Simultaneous determination of multiple components in rat plasma by UHPLC-sMRM for pharmacokinetic studies after oral administration of Qingjin Yiqi Granules

As a Traditional Chinese Medicine prescription, Qingjin Yiqi Granules (QJYQ) provides an effective treatment for patients recovering from COVID-19. However, the pharmacokinetics characteristics of the main components of QJYQ in vivo are still unknown. An efficacious ultra-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) was developed and validated for the simultaneous determination of 33 components in rat plasma after oral administration of QJYQ. The plasma samples were precipitated with 400 µL methanol/acetonitrile (1/1, v/v) and analyzed in scheduled multiple reaction monitoring mode. The linear relationship of the 33 components was good (r > 0.9928). The lower limit of quantification for 33 components ranged from 0.4–60.5 ng/mL. The average recoveries and matrix effects of the analytes ranged from 72.9% to 115.0% with RSD of 1.4%–15.0%. All inter-day and intra-day RSDs were within 15.0%. After oral administration (3.15 g/kg), the validated approach was effectively applied to the pharmacokinetics of main components of QJYQ. Finally, fifteen main constituents of QJYQ with large plasma exposure were obtained, including baicalin, wogonoside, wogonin, apigenin-7-O-glucuronide, verbenalin, isoferulic acid, hesperidin, liquiritin, harpagide, protocatechuic acid, p-Coumaric acid, ferulic acid, sinapic acid, liquiritin apioside and glycyrrhizic acid. The present research lays a foundation for clarifying the therapeutic material basis of QJYQ and provides a reference for further scientific research and clinical application of QJYQ.

An efficient method for qualitation and quantitation of multi-components of the herbal medicine Qingjin Yiqi Granules.

Qingjin Yiqi Granules (QJYQ) is a Traditional Chinese Medicines (TCMs) prescription for the patients with post-COVID-19 condition. It is essential to carry out the quality evaluation of QJYQ. A comprehensive investigation was conducted by establishing deep-learning assisted mass defect filter (deep-learning MDF) mode for qualitative analysis, ultra-high performance liquid chromatography and scheduled multiple reaction monitoring method (UHPLC-sMRM) for precise quantitation to evaluate the quality of QJYQ. Firstly, a deep-learning MDF was used to classify and characterize the whole phytochemical components of QJYQ based on the mass spectrum (MS) data of ultra-high performance liquid chromatography quadrupole time of flight tandem mass spectrometry (UHPLC-Q-TOF/MS). Secondly, the highly sensitive UHPLC-sMRM data-acquisition method was established to quantify the multi-ingredients of QJYQ. Totally, nine major types of phytochemical compounds in QJYQ were intelligently classified and 163 phytochemicals were initially identified. Furthermore, fifty components were rapidly quantified. The comprehensive evaluation strategy established in this study would provide an effective tool for accurately evaluating the quality of QJYQ as a whole.

Association between risk of venous thromboembolism and mortality in patients with COVID-19.

OBJECTIVES: To investigate the association of risk of venous thromboembolism with 30-day mortality in COVID-19 patients. METHODS: A total of 1030 COVID-19 patients were retrospectively collected, with baseline data on demographics, sequential organ failure assessment (SOFA) score, and VTE risk assessment models (RAMs), including Padua prediction score (PPS), International Medical Prevention Registry (IMPROVE), and Caprini. RESULTS: Thirty-day mortality increased progressively from 2% in patients at low VTE risk to 63% in those at high risk defined by PPS. Similar findings were observed in IMPROVE and Caprini scores. Progressive increases in VTE risk were also associated with higher SOFA score. High risk of VTE was independently associated with mortality regardless of adjusted gender, smoking status and some comorbidities, with hazard ratios of 29.19, 37.37 and 20.60 for PPS, IMPROVE and Caprini RAM, respectively (P < 0.001 for all comparisons). The predictive accuracy of PPS (area under curve (AUC) 0.900), IMPROVE (AUC 0.917), or Caprini (AUC 0.861) RAM for risk of hospitalized mortality was unexpectedly strong. CONCLUSIONS: We established that the presence of a high risk of VTE identifies a group of COVID-19 patients at higher risk for mortality. Furthermore, there is a high accuracy of VTE RAMs to predict mortality in these patients.

Derivation and validation of a prognostic model for predicting in-hospital mortality in patients admitted with COVID-19 in Wuhan, China: the PLANS (platelet lymphocyte age neutrophil sex) model.

BACKGROUND: Previous published prognostic models for COVID-19 patients have been suggested to be prone to bias due to unrepresentativeness of patient population, lack of external validation, inappropriate statistical analyses, or poor reporting. A high-quality and easy-to-use prognostic model to predict in-hospital mortality for COVID-19 patients could support physicians to make better clinical decisions. METHODS: Fine-Gray models were used to derive a prognostic model to predict in-hospital mortality (treating discharged alive from hospital as the competing event) in COVID-19 patients using two retrospective cohorts (n = 1008) in Wuhan, China from January 1 to February 10, 2020. The proposed model was internally evaluated by bootstrap approach and externally evaluated in an external cohort (n = 1031). RESULTS: The derivation cohort was a case-mix of mild-to-severe hospitalized COVID-19 patients (43.6% females, median age 55). The final model (PLANS), including five predictor variables of platelet count, lymphocyte count, age, neutrophil count, and sex, had an excellent predictive performance (optimism-adjusted C-index: 0.85, 95% CI: 0.83 to 0.87; averaged calibration slope: 0.95, 95% CI: 0.82 to 1.08). Internal validation showed little overfitting. External validation using an independent cohort (47.8% female, median age 63) demonstrated excellent predictive performance (C-index: 0.87, 95% CI: 0.85 to 0.89; calibration slope: 1.02, 95% CI: 0.92 to 1.12). The averaged predicted cumulative incidence curves were close to the observed cumulative incidence curves in patients with different risk profiles. CONCLUSIONS: The PLANS model based on five routinely collected predictors would assist clinicians in better triaging patients and allocating healthcare resources to reduce COVID-19 fatality.

DVT incidence and risk factors in critically ill patients with COVID-19.

Few data are available on the incidence of deep vein thrombosis (DVT) in critically ill COVID-19 with thrombosis prophylaxis. This study retrospectively included 88 patients in the ICU with critically ill COVID-19 at Jinyintan Hospital in Wuhan, China. All patients underwent compression ultrasonography for identifying DVT. Firth logistic regression was used to examine the association of DVT with sex, age, hypoalbuminemia, D-dimer, and SOFA score. The median (interquartile range [IQR]) age and SOFA score of 88 patients were 63 (55-71) years old and 5 (4-6), respectively. Despite all patients receiving guideline-recommended low-molecular-weight heparin (LMWH) thromboprophylaxis, the incidence of DVT was 46% (95% CI 35-56%). Proximal DVT was recognized in 9% (95% CI 3-15%) of the patients, while 46% (95% CI 35-56%) of patients had distal DVT. All of the proximal DVT combined with distal DVT. Risk factors of DVT extension occurred in all distal DVT patients. As Padua score ≥ 4 or IMPROVE score ≥ 2, 53% and 46% of patients had DVT, respectively. Mortality was higher in patients with acute DVT (30%) compared with non-DVT (17%), but did not reach statistical significance. Hypoalbuminemia (odds ratio [OR], 0.17; 95% CI 0.06-0.05, P = 0.001), higher SOFA score (OR per IQR, 2.07; 95% CI 1.38-3.39, P = 0.001), and elevated D-dimer (OR per IQR, 1.04; 95% CI 1.03-1.84, P = 0.029) were significant DVT risk factors in multivariable analyses. High incidence of DVT was identified in patients with critically ill COVID-19, despite the use of guideline-recommended pharmacologic thromboprophylaxis. The presence of hypoalbuminemia, higher SOFA score, and elevated D-dimer were significantly independent risk factors of DVT. More effective VTE prevention and management strategies may need to be addressed.