Serum neurofilament light chain levels in migraine patients: a monocentric case-control study in China.

PURPOSE: Serum neurofilament light chain (sNfL) can reflect nerve damage. Whether migraine can cause neurological damage remain unclear. This study assesses sNfL levels in migraine patients and explores whether there is nerve damage in migraine. METHODS: A case-control study was conducted in Xiamen, China. A total of 138 migraine patients and 70 healthy controls were recruited. sNfL (pg/mL) was measured on the single-molecule array platform. Univariate, Pearson correlation and linear regression analysis were used to assess the relationship between migraine and sNfL levels, with further subgroup analysis by migraine characteristics. RESULTS: Overall, 85.10% of the 208 subjects were female, with a median age of 36 years. sNfL levels were higher in the migraine group than in the control group (4.85 (3.49, 6.62) vs. 4.11 (3.22, 5.59)), but the difference was not significant (P = 0.133). The two groups showed an almost consistent trend in which sNfL levels increased significantly with age. Subgroup analysis showed a significant increase in sNfL levels in patients with a migraine course ≥ 10 years (ß = 0.693 (0.168, 1.220), P = 0.010). Regression analysis results show that age and migraine course are independent risk factors for elevated sNfL levels, and there is an interaction between the two factors. Patients aged < 45 years and with a migraine course ≥ 10 years have significantly increased sNfL levels. CONCLUSIONS: This is the first study to evaluate sNfL levels in migraine patients. The sNfL levels significantly increased in patients with a migraine course ≥ 10 years. More attention to nerve damage in young patients with a long course of migraine is required.

Cancer screening in hospitalized ischemic stroke patients: a multicenter study focused on multiparametric analysis to improve management of occult cancers.

Background/aims: The reciprocal promotion of cancer and stroke occurs due to changes in shared risk factors, such as metabolic pathways and molecular targets, creating a "vicious cycle." Cancer plays a direct or indirect role in the pathogenesis of ischemic stroke (IS), along with the reactive medical approach used in the treatment and clinical management of IS patients, resulting in clinical challenges associated with occult cancer in these patients. The lack of reliable and simple tools hinders the effectiveness of the predictive, preventive, and personalized medicine (PPPM/3PM) approach. Therefore, we conducted a multicenter study that focused on multiparametric analysis to facilitate early diagnosis of occult cancer and personalized treatment for stroke associated with cancer. Methods: Admission routine clinical examination indicators of IS patients were retrospectively collated from the electronic medical records. The training dataset comprised 136 IS patients with concurrent cancer, matched at a 1:1 ratio with a control group. The risk of occult cancer in IS patients was assessed through logistic regression and five alternative machine-learning models. Subsequently, select the model with the highest predictive efficacy to create a nomogram, which is a quantitative tool for predicting diagnosis in clinical practice. Internal validation employed a ten-fold cross-validation, while external validation involved 239 IS patients from six centers. Validation encompassed receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and comparison with models from prior research. Results: The ultimate prediction model was based on logistic regression and incorporated the following variables: regions of ischemic lesions, multiple vascular territories, hypertension, D-dimer, fibrinogen (FIB), and hemoglobin (Hb). The area under the ROC curve (AUC) for the nomogram was 0.871 in the training dataset and 0.834 in the external test dataset. Both calibration curves and DCA underscored the nomogram's strong performance. Conclusions: The nomogram enables early occult cancer diagnosis in hospitalized IS patients and helps to accurately identify the cause of IS, while the promotion of IS stratification makes personalized treatment feasible. The online nomogram based on routine clinical examination indicators of IS patients offered a cost-effective platform for secondary care in the framework of PPPM. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-024-00354-8.