Diabetes mellitus is associated with 90-day mortality in old critically ill COVID-19 patients: a multicenter prospective observational cohort study.

BACKGROUND: Several studies have found an association between diabetes mellitus, disease severity and outcome in COVID-19 patients. Old critically ill patients are particularly at risk. This study aimed to investigate the impact of diabetes mellitus on 90-day mortality in a high-risk cohort of critically ill patients over 70 years of age. METHODS: This multicentre international prospective cohort study was performed in 151 ICUs across 26 countries. We included patients ≥ 70 years of age with a confirmed SARS-CoV-2 infection admitted to the intensive care unit from 19th March 2020 through 15th July 2021. Patients were categorized into two groups according to the presence of diabetes mellitus. Primary outcome was 90-day mortality. Kaplan-Meier overall survival curves until day 90 were analysed and compared using the log-rank test. Mixed-effect Weibull regression models were computed to investigate the influence of diabetes mellitus on 90-day mortality. RESULTS: This study included 3420 patients with a median age of 76 years were included. Among these, 37.3% (n = 1277) had a history of diabetes mellitus. Patients with diabetes showed higher rates of frailty (32% vs. 18%) and several comorbidities including chronic heart failure (20% vs. 11%), hypertension (79% vs. 59%) and chronic kidney disease (25% vs. 11%), but not of pulmonary comorbidities (22% vs. 22%). The 90-day mortality was significantly higher in patients with diabetes than those without diabetes (64% vs. 56%, p < 0.001). The association of diabetes and 90-day mortality remained significant (HR 1.18 [1.06-1.31], p = 0.003) after adjustment for age, sex, SOFA-score and other comorbidities in a Weibull regression analysis. CONCLUSION: Diabetes mellitus was a relevant risk factor for 90-day mortality in old critically ill patients with COVID-19. STUDY REGISTRATION: NCT04321265, registered March 19th, 2020.

Family support in intensive care units during COVID-19 visit ban: A multinational Delphi Study during first COVID-19 wave.

OBJECTIVES: This study assessed opinions and experiences of healthcare professionals, former patients and family members during the first wave of the COVID-19 pandemic and focuses on challenges in family-centred care for intensive care unit patients and affected families. RESEARCH METHODOLOGY/DESIGN: A two-round modified Delphi process assessed the opinions and experiences of experts such as healthcare professionals, former patients and their families (n = 151). SETTING: This study was conducted across four countries in Europe. RESULTS: In total, 121 participants (response rate 80.13%) answered the first Delphi round; the second was answered by 131 participants (response rate 86.75%). Participants perceived family support in the intensive care unit as highly important during the COVID-19 pandemic. Enabling contact amongst patients, families and clinicians is regarded as essential to build hope and confidence in the treatment and the recovery process. The extraordinary situation led to the implementation of new communication structures such as video calls and websites. CONCLUSION: A consensus was reached between healthcare professionals that virtual contact is essential for patients with COVID-19 and their families during visit restrictions. This should be done to establish confidence in the treatment.

The association of prior paracetamol intake with outcome of very old intensive care patients with COVID-19: results from an international prospective multicentre trial.

BACKGROUND: In the early COVID-19 pandemic concerns about the correct choice of analgesics in patients with COVID-19 were raised. Little data was available on potential usefulness or harmfulness of prescription free analgesics, such as paracetamol. This international multicentre study addresses that lack of evidence regarding the usefulness or potential harm of paracetamol intake prior to ICU admission in a setting of COVID-19 disease within a large, prospectively enrolled cohort of critically ill and frail intensive care unit (ICU) patients. METHODS: This prospective international observation study (The COVIP study) recruited ICU patients ≥ 70 years admitted with COVID-19. Data on Sequential Organ Failure Assessment (SOFA) score, prior paracetamol intake within 10 days before admission, ICU therapy, limitations of care and survival during the ICU stay, at 30 days, and 3 months. Paracetamol intake was analysed for associations with ICU-, 30-day- and 3-month-mortality using Kaplan Meier analysis. Furthermore, sensitivity analyses were used to stratify 30-day-mortality in subgroups for patient-specific characteristics using logistic regression. RESULTS: 44% of the 2,646 patients with data recorded regarding paracetamol intake within 10 days prior to ICU admission took paracetamol. There was no difference in age between patients with and without paracetamol intake. Patients taking paracetamol suffered from more co-morbidities, namely diabetes mellitus (43% versus 34%, p < 0.001), arterial hypertension (70% versus 65%, p = 0.006) and had a higher score on Clinical Frailty Scale (CFS; IQR 2-5 versus IQR 2-4, p < 0.001). Patients under prior paracetamol treatment were less often subjected to intubation and vasopressor use, compared to patients without paracetamol intake (65 versus 71%, p < 0.001; 63 versus 69%, p = 0.007). Paracetamol intake was not associated with ICU-, 30-day- and 3-month-mortality, remaining true after multivariate adjusted analysis. CONCLUSION: Paracetamol intake prior to ICU admission was not associated with short-term and 3-month mortality in old, critically ill intensive care patients suffering from COVID-19. TRIAL REGISTRATION: This prospective international multicentre study was registered on ClinicalTrials.gov with the identifier "NCT04321265" on March 25, 2020.

Development and validation of a prognostic model for the early identification of COVID-19 patients at risk of developing common long COVID symptoms.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic demands reliable prognostic models for estimating the risk of long COVID. We developed and validated a prediction model to estimate the probability of known common long COVID symptoms at least 60 days after acute COVID-19. METHODS: The prognostic model was built based on data from a multicentre prospective Swiss cohort study. Included were adult patients diagnosed with COVID-19 between February and December 2020 and treated as outpatients, at ward or intensive/intermediate care unit. Perceived long-term health impairments, including reduced exercise tolerance/reduced resilience, shortness of breath and/or tiredness (REST), were assessed after a follow-up time between 60 and 425 days. The data set was split into a derivation and a geographical validation cohort. Predictors were selected out of twelve candidate predictors based on three methods, namely the augmented backward elimination (ABE) method, the adaptive best-subset selection (ABESS) method and model-based recursive partitioning (MBRP) approach. Model performance was assessed with the scaled Brier score, concordance c statistic and calibration plot. The final prognostic model was determined based on best model performance. RESULTS: In total, 2799 patients were included in the analysis, of which 1588 patients were in the derivation cohort and 1211 patients in the validation cohort. The REST prevalence was similar between the cohorts with 21.6% (n = 343) in the derivation cohort and 22.1% (n = 268) in the validation cohort. The same predictors were selected with the ABE and ABESS approach. The final prognostic model was based on the ABE and ABESS selected predictors. The corresponding scaled Brier score in the validation cohort was 18.74%, model discrimination was 0.78 (95% CI: 0.75 to 0.81), calibration slope was 0.92 (95% CI: 0.78 to 1.06) and calibration intercept was -0.06 (95% CI: -0.22 to 0.09). CONCLUSION: The proposed model was validated to identify COVID-19-infected patients at high risk for REST symptoms. Before implementing the prognostic model in daily clinical practice, the conduct of an impact study is recommended.

COVID-19 machine learning model predicts outcomes in older patients from various European countries, between pandemic waves, and in a cohort of Asian, African, and American patients.

BACKGROUND: COVID-19 remains a complex disease in terms of its trajectory and the diversity of outcomes rendering disease management and clinical resource allocation challenging. Varying symptomatology in older patients as well as limitation of clinical scoring systems have created the need for more objective and consistent methods to aid clinical decision making. In this regard, machine learning methods have been shown to enhance prognostication, while improving consistency. However, current machine learning approaches have been limited by lack of generalisation to diverse patient populations, between patients admitted at different waves and small sample sizes. OBJECTIVES: We sought to investigate whether machine learning models, derived on routinely collected clinical data, can generalise well i) between European countries, ii) between European patients admitted at different COVID-19 waves, and iii) between geographically diverse patients, namely whether a model derived on the European patient cohort can be used to predict outcomes of patients admitted to Asian, African and American ICUs. METHODS: We compare Logistic Regression, Feed Forward Neural Network and XGBoost algorithms to analyse data from 3,933 older patients with a confirmed COVID-19 diagnosis in predicting three outcomes, namely: ICU mortality, 30-day mortality and patients at low risk of deterioration. The patients were admitted to ICUs located in 37 countries, between January 11, 2020, and April 27, 2021. RESULTS: The XGBoost model derived on the European cohort and externally validated in cohorts of Asian, African, and American patients, achieved AUC of 0.89 (95% CI 0.89-0.89) in predicting ICU mortality, AUC of 0.86 (95% CI 0.86-0.86) for 30-day mortality prediction and AUC of 0.86 (95% CI 0.86-0.86) in predicting low-risk patients. Similar AUC performance was achieved also when predicting outcomes between European countries and between pandemic waves, while the models showed high calibration quality. Furthermore, saliency analysis showed that FiO2 values of up to 40% do not appear to increase the predicted risk of ICU and 30-day mortality, while PaO2 values of 75 mmHg or lower are associated with a sharp increase in the predicted risk of ICU and 30-day mortality. Lastly, increase in SOFA scores also increase the predicted risk, but only up to a value of 8. Beyond these scores the predicted risk remains consistently high. CONCLUSION: The models captured both the dynamic course of the disease as well as similarities and differences between the diverse patient cohorts, enabling prediction of disease severity, identification of low-risk patients and potentially supporting effective planning of essential clinical resources. TRIAL REGISTRATION NUMBER: NCT04321265.

A retrospective cohort study comparing differences in 30-day mortality among critically ill patients aged ≥ 70 years treated in European tax-based healthcare systems (THS) versus social health insurance systems.

In Europe, tax-based healthcare systems (THS) and social health insurance systems (SHI) coexist. We examined differences in 30-day mortality among critically ill patients aged ≥ 70 years treated in intensive care units in a THS or SHI. Retrospective cohort study. 2406 (THS n = 886; SHI n = 1520) critically ill ≥ 70 years patients in 129 ICUs. Generalized estimation equations with robust standard errors were chosen to create population average adjusted odds ratios (aOR). Data were adjusted for patient-specific variables, organ support and health economic data. The primary outcome was 30-day-mortality. Numerical differences between SHI and THS in SOFA scores (6 ± 3 vs. 5 ± 3; p = 0.002) were observed, but clinical frailty scores were similar (> 4; 17% vs. 14%; p = 0.09). Higher rates of renal replacement therapy (18% vs. 11%; p < 0.001) were found in SHI (aOR 0.61 95%CI 0.40-0.92; p = 0.02). No differences regarding intubation rates (68% vs. 70%; p = 0.33), vasopressor use (67% vs. 67%; p = 0.90) and 30-day-mortality rates (47% vs. 50%; p = 0.16) were found. Mortality remained similar between both systems after multivariable adjustment and sensitivity analyses. The retrospective character of this study. Baseline risk and mortality rates were similar between SHI and THS. The type of health care system does not appear to have played a role in the intensive care treatment of critically ill patients ≥ 70 years with COVID-19 in Europe.

Sex-specific treatment characteristics and 30-day mortality outcomes of critically ill COVID-19 patients over 70 years of age-results from the prospective COVIP study.

PURPOSE: Older critically ill patients with COVID-19 have been the most vulnerable during the ongoing pandemic, with men being more prone to hospitalization and severe disease than women. We aimed to explore sex-specific differences in treatment and outcome after intensive care unit (ICU) admission in this cohort. METHODS: We performed a sex-specific analysis in critically ill patients ≥ 70 yr of age with COVID-19 who were included in the international prospective multicenter COVIP study. All patients were analyzed for ICU admission and treatment characteristics. We performed a multilevel adjusted regression analysis to elucidate associations of sex with 30-day mortality. RESULTS: A total of 3,159 patients (69.8% male, 30.2% female; median age, 75 yr) were included. Male patients were significantly fitter than female patients as determined by the Clinical Frailty Scale (fit, 67% vs 54%; vulnerable, 14% vs 19%; frail, 19% vs 27%; P < 0.001). Male patients more often underwent tracheostomy (20% vs 14%; odds ratio [OR], 1.57; P < 0.001), vasopressor therapy (69% vs 62%; OR, 1.25; P = 0.02), and renal replacement therapy (17% vs 11%; OR, 1.96; P < 0.001). There was no difference in mechanical ventilation, life-sustaining treatment limitations, and crude 30-day mortality (50% male vs 49% female; OR, 1.11; P = 0.19), which remained true after adjustment for disease severity, frailty, age and treatment limitations (OR, 1.17; 95% confidence interval, 0.94 to 1.45; P = 0.16). CONCLUSION: In this analysis of sex-specific treatment characteristics and 30-day mortality outcomes of critically ill patients with COVID-19 ≥ 70 yr of age, we found more tracheostomy and renal replacement therapy in male vs female patients, but no significant association of patient sex with 30-day mortality. STUDY REGISTRATION: www. CLINICALTRIALS: gov (NCT04321265); registered 25 March 2020).

RéSUMé: OBJECTIF: Les patients âgés gravement malades atteints de la COVID-19 ont été les plus vulnérables pendant la pandémie actuelle, les hommes étant plus sujets à l'hospitalisation et aux maladies graves que les femmes. Nous avons cherché à explorer les différences spécifiques au sexe dans le traitement et les devenirs après l'admission à l'unité de soins intensifs (USI) dans cette cohorte. MéTHODE: Nous avons effectué une analyse spécifique au sexe chez des patients gravement malades âgés de ≥ 70 ans atteints de COVID-19 qui ont été inclus dans l'étude prospective multicentrique internationale COVIP. Tous les patients ont été analysés pour connaître les détails de leur admission à l'USI et les caractéristiques de leur traitement. Nous avons réalisé une analyse de régression ajustée à plusieurs niveaux pour élucider les associations entre le sexe et la mortalité à 30 jours. RéSULTATS: Au total, 3159 patients (69,8 % d'hommes, 30,2 % de femmes; âge médian, 75 ans) ont été inclus. Les patients de sexe masculin étaient significativement plus en forme que les patientes, tel que déterminé par l'échelle de fragilité clinique (bonne santé, 67 % vs 54 %; vulnérables, 14 % vs 19 %; fragiles, 19 % vs 27 %; P < 0,001). Les patients de sexe masculin ont plus souvent bénéficié d'une trachéostomie (20 % vs 14 %; rapport de cotes [RC], 1,57; P < 0,001), d'un traitement vasopresseur (69 % vs 62 %; RC, 1,25; P = 0,02) et d'un traitement substitutif de l'insuffisance rénale (17 % vs 11 %; RC, 1,96; P < 0,001). Il n'y avait aucune différence en matière de ventilation mécanique, de limites des traitements de maintien en vie et de mortalité brute à 30 jours (50 % d'hommes vs 49 % de femmes; RC, 1,11; P = 0,19), ce qui est demeuré le cas après ajustement pour tenir compte de la gravité de la maladie, de la fragilité, de l'âge et des limites du traitement (RC, 1,17 ; intervalle de confiance à 95 %, 0,94 à 1,45; P = 0,16). CONCLUSION: Dans cette analyse des caractéristiques de traitement spécifiques au sexe et des résultats de mortalité à 30 jours des patients gravement malades atteints de COVID-19 de ≥ 70 ans, nous avons noté un nombre plus élevé de trachéotomies et de traitements substitutifs de l'insuffisance rénale chez les hommes vs les femmes, mais aucune association significative entre le sexe des patients et la mortalité à 30 jours. ENREGISTREMENT DE L'éTUDE: www.ClinicalTrials.gov (NCT04321265); enregistré le 25 mars 2020.

Noninvasive ventilation in COVID-19 patients aged ≥ 70 years-a prospective multicentre cohort study.

BACKGROUND: Noninvasive ventilation (NIV) is a promising alternative to invasive mechanical ventilation (IMV) with a particular importance amidst the shortage of intensive care unit (ICU) beds during the COVID-19 pandemic. We aimed to evaluate the use of NIV in Europe and factors associated with outcomes of patients treated with NIV. METHODS: This is a substudy of COVIP study-an international prospective observational study enrolling patients aged ≥ 70 years with confirmed COVID-19 treated in ICU. We enrolled patients in 156 ICUs across 15 European countries between March 2020 and April 2021.The primary endpoint was 30-day mortality. RESULTS: Cohort included 3074 patients, most of whom were male (2197/3074, 71.4%) at the mean age of 75.7 years (SD 4.6). NIV frequency was 25.7% and varied from 1.1 to 62.0% between participating countries. Primary NIV failure, defined as need for endotracheal intubation or death within 30 days since ICU admission, occurred in 470/629 (74.7%) of patients. Factors associated with increased NIV failure risk were higher Sequential Organ Failure Assessment (SOFA) score (OR 3.73, 95% CI 2.36-5.90) and Clinical Frailty Scale (CFS) on admission (OR 1.46, 95% CI 1.06-2.00). Patients initially treated with NIV (n = 630) lived for 1.36 fewer days (95% CI - 2.27 to - 0.46 days) compared to primary IMV group (n = 1876). CONCLUSIONS: Frequency of NIV use varies across European countries. Higher severity of illness and more severe frailty were associated with a risk of NIV failure among critically ill older adults with COVID-19. Primary IMV was associated with better outcomes than primary NIV. Clinical Trial Registration NCT04321265 , registered 19 March 2020, https://clinicaltrials.gov .

Early and Rapid Identification of COVID-19 Patients with Neutralizing Type I Interferon Auto-antibodies.

PURPOSE: Six to 19% of critically ill COVID-19 patients display circulating auto-antibodies against type I interferons (IFN-AABs). Here, we establish a clinically applicable strategy for early identification of IFN-AAB-positive patients for potential subsequent clinical interventions. METHODS: We analyzed sera of 430 COVID-19 patients from four hospitals for presence of IFN-AABs by ELISA. Binding specificity and neutralizing activity were evaluated via competition assay and virus-infection-based neutralization assay. We defined clinical parameters associated with IFN-AAB positivity. In a subgroup of critically ill patients, we analyzed effects of therapeutic plasma exchange (TPE) on the levels of IFN-AABs, SARS-CoV-2 antibodies and clinical outcome. RESULTS: The prevalence of neutralizing AABs to IFN-α and IFN-ω in COVID-19 patients from all cohorts was 4.2% (18/430), while being undetectable in an uninfected control cohort. Neutralizing IFN-AABs were detectable exclusively in critically affected (max. WHO score 6-8), predominantly male (83%) patients (7.6%, 18/237 for IFN-α-AABs and 4.6%, 11/237 for IFN-ω-AABs in 237 patients with critical COVID-19). IFN-AABs were present early post-symptom onset and at the peak of disease. Fever and oxygen requirement at hospital admission co-presented with neutralizing IFN-AAB positivity. IFN-AABs were associated with lower probability of survival (7.7% versus 80.9% in patients without IFN-AABs). TPE reduced levels of IFN-AABs in three of five patients and may increase survival of IFN-AAB-positive patients compared to those not undergoing TPE. CONCLUSION: IFN-AABs may serve as early biomarker for the development of severe COVID-19. We propose to implement routine screening of hospitalized COVID-19 patients for rapid identification of patients with IFN-AABs who most likely benefit from specific therapies.

Neuro-axonal injury in COVID-19: the role of systemic inflammation and SARS-CoV-2 specific immune response.

Background: In coronavirus disease-2019 (COVID-19) patients, there is increasing evidence of neuronal injury by the means of elevated serum neurofilament light chain (sNfL) levels. However, the role of systemic inflammation and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific immune response with regard to neuronal injury has not yet been investigated. Methods: In a prospective cohort study, we recruited patients with mild-moderate (n = 39) and severe (n = 14) COVID-19 and measured sNfL levels, cytokine concentrations, SARS-CoV-2-specific antibodies including neutralizing antibody titers, and cell-mediated immune responses at enrollment and at 28(±7) days. We explored the association of neuro-axonal injury as by the means of sNfL measurements with disease severity, cytokine levels, and virus-specific immune responses. Results: sNfL levels, as an indicator for neuronal injury, were higher at enrollment and increased during follow-up in severely ill patients, whereas during mild-moderate COVID-19, sNfL levels remained unchanged. Severe COVID-19 was associated with increased concentrations of cytokines assessed [interleukin (IL)-6, IL-8, interleukin-1 beta (IL-1ß), and tumor necrosis factor-alpha (TNF-α)], higher anti-spike IgG and anti-nucleocapsid IgG concentrations, and increased neutralizing antibody titers compared with mild-moderate disease. Patients with more severe disease had higher counts of defined SARS-CoV-2-specific T cells. Increases in sNfL concentrations from baseline to day 28(±7) positively correlated with anti-spike protein IgG antibody levels and with titers of neutralizing antibodies. Conclusion: Severe COVID-19 is associated with increased serum concentration of cytokines and subsequent neuronal injury as reflected by increased levels of sNfL. Patients with more severe disease developed higher neutralizing antibody titers and higher counts of SARS-CoV-2-specific T cells during the course of COVID-19 disease. Mounting a pronounced virus-specific humoral and cell-mediated immune response upon SARS-CoV-2 infection did not protect from neuro-axonal damage as by the means of sNfL levels.

Variations in end-of-life care practices in older critically ill patients with COVID-19 in Europe.

BACKGROUND: Previous studies reported regional differences in end-of-life care (EoLC) for critically ill patients in Europe. OBJECTIVES: The purpose of this post-hoc analysis of the prospective multicentre COVIP study was to investigate variations in EoLC practices among older patients in intensive care units during the coronavirus disease 2019 pandemic. METHODS: A total of 3105 critically ill patients aged 70 years and older were enrolled in this study (Central Europe: n = 1573; Northern Europe: n = 821; Southern Europe: n = 711). Generalised estimation equations were used to calculate adjusted odds ratios (aORs) to population averages. Data were adjusted for patient-specific variables (demographic, disease-specific) and health economic data (gross domestic product, health expenditure per capita). The primary outcome was any treatment limitation, and 90-day mortality was a secondary outcome. RESULTS: The frequency of the primary endpoint (treatment limitation) was highest in Northern Europe (48%), intermediate in Central Europe (39%) and lowest in Southern Europe (24%). The likelihood for treatment limitations was lower in Southern than in Central Europe (aOR 0.39; 95% confidence interval [CI] 0.21-0.73; p = 0.004), even after multivariable adjustment, whereas no statistically significant differences were observed between Northern and Central Europe (aOR 0.57; 95%CI 0.27-1.22; p = 0.15). After multivariable adjustment, no statistically relevant mortality differences were found between Northern and Central Europe (aOR 1.29; 95%CI 0.80-2.09; p = 0.30) or between Southern and Central Europe (aOR 1.07; 95%CI 0.66-1.73; p = 0.78). CONCLUSION: This study shows a north-to-south gradient in rates of treatment limitation in Europe, highlighting the heterogeneity of EoLC practices across countries. However, mortality rates were not affected by these results.

Development and early diagnosis of critical illness myopathy in COVID-19 associated acute respiratory distress syndrome.

BACKGROUND: The COVID-19 pandemic has greatly increased the incidence and clinical importance of critical illness myopathy (CIM), because it is one of the most common complications of modern intensive care medicine. Current diagnostic criteria only allow diagnosis of CIM at an advanced stage, so that patients are at risk of being overlooked, especially in early stages. To determine the frequency of CIM and to assess a recently proposed tool for early diagnosis, we have followed a cohort of COVID-19 patients with acute respiratory distress syndrome and compared the time course of muscle excitability measurements with the definite diagnosis of CIM. METHODS: Adult COVID-19 patients admitted to the Intensive Care Unit of the University Hospital Bern, Switzerland requiring mechanical ventilation were recruited and examined on Days 1, 2, 5, and 10 post-intubation. Clinical examination, muscle excitability measurements, medication record, and laboratory analyses were performed on all study visits, and additionally nerve conduction studies, electromyography and muscle biopsy on Day 10. Muscle excitability data were compared with a cohort of 31 age-matched healthy subjects. Diagnosis of definite CIM was made according to the current guidelines and was based on patient history, results of clinical and electrophysiological examinations as well as muscle biopsy. RESULTS: Complete data were available in 31 out of 44 recruited patients (mean [SD] age, 62.4 [9.8] years). Of these, 17 (55%) developed CIM. Muscle excitability measurements on Day 10 discriminated between patients who developed CIM and those who did not, with a diagnostic precision of 90% (AUC 0.908; 95% CI 0.799-1.000; sensitivity 1.000; specificity 0.714). On Days 1 and 2, muscle excitability parameters also discriminated between the two groups with 73% (AUC 0.734; 95% CI 0.550-0.919; sensitivity 0.562; specificity 0.857) and 82% (AUC 0.820; CI 0.652-0.903; sensitivity 0.750; specificity 0.923) diagnostic precision, respectively. All critically ill COVID-19 patients showed signs of muscle membrane depolarization compared with healthy subjects, but in patients who developed CIM muscle membrane depolarization on Days 1, 2 and 10 was more pronounced than in patients who did not develop CIM. CONCLUSIONS: This study reports a 55% prevalence of definite CIM in critically ill COVID-19 patients. Furthermore, the results confirm that muscle excitability measurements may serve as an alternative method for CIM diagnosis and support its use as a tool for early diagnosis and monitoring the development of CIM.

Symptoms of post-traumatic stress disorder (PTSD) in next of kin during suspension of ICU visits during the COVID-19 pandemic: a prospective observational study.

BACKGROUND: During the COVID-19 pandemic, suspension of visits by next of kin to patients in intensive care units (ICU), to prevent spread of the SARS-CoV-2 virus, has been a common practice. This could impede established family-centered care and may affect the mental health of the next of kin. The aim of this study was to explore symptoms of post-traumatic stress syndrome (PTSD) in the next of kin of ICU patients. METHODS: In this prospective observational single-center study, next of kin of ICU patients were interviewed by telephone, using the Impact of Event Scale-Revised (IES-R), to assess symptoms of acute stress disorder during the ICU stay and PTSD symptoms at 3 months after the ICU stay. The primary outcome was the prevalence of severe PTSD symptoms (IES-R score ≥ 33) at 3 months. The secondary outcomes comprised the IES-R scores during the ICU stay, at 3 months, and the prevalence of severe symptoms of acute stress disorder during ICU stay. An inductive content analysis was performed of the next of kin's comments regarding satisfaction with patient care and the information they were given. RESULTS: Of the 411 ICU patients admitted during the study period, 62 patients were included together with their next of kin. An IES-R score > 33 was observed in 90.3% (56/62) of next of kin during the ICU stay and in 69.4% (43/62) 3 months later. The median IES-R score was 49 (IQR 40-61) during the ICU stay and 41 (IQR 30-55) at 3 months. The inductive content analysis showed that communication/information (55%), support (40%), distressing emotions (32%), and suspension of ICU visits (24%) were mentioned as relevant aspects by the next of kin. CONCLUSIONS: During the suspension of ICU visits in the COVID-19 pandemic, high prevalence and severity of both symptoms of acute stress disorder during the ICU stay and PTSD symptoms 3 months later were observed in the next of kin of ICU patients.

Disease-Course Adapting Machine Learning Prognostication Models in Elderly Patients Critically Ill With COVID-19: Multicenter Cohort Study With External Validation.

BACKGROUND: The COVID-19 pandemic caused by SARS-CoV-2 is challenging health care systems globally. The disease disproportionately affects the elderly population, both in terms of disease severity and mortality risk. OBJECTIVE: The aim of this study was to evaluate machine learning-based prognostication models for critically ill elderly COVID-19 patients, which dynamically incorporated multifaceted clinical information on evolution of the disease. METHODS: This multicenter cohort study (COVIP study) obtained patient data from 151 intensive care units (ICUs) from 26 countries. Different models based on the Sequential Organ Failure Assessment (SOFA) score, logistic regression (LR), random forest (RF), and extreme gradient boosting (XGB) were derived as baseline models that included admission variables only. We subsequently included clinical events and time-to-event as additional variables to derive the final models using the same algorithms and compared their performance with that of the baseline group. Furthermore, we derived baseline and final models on a European patient cohort, which were externally validated on a non-European cohort that included Asian, African, and US patients. RESULTS: In total, 1432 elderly (≥70 years old) COVID-19-positive patients admitted to an ICU were included for analysis. Of these, 809 (56.49%) patients survived up to 30 days after admission. The average length of stay was 21.6 (SD 18.2) days. Final models that incorporated clinical events and time-to-event information provided superior performance (area under the receiver operating characteristic curve of 0.81; 95% CI 0.804-0.811), with respect to both the baseline models that used admission variables only and conventional ICU prediction models (SOFA score, P<.001). The average precision increased from 0.65 (95% CI 0.650-0.655) to 0.77 (95% CI 0.759-0.770). CONCLUSIONS: Integrating important clinical events and time-to-event information led to a superior accuracy of 30-day mortality prediction compared with models based on the admission information and conventional ICU prediction models. This study shows that machine-learning models provide additional information and may support complex decision-making in critically ill elderly COVID-19 patients. TRIAL REGISTRATION: ClinicalTrials.gov NCT04321265; https://clinicaltrials.gov/ct2/show/NCT04321265.

The association of the Activities of Daily Living and the outcome of old intensive care patients suffering from COVID-19.

PURPOSE: Critically ill old intensive care unit (ICU) patients suffering from Sars-CoV-2 disease (COVID-19) are at increased risk for adverse outcomes. This post hoc analysis investigates the association of the Activities of Daily Living (ADL) with the outcome in this vulnerable patient group. METHODS: The COVIP study is a prospective international observational study that recruited ICU patients ≥ 70 years admitted with COVID-19 (NCT04321265). Several parameters including ADL (ADL; 0 = disability, 6 = no disability), Clinical Frailty Scale (CFS), SOFA score, intensive care treatment, ICU- and 3-month survival were recorded. A mixed-effects Weibull proportional hazard regression analyses for 3-month mortality adjusted for multiple confounders. RESULTS: This pre-specified analysis included 2359 patients with a documented ADL and CFS. Most patients evidenced independence in their daily living before hospital admission (80% with ADL = 6). Patients with no frailty and no disability showed the lowest, patients with frailty (CFS ≥ 5) and disability (ADL < 6) the highest 3-month mortality (52 vs. 78%, p < 0.001). ADL was independently associated with 3-month mortality (ADL as a continuous variable: aHR 0.88 (95% CI 0.82-0.94, p < 0.001). Being "disable" resulted in a significant increased risk for 3-month mortality (aHR 1.53 (95% CI 1.19-1.97, p 0.001) even after adjustment for multiple confounders. CONCLUSION: Baseline Activities of Daily Living (ADL) on admission provides additional information for outcome prediction, although most critically ill old intensive care patients suffering from COVID-19 had no restriction in their ADL prior to ICU admission. Combining frailty and disability identifies a subgroup with particularly high mortality. TRIAL REGISTRATION NUMBER: NCT04321265.

Neuro-axonal injury in COVID-19: the role of systemic inflammation and SARS-CoV-2 specific immune response

Background: In coronavirus disease-2019 (COVID-19) patients, there is increasing evidence of neuronal injury by the means of elevated serum neurofilament light chain (sNfL) levels. However, the role of systemic inflammation and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)–specific immune response with regard to neuronal injury has not yet been investigated. Methods: In a prospective cohort study, we recruited patients with mild–moderate (n = 39) and severe (n = 14) COVID-19 and measured sNfL levels, cytokine concentrations, SARS-CoV-2-specific antibodies including neutralizing antibody titers, and cell-mediated immune responses at enrollment and at 28(±7) days. We explored the association of neuro-axonal injury as by the means of sNfL measurements with disease severity, cytokine levels, and virus-specific immune responses. Results: sNfL levels, as an indicator for neuronal injury, were higher at enrollment and increased during follow-up in severely ill patients, whereas during mild–moderate COVID-19, sNfL levels remained unchanged. Severe COVID-19 was associated with increased concentrations of cytokines assessed [interleukin (IL)-6, IL-8, interleukin-1 beta (IL-1β), and tumor necrosis factor-alpha (TNF-α)], higher anti-spike IgG and anti-nucleocapsid IgG concentrations, and increased neutralizing antibody titers compared with mild–moderate disease. Patients with more severe disease had higher counts of defined SARS-CoV-2-specific T cells. Increases in sNfL concentrations from baseline to day 28(±7) positively correlated with anti-spike protein IgG antibody levels and with titers of neutralizing antibodies. Conclusion: Severe COVID-19 is associated with increased serum concentration of cytokines and subsequent neuronal injury as reflected by increased levels of sNfL. Patients with more severe disease developed higher neutralizing antibody titers and higher counts of SARS-CoV-2-specific T cells during the course of COVID-19 disease. Mounting a pronounced virus-specific humoral and cell-mediated immune response upon SARS-CoV-2 infection did not protect from neuro-axonal damage as by the means of sNfL levels.

Association of chronic heart failure with mortality in old intensive care patients suffering from Covid-19.

AIMS: Chronic heart failure (CHF) is a major risk factor for mortality in coronavirus disease 2019 (COVID-19). This prospective international multicentre study investigates the role of pre-existing CHF on clinical outcomes of critically ill old (≥70 years) intensive care patients with COVID-19. METHODS AND RESULTS: Patients with pre-existing CHF were subclassified as having ischaemic or non-ischaemic cardiac disease; patients with a documented ejection fraction (EF) were subclassified according to heart failure EF: reduced (HFrEF, n = 132), mild (HFmrEF, n = 91), or preserved (HFpEF, n = 103). Associations of heart failure characteristics with the 30 day mortality were analysed in univariate and multivariate logistic regression analyses. Pre-existing CHF was reported in 566 of 3917 patients (14%). Patients with CHF were older, frailer, and had significantly higher SOFA scores on admission. CHF patients showed significantly higher crude 30 day mortality [60% vs. 48%, P < 0.001; odds ratio 1.87, 95% confidence interval (CI) 1.5-2.3] and 3 month mortality (69% vs. 56%, P < 0.001). After multivariate adjustment for confounders (SOFA, age, sex, and frailty), no independent association of CHF with mortality remained [adjusted odds ratio (aOR) 1.2, 95% CI 0.5-1.5; P = 0.137]. More patients suffered from pre-existing ischaemic than from non-ischaemic disease [233 vs. 328 patients (n = 5 unknown aetiology)]. There were no differences in baseline characteristics between ischaemic and non-ischaemic disease or between HFrEF, HFmrEF, and HFpEF. Crude 30 day mortality was significantly higher in HFrEF compared with HFpEF (64% vs. 48%, P = 0.042). EF as a continuous variable was not independently associated with 30 day mortality (aOR 0.98, 95% CI 0.9-1.0; P = 0.128). CONCLUSIONS: In critically ill older COVID-19 patients, pre-existing CHF was not independently associated with 30 day mortality. TRIAL REGISTRATION NUMBER: NCT04321265.

LRR-protein RNH1 dampens the inflammasome activation and is associated with COVID-19 severity.

Inflammasomes are cytosolic innate immune sensors of pathogen infection and cellular damage that induce caspase-1-mediated inflammation upon activation. Although inflammation is protective, uncontrolled excessive inflammation can cause inflammatory diseases and can be detrimental, such as in coronavirus disease (COVID-19). However, the underlying mechanisms that control inflammasome activation are incompletely understood. Here we report that the leucine-rich repeat (LRR) protein ribonuclease inhibitor (RNH1), which shares homology with LRRs of NLRP (nucleotide-binding oligomerization domain, leucine-rich repeat, and pyrin domain containing) proteins, attenuates inflammasome activation. Deletion of RNH1 in macrophages increases interleukin (IL)-1ß production and caspase-1 activation in response to inflammasome stimulation. Mechanistically, RNH1 decreases pro-IL-1ß expression and induces proteasome-mediated caspase-1 degradation. Corroborating this, mouse models of monosodium urate (MSU)-induced peritonitis and lipopolysaccharide (LPS)-induced endotoxemia, which are dependent on caspase-1, respectively, show increased neutrophil infiltration and lethality in Rnh1 -/- mice compared with wild-type mice. Furthermore, RNH1 protein levels were negatively related with disease severity and inflammation in hospitalized COVID-19 patients. We propose that RNH1 is a new inflammasome regulator with relevance to COVID-19 severity.