Objective:To investigate the impact of frailty on post-stroke depression (PSD) in patients with acute ischemic stroke and to identify risk factors for PSD in order to construct a risk prediction model.Methods:A convenience sampling method was used to recruit a total of 450 patients with acute ischemic stroke who were treated in the Department of Neurology at the Affiliated Hospital of Jining Medical University from March 2023 to April 2024. Data were collected using the Edmonton Frail Scale, Hamilton Depression Rating Scale, Barthel Index (Activities of Daily Living, ADL), Pittsburgh Sleep Quality Index, and Morse Fall Scale. Binary logistic regression analysis was performed to explore the impact of frailty on PSD and to identify other risk factors. Based on the results, a predictive model was developed.Results:A total of 450 questionnaires were distributed, with 412 valid responses returned, yielding a valid response rate of 91.56%. The incidence of PSD among the 412 patients was 45.63% (188/412). Binary Logistic regression analysis showed that frailty, sleep disturbance, C-reactive protein (CRP), and ADL score were the influencing factors for PSD in patients with acute ischemic stroke ( P<0.05). These factors were incorporated into the predictive model, and a risk nomogram was constructed. The area under the curve of the model was 0.764 [95% CI (0.716, 0.811) ], indicating good discriminative ability. Internal validation of the nomogram using the Hosmer-Lemeshow goodness-of-fit test showed χ 2=5.883, P=0.66 ( P>0.05), suggesting good calibration of the model. Conclusions:Frailty increases the risk of post-stroke depression in patients with acute ischemic stroke. Sleep disturbance, CRP level, and ADL score are important screening indicators for PSD risk. Targeted assessment and early intervention are recommended to reduce the likelihood of PSD.

Objective:To investigate the impact of frailty on post-stroke depression (PSD) in patients with acute ischemic stroke and to identify risk factors for PSD in order to construct a risk prediction model.Methods:A convenience sampling method was used to recruit a total of 450 patients with acute ischemic stroke who were treated in the Department of Neurology at the Affiliated Hospital of Jining Medical University from March 2023 to April 2024. Data were collected using the Edmonton Frail Scale, Hamilton Depression Rating Scale, Barthel Index (Activities of Daily Living, ADL), Pittsburgh Sleep Quality Index, and Morse Fall Scale. Binary logistic regression analysis was performed to explore the impact of frailty on PSD and to identify other risk factors. Based on the results, a predictive model was developed.Results:A total of 450 questionnaires were distributed, with 412 valid responses returned, yielding a valid response rate of 91.56%. The incidence of PSD among the 412 patients was 45.63% (188/412). Binary Logistic regression analysis showed that frailty, sleep disturbance, C-reactive protein (CRP), and ADL score were the influencing factors for PSD in patients with acute ischemic stroke ( P<0.05). These factors were incorporated into the predictive model, and a risk nomogram was constructed. The area under the curve of the model was 0.764 [95% CI (0.716, 0.811) ], indicating good discriminative ability. Internal validation of the nomogram using the Hosmer-Lemeshow goodness-of-fit test showed χ 2=5.883, P=0.66 ( P>0.05), suggesting good calibration of the model. Conclusions:Frailty increases the risk of post-stroke depression in patients with acute ischemic stroke. Sleep disturbance, CRP level, and ADL score are important screening indicators for PSD risk. Targeted assessment and early intervention are recommended to reduce the likelihood of PSD.

From October 2021 to February 2023, we retrospectively analyzed the clinical and laboratory data of six patients (three male and three female, median age: 54 years, age range: 29-73 years) with mast cell leukemia (MCL) diagnosed in the First Affiliated Hospital of Soochow University (The Mastocytosis Collaborative Network of China). All patients had acute MCL, with at least one C-finding present. The main clinical presentations were hypoalbuminemia ( n=4), fatigue ( n=3), fever ( n=2), abdominal discomfort ( n=2), osteolytic lesions ( n=2), dizziness ( n=1), skin flushing ( n=1), and weight loss ( n=1). Splenomegaly and lymphadenopathy were noted in six and three patients, respectively. Six patients were strongly positive for CD117, five were positive for CD30 and CD25, and four were positive for CD2. Four patients had a normal karyotype and two patients had an abnormal karyotype. Gene mutations were detected in 4/6 cases. The median serum tryptase level was 24.9 (range: 20.1-171.9) μg/L. Two patients were treated with venetoclax and azacitidine for induction (one patient achieved partial remission by combination with afatinib, while there was no remission after combination with dasatinib in the other patient). Two patients did not achieve complete remission despite treatment with cladribine and imatinib, respectively. One patient treated with interferon combined with glucocorticoids was lost to follow-up, and one patient abandoned treatment. The follow-up time ranged from 1.1 to 21.7 months. Three patients died and two survived. Overall, MCL is a rare subtype of systemic mastocytosis with heterogeneous clinical course, and these patients have poor outcome. A better understanding of the clinical characteristics, treatment, and prognosis of MCL is urgently needed.

Objective:To screen risk factors for carotid plaque vulnerability in patients with ischemic stroke and construct a risk prediction model.Methods:From November 2019 to January 2021, a total of 164 patients with ischemic stroke hospitalized in the Neurology Department of the Affiliated Hospital of Jining Medical University were selected as the study subjects by convenience sampling method. Color doppler ultrasound was used to measure carotid plaques in patients with ischemic stroke to determine whether they were vulnerable plaques. The patients were surveyed using the General Information Questionnaire and the Type D Personality Scale. Binary Logistic regression analysis was used to explore the risk factors of carotid plaque vulnerability in ischemic stroke patients, and based on this, a risk prediction model for carotid plaque vulnerability in ischemic stroke patients was constructed.Results:A total of 87 patients with ischemic stroke had vulnerable carotid plaques. The results of binary Logistic regression analysis showed that age ( OR=1.136, 95% CI: 1.052-1.226), total score of Type D Personality Scale ( OR=1.170, 95% CI: 1.043-1.312), smoking history ( OR=3.058, 95% CI: 1.054-8.875), homocysteine ( OR=1.400, 95% CI: 1.179-1.664), triglycerides ( OR=2.356, 95% CI: 1.534-3.619) were risk factors for carotid plaque vulnerability in stroke patients ( P<0.05). The results of risk prediction model based on risk factors show that, the area under the receiver operating characteristic of the subjects was 0.935, indicating good clinical predictive ability. Conclusions:Age, total score of Type D Personality Scale, smoking history, homocysteine and triglyceride are risk factors of carotid plaque vulnerability in stroke patients. The risk prediction model can early identify and screen high-risk factors for carotid plaque vulnerability in ischemic stroke patients, and is worthy of clinical promotion and practice.

Objective:To understand the characteristics of type D personality in patients with ischemic stroke, and to explore the correlation between type D personality and carotid plaque vulnerability in patients with ischemic stroke.Methods:From November 2019 to December 2020, convenience sampling was used to select 125 patients with ischemic stroke who underwent carotid color Doppler ultrasound examination in the Department of Neurology, Affiliated Hospital of Jining Medical University as the research subject. Carotid plaques were measured by color Doppler ultrasound in patients with ischemic stroke to determine whether they were vulnerable plaques. The patients were investigated using the Type D Personality Scale.Results:The proportion of type D personality in ischemic stroke patients was 52.8% (66/125) . Logistic regression analysis showed that type D personality and the social inhibition dimension of type D personality were the influencing factors of carotid plaque vulnerability in patients with ischemic stroke ( P<0.05) . Conclusions:Type D personality is closely associated with carotid plaque vulnerability in ischemic stroke patients. Medical and nursing staff should strengthen the screening of type D personality in patients with ischemic stroke and implement early intervention.