Development of a breast cancer prognostic model based on vesicle-mediated transport-related genes to predict immune landscape and clinical drug therapy.

BACKGROUND: Vesicle-mediated transport, vital for substance exchange and intercellular communication, is linked to tumor initiation and progression. This work was designed to study the role of vesicle-mediated transport-related genes (VMTRGs) in breast cancer (BC)prognosis. METHODS: Univariate Cox analysis was utilized to screen prognosis-related VMTRGs. BC samples underwent unsupervised clustering based on VMTRGs to analyze survival, clinical factors, and immune cell abundance across different subtypes. We constructed a risk model using univariate Cox and LASSO regression analysis, with validation conducted using GEO datasets. Subsequently, we performed tumor mutational burden analysis, and immune landscape analysis on both groups. Ultimately, we conducted immunophenoscore (IPS) scoring to forecast immunotherapy and performed drug sensitivity analysis. RESULTS: We identified 102 VMTRGs associated with BC prognosis. Using these 102 VMTRGs, BC patients were classified into 3 subtypes, with Cluster3 patients showing significantly better survival rates. We constructed a prognostic model for BC based on 12 VMTRGs that effectively predicted patient survival. Riskscore was an independent prognostic factor for BC patients. According to median risk score, high-risk group (HRG) had higher TMB values. The immune landscape of the HRG exhibited characteristics of cold tumor, with higher immune checkpoint expression levels and lower IPS scores, whereas Gemcitabine, Nilotinib, and Oxaliplatin were more suitable for treating low-risk group. CONCLUSION: We classified BC subtypes and built a prognostic model based on VMTRGs. The genes in the prognostic model may serve as potential targets for BC therapy.

The impact of nursing interventions on the rehabilitation outcome of patients after lumbar spine surgery.

BACKGROUND: This study aimed to investigate the impact of nursing interventions on the rehabilitation outcomes of patients after lumbar spine surgery and to provide effective references for future postoperative care for patients undergoing lumbar spine surgery. METHODS: The study included two groups: a control group receiving routine care and an observation group receiving additional comprehensive nursing care. The comprehensive care encompassed postoperative rehabilitation, pain, psychological, dietary management, and discharge planning. The Visual Analogue Scale (VAS), Oswestry Disability Index (ODI), Short-Form 36 (SF-36) Health Survey, self-rating depression scale (SDS) and self-rating anxiety scale(SAS) were used to assess physiological and psychological recovery. Blood albumin, haemoglobin, neutrophil counts, white blood cell counts, red blood cell counts, inflammatory markers (IL-6, IL-10, and IFN-γ) were measured, and the incidence of postoperative adverse reactions was also recorded. RESULTS: Patients in the observation group exhibited significantly improved VAS, ODI, SF-36, SDS and SAS scores assessments post-intervention compared to the control group (P < 0.05). Moreover, levels of IL-6, IL-10, and IFN-γ were more favorable in the observation group post-intervention (P < 0.05), indicating a reduction in inflammatory response. There was no significant difference in the incidence of postoperative adverse reactions between the groups (P > 0.05), suggesting that the comprehensive nursing interventions did not increase the risk of adverse effects. CONCLUSION: Comprehensive nursing interventions have a significant impact on the postoperative recovery outcomes of patients with LSS, alleviating pain, reducing inflammation levels, and improving the overall quality of patient recovery without increasing the patient burden. Therefore, in clinical practice, it is important to focus on comprehensive nursing interventions for patients with LSS to improve their recovery outcomes and quality of life.

Dysregulated ceRNA network modulated by copy number variation-driven lncRNAs in breast cancer: A comprehensive analysis.

Breast cancer is a malignancy harmful to physical and mental health in women, with quite high mortality. Copy number variations (CNVs) are vital factors affecting the progression of breast cancer. Detecting CNVs in breast cancer to predict the prognosis of patients has become a promising approach to accurate treatment in recent years. The differential analysis was performed on CNVs of long noncoding RNAs (lncRNAs) as well as the expression of lncRNAs, microRNAs (miRNAs) and mRNAs in normal tissue and breast tumor tissue based on The Cancer Genome Atlas (TCGA) database. The CNV-driven lncRNAs were identified by the Kruskal-Wallis test. Meanwhile, a competitive endogenous RNA (ceRNA) network regulated by CNV-driven lncRNA was constructed. As the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed, the mRNAs in the dysregulated ceRNA network were mainly enriched in the biological functions and signaling pathways, including the Focal Adhesion-PI3K-Akt-mTOR-signaling pathway, the neuronal system, metapathway biotransformation Phase I and II and blood circulation, etc. The relationship between the CNVs of five lncRNAs and their gene expression in the ceRNA network was analyzed via a chi-square test, which confirmed that except for LINC00243, the expression of four lncRNAs was notably correlated with the CNVs. The survival analysis revealed that only the copy number gain of LINC00536 was evidently related to the poor prognosis of patients. The CIBERSORT algorithm showed that five lncRNAs were correlated with the abundance of immune cell infiltration and immune checkpoints. In a word, by analyzing CNV-driven lncRNAs and the ceRNA network regulated by these lncRNAs, this study explored the mechanism of breast cancer and provided novel insights into new biomarkers.

Construction and validation of a predictive model for postoperative urinary retention after lumbar interbody fusion surgery.

BACKGROUND: Postoperative urine retention (POUR) after lumbar interbody fusion surgery may lead to recatheterization and prolonged hospitalization. In this study, a predictive model was constructed and validated. The objective was to provide a nomogram for estimating the risk of POUR and then reducing the incidence. METHODS: A total of 423 cases of lumbar fusion surgery were included; 65 of these cases developed POUR, an incidence of 15.4%. The dataset is divided into a training set and a validation set according to time. 18 candidate variables were selected. The candidate variables were screened through LASSO regression. The stepwise regression and random forest analysis were then conducted to construct the predictive model and draw a nomogram. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve and the calibration curve were used to evaluate the predictive effect of the model. RESULTS: The best lambda value in LASSO was 0.025082; according to this, five significant variables were screened, including age, smoking history, surgical method, operative time, and visual analog scale (VAS) score of postoperative low back pain. A predictive model containing four variables was constructed by stepwise regression. The variables included age (ß = 0.047, OR = 1.048), smoking history (ß = 1.950, OR = 7.031), operative time (ß = 0.022, OR = 1.022), and postoperative VAS score of low back pain (ß = 2.554, OR = 12.858). A nomogram was drawn based on the results. The AUC of the ROC curve of the training set was 0.891, the validation set was 0.854 in the stepwise regression model. The calibration curves of the training set and validation set are in good agreement with the actual curves, showing that the stepwise regression model has good prediction ability. The AUC of the training set was 0.996, and that of the verification set was 0.856 in the random forest model. CONCLUSION: This study developed and internally validated a new nomogram and a random forest model for predicting the risk of POUR after lumbar interbody fusion surgery. Both of the nomogram and the random forest model have high accuracy in this study.

Uptake, Accumulation, and translocation of azoxystrobin by Vegetable plants in soils: influence of soil characteristics and plant species.

Although azoxystrobin has been widely applied on various crops, little is known about the bioavailability of azoxystrobin in the soil-vegetable system. In this study, the uptake, accumulation and translocation of azoxystrobin as affected by soil characteristics and plant species were respectively investigated. The accumulation amount of azoxystrobin in pakchoi increased as soil adsorption decreased and was positively associated with its concentration in pore water (Cpw), which was mainly affected by soil organic matter content. Therefore, Cpw could be a candidate for the estimation of azoxystrobin accumulation in pakchoi. In all the tested vegetables, azoxystrobin was mainly accumulated in roots, and its upward translocation was limited. Root lipid content was a major factor affecting the uptake and translocation of azoxystrobin in different vegetables.

Maximum likelihood-based extended Kalman filter for COVID-19 prediction.

Prediction of COVID-19 spread plays a significant role in the epidemiology study and government battles against the epidemic. However, the existing studies on COVID-19 prediction are dominated by constant model parameters, unable to reflect the actual situation of COVID-19 spread. This paper presents a new method for dynamic prediction of COVID-19 spread by considering time-dependent model parameters. This method discretises the susceptible-exposed-infected-recovered-dead (SEIRD) epidemiological model in time domain to construct the nonlinear state-space equation for dynamic estimation of COVID-19 spread. A maximum likelihood estimation theory is established to online estimate time-dependent model parameters. Subsequently, an extended Kalman filter is developed to estimate dynamic COVID-19 spread based on the online estimated model parameters. The proposed method is applied to simulate and analyse the COVID-19 pandemics in China and the United States based on daily reported cases, demonstrating its efficacy in modelling and prediction of COVID-19 spread.

Application of a rehabilitation management strategy based on symptom management theory in postoperative functional exercises in patients with lower extremity arteriosclerosis obliterans.

BACKGROUND: Lower extremity arteriosclerosis obliterans (ASO) is the most common occlusive disease of the peripheral blood vessels. OBJECTIVE: To explore the application effect of symptom management-based rehabilitation strategy in postoperative functional exercises in patients with lower extremity ASO. METHODS: The researchers selected 136 patients that underwent lower extremity ASO surgery for the first time in their department from January to September 2020. Patients were divided into a control group (n= 68) and an experimental group (n= 68). The control group implemented routine discharge rehabilitation education and continuous nursing. On this basis, the experimental group applied the symptom management theory to the rehabilitation management strategy to compare the degree of pain, the ankle-brachial index, self-care ability and quality of life between the two groups before and after the intervention. RESULTS: Three months (P= 0.045) and six months (P=0.013) after discharge, the experimental group's degree of pain was significantly lower than that of the control group. At one month (P= 0.019), three months (P= 0.003) and six months (P= 0.000) after discharge, the experimental group recovered significantly better than the control group. At six months after discharge, the self-care ability, mood status and physical pain of the experimental group were significantly higher than in the control group (P< 0.05). CONCLUSION: The rehabilitation management strategy, which is based on symptom management theory, can effectively improve the symptoms, quality of life and self-efficacy of ASO patients in continuous care. This nursing strategy is worthy of clinical promotion.

The impact of the doctor-nurse-patient workshop transitional care model on the post-operative quality of life of patients with laryngeal cancer.

OBJECTIVE: The aim of this study is to assess the efficacy of the doctor-nurse-patient workshop transitional care model on post-operative care for patients with laryngeal cancer and its influence on quality of life. METHODS: A total of 68 patients with laryngeal cancer who underwent surgical treatment at the hospital between 2021 and 2022 were included in the study. The patients were divided into two groups, a control group and a research group, each consisting of 34 patients, based on the chronological sequence of their surgeries. Patients in the control group received standard nursing care, while those in the research group received the doctor-nurse-patient workshop transitional care model in addition to standard nursing care. After 2 months of care, levels of albumin (ALB), total protein (TP), hemoglobin (Hb), and quality of life scores (measured using the Quality of Life Instrument for Head and Neck Cancer, QLICP-HN) were compared between the two groups. Additionally, the incidence of adverse events during the recovery period was assessed and compared between the two groups. RESULTS: Following 2 months of care, patients in the research group exhibited elevated ALB, TP, and Hb levels compared to those in the control group. Additionally, the average QLICP-HN scores were higher in the research group, while the incidence of adverse events was lower compared to the control group. CONCLUSION: Implementing the doctor-nurse-patient workshop transitional care model in home care for patients with laryngeal cancer can enhance their nutritional status post-surgery and improve their quality of life during home rehabilitation. This, in turn, leads to a reduction in the incidence of adverse events and complications during the recovery period.

The association between the composite dietary antioxidant index and thyroid functionality among adults in the USA: NHANES 2007-2012.

Objective: Composite Dietary Antioxidant Index (CDAI) values serve as a summary of an individual's combined dietary antioxidant intake. Although specific antioxidants are known to reduce thyroid damage from oxidative stress, the relationship between the CDAI and thyroid function remains uncertain. The purpose of this study was thus to investigate this relationship in greater detail while focusing on a representative American adult population. Methods: A total of 6,860 subjects from the 2007-2012 NHANES cohort were included in this study. Associations between CDAI values and thyroid function were evaluated with weighted linear regression models and smoothed curve fitting. Subgroup analyses were also performed. Results: The weighted mean (SD) values for variables analyzed in this study included a CDAI of 0.13 (0.06), serum free T4 (FT4) levels of 0.80 (0.01) ng/dL, and serum total T4 (TT4) levels of 7.80 (0.03) ug/dL. Lower CDAI values were found to be associated with higher levels of FT4 and TT4 using both unadjusted and adjusted models that accounted for relevant confounders (adjusted model, FT4 ß = -0.003, p = 0.005; TT4 ß = -0.035, p < 0.001). This negative correlation persisted when CDAI was categorized into quartiles (FT4, p for trend = 0.014; TT4, p for trend = 0.003). Conclusion: These findings suggest that a diet rich in antioxidants, as reflected by higher CDAI scores, is associated with significant decreases in levels of free and total T4. Further analyses will be necessary to better clarify the underlying mechanisms behind these observations.

Recent advances in CAR-T therapy for the treatment of acute myeloid leukemia.

Chimeric antigen receptor T-cell (CAR-T) therapy, which has demonstrated notable efficacy against B-cell malignancies and is approved by the US Food and Drug Administration for clinical use in this context, represents a significant milestone in cancer immunotherapy. However, the efficacy of CAR-T therapy for the treatment of acute myeloid leukemia (AML) is poor. The challenges associated with the application of CAR-T therapy for the clinical treatment of AML include, but are not limited to, nonspecific distribution of AML therapeutic targets, difficulties in the production of CAR-T cells, AML blast cell heterogeneity, the immunosuppressive microenvironment in AML, and treatment-related adverse events. In this review, we summarize the recent findings regarding various therapeutic targets for AML (CD33, CD123, CLL1, CD7, etc.) and the results of the latest clinical studies on these targets. Thereafter, we also discuss the challenges related to CAR-T therapy for AML and some promising strategies for overcoming these challenges, including novel approaches such as gene editing and advances in CAR design.

Recent advances in CAR-T therapy for acute myeloid leukemia Acute myeloid leukemia (AML) remains a clinical challenge despite the advent of chimeric receptor T-cell (CAR-T) therapy, as there are obstacles hindering the application of CAR-T cells in AML. In this review, we discuss the results of current relevant clinical trials, existing treatment strategies for AML and recent advances in preclinical research to provide insight for overcoming the inefficacy of CAR-T therapy for AML.

Urban health advantage and penalty in aging populations: a comparative study across major megacities in China.

Background: Urban living is linked to better health outcomes due to a combination of enhanced access to healthcare, transportation, and human development opportunities. However, spatial inequalities lead to disparities, resulting in urban health advantages and penalties. Understanding the relationship between health and urban development is needed to generate empirical evidence in promoting healthy aging populations. This study provides a comparative analysis using epidemiological evidence across diverse major Chinese cities, examining how their unique urban development trajectories over time have impacted the health of their aging residents. Methods: We tracked changes in air pollution (NO2, PM2.5, O3), green space (measured by NDVI), road infrastructure (ring road areas), and nighttime lighting over 20 years in six major cities in China. We followed a longitudinal cohort of 4992 elderly participants (average age 87.8 years) over 16,824 person-years. We employed Cox proportional hazard regression to assess longevity, assessing 14 variables, including age, sex, ethnicity, marital status, residence, household income, occupation, education, smoking, alcohol consumption, exercise, and points of interest (POI) count of medicine-related facilities, sports, and leisure service-related places, and scenic spots within a 5 km-radius buffer. Findings: Geographic proximity to points of interest significantly improves survival. Elderly living in proximity of the POI-rich areas had a 34.6%-35.6% lower mortality risk compared to those in POI-poor areas, for the highest compared to the lowest quartile. However, POI-rich areas had higher air pollution levels, including PM2.5 and NO2, which was associated with a 21% and 10% increase in mortality risk for increase of 10 µg/m3, respectively. The benefits of urban living had higher effect estimates in monocentric cities, with clearly defined central areas, compared to polycentric layouts, with multiple satellite city centers. Interpretation: Spatial inequalities create urban health advantages for some and penalties for others. Proximity to public facilities and economic activities is associated with health benefits, and may counterbalance the negative health impacts of lower green space and higher air pollution. Our empirical evidence show optimal health gains for age-friendly urban environments come from a balance of infrastructure, points of interest, green spaces, and low air pollution. Funding: Natural Science Foundation of Beijing (IS23105), National Natural Science Foundation of China (82250610230, 72061137004), World Health Organization (2024/1463606-0), Research Fund Vanke School of Public Health Tsinghua University (2024JC002), Beijing TaiKang YiCai Public Welfare Foundation, National Key R&D Program of China (2018YFC2000400).

The Relationship between Nutritional Status and Thyroid Function among Adults in the USA: NHANES 2007-2012.

Controlled Nutritional Status (CONUT) scores have been developed as quantitative tools that can be employed to gauge the nutritional status of individual patients. However, there has been very little research investigating the association between these CONUT scores and the function of the thyroid. As such, the present study was designed to address this research gap through the evaluation of a representative cohort of American adults. National Health and Nutrition Examination Survey (NHANES) data were herein used to separate subjects into those with normal nutritional status (CONUT score: 0-1) from those who were malnourished (CONUT scores > 1). Associations between these CONUT scores and the function of the thyroid were investigated through linear regression modeling, employing weighted analytical strategies and subgroup analyses. Overall, 8,082 individuals from the NHANES 2007-2012 cohort were enrolled in this analysis. These individuals exhibited a weighted mean CONUT score of 0.72 (0.02). 6661 (weighted proportion: 83.12%) in the normal nutritional status group and 1421 (16.88%) in the malnourished group. In adjusted analyses, subjects who were malnourished were found to present with an increase in FT4 levels (ß = 0.033; p < 0.001 together with reduced TT3 levels (ß = -3.526; p = 0.01). The present data offer evidence in support of higher CONUT scores, which correspond to malnutrition, being related to increases in FT4 levels together with reductions in TT3 levels. More studies will be crucial to further probe the mechanistic drivers of these results.

The key to improving the beauty of the giant retaining wall in valleys: Increasing visual extension.

The retaining wall is a passive engineering measure to prevent and control unsafe factors caused by rock collapse in the valleys. Existing studies have mainly focused on its functional robustness and safety features, with few exploring its visual quality in the landscape. A multiple regression analysis was applied to evaluate the Scenic Beauty Estimation (SBE) of the giant retaining wall in Jiuzhaigou's (a world natural heritage site) Heye Village, then the factors affecting SBE were analyzed. It is found that enhancing the sense of perspective and spatial hierarchy of retaining-wall murals in narrow roads contributes to the extension of observers' sight, which is the key to improving SBE. Furthermore, the showcase of folk culture in murals can realize the beautification function of the giant retaining walls. In addition, the SBE of giant retaining walls is also linked to coordination, where the walls embellished with the natural landscape and folk culture murals have better SBE performance than those with local stones. This study provides a reference for constructing scenic beauty after fulfilling the safety function of retaining wall engineering.

Maximum likelihood-based extended Kalman filter for soft tissue modelling.

Realistic modelling of human soft tissue is very important in medical applications. This paper proposes a novel method by dynamically incorporating soft tissue characterisation in the process of soft tissue modelling to increase the modelling fidelity. This method defines nonlinear tissue deformation with unknown mechanical properties as a problem of nonlinear filtering identification to dynamically identify mechanical properties and further estimate nonlinear deformation behaviour of soft tissue. It combines maximum likelihood theory, nonlinear filtering and nonlinear finite element method (NFEM) for modelling of nonlinear tissue deformation behaviour based on dynamic identification of homogeneous tissue properties. On the basis of hyperelasticity, a nonlinear state-space equation is established by discretizing tissue deformation through NFEM for dynamic filtering. A maximum likelihood algorithm is also established to dynamically identify tissue mechanical properties during the deformation process. Upon above, a maximum likelihood-based extended Kalman filter is further developed for dynamically estimating tissue nonlinear deformation based on dynamic identification of tissue mechanical properties. Simulation and experimental analyses reveal that the proposed method not only overcomes the NFEM limitation of expensive computations, but also absorbs the NFEM merit of high accuracy for modelling of homogeneous tissue deformation. Further, the proposed method also effectively identifies tissue mechanical properties during the deformation modelling process.

Absorption, metabolism and distribution of carbosulfan in maize plants (Zea mays L.).

BACKGROUND: The insecticide carbosulfan is usually applied as a soil treatment or seed-coating agent, and so may be absorbed by crops and pose dietary risks. Understanding the uptake, metabolism and translocation of carbosulfan in crops is conducive to its safe application. In this study, we investigated the distribution of carbosulfan and its toxic metabolites in maize plants at both the tissue and subcellular levels, and explored the uptake and translocation mechanism of carbosulfan. RESULTS: Carbosulfan was mainly taken up by maize roots via the apoplast pathway, was preferentially distributed in cell walls (51.2%-57.0%) and most (85.0%) accumulated in roots with only weak upward translocation. Carbofuran, the main metabolite of carbosulfan in maize plants, was primarily stored in roots. However, carbofuran could be upwardly translocated to shoots and leaves because of its greater distribution in root-soluble components (24.4%-28.5%) compared with carbosulfan (9.7%-14.5%). This resulted from its greater solubility compared with its parent compound. The metabolite 3-hydroxycarbofuran was found in shoots and leaves. CONCLUSION: Carbosulfan could be passively absorbed by maize roots, mainly via the apoplastic pathway, and transformed into carbofuran and 3-hydroxycarbofuran. Although carbosulfan mostly accumulated in roots, its toxic metabolites carbofuran and 3-hydroxycarbofuran could be detected in shoots and leaves. This implies that there is a risk in the use of carbosulfan as a soil treatment or seed coating. © 2023 Society of Chemical Industry.

Exosomes as Potential Functional Nanomaterials for Tissue Engineering.

Exosomes are cell-derived extracellular vesicles of 40-160 nm diameter, which carry numerous biomolecules and transmit information between cells. They are used as functional nanomaterials with great potential in biomedical areas, such as active agents and delivery systems for advanced drug delivery and disease therapy. In recent years, potential applications of exosomes in tissue engineering have attracted significant attention, and some critical progress has been made. This review gives a complete picture of exosomes and their applications in the regeneration of various tissues, such as the central nervous systems, kidney, bone, cartilage, heart, and endodontium. Approaches employed for modifying exosomes to equip them with excellent targeting capacity are summarized. Furthermore, current concerns and future outlook of exosomes in tissue engineering are discussed.

Enantioselectivity of new chiral triazole fungicide mefentrifluconazole: Bioactivity against phytopathogen, and acute toxicity and bioaccumulation in earthworm (Eisenia fetida).

Elaborating the environmental behavior of mefentrifluconazole, a novel triazole fungicide, in stereoselective level is of paramount importance for the application of the pesticide in agriculture. In this study, the enantioselective bioactivity, acute toxicity and stereoselective bioaccumulation of mefentrifluconazole in earthworm (Eisenia fetida) were investigated. Bioactivity tests against four pathogens revealed that R-(-)-mefentrifluconazole exhibited approximately 11-113 times higher bioactivity than its S-(+)-mefentrifluconazole. However, the LC50 of S-(+)-, rac- and R-(-)-mefentrifluconazole to earthworm was measured to be 4.1, 11.4 and 7.3 µg/cm2, respectively, indicating active ingredient R-(-)-mefentrifluconazole is less toxic than its racemate and S-form. Accumulation of mefentrifluconazole in earthworms was non-enantioselective and negatively related to its adsorption onto soils. The concentration of mefentrifluconazole in in situ pore water (CIPW) and CaCl2 extraction (CCaCl2) was closely related to its accumulation in earthworms, suggesting that CIPW and CCaCl2 could be appropriate indicators for estimation of the bioavailability of mefentrifluconazole in soil. Conclusively, our study provides necessary information for the risk assessment of mefentrifluconazole in agriculture.

Global Impact of Coronavirus Disease 2019 Infection Requiring Admission to the ICU: A Systematic Review and Meta-analysis.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has placed unprecedented burden on the delivery of intensive care services worldwide. RESEARCH QUESTION: What is the global point estimate of deaths and risk factors for patients who are admitted to ICUs with severe COVID-19? STUDY DESIGN AND METHODS: In this systematic review and meta-analysis Medline, Embase, and the Cochrane library were searched up to August 1, 2020. Pooled prevalence of participant characteristics, clinical features, and outcome data was calculated with the use of random effects models. Subgroup analyses were based on geographic distribution, study type, quality assessment, sample size, end date, and patient disposition. Studies that reported in-hospital mortality rate of adult patients (age >18 years) with confirmed COVID-19 admitted to an ICU met study eligibility criteria. Critical evaluation was performed with the Newcastle Ottawa Scale for nonrandomized studies. RESULTS: Forty-five studies with 16,561 patients from 17 countries across four continents were included. Patients with COVID-19 who were admitted to ICUs had a mean age of 62.6 years (95% CI, 60.4-64.7). Common comorbidities included hypertension (49.5%; 95% CI, 44.9-54.0) and diabetes mellitus (26.6%; 95% CI, 22.7-30.8). More than three-quarters of cases experienced the development of ARDS (76.1%; 95% CI, 65.7-85.2). Invasive mechanical ventilation was required in 67.7% (95% CI, 59.1-75.7) of case, vasopressor support in 65.9% (95% CI, 52.4-78.4) of cases, renal replacement therapy in 16.9% (95% CI, 12.1-22.2) of cases, and extracorporeal membrane oxygenation in 6.4% (95% CI, 4.1-9.1) of cases. The duration of ICU and hospital admission was 10.8 days (95% CI, 9.3-18.4) and 19.1 days (95% CI, 16.3-21.9), respectively, with in-hospital mortality rate of 28.1% (95% CI, 23.4-33.0; I2 = 96%). No significant subgroup effect was observed. INTERPRETATION: Critically ill patients with COVID-19 who are admitted to the ICU require substantial organ support and prolonged ICU and hospital level care. The pooled estimate of global death from severe COVID-19 is <1 in 3.

Finite-element kalman filter with state constraint for dynamic soft tissue modelling.

This research work proposes a novel method for realistic and real-time modelling of deformable biological tissues by the combination of the traditional finite element method (FEM) with constrained Kalman filtering. This methodology transforms the problem of deformation modelling into a problem of constrained filtering to estimate physical tissue deformation online. It discretises the deformation of biological tissues in 3D space according to linear elasticity using FEM. On the basis of this, a constrained Kalman filter is derived to dynamically compute mechanical deformation of biological tissues by minimizing the error between estimated reaction forces and applied mechanical load. The proposed method solves the disadvantage of costly computation in FEM while inheriting the superiority of physical fidelity.

Extended Kalman Filter Nonlinear Finite Element Method for Nonlinear Soft Tissue Deformation.

BACKGROUND AND OBJECTIVE: Soft tissue modelling is crucial to surgery simulation. This paper introduces an innovative approach to realistic simulation of nonlinear deformation behaviours of biological soft tissues in real time. METHODS: This approach combines the traditional nonlinear finite-element method (NFEM) and nonlinear Kalman filtering to address both physical fidelity and real-time performance for soft tissue modelling. It defines tissue mechanical deformation as a nonlinear filtering process for dynamic estimation of nonlinear deformation behaviours of biological tissues. Tissue mechanical deformation is discretized in space using NFEM in accordance with nonlinear elastic theory and in time using the central difference scheme to establish the nonlinear state-space models for dynamic filtering. RESULTS: An extended Kalman filter is established to dynamically estimate nonlinear mechanical deformation of biological tissues. Interactive deformation of biological soft tissues with haptic feedback is accomplished as well for surgery simulation. CONCLUSIONS: The proposed approach conquers the NFEM limitation of step computation but without trading off the modelling accuracy. It not only has a similar level of accuracy as NFEM, but also meets the real-time requirement for soft tissue modelling.