Background: Skeletal muscle parameters at the first lumbar vertebra (L1) level on computed tomography (CT) are common indicators for muscle mass. However, their relationship with the severity and prognosis of amyotrophic lateral sclerosis (ALS) patients remains unclear.Methods: This cohort study included ALS patients who underwent chest CT scans between January 2018 and January 2022 and healthy controls (HCs) matched for gender and age. Overall survival (OS) was determined from the date of chest CT to death, tracheal intubation or 1 January 2024. Using ImageJ software, skeletal muscle area and density (L1 SMA/SMD), skeletal muscle index (L1 SMI), paraspinal muscle area and density (L1 PMA/PMD) and subcutaneous fat area and density (L1 SFA/SFD) at L1 were quantified. The relationships between the quantified muscle parameters and both King's clinical stages and the Revised ALS Functional Rating Scale (ALSFRS‐R) were analysed. The Cox proportional hazard model was used to evaluate the hazard ratio (HR) of skeletal muscle parameters as risk factors for outcome events, and to construct a nomogram.Results: Muscle parameters in ALS patients (n = 102; 36.27% female; mean age, 60.85 ± 10.58 years) were significantly lower compared with HCs (p < 0.001). L1 SMD (p = 0.047) and L1 PMD (p = 0.003) both differed significantly across the King's clinical stages. ALSFRS‐R scores correlated with L1 SMA (r = 0.35, p < 0.001), L1 SMI (r = 0.34, p < 0.001), L1 PMA (r = 0.27, p = 0.007) and L1 PMD (r = 0.27, p = 0.007). Multivariate Cox regression analysis revealed that L1 SMA (HR = 0.96, 95% confidence interval [CI] = 0.94–0.98, p = 0.001), L1 SMD (HR = 0.92, 95% CI = 0.88–0.96, p < 0.001) and L1 PMA (HR = 1.06, 95% CI = 1.01–1.11, p = 0.022) significantly influenced ALS survival, with area under the curves (AUCs) of 0.687 and 0.851 for 1‐ and 3‐year OS prediction. The consistency index (C‐index) for the nomogram was 0.72 (95% CI = 0.641–0.793).Conclusions: Skeletal muscle parameters at L1 level on CT are significantly associated with clinical severity and prognosis in ALS.Trial Registration: Chinese Clinical Trial Registration Center: ChiCTR230078702

Background: Since peripheral leukocytes may contribute to the pathophysiology of stroke, the aim of this study was to elucidate the relationship between leukocytes and stroke outcomes and identify which leukocyte subtypes most accurately predict functional outcomes and poststroke fatigue (PSF) in stroke patients. Methods: A total of 788 ischemic stroke patients within 72 h of onset of disease were admitted in our study. Stroke‐associated infection (SAI) and PSF were evaluated according to diagnosis standards by a special neurologist. Analyses were performed using SPSS 23.0 and GraphPad Prism 10.0. Results: Neutrophil‐to‐lymphocyte ratio (NLR) has discriminative power in predicting stroke outcome, and the area under the curve (AUC) of NLR to distinguish stroke outcomes was 0.689 (95% confidence interval, 0.646–0.732). Positive correlation was found between NLR levels and NIHSS score on admission ( r = 0.2786, p < 0.001). Risk model for predicting stroke outcome was constructed using age, NIHSS, previous stroke history, triglycerides, glucose and hemoglobin levels, thrombolysis treatment, and NLR, with an AUC of 0.865. Patients who developed SAI and PSF both had significantly higher NLR levels at admission than those patients not diagnosed with SAI and PSF ( p < 0.0001). A risk model was constructed to predict PSF based on parameters including age, NIHSS score, lipoprotein(a) and NLR, and an AUC of 0.751. Conclusions: Higher NLR levels in the acute phase of stroke might indicate a higher incidence of SAI and PSF. Therefore, higher NLR is associated with a poor stroke prognosis.