Background Patients with COVID-19 infection are commonly reported to have an increased risk of venous thrombosis. The choice of anti-thrombotic agents and doses are currently being studied in randomized controlled trials and retrospective studies. There exists a need for individualized risk stratification of venous thromboembolism (VTE) to assist clinicians in decision-making on anticoagulation. We sought to identify the risk factors of VTE in COVID-19 patients, which could help physicians in the prevention, early identification, and management of VTE in hospitalized COVID-19 patients and improve clinical outcomes in these patients. Method This is a multicenter, retrospective database of four main health systems in Southeast Michigan, United States. We compiled comprehensive data for adult COVID-19 patients who were admitted between 1st March 2020 and 31st December 2020. Four models, including the random forest, multiple logistic regression, multilinear regression, and decision trees, were built on the primary outcome of in-hospital acute deep vein thrombosis (DVT) and pulmonary embolism (PE) and tested for performance. The study also reported hospital length of stay (LOS) and intensive care unit (ICU) LOS in the VTE and the non-VTE patients. Four models were assessed using the area under the receiver operating characteristic curve and confusion matrix. Results The cohort included 3531 admissions, 3526 had discharge diagnoses, and 6.68% of patients developed acute VTE (N = 236). VTE group had a longer hospital and ICU LOS than the non-VTE group (hospital LOS 12.2 days vs. 8.8 days, p < 0.001; ICU LOS 3.8 days vs. 1.9 days, p < 0.001). 9.8% of patients in the VTE group required more advanced oxygen support, compared to 2.7% of patients in the non-VTE group (p < 0.001). Among all four models, the random forest model had the best performance. The model suggested that blood pressure, electrolytes, renal function, hepatic enzymes, and inflammatory markers were predictors for in-hospital VTE in COVID-19 patients. Conclusions Patients with COVID-19 have a high risk for VTE, and patients who developed VTE had a prolonged hospital and ICU stay. This random forest prediction model for VTE in COVID-19 patients identifies predictors which could aid physicians in making a clinical judgment on empirical dosages of anticoagulation.

We investigated the effects of early intervention with maternal fecal microbiota and antibiotics on gut microbiota and the metabolites. Five litters of healthy neonatal piglets (Duroc × Landrace × Yorkshire, nine piglets in each litter) were used. Piglets in each litter were orally treated with saline (CO), amoxicillin treatment (AM), or maternal fecal microbiota transplantation (MFMT) on days 1–6, with three piglets in each treatment. Results were compared to the CO group. MFMT decreased the relative abundances of Clostridium sensu stricto and Parabacteroides in the colon on day 7, whereas the abundance of Blautia increased, and the abundance of Corynebacterium in the stomach reduced on day 21. AM reduced the abundance of Arcanobacterium in the stomach on day 7 and reduced the abundances of Streptococcus and Lachnoclostridium in the ileum and colon on day 21, respectively. The metabolite profile indicated that MFMT markedly influenced carbohydrate metabolism and amino acid (AA) metabolism on day 7. On day 21, carbohydrate metabolism and AA metabolism were affected by AM. The results suggest that MFMT and AM discriminatively modulate gastrointestinal microflora and alter the colonic metabolic profiles of piglets and show different effects in the long-term. MFMT showed a location-specific influence on the gastrointestinal microbiota.

Our study showed that the frequency of KRAS mutations in Taiwan was significantly higher than that reported in Caucasians. The occurrence of RAS pathway mutations was associated with recurrent genetic/cytogenetic abnormalities in pediatric B-precursor ALL.

The mutational profiles of acute myeloid leukemia (AML) with partial tandem duplication of mixed-lineage leukemia gene (MLL-PTD) have not been comprehensively studied. We studied 19 gene mutations for 98 patients with MLL-PTD AML to determine the mutation frequency and clinical correlations. MLL-PTD was screened by reverse-transcriptase PCR and confirmed by real-time quantitative PCR. The mutational analyses were performed with PCR-based assays followed by direct sequencing. Gene mutations of signaling pathways occurred in 63.3% of patients, with FLT3-ITD (44.9%) and FLT3-TKD (13.3%) being the most frequent. 66% of patients had gene mutations involving epigenetic regulation, and DNMT3A (32.7%), IDH2 (18.4%), TET2 (18.4%), and IDH1 (10.2%) mutations were most common. Genes of transcription pathways and tumor suppressors accounted for 23.5% and 10.2% of patients. RUNX1 mutation occurred in 23.5% of patients, while none had NPM1 or double CEBPA mutation. 90.8% of MLL-PTD AML patients had at least one additional gene mutation. Of 55 MLL-PTD AML patients who received standard chemotherapy, age older than 50 years and DNMT3A mutation were associated with inferior outcome. In conclusion, gene mutations involving DNA methylation and activated signaling pathway were common co-existed gene mutations. DNMT3A mutation was a poor prognostic factor in MLL-PTD AML.