Neurocritical care involves complex pathophysiological mechanisms, and its incidence is higher, injuries are more severe, and treatment is more challenging in high-altitude environments. This consensus, based on the latest domestic and international evidence-based medical data, establishes a standardized, goal-oriented framework for neurocritical care management applicable in high-altitude regions and nationwide. The consensus was developed following international standards for evidence quality assessment and underwent two rounds of Delphi expert consultation, resulting in 32 recommendation statements covering three parts: management systems, monitoring and assessment, and core strategies. Key updates include: advocating for the establishment of independent neurocritical care units and implementing precise tiered diagnosis and treatment based on the "Five Differences in Critical Care" concept; constructing a "trinity" multimodal brain monitoring system centered on cerebral blood flow, cerebral oxygenation, and brain function, emphasizing routine bedside transcranial Doppler ultrasound, cerebral oximetry, and continuous electroencephalography monitoring; shifting management strategies from mild hypothermia therapy to targeted temperature management, and defining the "446" target management pathway for the supercritical stage; emphasizing the assessment of static and dynamic cerebrovascular autoregulation functions through multimodal methods to achieve individualized optimal mean arterial pressure management; elevating cerebrospinal fluid management goals to the level of "glymphatic system" function maintenance; implementing a multidisciplinary collaborative, whole-process management model focusing on patients' long-term neurological functional outcomes; de-escalation criteria include multidimensional indicators such as recovery of brain structure, restoration of cerebrovascular autoregulation, improvement in cerebrospinal fluid dynamics, and reduction in biomarker levels; and integrating cutting-edge technologies like artificial intelligence into post-critical care management and rehabilitation planning. This consensus systematically integrates the entire process of neurocritical care management, reflecting the modern connotation of goal-oriented, dynamic, and multimodal integration in neurocritical care medicine. It aims to adapt to new trends such as deepening understanding of pathophysiological mechanisms, the integration of medicine and engineering, and the empowerment of artificial intelligence, thereby further advancing the discipline of critical care medicine.

OBJECTIVE To explore the mechanism by which Qingre antai decoction improves pregnancy outcomes of threatened abortion rats with blood heat syndrome. METHODS The pregnant rats were randomly divided into normal group， model group， dydrogesterone group （0.002 g/kg）， and Qingre antai decoction group （44.1 g/kg）， with 13 rats in each group. Except for normal group， other groups were given warming-yang Chinese medicine and corresponding drugs intragastrically， once a day， for 12 consecutive days. On the 13th day of pregnancy， a single intragastric administration of mifepristone （5 mg/kg） was performed to establish a model of threatened abortion with blood heat syndrome. On the 14th day of pregnancy， the abortion rate and uterine coefficient were calculated； the pathological morphology of pregnant uterine was observed； the serum levels of 3，5，3′-triiodothyronine （T3）， thyroid hormone （T4）， thyroid stimulating hormone （TSH）， as well as the levels of vascular endothelial growth factor （VEGF） and nitric oxide （NO） in the pregnant uterus were all determined； the expressions of mRNA and protein related to Janus kinase 2 （JAK2）/signal transducer and activator of transcription 3 （STAT3） and phosphatidylinositol 3-kinase （PI3K）/protein kinase B （AKT） pathways were detected. RESULTS Compared with normal group， the model group exhibited endometrial tissue damage， a reduced number of decidual cells， and a significant presence of blood stasis within the uterus； abortion rate， the serum levels of T3， T4 and TSH， the mRNA expressions of JAK2， STAT3 and suppressor of cytokine signaling 3 （SOCS3） as well as protein expressions of p-JAK2， p-STAT3 and SOCS3 in the pregnant uterus were increased significantly （ P ＜0.05）； uterine coefficient， the levels of VEGF and NO in pregnant uterus， mRNA expressions of VEGFR2， PI3K， AKT and endothelial nitric oxide synthase（eNOS）， protein expressions of VEGFR2， PI3K and eNOS as well as phosphorylation level of AKT in the pregnant uterus were significantly reduced （ P ＜0.05）. Compared with model group， the endometrial tissue damage and congestion in the Qingre antai decoction group were significantly improved， and the levels of the aforementioned quantitative indicators were significantly reversed （ P ＜0.05）. CONCLUSIONS Qingre antai decoction can improve the pregnancy outcomes in rats with threatened abortion of blood heat syndrome， the mechanism of which may be associated with inhibiting JAK2/STAT3 pathway and activating PI3K/AKT pathway.

Objective To investigate the predictive value of combined radiomic features derived from chest CT scans with clinical characteristics for epidermal growth factor receptor(EGFR)gene mutations in non-small cell lung cancer(NSCLC).Methods A multi-center case-control study was conducted on the clinical data and CT images of 1 070 NSCLC patients from the radiology departments of the 3 medical institutions between January 2013 and October 2023.The 719 NSCLC patients from the First Affiliated Hospital of Army Medical University were randomly divided into a training set and an internal validation set in a ratio of 7∶3;The 173 patients in the Eastern Theatre General Hospital and the 178 patients in Army Medical Centre of PLA were assigned into the external validation set 1 and 2,respectively.Least absolute shrinkage and selection operator(LASSO)regression was employed to identify the optimal radiomic features,which were subsequently used to construct a radiomics model.Univariate and multivariate logistic regression analyses were applied to identify clinical features associated with EGFR mutation,thereby developing a clinical model.The radiomic and clinical features were subsequently combined to develop a comprehensive model.All the 3 classification models were built using random forest(RF)machine learning.The area under curve(AUC),accuracy,sensitivity and specificity were utilized to evaluate the predictive performance of the models.Calibration curve was plotted to assess the goodness of fit of the comprehensive model,while decision curve analysis was performed to assess the clinical utility of the model.Results The AUC value of the radiomics model was 0.762 4(95%CI:0.692 4～0.825 1),0.745 4(95%CI:0.671 1～0.814 3),and 0.724 7(95%CI:0.639 7～0.801 6),respectively,in the internal validation set,external validation set 1,and external validation set 2;The AUC value of the clinical prediction model was 0.691 7(95%CI:0.627 9～0.757 6),0.652 5(95%CI:0.576 7～0.729 1),and 0.779 2(95%CI:0.712 5～0.847 3),respectively in the above sets in turn;The comprehensive model constructed based on clinical features and radiomic features showed the best predictive efficacy,with an AUC value of 0.818 0(95%CI:0.757 7～0.874 3),0.782 4(95%CI:0.703 1～0.848 2),and 0.796 6(95%CI:0.718 1～0.868 6),respectively in the above sets.Calibration curve analysis indicated that the comprehensive model had a good fit,while decision curve analysis revealed that the model provided a favorable net benefit.Conclusion Our comprehensive model constructed based on chest CT radiomic features and clinical characteristics shows superior predictive performance for EGFR gene mutations in NSCLC across multiple center datasets,which may be helpful for clinical decision-making for treatment strategies.

Objective To evaluate the predictive value of deep learning features from chest CT images combined with clinical and radiomics features for epidermal growth factor receptor(EGFR)mutations in non-small cell lung cancer(NSCLC).Methods This case-control study retrospectively analyzed clinical and imaging data of 1 070 NSCLC patients from radiology departments at three hospitals(January 2013 to October 2023).Patients were divided into:a training set(n=502)and internal validation set(n=217)via 7∶3 randomization of 719 cases from the First Affiliated Hospital of Army Medical University;external validation set 1(n=173)from General Hospital of Eastern Theater Command;external validation set 2(n=178)from Daping Hospital of Army Medical University.Deep learning features were extracted using a 2.5D convolutional neural network(CNN)with ResNet101 backbone,radiomics features were derived from CT images,and clinical risk factors were identified to construct models.An integrated model combined deep learning,clinical,and radiomics features.All four models were developed using random forest(RF)classifiers.Calibration curves assessed goodness-of-fit,and decision curve analysis(DCA)evaluated clinical utility.Results The deep learning model achieved AUCs of 0.833 7(95%CI:0.770 6～0.884 7),0.815 1(0.741 6～0.882 8),and 0.810 1(0.745 2～0.873 6)in the internal and two external validation sets,respectively.Clinical models yielded AUCs of 0.731 0(0.660 2～0.802 1),0.746 0(0.666 4～0.824 9),and 0.813 4(0.743 1～0.883 6);radiomics models showed AUCs of 0.762 4(0.692 4～0.825 1),0.745 4(0.671 1～0.814 3),and 0.724 7(0.639 7～0.801 6).The integrated model demonstrated optimal performance with AUCs of 0.905 5(0.857 0～0.945 4),0.832 7(0.763 3～0.896 4),and 0.889 0(0.834 4～0.934 3).DCA indicated significant net benefit for EGFR prediction at threshold probabilities of 0.15～0.85 using the integrated model.Conclusion Deep learning features from CT images effectively predict EGFR mutation status in NSCLC.The integrated model combining deep learning,clinical,and radiomics features further enhances predictive performance.

Objective: To evaluate the clinical efficacy of preimplantation genetic testing for monogenic disorders(PGT-M) in families with hereditary epilepsy. Methods : Whole-exome sequencing(WES) and familial co-segregation analysis were performed to validate the pathogenicity of variants(PCDH19 c. 1031C > G and LGI1 c. 856T >G) in two monogenic epilepsy families. A clinical PGT-M pathway was implemented,and reproductive outcomes were tracked. Results: In Family 1(PCDH19 likely pathogenic variant),13 blastocysts were biopsied over two ovarian stimulation cycles,yielding 3 unaffected euploid embryos(23. 1%). After the third frozen embryo transfer,a healthy male infant was successfully delivered. Prenatal diagnosis confirmed that the fetus did not carry the pathogenic variant PCDH19. Family 2(LGI1 variant of uncertain significance,VUS) screened 14 blastocysts,identifying 2 unaffected euploid embryos(14. 3%),with the first transfer unsuccessful. A clinical pregnancy was currently ongoing following the second frozen-thawed embryo transfer(FET). Conclusion PGT-M can precisely block the vertical transmission of monogenic epileptic pathogenic variants,offering an effective reproductive intervention strategy for families with hereditary epilepsy.

Objective: To investigate the impact of endometriosis on pregnancy and delivery outcomes in patients undergoing single euploid frozen_thawed blastocyst transfer cycles following preimplantation genetic testing. Methods : A retrospective analysis was performed on clinical data from patients undergoing frozen_thawed blastocyst transfer after preimplantation genetic testing at the reproductive center of The First Affiliated Hospital of Anhui Medical University. The endometriosis group comprised 84 treatment cycles. After 1 : 3 propensity score matching , 252 treatment cycles from non_endometriosis patients were included as the control group. General characteristics and clinical outcomes were compared between the two groups. Results: There were no statistically significant differences between the two groups in terms of general characteristics , human chorionic gonadotropin ( HCG) positive rate , cycle clinical pregnancy rate per cycle , early miscarriage rate , preterm birth rate , live birth rate per cycle , cesarean section rate , delivery weeks , cumulative clinical pregnancy rate , and cumulative live birth rate (all P > 0. 05) . Conclusion Endometriosis may not reduce the pregnancy rate and live birth rate in single frozen euploid blastocyst transfer cycles .

Objective: To explore the role of the c.598G>A mutation of the ITGB3 gene in the occurrence of fetal and neonatal alloimmune thrombocytopenia (FNAIT) through its expression in vitro. Methods: The platelet antibodies in the sera of the affected neonate and her mother were detected using commercial enzyme-linked immunosorbent assay (ELISA), solid-phase agglutination, flow cytometry and the gold standard monoclonal antibody-specific immobilization of platelet antigens (MAIPA). The common human platelet antigen (HPA) genotypes of the neonate and her parents were obtained using the HPA-SSP method. The presence of mutations was analyzed by sequencing the exons of the ITGB3 and ITGA2B genes. The target gene of ITGB3 was obtained by PCR amplification using the existing human platelet cDNA. The wild-type ITGB3 eukaryotic expression vector was constructed by TA cloning technology. The 598G>A mutant ITGB3 eukaryotic expression vector was obtained by point mutation, and the plasmid DNA was co-transfected with that of ITGA2B (αⅡb) into HEK293 cells. The transfected cells stably expressing GP Ⅱb/Ⅲa were screened and obtained. The expression of GP Ⅱb/Ⅲa in 598G>A mutant transfected cells and the presence of antibodies against this mutation in the serum of mother were detected by flow cytometry and MAIPA. Results: Antibodies against HLA-class Ⅰ and GP Ⅱb/Ⅲa glycoproteins were detected in the serum of the neonate's mother, and subsequent HLA antibody-specific testing confirmed the presence of antibodies against HLA-B 57∶01 and A 02∶05. ITGB3 sequencing showed that the neonate and her father carried the c.598G>A point mutation, which results in the change of glutamate to lysine at position 200. Antibodies against GP Ⅱb/Ⅲa glycoproteins were not detected using constructed c.598G>A mutant transfected cells reacted with the maternal serum. Conclusion: The in vitro expression and analysis of the ITGB3 c.598G>A mutation did not support a role for this mutation in the pathogenesis of FNAIT. The establishment of this method facilitates the discovery of new platelet low-frequency antigens, and provides a theoretical foundation for the detection of antibodies against platelet antigens associated with patients with adverse pregnancy and childbirth histories.

Background: Intraoperative hypercapnia reduces the time to emergence from volatile anesthetics, but few clinical studies have explored the effect of hypercapnia on the emergence time from intravenous (IV) anesthesia. We investigated the effect of inducing mild hypercapnia during the recovery period on the emergence time after total IV anesthesia (TIVA). Methods: Adult patients undergoing transurethral lithotripsy under TIVA were randomly allocated to normocapnia group (end-tidal carbon dioxide [ETCO2] 35–40 mmHg) or mild hypercapnia group (ETCO2 50-55 mmHg) during the recovery period. The primary outcome was the extubation time. The spontaneous breathing-onset time, voluntary eye-opening time, and hemodynamic data were collected. Changes in the cerebral blood flow velocity in the middle cerebral artery were assessed using transcranial Doppler ultrasound. Results: In total, 164 patients completed the study. The extubation time was significantly shorter in the mild hypercapnia (13.9 ± 5.9 min, P = 0.024) than in the normocapnia group (16.3 ± 7.6 min). A similar reduction was observed in spontaneous breathing-onset time (P = 0.021) and voluntary eye-opening time (P = 0.008). Multiple linear regression analysis revealed that the adjusted ETCO2 level was a negative predictor of extubation time. Middle cerebral artery blood flow velocity was significantly increased after ETCO2 adjustment for mild hypercapnia, which rapidly returned to baseline, without any adverse reactions, within 20 min after extubation. Conclusions Mild hypercapnia during the recovery period significantly reduces the extubation time after TIVA. Increased ETCO2 levels can potentially enhance rapid recovery from IV anesthesia.

Background: Intraoperative hypercapnia reduces the time to emergence from volatile anesthetics, but few clinical studies have explored the effect of hypercapnia on the emergence time from intravenous (IV) anesthesia. We investigated the effect of inducing mild hypercapnia during the recovery period on the emergence time after total IV anesthesia (TIVA). Methods: Adult patients undergoing transurethral lithotripsy under TIVA were randomly allocated to normocapnia group (end-tidal carbon dioxide [ETCO2] 35–40 mmHg) or mild hypercapnia group (ETCO2 50-55 mmHg) during the recovery period. The primary outcome was the extubation time. The spontaneous breathing-onset time, voluntary eye-opening time, and hemodynamic data were collected. Changes in the cerebral blood flow velocity in the middle cerebral artery were assessed using transcranial Doppler ultrasound. Results: In total, 164 patients completed the study. The extubation time was significantly shorter in the mild hypercapnia (13.9 ± 5.9 min, P = 0.024) than in the normocapnia group (16.3 ± 7.6 min). A similar reduction was observed in spontaneous breathing-onset time (P = 0.021) and voluntary eye-opening time (P = 0.008). Multiple linear regression analysis revealed that the adjusted ETCO2 level was a negative predictor of extubation time. Middle cerebral artery blood flow velocity was significantly increased after ETCO2 adjustment for mild hypercapnia, which rapidly returned to baseline, without any adverse reactions, within 20 min after extubation. Conclusions Mild hypercapnia during the recovery period significantly reduces the extubation time after TIVA. Increased ETCO2 levels can potentially enhance rapid recovery from IV anesthesia.