Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Humans ; Aortic Valve/surgery* ; Retrospective Studies ; Transcatheter Aortic Valve Replacement ; Sex Factors ; Heart Valve Prosthesis Implantation ; Treatment Outcome ; China ; Aortic Valve Stenosis/surgery* ; Risk Factors ; Risk Assessment

Humans ; Retrospective Studies ; Transcatheter Aortic Valve Replacement/adverse effects* ; Risk Assessment ; China ; Prognosis ; Aortic Valve Stenosis/surgery* ; Treatment Outcome ; Risk Factors ; Aortic Valve

BACKGROUND: Management of gastric leak after sleeve gastrectomy (SG) is challenging due to its unpredictable outcomes. We aimed to summarize the characteristics of SG leaks and analyze interventions and corresponding outcomes in a real-world setting. METHODS: To retrospectively review of 15,721 SG procedures from 2010 to 2020 based on a national registry. A cumulative sum analysis was used to identify a fitting curve of gastric leak rate. The Kaplan-Meier method and log-rank tests were performed to calculate and compare the probabilities of relevant outcomes. The logistic regression analysis was conducted to determine the predictors of acute leaks. RESULTS: A total of 78 cases of SG leaks were collected with an incidence of 0.5% (78/15,721) from this registry (6 patients who had the primary SG in non-participating centers). After accumulating 260 cases in a bariatric surgery center, the leak rate decreased to a stably low value of under 1.17%. The significant differences presented in sex, waist circumference, and the proportion of hypoproteinemia and type 2 diabetes at baseline between patients with SG leak and the whole registry population ( P = 0.005, = 0.026, <0.001, and = 0.001, respectively). Moreover, 83.1% (59/71) of the leakage was near the esophagogastric junction region. Leakage healed in 64 (88.9%, 64/72) patients. The median healing time of acute and non-acute leaks was 5.93 months and 8.12 months, respectively. Acute leak (38/72, 52.8%) was the predominant type with a cumulative reoperation rate >50%, whereas the cumulative healing probability in the patients who required surgical treatment was significantly lower than those requring non-surgical treatment ( P = 0.013). Precise dissection in the His angle area was independently associated with a lower acute leak rate, whereas preservation ≥2 cm distance from the His angle area was an independent risk factor. CONCLUSIONS Male sex, elevated waist circumference, hypoproteinaemia, and type 2 diabetes are risk factors of gastric leaks after SG. Optimizing surgical techniques, including precise dissection of His angle area and preservation of smaller gastric fundus, should be suggested to prevent acute leaks.
Humans ; Male ; Retrospective Studies ; Diabetes Mellitus, Type 2/complications* ; Obesity, Morbid ; Anastomotic Leak/epidemiology* ; Gastrectomy/methods* ; Reoperation/methods* ; Registries ; Laparoscopy/methods* ; Treatment Outcome

BACKGROUND: Weather conditions are a possible contributing factor to age-related macular degeneration (AMD), a leading cause of irreversible loss of vision. The present study evaluated the joint effects of meteorological factors and fine particulate matter (PM_2.5) on AMD. METHODS: Data was extracted from a national cross-sectional survey conducted across 10 provinces in rural China. A total of 36,081 participants aged 40 and older were recruited. AMD was diagnosed clinically by slit-lamp ophthalmoscopy, fundus photography, and spectral domain optical coherence tomography (OCT). Meteorological data were calculated by European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis and were matched to participants' home addresses by latitude and longitude. Participants' individual PM_2.5 exposure concentrations were calculated by a satellite-based model at a 1-km resolution level. Multivariable-adjusted logistic regression models paired with interaction analysis were performed to investigate the joint effects of meteorological factors and PM_2.5 on AMD. RESULTS: The prevalence of AMD in the study population was 2.6% (95% CI 2.42-2.76%). The average annual PM_2.5 level during the study period was 63.1 ± 15.3 µg/m³. A significant positive association was detected between AMD and PM_2.5 level, temperature (T), and relative humidity (RH), in both the independent and the combined effect models. For PM_2.5, compared with the lowest quartile, the odds ratios (ORs) with 95% confidence intervals (CIs) across increasing quartiles were 0.828 (0.674,1.018), 1.105 (0.799,1.528), and 2.602 (1.516,4.468). Positive associations were observed between AMD and temperature, with ORs (95% CI) of 1.625 (1.059,2.494), 1.619 (1.026,2.553), and 3.276 (1.841,5.830), across increasing quartiles. In the interaction analysis, the estimated relative excess risk due to interaction (RERI) and the attributable proportion (AP) for combined atmospheric pressure and PM_2.5 was 0.864 (0.586,1.141) and 1.180 (0.768,1.592), respectively, indicating a synergistic effect between PM_2.5 and atmospheric pressure. CONCLUSIONS This study is among the first to characterize the coordinated effects of meteorological factors and PM_2.5 on AMD. The findings warrant further investigation to elucidate the relationship between ambient environment and AMD.
Humans ; Adult ; Middle Aged ; Cross-Sectional Studies ; Air Pollutants/analysis* ; Particulate Matter/analysis* ; China/epidemiology* ; Macular Degeneration/etiology* ; Meteorological Concepts

Objective:To investigate the efficacy of a machine learning model based on radiomics of brain lesions on T 2WI in differentiating multiple sclerosis (MS) from neuromyelitis optica spectrum disorders (NMOSD). Methods:Totally 223 MS and NMOSD patients who were treated from January 2009 to September 2018 in Beijing Tiantan Hospital Affiliated to Capital Medical University, Donghu Branch of the First Affiliated Hospital of Nanchang University, Tianjin Medical University General Hospital, and Xuanwu Hospital of Capital Medical University were analyzed retrospectively, and according to the proportion of 7∶3, 223 patients were completely randomly divided into training set (156 cases) and test set (67 cases). A total of 74 patients with MS and NMOSD who were treated in Huashan Hospital Affiliated to Fudan University and China-Japan Friendship Hospital of Jilin University from January 2009 to September 2018 and in Xianghu Branch of the First Affiliated Hospital of Nanchang University from March 2020 to September 2021 were collected as an independent external validation set. All patients underwent brain cross-sectional MR T 2WI, radiomics features were extracted from T 2WI, and features were selected by max-relevance and min-redundancy and least absolute shrinkage and selection operator algorithms. Then various machine learning classifier models (logistic regression, decision tree, AdaBoost, random forest or support vector machine) were constructed to differentiate MS from NMOSD. The area under curve (AUC) of receiver operating characteristics was used to evaluate the performance of each classifier model in the training set, test set and external validation set. Results:Based on multi-center T 2WI, a total of 11 radiomics features related to the discrimination between MS and NMOSD were extracted and classifier models were constructed. Among them, the random forest model had the best efficiency in distinguishing MS from NMOSD, and its AUC values for distinguishing MS from NMOSD in the training set, test set and external validation set were 1.000, 0.944 and 0.902, with specificity of 100%, 76.9% and 86.0%, and sensitivity of 100%, 92.1% and 79.7%, respectively. Conclusion:The random forest model based on the radiomic features of T 2WI of brain lesions can effectively distinguish MS from NMOSD.

Objective: To investigate the distribution of HIV-1 genetic subtypes and pretreatment drug resistance (PDR) among men who have sex with men (MSM) from 19 cities of 6 provinces in China. Methods: From April to November 2019, 574 plasma samples of ART-naive HIV-1 infected MSM were collected from 19 cities in Hebei, Shandong, Jiangsu, Zhejiang, Fujian, and Guangdong provinces, total ribonucleic acid (RNA) was extracted and amplified the HIV-1 pol gene region by nested polymerase chain reaction (PCR) after reverse transcription. Then sequences were used to construct a phylogenetic tree to determine genetic subtypes and submitted to the Stanford drug resistance database for drug resistance analysis. Results: A total of 479 samples were successfully amplified by PCR. The HIV-1 genetic subtypes included CRF01_AE, CRF07_BC, B, CRF55_01B, CRF59_01B, CRF65_cpx, CRF103_01B, CRF67_01B, CRF68_01B and unrecognized subtype, which accounted for 43.4%, 36.3%, 6.3%, 5.9%, 0.8%, 0.8%, 0.4%, 0.4%, 0.2% and 5.5%, respectively. The distribution of genetic subtypes among provinces is statistically different (χ²=44.141, P<0.001). The overall PDR rate was 4.6% (22/479), the drug resistance rate of non-nucleoside reverse transcriptase inhibitors, nucleoside reverse transcriptase inhibitors, and protease inhibitors were 3.5% (17/479), 0.8% (4/479) and 0.2% (1/479), respectively. The PDR rate of recent infections was significantly higher than that of long-term infections (χ²=4.634, P=0.031). Conclusions: The HIV-1 genetic subtypes among MSM infected with HIV-1 from 19 cities of 6 provinces in China are diverse, and the distribution of subtypes is different among provinces. The overall PDR rate is low, while the PDR rate of recent infections was significantly higher than that of long-term infections, suggesting the surveillance of PDR in recent infections should be strengthened.
China/epidemiology* ; Cities ; Drug Resistance ; Drug Resistance, Viral/genetics* ; Female ; Genotype ; HIV Infections/epidemiology* ; HIV Seropositivity/drug therapy* ; HIV-1/genetics* ; Homosexuality, Male ; Humans ; Male ; Phylogeny ; Reverse Transcriptase Inhibitors/therapeutic use* ; Sexual and Gender Minorities

Objective To establish a deep learning-based visual model for intelligent recognition of Oncomelania hupensis, the intermediate host of Schistosoma japonicum, and evaluate the effects of different training strategies for O. hupensis image recognition. Methods A total of 2 614 datasets of O. hupensis snails and 4 similar snails were generated through field sampling and internet capture, and were divided into training sets and test sets. An intelligent recognition model was created based on deep learning, and was trained and tested. The precision, sensitivity, specificity, accuracy, F1 score and Youden index were calculated. In addition, the receiver operating characteristic (ROC) curve of the model for snail recognition was plotted to evaluate the effects of “new learning”, “transfer learning” and “transfer learning + data enhancement” training strategies on the accuracy of the model for snail recognition. Results Under the “transfer learning + data enhancement” strategy, the precision, sensitivity, specificity, accuracy, Youden index and F1 score of the model were 90.10%, 91.00%, 97.50%, 96.20%, 88.50% and 90.51% for snail recognition, which were all higher than those under both “new learning” and “transfer learning” strategies. There were significant differences in the sensitivity, specificity and accuracy of the model for snail recognition under “new learning”, “transfer learning” and “transfer learning + data enhancement” training strategies (all P values < 0.001). In addition, the area under the ROC curve of the model was highest (0.94) under the “transfer learning + dataenhancement” training strategy. Conclusions This is the first visual model for intelligent recognition of O. hupensis based on deep learning, which shows a high accuracy for snail image recognition. The “transfer learning + data enhancement” training strategy is helpful to improve the accuracy of the model for snail recognition.

Objective:To systematically evaluate the efficacy of oral Chinese herbal prescriptions combined with transcatheter arterial chemoembolization （TACE） against primary hepatic carcinoma （PHC） and screen the basic Chinese herbs，in order to provide certain reference for clinical medication. Method:The randomized controlled trials concerning the treatment of PHC with oral Chinese herbal prescriptions plus TACE were retrieved from CBM，China National Knowledge Infrastructure （CNKI），Chongqing Weipu Database for Chinese Technical Periodicals （VIP），and Wanfang Data Knowledge Service Platform.The quality of the included trials was evaluated by Cochrane handbook，and the Meta-analysis was performed using RevMan 5.3.The enumeration data were expressed by odds ratio （OR），the measurement data by mean difference （MD） or standardized mean difference （SMD），and the effect size by 95% confidence interval （CI）.The data of oral Chinese herbal prescriptions involved in trials were sorted out and subjected to association rule analysis and frequency analysis based on the Traditional Chinese Medicine Inheritance Support System （TCMISS），for exploring the basic Chinese herbs and their dosages against PHC. Result:A total of 75 randomized controlled trials were included，involving 7 406 cases. As revealed by the Meta-analysis，oral Chinese herbal prescriptions combined with TACE was significantly better than TACE alone in improving the short-term curative effect ［OR=2.05，95%CI（1.83，2.29）］，decreasing alpha fetoprotein （AFP） ［MD=-59.02，95%CI（-79.03，-39.01）］，ameliorating liver function ［SMD=-1.23，95%CI（-1.58，-0.88）］，boosting immunity ［SMD=1.08，95%CI（0.84，1.32）］，adjusting Karnofsky Performance Status （KPS） scale score ［OR=2.7，95%CI（1.11，11.02）］，elevating survival rate ［OR=2.31，95%CI（1.96，2.71）］，and reducing adverse reactions ［OR=0.38，95%CI（0.34，0.43）］.Data mining results showed that the basic Chinese herbs against PHC were Bupleuri Radix，Paeoniae Alba Radix，Atractylodis Macrocephalae Rhizoma，Poria，and Glycyrrhizae Radix et Rhizoma，with their clinical dosages listed as follows：6-15 g for Bupleuri Radix，10-15 g for Paeoniae Alba Radix，9-15 g for Atractylodis Macrocephalae Rhizoma，10-15 g for Poria，and 3-10 g for Glycyrrhizae Radix et Rhizoma. Conclusion:The oral Chinese herbal prescriptions combined with TACE produce better effects in treatment of PHC as compared with TACE alone.These five basic Chinese herbs have anti-cancer effect，and their dosages are within the ranges stipulated in 2020 edition of Chinese Pharmacopoeia.This Meta-analysis has provided certain reference for clinical medication.

Aortic Valve/surgery* ; Aortic Valve Stenosis/surgery* ; China/epidemiology* ; Heart Valve Prosthesis Implantation ; Humans ; Severity of Illness Index ; Treatment Outcome