Behlouli Hassan, Feldman Deborah E, Ducharme Anique, Frenette Marc, Giannetti Nadia, Grondin François, Michel Caroline, Sheppard Richard, Pilote Louise
Divisions of Internal Medicine and Clinical Epidemiology, McGill University Health Centre.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:6242-6. doi: 10.1109/IEMBS.2009.5334659.
Quality of life (QoL) is an important end point in heart failure (HF) studies. The Minnesota Living with Heart Failure questionnaire (MLHFQ) is the instrument most widely used to evaluate QoL in Heart Failure (HF) patients. It is a questionnaire containing 21 questions with scores ranging from 0 to 105. A best cut-off value for MLHFQ scores to identify those patients with good, moderate or poor QoL has not been determined.
To determine a cut-off score for the MLHFQ based on the neural network (NN) approach. These cut-off scores will help discriminate between HF patients having good, moderate or poor QoL.
This research was carried out in the context of a longitudinal cohort study of new patients attending specialized HF clinics in six participating centers in Quebec, Canada. Patients completed a questionnaire that included the MLHFQ. In addition to this scale, self-perceived health status and clinical information related to the severity of HF were obtained including: the New York Heart Association (NYHA) functional class, 6 minute walk test and survival status. We analyzed the database using NN and conventional statistical tools. The NN is a statistical program that recognizes clusters of MLHFQ and relates similar QoL measures to one another. Among the 531 eligible patients, 447 patients with complete questionnaires were used to build randomly two sets for training (learning set) and for testing (validation set) the NN.
Participants had a mean age of 65 years and 24% were women. The median MLHFQ score was 45 (inter-quartile range: 27 to 64). NN identified 3 distinct clusters of MLHFQ that represent the full spectrum of possible scores on the MLHFQ. We estimated that a score of < 24 on the MLHFQ represents a good QoL, a score between 24 and 45 represents a moderate QoL, and a score > 45 represents a poor QoL. Validation with the different severity measures confirmed these categories. These cut-offs allowed us to reach a good total accuracy (91%). These cutoffs were strongly correlated with survival status (p = 0.004), self-perceived health status (p = 0.0032), NYHA functional class (p<0.0001) and standardized 6 minutes walk test (p = 0.05)
The identification of three levels of MLHFQ should be useful in clinical decision making.
生活质量（QoL）是心力衰竭（HF）研究中的一个重要终点。明尼苏达心力衰竭生活问卷（MLHFQ）是评估心力衰竭（HF）患者生活质量最广泛使用的工具。它是一份包含21个问题的问卷，得分范围为0至105。尚未确定用于识别生活质量良好、中等或较差患者的MLHFQ得分的最佳临界值。
基于神经网络（NN）方法确定MLHFQ的临界分数。这些临界分数将有助于区分生活质量良好、中等或较差的HF患者。
本研究是在加拿大魁北克六个参与中心对新就诊于专科HF诊所的患者进行的纵向队列研究的背景下开展的。患者完成了一份包括MLHFQ的问卷。除了该量表外，还获取了自我感知的健康状况以及与HF严重程度相关的临床信息，包括：纽约心脏协会（NYHA）功能分级、6分钟步行试验和生存状况。我们使用NN和传统统计工具分析了数据库。NN是一个统计程序，可识别MLHFQ的聚类，并将相似的生活质量测量值相互关联。在531名符合条件的患者中，447名问卷完整的患者被随机用于构建两组，一组用于训练（学习集）NN，另一组用于测试（验证集）NN。
参与者的平均年龄为65岁，24%为女性。MLHFQ得分的中位数为45（四分位间距：27至64）。NN识别出MLHFQ的3个不同聚类，代表了MLHFQ上所有可能得分的范围。我们估计，MLHFQ得分<24表示生活质量良好，得分在24至45之间表示生活质量中等，得分>45表示生活质量较差。用不同的严重程度测量方法进行验证证实了这些类别。这些临界值使我们达到了较高的总准确率（91%）。这些临界值与生存状况（p = 0.004）、自我感知的健康状况（p = 0.0032）、NYHA功能分级（p<0.0001）和标准化6分钟步行试验（p = 0.05）密切相关。
确定MLHFQ的三个水平应有助于临床决策。
