A prediction model of low back pain risk: a population based cohort study in Korea

다국어 초록 (Multilingual Abstract)

Background: Well-validated risk prediction models help to identify individuals at high risk of diseases and suggest preventive measures. A recent systematic review reported lack of validated prediction models for low back pain (LBP). We aimed to develop prediction models to estimate the 8-year risk of developing LBP and its re-currence.Methods: A population based prospective cohort study using data from 435,968 participants in the National Health Insurance Service–National Sample Cohort en-rolled from 2002 to 2010. We used Cox proportional hazards models.Results: During median follow-up period of 8.4 years, there were 143,396 (32.9%) first onset LBP cases. The prediction model of first onset consisted of age, sex, in-come grade, alcohol consumption, physical exercise, body mass index (BMI), total cholesterol, blood pressure, and medical history of diseases. The model of 5-year recurrence risk was comprised of age, sex, income grade, BMI, length of prescrip-tion, and medical history of diseases. The Harrell’s C-statistic was 0.812 (95% con-fidence interval [CI], 0.804-0.820) and 0.916 (95% CI, 0.907-0.924) in validation cohorts of LBP onset and recurrence models, respectively. Age, disc degeneration, and sex conferred the highest risk points for onset, whereas age, spondylolisthesis, and disc degeneration conferred the highest risk for recurrence. Conclusions: LBP risk prediction models and simplified risk scores have been de-veloped and validated using data from general medical practice. This study also offers an opportunity for external validation and updating of the models by incorpo-rating other risk predictors in other settings, especially in this era of precision medi-cine.

참고문헌 (Reference)

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