Relationship between the Clinical Frailty Scale and short-term mortality in patients ≥ 80 years old acutely admitted to the ICU: a prospective cohort study.

BACKGROUND: The Clinical Frailty Scale (CFS) is frequently used to measure frailty in critically ill adults. There is wide variation in the approach to analysing the relationship between the CFS score and mortality after admission to the ICU. This study aimed to evaluate the influence of modelling approach on the association between the CFS score and short-term mortality and quantify the prognostic value of frailty in this context. METHODS: We analysed data from two multicentre prospective cohort studies which enrolled intensive care unit patients ≥ 80 years old in 26 countries. The primary outcome was mortality within 30-days from admission to the ICU. Logistic regression models for both ICU and 30-day mortality included the CFS score as either a categorical, continuous or dichotomous variable and were adjusted for patient's age, sex, reason for admission to the ICU, and admission Sequential Organ Failure Assessment score. RESULTS: The median age in the sample of 7487 consecutive patients was 84 years (IQR 81-87). The highest fraction of new prognostic information from frailty in the context of 30-day mortality was observed when the CFS score was treated as either a categorical variable using all original levels of frailty or a nonlinear continuous variable and was equal to 9% using these modelling approaches (p < 0.001). The relationship between the CFS score and mortality was nonlinear (p < 0.01). CONCLUSION: Knowledge about a patient's frailty status adds a substantial amount of new prognostic information at the moment of admission to the ICU. Arbitrary simplification of the CFS score into fewer groups than originally intended leads to a loss of information and should be avoided. Trial registration NCT03134807 (VIP1), NCT03370692 (VIP2)

Fluid challenges in intensive care: the FENICE study A global inception cohort study

Fluid challenges (FCs) are one of the most commonly used therapies in critically ill patients and represent the cornerstone of hemodynamic management in intensive care units. There are clear benefits and harms from fluid therapy. Limited data on the indication, type, amount and rate of an FC in critically ill patients exist in the literature. The primary aim was to evaluate how physicians conduct FCs in terms of type, volume, and rate of given fluid; the secondary aim was to evaluate variables used to trigger an FC and to compare the proportion of patients receiving further fluid administration based on the response to the FC.This was an observational study conducted in ICUs around the world. Each participating unit entered a maximum of 20 patients with one FC.2213 patients were enrolled and analyzed in the study. The median [interquartile range] amount of fluid given during an FC was 500 ml (500-1000). The median time was 24 min (40-60 min), and the median rate of FC was 1000 [500-1333] ml/h. The main indication for FC was hypotension in 1211 (59 %, CI 57-61 %). In 43 % (CI 41-45 %) of the cases no hemodynamic variable was used. Static markers of preload were used in 785 of 2213 cases (36 %, CI 34-37 %). Dynamic indices of preload responsiveness were used in 483 of 2213 cases (22 %, CI 20-24 %). No safety variable for the FC was used in 72 % (CI 70-74 %) of the cases. There was no statistically significant difference in the proportion of patients who received further fluids after the FC between those with a positive, with an uncertain or with a negatively judged response.The current practice and evaluation of FC in critically ill patients are highly variable. Prediction of fluid responsiveness is not used routinely, safety limits are rarely used, and information from previous failed FCs is not always taken into account

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Prognosis and antibody profiles in survivors of critical illness from COVID-19: a prospective multicentre cohort study.

BACKGROUND: There is a need to assess the long-term outcomes of survivors of critical illness from COVID-19. METHODS: Ninety-two survivors of critical illness from COVID-19 from four hospitals in Hubei Province, China participated in this prospective cohort study. Multiple characteristics, including lung function (lung volumes, diffusing capacity for carbon monoxide, chest computed tomography scores, and walking capacity); immune status (SARS-CoV-2-neutralising antibody and all subtypes of immunoglobulin (Ig) G against SARS-CoV-2, immune cells in response to ex vivo antigen peptide stimuli, and lymphocyte count and its subtypes); liver, coagulation, and kidney functions; quality of life; cognitive function; and mental status, were assessed after 3, 6, and 12 months of follow-up. RESULTS: Amongst the 92 enrolled survivors, 72 (78%) patients required mechanical ventilation. At 12 months, the predicted percentage diffusing capacity of lung for carbon monoxide was 82% (inter-quartile range [IQR]: 76-97%) with a residual volume of 77 (64-88)%. Other lung function parameters and the 6-min walk test improved gradually over time and were almost back to normal by 12 months. The titres of IgG and neutralising antibody to COVID-19 remained high at 12 months compared with those of controls who were not infected with COVID-19, although IgG titres decreased significantly from 34.0 (IQR: 23.8-74.3) to 15.0 (5.8-24.3) AU ml-1 (P<0.001), whereas neutralising antibodies decreased from 29.99 (IQR: 19.43-53.93) AU ml-1 at 6 months to 19.75 (13.1-29.8) AU ml-1 (P<0.001) at 12 months. In general, liver, kidney, physical, and mental functions also improved over time. CONCLUSIONS: Survivors of critical illness from COVID-19 show some persistent long-term impairments in lung function. However, a majority of these tests were normal by 12 months. These patients still had detectable levels of neutralising antibodies against SARS-CoV-2 and all types of IgG at 12 months, but the levels had declined over this time period. CLINICAL TRIAL REGISTRATION: None