A bibliometric analysis of the application of artificial intelligence to advance individualized diagnosis and treatment of critical illness.

Background: Artificial intelligence (AI) has been extensively applied in the individualized diagnosis and treatment of critical illness, and numerous studies have been published on this topic. Therefore, a bibliometric analysis of these publications should be performed to provide a direction of hot topics and future research trends. Methods: A bibliometric analysis was performed on the research articles to identify the hot topics and any unsolved issues regarding the use of AI in individualized diagnosis and treatment of critical illness. Articles published from January 2011 to December 2021 were retrieved from the Web of Science (WOS) core collection database for bibliometric analysis, and a cross-sectional analysis of the relevant studies that had been registered at ClinicalTrials.gov was also conducted. Results: The number of articles published showed an annually increasing trend, with a worldwide geographic distribution over the past decade. Ultimately, 427 research articles were included in the bibliometric analysis. The relevant articles were divided into four separate clusters that focused on AI application aspects, prediction model establishment, coronavirus disease 2019 (COVID-19) treatment and outcome assessments, respectively. "Machine learning" was the most frequent keyword (147 occurrences, 165 links, and 395 total link strengths) followed by "risk", "models", and "mortality". With 205 articles, the United States of America (USA) had interacted the most with other countries (20 links, and 94 total link strength), while the domestic research institutes in China had infrequently collaborated with others. Approximately 130 trials focusing on the application of AI in the intensive care unit (ICU) and emergency department (ED) had been registered at ClinicalTrial.gov, and most of them (n=71, 54.6%) were interventional. The main research objectives of these trials were to provide decision making assistance and establish prediction models. However, only 3.8% (5 trials) of them had reached exact conclusions which favored the application of AI. Conclusions: The application of AI has raised great interest in critical illness and has mainly been focused on decision making assistance and prediction model establishment. Cooperation between agencies engaged in AI research needs to be strengthened. An increasing number of trials have been registered at ClinicalTrial.gov, and the results of them are promising. Keywords: Bibliometric analysis; artificial intelligence (AI); individualized diagnosis; critical care medicine; emergency department (ED).

[Effects of hydrogen sulfide on myocardial fibrosis and MAPK1/3 and MMP-8 expression in diabetic rats].

OBJECTIVE: To explore the effects of hydrogen sulfide (H(2)S) on myocardial fibrosis and expressions of MAPK1/3 and MMP-8 in diabetic rats. METHODS: Forty adult male SD rats were randomized into 4 groups, namely the control group, diabetes mellitus group (STZ group), diabetes mellitus with H(2)S treatment group (STZ+H(2)S group), and normal rats with H(2)S treatment group (H(2)S group). Diabetes was induced by intraperitoneal injections of 40 mg/kg streptozotocin (STZ). The rats in the control group received daily intraperitoneal injections of saline, and those in STZ+H(2)S group and H(2)S group were given NaHS (100 µmol/kg) injections. After 8 weeks, the pathologies of cardiac fibrosis were examined with HE staining, and the expressions of collagen I, MAPK1/3 and MMP-8 were analyzed with Western blotting. RESULTS: Compared with the control group, the diabetic rats showed increased collagen content and obvious interstitial fibrosis in the myocardial tissue with significantly increased expression levels of collagen I, MAPK1/3 and MMP-8 (P<0.05); all these changes were obviously reversed by treatment with H(2)S (P<0.05). Collagen I, MAPK1/3 and MMP-8 expression levels and the degree of myocardial fibrosis were comparable between H(2)S group and control group (P>0.05). CONCLUSION: Hydrogen sulfide can attenuate cardiac fibrosis in diabetic rats, and the mechanism may involve the inhibition of MAPK1/3/MMP-8 signal pathway.

[Uterine involution after cesarean section promoted with acupuncture: a randomized controlled trial].

OBJECTIVE: To explore the effect and feasibility of acupuncture in uterine involution after cesarean section. METHODS: Seventy cases of cesarean section in primipara were randomized into an observation group (33 cases) and a control group (37 cases). In the control group, the conventional treatment was adopted after cesarean section. In the observation group, on the basic treatment as the control group, acupuncture was applied at Sanyinjiao (SP 6), Hegu (LI 4), Qihai (CV 6) and Guanyuan (CV 4). In 2 h after operation, acupuncture started, once a day, continuously for five times. The daily height of uterine fundus, daily uterine fundus decreasing degree, postpartum blood loss, lochia duration and ultrasonic B test in 42 days of postpartum were compared between the two groups. RESULTS: The therapeutic methods of the two groups all promoted uterine contraction. The postpartum height of uterine fundus in the observation group was lower than that in the control group (all P<0.05) and the uterine fundus decreasing degree was higher than that in the control group (all P<0.05). The blood loss in 2 h, 6 to 12 h and 24 to 48 h of postpartum was less than that in the control group (all P<0.05). The lochia duration in the observation group was shorter than that in the control group (P<0.05). CONCLUSION: Acupuncture promotes uterine contraction, reduces postpartum blood loss and lochia duration and benefits uterine involution after cesarean section.

[Determination of avermectin and ivermectin in swine muscular tissues using high performance liquid chromatography-tandem mass spectrometry].

OBJECTIVE: To develop a method for simultaneous determination of avermectin (AVM) and ivermectin (IVM) in swine muscular tissues using high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). METHODS: The AVM and IVM were extracted with acetonitrile, cleaned with basic alumina solid phase extraction cartridges, separated through C8 column, and then detected by mass spectrometry in positive ion mode with multiple reaction monitoring (MRM) using an electrospray ionization interface, with quantitative ion pair of 890.4/305.3 and 892.5/307.3 for AVM and IVM, respectively. RESULTS: The linear ranges for both AVM and IVM were between 5 microg/L and 100 microg/L, with a correlation coefficient of 0.9999. The detection limit was 2.0 microg/kg. The recoveries at the spiked concentration of 2 microg/kg, 10 microg/kg and 20 microg/kg ranged from 77.4% to 83.1% for AVM and 77.2% to 84.8% for IVM, with relative standard deviation (RSD) ranging from 8.7% to 11.7% for AVM and 6.3% to 10.3% for IVM, respectively. No AVM and IVM residues were detected in samples taken from Chengdu markets. CONCLUSION: A HPLC-MS/MS method was successfully developed for determining AVM and IVM in swine muscular tissues, which is simple, sensitive and precise and can meet both domestic and international requirements.