Objective:To observe any differences in the brain′s functional responses during swallowing with healthy young, middle-aged and elderly individuals.Methods:Fifteen healthy young people formed the youth group, while 15 healthy middle-aged or elderly subjects were the middle-aged and elderly group. Both groups performed repeated swallowing tasks while being observed using functional near-infrared spectroscopy. The data were processed using NirSpark software, and brain activation was compared between the two groups.Results:Swallowing-related brain regions were all significantly activated in the youth group, while in the middle-aged and elderly group only the primary motor cortex (M1), primary somatosensory cortex (PSC), premotor and supplementary motor cortex (pSMC), and inferior central region on the left side showed significantly increased activation. Compared to the youth group, the middle-aged and elderly group exhibited significantly reduced activation in seven channels, including the right M1 and pSMC, the left M1, the pSMC, the PSC, the dorsolateral prefrontal cortex and frontal pole area.Conclusions:The middle-aged and elderly show significantly less activation in certain brain regions during swallowing compared with younger persons. That may be related to aging and its associated cognitive decline, as well as reduced motor and sensory abilities related to swallowing.

Objective:To explore the factors influencing the recovery of swallowing function after a brainstem hemorrhage and to construct a prediction model.Methods:Clinical data on 134 persons with dysphagia after a brainstem hemorrhage were collected retrospectively. According to their swallowing ability at discharge, the patients were divided into a swallowing recovery group and a non-recovery group. Univariate correlation analysis and multivariate logistic regression analysis were used to explore the independent factors influencing the recovery of swallowing function and to construct a prediction nomogram. The receiver operating characteristics (ROC) curves were evaluated to analyze the nomogram′s predictive value and those of the relevant influencing factors.Results:Sixty-two of the patients (46%) had recovered their swallowing function at discharge, while 72 (54%) had not. Univariate correlation analysis showed that there had been significant differences in tracheal intubation, NIHSS score, FOIS score, Barthel index and Glasgow coma scale (GCS )score between the two groups, on average. The multivariate logistic regressions showed that a low NIHSS score, a high FOIS score and a high GCS score were independent predictors of swallowing function recovery, so they were used in the prediction model. ROC curve analysis showed that the area under the curve (AUC) of the prediction model was 0.953 (95% CI: 0.902~0.982) with a sensitivity of 87% and a specificity of 93%. The model′s predictions were thus better than using an NIHSS score, GCS score or FOIS score alone. Conclusions:NIHSS score, GCS score and FOIS score can independently predict the recovery of swallowing function after a brainstem hemorrhage. A prediction model constructed using all three has good predictive power.

Objective:To observe any therapeutic effect of transcranial direct current stimulation (tDCS) combined with intermittent oroesophageal tube feeding (IOE) on dysphagia among ischemic stroke survivors.Methods:Eighty-four ischemic stroke survivors with dysphagia were randomized into an observation group and a control group, each of 42. In addition to conventional rehabilitation, swallowing training and IOE, the observation group received tDCS while the control group received sham stimulation. Before and after 14 days of this treatment, both groups′ swallowing, life quality and depression were evaluated using the Penetration Aspiration Scale (PAS), the Functional Oral Intake Scale (FOIS), the Dysphagia Handicap Index (DHI), and a 9-item patient health questionnaire (PHQ-9).Results:There were no significant differences between the two groups before the experiment in terms of their general data, their average PAS, FOIS, DHI or PHQ-9 scores, or the incidence of depression. After the treatment, significant improvement was observed in the above indicators among both groups, but with significantly better average PAS, FOIS, DHI [(51.25±6.78) vs. (44.78±5.75)] and PHQ-9 [(4.17±1.15) vs. (6.01±1.93)] scores and less depression (14.29% vs. 42.86%) in the observation group compared with the control group.Conclusions:Combining tDCS with IOE better improves swallowing function, depression, and life quality after an ischemic stroke.

Objective:To analyze the factors influencing the prognoses of stroke survivors with pseudobulbar palsy (PBP) dysphagia and construct a prediction model.Methods:Data on two hundred and fifty-one stroke survivors with PBP dysphagia were collected and analyzed retrospectively. The subjects were divided into a good prognosis group ( n=164) and a poor prognosis group ( n=87) according to the results of Kubota water swallowing tests administered at discharge. Their clinical data were analyzed using univariate correlation analysis, and the statistically significant independent variables found were further analyzed using multivariate logistic regression to obtain the important predictors of prognosis. R software was then used to assemble the useful factors into a nomogram prediction model. The area under the receiver operating characteristics (ROC) curve was employed to verify the model′s predictive power. Results:According to the univariate correlation analysis, significant differences were found between the two groups′ average National Institutes of Health Stroke Scale (NIHSS) scores, mouth opening grades and ages. The multivariate logistic regression analysis showed that NIHSS score, mouth opening grade and age could be useful and independent predictors of poor prognosis. The ROC curve analysis showed that the area under the curve for the nomogram model was 0.727, with a sensitivity of 59.8% and a specificity of 81.6%, suggesting that the model had good predictive power and was properly calibrated.Conclusions:NIHSS score, mouth opening grade and age are independent predictors of prognosis for stroke patients with PBP dysphagia. The nomogram model constructed in this study is of great value in developing a prognosis for such patients, which is helpful in the prevention and treatment of post-stroke dysphagia.

Objective:To analyze the factors influencing the prognoses of stroke survivors with pseudobulbar palsy (PBP) dysphagia and construct a prediction model.Methods:Data on two hundred and fifty-one stroke survivors with PBP dysphagia were collected and analyzed retrospectively. The subjects were divided into a good prognosis group ( n=164) and a poor prognosis group ( n=87) according to the results of Kubota water swallowing tests administered at discharge. Their clinical data were analyzed using univariate correlation analysis, and the statistically significant independent variables found were further analyzed using multivariate logistic regression to obtain the important predictors of prognosis. R software was then used to assemble the useful factors into a nomogram prediction model. The area under the receiver operating characteristics (ROC) curve was employed to verify the model′s predictive power. Results:According to the univariate correlation analysis, significant differences were found between the two groups′ average National Institutes of Health Stroke Scale (NIHSS) scores, mouth opening grades and ages. The multivariate logistic regression analysis showed that NIHSS score, mouth opening grade and age could be useful and independent predictors of poor prognosis. The ROC curve analysis showed that the area under the curve for the nomogram model was 0.727, with a sensitivity of 59.8% and a specificity of 81.6%, suggesting that the model had good predictive power and was properly calibrated.Conclusions:NIHSS score, mouth opening grade and age are independent predictors of prognosis for stroke patients with PBP dysphagia. The nomogram model constructed in this study is of great value in developing a prognosis for such patients, which is helpful in the prevention and treatment of post-stroke dysphagia.

Objective:To observe any differences in the brain′s functional responses during swallowing with healthy young, middle-aged and elderly individuals.Methods:Fifteen healthy young people formed the youth group, while 15 healthy middle-aged or elderly subjects were the middle-aged and elderly group. Both groups performed repeated swallowing tasks while being observed using functional near-infrared spectroscopy. The data were processed using NirSpark software, and brain activation was compared between the two groups.Results:Swallowing-related brain regions were all significantly activated in the youth group, while in the middle-aged and elderly group only the primary motor cortex (M1), primary somatosensory cortex (PSC), premotor and supplementary motor cortex (pSMC), and inferior central region on the left side showed significantly increased activation. Compared to the youth group, the middle-aged and elderly group exhibited significantly reduced activation in seven channels, including the right M1 and pSMC, the left M1, the pSMC, the PSC, the dorsolateral prefrontal cortex and frontal pole area.Conclusions:The middle-aged and elderly show significantly less activation in certain brain regions during swallowing compared with younger persons. That may be related to aging and its associated cognitive decline, as well as reduced motor and sensory abilities related to swallowing.

Objective:To explore the factors influencing the recovery of swallowing function after a brainstem hemorrhage and to construct a prediction model.Methods:Clinical data on 134 persons with dysphagia after a brainstem hemorrhage were collected retrospectively. According to their swallowing ability at discharge, the patients were divided into a swallowing recovery group and a non-recovery group. Univariate correlation analysis and multivariate logistic regression analysis were used to explore the independent factors influencing the recovery of swallowing function and to construct a prediction nomogram. The receiver operating characteristics (ROC) curves were evaluated to analyze the nomogram′s predictive value and those of the relevant influencing factors.Results:Sixty-two of the patients (46%) had recovered their swallowing function at discharge, while 72 (54%) had not. Univariate correlation analysis showed that there had been significant differences in tracheal intubation, NIHSS score, FOIS score, Barthel index and Glasgow coma scale (GCS )score between the two groups, on average. The multivariate logistic regressions showed that a low NIHSS score, a high FOIS score and a high GCS score were independent predictors of swallowing function recovery, so they were used in the prediction model. ROC curve analysis showed that the area under the curve (AUC) of the prediction model was 0.953 (95% CI: 0.902~0.982) with a sensitivity of 87% and a specificity of 93%. The model′s predictions were thus better than using an NIHSS score, GCS score or FOIS score alone. Conclusions:NIHSS score, GCS score and FOIS score can independently predict the recovery of swallowing function after a brainstem hemorrhage. A prediction model constructed using all three has good predictive power.

Objective:To observe any therapeutic effect of transcranial direct current stimulation (tDCS) combined with intermittent oroesophageal tube feeding (IOE) on dysphagia among ischemic stroke survivors.Methods:Eighty-four ischemic stroke survivors with dysphagia were randomized into an observation group and a control group, each of 42. In addition to conventional rehabilitation, swallowing training and IOE, the observation group received tDCS while the control group received sham stimulation. Before and after 14 days of this treatment, both groups′ swallowing, life quality and depression were evaluated using the Penetration Aspiration Scale (PAS), the Functional Oral Intake Scale (FOIS), the Dysphagia Handicap Index (DHI), and a 9-item patient health questionnaire (PHQ-9).Results:There were no significant differences between the two groups before the experiment in terms of their general data, their average PAS, FOIS, DHI or PHQ-9 scores, or the incidence of depression. After the treatment, significant improvement was observed in the above indicators among both groups, but with significantly better average PAS, FOIS, DHI [(51.25±6.78) vs. (44.78±5.75)] and PHQ-9 [(4.17±1.15) vs. (6.01±1.93)] scores and less depression (14.29% vs. 42.86%) in the observation group compared with the control group.Conclusions:Combining tDCS with IOE better improves swallowing function, depression, and life quality after an ischemic stroke.

Objective:To explore the risk factors for malnutrition after a tracheotomy and to construct a predictive model useful for its prevention through early intervention.Methods:Clinical data describing 440 tracheotomy patients were subjected to a retrospective analysis. The variables examined were age, sex, etiology, Glasgow Coma Score (GCS), activities of daily living (ADL) score, age-corrected Charlson comorbidity index (aCCI), food intake, swallowing function, incidence of infections, as well as any history of diabetes mellitus, hypertension, smoking or alcohol consumption. Patients identified as being at risk of malnutrition (NRS-2002≥3) were screened using the Nutritional Risk Screening tool (NRS-2002) and the European Society of Clinical Nutrition and Metabolism′s ESPEN2015 criteria. The subjects were thus categorized into a malnutrition group of 343 and a control group of 97. Unifactorial and multifactorial logistic regression analyses were performed, and stepwise regression was applied to include the factors found significant in the unifactorial analysis into the multifactorial logistic regression analysis, and to construct a column-line graph prediction model. The clinical utility of the model was assessed by applying the receiver operator characteristics (ROC) curves, calibration plots and decision curve analysis (DCA).Results:Of the 440 persons studied, 343 (78%) were malnourished. The multivariate logistic regression analysis showed that pulmonary infection, dysphagia, low GCS score and high aCCI score were significant risk factors for malnutrition after a tracheotomy. A prediction nomograph was constructed. After fitting and correcting, the area under the curve (AUC) of the prediction model′s ROC curve was 0.911, the specificity was 80.4%, and the sensitivity was 91.3%. That was significantly higher than the AUCs for pulmonary infection (0.809), dysphagia (0.697), aCCI (0.721) and GCS (0.802). Bootstrap self-sampling was used to verify the model internally. After 1000 samples the average absolute error between the predicted risk and the actual risk was 0.013, indicating good prediction ability. The DCA results demonstrated that the model has substantial clinical applicability across a range of nutritional interventions, particularly for threshold probability values ranging from 0 to 0.96.Conclusion:Pulmonary infection, dysphagia, low GCS score, and high aCCI score are risk factors for malnutrition among tracheotomy patients. The nomogram model constructed in this study has good predictive value for the occurrence of malnutrition among such patients.

Objective:To establish ultra performance liquid chromatography (UPLC) characteristic chromatogram of Pulsatilla chinensis; To provide reference for the origin identification and quality control of Pulsatilla chinensis. Methods:UPLC Method was adopted. The determination was performed on a column of Agilent SB C18 (2.1 mm×100 mm, 1.8 μm) . The mobile phase was acetonitrile-methanol (2:1) -0.1% phosphoric acid solution by fradient elution at a flow rate of 0.30ml/min. The column temperature was 30 ℃. The detection wavelength was 215 nm. The injection volume was 2 μl. The common counterfeit products and medicinal herbs of Pulsatilla chinensis from different areas were evaluated by comparison of characteristic chromatogram, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). Results:There were 9 characteristic peaks in the characteristic chromatogram of Pulsatilla chinensis, and 8 common peaks were identified by high resolution mass spectrometry and comparison of reference materials. Through PCA analysis, it was possible to clearly distinguish the medicinal herbs of Pulsatilla chinensis from different areas. Combined with OPLS-DA analysis, it was found that peak 2, peak 3, peak 6 were the main markers of Pulsatilla chinensis from different producing areas. Conclusion:The established method has good specificity, repeatability and durability, and it can effectively distinguish the common counterfeits of Pulsatilla chinensis, and provide the basis of quality control and selection of origin for Pulsatilla chinensis.