Establishment and Validation of a Clinical Prediction Model for Chronic Low Back Pain
Objective To investigate the incidence and related pathogenic factors of chronic low back pain(CLBP)and to establish and validate a clinical prediction model.Methods From May to October in 2022,a self-designed risk factor questionnaire for chronic low back pain was used to collect relevant information from outpatients in 10 com-munity health service centers in Chengdu,Sichuan province,including south railway station and longzhou road.LASSO regression was used to screen potential risk factors,and Logistic regression was used to establish a clinical prediction model for CLBP.The degree of fit,accuracy,discrimination of the prediction model were further validated by HL goodness of fit test,the C-index,calibration curve.Internal validation was performed using the Boot-strap to test the internal stability of the model and to externally validate the model after 5 months.Results There were 434 people with chronic low back pain among 760 study participants,with a prevalence rate of 56.8％.27 po-tential factors were screened by LASSO regression into 7 relevant factors,of which 6 were independent influences on the occurrence of CLBP.The prediction model constructed accordingly had a differentiation C-index of 0.815(95％CI:0.772-0.857)and an accuracy C-index of 0.778(95％CI:0.772-0.857).Conclusion The CLBP prediction model constructed by patients'age,work requirements,comfort of table and chair,social support,exercise intensity,and regularity of three meals can effectively predict whether patients have the risk of chronic low back pain.
Chronic low back painIncidenceClinical modelNomograph
NETL
NSTL
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