Background: The hypotension prediction index (HPI) is an algorithm designed to predict hypotension. Some studies have reported that HPI-guided hemodynamic management strategies decrease intraoperative hypotension and complications; however, the effect of HPI on reducing perioperative complications is controversial. This meta-analysis aimed to assess the efficacy of the HPI in reducing major complications and intraoperative hypotension. Methods: We conducted this meta-analysis according to the PRISMA statement and Cochrane Handbook guidelines. A comprehensive literature review was conducted to identify studies focusing on the efficacy of HPI-guided management in reducing intraoperative hypotension and postoperative complications. The PubMed, Embase, Scopus, and Web of Science databases were searched, and the resulting data were combined to calculate the pooled mean differences or risk ratios (RRs) with 95% CIs of both randomized controlled trials (RCTs) and retrospective studies, as appropriate. Heterogeneity and potential publication bias were also assessed. Results: Nineteen articles (12 RCTs and 7 retrospective studies) with 2570 recruited patients were included in this meta-analysis. The critical evaluation of the study quality revealed a low risk of bias in the included RCTs. Among the non-randomized trials, one was rated 7, two were rated 8, and the remaining four were rated 9 on the Newcastle-Ottawa Scale, indicating high quality and a low risk of bias. HPI-guided management significantly reduced intraoperative hypotension and associated major complications (RR = 0.79, 95% CI [0.69–0.90], I2 = 0, P < 0.001). Blood loss and length of hospital stay were comparable between the groups. Conclusions HPI-guided management significantly reduced intraoperative hypotension and major complications.

ObjectiveMigraine is a leading neurological disorder and the fourth most common cause of years lived with disability worldwide, affecting nearly 116 million individuals. Although pharmacological treatments are available, their efficacy is often limited by side effects and variable response rates. Repetitive transcranial magnetic stimulation (rTMS) over the dorsolateral prefrontal cortex (DLPFC) offers a safe, non-invasive alternative for migraine management. However, the neurophysiological mechanisms, particularly how rTMS modulates local cortical excitability and distributed pain-related circuits, remain poorly understood. Elucidating these mechanisms is essential for optimizing treatment protocols and improving clinical outcomes. MethodsThis study employed concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) to investigate neuroplastic and neurocircuitry mechanisms of DLPFC-rTMS in migraine. Study 1 compared 30 migraineurs and 28 healthy controls to identify abnormalities in TMS-evoked potentials (TEPs) and significant current density (SCD) within sensory-discriminative regions including the primary somatosensory cortex (S1) and posterior insula (pINS), cognitive-affective regions including the anterior insula (aINS) and midcingulate cortex (MCC), and a descending modulatory region, the periaqueductal gray (PAG). Study 2 used a single-blind, crossover, sham-controlled design in 34 healthy participants. Each participant received both active (10 Hz, 80% RMT, 1 500 pulses) and sham DLPFC-rTMS in counterbalanced order. TMS-EEG and cold pain tolerance were assessed before and after each session. ResultsIn Study 1, migraineurs showed a significantly less negative N120 amplitude compared to healthy controls (P=0.027, Cohen’s d=0.60), indicating local intracortical disinhibition. No group differences were observed for N40, P60, or P180 components. At the source level, migraineurs exhibited significantly higher SCD in the S1, pINS, aINS, and MCC (allQ<0.05), but not in the ventroposterior thalamus (vpTHAL), mediodorsal thalamus (mdTHAL), or PAG. In Study 2, active rTMS significantly reduced SCD from pre- to post-stimulation in the S1, aINS, and MCC (all Q<0.05). Sham stimulation also reduced SCD in the S1 (Q<0.05) but not in the aINS or MCC. Although no significant group-level analgesic effect was observed between active and sham conditions (P=0.107), correlation analyses revealed that greater SCD reductions in the S1 and MCC were significantly associated with higher post-rTMS pain tolerance (R=-0.487 and -0.495, both Q<0.01) and larger improvements in pain tolerance(R=-0.487 and -0.451, both Q<0.05). No such correlations were found following sham stimulation, suggesting that the behavioural relevance of neural changes is specific to active rTMS. ConclusionThis study provides novel evidence that migraineurs exhibit both local neuroplastic abnormalities (reduced N120 amplitude) and hyperactivity in key pain-processing regions (S1, pINS, aINS, MCC). A single session of DLPFC-rTMS reduced hyperactivity in the aINS, MCC, and S1. Notably, greater reductions in the S1 and MCC were associated with improved pain tolerance. These findings identify distinct cortical circuitries, particularly within the cognitive-affective pain network, that may serve as potential biomarkers for optimizing rTMS treatment in migraine and other chronic pain conditions. Future studies should validate these results in patient populations experiencing spontaneous migraine attacks and explore multi-session or accelerated rTMS protocols.

Hearing loss is the most prevalent disabling disease. Cochlear implantation（CI） serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system（Favorable, Marginal, Poor）. The consensus focuses on common hereditary non-syndromic hearing loss（such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1） and syndromic hereditary hearing loss（such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome）, which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans ; Cochlear Implantation ; Prognosis ; Hearing Loss/surgery* ; Consensus ; Connexin 26 ; Mutation ; Sulfate Transporters ; Connexins/genetics*

BACKGROUND: Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery. METHODS: PPCs were defined according to the European Perioperative Clinical Outcome standards as occurring within 7 postoperative days. Data of cases meeting inclusion/exclusion criteria were extracted from the anesthesia information management system to create three datasets: The development (data of Huashan Hospital, Fudan University from 2018 to 2020), temporal validation (data of Huashan Hospital, Fudan University in 2021) and external validation (data of other three hospitals in 2023) datasets. Machine learning models of six algorithms were trained using either 35 retrievable and plausible features or the 11 features selected by Lasso regression. Temporal validation was conducted for all models and the 11-feature models were also externally validated. Independent risk factors were identified and feature importance in top models was analyzed. RESULTS: PPCs occurred in 712 of 7533 (9.5%), 258 of 2824 (9.1%), and 207 of 2300 (9.0%) patients in the development, temporal validation and external validation datasets, respectively. During cross-validation training, all models except Bayes demonstrated good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.840. In temporal validation of full-feature models, deep neural network (DNN) performed the best with an AUC of 0.835 (95% confidence interval [CI]: 0.805-0.858) and a Brier score of 0.069, followed by Logistic regression (LR), random forest and XGBoost. The 11-feature models performed comparable to full-feature models with very close but statistically significantly lower AUCs, with the top models of DNN and LR in temporal and external validations. An 11-feature nomogram was drawn based on the LR algorithm and it outperformed the minimally modified Assess respiratory RIsk in Surgical patients in CATalonia (ARISCAT) and Laparoscopic Surgery Video Educational Guidelines (LAS VEGAS) scores with a higher AUC (LR: 0.824, ARISCAT: 0.672, LAS: 0.663). Independent risk factors based on multivariate LR mostly overlapped with Lasso-selected features, but lacked consistency with the important features using the Shapley additive explanation (SHAP) method of the LR model. CONCLUSIONS: The developed models, especially the DNN model and the nomogram, had good discrimination and calibration, and could be used for predicting PPCs in neurosurgical patients. The establishment of machine learning models and the ascertainment of risk factors might assist clinical decision support for improving surgical outcomes. TRIAL REGISTRATION ChiCTR 2100047474; https://www.chictr.org.cn/showproj.html?proj=128279 .
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Algorithms ; Lung Diseases/etiology* ; Machine Learning ; Neurosurgical Procedures/adverse effects* ; Postoperative Complications/diagnosis* ; Risk Factors ; ROC Curve

This study identified blood-entering components of Anshen Dropping Pills and explored their anti-insomnia effects and mechanisms. The main blood-entering components of Anshen Dropping Pills were detected and identified by UPLC-Q-TOF-MS/MS. The rationality of the formula was assessed by using enrichment analysis based on the relationship between drugs and symptoms, and core targets of its active components were selected as the the potential anti-insomnia targets of Anshen Dropping Pills through network pharmacology analysis. Furthermore, protein-protein interaction(PPI) network, Gene Ontology(GO) enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis were performed on the core targets. An active component-core target network for Anshen Dropping Pills was constructed. Finally, the effects of low-, medium-, and high-dose groups of Anshen Dropping Pills on sleep episodes, sleep duration, and sleep latency in mice were measured by supraliminal and subliminal pentobarbital sodium experiments. Moreover, total scores of the Pittsburgh sleep quality index(PSQI) scale was used to evaluate the changes before and after the treatment with Anshen Dropping Pills in a clinical study. The enrichment analysis based on the relationship between drugs and symptoms verified the rationality of the Anshen Dropping Pills formula, and nine blood-entering components of Anshen Dropping Pills were identified by UPLC-Q-TOF-MS/MS. The network proximity revealed a significant correlation between eight components and insomnia, including magnoflorine, liquiritin, spinosin, quercitrin, jujuboside A, ginsenoside Rb_3, glycyrrhizic acid, and glycyrrhetinic acid. Network pharmacology analysis indicated that the major anti-insomnia pathways of Anshen Dropping Pills involved substance and energy metabolism, neuroprotection, immune system regulation, and endocrine regulation. Seven core genes related to insomnia were identified: APOE, ALB, BDNF, PPARG, INS, TP53, and TNF. In summary, Anshen Dropping Pills could increase sleep episodes, prolong sleep duration, and reduce sleep latency in mice. Clinical study results demonstrated that Anshen Dropping Pills could decrease total scores of PSQI scale. This study reveals the pharmacodynamic basis and potential multi-component, multi-target, and multi-pathway effects of Anshen Dropping Pills, suggesting that its anti-insomnia mechanisms may be associated with the regulation of insomnia-related signaling pathways. These findings offer a theoretical foundation for the clinical application of Anshen Dropping Pills.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Tandem Mass Spectrometry/methods* ; Sleep Initiation and Maintenance Disorders/metabolism* ; Mice ; Network Pharmacology ; Male ; Chromatography, High Pressure Liquid ; Humans ; Protein Interaction Maps/drug effects* ; Sleep/drug effects* ; Female ; Adult

The manufacturing process is crucial for ensuring the safety and efficacy of traditional Chinese medicine(TCM) preparations. Using advanced technologies, innovative methods, and new equipment tailored for TCM to enhance the quality control of TCM preparations in the manufacturing process helps to ensure the product quality and foster high-quality development of the TCM industry. Upon current technical requirements, such as Guideline for Studies on Pharmaceutical Changes in Marketed Traditional Chinese Medicine Preparations(Trial) and Guideline for Study on Quality Control in Manufacturing Process of Oral Traditional Chinese Medicine Preparations(Trial), this paper analyzes the characteristics and current development of quality control in the manufacturing process of TCM preparations. It also discusses the significant roles that quality control in manufacturing process plays in ensuring the quality consistency and in the evaluation and decision-making of changes in marketed TCM preparations. Furthermore, to benefit the high-quality development of the TCM industry, this paper offers recommendations for improving quality control of TCM preparations in the manufacturing process and implementing new technologies and methods.
Quality Control ; Drugs, Chinese Herbal/chemistry* ; Medicine, Chinese Traditional/standards* ; Decision Making ; Humans

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

Sishen Pills and its separated prescriptions are classic prescriptions of traditional Chinese medicine to treat intestinal diseases. In this study, a high-performance liquid chromatography-electrospray ionization tandem mass spectrometry(HPLC-ESI-MS/MS) technology was used to identify the components of Sishen Pills, Ershen Pills, and Wuweizi Powder. The positive and negative ion sources of electrospray ionization were simultaneously collected by mass spectrometry. A total of 11 effective components were detected in Sishen Pills, with four effective components detected in Ershen Pills and eight effective components detected in Wuweizi Powder, respectively. To explore the effects of Sishen Pills and its separated prescriptions on the human intestinal flora, an in vitro anaerobic fermentation model was established, and the human intestinal flora was incubated with Sishen Pills, Ershen Pills, and Wuweizi Powder in vitro. The 16S rDNA sequencing technology was used to analyze the changes in the intestinal flora. The results showed that compared with the control group, Sishen Pills, and its separated prescriptions could decrease the intestinal flora abundance and increase the Shannon index after fermentation. The abundance of Bifidobacterium was significantly increased in the Sishen Pills and Ershen Pills groups. However, the abundance of Lactobacillus, Weissella, and Pediococcus was significantly increased in the Wuweizi Powder group. After fermentation for 12 h, the pH of the fermentation solution of three kinds of liquids with feces gradually decreased and was lower than that of the control group. The decreasing amplitude in the Wuweizi Powder group was the most obvious. The single-bacteria fermentation experiments further confirmed that Sishen Pills and Wuweizi Powder had inhibitory effects on Escherichia coli, Staphylococcus aureus, and Enterococcus faecalis, and the antibacterial activity of Wuweizi Powder was stronger than that of Sishen Pills. Both Sishen Pills and Ershen Pills could promote the growth of Lactobacillus brevis, and Ershen Pills could promote the growth of Bifidobacterium adolescentis. This study provided a more sufficient theoretical basis for the clinical application of Sishen Pills and its separated prescriptions.
Humans ; Gastrointestinal Microbiome/drug effects* ; Drugs, Chinese Herbal/chemistry* ; Fermentation/drug effects* ; Bacteria/drug effects* ; Chromatography, High Pressure Liquid ; Tandem Mass Spectrometry ; Intestines/microbiology*

"Prescriptions being modified according to the syndrome and processing following prescription" is one of the characteristics of clinical medication in traditional Chinese medicine(TCM), and it is also an important sign that distinguishes TCM from other traditional medicine. The processing methods of TCM decoctions originate from the ingenious combination of medicinal materials, the mutual restraint of seven emotions, the harmony of four properties, and the pairing and combining of medicinal materials in prescriptions. They are the concrete embodiment of the essence and characteristics of "prescriptions being modified according to the syndrome and processing following prescription". However, due to insufficient inheritance and innovation, many characteristic varieties and pharmaceutical experience have been lost or forgotten. There is an urgent need to systematically explore and organize the processing theory and characteristic varieties of TCM decoctions, delve into the scientific connotation of the processing principles, and optimize the processing technology. Therefore, this article systematically organizes and summarizes the historical evolution and modern research progress of TCM decoction processing, conducts in-depth reflection on the current problems, and puts forward reasonable suggestions, with the aim of further inheriting, enriching, and developing the processing theory of TCM decoctions and providing support for ensuring the clinical efficacy of prescriptions.
Drugs, Chinese Herbal/isolation & purification* ; Humans ; Medicine, Chinese Traditional/methods*