Pain when it "counts": hurdle analysis of clinical pain ratings improves data model performance

关键时刻的疼痛:临床疼痛评级的障碍分析可提高数据模型性能

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Abstract

OBJECTIVES: The Numerical Rating Scale is widely used for patient-reported appraisals of pain intensity; however, scale properties have limited utility for assessing chronic pain. Specifically, single pain ratings demonstrate high intraindividual variability. We propose an efficient alternative, termed hurdle analysis, separately analyzing zero and nonzero pain ratings. METHODS: This retrospective study of 23,480 US Veterans diagnosed with low back pain (LBP) included 2.1 million unique pain ratings. Marginal distributions comprised of all pain ratings for each individual were parametrized with usual and hurdle analysis methods to holistically assess scale utilization. RESULTS: The population was 87% male and 13% female; 41% Black, 38% White, and 2% Hispanic; modal age range was 65 years to 84 years (45 years-64 years) for men (women). Focusing on statistically informative records, ie, those with ≥100 pain ratings (22% of the total), the median [interquartile range] pain rating was 3.5 [2.3-4.7] (4.0 [3.0-5.1]) for men (women). Marginal distributions were non-normal, with zero being the modal value in 79% (73%) of men (women). In hurdle analysis, the average proportion of zeroes was 0.39 (0.31) for men (women); the average nonzero pain rating was 5.9 [5.1-6.6] (6.0 [5.3-6.7]) for men (women). The nonzero averages, in contrast to standard averages, were normally distributed for the population and compared with data showed less bias and variance. CONCLUSION: Analysis of clinical pain ratings from Veterans with LBP with hurdle analysis yielded improved estimates of pain when-pain-is-present (ie, nonzero pain) and also demonstrated the variable presence of pain in this population. Further study of this approach appears warranted.

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