Objective To investigate the predictive value of pan-immune-inflammation value(PIV),blood urea nitrogen to albumin ratio(BAR),collateral circulation and National Institutes of Health stroke scale(NIHSS)score for disease progression and short-term prognosis in patients with acute perforating artery cerebral infarction(APACI).Methods Patients with APACI admitted to the Neurology Department of Anhui NO.2 Provincial People's Hospital from January 2019 to October 2024 were retrospectively enrolled in this study.General and clinical data,including age,gender,previous history(hypertension,diabetes,hyperlipidemia,coronary heart disease,atrial fibrillation),smoking history,drinking history,NIHSS scores at admission were collected.Fasting venous blood samples were collected from the patients within 24 h after admission to detect levels of neutrophils,lymphocytes,monocytes,platelets,blood urea nitrogen,and serum albumin.PIV(PIV=neutrophils × platelets × monocytes/lymphocytes)and BAR were calculated.The location of lesions and Fazekas classification of white matter lesions were evaluated using head MRI and MR angiography at admission.Collateral circulation status was assessed based on CT angiography upon admission.Disease progression was defined through comparing the NIHSS score at 72-hour after admission to the score at admission(an increase of 2 or more points in NIHSS score indicating disease progression).The patients were divided into a progression group and a non-progression group based on the increase in NIHSS score,as aforementioned.Patients follow-up was conducted through phone call or outpatient visits at 90 d after discharge.The modified Rankin scale(mRS)was used to evaluate the prognosis,with a mRS score of 0-2 indicates good prognosis,and a 3-6 indicates poor prognosis.Factors with statistically significant differences in univariate analysis were included in a multivariate Logistic regression analysis to explore the influencing factors of disease progression and poor prognosis in patients with APACI.The receiver operating characteristic(ROC)curve was used to evaluate the predictive value of each indicator for disease progression and poor prognosis in patients with APACI.Results A total of 165 patients with APACI were enrolled in this study,including 121 males and 44 females,aged 27-86 years,with an average of(61±11)years.Among all patients enrolled,56 patients were included in the progression group and 109 patients in the non-progression group,124 patients showed good prognosis and 41 patients had poor prognosis.No statistically significant differences were found in age,gender,smoking history,drinking history,hypertension,diabetes,hyperlipidemia,coronary heart disease,atrial fibrillation,lesion location,and Fazekas classification of white matter lesions between the progression group and the non-progression group(all P＞0.05).While the NIHSS score at admission,proportion of poor collateral circulation,PIV and BAR in the progression group were significantly higher than those in the non-progression group(all P＜0.05).Multivariate Logistic regression analysis showed that high NIHSS score at admission(OR,1.177,95％CI 1.001-1.384,P=0.049),poor collateral circulation(OR,3.107,95％CI 1.216-7.939,P=0.018),high PIV(OR,1.006,95％CI 1.003-1.009,P=0.001),and high BAR(OR,1.610 × 109,95％CI 5.769 × 104-4.494 × 1013,P＜0.01)were independent risk factors of disease progression in patients with APACI.ROC curve analysis results showed that the area under the curve(AUC)of combination of PIV,BAR,collateral circulation and NIHSS score at admission for predicting disease progression in patients with APACI was 0.914(95％ CI0.861-0.952,P＜0.01),which was greater than that of each indicator(all P＜0.05).No statistically significant differences were found in smoking,drinking,hypertension,hyperlipidemia,coronary heart disease,atrial fibrillation,lesion location,and BAR between the poor prognosis and the good prognosis group(all P＞0.05).Compared with the good prognosis group,the poor prognosis group had significantly older age and higher proportion of patients with diabetes,NIHSS score at admission,proportion of patients with poor collateral circulation,and PIV(all P＜0.05).Moreover,the proportion of men in the poor prognosis group was lower than that in the good prognosis group(P=0.039).There was a statistically significant difference between the good prognosis group and the poor prognosis group in the Fazekas classification of white matter lesions(P＜0.01).Multivariate Logistic regression analysis showed that high NIHSS score at admission(OR,1.345,95％CI 1.081-1.674,P=0.008),poor collateral circulation(OR,3.903,95％CI 1.061-14.355,P=0.040),and high PIV(OR,1.011,95％CI 1.005-1.017,P＜0.01)were independent risk factors of poor prognosis in patients with APACI.The AUC for predicting poor prognosis in patients with APACI through combining PIV,collateral circulation and NIHSS score at admission was 0.911(95％CI 0.857-0.950,P＜0.01),which is greater than using poor collateral circulation or NIHSS score at admission alone(both P＜0.05).However,there was no statistically significant difference in AUC between the PIV,collateral circulation and NIHSS score combined predictive model and the PIV(alone)predictive model(P＞0.05).Conclusions High PIV,high BAR,poor collateral circulation,and high NIHSS score at admission were independent risk factors of disease progression in patients with APACI.Combination of these four indices demonstrates relatively high predictive value for disease progression.In addition,high PIV,poor collateral circulation,and high NIHSS score at admission are independent risk factors of poor prognosis in patients with APACI.Joint detection of the three indices may assist in short-term prognosis evaluation of patients with APACI.

Objective To investigate the predictive value of pan-immune-inflammation value(PIV),blood urea nitrogen to albumin ratio(BAR),collateral circulation and National Institutes of Health stroke scale(NIHSS)score for disease progression and short-term prognosis in patients with acute perforating artery cerebral infarction(APACI).Methods Patients with APACI admitted to the Neurology Department of Anhui NO.2 Provincial People's Hospital from January 2019 to October 2024 were retrospectively enrolled in this study.General and clinical data,including age,gender,previous history(hypertension,diabetes,hyperlipidemia,coronary heart disease,atrial fibrillation),smoking history,drinking history,NIHSS scores at admission were collected.Fasting venous blood samples were collected from the patients within 24 h after admission to detect levels of neutrophils,lymphocytes,monocytes,platelets,blood urea nitrogen,and serum albumin.PIV(PIV=neutrophils × platelets × monocytes/lymphocytes)and BAR were calculated.The location of lesions and Fazekas classification of white matter lesions were evaluated using head MRI and MR angiography at admission.Collateral circulation status was assessed based on CT angiography upon admission.Disease progression was defined through comparing the NIHSS score at 72-hour after admission to the score at admission(an increase of 2 or more points in NIHSS score indicating disease progression).The patients were divided into a progression group and a non-progression group based on the increase in NIHSS score,as aforementioned.Patients follow-up was conducted through phone call or outpatient visits at 90 d after discharge.The modified Rankin scale(mRS)was used to evaluate the prognosis,with a mRS score of 0-2 indicates good prognosis,and a 3-6 indicates poor prognosis.Factors with statistically significant differences in univariate analysis were included in a multivariate Logistic regression analysis to explore the influencing factors of disease progression and poor prognosis in patients with APACI.The receiver operating characteristic(ROC)curve was used to evaluate the predictive value of each indicator for disease progression and poor prognosis in patients with APACI.Results A total of 165 patients with APACI were enrolled in this study,including 121 males and 44 females,aged 27-86 years,with an average of(61±11)years.Among all patients enrolled,56 patients were included in the progression group and 109 patients in the non-progression group,124 patients showed good prognosis and 41 patients had poor prognosis.No statistically significant differences were found in age,gender,smoking history,drinking history,hypertension,diabetes,hyperlipidemia,coronary heart disease,atrial fibrillation,lesion location,and Fazekas classification of white matter lesions between the progression group and the non-progression group(all P＞0.05).While the NIHSS score at admission,proportion of poor collateral circulation,PIV and BAR in the progression group were significantly higher than those in the non-progression group(all P＜0.05).Multivariate Logistic regression analysis showed that high NIHSS score at admission(OR,1.177,95％CI 1.001-1.384,P=0.049),poor collateral circulation(OR,3.107,95％CI 1.216-7.939,P=0.018),high PIV(OR,1.006,95％CI 1.003-1.009,P=0.001),and high BAR(OR,1.610 × 109,95％CI 5.769 × 104-4.494 × 1013,P＜0.01)were independent risk factors of disease progression in patients with APACI.ROC curve analysis results showed that the area under the curve(AUC)of combination of PIV,BAR,collateral circulation and NIHSS score at admission for predicting disease progression in patients with APACI was 0.914(95％ CI0.861-0.952,P＜0.01),which was greater than that of each indicator(all P＜0.05).No statistically significant differences were found in smoking,drinking,hypertension,hyperlipidemia,coronary heart disease,atrial fibrillation,lesion location,and BAR between the poor prognosis and the good prognosis group(all P＞0.05).Compared with the good prognosis group,the poor prognosis group had significantly older age and higher proportion of patients with diabetes,NIHSS score at admission,proportion of patients with poor collateral circulation,and PIV(all P＜0.05).Moreover,the proportion of men in the poor prognosis group was lower than that in the good prognosis group(P=0.039).There was a statistically significant difference between the good prognosis group and the poor prognosis group in the Fazekas classification of white matter lesions(P＜0.01).Multivariate Logistic regression analysis showed that high NIHSS score at admission(OR,1.345,95％CI 1.081-1.674,P=0.008),poor collateral circulation(OR,3.903,95％CI 1.061-14.355,P=0.040),and high PIV(OR,1.011,95％CI 1.005-1.017,P＜0.01)were independent risk factors of poor prognosis in patients with APACI.The AUC for predicting poor prognosis in patients with APACI through combining PIV,collateral circulation and NIHSS score at admission was 0.911(95％CI 0.857-0.950,P＜0.01),which is greater than using poor collateral circulation or NIHSS score at admission alone(both P＜0.05).However,there was no statistically significant difference in AUC between the PIV,collateral circulation and NIHSS score combined predictive model and the PIV(alone)predictive model(P＞0.05).Conclusions High PIV,high BAR,poor collateral circulation,and high NIHSS score at admission were independent risk factors of disease progression in patients with APACI.Combination of these four indices demonstrates relatively high predictive value for disease progression.In addition,high PIV,poor collateral circulation,and high NIHSS score at admission are independent risk factors of poor prognosis in patients with APACI.Joint detection of the three indices may assist in short-term prognosis evaluation of patients with APACI.

In recent years, the increasing incidence of perinatal depression has become an important public health problem. In addition to the traditional social demographic factors, biological factors, obstetric factors, etc., the association between air pollution and perinatal depression (PND) has also attracted more and more attention. In this paper, studies on the association between air pollution and PND were reviewed, especially the associations of PND with ambient air pollutants such as PM_2.5, PM₁₀, NO₂, and O₃ as well as indoor air pollutants such as tobacco smoke, and the characteristics and possible biological mechanisms of the influence of different pollutants on PND were summarized. Based on the available studies, various outdoor air pollutants are associated with PND, and some pollutants may exhibit a dose-response relationship with it. As for indoor air pollution, studies only have focused on the impact of tobacco exposure on PND, and as yet, no study has explored the association between other indoor pollutants (e.g. cooking oil smoke and solid fuel) and PND. Current studies indicate that air pollution may act on PND through oxidative stress and neuroendocrine mechanisms, but the exact biological mechanism remains to be further studied. In the future, further studies should be encouraged on the epidemiological associations of other indoor air pollutants with PND and the interactions between other factors and air pollution on PND, and the underlying biological mechanisms, to provide new insights for the prevention of PND from the perspective of environmental health.

Objective To discuss the clinical features of dystonia manifested as Parkinsonism ( PKS) . Methods Clinical materials of a patient with dystonia manifested as PKS were analyzed retrospectively. Results The onset age of the young women was 31 years old, who was started asymmetrically with symptoms of claudication and tremor of the right foot. Levodopa had a short-term effect. The results of dopamine transporter ( DAT) PET showed that DAT in retrolentiform part were decreased significantly. Atypical Parkinson's disease was considered and she was treated as PKS long-termly. Subsequently, heterozygous mutation of c. 268-4T>A (NM_018105) in DYT6 gene was found through the next-generation sequencing, which was a kind of splicing mutation and confirmed by the first-generation sequencing. Conclusions Patients with dystonia might share similar clinical manifestations with PKS. Particularly, they should be differentiated with young-onset Parkinson's disease combined with focal dystonia. Clinical observation and genetic testing are important approaches to differentiate them.