[Association between blood lipid levels and prognosis in patients with sudden sensorineural hearing loss and...

Objective: To explore the association between blood lipid levels and prognosis in patients with sudden sensorineural hearing loss (SSNHL) and develop a predictive model. Methods: The clinical data of unilateral SSNHL patients from the Chinese PLA General Hospital between January 2008 and December 2022 were retrospectively analyzed. Patients were divided into treatment-effective and ineffective groups based on their hearing recovery (prognosis) after treatment. Restricted cubic spline (RCS) analysis was used to examine the nonlinear relationship between blood lipid levels and prognosis. The data were randomly split into training and testing sets at a 7∶3 ratio using a computer-based algorithm, and sex-stratified predictive models for prognosis were developed using stepwise logistic regression. The performance of the models was evaluated through receiver operating characteristic (ROC) curves, Hosmer-Lemeshow goodness-of-fit tests, and decision curve analysis (DCA), respectively. Results: A total of 1 329 patients aged (41.4±10.9) years were included, with 682 males and 647 females. RCS analysis showed no nonlinear relationship between lipid metabolism indicators and prognosis in sudden sensorineural hearing loss (all P>0.05). The male predictive model included eight variables: age, low-density lipoprotein cholesterol (LDL-C), smoking, drinking, time of onset, tinnitus, vertigo, and audiogram type. The areas under the ROC curve (AUC) for the training set and validation set were 0.873 (95%CI: 0.839-0.908) and 0.823 (95%CI: 0.760-0.886), respectively. The female predictive model included sevenvariables: age, body mass index (BMI), triglycerides (TG), time of onset, vertigo, hearing level, and audiogram type. The AUC was 0.864 (95%CI: 0.828-0.901) for the training set and 0.833 (95%CI: 0.766-0.900) for the validation set. The model evaluation showed no significant bias in the Hosmer-Lemeshow test for both groups (both P>0.05). The DCA showed a positive net benefit for risk-threshold probabilities of 0-0.93 in both the training and validation sets for male patients. For female patients, the net benefit was positive for thresholds of 0-0.94 in the training set and across nearly the entire range in the validation set. Conclusions: The prognosis of male patients is significantly influenced by smoking, drinking, and LDL-C metabolism disorders, while female patients are affected by BMI and TG levels. The predictive models based on blood lipid levels demonstrated good discrimination, calibration, and clinical applicability.