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Background: Few studies have examined the association between treatment given time and clinical outcomes, which is indeed of great importance to clinical management of coronavirus disease 2019 (COVID-19). We performed this study to explore whether early treatment brings favorable clinical outcomes. Methods: In this retrospective multicenter study, we included patients aged 18 to 87 years with confirmed COVID-19 on admission from 54 hospitals in nine provinces of China from 21 January to 10 March, 2020. Final date of follow-up was March 17, 2020. All patients were treated by Lung cleansing & detoxifying decoction combined with western medicine. Patients were divided into four groups according to the interval from the first date of onset of symptoms to the date of starting a treatment, i.e., ≤1 week group (≤7 days), 1-2 weeks group (>7 days and ≤14 days), 2-3 weeks group (>14 days and ≤21 days) and >3 weeks group (>21 days). Multivariable Cox proportional hazard ratio (HR) models were used to estimate unadjusted and adjusted HRs and 95% confidence intervals (CIs) for the association between the treatment given time and clinical outcomes (time to recovery, days of viral shedding, duration of hospital stay, course of disease, fever and CT images). Findings: Of the 782 patients (median age was 46 years old, and 405 (52%) were male), there were 321 (41%) patients in ≤1 week group, 221 (28%) in 1-2 weeks group, 123 (16%) in 2-3 weeks group and 117 (15%) in >3 weeks group. Compared to patients in later treatment group (greater than 3 weeks), patients in earlier treatment groups of less than 1 week, 1 to 2 weeks, or 2 to 3 weeks had higher likelihood of recovery, with adjusted HR (95% CI) of 3.81 (2.65-5.48), 2.63 (1.86-3.73) and 1.92 (1.34-2.75), respectively. The median days of viral shedding was 13 days and 12 days in 2-3 weeks group and 3 weeks group (P=0.0137). The median course of disease decreased from 34 days to 24 days, 21 days and 18 days when treatment was given every one week in advance compared to that was given later than 3 weeks from the onset of symptoms (P

Background: Novel coronavirus pneumonia (NCP) is often changing rapidly and fatal. Early detection and early triage of coronavirus disease 2019 (Covid-19) is the key to success management of the disease. An easily obtainable yet accurate variable for both diagnosis and prognosis is urgently needed. We aim to report predictive Value of the Neutrophil-to-Lymphocyte Ratio(NLR) for diagnosis and worse clinical course of the COVID-19, which have not been well demonstrated. Methods: Our study consisted of two stages, at the first stage, a retrospective, single-center, cohort study including was conducted in Heilongjiang, on admission, demographic, clinical, and laboratory data were collected and compared between patients with COVID-19 and patients with non COVID-19; we used multivariable logistic regression methods to explore the risk factors associated with COVID-19;A receiver operating characteristic(ROC) analysis was conducted to calculate the area under the curve(AUC) to assess predictive value of NLR for diagnosis of COVID 19. At the second stage, we conducted retrospective, multi-center and large sample study in 43 hospitals from ten provinces of China, COVID-19 patients with laboratory-confirmed divided into three groups including mild cases, ordinary cases and severe cases. Multivariate logistic regression methods were used to identify the risk factors for the deterioration of COVID-19, along with, a receiver operating characteristic (ROC) curve was also drawn to assess impact on the clinical course of the COVID-19. Findings: We recruited a total of 635 patients with COVID-19 and 27 cases with non COVID-19(Viral pneumonia) from 28 January to 25 February. A total of 88 cases were enrolled with a retrospective, single-center, cohort study from Heilongjiang province, of these, COVID-19 cases were 61(69%) and non COVID-19 cases were 27(31%). On admission, fever (69%) was the most common symptoms, cough (56%) and fatigue(53%). An average(SD) of NLR of COVID-19 patients and non- COVID-19 patients were3.48±2.04 and 2.21±1.14, respectively. multivariable regression showed increasing odds of COVID-19 patients associated with NLR(odds ratio 1.752, 95% CI 1.111-2.763, per 1 unit increase; p=0.016). In addition, the area under the curve (AUC) of NLR was 0.707 and cutoff value was 2.22. At the second stage, 635 patients with COVID were enrolled with a retrospective, multi-center, large sample study in the 43 settings from 10 provinces, of these, mild case were 86(14%), ordinary cases [486(76%)],severe cases[63(10%)], common symptoms was at onset of disease were cough[356(56%)], an average of NLR of 635 patients was 4.04±4.68, and elevated NLR with the deterioration of clinical course[mild case(2.73±2.28), ordinary cases(3.58±3.07), severe cases(9.38±10.52), P

Numerous chiral drugs have been developed for neurological diseases, but chiral drug safety and pharmacological research still faces great challenges in enantioselectivity and sensitivity of chiral analysis. A rapid, stable and high-efficiency gold nanodendrite-based electrochemical sensing method was proposed as a versatile differential potential ratiometric strategy for highly selective chiral recognition of dual 3,4-dihydroxyphenylalanine (DOPA) enantiomers. Using simple electrochemical deposition, the gold nanodendrite (AuND) membrane was steadily modified on the glassy carbon electrode (GCE) with high specific chiral identifiability and robust signal amplifiability. Based on a sequence of systematic optimization, an apparent potential difference (PD) was detected up to 108 mV from oxidation peaks of DOPA enantiomers. Furthermore, according to a regulatable concentration range from 10 μM to 100 μM, different proportions of L-/d-DOPA had a good linear relationship with corresponding peak potentials (Eps) in the racemic mixture. Superior to traditional enantiorecognition of single chiral drug, both DOPA enantiomers enabled to be simultaneously distinguished with high repeatability, selectivity, and anti-interference ability on the AuND/GCE. This unique semi-quantitative AuND-based potential sensing strategy was proposed to efficiently quantify the proportion of L-/d-DOPA for chiral drug recognition, emerging positive potential for numerous applications in pharmacology and clinical diagnosis.

Graphical abstract, The coronavirus disease 2019 (COVID-19) epidemic has been almost controlled in China under a series of policies, including “early diagnosis and early treatment”. This study aimed to explore the association between early treatment with Qingfei Paidu decoction (QFPDD) and favorable clinical outcomes. In this retrospective multicenter study, we included 782 patients (males, 56 %; median age 46) with confirmed COVID-19 from 54 hospitals in nine provinces of China, who were divided into four groups according to the treatment initiation time from the first date of onset of symptoms to the date of starting treatment with QFPDD. The primary outcome was time to recovery; days of viral shedding, duration of hospital stay, and course of the disease were also analyzed. Compared with treatment initiated after 3 weeks, early treatment with QFPDD after less than 1 week, 1-2 weeks, or 2-3 weeks had a higher likelihood of recovery, with adjusted hazard ratio (HR) (95 % confidence interval [CI]) of 3.81 (2.65–5.48), 2.63 (1.86-3.73), and 1.92 (1.34-2.75), respectively. The median course of the disease decreased from 34 days to 24 days, 21 days, and 18 days when treatment was administered early by a week (P < 0.0001). Treatment within a week was related to a decrease by 1-4 days in the median duration of hospital stay compared with late treatment (P

Open education is a new type of education, which is produced along with the development of modern information technology. It is a teaching model based on modern information technology. With the continuous reform of China’s education system, the autonomy of students in major colleges and universities is increasing. However, because students do not understand the course, it is very difficult to select courses. Therefore, it is especially important to excavate the university teaching platform database. This paper briefly introduces the concept of association rules mining algorithm, mainly studies the application of association rules mining algorithm in the open education learning system, in order to provide meaningful guidance for students’ elective courses, thus improving students’ academic performance.