METHODS: Experimental infections, morphological and molecular characterizations were used for discrimination of a new Sarcocystis species isolated from colubrid snakes and small mammals collected in Thailand, Borneo and China.
RESULTS: We identified a new species, Sarcocystis muricoelognathis sp. nov., that features a relatively wide geographic distribution and infects both commensal and forest-inhabiting intermediate hosts. Sarcocystis sporocysts collected from rat snakes (Coelognathus radiatus, C. flavolineatus) in Thailand induced development of sarcocysts in experimental SD rats showing a type 10a cyst wall ultrastructure that was identical with those found in Rattus norvegicus from China and the forest rat Maxomys whiteheadi in Borneo. Its cystozoites had equal sizes in all intermediate hosts and locations, while sporocysts and cystozoites were distinct from other Sarcocystis species. Partial 28S rRNA sequences of S. muricoelognathis from M. whiteheadi were largely identical to those from R. norvegicus in China but distinct from newly sequenced Sarcocystis zuoi. The phylogeny of the nuclear 18S rRNA gene placed S. muricoelognathis within the so-called S. zuoi complex, including Sarcocystis attenuati, S. kani, S. scandentiborneensis and S. zuoi, while the latter clustered with the new species. However, the phylogeny of the ITS1-region confirmed the distinction between S. muricoelognathis and S. zuoi. Moreover, all three gene trees suggested that an isolate previously addressed as S. zuoi from Thailand (KU341120) is conspecific with S. muricoelognathis. Partial mitochondrial cox1 sequences of S. muricoelognathis were almost identical with those from other members of the group suggesting a shared, recent ancestry. Additionally, we isolated two partial 28S rRNA Sarcocystis sequences from Low's squirrel Sundasciurus lowii that clustered with those of S. scandentiborneensis from treeshews.
CONCLUSIONS: Our results provide strong evidence of broad geographic distributions of rodent-associated Sarcocystis and host shifts between commensal and forest small mammal species, even if the known host associations remain likely only snapshots of the true associations.
BACKGROUND: Smartphones have become indispensable tools for students. However, excessive use can lead to smartphone addiction, causing physiological, psychological and social harm. Nursing students represent a unique population whose smartphone use may differ from other disciplines due to clinical training demands.
METHODS: A scoping review was conducted following the Arksey and O'Malley framework. Seven databases were systematically searched from inception to August 2023. Inclusion criteria encompassed original research on smartphone addiction, harms and risks among nursing students. Data were extracted and thematically synthesized.
RESULTS: Studies (n=39) met inclusion criteria, representing 15 countries. Rates of smartphone addiction among nursing students ranged from 19% to 72%, averaging 40-50%. Incorporated into Engel's biopsychosocial models, the harm is emphasized across individual inclinations, emotional aspects, cognitive processes and executive functions. Physiological harms include sleep disruption, vision concerns,other physiological concerns. psychologically, addiction correlated with increased anxiety and depression,decline in self-esteem, learning and attention and other psychological concerns. socially, it encompasses harms such as interpersonal relationships challenges, career development and decline in social abilities. The I-PACE model identifies various risk factors for smartphone addiction among nursing students, including personal factors such as interpersonal relationship anxiety and perceived academic pressure, affective factors like high stress and learning burnout, cognitive factors such as the need for online social interaction and low perception of social support, as well as executive factors like extended usage duration, poor self-control and usage before sleep.
CONCLUSION: Smartphone addiction among nursing students presents tangible harms. A proposed theoretical model integrating established frameworks provides avenues to better comprehend addiction genesis and potential intervention strategies. Given addiction's multi-factorial nature, future research investigating harm mitigation through optimizing predisposing, precipitating and perpetuating factors is warranted.
METHODS: Prospectively collected data from the AARC database were analyzed.
RESULTS: Of the 1249 AH patients, (aged 43.8 ± 10.6 years, 96.9% male, AARC score 9.2 ± 1.9), 38.8% died on a 90 day follow-up. Of these, 150 (12.0%) had mild-moderate AH (MAH), 65 (5.2%) had SAH and 1034 (82.8%) had ACLF. Two hundred and eleven (16.9%) patients received CS, of which 101 (47.87%) were steroid responders by day 7 of Lille's model, which was associated with improved survival [Hazard ratio (HR) 0.15, 95% CI 0.12-0.19]. AARC-ACLF grade 3 [OR 0.28, 0.14-0.55] was an independent predictor of steroid non-response and mortality [HR 3.29, 2.63-4.11]. Complications increased with degree of liver failure [AARC grade III vs. II vs I], bacterial infections [48.6% vs. 37% vs. 34.7%; p
METHODS: We recruited ACLF patients between 2009 and 2020 from APASL-ACLF Research Consortium (AARC). Their clinical data, investigations and organ involvement were serially noted for 90-days and utilized for AI modelling. Data were split randomly into train and validation sets. Multiple AI models, MELD and AARC-Model, were created/optimized on train set. Outcome prediction abilities were evaluated on validation sets through area under the curve (AUC), accuracy, sensitivity, specificity and class precision.
RESULTS: Among 2481 ACLF patients, 1501 in train set and 980 in validation set, the extreme gradient boost-cross-validated model (XGB-CV) demonstrated the highest AUC in train (0.999), validation (0.907) and overall sets (0.976) for predicting 30-day outcomes. The AUC and accuracy of the XGB-CV model (%Δ) were 7.0% and 6.9% higher than the standard day-7 AARC model (p
Methods: This was a worldwide multi-institutional survey among members of the International Society of EUS Task Force (ISEUS-TF). The survey was administered by E-mail through the SurveyMonkey website. In some cases, percentage agreement with some statements was calculated; in others, the options with the greatest numbers of responses were summarized. Another questionnaire about the level of recommendation was designed to assess the respondents' answers.
Results: ISEUS-TF members developed a questionnaire containing 17 questions that was sent to 53 experts. Thirty-five experts completed the survey within the specified period. Among them, 40% and 54.3% performed 50-200 and more than 200 EUS sampling procedures annually, respectively. Some practice patterns regarding FNA/FNB were recommended.
Conclusion: This is the first worldwide survey of EUS-FNA and FNB practice patterns. The results showed wide variations in practice patterns. Randomized studies are urgently needed to establish the best approach for optimizing the FNA/FNB procedures.
METHODS: Prospectively collected data of ACLF patients from APASL-ACLF Research Consortium (AARC) was analyzed for 30-day outcomes. The models evaluated at days 0, 4, and 7 of presentation for 30-day mortality were: AARC (model and score), CLIF-C (ACLF score, and OF score), NACSELD-ACLF (model and binary), SOFA, APACHE-II, MELD, MELD-Lactate, and CTP. Evaluation parameters were discrimination (c-indices), calibration [accuracy, sensitivity, specificity, and positive/negative predictive values (PPV/NPV)], Akaike/Bayesian Information Criteria (AIC/BIC), Nagelkerke-R2, relative prediction errors, and odds ratios.
RESULTS: Thirty-day survival of the cohort (n = 2864) was 64.9% and was lowest for final-AARC-grade-III (32.8%) ACLF. Performance parameters of all models were best at day 7 than at day 4 or day 0 (p 12 had the lowest 30-day survival (5.7%).
CONCLUSIONS: APASL-ACLF is often a progressive disease, and models assessed up to day 7 of presentation reliably predict 30-day mortality. Day-7 AARC model is a statistically robust tool for classifying risk of death and accurately predicting 30-day outcomes with relatively lower prediction errors. Day-7 AARC score > 12 may be used as a futility criterion in APASL-ACLF patients.
METHODS: A prospective-retrospective cohort of 985 patients was identified from the APASL-ACLF Research Consortium (AARC) database and the Chinese Study Group. Complications of ACLF (ascites, infection, hepatorenal syndrome, hepatic encephalopathy, upper gastrointestinal bleeding) as well as cirrhosis and the current main prognostic models were measured for their predictive ability for 28- or 90-day mortality.
RESULTS: A total of 709 patients with HBV-ACLF as defined by the AARC criteria were enrolled. Among these HBV-ACLF patients, the cirrhotic group showed significantly higher mortality and complications than the non-cirrhotic group. A total of 36.1% and 40.1% of patients met the European Association for the Study of Liver (EASL)-Chronic Liver Failure consortium (CLIF-C) criteria in the non-cirrhotic and cirrhotic groups, respectively; these patients had significantly higher rates of mortality and complications than those who did not satisfy the CLIF-C criteria. Furthermore, among patients who did not meet the CLIF-C criteria, the cirrhotic group exhibited higher mortality and complication rates than the non-cirrhotic group, without significant differences in organ failure. The Tongji prognostic predictor model score (TPPMs), which set the number of complications as one of the determinants, showed comparable or superior ability to the Chinese Group on the Study of Severe Hepatitis B-ACLF score (COSSH-ACLFs), APASL-ACLF Research Consortium score (AARC-ACLFs), CLIF-C organ failure score (CLIF-C OFs), CLIF-C-ACLF score (CLIF-C-ACLFs), Model for End-Stage Liver Disease score (MELDs) and MELD-sodium score (MELD-Nas) in HBV-ACLF patients, especially in cirrhotic HBV--ACLF patients. Patients with two (OR 4.70, 1.88) or three (OR 8.27, 2.65) complications had a significantly higher risk of 28- or 90-day mortality, respectively.
CONCLUSION: The presence of complications is a major risk factor for mortality in HBV-ACLF patients. TPPM possesses high predictive ability in HBV-ACLF patients, especially in cirrhotic HBV-ACLF patients.
METHODS: We identified drugs as precipitants of ACLF among prospective cohort of patients with ACLF from the Asian Pacific Association of Study of Liver (APASL) ACLF Research Consortium (AARC) database. Drugs were considered precipitants after exclusion of known causes together with a temporal association between exposure and decompensation. Outcome was defined as death from decompensation.
RESULTS: Of the 3,132 patients with ACLF, drugs were implicated as a cause in 329 (10.5%, mean age 47 years, 65% men) and other nondrug causes in 2,803 (89.5%) (group B). Complementary and alternative medications (71.7%) were the commonest insult, followed by combination antituberculosis therapy drugs (27.3%). Alcoholic liver disease (28.6%), cryptogenic liver disease (25.5%), and non-alcoholic steatohepatitis (NASH) (16.7%) were common causes of underlying liver diseases. Patients with drug-induced ACLF had jaundice (100%), ascites (88%), encephalopathy (46.5%), high Model for End-Stage Liver Disease (MELD) (30.2), and Child-Turcotte-Pugh score (12.1). The overall 90-day mortality was higher in drug-induced (46.5%) than in non-drug-induced ACLF (38.8%) (P = 0.007). The Cox regression model identified arterial lactate (P < 0.001) and total bilirubin (P = 0.008) as predictors of mortality.
DISCUSSION: Drugs are important identifiable causes of ACLF in Asia-Pacific countries, predominantly from complementary and alternative medications, followed by antituberculosis drugs. Encephalopathy, bilirubin, blood urea, lactate, and international normalized ratio (INR) predict mortality in drug-induced ACLF.