Objective:Cognitive impairment is one of the common complications of stroke,which can affect the rehabili-tation and their quality of life.It is very important to build reliable risk prediction model tools to detect post-stroke cognitive impairment(PSCI)in advance,but there is still no clinical risk prediction model for PSCI.Our aim was to identify the influencing factors of PSCI in convalescent stroke patients and construct a nomo-gram model for predicting the risk of PSCI based on these factors.Method:We retrospectively collected the demographic characteristics and clinically relevant data of convales-cent stroke patients hospitalized in Guangdong Provincial Hospital of Chinese Medicine from December 2019 to December 2022.Then we randomly divided the whole data set into the training set and the validation set according to 7:3,the former data was used to construct a nomogram model for predicting the risk of PSCI,and the latter data was used to evaluate the model performance.Univariate and multivariate logistic regression were used to analyze the factors affecting PSCI in convalescent stroke patients.Based on these factors,we used the R software to construct a PSCI risk prediction model who was visualized through a nomogram.The model performance was evaluated using the area under the curve(AUC),sensitivity,specificity,calibration curve,and decision curve analysis(DCA).Result:Our prediction model indicated that age,right hemiparesis,hypertension,coronary heart disease,hyper-homocysteinemia,Fugl-Meyer assessment scale(FMA)score,modified Barthel index(MBI)score and,mean cor-puscular hemoglobin were independent factors influencing the occurrence of PSCI in convalescent stroke pa-tients.The AUC,sensitivity and specificity of the model were 0.804,75.5％and 73.7％in the training set,and 0.737,82.9％and 62.8％in the validation set,suggesting that the model had a good discrimination.The calibra-tion curve of the training and validation sets indicated a good consistency between the prediction and the real observation.The decision curve analysis of the training and validation sets showed that the PSCI risk prediction model performed well in terms of the net clinical benefit.Conclusion:The PSCI risk prediction nomogram model constructed in this study can be personalize prediction of cognitive impairment probabilities in convalescent stroke patients,which can help healthcare providers to de-tect and treat PSCI early and improve patient outcome.

OBJECTIVE: To investigate the effect of electroacupuncture (EA) on neurological function in rats with cerebral ischemia-reperfusion injury (CIRI) by regulating adenosine monophosphate-activated protein kinase (AMPK)/mammalian target of rapamycin (mTOR)/Unc-51-like kinase 1 (ULK1) signaling pathway. METHODS: Thirty-three male SD rats were randomly divided into a sham-operation group, a model group and an EA group, with 11 rats in each group. The right middle cerebral artery occlusion/reperfusion (MCAO/R) model was prepared by thread occlusion method in the model group and the EA group. In the sham-operation group, no thread was inserted after vascular separation. After the success of modeling, in the EA group, EA was applied to "Baihui" (GV 20) and "Zusanli" (ST 36) on the affected side, with disperse-dense wave, the frequency of 2 Hz/15 Hz, for 20 min, once a day. EA was delivered continuously for 3 days. On day 1 and day 3 of operation, the score of the modified neurological deficit scale (mNSS) was evaluated. After intervention completion, the cerebral infarction area was measured by the thiazolyl blue tetrazolium chloride (TTC) method. Nissl staining was used to observe the damage of cortical neurons on the ischemic side in each group. Using transmission electron microscopy, the ultrastructure of cortical neurons on the ischemic side was observed. With the immunofluorescence method adopted, the positive expression of the related protein 1 light chain 3 (LC3) and benzyl chloroform (Beclin-1) on the ischemic side was detected. The protein expression of p-AMPK, AMPK, p-mTOR, mTOR, pS757-ULK1, ULK1 and chelating ligand 1 (p62) in the ischemic cortex was detected using Western blot method. RESULTS: ① Compared with the sham-operation group, in the model group, the mNSS score increased (P<0.01), the percentage of infarction area was increased (P<0.01); the cortical neurons on the ischemic side were loosely distributed, with karyopyknosis and vacuolization, and the number of neurons was reduced (P<0.01); the cells were swollen and ruptured, mitochondrial shrunk, electron density higher, and there were a large number of autophagic debris. The positive expression of LC3 and Beclin-1 was elevated (P<0.01), and p-mTOR/mTOR, pS757-ULK1/ULK1 and the protein expression of p62 dropped (P<0.01) in the ischemic cortex. ② Compared with the model group, in the EA group, the mNSS score was reduced (P<0.05). The percentage of cerebral infarction area was descreased (P<0.01); and the neurons were regularly distributed, the number of neurons increased (P<0.01), the structure of mitochondria was clearer, the crest fracture alleviated, and the damage of neurons attenuated. The positive expression of LC3 and Beclin-1 was dropped (P<0.01), and p-AMPK/AMPK reduced (P<0.05), and p-mTOR/ mTOR, pS757-ULK1/ULK1 and the protein expression of p62 increased (P<0.01) in the ischemic cortex. CONCLUSION EA at "Baihui" (GV 20) and "Zusanli" (ST 36) inhibits autophay, attenuates neurological deficit and cerebral pathological damage in CIRI rats to protect the nerves, which may be obtained by regulating AMPK/mTOR/ULK1 signaling pathway.
Animals ; Electroacupuncture ; Male ; Rats ; TOR Serine-Threonine Kinases/genetics* ; Rats, Sprague-Dawley ; Autophagy-Related Protein-1 Homolog/genetics* ; Reperfusion Injury/metabolism* ; Signal Transduction ; AMP-Activated Protein Kinases/genetics* ; Brain Ischemia/metabolism* ; Humans ; Acupuncture Points

Objective:Cognitive impairment is one of the common complications of stroke,which can affect the rehabili-tation and their quality of life.It is very important to build reliable risk prediction model tools to detect post-stroke cognitive impairment(PSCI)in advance,but there is still no clinical risk prediction model for PSCI.Our aim was to identify the influencing factors of PSCI in convalescent stroke patients and construct a nomo-gram model for predicting the risk of PSCI based on these factors.Method:We retrospectively collected the demographic characteristics and clinically relevant data of convales-cent stroke patients hospitalized in Guangdong Provincial Hospital of Chinese Medicine from December 2019 to December 2022.Then we randomly divided the whole data set into the training set and the validation set according to 7:3,the former data was used to construct a nomogram model for predicting the risk of PSCI,and the latter data was used to evaluate the model performance.Univariate and multivariate logistic regression were used to analyze the factors affecting PSCI in convalescent stroke patients.Based on these factors,we used the R software to construct a PSCI risk prediction model who was visualized through a nomogram.The model performance was evaluated using the area under the curve(AUC),sensitivity,specificity,calibration curve,and decision curve analysis(DCA).Result:Our prediction model indicated that age,right hemiparesis,hypertension,coronary heart disease,hyper-homocysteinemia,Fugl-Meyer assessment scale(FMA)score,modified Barthel index(MBI)score and,mean cor-puscular hemoglobin were independent factors influencing the occurrence of PSCI in convalescent stroke pa-tients.The AUC,sensitivity and specificity of the model were 0.804,75.5％and 73.7％in the training set,and 0.737,82.9％and 62.8％in the validation set,suggesting that the model had a good discrimination.The calibra-tion curve of the training and validation sets indicated a good consistency between the prediction and the real observation.The decision curve analysis of the training and validation sets showed that the PSCI risk prediction model performed well in terms of the net clinical benefit.Conclusion:The PSCI risk prediction nomogram model constructed in this study can be personalize prediction of cognitive impairment probabilities in convalescent stroke patients,which can help healthcare providers to de-tect and treat PSCI early and improve patient outcome.

OBJECTIVETo observe the clinical effect of acupuncture at Baihui(GV 20) and Shenting(GV 24) combined with rehabilitation for post-stroke cognitive impairment(PSCI).

METHODSFifty patients with PSCI were randomly assigned to an observation group and a control group,25 cases in each one. In the control group,basic treatment and regular rehabilitation were applied. In the observation group,acupuncture at Baihui(GV 20) and Shenting(GV 24) and the same therapies as the control group were used for continuous four weeks,once a day and five times a week. Mini-mental state examination(MMSE) and Montreal cognitive assessment(MoCA) were observed before and after treatment in the two groups.

RESULTSAfter treatment,the scores of MMSE and MoCA were improved apparently(both<0.05),with better results in the observation group(both<0.05).

CONCLUSIONSAcupuncture at Baihui(GV 20) and Shenting(GV 24) combined with basic treatment and regular rehabilitation can obviously improve the cognitive function of PSCI,and the effect is superior to that of basic treatment and regular rehabilitation.

Objective To observe the therapeutic effect of consciousness-restoring needling combined with comprehensive rehabilitation training on motor function and the activities of daily living of poststroke patients with hemiplegia. Methods Sixty qualified patients were evenly randomized into observation group and control group. All of the patients were given conventional medicine treatment and conventional rehabilitation training, and the treatment group was given consciousness-restoring needling additionally. The therapeutic effects were compared at the end of first session of treatment for 4 weeks and 12 weeks after the first session of treatment. The Fugl-Meyer motor assessment scale (FMA), modified Barthel Index (MBI) and Stroke-Specific Quality of Life Scale ( SS-QQL) were taken as the main evaluation indexes. Results The differences of FMA, MBI and SS-QOL scores were insignificant between the two groups before treatment ( P>0.05). At the end of treatment for 4 weeks, FMA, MBI and SS-QOL scores were increased in the two groups (P<0.05), and the increase was more obvious in the observation group (P<0.05). The results of follow-up till the 12th week showed that FMA, MBI and SS-QOL scores were still higher than the baseline level ( P<0.05). Conclusion Consciousness-restoring needling combined with comprehensive rehabilitation training has better effect on improving motor function and the activities of daily living of poststroke hemiplegia patients than comprehensive rehabilitation training alone.