Evidence indicates that glucose variation (GV) plays an important role in mortality of critically ill patients. We aimed to investigate the relationship between the coefficient of variation of 24-h venous blood glucose (24-hVBGCV) and mortality among patients with acute respiratory failure. The records of 1625 patients in the Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC II) database were extracted. The 24-hVBGCV was calculated as the ratio of the standard deviation (SD) to the mean venous blood glucose level, expressed as a percentage. The outcomes included ICU mortality and in-hospital mortality. Participants were divided into three subgroups based on tertiles of 24-hVBGCV. Multivariable logistic regression models were used to evaluate the relationship between 24-hVBGCV and mortality. Sensitivity analyses were also performed in groups of patients with and without diabetes mellitus. Taking the lowest tertile as a reference, after adjustment for all the covariates, the highest tertile was significantly associated with ICU mortality  and in-hospital mortality , especially in the population without diabetes. The 24-hVBGCV may be associated with ICU and in-hospital mortality in patients with acute respiratory failure in the ICU, especially in those without diabetes.  A previous study indicated that increased standard deviation (SD) and coefficient of variation (CV), are independently associated with longer hospital stay and higher mortality in non-critically ill patients2. Besides, in critically ill patients, the higher mean absolute glucose (MAG) change over a given period or SD also conferred a strong independent risk of mortality6. However, the relationship between coefficient of variation of 24-h venous blood glucose (24-hVBGCV), calculated as the ratio of the SD to the mean of venous blood glucose readings available during first 24-h in ICU, and mortality among patients with acute respiratory failure in intensive care unit (ICU) remains unclear. Therefore, the present study was conducted to explore this relationship using the Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II) database.Glucose variation (GV) has been identified as a risk factor for adverse outcomes in various patientsP = 0.005), SOFA score (P < 0.001), diabetes (P < 0.001), renal failure (P < 0.001), and use of insulin (P < 0.001). There was no statistical significance regarding sex, ethnicity, obesity, chronic pancreatitis, heart failure, or infection (P > 0.05). In the three groups (lowest to highest tertiles), both ICU mortality and in-hospital mortality were significantly different .The baseline characteristics of the study participants are shown in Table In univariate analysis, taking the lowest tertile as a reference, the highest tertile was associated with ICU mortality  and in-hospital mortality . After adjustment for a series of covariates, the highest tertile was also related to higher ICU mortality  and in-hospital mortality , compared with the lowest tertile of 24-hVBGCV , which indicates that whether or not patients have diabetes has no effect on the relationship between 24-hVBGCV and mortality. Considering the clinical practice, the population was also divided into two subgroups: diabetes or non-diabetes patients. Surprisingly, compared with the lowest 24-hVBGCV tertile, the highest tertile was associated with ICU mortality  and in-hospital mortality  in non-diabetes patients after adjusting for all the covariates , also confirmed that patients with lower GV had lower ICU/in-hospital mortality than those with higher GV. However, the population was limited to patients with hyperglycemia and lower SOFA scores; importantly, all blood glucose values from admission to discharge were collected and utilized, which might compromise the feasibility of possible risk stratification in the future.Previous studies have focused on the relationship between GV and mortality12, we conducted a sensitivity analysis to explore whether such a relationship exists in patients with or without diabetes. Surprisingly, compared with the lowest 24-hVBGCV tertile, the highest tertile was associated with ICU mortality and in-hospital mortality in non-diabetic patients after adjustment for all the covariates. Our results are consistent with previously published findings using mean absolute glucose change per hour or SD in critically ill patients14. Therefore, our findings showed that 24-hVBGCV might serve as an independent risk factor of mortality in patients with acute respiratory failure.In the present study, 24-hVBGCV was calculated during the first 24 h after ICU admission, it may provide an earlier prediction of mortality. In the regression model, we adjusted for a series of covariates that may influence mortality; in addition, use of insulin was adjusted into the regression model to eliminate the influence of glucose level. Furthermore, considering the relationship between hyperglycemia and mortality17. In vitro, Quagliaro et al.15found that exposure of endothelial cells to intermittent high glucose stimulated reactive oxygen species overproduction, leading to accelerated cellular apoptosis. Studies in both patients with diabetes and healthy subjects observed that oscillating glucose produced further significant increases in endothelial dysfunction and oxidative stress compared with sustained high glucose17. For non-diabetic patients, acute stress response and inflammatory response were the main causes of increased glucose14. In addition, El-Osta et al.18found that even short-term hyperglycemic spikes could have long-lasting effects on vascular cells. A meta-analysis including at least 12 independent cohorts was shown the relation of glucose variability to ICU mortality in non-diabetic patients with stress hyperglycemia19. Diabetic patients may develop a relative tolerance to the cardiovascular effects associated with moderate degrees of hyperglycemia14. Moreover, hyperglycemia itself is an independent risk factor for death; thus, death caused by diabetes and its complications might conceal the effect of blood glucose fluctuation on mortality12. Therefore, it was reasonable that we found a significant association between GV and mortality in the non-diabetic group rather than in the diabetic group.Previous studies have demonstrated that high GV leads to greater oxidative stress and endothelial dysfunction than dose sustained hyperglycemiaThis study has the following strengths. First, a large cohort of patients were enrolled from various units , reflecting a real-world situation. Second, this was a homogeneous group of critically ill patients with acute respiratory failure, excluding patients with the extra fluctuations in blood glucose caused by surgical procedures. In addition, the 24-hVBGCV was adopted to avoid the calculation error caused by the difference in blood glucose monitoring frequencies in the treatment process of patients due to diabetes. However, our study also has some limitations. Because of the retrospective design of the study, potential bias  may exist. Moreover, our study investigated the association between 24-hVBGCV and mortality in patients with acute respiratory failure, rather than causality. Therefore, well-designed prospective studies are needed for future investigation.This is a retrospective cohort study using patients’ data from the MIMIC-II database. It was approved by the Institutional Review Boards of Beth Israel Deaconess Medical Center  and the Massachusetts Institute of Technology . The patients’ consent was waived because of the retrospective design of the study.20. All data used for this study were de-identified and available upon request. All authors had completed the Collaborative Institutional Training Initiative course at the University of Miami and received permission to access the MIMIC database.More than 30,000 patients in the MIMIC-II database were enrolled from the intensive care unit (ICU) at Beth Israel Deaconess Medical Center from 2001 to 2008. The database included demographic characteristics, physiological data, treatments, laboratory and radiological data, medical history, and survival outcomesThe following measures were extracted for each patient: age at admission, sex, ethnicity, the first 24-h Sequential Organ Failure Assessment (SOFA) score after admission to the ICU, use of insulin, clinical status , survival outcome, and records of IV glucose monitoring during the first 24 h of ICU stay. The extraction of data was performed by SAS version 9.4 .All patients (≥ 15 years old) in the database diagnosed with acute respiratory failure coded with International Classification of Diseases, Ninth Revision (ICD-9) were selected for the analysis. Individuals were excluded if (1) their number of 24-h blood glucose measurements was < 2, (2) they had multiple admissions to the hospital or ICU, (3) they stayed in the ICU for less than 24 h, or (4) they had missing covariates.The data of 3512 patients with acute respiratory failure were extracted from the MIMIC-II database. The data of 547 (number of 24-h blood glucose measurements < 2), 1,308 , and 32 (missing covariates) patients were excluded. Finally, 1625 patients were included in this study . Patients were divided into three groups according to the tertiles of 24-hVBGCV.The outcomes were ICU mortality and in-hospital mortality.Continuous variables are presented as mean ± SD and compared using analysis of variance (ANOVA). Categorical variables are presented as percentages and compared using a chi-squared test. Logistic regression models were used to assess the impact of 24-hVBGCV on ICU and hospital mortality. In multivariate regression analyses, the adjusted covariates included age, sex, ethnicity, SOFA score, obesity, use of insulin, and related comorbidities that could influence mortality or glucose . Interaction analyses were performed between 24-hVBGCV and diabetes. Subgroup analyses were performed between subjects with and without diabetes. The odds ratios (OR) and their 95% confidence intervals (CI) were generated for logistic regression. All data were analyzed using SPSS version 18.0 . P values less than 0.05 indicated statistical significance.


The pathology associated with COVID-19 infection is progressively being revealed. Recent postmortem assessments have revealed acute airway inflammation as well as diffuse alveolar damage, which bears resemblance to severe acute respiratory syndromes induced by both SARS-CoV and MERS-CoV infections. Although recent papers have highlighted some neuropathologies associated with COVID-19 infection, little is known about this topic of great importance in the area of public health. Here, we discuss how neuroinflammation related to COVID-19 could be triggered by direct viral neuroinvasion and/or cytokine release over the course of the infection. COVID-19 is a disease caused by the SARS-CoV-2 virus, a beta coronavirus discovered in late 2019 in Wuhan, China. Reports from China at the onset of the outbreak and from other countries thereafter clearly demonstrated that the majority of patients 81%) have mild symptoms without pneumonia or mild pneumonia, and among patients with more significant symptoms, 14% have severe respiratory distress and 5% have respiratory failure, septic shock, and/or multiple organ failure . Recent 1% have m


Rich-club analysis was also performed to explore the rich-club organization of brain structural networks. Our results showed that the parcellation scale and imaging protocol have significant effects on the network attributes, with the parcellation scale having a substantially larger effect. Regardless of the parcellation scale, the brain structural networks exhibited a rich-club organization with similar cortical distributions across the parcellation scales involving at least 400 nodes. Compared to single b-value diffusion acquisitions, the deterministic tractography using multishell diffusion imaging data consisting of shells with b-values higher than 5000 s/mm2 resulted in significantly improved fiber-tracking results at the locations where fiber bundles cross each other. Brain structural networks constructed using the multishell acquisition scheme including high b-values also exhibited significantly shorter characteristic path lengths, higher global efficiency and lower modularity. Our results showed that both parcellation scale and sampling protocol can significantly impact the rich-club organization of brain structural networks. Therefore, caution should be taken concerning the reproducibility of connectivity results with regard to the parcellation scale and sampling scheme.The majority of network studies of human brain structural connectivity are based on single-shell diffusion-weighted imaging (DWI) data. Recent advances in imaging hardware and software capabilities have made it possible to acquire multishell  high-quality data required for better characterization of white-matter crossing-fiber microstructures. The purpose of this study was to investigate the extent to which brain structural organization and network topology are affected by the choice of diffusion magnetic resonance imaging (MRI) acquisition strategy and parcellation scale. We performed graph-theoretical network analysis using DWI data from 35 Human Connectome Project subjects. Our study compared four single-shell (b = 1000, 3000, 5000, 10,000 s/mm The human brain connectome has greatly expanded our understanding of how cognitive processes emanate from a fundamental structural substrate . In the To investigate the rich-club organization of large-scale brain structural networks, a brain graph is first constructed by gray-matter parcellation, in which parcels serve as nodes and links represent large-scale fiber tracts connecting nodes . The bra2) of the MGH–USC Adult Diffusion Dataset allows investigating patterns of structural connectivity by estimating slow water diffusion and shorter-range fibers, the main requirement to investigate the effect of diffusion parameters on brain structural networks and topology.It has been shown that spatial scale and DWI acquisition protocols can significantly affect the behavior and topological properties of brain networks constructed using single-shell DWI data . AdvanceIn this study, we performed graph-theoretical network analysis to quantify the extent to which the choice of parcellation scales and diffusion parameters  could affect the organization of brain structural networks and topology. We further investigated the rich-club organization of brain structural networks at different nodal scales and DWI schemes by exploring whether the use of higher b-values could affect the estimation of short- to long-range white-matter streamlines.The processing pipeline includes brain tissue segmentation, anatomical parcellation, single/multishell brain tractography and structural connectivity analysis . The whohttps://ida.loni.usc.edu/login.jsp, accessed on 10 January 2020). Before data collection, informed written consent was obtained from all participants, and the experiments were approved by the institutional review board of Partners Healthcare [Thirty-five healthy adult subjects  were included in this study from the publicly available database of the Human Connectome Project  was excluded due to incomplete acquisition .All MR data, including anatomical (T1w and T2w) and diffusion-weighted (DW) images, were acquired on the 3T CONNECTOM MRI scanner. The T1w images were acquired with a 3D multi-echo magnetization-prepared rapid acquisition gradient echo (ME-MPRAGE) sequence and a 1 mm isotropic-voxel resolution. The T2w images were obtained with a T2-SPACE sequence at 0.7 mm isotropic resolution. The diffusion data were collected with a SE-EPI sequence with an isotropic resolution of 1.5 mm and parallel imaging. For data acquisition, four shells were selected at b = 1000, 3000, 5000 and 10,000 s/mmA non-DW image (b = 0) was acquired at the beginning of each run, as well as every 13 image volumes, yielding 552 volumes in total, including 512 DW and 40 non-DW volumes for each subject with a phase-encoding direction from anterior to posterior. The structural scans were corrected for geometric distortions. The concatenated diffusion data of all 4 b-values (552 image volumes) were also corrected for head motions and eddy current distortion ,16,17. Ihttp://dsi-studio.labsolver.org, accessed on 30 February 2021) using the generalized q-sampling imaging (GQI) method [2) and multishell  diffusion schemes were used. The optimal value of the diffusion sampling length ratio was chosen for each scheme such that the fiber-tracking algorithm could resolve crossing fibers in crossing regions  and also correctly estimate fiber directions in noncrossing regions .Deterministic fiber tracking was performed with DSI Studio  method . To inveUsing each of the eight sampling schemes, a deterministic fiber-tracking algorithm was used to generate 1,000,000 streamlines for each subject by performing random seeding within the entire white-matter volume. Quantitative anisotropy (QA) was calculated for the orientation distribution function (ODF) peak in each voxel. QA enables direction-specific thresholding during tractography and is therefore less susceptible to partial volume effects and noise . The anghttp://surfer.nmr.mgh.harvard.edu, accessed on 24 February 2021) according to the Desikan–Kiliany atlas [For multiscale parcellation, the T1w anatomical data were first partitioned into 68 structurally defined regions using FreeSurfer . Each structural network W was represented by an N × N matrix, where N is the number of parcels (nodes), and each entry ijw represents the number of reconstructed streamlines connecting nodes i and j. For structural connectivity analysis, an adjacency (binary) matrix U was then constructed from each weighted network by a threshold defined as 0.1% (default threshold in DSI Studio) of the maximum number of track counts in the matrix. This threshold was used to discard spurious connections that were potentially influenced by noise. For the rich-club analysis, a backbone structural connectivity matrix (UB) was computed for each sampling scheme and nodal scale using the method described in [For each subject, forty-eight structural brain networks were constructed using the single- and multishell schemes at six nodal scales  using DSI Studio  model, in which both the graph and the random graph had the same average nodal degree [RC (average clustering coefficient) and RI (average path length) were estimated as follows:d denotes the average nodal degree, and N is the number of nodes. Based on the σ-ratio, G has the small-world property of γ > 1 and λ ≈ 1. These two conditions were reduced to a single test σ > 1. We also used Newman’s method to estimate the modularity for each connectivity matrix by maximizing the number of within-group edges and minimizing the number of between-group edges in order to subdivide each network into nonoverlapping delineated groups of nodes [To quantify the effect of the parcellation scale and DWI scheme on the topological properties of the unweighted structural networks, five graph metrics, including small-worldness, clustering coefficient, characteristic path length, modularity and global efficiency  constructed for each sampling scheme and nodal scale, for each degree k varying from 1 to the maximum degree in the network, a rich-club coefficient Φ(k) was computed as follows [> k and N ≥ k represent the number of connections between the remaining nodes in BU and the total number of possible connections between the remaining nodes if they were fully connected, respectively. For each backbone network, a normalized rich-club coefficient Φnorm(k) was then computed with respect to Φrandom(k), computed as the average rich-club coefficient over m (herein 1000) random networks of equal size with similar connectivity distribution, generated by randomizing the connections of the network while keeping the degree distribution of the matrix intact [norm greater than 1 over a range of k reflects the existence of a rich-club organization for the network. A high rich-club coefficient indicates that the hubs are well connected. In general, the choice of the k level is arbitrary and study dependent [k level in a way to have 20% of each network’s nodes ranked as rich club to identify the rich-club spatial distribution for each parcellation scale and imaging scheme. Brain regions exhibiting the rich-club property were also identified in the backbone brain structural networks constructed for each sampling scheme and nodal scale.To investigate the rich-club organization of the backbone networks  computed over 1000 random topologies yielded a null distribution of rich-club coefficients. For the range of k within the rich-club zones, it was tested whether Φ significantly exceeded Φrandom (averaged over the examined range of k) by assigning a p value computed as the percentage of Φrandom that exceeded Φ. At each parcellation scale, the topological properties of the unweighted networks constructed for different sampling schemes at the subject level were compared using the nonparametric Friedman test to investigate the significance (with p < 0.05) of differences between the networks.To assess the statistical significance of rich-club organization, permutation testing was used ,29. The 2) and 70.1 mm   . As show2 have better-resolved crossing configurations inside the voxels due to the higher angular resolution that can be achieved at higher b-values. In addition, visual inspection showed erroneous fiber tractography results  for the schemes with lower b-values (1000 and 3000 s/mm2). Overall, the inclusion of DW directions with higher b-values in the tractography procedure improved the tractography results at the locations where fiber bundles cross each other. Furthermore, our study shows that the three- and four-shell sampling schemes provided better tractography results for resolving crossing fibers with fewer false positives.2 exhibited higher small-worldness in comparison with other b-values regardless of the nodal scale. In this category, the lowest small-worldness was obtained with b = 5000 s/mm2. Among the multishell imaging schemes, the networks constructed using the three-shell  and two-shell  sampling schemes exhibited the highest and lowest small-worldness, respectively. Overall, the imaging schemes that included shells with b-values higher than 5000 s/mm2 exhibited significantly lower small-worldness. Moreover, the networks constructed at finer nodal scales displayed significantly (p < 0.05) higher small-worldness with larger confidence intervals across subjects in comparison with lower nodal scales.Our results showed an increasing trend for the small-worldness curves (σ) with an increasing number of nodes for each DWI scheme . The net2.To investigate whether the increase in small-worldness was due to an increase in clustering coefficient or a decrease in path length, we explored the trend of these metrics with an increasing number of nodes with respect to 1000 randomized networks generated for each structural network. As shown , both th2 exhibited lower values of modularity in comparison with the single-shell or other multishell sampling schemes. Regardless of the sampling scheme, the statistical comparison showed significant differences (p < 0.05) between the modularity values computed for the networks at different nodal scales.Modularity also showed an increasing trend with the nodal scale, demonstrating the tendency of the structural networks to form more communities at finer nodal scales, especially for the networks constructed using the single-shell schemes . Regardl2 and 10,000 s/mm2 exhibited the highest and lowest global efficiency regardless of the nodal scale, respectively. Among the multishell sampling schemes, the networks constructed using two shells  and three shells  exhibited the lowest and highest efficiency, respectively. Significant differences (p < 0.05) in global efficiency were observed between the single- and multishell schemes at different nodal scales. Overall, the inclusion of b-values higher than 5000 s/mm2 increased the global efficiency of the structural networks.The global efficiency declined exponentially with the nodal scale . Among tk) of the backbone structural brain networks (black lines in norm (k) (shown in red) also displayed an upward trend. The intervals, in which the networks exhibited a rich-club organization, are shown in gray , with k levels within the range of 12 to 22  and the imaging protocols based on single-shell or multishell sampling schemes. For fiber tracking, we used GQI, shown to be an efficient method for solving complex crossing-fiber configurations. In this method, QA is calculated as an indicator of the population of spins in a particular direction. The QA-aided tractography has been shown to outperform the fractional anisotropy-aided tractography, especially in low SNR conditions . At the p < 0.05) between the values of the graph metrics derived from the single- and multi-shell-based brain structural networks across all parcellation scales. Increasing the number of nodes from 68 to 1000 resulted in significant increases (with p < 0.05) in small-worldness due to increases in the clustering coefficient. This trend of changes is probably due to the increase in the sparsity (ratio of the number of nodes-to-links) of brain structural networks [With regard to the nodal scale, we calculated five graph metrics including small-worldness, characteristic path length, clustering coefficient, global efficiency and modularity, attributes widely used to characterize brain networks ,25. We fnetworks . This st2 were largely different from those obtained using the other single-shell or multishell imaging schemes, more likely due to longer white-matter streamlines generated with high b-values (2) across different nodal scales. In this case, the resulting networks exhibited higher efficiencies and tended to form fewer modules or communities connected through longer path lengths between high-degree nodes (hubs).With regard to the impact of the imaging protocol, the network metrics also showed dependence on the sampling scheme, although with a reduced effect compared to the nodal scale. Our results are in agreement with those reported by Zalesky et al. , who havb-values . The pre2) can significantly improve the tractography results obtained using deterministic tractography at the locations where fiber bundles cross each other [As also reported in , single-ch other ,32.Finally, consistent with the findings of other studies ,25,33, oOverall, our findings show that both the parcellation scale and sampling scheme can significantly affect the reproducibility of connectivity results. Therefore, comparison between different studies on structural brain network organization should be performed by taking into account the nodal scales and acquisition protocols used for connectivity analysis.A limitation of our study is that we used deterministic fiber tracking that can generate many false-negative streamlines ,36. The The main goal of our study was to investigate whether the topological properties of brain structural networks depend on the diffusion sampling scheme and the nodal scale. At the group level, the topological properties and rich-club organization of the structural brain networks showed significant dependence on both the nodal scale and imaging scheme. The parcellation scale, however, affected more strongly the topology of the constructed brain structural networks. Using the multiscale approach, we could evaluate the reproducibility of connectivity results across different parcellation scales, a critical step recommended in other studies . Our res


Coinfection with severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) and another virus may influence the clinical trajectory of emergency department (ED) patients. However, little empirical data exists on the clinical outcomes of coinfection with SARS-CoV-2In this retrospective cohort analysis, we included adults presenting to the ED with confirmed, symptomatic coronavirus 2019 who also underwent testing for additional viral pathogens within 24 hours. To investigate the association between coinfection status with each of the outcomes, we performed logistic regression.Of 6,913 ED patients, 5.7% had coinfection. Coinfected individuals were less likely to experience index visit or 30-day hospitalization .Coinfection is relatively uncommon in symptomatic ED patients with SARS-CoV-2 and the clinical short- and long-term outcomes are more favorable in coinfected individuals. According to the US Centers for Disease Control and Prevention, as of October 2021 the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus has caused an estimated 684 hospitalizations per 100,000 population and 711,020 deaths in the United States.With the introduction of reverse transcription real-time polymerase chain reaction assays the detection of viral coinfections has grown.A cross-sectional study of 1206 patients with respiratory symptoms revealed that 20.7% were positive for SARS-CoV-2 and at least one additional virus.Therefore, our objectives were to determine the frequency of SARS-CoV-2 and any additional respiratory virus (coinfection) among ED patients. Secondarily, we were interested in comparing encounters with and without coinfection in terms of the following: a) baseline characteristics; b) short-term outcomes ; and c) 30-day clinical outcomes . We hypothesized that patients with SARS-CoV-2 coinfection would be more likely to experience unfavorable short- and long-term outcomes.The national Registry of Suspected COVID-19 in Emergency Care (RECOVER) network recorded clinical data on 35,120 ED patient encounters for COVID-19 symptoms.≥ 18 years from 86 hospitals in 27 states. Eligibility for enrollment required that a molecular diagnostic test to have been performed in the ED setting or within 24 hours for patients with possible SARS-CoV-2 infection. Registry guidance advised that patients without suspected infection but who had swab testing performed in the ED only to comply with a hospital screening policy for admissions or preoperative testing be excluded.In this retrospective cohort analysis, we included RECOVER network encounters by adults What do we already know about this issue?Some reports of viral coinfection preceding the COVID-19 pandemic suggest higher disease severity with coinfection.What was the research question?What is the rate of SARS-CoV-2 coinfection among emergency department patients and its impact on clinical outcomes?What was the major finding of the study?Of 6,913 ED patients, 5.7% had coinfection. Coinfected individuals were less likely to experience index visit or 30-day hospitalization.How does this improve population health?Adults with coinfection with SARS-CoV-2 do not have worse clinical outcomes, compared to those without coinfection. This suggests that the impact of extended viral panels on clinical management is limited.The primary exposure was coinfection by any respiratory virus(es)  at the index ED visit.The outcomes of interest were hospitalization at the index ED visit, any hospitalization within 30 days of index ED visit, and severe COVID-19. Severe COVID-19 was defined as intubation with mechanical ventilation and/or death within 30 days.10We described the baseline characteristics and clinical presentation at the index ED visit as well as outcomes. To investigate the association between coinfection status with each of the outcomes, we then constructed unadjusted and adjusted logistic regression models. In the multivariable model, we adjusted for 10 potential confounders based on a priori knowledge: age; gender; race/ethnicity; hypertension; cardiovascular diseases; chronic obstructive pulmonary disease; other chronic lung diseases; obesity; diabetes; and cancer.After exclusion of records from seven sites that used different inclusion criteria , incomplete records , children (n = 426), and encounters without non-SARS-CoV-2 viral testing , our analytic sample included 6913 patient encounters . Among tOverall, 1,843 (27%) patients had SARS-CoV-2 of whom 1,726 (94%) had SARS-CoV-2 alone and 117 (6%) were coinfected with an additional virus . Those wP<0.001), and less likely to result in any hospitalization within 30 days , compared to encounters with patients testing positive for SARS-CoV-2 alone. In the multivariable model, compared with patients who had only SARS-CoV-2, those with SARS-CoV-2 and at least one additional virus had lowered adjusted odds of hospitalization at the index ED visit  and hospitalization within 30 days . Coinfected patients did not have an increased odds of severe COVID-19 .Encounters in which patients were coinfected were significantly less likely to result in hospitalization at the index ED visit  among symptomatic ED patients, and coinfection was not associated with hospitalization or other unfavorable short- and long-term outcomes. To our knowledge this is the first study examining clinical outcomes of symptomatic ED patients with SARS-CoV-2 based on coinfection status.There are several potential explanations for why coinfection appeared to have a “protective” effect. First, ED patients found to be coinfected could have had an asymptomatic SARS-CoV-2 infection and may have had presenting symptoms from their other virus. Another explanation could be that individuals with high rates of prior viral exposure – through their occupation or social behaviors – may have primed their immune system with other coronaviruses and respiratory pathogens and may, therefore, have experienced less severe COVID-19.Compared to other published studies on coinfection, we found similar rates of other viruses, with RSV being most common.19Clinical and policy implications of our study include that viral coinfection status does not confer greater risk of clinical deterioration among ED patients. Based on our results adults with multiple viral pathogens (coinfection with SARS-CoV-2) do not have worse clinical outcomes, compared to those without infection, which suggest that the impact of extended viral panels on clinical management is limited. A study by Burk et alMultiple guideline groups have addressed the role of laboratory testing for viruses in different patient populations.Future directions include evaluating coinfection status among patients who are asymptomatic. Most studies published on this topic include only symptomatic patients, and coinfection rates may be higher in this population.28One potential limitation of this work is that coinfection rates may be lower than true rates, given clinician and site variability in respiratory virus testing. Additionally, as this was a retrospective analysis site investigators did not change clinical care or practice patterns. Thus, it was at the discretion of the emergency clinician whether to order an extended viral panel or solely a COVID-19 test. The ordering of extended viral panels is likely clinician, patient, and site specific. We also could not account for important confounders, such as smoking, frailty, and socioeconomic factors. Another possible limitation is that respiratory viruses are seasonal, and our data includes encounters from February–October 2020 only.Sixty-seven percent of our included patients were admitted. This high rate of admission could suggest that extended viral panels were more often ordered on patients with higher disease severity. Thus, there is a potential issue of confounding by indication. Strengths of our study include its generalizability; our data represents ED encounters throughout the US. Although we have statistically significant inference with the sample size in our cohort, an external validation in a separate patient sample would further enhance generalizability of the inference. Patient presentations to the ED likely reflect those with clinically meaningful illness (vs serum antibody testing that was included in prior studies).10We found that coinfection is relatively uncommon in patients with SARS-CoV-2 and the clinical short- and long-term outcomes for patients are more favorable in coinfected individuals. These findings provide insight into the clinical course of patients with coinfection and lend support to the theory that commonly encountered respiratory viruses could stimulate the immune response to protect individuals from SARS-CoV-2.15


The improved switching strategy increases the probability of switching to second-line ART when virologic failure is diagnosed through viral load testing. The PDR testing strategy involves a one-time PDR test prior to ART initiation to guide choice of initial regimen. When DTG is not available, PDR testing is dominated by the improved switching strategy, which has an incremental cost-effectiveness ratio (ICER) of USD 579/life-year gained (LY), relative to the status quo. If DTG is available, improved switching has a similar ICER (USD 591/LY) relative to the DTGstatus quo. Even when substantial financial investment is needed to achieve improved regimen switching practices, the improved switching strategy still has the potential to be cost-effective in a wide range of sub-Saharan African countries. Our analysis highlights the importance of strengthening existing laboratory monitoring systems to improve the health of children living with HIV.Improvement of antiretroviral therapy (ART) regimen switching practices and implementation of pretreatment drug resistance (PDR) testing are two potential approaches to improve health outcomes for children living with HIV. We developed a microsimulation model of disease progression and treatment focused on children with perinatally acquired HIV in sub-Saharan Africa who initiate ART at 3 years of age. We evaluated the cost-effectiveness of diagnostic-based strategies ( In sub-Saharan Africa, the prevalence of pretreatment drug resistance (PDR) to non-nucleoside reverse transcriptase inhibitor (NNRTI)-based antiretroviral therapy (ART) among children living with HIV is increasing, and PDR is associated with an increased risk of virologic failure ,2. In 20Despite efforts to expand early infant diagnosis programs, nearly 40% of HIV-exposed infants are not retained in care long enough to definitively determine their HIV status . As a reUse of dolutegravir (DTG) is expected to address the challenges associated with PDR to NNRTI-based ART. Although DTG was approved for children in 2019 and is now recommended for use as first-line ART , its impIn children initiating ART who are 3 years and older, and for whom DTG is not currently an option, there are two diagnostic-based strategies that can potentially address the increased risk of virologic failure associated with PDR. First, introduction of PDR testing could be used to guide choice of first-line regimen, providing PI-based ART for children diagnosed with PDR. To date, the use of drug resistance testing for patient care in sub-Saharan Africa has been extremely limited due to multiple barriers, including the cost of testing and limited laboratory infrastructure . Prior sA second diagnostic-based strategy that can potentially improve health outcomes for children with or without PDR is to strengthen viral load testing systems, such that virologic failure is diagnosed in a more timely manner, and to facilitate a faster transition to second-line ART once virologic failure is detected . In 2013In this model-based analysis, we evaluated the cost-effectiveness of two diagnostic-based strategies, PDR testing and improved regimen switching practices when virologic failure is diagnosed on first-line ART, in the context of no dolutegravir availability for children initiating ART at 3 years of age. We then also evaluated the potential cost-effectiveness of improved regimen switching when an appropriate DTG-based ART formulation is available as the first-line regimen for children 3 years of age.status quo and two diagnostic-based strategies in a scenario in which pediatric DTG is not available, over a 10-year time horizon. In the status quo strategy, we assumed that, under current clinical practice, a child diagnosed with virologic failure while on NNRTI-based first-line ART has a 40% probability of switching to PI-based second-line ART . Finally, in the PDR testing strategy, all children are tested for PDR prior to ART initiation, and children diagnosed with PDR initiate ART with a PI-based regimen.We developed a microsimulation model of disease progression and treatment focused on children with perinatally acquired HIV in sub-Saharan Africa who initiate ART at 3 years of age see . Using t ART see . In the DTG status quo strategy, we assumed DTG-based ART is used as the first-line regimen, which is associated with a lower probability of virologic failure than NNRTI-based ART, and a child diagnosed with virologic failure while on first-line ART has a 40% probability of switching to PI-based second-line ART. In the DTG improved switching strategy, we assumed a child diagnosed with virologic failure while on DTG-based first-line ART has an 80% probability of switching to PI-based second-line ART (double compared to DTG status quo). Because rates of PDR to DTG are currently low, we omitted the PDR testing strategy and only evaluated the comparative clinical and cost-effectiveness of improvements of ART regimen switching practices when virologic failure is diagnosed (DTG improved switching) against the DTG status quo.Next, in a separate scenario, we evaluated the cost-effectiveness of diagnostic-based strategies when a pediatric DTG formulation is available and replaces NNRTIs in first-line ART. In this scenario, under the We developed a microsimulation model of disease progression and treatment for children living with HIV, starting at time of birth. Our pediatric HIV microsimulation model was based on an adaptation of a previously published model for adult HIV . It was We assumed that the probability of virologic failure during the first 12 months of ART is higher for children with PDR if they are initially treated with NNRTI-based ART (64.1% probability of virologic failure) compared those with PDR who receive PI-based ART (19.2% probability of virologic failure) and those who do not have PDR and are initially treated with NNRTI-based ART (19.2% probability of virologic failure). These model parameters assume the odds of virologic failure with initial ART are 7.5 times higher (odds ratio = 7.5) for those with PDR receiving an NNRTI-based regimen compared to those without PDR or those with PDR receiving PI-based ART as their initial regimen see . We assuFor each strategy modeled, we projected several health outcomes, including proportion of children with viral suppression, proportion of children surviving over time, person-months of ART use, proportion of children using PI-based ART, and total life years (LYs) accrued. To evaluate cost-effectiveness, we also considered the total direct health care costs incurred, reported in 2020 USD. Incremental cost-effectiveness ratios (ICERs) were calculated in terms of USD/LY gained. We adopted a health sector perspective, discounted future costs and benefits 3% annually, and adhered to the recent recommendations of the Second Panel on Cost-Effectiveness in Health and Medicine .To address uncertainty associated with epidemiologic, clinical, and cost parameters, we conducted one-way sensitivity analyses for multiple parameters, including PDR prevalence, probability of virologic failure with PDR on NNRTI-based ART, probability of virologic failure on PI-based second-line ART, and the costs of various components of HIV care . Of noteimproved switching or DTG improved switching) do not incur any additional costs to achieve this improved switching, other than the additional cost of PI-based ART relative to first-line ART. However, in reality, any potential intervention designed to address this issue is likely to require financial investment. While some effective interventions have been identified to facilitate timely transition to second-line ART [status quo).In the base-case and sensitivity analyses described above, strategies with increased probability of switching to second-line ART when virologic failure is diagnosed , and finally status quo (63.7%). Similarly, the proportion of children alive 5 years after ART initiation was highest with the improved switching strategy (71.2%), followed by the PDR testing strategy (71.0%), and finally status quo (69.3%). When DTG was available, the proportion of children with suppressed viral load at 5 years after ART initiation was higher with the DTG improved switching strategy than the DTG strategy (68.3% vs. 67.4%), as was the proportion of children alive 5 years after ART initiation (72.1% vs. 71.4%). Overall, viral suppression and survival outcomes were better when DTG was available compared to when it was not . Person-months of ART use were also increased , which costs more than NNRTI-based ART. For improved switching, increased ART costs made up 81% of the extra costs compared to the status quo. For PDR testing, increased ART costs and PDR testing made up 51% and 46% of the extra costs compared to the status quo, respectively.Compared to the ectively . As thesDTG status quo) resulted in 1.6% higher costs for viral load testing and outpatient visits, collectively, and more person-months of ART use (84.4 vs. 82.3 per person), compared to the status quo. However, higher rates of viral suppression with DTG were associated with less use of PI-based ART (4.5 person-months vs. 13.7 person-months per person) and a 5% decrease in total costs for DTG status quo compared to the status quo.Due to higher survival, using DTG as first-line ART for children 3 years of age  compared to the status quo, resulting in an ICER of USD 579/LY gained. PDR testing was dominated by improved switching, as improved switching achieved greater health gains (by 33 discounted LYs per 1000 children initiating ART) at a lower cost . When we only considered strategies with DTG availability, DTG improved switching gained 43 additional discounted LYs (per 1000 children initiating ART) compared to DTG, resulting in an ICER of USD 591/LY gained.Overall, strategies with DTG availability resulted in more LY’s gained compared to strategies without DTG availability ; Table 3improved switching and DTG + improved switching strategies were the cost of PI-based ART, cost of outpatient care, and cost of viral load testing , but only when improved switching increased the probability of switching to PI-based second-line ART when virologic failure is diagnosed from 40% to only 60% or less (instead of 80%). However, this was achieved at a significantly higher cost per life-year gained  to USD 1186/LY gained (with a 50% probability of switching)  . When wer range; , and it r range; .As ART programs throughout sub-Saharan Africa await the availability of DTG for young children, improvement of ART regimen switching practices and implementation of PDR testing are two potential approaches to improve health outcomes in this population. We used a model-based analysis to evaluate the cost-effectiveness of these two diagnostic-based strategies in a setting without DTG availability for children initiating ART at 3 years of age. We also evaluated the potential cost-effectiveness of improved regimen switching when DTG-based ART was available as the first-line regimen.In the context of no DTG availability, we found that improving regimen switching practices when virologic failure is diagnosed (increasing probability of switching to second-line ART from 40% to 80%) dominated PDR testing, with an ICER of USD 579/LY gained compared to the current standard of care ; Table 3We found that the availability of DTG-based first-line ART provided greater health benefits than any of the non-DTG-containing strategies, thus supporting the importance of implementing DTG as soon as it is available for young children ,18. ThisAlthough rates of virologic suppression in children are expected to improve as DTG is used more widely, if not addressed, suboptimal regimen switching practices for patients with virologic failure are likely to persist even with DTG use. We found that potential interventions to improve regimen switching practices are likely to be similarly cost-effective when DTG-based ART is the first-line regimen compared to when NNRTI-based ART is the first-line regimen . One of Once DTG becomes more widely available to children, more research will be needed to better understand potential risk factors for virologic failure with DTG-based ART in this population, such as nucleoside reverse transcriptase inhibitor (NRTI) backbone resistance. To date, evidence shows that PI-based ART achieves relatively high rates of viral suppression even with a non-active NRTI backbone, but such evidence is currently lacking for DTG-based ART . If chilOur model also has some additional limitations. First, our broad focus on sub-Saharan Africa is intended to provide conceptual insights that are widely applicable in LMIC. However, each country will face its own particular considerations. For example, viral load testing may not be accessible for all children on ART, as we assumed. Also, baseline rates of switching to second-line ART when virologic failure is diagnosed are likely to vary by ART program. Second, our scenario analyses imply that the cost of potential interventions to improve regimen switching practices will be directly proportional to the number of children with virologic failure. As implementation scientists advance this work, they may find that some potential interventions experience economies of scale or diminishing returns as they scale-up. Additional analyses can be conducted and tailored to better meet the specifications of new interventions as they are developed. Third, our assumptions about the probability of virologic failure on DTG-based first-line ART are based on extrapolations from adult data. Last, our analysis focused only on children initiating ART at 3 years of age. However, the insights gained by our analysis regarding the potential cost-effectiveness of improving regimen switching practices are likely to have similar implications for children initiating ART at a younger age. Moreover, if implemented among adult men and women, improving switching practices could potentially decrease not only PDR among children but also the incidence of HIV among infants altogether.In conclusion, while ART programs await the availability of DTG for young children, increased investment to improve regimen switching practices has the potential to be a cost-effective approach for improving health outcomes for children living with HIV. Our analysis provides economic data to further support ongoing calls to strengthen existing viral load testing systems to improve health outcomes . Thus, o


The onset of the Coronavirus 2019 (COVID-19) pandemic has challenged the worldwide healthcare sector, including dentistry. The highly infectious nature of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and risk of transmission through aerosol generating procedures has profoundly impacted the delivery of dental care services globally. As dental practices with renewed infection control strategies and preventive measures are re-opening in the “new normal” period, it is the responsibility of healthcare professionals to constantly analyze new data and limit the spread of COVID-19 in dental care settings. In the light of new variants of SARS-CoV-2 rapidly emerging in different geographic locations, there is an urgent need to comply more than ever with the rigorous public health measures to mitigate COVID-19 transmission. The aim of this article is to provide dental clinicians with essential information regarding the spread of SARS-CoV-2 virus and protective measures against COVID-19 transmission in dental facilities. We complied and provided guidance and standard protocols recommended by credible national and international organizations. This review will serve as an aid to navigating through this unprecedented time with ease. Here we reviewed the available literature recommended for the best current practices that must be taken for a dental office to function safely and successfully. Currently, the rapidly escalating outbreak of 2019 novel Coronavirus (COVID-19) caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) presents serious global concerns that are impacting public health, overall healthcare systems, and the global economy. The Hubei Province of China reported the first patient with pneumonia of unknown cause, resembling viral pneumonia on 31 December 2019 . As of 2The transmission patterns of SARS-CoV-2 suggest that respiratory droplets and direct contact are the main routes of transmission . With thThe article aims to provide dental practitioners with essential knowledge concerning SARS-CoV-2 spread and protective measures against COVID-19 transmission. Here we reviewed available literature about COVID-19 and compiled the relevant guidance and standard-of-care recommended by public health organizations. Coronaviridae ..40].At the onset of the pandemic, the response by many dental practices was to open only for urgent and emergency visits, since dentists would be at high-risk. When providing emergency and urgent dental procedures, the CDC states that it is “crucial to minimize aerosol generation and the ensuing probability of transmission to personnel and patients” . AccordiA study conducted on a cluster of patients who underwent surgery  and who had SARS-CoV-2 infection within seven days before or 30 days after surgery reported both post-operative pulmonary complications in half of the patients with peri-operative SARS-CoV-2 infection, and increased mortality. The study encouraged postponement of non-critical elective procedures and promoted non-surgical treatment options to delay the demand for surgery .Currently, as dental facilities slowly begin to deliver elective dental services once again, it is crucial for the dental professionals to constantly analyze the data from their state and local healthcare departments to keep updated on zone and community-specific COVID-19 human transmission statistics and precautionary directives. Demonstrate signs and symptoms of COVID-19.Have been in contact with people with suspected or confirmed cases of COVID-19 but are themselves asymptomatic.Present no symptoms or had no known contact with suspected or confirmed COVID-19 individuals but still were tested by early identification in special settings.Have been confirmed to have COVID-19 but are no longer symptomatic.Were tested by public health officials for contact tracing or tracking the speed of COVID-19.In the evolution of the current pandemic, screening patients for COVID-19-related signs and symptoms prior to scheduling an appointment has emerged as an important tool to identify patients in need for isolation and also for contact tracing. Screening strategies include diagnostic testing, screening questionnaires, and temperature/symptom check protocols. The CDC has released a summary of consolidated recommendations for testing people for SARS-CoV-2 infection in certain situations:Source: CDC COVID-19 testing recommendations .To date, the CDC has approved both viral and antibody tests for COVID-19. Viral tests determine the current SARS-CoV-2 infection status by checking nasal swabs. Antibody tests determine the past infection of SARS-CoV-2 by checking blood for antibodies against SARS-CoV-2. At present, a confirmatory diagnosis for COVID-19 is given by testing respiratory samples with a real-time polymerase chain reaction (RT-PCR) diagnostic panel . Other tIn dental practice, telehealth platforms can help assess the risk profile of a patient, needs, and aid in establishing a dental triage .Screening of patients before visiting the dental clinic will prevent exposure and spread of virus to clinical staff. At the same time, all the clinical staff should be screened every day for COVID-19 symptoms.Considering that SARS-CoV-2 has been consistently detected in saliva , this fiIt is also imperative that employers and facility managers develop patient management strategies and overall practice controls  as shown in Similarly, for optimal safety and protection, patient management strategies must be enforced before the dental appointment, upon patient arrival at the dental facility, during the procedure, and when leaving the dental facility. Recent data suggest that without social distancing or any other preventive measures, the risk of transmitting the coronavirus is 17.4%. However, a mask or respirator will reduce the risk of transmission to 3.1% . Schedule appointments thoughtfully, ensuring limited number of patients in the clinic at any given time, and observing at least six feet of physical distancing.Minimize the number of patients in the waiting area and personnel in the operating area at any given time.Encourage patients to present alone, if possible, thus limiting the number of visitors in the clinic areas.Advise patients and accompanying persons to arrive with a face covering or provide a surgical mask upon arrival.Assess temperatures using a non-contact thermometer of all patients, visitors, and staff to rule out fever upon arrival.Re-verify the screening questions verbally and through observation to rule out any COVID-19 signs and symptoms.Ensure the waiting area is free of magazines, reading materials, and toys in order to limit the transmission through surfaces.Install physical barriers (plastic or fiberglass) at the front desks to limit transmission in the reception area.Post signs, posters, and flyers regarding COVID-19 recommendations and information addressing hand hygiene and cough etiquette in the dental care facilities for patient and staff education.Educate patients on the possibility of prolonged appointments due to newer disinfection measures.Implement contactless payments or pre-payments, thus reducing the number of interactions between patients and personnel.Request patients to inform the clinic if they develop symptoms within 14 days of appointment.Interim guidance developed by Public health agency of Canada recommends dental personnel to routinely practice point-of-care risk assessment (PCRA) prior to clinical interaction with the patient to assess the risk of infection exposure, high risk tasks and appropriate measures to minimize the potential exposure .All dental personnel should adhere to standard infection control precautions, including personal protective equipment (PPE).The CDC recommends health care workers to use N95 filtering facepiece respirators (FFR) that can filter at least 95% of all particles, including bacteria and viruses to a size of almost 0.3 µm. European standards classify filtering facepiece respirators (FFR) as FFP1 with minimum filtration efficiency (MFE) of 80%, FFP2 with MFE 94% and, FFP 3 with MFE 99%. European standard FFP2 are equivalent to N95 FFR’s . Healthc(a)National Institute for Occupational Safety and Health (NIOSH) approved Filtering facepiece respirators: N99, N100, P95, P99, P100, R95, R99, and R100 .(b)An air purifying elastomeric respirator with appropriate filters and cartridges.(c)Powered air purifying respirators (PAPR): These are reusable battery powered respirators attached to a high efficiency particulate arrestor (HEPA) filter. PAPR provides better respiratory protection than N95 FFR. However, an ergonomic impact due to the weight of the filter can occur .(d)In the event of unavailability of a respirator for an aerosol generating procedure, the CDC recommends use of a surgical mask and a full-face shield .Alternatives for N95 FFR include diverse options:Conduct a seal check of the FFR to determine whether the mask is properly worn, and types of seal checks include positive and negative pressure checks.Dental healthcare personnel (DHCP) should limit clinical care to one patient at a time if possible.Operating areas should be set up with only clean or sterile instruments. Any equipment that is exposed but not used during a procedure should be considered contaminated and should be disposed of or autoclaved properly.Minimize aerosol-inducing and -generating procedures when possible and prioritize atraumatic restorations and minimally invasive procedures utilizing hand instruments only.Minimize the number of intra-oral radiographs that could induce aerosols through coughing or gagging. Extra- over intra-oral imaging is preferred.Aerosol generating procedures should be conducted in airborne infection isolation rooms (AIIR).Airborne precautions should be employed when aerosol generating procedures are conducted. Four-handed dentistry is recommended using high vacuum suctions (HVE), rubber dams, and other appropriate appliances, such as extra-oral vacuum aspirators (EOVA) that can reduce infectious aerosol dispersion.CDC guidelines mention the possibility of clinical effectiveness of preprocedural mouth rinses (PPMR) containing antimicrobial products, such as povidone-iodine, chlorhexidine, essential oils, and/or cetylpyridinium chloride for reducing the viral load in the aerosols and spatter. However, given that there are no adequate data published on the clinical effectiveness of preprocedural rinses on reducing viral titers of SARS-CoV-2, well-designed human trials are necessary to investigate this area of concern.Engineering controls, such as maintaining ventilation systems in a clean to less clean air flow direction, HEPA air filtration units for enhanced air cleaning, and heating, ventilation, and air-conditioning (HVAC) systems for increased filtration efficiency should be considered.The CDC recommends upper-room ultraviolet germicidal irradiation (UVGI) of wavelengths 200 and 280 nm as an adjunct to establishing adequate ventilation and air venting.Implement strict hand hygiene measures before and after contact with patients, before donning and after removal of all PPE, and after contact with any potentially contaminated surfaces. Proper hand hygiene measures require using water and soap and alcohol-based hand rubs  for at least 20 sec.To clean and disinfect the operating area after a dental procedure, the CDC recommends a wait time of 15 min for air change to occur. Routine cleaning and standard disinfection should be conducted with an Environmental Protection Agency (EPA)-registered disinfectant. In a situation in which an aerosol generating procedure is conducted on a suspected or COVID-19 confirmed patient, the Australian Dental Association recommends “terminal/infectious clean” of the dental setting in which a two-step cleaning with detergent followed by hospital grade disinfectant is to be used . are changes in work procedures, such as written safety policies, rules, supervision, schedules, and training with the goal of reducing the duration, frequency, and severity of exposure to hazardous chemicals or situations. Engineering controls eliminate or reduce exposure to a chemical or physical hazard through the use or substitution of engineered machinery or equipment. PPE: Personal protective equipment. (Source: The MSDS Hyper Glossary). SOURCE: CDC: Strategies for optimizing the supply of N95 Respirators )..PPE for droplet and contact precautions is recommended for use during procedures that do not involve high-risk aerosol-generating medical procedures. This procedure includes several pieces of PPE: (1) surgical mask, (2) eye protection (goggles or procedure mask with face shield), (3) Association for the Advancement of Medical Instrumentation (AAMI) level-two gowns, and (4) gloves that overlap the gown sleeve.PPE for airborne, droplet, and contact precautions is recommended for a healthcare provider present in the operating area during high-risk aerosol-generating medical procedures. This procedure includes several pieces of PPE: (1) N95 respirator, (2) eye protection (goggles or procedure mask with face shield), (3) head covering, (4) AAMI level-two gowns, and (5) gloves that overlap the gown sleeve.PPE for airborne, droplet, and contact precautions for high risk AGMPs is recommended for healthcare providers directly involved in high-risk aerosol-generating medical procedures. This procedure includes several pieces of PPE: (1) N95 respirator, (2) eye protection (goggles or procedure mask with face shield), (3) head covering, (4) AAMI level two/three gowns, and (5) double gloves that overlap the gown sleeve. Lockhart et al.  recommenInfectious aerosols generated from aerosol-generating dental procedures endanger dental personnel due to the risk of infection through inhalation, direct contact, and/or autoinoculation. The latest research characterizes the size of dental aerosols to be <0.3 µm (0.05–0.15 µm diameter range corresponding to the reported size of SARS-CoV-2 virus [0.05–0.15 µm]) and are estimated to be airborne for 28 to 34 min after the cease of dental aerosol generating procedures . The resIdeally, the CDC recommends aerosol-generating dental procedures to be conducted on a single patient in a negative pressure AIIR . The airTake time to plan and to communicate modifications to usual approach.Use highest level of PPE that is available .Limit the number of personnel to those who are necessary to safely perform the procedure.Restrict operating area access once patient has entered the room.Limit direct contact with patient as much as possible.Employ the least number of aerosol-generating techniques and reduce open airway time.Minimize handling of contaminated instruments and surfaces on which respiratory secretions may have settled.Anti-retraction valves which prevent cross-contamination of the water.Use of 3%hydrogen peroxide as mouthwash before procedure.PPMR/gargle with PVP-I is considered effective in reducing the viral load of SARS-CoV  and MERSRecent literature suggests the correlation between COVID-19 complications, oral health, and periodontal disease, and explores the possibility of reducing COVID-19-associated systemic complications by improving oral hygiene ,65. The It is evident that the oral microbiome is an important determinant of lung microbiomes in both healthy and immunocompromised individuals. Importantly, a unique thought that has yet to be explored is the therapeutic alteration of the lung microbiome by changing the oral microbiome. Although much about the oral lung microbiome is yet to be understood, the authors have made it very clear that good oral health is beneficial and can help prevent the risks of being infected with systemic diseases. Considering the clinical significance of antibiotic misuse across healthcare fields, dentistry may indirectly impact COVID-19 by triggering deaths due to secondary infection . AccordiIn the initial months of the COVID-19 pandemic, dental care along with other healthcare sectors came to a standstill. Now, in the wake of enhanced infection control practices and availability of adequate PPE, the dental care sector and dental economy have both been rebounding. In the United States, as of 15 February 2020, the ADA reports that patient volume to dental offices is recovering up to 81% of pre-COVID-19 levels, and dental staffing is stabilizing at 91% of pre-COVID-19 levels . HoweverThe COVID-19 pandemic is an unprecedented disaster that has significantly impacted the healthcare system, including dentistry. After analyzing the available data on SARS-CoV-2 and considering the fact of rapidly emerging trends in COVID-19 transmission, this study recognizes the multitude of implications regarding its spread, infection control, and prevention. This review article highlights relevant guidance and protocols recommended to mitigate SARS-CoV-2 transmission in dental facilities. In the wake of new data, it is expected that more innovative armamentarium and upgrades to infection control procedures in dental offices will be implemented ,73. In t


The main reason for a missing SARS-CoV-2 vaccination (70%) was being sceptical about the vaccine itself . Conclusions: Vaccination coverage against SARS-CoV-2 is high in patients with rheumatic diseases. Nevertheless, there are unmet needs regarding vaccination education to further increase vaccination rates.Background: In the second year of the COVID-19 pandemic, highly effective and safe vaccines became available. Since patients with rheumatic diseases show increased susceptibility to infections and typical medications raise the risk of severe COVID-19, high vaccination coverage is of significant importance to these patients. Methods: Consecutive patients with different rheumatic diseases were asked for their vaccination status regarding COVID-19, influenza and Streptococcus pneumoniae during their routine consultations. Any reported vaccination was validated with their personal vaccination card and/or by reviewing the CovPass smartphone app. Reasons for not having a COVID-19 vaccination were documented. Results: A total of 201 patients (mean age 62.3 ± 14.1 years) were included, the majority of them (44.3%) with rheumatoid arthritis, followed by spondyloarthritis (27.4%) and connective tissue diseases (21.4%). Vaccination coverage for SARS-CoV-2 was 80.1%; 85.6% got at least the first vaccination shot. Both valid influenza and pneumococcus coverage were associated with a higher probability of SARS-CoV-2 vaccination (odds ratio (OR) 6.243, 95% confidence interval (CI) 2.637–14.783,  The COVID-19 pandemic puts people with rheumatic diseases at an increased risk since they are highly susceptible to infections. During the last year, typical rheumatologic therapies such as high-dose glucocorticoids and the CD20-depleting agent rituximab have been shown to predispose patients to severe COVID-19 . ConsequCOVID-19 vaccination is recommended for patients with rheumatic diseases by the Standing Committee on Vaccination (STIKO) of the Robert Koch Institute (RKI) as well as the German Society for Rheumatology (DGRh) ,11.Contrary to the well-known COVID-19 vaccination rates in the general population, details on vaccination coverage in people with rheumatic diseases are scarce. The primary aim of this study was, therefore, to measure vaccination coverage of COVID-19 in a German cohort of patients with rheumatic diseases. To gain more insight into individual vaccination behaviour and confidence, current influenza and pneumococcal protection were evaluated. Finally, reasons for vaccination hesitancy have been documented.Consecutive adult patients with a rheumatic disease were recruited from our outpatient clinic during their regular consultations between June and August 2021. They were asked for their vaccination status regarding SARS-CoV-2, influenza  and Streptococcus pneumoniae (within the last five years). Vaccines were typically administered by general practitioners or in vaccination centres. None were applied in our outpatient clinic. Any reported vaccination was double-checked by either reviewing the individual vaccination cards or using the CovPass smartphone app. CovPass is an application from the Robert Koch Institute for German residents, which allows a European Union Digital COVID Certificate for their valid SARS-CoV-2 vaccination to be stored and recalled . ApproveThe design of the study was approved by the ethics committee of the University of Leipzig (282/21-ek), and informed consent was obtained from all participants before study enrolment.p-value was <0.05. All analyses were two-tailed and conducted using GraphPad PRISM Version 8 for Mac .To describe continuous data, mean and standard deviation (SD) were used. Categorical data were described with absolute or relative frequencies. To compare the frequencies of categorical variables, Chi-squared tests were performed. A significant statistical difference was assumed when the n = 201 patients with different rheumatic diseases .In total, p < 0.0001). For patients with a valid pneumococcal vaccination, we saw a similar relationship ; see The probability of being vaccinated against SARS-CoV-2 was markedly higher among patients with a valid influenza vaccination in 2020 (odds ratio (OR) 6.243, 95% confidence interval (CI) 2.637–14.783, When asking patients for their motives for not being vaccinated, scepticism regarding the used vaccines and fear of unwanted side effects was found to be the main reason 70%, see . This paThe main outcome of our study is the high vaccination rate against SARS-CoV-2 in a German cohort with inflammatory rheumatic diseases. Of importance, vaccination was more likely in patients with either a valid influenza or pneumococcus vaccination and in patients 60 years of age or older.An Australian online survey among patients with rheumatic diseases regarding vaccination willingness reported that 65% were willing to have a COVID-19 vaccine . While tOur study collected data in the middle of 2021. In the beginning of 2021, COVID-19 vaccination was recommended verbally to all our patients during their outpatient consultations. This might have contributed to the high vaccination rate of 80% we observed. The current vaccination rates for the general population in Germany as of September 9th were 66.3% (at least one shot) and 61.9% (complete vaccination) . A FrencThe association between an increased age (≥60 years) and probability of SARS-CoV-2 vaccination most likely is a result of the vaccine shortage at the beginning of 2021: German recommendations consequently stratified vaccination priority according to risk, and therefore, older people got vaccinated first (vaccination prioritizing was cancelled in June 2021 ). On theThe main patient concern regarding the COVID-19 vaccination was that the vaccines might not have been studied properly, so some patients feared unwanted side effects. This finding is in line with an investigation in cancer patients . AccordiThe main limitation of our investigation is the tertiary character of our university hospital with specialized rheumatologic care. The findings in our study might therefore not be generalizable to standard rheumatologic care settings. Nonetheless, we believe that our finding of a high vaccination rate among patients with rheumatic diseases is encouraging and contributes greatly to our current knowledge regarding COVID vaccination.Vaccination rates against SARS-CoV-2 are fortunately high in our cohort of patients with rheumatic diseases in a tertiary university hospital. Scepticism regarding the safety of the approved vaccines was the main reason for not being vaccinated in our cohort. This finding emphasizes the importance of patient education with particular attention to the safety of the available COVID-19 vaccines. Preferably, education should be ensured by both rheumatologists and general practitioners to further improve vaccination rates.


BRCA1/2 mutation  were matched 1:2 with non-gBRCA controls (n = 150) by treatment arm, lymph node status, and age to evaluate pCR rates and association of benefit from platinum/PARP inhibitors with validated RNA expression-based immune, proliferation, and genomic instability scores among gBRCA with the addition of carboplatin ± veliparib to NAC. Among the well-matched cohorts, odds of pCR were not higher in gBRCA cancers who received standard NAC with carboplatin  or with carboplatin/veliparib  compared to non-gBRCA cancers. Higher PAM50 proliferation, GeparSixto immune, and CIN70 genomic instability scores were each associated with higher pCR rate in the overall cohort, but not specifically in gBRCA cases. In this study, gBRCA carriers did not have higher odds of pCR than non-gBRCA controls when carboplatin ± veliparib was added to NAC, and showed no significant differences in molecular, immune, chromosomal instability, or proliferation gene expression metrics.In the BrighTNess trial, carboplatin added to neoadjuvant chemotherapy (NAC) was associated with increased pathologic complete response (pCR) rates in patients with stage II/III triple-negative breast cancer (TNBC). In this matched cohort study, cases with a germline  To improve pCR rates, studies have attempted to add additional agents to the anthracycline plus taxane NAC backbone. Three studies have shown an improvement in pCR rate with the addition of carboplatin: GeparSixto5, CALGB 406036, and I-SPY27. Expanding on I-SPY2, BrighTNess was a phase III, multicenter, international, randomized, double-blind, placebo-controlled clinical trial, which enrolled 634 patients with stage II/III TNBC 2:1:1 to NAC with: (A) paclitaxel plus carboplatin plus veliparib followed by doxorubicin plus cyclophosphamide (TCV-AC), (B) paclitaxel plus carboplatin followed by doxorubicin plus cyclophosphamide (TC-AC), or (C) paclitaxel followed by doxorubicin plus cyclophosphamide (T-AC). In BrighTNess, the rate of pCR was higher in the TCV-AC (53%) and TC-AC (58%) arms, compared to T-AC (31%)8.In localized triple-negative breast cancer (TNBC), neoadjuvant chemotherapy (NAC) allows for assessment of pathologic response to chemotherapy. Pathologic complete response (pCR) is associated with improved overall survival compared to residual diseaseBRCA mutations result in impaired DNA damage repair by homologous recombination, which leads to sensitivity to PARP inhibitors and platinum chemotherapy in metastatic TNBC, as seen in the OlympiAD and TNT trials, respectively10. In the BrighTNess trial, 14–16% of patients in each arm had a confirmed deleterious germline BRCA1/2 mutation8. Interestingly, in the subgroup analysis of patients with germline BRCA mutations there was no difference in pCR between BRCA mutated and wildtype patients overall: 51% of patients with a BRCA mutation (gBRCA), achieved a pCR, compared to 48% of patients that did not harbor a BRCA mutation (non-gBRCA)8. There was a trend among patients with germline BRCA mutations toward higher pCR rates compared to T-AC alone (41%) with the addition of carboplatin to paclitaxel (50%), and a further trend toward higher pCR as veliparib was added to carboplatin and paclitaxel (57%)8. In non-gBRCA patients, pCR rates were 29% for T-AC alone, 59% with the addition of carboplatin, and 53% with the addition of veliparib with carboplatin8.11. We found that in multivariable analysis, proliferation and immune signatures were independently associated with pCR but that carboplatin benefit was not significantly different in basal-like vs. non-basal subgroups. Exploratory gene expression immune analyses suggested that tumors with higher inferred CD8+ T-cell infiltration may receive greater benefit with the addition of carboplatin11.Recently, we published correlative genomic analysis of gene expression for 482 of 634 patients enrolled in BrighTNessBRCA mutated TNBC in the BrighTNess trial may benefit differentially from the addition of carboplatin or veliparib to NAC and may have distinct immune gene expression profiles. To evaluate this, we analyzed the association of pCR rate with treatment arm in a matched cohort study of patients with germline BRCA1/2 (gBRCA) mutations compared to non-gBRCA controls. Using RNA sequencing of pre-treatment biopsies from the BrighTNess trial, we compared molecular subtype (PAM50 and TNBCtype), a measure of tumor proliferation (PAM50 proliferation score), a measure of chromosomal instability (CIN70), and measures of infiltrating immune cells (GeparSixto immune activation signature and relative immune cell abundance by TIMER) between gBRCA and non-gBRCA patients. Then, we determined if any of these measures were associated with pCR, which would indicate a subset of patients that would potentially benefit from the addition of carboplatin or veliparib.Based on these data, we hypothesized that patients with BRCA1/2 mutated (gBRCA) cases and 150 non-gBRCA matched controls. BRCA cases and controls did not differ significantly by intentionally matched characteristics , nor by doxorubicin and cyclophosphamide (AC) administration schedule, Eastern Cooperative Oncology Group performance status, PAM50 subtype, TNBCtype, or rate of pCR , but there was no significant interaction between the scores and BRCA status  association with BRCA cases: WNT/Beta-catenin signaling , two neutrophil gene sets (IRIS), and two memory B-cell gene sets (IRIS)  using Hallmark and Immune Response In Silico (IRIS)13. This had led to uneven uptake of carboplatin in clinical practice. Among patients with germline BRCA mutations and metastatic breast cancer, the TNT, OlymiAD, and Brocade3 trials showed improved response rate and progression-free survival with the addition of carboplatin and/or PARP inhibitors14. This led to the hypothesis that patients with a germline BRCA mutation may specifically benefit from the addition of platinum chemotherapy and/or a PARP inhibitor to NAC. However, in the neoadjuvant setting, despite small studies suggesting a benefit of platinum chemotherapy in patients with BRCA mutations16, GeparSixto and INFORM showed no clear benefit with the addition of carboplatin or cisplatin, respectively18, reinforcing the need for greater understanding of the different results of metastatic trials versus neoadjuvant trials.The role of carboplatin in NAC regimens for TNBC remains debated. While there is a clear increase in pCR rates with the addition of carboplatin to standard anthracycline-taxane chemotherapy, the long-term benefit of the addition of platinum is less clearBRCA mutations benefit from the addition of carboplatin and/or PARP inhibitor; and 2) whether tumors with germline BRCA mutations have distinct proliferation, immune, and genomic instability gene expression signatures. This study builds on our initial analyses of RNAseq in this cohort that demonstrated carboplatin benefit was not significantly different in basal-like vs. non-basal subgroups but tumors with higher inferred CD8+ T-cell infiltration may receive greater benefit with addition of carboplatin in exploratory gene expression immune analyses11.In this study, we present a large cohort of gBRCA patients compared with well-matched non-gBRCA controls, all of whom received uniform therapy as part of a randomized clinical trial consisting of standard NAC alone or with the addition of carboplatin with or without veliparib. This provides an opportunity to investigate the key questions of 1) whether matched patients with germline BRCA mutations. We await event-free survival data from the BrighTNess study as well as phase III neoadjuvant trials in early-stage TNBC of NRG-BR003 (NCT024889967) comparing AC-T vs AC-TC as well as NSABP B-56 comparing VCT-AC to TC-AC and T-AC (NCT02032277). However, this cohort establishes that germline BRCA mutation carriers with TNBC do not receive further pCR benefit from the addition of carboplatin with or without veliparib to NAC. Intriguingly, the presence of a gBRCA mutation did not predict an increase in the pCR rate with the addition of either carboplatin or carboplatin and veliparib to neoadjuvant T-AC chemotherapy; in fact, it was in non-gBRCA patients that the addition of carboplatin with or without veliparib significantly increased the pCR rate. We hypothesize that with homologous recombination deficiency, the gBRCA tumors may be already intrinsically highly sensitive to standard anthracycline-taxane chemotherapy, offering less potential benefit with additional therapy. It should be noted that the data in this study do not have implications for the use of adjuvant PARP inhibitors for gBRCA carriers, related to the recently-published OlympiA study19.We found no significant difference in pCR between gBRCA and non-gBRCA patients among treatment arms in BrighTNess. This analysis does not include long-term follow up data and, notably, also does not include somatic BRCA1 and 2 tumors tend to be BL1 and BL2 TNBCtypes, BRCA1 tumors tend to be basal-like PAM50 subtype with high tumor inflammation signatures and many tumor-infiltrating immune cells, and BRCA2 tumors tend to be luminal A/B PAM50 subtype25.The fact that the gBRCA and non-gBRCA cohorts were so well balanced allows for straightforward comparison of pCR in the two groups. However, it is surprising that the gBRCA and non-gBRCA cohorts in this study are so well matched by PAM50 subtype, TNBC subtype, PAM50 proliferation score, GeparSixto score, and proportions of subsets of tumor-infiltrating immune cells. Previous reports have shown that both 29, but inconsistent with the translational analysis of I-SPY2 which found that CIN70 did not predict response to veliparib with carboplatin30. The strong association found between CIN70 and proliferation reflects that the CIN70 score contains genes associated with proliferation and is consistent with CIN70 correlation with tumor grade31.In the cohort of both gBRCA and non-gBRCA patients, higher PAM50 proliferation score, CIN70 score, and GeparSixto immune signature were associated with higher odds of pCR, which is consistent with previous reports of association of pCR with high proliferation and immune signatures in breast cancer32 or plus carboplatin33 further enhance pCR rates. As of yet, no subset analyses of germline BRCA patients from these studies have been reported. As we seek to personalize therapy for breast cancer patients, further research is warranted into the complex interplay between germline BRCA mutation, platinum chemotherapy or PARP inhibitors, and the immune microenvironment and immunotherapy.Recently, two studies demonstrate that the addition of immunotherapy to T-AC NAC alone34. Veliparib is established to have relatively less PARP trapping relative to other PARP inhibitors, which my facilitate combination with chemotherapy yet also limits our ability to extrapolate to other PARP inhibitors. Finally, recent FDA approval of immunotherapy as part of neoadjuvant therapy for TNBCs in the US reinforces the importance of validation studies in immunotherapy-containing cohorts.This study does have limitations. This is an exploratory secondary analysis of clinical and genomic data from a phase III clinical trial and the power of the analysis may be limited by the small sample size. As these were not prespecified analyses, we pursued a matched cohort study design, which overcomes limitations of gBRCA vs. non-gBRCA studies where receptor subtype are frequently mixed and treatment heterogeneous, and attempted to control for covariates in multivariable analyses. Additionally, DNA metrics of HRD have not yet been fully analyzed , although preliminary analyses of Myriad HRD assay was not associated with differential benefit to addition of carboplatin alone or with veliparibBRCA carriers.In conclusion, in the overall cohort of both gBRCA and non-gBRCA patients, higher proliferation score, CIN70 score, and GeparSixto immune signature were associated with higher pCR rate and may be more useful biomarkers of patients who will benefit from the addition of carboplatin to neoadjuvant AC-T chemotherapy. The addition of carboplatin or carboplatin and veliparib to neoadjuvant T-AC chemotherapy was associated with increased pCR rate in non-gBRCA patients but not g2 IV weekly for 12 doses plus carboplatin AUC 6 IV every 3 weeks for four cycles plus veliparib 50 mg orally twice daily for 12 weeks); Arm B: TC (paclitaxel plus carboplatin plus veliparib placebo); or Arm C: T (paclitaxel plus carboplatin placebo plus veliparib placebo). Then all patients received AC every 2–3 weeks for four cycles, with the schedule selected by the treating physician. We matched non-gBRCA patients 2:1 (N = 150:75) to gBRCA cases by treatment arm, lymph node stage, and 10-year age range to balance the groups and reduce confounding. This cohort represents 225 of the previously assessed 482 patients11. The present analysis was not a preplanned analysis. Clinical data were locked as of January 1, 2018.The BrighTNess trial  enrolled 634 patients with stage II/III TNBC and was performed in accordance with The Code of Ethics of the World Medical Association (Declaration of Helsinki). Informed consent was obtained for all human subjects. Patients were randomized 2:1:1 to Arm A: TCV  and was conducted according to the protocol approved by institutional review boards at investigational sites. The full protocol is available as a Supplemental file. Informed consent was obtained for all human subjects. This matched cohort study was approved by the Dana-Farber Cancer Institute Institutional Review Board.11, total RNA was extracted and underwent whole transcriptome RNA sequencing (RNAseq) on an Illumina HiSeq 3000 with single end 50 bp reads using RiboZero Gold rRNA depletion at the Washington University McDonnell Genome Institute. Samples with >10 million unique reads were included for further analyses as Reads per Kilobase per Million Reads (RPKM). RNA-seq reads were aligned to the Ensembl release 76 top-level assembly with STAR version 2.0.4b. Gene counts were derived from the number of uniquely aligned unambiguous reads by Subread:featureCount version 1.4.5. Transcript counts were produced by Sailfish version 0.6.3. All gene-level and transcript counts were then imported into the R/Bioconductor package EdgeR and TMM normalization size factors were calculated to adjust samples for differences in library size, resulting in RPKM which were used in downstream analyses. Genes or transcripts not expressed in any sample or less than one count-per-million in the minimum group size minus one were excluded from further analysis.A pre-treatment biopsy was collected in RNAlater. As detailed previously35 after balancing TNBC data with an equal number of estrogen receptor-positive cases from The Cancer Genome Atlas36. TNBCtype was determined with the TNBCtype tool after normalization to fixed upper quantile37. PAM50 ‘proliferation signature’ was derived from the ‘Bioclassifier’ package35. The GeparSixto immune signature of genes associated with tumor-infiltrating lymphocytes in GeparSixto38 and CIN70 signature of chromosomal instability31 were calculated as described previously. Proportions of infiltrating immune cell subsets were calculated using the TIMER algorithm39. Single sample Gene Set Enrichment Analysis (ssGSEA)40 was performed using Hallmark and Immune Response In Silico (IRIS)12/ImmuneSigDB41 gene sets.PAM50 subtype was determined with the ‘Bioclassifier’ package8. Chi-square tests were used to compare cohort characteristics. Student’s t-tests were used to compare the mean of continuous variables where the assumption of equal variances was met. For variables that did not meet this assumption, Welch’s t-tests were used. Logistic regression was performed to compare pCR with PAM50 subtype, proliferation score, GeparSixto score, CIN70 score, treatment arm, BRCA status, and interactions. T-tests were used to compare ssGSEA gene set scores, with multiple test correction using the method of Benjamini-Hochberg. Statistical analyses were performed with SAS version 9.4. Figures were generated with R version 3.5.1.pCR was determined by site pathologists following completion of neoadjuvant therapy, and was defined as absence of cancer cells in the breast and lymph nodesFurther information on research design is available in the Supplementary InformationReporting Summary