Obstructive sleep apnea (OSA) is a sleep disorder characterized by recurrent upper respiratory tract obstruction, sleep fragmentation, and hypoxia during sleep. This disease often leads to cognitive, emotional, and memory related neurological damage, and its mechanism is closely associated with the disruption of the blood-brain barrier (BBB). This article mainly discusses the relationship between BBB damage caused by OSA and vascular cognitive impairment (VCI), as well as the role of early prevention, intervention, and repairing BBB on reducing VCI.

Post-stroke cognitive impairment (PSCI) refers to a clinical syndrome that occurs after a stroke and meets the diagnostic criteria for cognitive impairment, lasting for more than 6 months, and seriously affecting the daily life of patients. The complement system has been confirmed to be associated with PSCI. This article reviews the correlation between complement system and PSCI, as well as the possibility of complement system as an intervention target for PSCI.

Objective:To investigate the correlation between paroxysmal slow-wave events (PSWEs) and cerebral small vessel disease (CSVD) and CSVD-related cognitive impairment.Methods:Patients with CSVD visited Weihai Municipal Hospital from March 2021 to April 2022 were included, and sex- and age-matched healthy controls were recruited for cross-sectional analysis. The patients with CSVD were further divided into cognitive impairment group and non-cognitive impairment group. The self-developed Python script was used to detect the PSWE parameters in electroencephalogram records. Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) were used to evaluate cognitive function. Multivariate logistic regression analysis was used to determine whether PWSE parameters were the independent related factors of CSVD and CSVD-related cognitive impairment. Multiple linear regression analysis was used to determine the correlation between the PSWE parameters and overall cognitive function (MoCA total score) in patients with CSVD. Results:A total of 76 patients with CSVD (including 41 patients with cognitive impairment and 35 patients without cognitive impairment) and 45 healthy controls were included. Compared with the healthy control group, PWSEs in the F3 (left frontal area) and O1 (left occipital area) regions of the CSVD group occurred more frequently and lasted longer (all P<0.05). Multivariate logistic regression analysis showed that the frequency (odds ratio [ OR] 1.080, 95% confidence interval [ CI] 1.023-1.140; P=0.005) and duration ( OR 1.006, 95% CI 1.001-1.011; P=0.023) of PWSEs in the left frontal area, as well as the frequency ( OR 1.052, 95% CI 1.010-1.095; P=0.014) and duration ( OR 1.003, 95% CI 1.000-1.006; P=0.028) of PWSEs in the left occipital region were the independent related factors for CSVD. The frequency ( OR 1.106, 95% CI 1.033-1.183; P=0.004) and duration ( OR1.010, 95% CI 1.003-1.017; P=0.004) of PWSEs in the left frontal area were the independent risk factors for cognitive impairment in patients with CSVD. Multiple linear regression analysis showed that the frequency ( β= –0.242, P=0.045) and duration ( β= –0.235, P=0.046) of PWSEs in the left frontal region were negatively correlated with the overall cognitive function score in patients with CSVD. Conclusions:The frequency and duration of PSWEs in some brain regions of patients with CSVD increase, and there is an independent correlation between PSWEs and cognitive impairment, suggesting that the damage of blood-brain barrier may participate in the pathogenesis of cognitive impairment in patients with CSVD.

Objective:To investigate the value of 18F-FDG PET/CT imaging signs and metabolic parameters in predicting tumor spread through air spaces (STAS) of stage Ⅰ lung adenocarcinoma. Methods:From January 2019 to December 2021, clinical, imaging and metabolic parameters of 381 patients (126 males, 255 females, age (61.2±9.2) years) with stage Ⅰ lung adenocarcinoma were retrospectively analyzed in the Affiliated Hospital of Qingdao University. According to the postoperative pathological results, patients were divided into STAS positive group and STAS negative group. According to the operation time, patients were divided into training set ( n=254) and verification set ( n=127). χ2 test or Mann-Whitney U test was used to compare the differences of different parameters between patients with STAS positive and negative, and binary logistic regression analysis was used to select the predictors of STAS status. The prediction model was established, and ROC curve was used to evaluate the predictive efficacy. Results:There were 49(19.3%, 49/254) patients with STAS positive and 205(80.7%, 205/254) patients with STAS negative in the training set, while those were 35(27.6%, 35/127) and 92(72.4%, 92/127) in the verification set. In the training set, the differences of age ( z=-2.30, P=0.021), type of lesions ( χ2=6.81, P=0.009), spiculation ( χ2=12.64, P<0.001), bronchus truncation ( χ2=6.98, P=0.008), ground glass ribbon sign ( χ2=26.93, P<0.001) and SUV max ( z=-4.62, P<0.001) between the two groups were statistically significant. Multivariate logistic regression analysis showed that age (odds ratio ( OR)=1.048, 95% CI: 1.004-1.094, P=0.032), ground glass ribbon sign ( OR=3.857, 95% CI: 1.693-8.788, P=0.001) and SUV max ( OR=1.133, 95% CI: 1.001-1.282, P=0.049) were independent predictors of STAS status in stage Ⅰ lung adenocarcinoma patients. The logistic regression model was P=1/(1+ e - x), x=-5.292+ 0.480×age (year)+ 1.493×ground glass ribbon sign+ 0.170×SUV max. The AUCs of the model in the training set and verification set were 0.770 and 0.801, with the sensitivity of 81.6%(40/49) and 82.9%(29/35), and the specificity of 69.8%(143/205) and 65.2%(60/92), respectively. Conclusion:Age, ground glass ribbon sign and SUV max have good predictive effects on the occurrence of STAS in stage Ⅰ lung adenocarcinoma.

Objective:To investigate the correlation between heart rate variability (HRV) and early neurological deterioration (END) and poor outcomes in patients with branch atheromatous disease (BAD).Methods:Patients with BAD admitted to the Department of Neurology, Weihai Municipal Hospital from September 2020 to September 2022 were enrolled prospectively. END was defined as an increase of ≥2 points in the total score of the National Institutes of Health Stroke scale (NIHSS) or an increase of ≥1 in motor item score within 72 h of admission compared with the baseline. Poor outcome was defined as the score of the modified Rankin Scale >2 at 6 months after the onset. Multivariate logistic regression analysis was used to determine whether HRV parameters were the independent influencing factors of END and poor outcomes in patients with BAD. Results:A total of 117 patients with BAD were enrolled, including 76 males (65.0%), aged 64.27±6.95 years. Thirty-eight patients (32.4%) had END, and 21 (17.9%) had poor outcomes. Percentage of the number of pairs of adjacent R-R intervals differentiating by more than 50 ms (pNN50), number of adjacent R-R intervals differentiating by more than 50 ms (NN50), power in low frequency range (LF) and power in high frequency range (HF) in the END group were significantly lower than those in the non-END group, and the LF/HF ratio was significantly higher than the non-END group (all P<0.05). The standard deviation of the R-R interval (SDNN), standard deviation of the average of R-R intervals in all 5-min segments (SDANN), and HF in the poor outcome group were significantly lower than those in the good outcome group. Multivariate logistic regression analysis showed that HF (odds ratio [ OR] 0.994, 95% confidence interval [ CI] 0.991-0.998; P<0.001) was an independent protective factor of END in patients with BAD, and LF/HF ratio ( OR 1.455, 95% CI 1.056-2.005; P=0.022) was an independent risk factor for END in patients with BAD; SDANN ( OR 0.997, 95% CI 0.993-0.999; P=0.023) was an independent protective factor of good outcomes in patients with BAD. Conclusion:HF and LF/HF ratios are the independent influencing factors of END in patients with BAD, and SDANN is an independent influencing factor of the poor outcomes in patients with BAD, suggesting that autonomic dysfunction is involved in the pathophysiological mechanism of END and poor outcomes in patients with BAD.

Objective:To investigate the effect of the possibility of sleep-disordered breathing (SDB) as assessed by the four-variable score on the platelet function and the risk of stroke recurrence in patients with acute ischemic stroke.Methods:Patients with acute ischemic stroke admitted to the Department of Neurology, Weihai Municipal Hospital from January 2020 to January 2021 were enrolled prospectively. Main inclusion criteria: admission within 24 h of onset; National Institutes of Health Stroke Scale score ≤3; Receiving aspirin + clopidogrel dual antiplatelet therapy. All patients were divided into a high possibility group and a low possibility group of SDB according to the four-variable score. 7±2 d after dual antiplatelet therapy, PL-12 multi-parameter platelet function analyzer was used to detect the maximum aggregation rate (MAR). The patients were followed up for 6 months after discharge and the recurrence of ischemic stroke was observed. The mediating effect model was established with the high possibility of SDB as the independent variable, MAR as the intermediary variable and stroke recurrence as the dependent variable. Firstly, MAR as the dependent variable and high probability of SDB as the independent variable were analyzed by linear regression; then, a binary logistic regression analysis was performed with ischemic stroke recurrence as the dependent variable and the high probability of SDB and MAR as independent variables. Results:A total of 213 patients were enrolled in the study. The average age of the patients was 62.70 ± 10.04 years old. There were 146 male (68.5%) and 121 patients (56.8%) were in the high possibility group (56.8%). During the follow-up period, 24 patients (11.3%) had stroke recurrence. Univariate analysis showed that arachidonic acid (AA) induced MAR (MAR-AA) and adenosine diphosphate (ADP) induced the MAR (MAR-ADP) in the high possibility group of SDB were significantly higher than those in the low possibility group (all P<0.05); MAR-AA and MAR-ADP in the recurrent group were significantly higher than those in the non-recurrent group (all P<0.05), and the proportion of high possibility of SDB in the recurrent group was significantly higher ( P=0.008). Binary logistic regression analysis showed that homocysteine (odds ratio 1.132, 95% confidence interval 1.048-1.223; P=0.002) and having high possibility of SDB (odds ratio 6.351, 95% confidence interval 1.134-35.566; P=0.035) were the independent risk factors for stroke recurrence in patients treated with dual antiplatelet therapy. Intermediary effect analysis showed that MAR had a significant intermediary effect on the risk of stroke recurrence in patients with high probability of SDB. Conclusion:The MAR and stroke recurrence rates in the high possibility group of SDB were significantly higher than those in the low possibility group, and its stroke risk was probably mediated by platelet hyperreactivity.

Objective:To explore the classification performance of combined model constructed from CT signs combined with radiomics for discriminating COVID-19 pneumonia and other viral pneumonia.Methods:The clinical and CT imaging data of 181 patients with viral pneumonia confirmed by reverse transcription-polymerase chain reaction in 15 hospitals of Yunnan Province from March 2015 to March 2020 were analyzed retrospectively. The 181 patients were divided into COVID-19 group (89 cases) and non-COVID-19 group (92 cases), which were further divided into training cohort (126 cases) and test cohort (55 cases) at a ratio of 7∶3 using random stratified sampling. The CT signs of pneumonia were determined and the radiomics features were extracted from the initial unenhanced chest CT images to build independent and combined models for predicting COVID-19 pneumonia. The diagnostic performance of the models were evaluated using receiver operating characteristic (ROC) analysis, continuous net reclassification index (NRI) calibration curve and decision curve analysis.Results:The combined models consisted of 3 significant CT signs and 14 selected radiomics features. For the radiomics model alone, the area under the ROC curve (AUC) were 0.904 (sensitivity was 85.5%, specificity was 84.4%, accuracy was 84.9%) in the training cohort and 0.866 (sensitivity was 77.8%, specificity was 78.6%, accuracy 78.2%) in the test cohort. After combining CT signs and radiomics features, AUC of the combined model for the training cohort was 0.956 (sensitivity was 91.9%, specificity was 85.9%, accuracy was 88.9%), while that for the test cohort was 0.943 (sensitivity was 88.9%, specificity was 85.7%, accuracy was 87.3%). The AUC values of the combined model and the radiomics model in the differentiation of COVID-19 group and the non-COVID-19 group were significantly different in the training cohort ( Z=-2.43, P=0.015), but difference had no statistical significance in the test cohort ( Z=-1.73, P=0.083), and further analysis using the NRI showed that the combined model in both the training cohort and the test cohort had a positive improvement ability compared with radiomics model alone (training cohort: continuous NRI 1.077, 95 %CI 0.783-1.370; test cohort: continuous NRI 1.421, 95 %CI 1.051-1.790). The calibration curve showed that the prediction probability of COVID-19 predicted by the combined model was in good agreement with the observed value in the training and test cohorts; the decision curve showed that a net benefit greater than 0.6 could be obtained when the threshold probability of the combined model was 0-0.75. Conclusion:The combination of CT signs and radiomics might be a potential method for distinguishing COVID-19 and other viral pneumonia with good performance.

Objective:To investigate the correlation between heart rate variability (HRV) and cerebral small vessel disease (CSVD) in patients with obstructive sleep apnea (OSA).Methods:Patients with OSA received polysomnography and brain MRI examination in Weihai Municipal Hospital from July 2019 to July 2020 were consecutively collected for cross-sectional analysis. The 5 min HRV before sleep (awake state) was analyzed. The patients were divided into CSVD group and non-CSVD group according to the overall burden of CSVD. The demographic data, clinical data, polysomnography parameters and HRV time domain and frequency domain parameters were compared between the two groups. Multivariate logistic regression analysis was used to determine the correlation between the HRV parameters and CSVD in patients with OSA. Results:A total of 100 patients with OSA were enrolled, including 79 males (79.0%), aged 52.36±8.66 years, apnea hypopnea index (AHI) 38.70±24.65/h. There were 46 patients (46.0%) in the CSVD group and 54 (54.0%) in the non-CSVD group. Univariate analysis showed that there were significant differences in age, AHI, oxygen desaturation index (ODI), percentage of blood oxygen saturation <90% in total sleep time (T90), square root of the mean of the sum of the squares of the difference between adjacent RR intervals (RMSSD), power in high frequency range (HF), power in low frequency range (LF) to HF ratio (LF/HF) between the CSVD group and the non-CSVD group (all P<0.05). Multivariate logistic regression analysis showed that after adjusting for age, body mass index, systolic blood pressure, AHI, ODI, and T90, RMSSD (odds ratio 0.625, 95% confidence interval 0.389-0.981; P=0.041) and LF/HF ratio (odds ratio 1.429, 95% confidence interval 1.011-2.020; P=0.043) were the independent influencing factors of CSVD in patients with OSA. Conclusion:Increased LF/HF and decreased RMSSD in OSA patients with CSVD suggest that the increased sympathetic excitability and decreased vagus function, which may be one of the pathophysiological mechanisms of occurring CSVD in patients with OSA.

Objective:To investigate the correlation between heart rate variability (HRV) and cognitive impairment in patients with obstructive sleep apnea (OSA).Methods:Patients received polysomnography in Weihai Municipal Hospital from June 2019 to November 2020 were enrolled as the subjects of cross-sectional analysis. According to the Montreal Cognitive Assessment score, the patients with OSA were divided into a cognitive impairment group and a non-cognitive impairment group. Multivariate logistic regression analysis was used to determine whether HRV parameters were the independent influencing factors of cognitive impairment in patients with OSA. Multiple linear regression analysis was used to determine the independent correlation between HRV parameters and overall cognition as well as each cognitive domain in patients with OSA. Results:A total of 115 patients with OSA were included, including 80 males (69.6%), aged 58.25±9.88 years. Among them, there were 61 in the cognitive impairment group (53.0%) and 54 in the non-cognitive impairment group (47.0%). The standard deviation of the R-R interval in normal sinus beats (SDNN), the square root of the mean of the sum of the squares of the difference between adjacent NN intervals (RMSSD), the percentage of the number of pairs of adjacent R-R intervals differing by more than 50 ms (pNN50) and the power in high-frequency range (HF; 0.15-0.40 Hz) in the cognitive impairment group were significantly lower than those in non-cognitive impairment group (all P<0.05). Multivariate logistic regression analysis showed that SDNN (odds ratio [ OR] 0.551, 95% confidence interval [ CI] 0.380-0.798; P=0.002), RMSSD ( OR 0.516, 95% CI 0.342-0.779; P=0.002), pNN50 ( OR 0.900, 95% CI 0.834-0.971; P=0.006), LF ( OR 0.821, 95% CI 0.687-0.982; P=0.030) and HF ( OR 0.687, 95% CI 0.525-0.899; P=0.006) were the independent protective factors of cognitive impairment in patients with OSA. Multiple linear regression analysis showed that SDNN ( β=0.208, P=0.023), RMSSD ( β=0.228, P=0.011), pNN50 ( β=0.186, P=0.040), HF ( β=0.235, P=0.010) is independently correlated with overall cognitive function in patients with OSA. Conclusion:The decline of HRV parameters SDNN, RMSSD, pNN50 and HF is independently correlated with cognitive impairment in patients with OSA, suggesting that the decline of vagus nerve function may be involved in the mechanism of cognitive impairment in patients with OSA.

Objective:To establish and validate a malignant risk prediction model of solitary pulmonary nodules (SPNs) with pulmonary fibrosis in long-term smokers based on 18F-flurodeoxyglucose (FDG) PET/CT. Methods:PET/CT images of 222 SPNs combined with pulmonary fibrosis which were shown in integrated CT scan in 169 patients (all males; age 68(63, 75) years) were analyzed retrospectively. All patients were examined in PET/CT Center of the Affiliated Hospital of Qingdao University from January 2011 to December 2019 and all had definite smoking history. The benign and malignant nodules were judged according to the pathological diagnosis or follow-up imaging data of lung lesions (follow-up≥2 years). The clinical characteristics (age, smoking index), morphological characteristics (longest diameter of lesion, density, location, distribution, relative position of fibrosis, spiculation, lobulation, calcification, vacuole, vascular convergence, pleural indentation, emphysema and severity of bilateral pulmonary fibrosis) and metabolic characteristics (maximum standardized uptake value (SUV max)) of the benign and malignant lesions were analyzed by χ2 test and Mann-Whitney U test. Then multivariate logistic regression analysis was applied to select independent risk factors of malignant nodules, and a risk prediction model was established and verified by the area under the receiver operating characteristic (ROC) curve and k-fold cross validation ( k=10) respectively. Results:Among 169 patients, 222 SPNs were detected (157 malignant nodules, 65 benign nodules). Univariate analysis showed that smoking index, speculation, lobulation, vascular convergence sign, calcification, emphysema, nodule size, relative position of nodule and fibrosis, SUV max and severity of bilateral pulmonary fibrosis were significantly different between the benign and malignant nodules ( z values: 2.514-9.858, χ2 values: 4.353-18.442, all P<0.05). Result of multivariate logistic regression analysis showed that calcification, vascular convergence and SUV max were the independent risk factors of malignant nodules combined with pulmonary fibrosis (odds ratio ( OR): 0.048-2.534, all P<0.05). The risk prediction model was as follow: P=1/(1+ e - x), x=-1.839-3.033×calcification+ 0.930×vascular convergence+ 0.754×SUV max(with calcification/vascular convergence=1, without calcification/vascular convergence=0). The area under ROC curve was 0.932(95% CI: 0.895-0.969), and the sensitivity and specificity of the model were 87.9% and 86.2%, respectively. Results of k-fold cross validation showed that the prediction accuracy of 10 test sets was 0.847±0.075, and was 0.862±0.010 in training sets. Conclusions:Calcification, vascular convergence and SUV max are independent risk factors of malignant SPNs combined with pulmonary fibrosis in long-term asymptomatic smokers. The model based on the above variables presents high diagnostic efficiency in diagnosing malignant SPNs.