Since early December 2019, the 2019 novel coronavirus disease (COVID-19) has caused pneumonia epidemic in Wuhan, Hubei province of China. This study aimed to investigate the factors affecting the ...progression of pneumonia in COVID-19 patients. Associated results will be used to evaluate the prognosis and to find the optimal treatment regimens for COVID-19 pneumonia.
Patients tested positive for the COVID-19 based on nucleic acid detection were included in this study. Patients were admitted to 3 tertiary hospitals in Wuhan between December 30, 2019, and January 15, 2020. Individual data, laboratory indices, imaging characteristics, and clinical data were collected, and statistical analysis was performed. Based on clinical typing results, the patients were divided into a progression group or an improvement/stabilization group. Continuous variables were analyzed using independent samples t-test or Mann-Whitney U test. Categorical variables were analyzed using Chi-squared test or Fisher's exact test. Logistic regression analysis was performed to explore the risk factors for disease progression.
Seventy-eight patients with COVID-19-induced pneumonia met the inclusion criteria and were included in this study. Efficacy evaluation at 2 weeks after hospitalization indicated that 11 patients (14.1%) had deteriorated, and 67 patients (85.9%) had improved/stabilized. The patients in the progression group were significantly older than those in the disease improvement/stabilization group (66 51, 70 vs. 37 32, 41 years, U = 4.932, P = 0.001). The progression group had a significantly higher proportion of patients with a history of smoking than the improvement/stabilization group (27.3% vs. 3.0%, χ = 9.291, P = 0.018). For all the 78 patients, fever was the most common initial symptom, and the maximum body temperature at admission was significantly higher in the progression group than in the improvement/stabilization group (38.2 37.8, 38.6 vs. 37.5 37.0, 38.4°C, U = 2.057, P = 0.027). Moreover, the proportion of patients with respiratory failure (54.5% vs. 20.9%, χ = 5.611, P = 0.028) and respiratory rate (34 18, 48 vs. 24 16, 60 breaths/min, U = 4.030, P = 0.004) were significantly higher in the progression group than in the improvement/stabilization group. C-reactive protein was significantly elevated in the progression group compared to the improvement/stabilization group (38.9 14.3, 64.8 vs. 10.6 1.9, 33.1 mg/L, U = 1.315, P = 0.024). Albumin was significantly lower in the progression group than in the improvement/stabilization group (36.62 ± 6.60 vs. 41.27 ± 4.55 g/L, U = 2.843, P = 0.006). Patients in the progression group were more likely to receive high-level respiratory support than in the improvement/stabilization group (χ = 16.01, P = 0.001). Multivariate logistic analysis indicated that age (odds ratio OR, 8.546; 95% confidence interval CI: 1.628-44.864; P = 0.011), history of smoking (OR, 14.285; 95% CI: 1.577-25.000; P = 0.018), maximum body temperature at admission (OR, 8.999; 95% CI: 1.036-78.147, P = 0.046), respiratory failure (OR, 8.772, 95% CI: 1.942-40.000; P = 0.016), albumin (OR, 7.353, 95% CI: 1.098-50.000; P = 0.003), and C-reactive protein (OR, 10.530; 95% CI: 1.224-34.701, P = 0.028) were risk factors for disease progression.
Several factors that led to the progression of COVID-19 pneumonia were identified, including age, history of smoking, maximum body temperature at admission, respiratory failure, albumin, and C-reactive protein. These results can be used to further enhance the ability of management of COVID-19 pneumonia.
The 2019 novel coronavirus has caused the outbreak of the acute respiratory disease in Wuhan, Hubei Province of China since December 2019. This study was performed to analyze the clinical ...characteristics of patients who succumbed to and who recovered from 2019 novel coronavirus disease (COVID-19).
Clinical data were collected from two tertiary hospitals in Wuhan. A retrospective investigation was conducted to analyze the clinical characteristics of fatal cases of COVID-19 (death group) and we compare them with recovered patients (recovered group). Continuous variables were analyzed using the Mann-Whitney U test. Categorical variables were analyzed by χ test or Fisher exact test as appropriate.
Our study enrolled 109 COVID-19 patients who died during hospitalization and 116 recovered patients. The median age of the death group was older than the recovered group (69 62, 74 vs. 40 33, 57 years, Z = 9.738, P < 0.001). More patients in the death group had underlying diseases (72.5% vs. 41.4%, χ = 22.105, P < 0.001). Patients in the death group had a significantly longer time of illness onset to hospitalization (10.0 6.5, 12.0 vs. 7.0 5.0, 10.0 days, Z = 3.216, P = 0.001). On admission, the proportions of patients with symptoms of dyspnea (70.6% vs. 19.0%, χ = 60.905, P < 0.001) and expectoration (32.1% vs. 12.1%, χ = 13.250, P < 0.001) were significantly higher in the death group. The blood oxygen saturation was significantly lower in the death group (85 77, 91% vs. 97 95, 98%, Z = 10.625, P < 0.001). The white blood cell (WBC) in death group was significantly higher on admission (7.23 4.87, 11.17 vs. 4.52 3.62, 5.88 ×10/L, Z = 7.618, P < 0.001). Patients in the death group exhibited significantly lower lymphocyte count (0.63 0.40, 0.79 vs. 1.00 0.72, 1.27 ×10/L, Z = 8.037, P < 0.001) and lymphocyte percentage (7.10 4.45, 12.73% vs. 23.50 15.27, 31.25%, Z = 10.315, P < 0.001) on admission, and the lymphocyte percentage continued to decrease during hospitalization (7.10 4.45, 12.73% vs. 2.91 1.79, 6.13%, Z = 5.242, P < 0.001). Alanine transaminase (22.00 15.00, 34.00 vs. 18.70 13.00, 30.38 U/L, Z = 2.592, P = 0.010), aspartate transaminase (34.00 27.00, 47.00 vs. 22.00 17.65, 31.75 U/L, Z = 7.308, P < 0.001), and creatinine levels (89.00 72.00, 133.50 vs. 65.00 54.60, 78.75 μmol/L, Z = 6.478, P < 0.001) were significantly higher in the death group than those in the recovered group. C-reactive protein (CRP) levels were also significantly higher in the death group on admission (109.25 35.00, 170.28 vs. 3.22 1.04, 21.80 mg/L, Z = 10.206, P < 0.001) and showed no significant improvement after treatment (109.25 35.00, 170.28 vs. 81.60 27.23, 179.08 mg/L, Z = 1.219, P = 0.233). The patients in the death group had more complications such as acute respiratory distress syndrome (ARDS) (89.9% vs. 8.6%, χ = 148.105, P < 0.001), acute cardiac injury (59.6% vs. 0.9%, χ = 93.222, P < 0.001), acute kidney injury (18.3% vs. 0%, χ = 23.257, P < 0.001), shock (11.9% vs. 0%, χ = 14.618, P < 0.001), and disseminated intravascular coagulation (DIC) (6.4% vs. 0%, χ = 7.655, P = 0.006).
Compared to the recovered group, more patients in the death group exhibited characteristics of advanced age, pre-existing comorbidities, dyspnea, oxygen saturation decrease, increased WBC count, decreased lymphocytes, and elevated CRP levels. More patients in the death group had complications such as ARDS, acute cardiac injury, acute kidney injury, shock, and DIC.
Noble metal nanocrystals have been extensively utilized as promising catalysts for chemical transformations and energy conversion. One of their significant applications lies in electrode materials in ...fuel cells (FCs) due to their superior electrocatalytic performance towards the reactions both on anode and cathode. Nowadays, tremendous efforts have been devoted to improve the catalytic performance and minimize the usage of precious metals. Constructing multicomponent noble metal nanocrystals with complex structures provides the opportunity to reach this goal due to their highly tunable compositions and morphologies, leading to the modification of the related electrochemical properties. In this review, we first highlight the recent advances in the controllable synthesis of noble metal alloy complex nanostructures including nanoframes/nanocages, branched structures, concave/convex structures, core-shell structures and ultrathin structures. Then the effects of the well-defined nanocrystals on the modified and improved electrochemical properties are outlined. Finally, we make a conclusion with the points on the challenges and perspectives of the controllable synthesis of noble metal alloy complex nanostructures and their electrocatalytic performance.
From the perspective of noble metal alloy nanocrystals with complex structures, we highlight their controllable synthesis and improved electrochemical property.
SET domain containing protein 2 (SETD2) involves in the progression and development of chemotherapy resistance in acute myeloid leukemia (AML). Hence, this study aimed to investigate the relationship ...of SETD2 expression with disease risk, features, treatment response, and survival profile in AML.
One-hundred and sixty primary AML patients were retrospectively analyzed. Their bone marrow (BM) samples before and after induction therapy were retrieved for SETD2 detection by RT-qPCR. Moreover, SETD2 expression in BM samples of 20 disease controls (DCs) were also determined.
SETD2 expression was downregulated in AML patients compared to DCs (P < 0.001). Higher SETD2 expression related to white blood cells ≤10 × 10
9
/L despite not reaching statistical significance (P = 0.062). One-hundred and nineteen (74.4%) AML patients achieved complete response (CR), while the remaining 41 (25.6%) did not achieve that. Furthermore, increased SETD2 expression was associated with CR achievement (P = 0.015). Survival analyses displayed that SETD2 high (vs. low) was related to prolonged event-free survival (EFS) (P = 0.001) and overall survival (OS) (P = 0.021). Moreover, increased SETD2 quartile was correlated with favorable EFS (P = 0.004) and OS (P = 0.042). After adjustment using multivariate Cox's regression analysis, higher SETD2 quartile was independently related to prolonged EFS hazard ratio (HR): 0.766, P = 0.013 and OS (HR: 0.669, P = 0.013). It was also noticed that SETD2 expression was elevated during the induction therapy (P < 0.001).
Detection of SETD2 may assist in estimating treatment response and survival profile in AML patients.
The 2019 novel coronavirus (2019-nCoV) causing an outbreak of pneumonia in Wuhan, Hubei province of China was isolated in January 2020. This study aims to investigate its epidemiologic history, and ...analyze the clinical characteristics, treatment regimens, and prognosis of patients infected with 2019-nCoV during this outbreak.
Clinical data from 137 2019-nCoV-infected patients admitted to the respiratory departments of nine tertiary hospitals in Hubei province from December 30, 2019 to January 24, 2020 were retrospectively collected, including general status, clinical manifestations, laboratory test results, imaging characteristics, and treatment regimens.
None of the 137 patients (61 males, 76 females, aged 20-83 years, median age 57 years) had a definite history of exposure to Huanan Seafood Wholesale Market. Major initial symptoms included fever (112/137, 81.8%), coughing (66/137, 48.2%), and muscle pain or fatigue (44/137, 32.1%), with other, less typical initial symptoms observed at low frequency, including heart palpitations, diarrhea, and headache. Nearly 80% of the patients had normal or decreased white blood cell counts, and 72.3% (99/137) had lymphocytopenia. Lung involvement was present in all cases, with most chest computed tomography scans showing lesions in multiple lung lobes, some of which were dense; ground-glass opacity co-existed with consolidation shadows or cord-like shadows. Given the lack of effective drugs, treatment focused on symptomatic and respiratory support. Immunoglobulin G was delivered to some critically ill patients according to their conditions. Systemic corticosteroid treatment did not show significant benefits. Notably, early respiratory support facilitated disease recovery and improved prognosis. The risk of death was primarily associated with age, underlying chronic diseases, and median interval from the appearance of initial symptoms to dyspnea.
The majority of patients with 2019-nCoV pneumonia present with fever as the first symptom, and most of them still showed typical manifestations of viral pneumonia on chest imaging. Middle-aged and elderly patients with underlying comorbidities are susceptible to respiratory failure and may have a poorer prognosis.
To determine the effect size of observed factors considering trigger factors based on parallel-serial models and to explore how multiple factors can be related to the result of complex events for ...low-probability events with binary outcomes.
A low-probability event with a true binary outcome can be explained by a trigger factor. The models were based on the parallel-serial connection of switches; causal factors, including trigger factors, were simplified as switches. Effect size values of an observed factor for an outcome were calculated as SAR = (Pe-Pn)/(Pe + Pn), where Pe and Pn represent percentages in the exposed and nonexposed groups, respectively, and SAR represents standardized absolute risk. The influence of trigger factors is eliminated by SAR. Actual data were collected to obtain a deeper understanding of the system.
SAR values of < 0.25, 0.25-0.50, and > 0.50 indicate low, medium, and high effect sizes, respectively. The system of data visualization based on the parallel-serial connection model revealed that at least 7 predictors with SAR > 0.50, including a trigger factor, were needed to predict schizophrenia. The SAR of the HLADQB1*03 gene was 0.22 for schizophrenia.
It is likely that the trigger factors and observed factors had a cumulative effect, as indicated by the parallel-serial connection model for binary outcomes. SAR may allow better evaluation of the effect size of a factor in complex events by eliminating the influence of trigger factors. The efficiency and efficacy of observational research could be increased if we are able to clarify how multiple factors can be related to a result in a pragmatic manner.
The introduction of sulfur atoms onto target molecules is an important area in organic synthesis, in particular in the synthesis of pharmaceutical compounds, and a wide variety of sulfuration agents ...have been developed for thionation reactions over the past few decades. In this Focus Review, we collect and summarize the C-S bond-formation reactions that have been used to construct C-S bonds in natural products and pharmaceutical compounds.
Age‐associated obesity and muscle atrophy (sarcopenia) are intimately connected and are reciprocally regulated by adipose tissue and skeletal muscle dysfunction. During ageing, adipose inflammation ...leads to the redistribution of fat to the intra‐abdominal area (visceral fat) and fatty infiltrations in skeletal muscles, resulting in decreased overall strength and functionality. Lipids and their derivatives accumulate both within and between muscle cells, inducing mitochondrial dysfunction, disturbing β‐oxidation of fatty acids, and enhancing reactive oxygen species (ROS) production, leading to lipotoxicity and insulin resistance, as well as enhanced secretion of some pro‐inflammatory cytokines. In turn, these muscle‐secreted cytokines may exacerbate adipose tissue atrophy, support chronic low‐grade inflammation, and establish a vicious cycle of local hyperlipidaemia, insulin resistance, and inflammation that spreads systemically, thus promoting the development of sarcopenic obesity (SO). We call this the metabaging cycle. Patients with SO show an increased risk of systemic insulin resistance, systemic inflammation, associated chronic diseases, and the subsequent progression to full‐blown sarcopenia and even cachexia. Meanwhile in many cardiometabolic diseases, the ostensibly protective effect of obesity in extremely elderly subjects, also known as the ‘obesity paradox’, could possibly be explained by our theory that many elderly subjects with normal body mass index might actually harbour SO to various degrees, before it progresses to full‐blown severe sarcopenia. Our review outlines current knowledge concerning the possible chain of causation between sarcopenia and obesity, proposes a solution to the obesity paradox, and the role of fat mass in ageing.
Working from a life course perspective, we develop hypotheses about age and gender differences in the link between marital quality and cardiovascular risk and test them using data from the first two ...waves of the National Social Life, Health, and Aging Project. The analytic sample includes 459 married women and 739 married men (aged 57-85 in the first wave) who were interviewed in both waves. We apply Heckmantype corrections for selection bias due to mortality and marriage. Cardiovascular risk is measured as hypertension, rapid heart rate, C-reactive protein, and general cardiovascular events. Results suggest that changes in marital quality and cardiovascular risk are more closely related for older married people than for their younger counterparts and that the link between marital quality and cardiovascular risk is more pronounced among women than among men at older ages. These findings fit with the gendered life course perspective and cumulative disadvantage framework.
This study proposes the comprehensive index of biomarker (CIB), based on the consistency of a biomarker in case control (Youden index, J) and cohort studies (Crc), to evaluate biomarker efficacy. CIB ...was calculated as the mean of J and Crc. Analysis of the effect of sensitivity and specificity on CIB and ROC analysis of CIB were performed in simulated and actual datasets. J and CIB had similar values for high-probability events (say probability was 0.50), but there was a significant difference between J and CIB for low-probability events (say probability was 0.05). Therefore, as the subjects considered for diagnosis are usually symptomatic, the occurrence of a disease can be assumed to be a high-probability event. In contrast, as the subjects considered in screening for a disease are usually healthy and asymptomatic, the occurrence of a disease is assumed to be a low-probability event. Although J is the common index used to evaluate the diagnostic effectiveness, unfortunately, the J value is significantly larger than CIB value in a low-probability event, showing overestimation for screening purpose. CIB could have more potential than J for determining the screening efficacy of a biomarker. The efficacy of a biomarker could differ for diagnostic, screening, predictive, and prognostic purposes, and it would be better to evaluate the efficacy of biomarkers for specific systems or contexts.
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