Objective:To systematically evaluate the efficacy, patient-reported outcomes (PROs) and safety of hyaluronic acid (HA) fillers and collagen stimulators (PCL/PLLA) for various facial aesthetic indications.Methods:This study focused on facial fillers approved and widely used in China, including HA fillers such as Juvéderm?, Restylane?, Belotero?, Fillmed?, and PCL/PLLA such as Ellansé?, L?viselle?, and CureWhite?. A systematic literature search was conducted across both English and Chinese databases, including PubMed, Cochrane Library, Embase, CNKI, and Wanfang Data, covering the period from database inception to August 24, 2023, to identify randomized controlled trials (RCTs). The characteristics and outcomes of the included RCTs were summarized and analyzed, including efficacy indicators by injection site, patient satisfaction, and safety profiles. Network meta-analysis (NMA) was performed using R software to compare efficacy outcomes, including the 6-month improvement response rate for nasolabial folds (NLF) and the global aesthetic improvement scale (GAIS).Results:A total of 38 articles were included. Among them, Juvéderm? was most frequently used as the treatment group (17 out of 38 articles), while Restylane? was the most common comparator (17 out of 38 articles), particularly in studies involving NLF injections (15 out of 16 articles). For collagen stimulators, only 2 studies on Ellansé? were included, both focusing solely on NLF treatment. Quality assessment showed that 34 studies were of medium to high quality, with Juvéderm? accounting for the majority of high-quality studies (11 articles). Based on injection sites, NLF was the most studied area (16 articles), followed by the midface (8 articles), and the remaining 14 articles covered other regions including lips, nose, chin, and infraorbital area. In the NLF region, the 6-month improvement response rate assessed by blinded investigators showed that Juvéderm? showed better outcomes than Restylane? ( RR=1.07, 95% CI: 0.89-1.32), while Belotero? was slightly inferior to Restylane? ( RR=0.97, 95% CI: 0.65-1.44), although the differences were not statistically significant. Subject-reported outcomes showed consistent trends with investigator assessments. For 6-month GAIS improvement, Juvéderm? and Restylane? showed comparable result within the HA filler category ( RR=1.01, 95% CI: 0.71-1.43). The collagen stimulator Ellansé? demonstrated numerically higher values than HA fillers ( RR=1.32, 95% CI: 0.86-2.08). However, none of these differences reached statistical significance. In midface treatments, Juvéderm? had more long-term evidence, with follow-up periods extending up to 24 months. Four studies reported numerically greater volume enhancement with Juvéderm? compared to Restylane?. For other facial areas, Juvéderm? had the most comprehensive clinical evidence, covering the widest range of injection sites. No relevant RCTs were available for collagen stimulators in these regions. Regarding patient satisfaction, 19 studies reported patient-reported outcomes, with Juvéderm? contributing 16 of them, and showing higher satisfaction in 6 head-to-head comparisons with Restylane?. In contrast, collagen stimulators currently lack such evidence. Safety result indicated that HA fillers were generally safe and well tolerated, while safety data for collagen stimulators remain limited due to insufficient high-quality evidence. Conclusion:Among the HA fillers, Juvéderm? has a large quantity and highest quality of clinical studies, and NMA result shows its superior efficacy in NLF. In comparison, the current evidence is still not sufficient to draw a clear conclusion for the PCL/PLLA due to a lack of adequate high-quality clinical evidence regarding its clinical efficacy, PROs, and safety.

Objective:To evaluate the accuracy of the oral healthcare information provided by different large language models (LLM) to explore their feasibility and limitations in the application of oral auxiliary, treatment and health consultation.Methods:This study designed eight items comprising 47 questions in total related to the diagnosis and treatment of oral diseases [to assess the performance of LLM as an artificial intelligence (AI) medical assistant], and five items comprising 35 questions in total about oral health consultations (to assess the performance of LLM as a simulated doctor). These questions were answered individually by the five LLM models (Erine Bot, HuatuoGPT, Tongyi Qianwen, iFlytek Spark, ChatGPT). Two attending physicians with more than 5 years of experience independently rated the responses using the 3C criteria (correct, clear, concise), and the consistency between the raters was assessed using the Spearman rank correlation coefficient, and the Kruskal-Wallis test and Dunn post hoc test were used to assess the statistical differences between the models. Additionally, this study used 600 questions from the 2023 dental licensing examination to evaluate the time taken to answer, scores, and accuracy of each model.Results:As an AI medical assistant, LLM can assist doctors in diagnosis and treatment decision-making, with an inter-evaluator Spearman coefficient of 0.505 ( P<0.01). As a simulated doctor, LLM can carry out patient popularization, with an inter-evaluator Spearman coefficient of 0.533 ( P<0.01). The 3C scores of each model as an AI medical assistant and a simulated doctor were respectively: 2.00 (1.00, 3.00) and 2.00 (2.00, 3.00) points of Erine Bot, 1.00 (1.00, 2.00) and 2.00 (1.00, 2.00) points of HuatuoGPT, 2.00 (1.00, 2.00) and 2.00 (1.00, 3.00) points of Tongyi Qianwen, 2.00 (1.00, 2.00) and 2.00 (1.75, 2.25) points of iFlytek Spark, 3.00 (2.00, 3.00) and 3.00 (2.00, 3.00) points of ChatGPT (full score of 4 points). The Kruskal-Wallis test results showed that, as an AI medical assistant or a simulated doctor, there were statistically differences in the 3C scores among the five large language models (all P<0.001). The average score of the 5 LLMs on the dental licensing examination was 370.2, with an accuracy rate of 61.7% (370.2/600) and a time consumption of 94.6 min. Specifically, Erine Bot took 115 min, scored 363 points with an accuracy rate of 60.5% (363/600), HuatuoGPT took 224 min and scored 305 points with an accuracy rate of 50.8% (305/600), Tongyi Qianwen took 43 min, scored 438 points with an accuracy rate of 73.0% (438/600), iFlytek Spark took 32 min, scored 364 points with an accuracy rate of 60.7% (364/600), and ChatGPT took 59 min, scored 381 points with an accuracy rate of 63.5% (381/600). Conclusions:Based on the evaluation of LLM′s dual roles as an AI medical assistant and a simulated doctor, ChatGPT performes the best, with basically correct, clear and concise answers, followed by Erine Bot, Tongyi Qianwen and iFlytek Spark, with HuatuoGPT lagging behind significantly. In the dental licensing examination, all the 4 LLM, except for HuatuoGPT, reach the passing level, and the time consumpution for answering is significantly reduced compared to the 8 h required for the exam regulations in all of the five models. LLM has the feasibility of application in oral auxiliary, treatment and health consultation, and it can help both doctors and patients obtain medical information quickly. Howere, their outputs carry a risk of errors (since the 3C scoring results do not reach the full marks), so prudent judgment should be exercised when using them.

Objective:To systematically evaluate the efficacy, patient-reported outcomes (PROs) and safety of hyaluronic acid (HA) fillers and collagen stimulators (PCL/PLLA) for various facial aesthetic indications.Methods:This study focused on facial fillers approved and widely used in China, including HA fillers such as Juvéderm?, Restylane?, Belotero?, Fillmed?, and PCL/PLLA such as Ellansé?, L?viselle?, and CureWhite?. A systematic literature search was conducted across both English and Chinese databases, including PubMed, Cochrane Library, Embase, CNKI, and Wanfang Data, covering the period from database inception to August 24, 2023, to identify randomized controlled trials (RCTs). The characteristics and outcomes of the included RCTs were summarized and analyzed, including efficacy indicators by injection site, patient satisfaction, and safety profiles. Network meta-analysis (NMA) was performed using R software to compare efficacy outcomes, including the 6-month improvement response rate for nasolabial folds (NLF) and the global aesthetic improvement scale (GAIS).Results:A total of 38 articles were included. Among them, Juvéderm? was most frequently used as the treatment group (17 out of 38 articles), while Restylane? was the most common comparator (17 out of 38 articles), particularly in studies involving NLF injections (15 out of 16 articles). For collagen stimulators, only 2 studies on Ellansé? were included, both focusing solely on NLF treatment. Quality assessment showed that 34 studies were of medium to high quality, with Juvéderm? accounting for the majority of high-quality studies (11 articles). Based on injection sites, NLF was the most studied area (16 articles), followed by the midface (8 articles), and the remaining 14 articles covered other regions including lips, nose, chin, and infraorbital area. In the NLF region, the 6-month improvement response rate assessed by blinded investigators showed that Juvéderm? showed better outcomes than Restylane? ( RR=1.07, 95% CI: 0.89-1.32), while Belotero? was slightly inferior to Restylane? ( RR=0.97, 95% CI: 0.65-1.44), although the differences were not statistically significant. Subject-reported outcomes showed consistent trends with investigator assessments. For 6-month GAIS improvement, Juvéderm? and Restylane? showed comparable result within the HA filler category ( RR=1.01, 95% CI: 0.71-1.43). The collagen stimulator Ellansé? demonstrated numerically higher values than HA fillers ( RR=1.32, 95% CI: 0.86-2.08). However, none of these differences reached statistical significance. In midface treatments, Juvéderm? had more long-term evidence, with follow-up periods extending up to 24 months. Four studies reported numerically greater volume enhancement with Juvéderm? compared to Restylane?. For other facial areas, Juvéderm? had the most comprehensive clinical evidence, covering the widest range of injection sites. No relevant RCTs were available for collagen stimulators in these regions. Regarding patient satisfaction, 19 studies reported patient-reported outcomes, with Juvéderm? contributing 16 of them, and showing higher satisfaction in 6 head-to-head comparisons with Restylane?. In contrast, collagen stimulators currently lack such evidence. Safety result indicated that HA fillers were generally safe and well tolerated, while safety data for collagen stimulators remain limited due to insufficient high-quality evidence. Conclusion:Among the HA fillers, Juvéderm? has a large quantity and highest quality of clinical studies, and NMA result shows its superior efficacy in NLF. In comparison, the current evidence is still not sufficient to draw a clear conclusion for the PCL/PLLA due to a lack of adequate high-quality clinical evidence regarding its clinical efficacy, PROs, and safety.

Objective:To evaluate the accuracy of the oral healthcare information provided by different large language models (LLM) to explore their feasibility and limitations in the application of oral auxiliary, treatment and health consultation.Methods:This study designed eight items comprising 47 questions in total related to the diagnosis and treatment of oral diseases [to assess the performance of LLM as an artificial intelligence (AI) medical assistant], and five items comprising 35 questions in total about oral health consultations (to assess the performance of LLM as a simulated doctor). These questions were answered individually by the five LLM models (Erine Bot, HuatuoGPT, Tongyi Qianwen, iFlytek Spark, ChatGPT). Two attending physicians with more than 5 years of experience independently rated the responses using the 3C criteria (correct, clear, concise), and the consistency between the raters was assessed using the Spearman rank correlation coefficient, and the Kruskal-Wallis test and Dunn post hoc test were used to assess the statistical differences between the models. Additionally, this study used 600 questions from the 2023 dental licensing examination to evaluate the time taken to answer, scores, and accuracy of each model.Results:As an AI medical assistant, LLM can assist doctors in diagnosis and treatment decision-making, with an inter-evaluator Spearman coefficient of 0.505 ( P<0.01). As a simulated doctor, LLM can carry out patient popularization, with an inter-evaluator Spearman coefficient of 0.533 ( P<0.01). The 3C scores of each model as an AI medical assistant and a simulated doctor were respectively: 2.00 (1.00, 3.00) and 2.00 (2.00, 3.00) points of Erine Bot, 1.00 (1.00, 2.00) and 2.00 (1.00, 2.00) points of HuatuoGPT, 2.00 (1.00, 2.00) and 2.00 (1.00, 3.00) points of Tongyi Qianwen, 2.00 (1.00, 2.00) and 2.00 (1.75, 2.25) points of iFlytek Spark, 3.00 (2.00, 3.00) and 3.00 (2.00, 3.00) points of ChatGPT (full score of 4 points). The Kruskal-Wallis test results showed that, as an AI medical assistant or a simulated doctor, there were statistically differences in the 3C scores among the five large language models (all P<0.001). The average score of the 5 LLMs on the dental licensing examination was 370.2, with an accuracy rate of 61.7% (370.2/600) and a time consumption of 94.6 min. Specifically, Erine Bot took 115 min, scored 363 points with an accuracy rate of 60.5% (363/600), HuatuoGPT took 224 min and scored 305 points with an accuracy rate of 50.8% (305/600), Tongyi Qianwen took 43 min, scored 438 points with an accuracy rate of 73.0% (438/600), iFlytek Spark took 32 min, scored 364 points with an accuracy rate of 60.7% (364/600), and ChatGPT took 59 min, scored 381 points with an accuracy rate of 63.5% (381/600). Conclusions:Based on the evaluation of LLM′s dual roles as an AI medical assistant and a simulated doctor, ChatGPT performes the best, with basically correct, clear and concise answers, followed by Erine Bot, Tongyi Qianwen and iFlytek Spark, with HuatuoGPT lagging behind significantly. In the dental licensing examination, all the 4 LLM, except for HuatuoGPT, reach the passing level, and the time consumpution for answering is significantly reduced compared to the 8 h required for the exam regulations in all of the five models. LLM has the feasibility of application in oral auxiliary, treatment and health consultation, and it can help both doctors and patients obtain medical information quickly. Howere, their outputs carry a risk of errors (since the 3C scoring results do not reach the full marks), so prudent judgment should be exercised when using them.

Carotid atherosclerotic plaque is the main cause of ischemic stroke. In recent years, with the continuous innovation of novel imaging technologies, numerous classification standards for carotid plaques provide more powerful evidence for the features of carotid plaques and perioperative vascular assessment, as well as the reference for surgeons in choosing therapeutic decisions. Ultrasound is the preferred non-invasive and convenient screening tool for carotid stenosis. Invasive examinations such as CT angiography and magnetic resonance angiography are suitable for carotid stenosis patients to determine the plaque composition and stability, which can guide surgical decision-making and help to prevent serious cardiovascular and cerebrovascular adverse events. Advances in the treatment of carotid artery stenosis have focused on the improvement and innovation of vascular interventional devices and surgical procedures, including double-layer stents, coated stents and transcarotid artery revascularization. As technology continues to evolve, molecular imaging and more minimally invasive screening as well as therapies will be the way forward.

Humans ; Aged ; Lung Diseases ; Pneumonia/drug therapy* ; Adrenal Cortex Hormones/therapeutic use* ; Pulmonary Disease, Chronic Obstructive/drug therapy* ; Administration, Inhalation ; Community-Acquired Infections/drug therapy*

Carotid atherosclerotic plaque is the main cause of ischemic stroke. In recent years, with the continuous innovation of novel imaging technologies, numerous classification standards for carotid plaques provide more powerful evidence for the features of carotid plaques and perioperative vascular assessment, as well as the reference for surgeons in choosing therapeutic decisions. Ultrasound is the preferred non-invasive and convenient screening tool for carotid stenosis. Invasive examinations such as CT angiography and magnetic resonance angiography are suitable for carotid stenosis patients to determine the plaque composition and stability, which can guide surgical decision-making and help to prevent serious cardiovascular and cerebrovascular adverse events. Advances in the treatment of carotid artery stenosis have focused on the improvement and innovation of vascular interventional devices and surgical procedures, including double-layer stents, coated stents and transcarotid artery revascularization. As technology continues to evolve, molecular imaging and more minimally invasive screening as well as therapies will be the way forward.

OBJECTIVE: To analyze the predictors of successful weaning off extracorporeal membrane oxygenation (ECMO) after extracorporeal cardiopulmonary resuscitation (ECPR). METHODS: The clinical data of 56 patients with cardiac arrest who underwent ECPR in Hunan Provincial People's Hospital (the First Affiliated Hospital of Hunan Normal University) from July 2018 to September 2022 were retrospectively analyzed. According to whether ECMO was successfully weaning off, patients were divided into the successful weaning off group and the failed weaning off group. The basic data, duration of conventional cardiopulmonary resuscitation (CCPR, the time from cardiopulmonary resuscitation to ECMO), duration of ECMO, pulse pressure loss, complications, and the use of distal perfusion tube and intra-aortic balloon pump (IABP) were compared between the two groups. Univariate and multivariate Logistic regression analyses were performed to identify the risk factors for weaning failure of ECMO. RESULTS: Twenty-three patients (41.07%) were successfully weaned from ECMO. Compared with the successful weaning off group, patients in the failed weaning off group were older (years old: 46.7±15.6 vs. 37.8±16.8, P < 0.05), higher incidence of pulse pressure loss and ECMO complications [81.8% (27/33) vs. 21.7% (5/23), 84.8% (28/33) vs. 39.1% (9/23), both P < 0.01], and longer CCPR time (minutes: 72.3±19.5 vs. 54.4±24.6, P < 0.01), shorter duration of ECMO support (hours: 87.3±81.1 vs. 147.7±50.8, P < 0.01), and worse improvement in arterial blood pH and lactic acid (Lac) levels after ECPR support [pH: 7.1±0.1 vs. 7.3±0.1, Lac (mmol/L): 12.6±2.4 vs. 8.9±2.1, both P < 0.01]. There were no significant differences in the utilization rate of distal perfusion tube and IABP between the two groups. Univariate Logistic regression analysis showed that the factors affecting the weaning off ECMO of ECPR patients were pulse pressure loss, ECMO complications, arterial blood pH and Lac after installation [pulse pressure loss: odds ratio (OR) = 3.37, 95% confidence interval (95%CI) was 1.39-8.17, P = 0.007; ECMO complications: OR = 2.88, 95%CI was 1.11-7.45, P = 0.030; pH after installation: OR = 0.01, 95%CI was 0.00-0.16, P = 0.002; Lac after installation: OR = 1.21, 95%CI was 1.06-1.37, P = 0.003]. After adjusting for the effects of age, gender, ECMO complications, arterial blood pH and Lac after installation, and CCPR time, showed that pulse pressure loss was an independent predictor of weaning failure in ECPR patients (OR = 1.27, 95%CI was 1.01-1.61, P = 0.049). CONCLUSIONS Early loss of pulse pressure after ECPR is an independent predictor of failed weaning off ECMO in ECPR patients. Strengthening hemodynamic monitoring and management after ECPR is very important for the successful weaning off ECMO in ECPR.
Humans ; Extracorporeal Membrane Oxygenation ; Blood Pressure ; Retrospective Studies ; Perfusion ; Cardiopulmonary Resuscitation

Temporary cardiac pacing is an essential technique in the diagnosis and treatment of arrhythmias. Due to its urgency, complexity, and uncertainty, it is necessary to develop an evidence-based emergency operation norms. Currently, there is no specific consensus guidelines at home or abroad. The Emergency Branch of Chinese Medical Association organized relevant experts to draft the Chinese emergency expert consensus on bedside temporary cardiac pacing (2023) to guide the operation and application of bedside cardiac pacing. The formulation of the consensus adopts the consensus meeting method and the evidentiary basis and recommendation grading of the Oxford Center for Evidence-based Medicine in the United States. A total of 13 recommendations were extracted from the discussion on the methods of bedside temporary cardiac pacing, the puncture site of transvenous temporary cardiac pacing, the selection of leads, the placement and placement of leads, pacemaker parameter settings, indications, complications and postoperative management. The recommended consensus includes the choice between transcutaneous and transvenous pacing, preferred venous access for temporary transvenous pacing, the target and best guidance method for implantation of bedside pacing electrodes, recommended default pacemaker settings, recommended indications for sinoatrial node dysfunction, atrioventricular block, acute myocardial infarction, cardiac arrest, ventricular and supraventricular arrhythmias. They also recommended ultrasound guidance and a shortened temporary pacing support time to reduce complications of temporary transvenous cardiac pacing, recommended bedrest, and anticoagulation after temporary transvenous pacing. Bedside temporary cardiac pacing is generally safe and effective. Accurate assessment, correct selection of the pacing mode, and timely performance of bedside temporary cardiac pacing can further improve the survival rate and prognosis of related emergency patients.
Humans ; Cardiac Pacing, Artificial/methods* ; Pacemaker, Artificial ; Arrhythmias, Cardiac/therapy* ; Myocardial Infarction/therapy* ; Electrodes

Objective To investigate the effect of silenced RBM8A gene on the biological behavior (proliferation, migration, and apoptosis) of human endometrial cancer HEC-1A cells and its possible mechanism. Methods The hairpin shRNA targeted by the RBM8A gene was designed, and the best shRNA silencing fragment was screened. The recombinant lentiviral interference vector carrying the target gene was constructed and used to infect HEC-1A cells. Cells with stable knockdown of RBM8A gene were screened by puromycin as the experimental group (shRBM8A), while the shRNA of nonsense sequence was designed as the control group (shControl). CCK-8 method was used to detect cell proliferation, and flow cytometry was used to detect cell apoptosis. Transwell assay was used to detect cell migration and invasion. Western blot was used to analyze the expression of apoptosis-related proteins and EMT signal transduction pathway related proteins. Results In comparison with the shControl group, after RBM8A knockdown, HEC-1A cell proliferation was reduced, apoptosis was increased, migration and invasion ability were significantly inhibited (P < 0.05), the expression of apoptosis-related proteins cleaved caspase 9 and caspase 3 increased, EMT-related protein E-cadherin expression increased, and Vimentin expression decreased. Conclusion RBM8A gene silencing can inhibit the proliferation, migration, and invasion and promote the apoptosis of endometrial cancer cells. The inhibition of EMT signal transduction pathway may be its mechanism.