Based on the theory of collateral disease， the treatment of late-stage sequela of cerebrovascular disease is considered to be primarily associated with deficiency and obstruction of cerebral collaterals and dysfunction of the spirit mechanism. Therefore， the fundamental therapeutic principle is to unblock and supplement the brain collaterals. Clinically， the late-stage sequelae of cerebrovascular disease are classified into four patterns， which are malnourishment， deficiency-heat， stasis obstruction， and phlegm clouding of brain collaterals. These are treated respectively with Tiansui Tongqiao Decoction （填髓通窍汤） to supplement essence and nourish the brain through moistening， unblocking and supplementing， Qingnao Touluo Decoction （清脑透络汤） to enrich yin， regulate spirit， and unblock collaterals through clearing and penetrating， Yiqi Tongluo Decoction （益气通络汤） to tonify qi and resolve stasis while softening tendons and unblocking collaterals， and Xinrun Touqiao Beverage （辛润透窍饮） to unblock and tonify yin and yang while unblocking the collaterals through acrid-moistening medicinals. Flexible modification of prescriptions according to individual symptoms was applied， resulting in favorable therapeutic outcomes.

This article summarizes the clinical experience in diagnosing and treating narcolepsy based on the wei qi theory. The key pathogenesis of narcolepsy is considered to be the disharmony of wei qi. In the initial stage， lung， spleen， and kidney deficiency leads to insufficient generation and propulsion of wei qi. In the progressive stage， phlegm-damp and qi stagnation obstruct sanjiao （三焦）， while the interstice of flesh is unrelaxed， and the skin pores are occluded， causing sluggish circulation of wei qi. In the attack stage， pathogens obstruct the upper jiao （焦）， whereas pectoral qi fails to diffuse， and wei qi becomes constrained and blocked in the yin aspect， which may transform into wind or heat and bind with phlegm and stasis， resulting in sudden excessive sleep， cataplexy， dream disturbance， hallucinations， and sleep paralysis. Accordingly， a three-stage differentiation and treatment strategy is proposed， including reinforcing the root and strengthening wei qi in the initial stage with Peiben Shiwei Decoction （培本实卫汤）， resolving phlegm and unblocking the pathways to smooth the flow of wei qi in the progressive stage with Tongjiao Dawei Decoction （通焦达卫汤）， and diffusing wei qi， awakening the spirit， and opening the upper jiao in the attack stage with Xuanwei Xingshen Decoction （宣卫醒神汤）. Clinically， treatment should distinguish deficiency from excess， the primary from the secondary， administer staged and dynamic treatments， and make good use of light， clear， ascending， dispersing， acrid， and aromatic medicinals to restore the movement of wei qi， thereby providing a reference for differentiation and treatment of narcolepsy in traditional Chinese medicine.

BackgroundMigraine is a common chronic neurological disease， and patent foramen ovale （PFO） has been closely associated with migraine. Current research primarily focuses on the pathological mechanism and the therapeutic effects of interventional closure， with limited attention paid to the impact of PFO on sleep quality in migraine patients. ObjectiveTo compare the difference in sleep quality between PFO-positive and PFO-negative migraine patients， and to analyzes influencing factors of sleep quality in PFO-positive migraine patients， so as to provide references for clinical interventions to improve sleep quality in PFO-positive migraine patients. MethodsA total of 673 migraine patients who met the diagnostic criteria of migraine in the International Classification of Headache Disorders， third edition （ICHD-3）， and all patients underwent contrast-enhanced transcranial Doppler （c-TCD） and transthoracic echocardiographic right heart contrast echocardiography （cTTE） in the Third Hospital of Mianyang from January 2020 to October 2024. Basic demographic data were collected using a self-designed questionnaire， headache severity was assessed with the Visual Analogue Scale （VAS）， and sleep quality was invaluated using the Pittsburgh Sleep Quality Index （PSQI）. PFO patients was diagnosed through c-TCD combined with c-TTE. Binary logistic regression analysis was employed to examine the influencing factors of sleep quality in PFO-positive migraine patients. ResultsA total of 673 （100.00%） migraine patients were enrolled， including 223 PFO-positive cases （33.14%） and 450 PFO-negative cases（66.86%）. The PFO-positive group showed significantly more severe headache severity （χ²=15.799， P<0.01） and poorer sleep quality （χ²=14.377， P<0.01） compared with PFO-negative group. PFO-positive patients demonstrated significantly higher barrier factor scores of sleep quality， sleep latency， sleep efficiency， sleep disturbance， hypnotic medication use， and daytime dysfunction compared with PFO-negative counterparts （t=3.634， 3.269， 2.785， 3.428， 2.907， 3.637， Bonferroni adjust P<0.05/7=0.007）.By contrast， no significant difference was noted in sleep duration scores between the two groups（t=2.349， Bonferroni adjust P>0.05/7=0.007）.The Binary Logistic regression analysis revealed that age （OR=1.021， 95% CI： 1.001~1.041）， headache severity （OR=6.030， 95% CI： 4.085~8.901）， and PFO grade （OR=1.893，95% CI： 1.288~2.784）were significant influencing factors for sleep quality in migraine patients with PFO. ConclusionMigraine patients with PFO-positive exhibited poorer sleep quality compared wtih PFO-negative patients. Older age， higher headache servity， and more severe PFO grade are identified as risk factors for impaired sleep quality in PFO-positive migraine patients.

PURPOSE: To compare the effects of empirical and modified hemostatic resuscitation for liver blast injury combined with seawater immersion. METHODS: Thirty rabbits were subjected to liver blast injury combined with seawater immersion, and were then divided into 3 groups randomly (n = 10 each): group A (no treatment after immersion), group B (empirical resuscitation with 20 mL hydroxyethyl starch, 50 mg tranexamic acid, 25 IU prothrombin complex concentrate and 50 mg/kg body weight fibrinogen concentrate), and group C (modified resuscitation with additional 10 IU prothrombin complex concentrate and 20 mg/kg body weight fibrinogen concentrate based on group B). Blood samples were gathered at specified moments for assessment of thromboelastography, routine coagulation test, and biochemistry. Mean arterial pressure, heart rate, and survival rate were also documented at each time point. The Kolmogorov-Smirnov test was used to examine the normality of data distribution. Multigroup comparisons were conducted with one-way ANOVA. RESULTS: Liver blast injury combined with seawater immersion resulted in severe coagulo-fibrinolytic derangement as indicated by prolonged prothrombin time (s) (11.53 ± 0.98 vs. 7.61 ± 0.28, p＜0.001), activated partial thromboplastin time (APTT) (s) (33.48 ± 6.66 vs. 18.23 ± 0.89, p＜0.001), reaction time (R) (min) (5.85 ± 0.96 vs. 2.47 ± 0.53, p＜0.001), decreased maximum amplitude (MA) (mm) (53.20 ± 5.99 vs. 74.92 ± 5.76, p＜0.001) and fibrinogen concentration (g/L) (1.19 ± 0.29 vs. 1.89 ± 0.32, p = 0.003), and increased D-dimer concentration (mg/L) (0.38 ± 0.32 vs. 0.05 ± 0.03, p = 0.005). Both empirical and modified hemostatic resuscitation could improve the coagulo-fibrinolytic states and organ function, as indicated by shortened APTT and R values, decreased D-dimer concentration, increased fibrinogen concentration and MA values, lower concentration of blood urea nitrogen and creatine kinase-MB in group B and group C rabbits in comparison to that observed in group A. Further analysis found that the R values (min) (4.67 ± 0.84 vs. 3.66 ± 0.98, p = 0.038), APTT (s) (23.16 ± 2.75 vs. 18.94 ± 1.05, p = 0.001), MA (mm) (60.10 ± 4.74 vs. 70.21 ± 3.01, p < 0.001), and fibrinogen concentration (g/L) (1.68 ± 0.21 vs. 1.94 ± 0.16, p = 0.013) were remarkably improved in group C than in group B at 2 h and 4 h after injury. In addition, the concentration of blood urea nitrogen (mmol/L) (24.11 ± 1.96 vs. 21.00 ± 3.78, p = 0.047) and creatine kinase-MB (U/L) (85.50 ± 13.60 vs. 69.74 ± 8.56, p = 0.013) were lower in group C than in group B at 6 h after injury. The survival rates in group B and group C were significantly higher than those in group A at 4 h and 6 h after injury (p < 0.001), however, there were no statistical differences in survival rates between group B and group C at each time point. CONCLUSIONS Modified hemostatic resuscitation could improve the coagulation parameters and organ function better than empirical hemostatic resuscitation.
Animals ; Rabbits ; Resuscitation/methods* ; Liver/injuries* ; Seawater ; Blast Injuries/therapy* ; Fibrinogen/administration & dosage* ; Male ; Tranexamic Acid/administration & dosage* ; Immersion ; Hydroxyethyl Starch Derivatives/administration & dosage*

PURPOSE: To construct a decision-making app for pre-hospital damage control resuscitation (PHDCR) for severely injured patients, and to make a preliminary trial test on the effectiveness and usability aspects of the constructed app. METHODS: Decision-making algorithms were first established by a thorough literature review, and were then used to be learned by computer with 3 kinds of text segmentation algorithms, i.e., dictionary-based segmentation, machine learning algorithms based on labeling, and deep learning algorithms based on understanding. B/S architecture mode and Spring Boot were used as a framework to construct the app. A total of 16 Grade-5 medical students were recruited to test the effectiveness and usability aspects of the app by using an animal model-based test on simulated PHDCR. Twelve adult Bama miniature pigs were subjected to penetrating abdominal injuries and were randomly assigned to the 16 students, who were randomly divided into 2 groups (n = 8 each): group A (decided on PHDCR by themselves) and group B (decided on PHDCR with the aid of the app). The students were asked to complete the PHDCR within 1 h, and then blood samples were taken and thromboelastography, routine coagulation test, blood cell count, and blood gas analysis were examined. The lab examination results along with the value of mean arterial pressure were used to compare the resuscitation effects between the 2 groups. Furthermore, a 4-statement-based post-test survey on a 5-point Likert scale was performed in group B students to test the usability aspects of the constructed app. RESULTS: With the above 3 kinds of text segmentation algorithm, B/S architecture mode, and Spring Boot as the development framework, the decision-making app for PHDCR was successfully constructed. The time to decide PHDCR was (28.8 ± 3.41) sec in group B, much shorter than that in group A (87.5 ± 8.53) sec (p < 0.001). The outcomes of animals treated by group B students were much better than that by group A students as indicated by higher mean arterial pressure, oxygen saturation and fibrinogen concentration and maximum amplitude, and lower R values in group B than those in group A. The post-test survey revealed that group B students gave a mean score of no less than 4 for all 4 statements. CONCLUSION A decision-making app for PHDCR was constructed in the present study and the preliminary trial test revealed that it could help to improve the resuscitation effect in animal models of penetrating abdominal injury.
Animals ; Swine ; Resuscitation/methods* ; Mobile Applications ; Humans ; Algorithms ; Emergency Medical Services/methods* ; Male ; Decision Making ; Female

Objective To investigate the associations between unilateral or bilateral hearing loss and 12 chronic diseases as well as multimorbidity among the oldest old in China,and to identify disparities in these associations of left-and right-side hearing loss with chronic diseases.Methods Totally 7 437 people aged ≥80 years old were selected from the Chinese Longitudinal Health and Longevity Survey(CLHLS)2018 cross-sectional data.With 12 chronic diseases and multimorbidity as outcome variables,the hearing loss as explanatory variable,socio-demographic characteristics,family factors,and lifestyle as covariates,the correlations of unilateral(left-or right-side)and bilateral hearing loss with chronic diseases and multimorbidity were analyzed using multivariate logistic regression model,and the trend analyses were carried out.Results There were 205(2.76％),227(3.05％)and 3 598(48.38％)old people with left-side,right-side and bilateral hearing loss,respectively.After adjusting for confounders,the oldest old with left-sided or bilateral hearing loss had a greater risk of multimorbidity compared with those with normal hearing function,with odds ratio(95％confidence interval)of 2.14(1.58-2.90)and 1.27(1.13-1.43),respectively,while no association between right-sided hearing loss and multimorbidity was observed(P＞0.05).Trend analysis showed that the risk of multimorbidity increased with hearing loss from none to unilateral and then to bilateral(P＜0.001).Conclusion Hearing loss may be related to the increased risk of multimorbidity in the oldest old,and the risk of those with bilateral hearing loss is higher.More attention should be paid to the prevention and treatment of hearing loss in the oldest old.

Objective To explore the feasibility,effectiveness,and safety of balloon catheter-assisted total hepatic vascular exclusion.Methods We designed and manufactured an endovascular catheter with three lumens and double balloons,which can be inserted into the retrahepatic inferior vena cava through the femoral vein.The superior and inferior vena cava of the liver can be blocked by filling balloon,and the total hepatic vascular exclusion was achieved by combining with pringle method.In animal experiments,total hepatic vascular exclusion was performed by balloon catheter-assist method(experimental group)or traditional methods(control group),and the complete time was compared between the two groups.Blood flow blocking effect was observed by angiography and incision of retrahepatic inferior vena cava under direct vision.The complications were recorded.Results Total hepatic vascular exclusion was successfully completed in both groups.The completion time in the experimental group was significantly shorter than that in the control group([12.5±1.2]min vs.[35.8±4.9]min,P<0.05).CT angiography,DSA,and direct vision of blood vessels all confirmed the effectiveness of balloon catheter-assisted hepatic blood flow exclusion.No catheter displacement,balloon rupture,or air embolism occurred.Conclusion The balloon catheter-assisted hepatic total vascular exclusion is simpler and more feasible than traditional method.

A 13-year-old boy was admitted to the hospital due to 1 month after trauma in a traffic accident on September 29，2017. After admission，due to a large amount of pleural effusion through the chest tube，thoracoscopic exploration and fiberboard dissection were performed，and the postoperative pleural effusion was not significantly reduced. The creatinine of pleural effusion was 913 μmol/L，CT showed that left hydronephrosis and perirenal encapsulated effusion were closely related to the ureter，so ureteral injury and urinothorax were considered. Retrograde ureterography revealed a defect of left ureter，approximately 6 cm in length，and left nephrectomy + left kidney rupture repair + renal autotransplantation was performed. 7 years later，the patient recovered well and the renal blood supply was good，no left hydronephrosis was found by MRU. Early diagnosis of ureteral injury is challenging，especially when accompanied by urinothorax. When life is stable，early diagnosis and treatment can reduce the loss of renal function after combined trauma. Renal autotransplantation is safe and effective for the treatment of long segmental ureteral defects.

Objective:To investigate the prognostic factors for esophageal cancer after radical resection and the application value of machine learning prediction model.Methods:The retrospective cohort study was conducted. The clinicopatholigical data of 406 esophageal cancer patients who were admitted to Qilu Hospital of Shandong University from January 2018 to March 2022 were collected. There were 357 males and 49 females, aged (64±8)years. All patients underwent radical resection of esophageal cancer. The 406 patients were randomly divided into a training set of 285 cases and a validation set of 121 cases at a 7∶3 ratio based on a random number table. The training set was used to construct prediction model, and the validation set was used to validate prediction model. Patients were divided into high-risk group and low-risk group based on risk scores. Observation indicators: (1) follow-up of patients and analysis of influencing factors for prognosis; (2) construction and validation of machine learning prediction models. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data between groups was conducted using the rank sum test. The Kaplan-Meier method was used to calculate survival rate and plot survival curve, and the Log-rank test was used for survival analysis. The Cox proportional hazard regression model was used for univariate and multivariate analyses. Independent influencing factors were included, and data processing, machine learning model construction, and visualization were performed using R packages including random survival forest (RSF), gradient boosting machine (GBM), least absolute shrinkage and selection operator Cox regression (LASSO-Cox), Cox proportional hazards model boosting (CoxBoost), survival support vector machine (survivalsvm), extreme gradient boosting (XGBoost), supervised principal component analysis (SuperPC), and Cox partial least squares regression (plsRcox). Receiver operating characteristic (ROC) curves were drawn, and sensitivity, specificity, and area under the curve (AUC) were calculated. The Delong test was used to assess the differences in AUC among different models in the training set, and the time-dependent ROC was used to compare the predictive performance of different models. Calibration curves were used to evaluate model accuracy, and decision curve analysis (DCA) was used to evaluate overall net benefit. Results:(1) Follow-up of patients and analysis of influencing factors for prognosis. All 406 patients were followed up postoperatively for 28(range, 6-36)months, with 1- and 3-year overall survival rate of 86.5% and 40.9%, respectively. The 285 patients in the training set were followed up postoperatively for 30(range, 6-36)months, with 1- and 3-year overall survival rate of 85.1% and 35.5%, respectively. The 121 patients in the validation set were followed up postoperatively for 25(range, 6-36)months, with 1- and 3-year overall survival rate of 87.0% and 43.2%, respectively. There was no significant difference in postoperative overall survival rate between the training set and the validation set ( χ2=3.20, P>0.05). Results of multivariate analysis showed that left thoracic surgical approach, preopera-tive neutrophil count, vascular invasion, perineural invasion, pathological T2-4 stage, pathological N2-3 stage, and postoperative pneumonia were independent risk factors affecting postoperative survival of 285 patients in the training set ( hazard ratio=1.466, 1.037, 1.482, 1.549, 5.268, 7.727, 22.202, 2.539, 2.686, 1.425, 95% confidence interval as 1.026-2.096, 1.003-1.073, 1.008-2.179, 1.105-2.170, 1.201-23.099, 1.833-32.576, 4.734-104.128, 1.577-4.087, 1.631-4.422, 1.018-1.994, P<0.05). (2) Construction and validation of machine learning prediction models. Independent risk factors affecting postoperative survival were included to construct RSF, GBM, LASSO-Cox, CoxBoost, survivalsvm, XGBoost, SuperPC, and plsRcox machine learning prediction models. Results of Delong test showed that there were significant differences in the AUC of RSF and GBM from the other six models ( P<0.05). Results of time-dependent ROC curve showed that all 8 machine learning predic-tion models had good discriminative ability in the training cohort, among which the RSF machine learning prediction model had the best predictive performance. Results of calibration curve showed that the RSF machine learning prediction model fitted well for predicting postoperative 1-, 2-, and 3-year overall survival in the training cohort, with high consistency with actual results. Results of decision curve analysis showed that within a threshold range of 0-0.80, the RSF machine learning prediction model provided a better overall net benefit. Further analysis showed that in the validation set, the AUC of RSF machine learning prediction model for postoperative 1-, 2-, and 3-year survival prediction were 0.786 (95% confidence interval as 0.609-0.962), 0.774 (95% confidence interval as 0.676-0.873), and 0.750 (95% confidence interval as 0.652-0.848), respectively. Results of calibration curve showed that the RSF machine learning prediction model fitted well for predicting postopera-tive 1-, 2-, and 3-year overall survival in the validation set, with high consistency with actual results. In the training set, the optimal cutoff value of the RSF machine learning prediction model risk score was 11.7. Patients with risk score ≥11.7 were classified as the high-risk group, and those with risk score <11.7 as the low-risk group. The median survival times of the two groups were 18.0 months and >36.0 months, respectively, showing a significant difference between them ( χ2=73.30, P<0.05). In the validation set, the optimal cutoff value of the RSF machine learning prediction model risk score was 11.7. Patients with risk score ≥11.7 were classified as the high-risk group, and those with risk score<11.7 as the low-risk group. The median survival times of the two groups were 17.0 months and>36.0 months for the high-risk and low-risk groups, respectively, showing a significant difference between them ( χ2=35.20, P<0.05). Conclusions:Left thoracic surgical approach, preoperative neutrophil count, vascular invasion, perineural invasion, pathological T2-4 stage, pathological N2-3 stage, and postoperative pneumonia are independent risk factors affecting survival of esophageal cancer patients after radical resection. The RSF machine learning prediction model constructed based on these factors can effectively distinguish the survival prognosis of high-risk and low-risk patients.

Objective:To evaluate the feasibility of transjugular transcatheter tricuspid valve replacement (TTVR) using the LuX-Valve Plus system (Ningbo Jenscare Scientific, China) for the treatment of severe tricuspid regurgitation in real-world clinical settings.Methods:This prospective study enrolled 81 patients with severe ricuspid regurgitation (≥3+) who underwent TTVR with the LuX-Valve Plus system at the Department of Cardiology, West China Hospital of Sichuan University between May 2022 and March 2024. Among them, 44 patients were from a compassionate-use study, and 37 were from two premarket clinical trials. Baseline clinical data, preprocedural imaging, procedural outcomes, and postprocedural follow-up data were collected. The primary endpoint events included device success, procedural success, and 30 d composite adverse events.Results:The age of the cohort was (74.5±7.8) years, with 54 females (67%). Device success and procedural success rates were both 90% (73/81). Post-procedural tricuspid regurgitation improved, with a 6% (5/81) incidence of moderate-to-severe paravalvular leakage. The rate of permanent pacemaker implantation was 12% (10/81), of which 5% (4/81) had pre-existing indications for pacemaker implantation. Major bleeding events occurred in 10% (8/81) of patients, and the 30 d composite endpoint rate was 25% (20/81).Conclusion:TTVR using the LuX-Valve Plus system demonstrates promising feasibility for high-risk surgical patients with severe tricuspid regurgitation, effectively reducing or eliminating regurgitation with acceptable safety. However, challenges remain in reducing risks of major adverse events, including permanent pacemaker implantation and severe bleeding.