Corcos Jacques, Behlouli Hassan, Beaulieu Sylvie
Urology Department, Sir Mortimer B. Davis-Jewish General Hospital, McGill University, Montreal, Quebec, Canada.
Neurourol Urodyn. 2002;21(3):198-203. doi: 10.1002/nau.10005.
We propose to determine cut-off scores for the Incontinence Impact Questionnaire (IIQ) based on the neural network (NN) approach. These cut-off scores should discriminate between patients having poor, moderate, or good quality of life (QoL) secondary to their incontinence problems. Data from two prospectively completed QoL questionnaires, the IIQ (n = 237) and the MOS 36-Item Short-Form Health Survey (SF-36) (n = 237), were analyzed using NN and conventional statistical tools. Kohonen networks identified three distinct clusters of IIQ scores. The three clusters represent the full spectrum of possible scores on the IIQ. We interpreted these clusters as reflecting good, moderate, and poor QoL. We estimated that a score of less than 50 on the IIQ would be representative of good QoL, between 50 and 70 would be moderate QoL, and greater than 70 would be indicative of poor QoL. Validation with the SF-36 data confirmed these categories. The present study demonstrated that the NN approach is opening new areas in the interpretation and clinical usefulness of QoL questionnaires. NN allowed the identification of three levels of QoL and should be useful in clinical decision making.
我们建议基于神经网络（NN）方法来确定尿失禁影响问卷（IIQ）的临界分数。这些临界分数应能区分因尿失禁问题导致生活质量（QoL）较差、中等或良好的患者。使用神经网络和传统统计工具分析了来自两份前瞻性完成的生活质量问卷的数据，即IIQ（n = 237）和MOS 36项简短健康调查（SF - 36）（n = 237）。Kohonen网络识别出IIQ分数的三个不同聚类。这三个聚类代表了IIQ上所有可能分数的范围。我们将这些聚类解释为反映了良好、中等和较差的生活质量。我们估计，IIQ得分低于50代表良好的生活质量，50至70之间代表中等生活质量，高于70则表明生活质量较差。用SF - 36数据进行的验证证实了这些类别。本研究表明，神经网络方法正在为生活质量问卷的解释和临床应用开辟新领域。神经网络能够识别出三个生活质量水平，在临床决策中应会很有用。
