Predictive Model and Risk Factors for Case Fatality of COVID-19: A Cohort of 21,392 Cases in Hubei, China

Patients' and Clinicians' Perceptions of the Clinical Utility of Predictive Risk Models for Chemotherapy-Related Symptom Management: Qualitative Exploration Using Focus Groups and Interviews

BACKGROUND

Interest in the application of predictive risk models (PRMs) in health care to identify people most likely to experience disease and treatment-related complications is increasing. In cancer care, these techniques are focused primarily on the prediction of survival or life-threatening toxicities (eg, febrile neutropenia). Fewer studies focus on the use of PRMs for symptoms or supportive care needs. The application of PRMs to chemotherapy-related symptoms (CRS) would enable earlier identification and initiation of prompt, personalized, and tailored interventions. While some PRMs exist for CRS, few were translated into clinical practice, and human factors associated with their use were not reported.

OBJECTIVE

We aim to explore patients' and clinicians' perspectives of the utility and real-world application of PRMs to improve the management of CRS.

METHODS

Focus groups (N=10) and interviews (N=5) were conducted with patients (N=28) and clinicians (N=26) across 5 European countries. Interactions were audio-recorded, transcribed verbatim, and analyzed thematically.

RESULTS

Both clinicians and patients recognized the value of having individualized risk predictions for CRS and appreciated how this type of information would facilitate the provision of tailored preventative treatments or supportive care interactions. However, cautious and skeptical attitudes toward the use of PRMs in clinical care were noted by both groups, particularly in relationship to the uncertainty regarding how the information would be generated. Visualization and presentation of PRM information in a usable and useful format for both patients and clinicians was identified as a challenge to their successful implementation in clinical care.

CONCLUSIONS

Findings from this study provide information on clinicians' and patients' perspectives on the clinical use of PRMs for the management of CRS. These international perspectives are important because they provide insight into the risks and benefits of using PRMs to evaluate CRS. In addition, they highlight the need to find ways to more effectively present and use this information in clinical practice. Further research that explores the best ways to incorporate this type of information while maintaining the human side of care is warranted.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02356081; https://clinicaltrials.gov/study/NCT02356081.

Improvements throughout the Three Waves of COVID-19 Pandemic: Results from 4 Million Inhabitants of North-West Italy

At the very beginning of the European spread of SARS-CoV-2, Piedmont was one of the most affected regions in Italy, with a strong impact on healthcare organizations. In this study, we evaluated the characteristics and outcomes of the COVID-19 patients in an entire region during the first three pandemic waves, identifying similarities and differences in the SARS-CoV-2 epidemic’s timeline. We collected the health-administrative data of all the Piedmont COVID-19 patients infected during the first three pandemic waves (1 March 2020–15 April 2020; 15 October 2020–15 December 2020; 1 March 2021–15 April 2021, respectively). We compared differences among the waves in subjects positive for SARS-CoV-2 and in patients admitted to ICU. Overall, 18.621 subjects tested positive during the first wave (405 patients/day), 144.350 (2366.4 patients/day) in the second, and 81.823 (1778.8 patients/day) in the third. In the second and third waves, we observed a reduction in median age, comorbidity burden, mortality in outpatients, inpatients, and patients admitted to ICU, in intubation, invasive ventilation and tracheostomy, and a parallel increase in the use of CPAP. Our study confirmed a trend towards younger and healthier patients over time but also showed an independent effect of the period on mortality and ICU admission. The appearance of new viral variants, the starting of vaccination, and organizational improvements in tracking, outpatients and inpatients management could have influenced these trends.

Implementing Silica Nanoparticles in the Study of the Airborne Transmission of SARS-CoV-2

Aerosol transmission constitutes one of the major transmission routes of the SARS-CoV-2 pathogen. Due to the pathogen's properties, research on its airborne transmission has some limitations. This paper focuses on silica nanoparticles (SiO2) of 40 and 200 nm sizes as the physicochemical markers of a single SARS-CoV-2 particle enabling experiments on the transmission of bioaerosols in public spaces. Mixtures of a determined silica concentration were sprayed on as an aerosol, whose particles, sedimented on dedicated matrices, were examined by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Since it was not possible to quantitatively identify the markers based on the obtained images, the filters exposed with the AirSampler aspirator were analyzed based on inductively coupled plasma optical emission spectroscopy (ICP-OES). The ICP-OES method enabled us to determine the concentration of silica after extracting the marker from the filter, and consequently to estimate the number of markers. The developed procedure opens up the possibility of the quantitative estimation of the spread of the coronavirus, for example in studies on the aerosol transmission of the pathogen in an open environment where biological markers-surrogates included-cannot be used.

Novel biomarker-based score (SAD-60) for predicting mortality in patients with COVID-19 pneumonia: a multicenter retrospective cohort of 1013 patients

Background: The aim was to explore a novel risk score to predict mortality in hospitalized patients with COVID-19 pneumonia. Methods: This was a retrospective, multicenter study. Results: A total of 1013 patients with COVID-19 were included. The mean age was 60.5 ± 14.4 years, and 581 (57.4%) patients were male. In-hospital death occurred in 124 (12.2%) patients. Multivariate analysis revealed peripheral capillary oxygen saturation (SpO2), albumin, D-dimer and age as independent predictors. The mortality score model was given the acronym SAD-60, representing SpO2, Albumin, D-dimer, age ≥60 years. The SAD-60 score (0.776) had the highest area under the curve compared with CURB-65 (0.753), NEWS2 (0.686) and qSOFA (0.628) scores. Conclusion: The SAD-60 score has a promising predictive capacity for mortality in hospitalized patients with COVID-19.

Topic Evolution of Chinese COVID-19 Policies Based on Co-Occurrence Clustering Network Analysis

This study aims to explore the changes of Chinese coronavirus disease-2019 (COVID-19) policy topics in the eclipse, outbreak, and convalescent stage of COVID-19 based on 4982 textual policies. By using the co-occurrence clustering network method, we find that the strict prevention and control of the epidemic is the only topic of policies in the eclipse stage. In the outbreak stage, strict epidemic prevention and control is still the most important policy topic. The policies of resuming work of “essential” enterprises and stabilizing market prices are important support and guarantee for fighting against COVID-19. In the convalescent stage, as the prevention and control of COVID-19 has become regular, promoting and ensuring the resumption of work in all sectors of society is the most important topic of the policies. Moreover, the success of Wuhan City’s fight against COVID-19 reflects China’s governance characteristics of “concentrating power to do a major event”. Finally, the possible improvements for Chinese COVID-19 policies are discussed, which can provide practical suggestions for government departments on how to effectively respond to public health emergencies.

Risk Factors of Hipertension and Diabetes Mellitus on COVID-19 Mortality

BACKGROUND: Case fatality rate (CFR) for global COVID-19 infections since June 14, 2021 was 2.17%, while CFR for Southest Asia were 1.39%. CFR in Indonesia so far were 3.05%. This missed from the target of the 2005-2025 RPJMK (Middle long run national health planning) in achieving healthy Indonesia; handling epidemic diseases must be able to reduce the mortality rate below 1%. The government issued the Decree of the Minister of Health Republic of Indonesia No. HK.01.07/Menkes/2020 concerning the Determination of Vaccine Types for the Management of COVID-19. However, the existence of this policy did not reduce the mortality rate trend of COVID-19 in Indonesia. Hypertension and diabetes mellitus were the larger risk factors for COVID-19 mortality. Guo et al. 2020 found comorbid COVID-19 sufferers were hypertension 24.7% and diabetes mellitus 21.2%. However, Mikami et al., 2020 stated differently that hypertension and diabetes mellitus were not at risk of COVID-19 mortality. AIM: Objective of this study was to estimate the average tendency of hypertension and diabetes mellitus as risk factor for COVID-19 mortality. METHODS: Meta-analysis with 16 articles analyzed by RevMan 5.4. RESULTS: pHR for hypertension was 1.15 (95% CI 1.00 - 1.32) and diabetes mellitus was 1.21 (95% CI 1.13 - 1.29). CONCLUSION: Hypertension had risk 1.15 times and diabetes mellitus had risk 1.21 times for COVID-19 mortality.

Reliable and Interpretable Mortality Prediction With Strong Foresight in COVID-19 Patients: An International Study From China and Germany

Cohort-independent robust mortality prediction model in patients with COVID-19 infection is not yet established. To build up a reliable, interpretable mortality prediction model with strong foresight, we have performed an international, bi-institutional study from China (Wuhan cohort, collected from January to March) and Germany (Würzburg cohort, collected from March to September). A Random Forest-based machine learning approach was applied to 1,352 patients from the Wuhan cohort, generating a mortality prediction model based on their clinical features. The results showed that five clinical features at admission, including lymphocyte (%), neutrophil count, C-reactive protein, lactate dehydrogenase, and α-hydroxybutyrate dehydrogenase, could be used for mortality prediction of COVID-19 patients with more than 91% accuracy and 99% AUC. Additionally, the time-series analysis revealed that the predictive model based on these clinical features is very robust over time when patients are in the hospital, indicating the strong association of these five clinical features with the progression of treatment as well. Moreover, for different preexisting diseases, this model also demonstrated high predictive power. Finally, the mortality prediction model has been applied to the independent Würzburg cohort, resulting in high prediction accuracy (with above 90% accuracy and 85% AUC) as well, indicating the robustness of the model in different cohorts. In summary, this study has established the mortality prediction model that allowed early classification of COVID-19 patients, not only at admission but also along the treatment timeline, not only cohort-independent but also highly interpretable. This model represents a valuable tool for triaging and optimizing the resources in COVID-19 patients.

Risk Factors for SARS-CoV-2 Infection, Pneumonia, Intubation, and Death in Northeast Mexico

Despite the social distancing and mobility restriction measures implemented for susceptible people around the world, infections and deaths due to COVID-19 continued to increase, even more so in the first months of 2021 in Mexico. Thus, it is necessary to find risk groups that can benefit from more aggressive preventive measures in a high-density population. This is a case-control study of suspected COVID-19 patients from Nuevo León, Mexico. Cases were: (1) COVID-19-positive patients and COVID-19-positive patients who (2) developed pneumonia, (3) were intubated and (4) died. Controls were: (1) COVID-19-negative patients, (2) COVID-19-positive patients without pneumonia, (3) non-intubated COVID-19-positive patients and (4) surviving COVID-19-positive patients. ≥ 18 years of age, not pregnant, were included. The pre-existing conditions analysed as risk factors were age (years), sex (male), diabetes mellitus, hypertension, chronic obstructive pulmonary disease, asthma, immunosuppression, obesity, cardiovascular disease, chronic kidney disease and smoking. The Mann-Whitney U tests, Chi square and binary logistic regression were used. A total of 56,715 suspected patients were analysed in Nuevo León, México, with 62.6% being positive for COVID-19 and, of those infected, 14% developed pneumonia, 2.9% were intubated and 8.1% died. The mean age of those infected was 44.7 years, while of those complicated it was around 60 years. Older age, male sex, diabetes, hypertension, and obesity were risk factors for infection, complications, and death from COVID-19. This study highlights the importance of timely recognition of the population exposed to pre-existing conditions to prioritise preventive measures against the virus.

A recombinant receptor-binding domain in trimeric form generates protective immunity against SARS-CoV-2 infection in nonhuman primates

A safe and effective vaccine is critical to combat the COVID-19 pandemic. Here, we developed a trimeric SARS-CoV-2 receptor-binding domain (RBD) subunit vaccine candidate that simulates the natural structure of the spike (S) trimer glycoprotein. Immunization with the RBD trimer-induced robust humoral and cellular immune responses, and a high level of neutralizing antibodies was maintained for at least 4.5 months. Moreover, the antibodies that were produced in response to the vaccine effectively cross-neutralized the SARS-CoV-2 501Y.V2 variant (B.1.351). Of note, when the vaccine-induced antibodies dropped to a sufficiently low level, only one boost quickly activated the anamnestic immune response, conferring full protection against a SARS-CoV-2 challenge in rhesus macaques without typical histopathological changes in the lung tissues. These results demonstrated that the SARS-CoV-2 RBD trimer vaccine candidate is highly immunogenic and safe, providing long-lasting, broad, and significant immunity protection in nonhuman primates, thereby offering an optimal vaccination strategy against COVID-19.

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A SARS-CoV-2 trimeric vaccine candidate demonstrates safe, long-lasting, broad, and significant immunity protection in nonhuman primates

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The vaccine-induced antibodies can effectively neutralize the SARS-CoV-2 501Y.V2 variant

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A booster vaccination can quickly activate the memory immune response to avoid re-infection

Hospitalization Costs of COVID-19 Cases and Their Associated Factors in Guangdong, China: A Cross-Sectional Study

Background: The ongoing COVID-19 pandemic has brought significant challenges to health system and consumed a lot of health resources. However, evidence on the hospitalization costs and their associated factors in COVID-19 cases is scarce. Objectives: To describe the total and components of hospitalization costs of COVID-19 cases, and investigate the associated factors of costs. Methods: We included 876 confirmed COVID-19 cases admitted to 33 designated hospitals from January 15th to April 27th, 2020 in Guangdong, China, and collected their demographic and clinical information. A multiple linear regression model was performed to estimate the associations of hospitalization costs with potential associated factors. Results: The median of total hospitalization costs of COVID-19 cases was $2,869.4 (IQR: $3,916.8). We found higher total costs in male (% difference: 29.7, 95% CI: 15.5, 45.6) than in female cases, in older cases than in younger ones, in severe cases (% difference: 344.8, 95% CI: 222.5, 513.6) than in mild ones, in cases with clinical aggravation than those without, in cases with clinical symptoms (% difference: 47.7, 95% CI: 26.2, 72.9) than those without, and in cases with comorbidities (% difference: 21.1%, 21.1, 95% CI: 4.4, 40.6) than those without. We also found lower non-pharmacologic therapy costs in cases treated with traditional Chinese medicine (TCM) therapy (% difference: -47.4, 95% CI: -64.5 to -22.0) than cases without. Conclusion: The hospitalization costs of COVID-19 cases in Guangdong were comparable to the national level. Factors associated with higher hospitalization costs included sex, older age, clinical severity and aggravation, clinical symptoms and comorbidities at admission. TCM therapy was found to be associated with lower costs for some non-pharmacologic therapies.

Association between exposure of light rare earth elements and outcomes of in vitro fertilization-embryo transfer in North China

The adverse health effects of rare earth elements (REEs) on reproductive health remain a subject of debate, and few clinical observations are available. This study investigated the association between light REEs (LREEs) exposure and the outcome of in vitro fertilization-embryo transfer (IVF-ET). We recruited a total of 305 women undergoing IVF-ET in Beijing City and Shandong Province of northern China. Their demographic information and lifestyle characteristics were collected using questionnaires at enrollment. Fasting blood samples were collected on the day before the IVF-ET treatment cycle began. Serum concentrations of the LREEs of concern were analyzed using inductively coupled plasma-mass spectrometry, and four LREEs were measured with a high detection rate, including lanthanum (La), cerium (Ce), praseodymium (Pr), and neodymium (Nd). We found that a higher serum La concentration was associated with a 30% increased likelihood of clinical pregnancy failure [relative risk (RR) = 1.30, 95% confidence interval (CI): 1.00-1.67] and a 230% increased likelihood of preclinical spontaneous abortion (RR = 3.30, 95% CI: 1.57-6.94). There was a negative correlation between serum La concentration and the number of good-quality oocytes. For the other LREEs, no statistically significant associations were observed. We concluded that a high serum La concentration may have an adverse effect on IVF-ET outcomes.

Geographical Pattern of COVID-19-Related Outcomes over the Pandemic Period in France: A Nationwide Socio-Environmental Study

BACKGROUND

Several studies have investigated the implication of air pollution and some social determinants on COVID-19-related outcomes, but none of them assessed the implication of spatial repartition of the socio-environmental determinants on geographic variations of COVID-19 related outcomes. Understanding spatial heterogeneity in relation to the socio-environmental determinant and COVID-19-related outcomes is central to target interventions toward a vulnerable population.

OBJECTIVES

To determine the spatial variability of COVID-19 related outcomes among the elderly in France at the department level. We also aimed to assess whether a geographic pattern of Covid-19 may be partially explained by spatial distribution of both long-term exposure to air pollution and deprived living conditions.

METHODS

This study considered four health events related to COVID-19 infection over the period of 18 March and 02 December 2020: (i) hospitalization, (ii) cases in intensive health care in the hospital, (iii) death in the hospital, and (iv) hospitalized patients recovered and returned back home. We used the percentage of household living in an overcrowding housing to characterize the living conditions and long-term exposure to NO2 to analyse the implication of air pollution. Using a spatial scan statistic approach, a Poisson cluster analysis method based on a likelihood ratio test and Monte Carlo replications was applied to identify high-risk clusters of a COVID-19-related outcome.

RESULT

our results revealed that all the outcomes related to COVID-19 infection investigated were not randomly distributed in France with a statistically significant cluster of high risk located in Eastern France of the hospitalization, cases in the intensive health care at the hospital, death in the hospital, and recovered and returned back home compared to the rest of France (relative risk, RR = 1.28, p-value = 0.001, RR = 3.05, p = 0.001, RR = 2.94, p = 0.001, RR = 2.51, p = 0.001, respectively). After adjustments for socio-environmental determinants, the crude cluster shifts according to different scenarios suggested that both the overcrowding housing level and long-term exposure to largely NO2 explain the spatial distribution of COVID-19-related outcomes.

CONCLUSIONS

Our findings suggest that the geographic pattern of COVID-19-related outcomes is largely explained by socio-spatial distribution of long-term exposure to NO2. However, to better understand spatial variations of COVID-19-related outcomes, it would be necessary to investigate and adjust it for other determinants. Thus, the current sanitary crisis reminds us of how unequal we all are in facing this disease.

An easy-to-use nomogram for predicting in-hospital mortality risk in COVID-19: a retrospective cohort study in a university hospital

BACKGROUND

One-fifth of COVID-19 patients are seriously and critically ill cases and have a worse prognosis than non-severe cases. Although there is no specific treatment available for COVID-19, early recognition and supportive treatment may reduce the mortality. The aim of this study is to develop a functional nomogram that can be used by clinicians to estimate the risk of in-hospital mortality in patients hospitalized and treated for COVID-19 disease, and to compare the accuracy of model predictions with previous nomograms.

METHODS

This retrospective study enrolled 709 patients who were over 18 years old and received inpatient treatment for COVID-19 disease. Multivariable Logistic Regression analysis was performed to assess the possible predictors of a fatal outcome. A nomogram was developed with the possible predictors and total point were calculated.

RESULTS

Of the 709 patients treated for COVID-19, 75 (11%) died and 634 survived. The elder age, certain comorbidities (cancer, heart failure, chronic renal failure), dyspnea, lower levels of oxygen saturation and hematocrit, higher levels of C-reactive protein, aspartate aminotransferase and ferritin were independent risk factors for mortality. The prediction ability of total points was excellent (Area Under Curve = 0.922).

CONCLUSIONS

The nomogram developed in this study can be used by clinicians as a practical and effective tool in mortality risk estimation. So that with early diagnosis and intervention mortality in COVID-19 patients may be reduced.

Community evidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission through air

BACKGROUND

Nine COVID-19 (Corona Virus Disease, 2019) cases were observed in one community in Guangzhou. All the cases lived in three vertically aligned units of one building sharing the same piping system, which provided one unique opportunity to examine the transmission mode of SARS-CoV-2.

METHODS

We interviewed the cases on the history of travelling and close contact with the index patients. Respiratory samples from all the cases were collected for viral phylogenetic analyses. A simulation experiment in the building and a parallel control experiment in a similar building were then conducted to investigate the possibility of transmission through air.

RESULTS

Index patients living in Apartment 15-b had a travelling history in Wuhan, and four cases who lived in Apartment 25-b and 27-b were subsequently diagnosed. Phylogenetic analyses showed that virus of all the patients were from the same strain of the virus. No close contacts between the index cases and other families indicated that the transmission might not occur through droplet and close contacts. Airflow detection and simulation experiment revealed that flushing the toilets could increase the speed of airflow in the pipes and transmitted the airflow from Apartment 15-b to 25-b and 27-b. Reduced exhaust flow rates in the infected building might have contributed to the outbreak.

CONCLUSIONS

The outbreak of COVID-19 in this community could be largely explained by the transmission through air, and future efforts to prevent the infection should take the possibility of transmission through air into consideration. A disconnected drain pipe and exhaust pipe for toilet should be considered in the architectural design to help prevent possible virus spreading through the air.