Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

BACKGROUND
Red blood cell distribution width (RDW), a component of an electronic complete blood count, is a measure of heterogeneity in the size of circulating erythrocytes. In patients with symptomatic cardiovascular disease (CVD), RDW is associated with mortality. However, it has not been demonstrated that RDW is a predictor of mortality independent of nutritional deficiencies or in the general population.


METHODS
Red blood cell distribution width was measured in a national sample of 8175 community-dwelling adults 45 years or older who participated in the 1988-1994 National Health and Nutrition Examination Survey; mortality follow-up occurred through December 31, 2000. Deaths from all causes, CVD, cancer, and other causes were examined as a function of RDW.


RESULTS
Higher RDW values were strongly associated with an increased risk of death. Compared with the lowest quintile of RDW, the following were adjusted hazard ratios (HRs) for all-cause mortality (and 95% confidence intervals [CIs]): second quintile, HR, 1.1 (95% CI, 0.9-1.3); third quintile, HR, 1.2 (95% CI, 1.0-1.4); fourth quintile, HR, 1.4 (95% CI, 1.2-1.8); and fifth quintile, HR, 2.1 (95% CI, 1.7-2.6). For every 1% increment in RDW, all-cause mortality risk increased by 22% (HR, 1.22; 95% CI, 1.15-1.30; P < .001). Even when analyses were restricted to nonanemic participants or to those in the reference range of RDW (11%-15%) without iron, folate, or vitamin B(12) deficiency, RDW remained strongly associated with mortality. The prognostic effect of RDW was observed in both middle-aged and older adults for multiple causes of death.


CONCLUSION
Red blood cell distribution width is a widely available test that is a strong predictor of mortality in the general population of adults 45 years or older.

Red Blood Cell Distribution Width and the Risk of Death in Middle-aged and Older Adults.

Coronavirus disease-19 (COVID-19) has been regarded as an infective-inflammatory disease, which affects mainly lungs. More recently, a multi-organ involvement has been highlighted, with different pathways of injury. A hemoglobinopathy, hypoxia and cell iron overload might have a possible additional role. Scientific literature has pointed out two potential pathophysiological mechanisms: i) severe acute respiratory syndrome-coronavirus-2 (SARS-CoV- 2) interaction with hemoglobin molecule, through CD147, CD26 and other receptors located on erythrocyte and/or blood cell precursors; ii) hepcidin-mimetic action of a viral spike protein, inducing ferroportin blockage. In this translational medicinebased narrative review, the following pathologic metabolic pathways, deriving from hemoglobin denaturation and iron metabolism dysregulation, are highlighted: i) decrease of functioning hemoglobin quote; ii) iron overload in cell/tissue (hyperferritinemia); iii) release of free toxic circulating heme; iv) hypoxemia and systemic hypoxia; v) reduction of nitric oxide; vi) coagulation activation; vii) ferroptosis with oxidative stress and lipoperoxidation; viii) mitochondrial degeneration and apoptosis. A few clinical syndromes may follow, such as pulmonary edema based on arterial vasoconstriction and altered alveolo-capillary barrier, sideroblastic-like anemia, endotheliitis, vasospastic acrosyndrome, and arterio- venous thromboembolism. We speculated that in COVID-19, beyond the classical pulmonary immune-inflammation view, the occurrence of an oxygen-deprived blood disease, with iron metabolism dysregulation, should be taken in consideration. A more comprehensive diagnostic/therapeutic approach to COVID-19 is proposed, including potential adjuvant interventions aimed at improving hemoglobin dysfunction, iron over-deposit and generalized hypoxic state.

https://www.mdpi.com/2039-7283/10/2/1271/pdf

COVID-19: hemoglobin, iron, and hypoxia beyond inflammation. A narrative review.

https://pure.mpg.de/pubman/item/item_3316873_8/component/file_3332051/Biophys%20J%202021%20Kubankova.pdf

Physical phenotype of blood cells is altered in COVID-19.

OBJECTIVES: We conducted a systematic literature review and meta-analysis of observational studies to investigate the association between diabetes, hypertension, body mass index (BMI) or smoking with the risk of death in patients with COVID-19 and to estimate the proportion of deaths attributable to these conditions. METHODS: Relevant observational studies were identified by searches in the PubMed, Cochrane library and Embase databases through 14 November 2020. Random-effects models were used to estimate summary relative risks (SRRs) and 95% CIs. Certainty of evidence was assessed using the Cochrane methods and the Grading of Recommendations, Assessment, Development and Evaluations framework. RESULTS: A total of 186 studies representing 210 447 deaths among 1 304 587 patients with COVID-19 were included in this analysis. The SRR for death in patients with COVID-19 was 1.54 (95% CI 1.44 to 1.64, I2=92%, n=145, low certainty) for diabetes and 1.42 (95% CI 1.30 to 1.54, I2=90%, n=127, low certainty) for hypertension compared with patients without each of these comorbidities. Regarding obesity, the SSR was 1.45 (95% CI 1.31 to 1.61, I2=91%, n=54, high certainty) for patients with BMI ≥30 kg/m2 compared with those with BMI <30 kg/m2 and 1.12 (95% CI 1.07 to 1.17, I2=68%, n=25) per 5 kg/m2 increase in BMI. There was evidence of a J-shaped non-linear dose-response relationship between BMI and mortality from COVID-19, with the nadir of the curve at a BMI of around 22-24, and a 1.5-2-fold increase in COVID-19 mortality with extreme obesity (BMI of 40-45). The SRR was 1.28 (95% CI 1.17 to 1.40, I2=74%, n=28, low certainty) for ever, 1.29 (95% CI 1.03 to 1.62, I2=84%, n=19) for current and 1.25 (95% CI 1.11 to 1.42, I2=75%, n=14) for former smokers compared with never smokers. The absolute risk of COVID-19 death was increased by 14%, 11%, 12% and 7% for diabetes, hypertension, obesity and smoking, respectively. The proportion of deaths attributable to diabetes, hypertension, obesity and smoking was 8%, 7%, 11% and 2%, respectively. CONCLUSION: Our findings suggest that diabetes, hypertension, obesity and smoking were associated with higher COVID-19 mortality, contributing to nearly 30% of COVID-19 deaths. TRIAL REGISTRATION NUMBER: CRD42020218115.

https://bmjopen.bmj.com/content/bmjopen/11/10/e052777.full.pdf

Diabetes, hypertension, body mass index, smoking and COVID-19-related mortality: a systematic review and meta-analysis of observational studies.

Importance Coronavirus disease 2019 (COVID-19) is an acute respiratory illness with a high rate of hospitalization and mortality. Biomarkers are urgently needed for patient risk stratification. Red blood cell distribution width (RDW), a component of complete blood counts that reflects cellular volume variation, has been shown to be associated with elevated risk for morbidity and mortality in a wide range of diseases. Objective To investigate whether an association between mortality risk and elevated RDW at hospital admission and during hospitalization exists in patients with COVID-19. Design, Setting, and Participants This cohort study included adults diagnosed with SARS-CoV-2 infection and admitted to 1 of 4 hospitals in the Boston, Massachusetts area (Massachusetts General Hospital, Brigham and Women’s Hospital, North Shore Medical Center, and Newton-Wellesley Hospital) between March 4, 2020, and April 28, 2020. Main Outcomes and Measures The main outcome was patient survival during hospitalization. Measures included RDW at admission and during hospitalization, with an elevated RDW defined as greater than 14.5%. Relative risk (RR) of mortality was estimated by dividing the mortality of those with an elevated RDW by the mortality of those without an elevated RDW. Mortality hazard ratios (HRs) and 95% CIs were estimated using a Cox proportional hazards model. Results A total of 1641 patients were included in the study (mean [SD] age, 62[18] years; 886 men [54%]; 740 White individuals [45%] and 497 Hispanic individuals [30%]; 276 nonsurvivors [17%]). Elevated RDW (>14.5%) was associated with an increased mortality risk in patients of all ages. The RR for the entire cohort was 2.73, with a mortality rate of 11% in patients with normal RDW (1173) and 31% in those with an elevated RDW (468). The RR in patients younger than 50 years was 5.25 (normal RDW, 1% [n = 341]; elevated RDW, 8% [n = 65]); 2.90 in the 50- to 59-year age group (normal RDW, 8% [n = 256]; elevated RDW, 24% [n = 63]); 3.96 in the 60- to 69-year age group (normal RDW, 8% [n = 226]; elevated RDW, 30% [104]); 1.45 in the 70- to 79-year age group (normal RDW, 23% [n = 182]; elevated RDW, 33% [n = 113]); and 1.59 in those ≥80 years (normal RDW, 29% [n = 168]; elevated RDW, 46% [n = 123]). RDW was associated with mortality risk in Cox proportional hazards models adjusted for age, D-dimer (dimerized plasmin fragment D) level, absolute lymphocyte count, and common comorbidities such as diabetes and hypertension (hazard ratio of 1.09 per 0.5% RDW increase and 2.01 for an RDW >14.5% vs ≤14.5%;P  Conclusions and Relevance Elevated RDW at the time of hospital admission and an increase in RDW during hospitalization were associated with increased mortality risk for patients with COVID-19 who received treatment at 4 hospitals in a large academic medical center network.

/pdf/association-of-red-blood-cell-distribution-width-with-bx0axqhrv9.pdf

Association of Red Blood Cell Distribution Width With Mortality Risk in Hospitalized Adults With SARS-CoV-2 Infection.

Background
Coronavirus disease 2019 (COVID19) is an acute respiratory illness with a high rate of hospitalization and mortality. Prognostic biomarkers are urgently needed. Red blood cell distribution width (RDW), a component of complete blood counts that reflects cellular volume variation, has been shown to be associated with elevated risk for morbidity and mortality in a wide range of diseases.

Methods
We retrospectively studied the relationship between RDW and COVID19 mortality risk for 1198 adult patients diagnosed with SARS COV2 at 4 Partners Healthcare Network Hospitals between March 4, 2020, and April 28, 2020.

Findings
Elevated RDW (> 14.5%) was associated with increased mortality in patients of all ages with a risk ratio of 2.5 (95% CI, 2.3-2.8). Stratified by age, the risk ratio was 6.2 (4.4-7.9, N = 312) 80 years. RDW was significantly associated with mortality in Cox proportional hazards models adjusted for age, D-Dimer, absolute lymphocyte count, and common comorbidities (p < 1e-4 for RDW in all cases). Patients whose RDW increased during admission had a ~3-fold elevation in mortality risk compared to those whose RDW did not change.

Interpretation
Elevated RDW at diagnosis and an increase in RDW during admission are both associated with increased mortality risk for adult COVID19 patients at a large academic medical center network.

/pdf/elevated-rdw-is-associated-with-increased-mortality-risk-in-51jlxon7va.pdf

Elevated RDW is Associated with Increased Mortality Risk in COVID-19

The main objective of this bachelor thesis in Industrial Technology Engineering is to predict dynamically
consistent walking motions from kinematic and dynamic measurements obtained at the
UPC Biomechanics Laboratory. A healthy gait cycle is captured and foot-ground contact forces are
measured. Then, in order to acquire the new motions, optimal control techniques are applied.
The human body is modeled with a multibody system formed by rigid bodies. Concretely, a twodimensional
simpli ed skeletal model focused on the lower extremity is used in this work. It is
formed by a total of 12 rigid bodies (trunk, pelvis and leg segments) and it has 10 degrees of freedom.
The inverse dynamic analysis is performed using OpenSim, a free software tool developed by
Stanford University that is widely used by the scienti c community.
The optimal control algorithm to obtain dynamically consistent walking motions from experimental
data is implemented in MATLAB. Moreover, the software used to solve the optimal control problem
is GPOPS-II, a general-purpose MATLAB-based software for solving multiple-phase optimal
control problems, developed by the University of Florida. Parameters of GPOPS-II are changed to
study the in
uence on the solution. Then, di erent formulations are analyzed to assess convergence
and similarity between the new motion and the captured one.
During this report, all the processes involved in the analysis and the related theory are detailed,
as well as the methodology used. Theoretical background is presented and complemented with
examples of other works. The skeletal model used is described in detail. The process to export
and obtain the experimental kinematics and dynamics using OpenSim is explained step by step.
Optimal control theory and GPOPS-II working environment, which are employed as the tool to
predict new motions, are also explained. And nally, results are presented and discussed.
This project is considered an initial study of optimal control techniques to predict human motion.
Thereby, it allows to understand these techniques and gain knowledge about how they can be used
in order to be applied, in the future, in more complex models.

Optimal control prediction of dynamically consistent walking motions

Motion prediction is a field of great interest in motor rehabilitation, because it can help to determine the optimal treatment for a specific patient or to personalise an assistive device. People with mobility impairments can be assisted by orthoses and exoskeletons, and they commonly need crutch assistance for balance. Walking with crutches modifies gait kinematics and dynamics, and it requires more energy than normal walking. The choice of the proper assistive device for each patient can improve gait function. For that, it is important to have realistic multibody models of subjects assisted by crutches, which include contact models to characterise crutch-ground interaction. Existing studies that predict crutch-assisted walking have used so far simple 2D models [1,2], or have modelled the resultant dynamic effect of arms and crutches as external forces and moments applied at the shoulders [3]. Moreover, in these studies only part of the walking cycle is simulated [1,2]. In [4], a threedimensional (3D) model of a subject assisted by upper limb crutches is driven by 3D-marker data, so a novel motion is not predicted. The aim of this work is to generate methods to predict crutch-assisted walking motions from an experimental motion capture. For this purpose, we present a 3D model of a healthy subject assisted by crutches, and we calibrate foot-ground and crutch-ground contact models.

Roger Pallarès López

Papers

Association of Red Blood Cell Distribution Width With Mortality Risk in Hospitalized Adults With SARS-CoV-2 Infection.

Elevated RDW is Associated with Increased Mortality Risk in COVID-19

Optimal control prediction of dynamically consistent walking motions

Calibration of foot-ground and crutch-ground contact models for optimal control prediction of crutch-assisted walking motions