 patients with sleep-disordered breathing. The respiratory-based variable with the highest sensitivity of predicting arousal (75%) was the standard deviation of SI. The respiratory-based variable with the highest specificity in predicting arousal was the standard deviation of tidal volume (81%). However, the sensitivity associated with this variable was only 68%. Thus, the respiratory-related measure with best overall scores in both sensitivity and specificity was the standard deviation of SI.

我们将去年进度报告中所述的工作延长了