Search

Background High Neutrophil-to-Lymphocyte Ratio (NLR), Monocyte-to-Lymphocyte Ratio (MLR), Platelet-to-Lymphocyte Ratio (PLR) were associated with worse prognosis of sepsis patients, but the relationship between NLR, MLR, PLR and mortality in sepsis patients with coronary artery disease (CAD) remains unclear. The purpose of this study was to explore the association between NLR, MLR, PLR and 28-day mortality in sepsis patients with CAD, and to evaluate diagnostic accuracy combining sequential organ failure assessment (SOFA) scores.Methods Our study was based on cross-sectional and 28-day in-hospital data obtained from the MIMIC-III database between 2008 and 2012. Clinical characteristics and laboratory test data has been collected from hospitalization record. The relationship between NLR, MLR, PLR and 28-day mortality in sepsis patients with CAD was examined using the Cox proportional hazards model. We applied Receiver operating characteristic (ROC) analysis for predicting 28-day mortality in sepsis patients with CAD by combining NLR, MLR and PLR with the sequential organ failure assessment SOFA scores.Results This study included 984 sepsis patients with CAD in total. Sepsis patients with CAD who had high NLR, MLR, and PLR had a higher risk of 28-day mortality. (All P Conclusion High NLR, MLR and PLR were associated with 28-day mortality in sepsis patients with CAD.

Background Passive immunotherapies to augment the humoral immunity against virus have been associated with prevention of severe illnesses and reduction of mortality of patients with coronavirus disease 2019 (COVID-19). However, less is known about the comparative effectiveness of different types of passive immunotherapies. The aim of this study is to compare efficacy and safety of passive immunotherapy in patients with COVID-19. Methods This is a two-part network meta-analysis which evaluate the efficacy of passive immunotherapy in outpatients and hospitalized patients separately. Electronic databases, including PubMed, EMBASE, and Cochrane CENTRAL were systematically searched for articles published before 26th April 2022. Randomized clinical trials that compared COVID-19 specific antiviral antibodies, convalescence plasma and hyperimmune anti-COVID-19 Intravenous Immunoglobulin with placebo, or control plasma, or standard of care in patients with COVID-19 were included. Two authors screened the studies independently. We extracted data and assessed the risk of bias of studies using the revised Cochrane risk of bias tool (RoB 2 tool) at study level. The primary outcome for outpatients is hospitalization within 30 days from randomization and are mortality, need of invasive mechanical ventilation, and severe advent events for hospitalized patients. Results In this systematic review and network meta-analysis, data were pooled from 41 eligible randomized control trials involving 42298 participants. In the first part of network meta-analysis which is consist of 9 eligible trials with 10093 participants, compared with control, specific antiviral antibodies (odds ratio [OR]: 0.22, 95% CI: 0.16, 0.28) rather than CP (OR: 0.75, 95%CI: 0.56, 1.01) reduced the risk of hospitalization; treatment with antibody reduced a greater risk of hospitalization (OR: 0.29, 95%CI: 0.19, 0.43) when compared with CP. For the analysis of secondary outcome in outpatients, antibody (OR: 0.10, 95%CI: 0.01, 0.37) rather than CP (OR: 0.81, 95%CI: 0.23, 2.78) reduced the risk of mortality. In the second party of meta-analysis, none of the passive immunotherapy was associated with the reduction of mortality, need of invasive mechanical ventilation and severe adverse events. Furthermore, none of passive immunotherapy was associated with improvement in 6 secondary outcomes. However, in subgroup analysis, the administration of antibody was associated with improvement of mortality, need of invasive mechanical ventilation, rate of discharge, duration of hospital stay, time to death and with less adverse events. Conclusions In this network meta-analysis of clinical trials of patients with COVID-19, we found that treatment with antiviral antibodies reduced the risk of hospitalization in outpatients. Among hospitalized adult patients, all three passive immunotherapies compared with control did not result in a statistically significant improvement of the primary outcomes, but use of neutralizing antibodies may lead to improvement of primary outcomes and key secondary outcomes in seronegative patients. Further development of broader-spectrum antibodies targeting to highly conserved domain of spike protein which avoids immune escape of new variants are needed.

As the flash-based solid-state drives(SSDs) gradually replace the mechanical hard disk drives(HDDs) as the mainstream storage, unlike the HDDs, SSDs have rich internal parallelism, which makes it have the excellent characteristics that HDDs do not have. External mergesort, as the classical algorithm of external sorting adopted in many systems and algorithms, has an important impact on the overall performance. Therefore, it is of great significance to optimize and improve the efficiency of external mergesort algorithm. The research work on optimizing raw external mergesort algorithm on SSDs is relatively few. Thus, aiming at the external mergesort problem, based on the characteristics of SSDs, this paper proposes the SortDecision algorithm which can calculate its optimal execution scheme, including merging way, read buffer size, and write buffer size which determine the execution process of external mergesort. Exploiting the above optimal execution scheme, external mergesort can obtain better efficiency. In the SortDecision algorithm, external mergesort problem on SSDs is formalized and transformed into a piecewise convex optimization problem. Then, the optimal external mergesort scheme is obtained by enumerating the solutions of each subconvex problem. The experimental results show that the external mergesort proceeds guided by SortDecision algorithm can achieve a speedup of 1 $\sim $ 6.7 compared to the traditional external mergesort algorithm in the case of limited memory provided. The richer the internal parallelism resources inside SSDs, the better the effect of SortDecision’s acceleration.

Background Cytomegalovirus (CMV) has high seroprevalence, and its active infection is associated with several adverse prognoses in adult patients with acute respiratory distress syndrome (ARDS). However, the role of active CMV infection in ARDS-associated fibroproliferation is unknown. This study aimed at determining the association between active CMV infection and lung fibroproliferation in adult patients with ARDS. Methods We retrospectively reviewed the medical records of all adult patients with ARDS who were admitted to the intensive care unit (ICU) from January 2018 to December 2020 at a national university-affiliated hospital in China. Study subjects were divided into active and non-active CMV infection groups based on CMV DNAemia within a 28-day ICU hospitalization. Lung fibroproliferation was measured using chest high-resolution computed tomography (HRCT) and N-terminal peptide of serum procollagen III (NT-PCP-III) within the first 28 days of ICU admission. Pulmonary fibrosis, clinical features, laboratory findings, treatment measures, and clinical outcomes were compared between the two groups. Results Among the 87 ARDS patients included in this study, the incidence of active CMV infection was 16.1% within the 28-day ICU admission period. In logistic regression analyze, active CMV infection was found to be associated with higher pulmonary fibrogenesis, pulmonary fibrosis score, and NT-PCP-III level (P P Conclusions Among adult patients with ARDS, active CMV infection was related to poor clinical outcomes. Active CMV infection was associated with ARDS-associated fibroproliferation. Prophylactic and preemptive use of anti-CMV agents on pulmonary fibrosis should be assessed to determine a consensus therapeutic strategy.

Recently there is an increasing need for interactive human-driven analysis on large volumes of data. Online aggregation (OLA), which provides a quick sketch of massive data before a long wait of the final accurate query result, has drawn significant research attention. However, the direct processing of OLA on duplicate data will lead to incorrect query answers, since sampling from duplicate records leads to an over representation of the duplicate data in the sample. This violates the prerequisite of uniform distributions in most statistical theories. In this paper, we propose CrowdOLA, a novel framework for integrating online aggregation processing with deduplication. Instead of cleaning the whole dataset, CrowdOLA retrieves block-level samples continuously from the dataset, and employs a crowd-based entity resolution approach to detect duplicates in the sample in a pay-as-you-go fashion. After cleaning the sample, an unbiased estimator is provided to address the error bias that is introduced by the duplication. We evaluate CrowdOLA on both real-world and synthetic workloads. Experimental results show that CrowdOLA provides a good balance between efficiency and accuracy.

Many developing countries are suffering from air pollution, especially the Particulate Matter with diameter of 2.5 micrometers or less (PM2.5). While quite a few air quality monitoring stations have been built by governments in a city's public areas, the indoor PM2.5 has not yet been monitored and dealt with effectively. Though many office buildings have an HVAC (heating, ventilation, and air conditioning) system, PM2.5 is not considered as a factor when the system circulates fresh air from outdoors. This paper introduces a real system that we have deployed in the offices of four Microsoft campuses in China. This system instantly monitors indoor air quality on different floors of a building (including office areas, gyms, garages, and restaurants), enabling Microsoft employees to enquire the air quality of a place by using a mobile phone or checking a website. The information can guide a user's decision making, e.g., finding the right time to work out in the gym or turn on individual air filters in her own office. Through analyzing the indoor and outdoor air quality data collected over a long period, our system can even offer actionable and energy-efficient suggestion to HVAC systems, e.g., automatically turning on the system only a few hours earlier than usual if it is a heavily polluted day, or identifying the filters in HVAC system that should be renewed.