An immune-protein score combining TRAIL, IP-10 and CRP for predicting severe COVID-19 disease.

COVID-19 patients are oftentimes over- or under-treated due to a deficit in predictive management tools. This study reports derivation of an algorithm that integrates the host levels of TRAIL, IP-10, and CRP into a single numeric score that is an early indicator of severe outcome for COVID-19 patients and can identify patients at-risk to deteriorate. 394 COVID-19 patients were eligible; 29% meeting a severe outcome (intensive care unit admission/non-invasive or invasive ventilation/death). The score's area under the receiver operating characteristic curve (AUC) was 0.86, superior to IL-6 (AUC 0.77; p = 0.033) and CRP (AUC 0.78; p < 0.001). Likelihood of severe outcome increased significantly (p < 0.001) with higher scores. The score differentiated severe patients who further deteriorated from those who improved (p = 0.004) and projected 14-day survival probabilities (p < 0.001). The score accurately predicted COVID-19 patients at-risk for severe outcome, and therefore has potential to facilitate timely care escalation and de-escalation and appropriate resource allocation.

The role of omega-3 polyunsaturated fatty acids in the intensive care unit.

PURPOSE OF REVIEW: This review provides an update on the actions of omega-3 polyunsaturated fatty acids (PUFAs) and presents the most recent findings from trials in patients in the intensive care unit (ICU) setting including relevant meta-analyses. Many specialized pro-resolving mediators (SPMs) are produced from bioactive omega-3 PUFAs and may explain many of the beneficial effects of omega-3 PUFAs, although other mechanisms of action of omega-3 PUFAs are being uncovered. RECENT FINDINGS: SPMs resolve inflammation, promote healing and support antiinfection activities of the immune system. Since publication of the ESPEN guidelines, numerous studies further support the use of omega-3 PUFAs. Recent meta-analyses favor the inclusion of omega-3 PUFAs in nutrition support of patients with acute respiratory distress syndrome or sepsis. Recent trials indicate that omega-3 PUFAs may protect against delirium and liver dysfunction in patients in the ICU, although effects on muscle loss are unclear and require further investigation. Critical illness may alter omega-3 PUFA turnover. There has been significant discussion about the potential for omega-3 PUFAs and SPMs in treatment of coronavirus disease 2019. SUMMARY: Evidence for benefits of omega-3 PUFAs in the ICU setting has strengthened through new trials and meta-analyses. Nevertheless, better quality trials are still needed. SPMs may explain many of the benefits of omega-3 PUFAs.

Nutritional and metabolic management of COVID-19 intensive care patients.

Nutritional and metabolic disturbances are observed in patients critically ill with Coronavirus disease 19 (COVID-19) patients. The aim of this review is to describe these disturbances during the progression of the disease, from the pre-intubation phase through the ventilated condition to the post extubation phase. The analysis of new data describing the prevalence of malnutrition, the modifications in energy expenditure and body composition are guiding medical nutritional therapy to prevent patients from experiencing severe energy deficit and muscle loss. Rehabilitation may be extremely prolonged and therefore, nutrition is mandatory to decrease this recondition period. This review also comments on the European Society of Parenteral and Enteral Nutrition (ESPEN) nutritional statements.

Transient diabetes insipidus in critically ill COVID19 patients.

PURPOSE: Vasopressin has become an important vasopressor drug while treating a critically ill patient to maintain adequate mean arterial pressure. Diabetes insipidus (DI) is a rare syndrome characterized by the excretion of a large volume of diluted urine, inappropriate for water homeostasis. We noticed that several COVID19 patients developed excessive polyuria suggestive of DI, with a concomitant plasma sodium-level increase and/or low urine osmolality. We noticed a temporal relationship between vasopressin treatment cessation and polyuria periods. We reviewed those cases to better describe this phenomenon. METHODS: We retrospectively collected COVID19 ECMO patients' (from July 6, 2020, to November 30, 2021) data from the electronic medical records. By examining urine output, urine osmolality (if applicable), plasma sodium level, and plasma osmolality, we set DI diagnosis. We described the clinical course of DI episodes and compared baseline characteristics between patients who developed DI and those who did not. RESULTS: Out of 37 patients, 12 had 18 episodes of DI. These patients were 7 years younger and had lower severity scores (APACHE-II and SOFA). Mortality difference was not seen between groups. 17 episodes occurred after vasopressin discontinuation; 14 episodes were treated with vasopressin reinstitution. DI lasted for a median of 21 h, with a median increase of 14 mEq/L of sodium. CONCLUSIONS: Temporary DI prevalence after vasopressin discontinuation in COVID19 ECMO patients might be higher than previously described for vasopressin-treated patients.

A novel machine learning model to predict respiratory failure and invasive mechanical ventilation in critically ill patients suffering from COVID-19.

In hypoxemic patients at risk for developing respiratory failure, the decision to initiate invasive mechanical ventilation (IMV) may be extremely difficult, even more so among patients suffering from COVID-19. Delayed recognition of respiratory failure may translate into poor outcomes, emphasizing the need for stronger predictive models for IMV necessity. We developed a two-step model; the first step was to train a machine learning predictive model on a large dataset of non-COVID-19 critically ill hypoxemic patients from the United States (MIMIC-III). The second step was to apply transfer learning and adapt the model to a smaller COVID-19 cohort. An XGBoost algorithm was trained on data from the MIMIC-III database to predict if a patient would require IMV within the next 6, 12, 18 or 24 h. Patients' datasets were used to construct the model as time series of dynamic measurements and laboratory results obtained during the previous 6 h with additional static variables, applying a sliding time-window once every hour. We validated the adaptation algorithm on a cohort of 1061 COVID-19 patients from a single center in Israel, of whom 160 later deteriorated and required IMV. The new XGBoost model for the prediction of the IMV onset was trained and tested on MIMIC-III data and proved to be predictive, with an AUC of 0.83 on a shortened set of features, excluding the clinician's settings, and an AUC of 0.91 when the clinician settings were included. Applying these models "as is" (no adaptation applied) on the dataset of COVID-19 patients degraded the prediction results to AUCs of 0.78 and 0.80, without and with the clinician's settings, respectively. Applying the adaptation on the COVID-19 dataset increased the prediction power to an AUC of 0.94 and 0.97, respectively. Good AUC results get worse with low overall precision. We show that precision of the prediction increased as prediction probability was higher. Our model was successfully trained on a specific dataset, and after adaptation it showed promise in predicting outcome on a completely different dataset. This two-step model successfully predicted the need for invasive mechanical ventilation 6, 12, 18 or 24 h in advance in both general ICU population and COVID-19 patients. Using the prediction probability as an indicator of the precision carries the potential to aid the decision-making process in patients with hypoxemic respiratory failure despite the low overall precision.

Nutritional management of individuals with obesity and COVID-19: ESPEN expert statements and practical guidance.

The COVID-19 pandemics has created unprecedented challenges and threats to patients and healthcare systems worldwide. Acute respiratory complications that require intensive care unit (ICU) management are a major cause of morbidity and mortality in COVID-19 patients. Among other important risk factors for severe COVID-19 outcomes, obesity has emerged along with undernutrition-malnutrition as a strong predictor of disease risk and severity. Obesity-related excessive body fat may lead to respiratory, metabolic and immune derangements potentially favoring the onset of COVID-19 complications. In addition, patients with obesity may be at risk for loss of skeletal muscle mass, reflecting a state of hidden malnutrition with a strong negative health impact in all clinical settings. Also importantly, obesity is commonly associated with micronutrient deficiencies that directly influence immune function and infection risk. Finally, the pandemic-related lockdown, deleterious lifestyle changes and other numerous psychosocial consequences may worsen eating behaviors, sedentarity, body weight regulation, ultimately leading to further increments of obesity-associated metabolic complications with loss of skeletal muscle mass and higher non-communicable disease risk. Therefore, prevention, diagnosis and treatment of malnutrition and micronutrient deficiencies should be routinely included in the management of COVID-19 patients in the presence of obesity; lockdown-induced health risks should also be specifically monitored and prevented in this population. In the current document, the European Society for Clinical Nutrition and Metabolism (ESPEN) aims at providing clinical practice guidance for nutritional management of COVID-19 patients with obesity in various clinical settings.

Practical guidance for the use of indirect calorimetry during COVID 19 pandemic.

The daily practice requires the use of indirect calorimetry to define the energy requirements of intensive care patients. In the time of COVID-19 pandemic, this practice is challenging. The purpose of this methodology paper is to provide practical guidance to health professionals to perform this measurement safely, using various metabolic monitors.

Nutrition of the COVID-19 patient in the intensive care unit (ICU): a practical guidance.

Five to 10% of the coronavirus SARS-CoV-2-infected patients, i.e., with new coronavirus disease 2019 (COVID-19), are presenting with an acute respiratory distress syndrome (ARDS) requiring urgent respiratory and hemodynamic support in the intensive care unit (ICU). However, nutrition is an important element of care. The nutritional assessment and the early nutritional care management of COVID-19 patients must be integrated into the overall therapeutic strategy. The international recommendations on nutrition in the ICU should be followed. Some specific issues about the nutrition of the COVID-19 patients in the ICU should be emphasized. We propose a flow chart and ten key issues for optimizing the nutrition management of COVID-19 patients in the ICU.

Clinical Course and Outcomes of Severe Covid-19: A National Scale Study

Knowledge of the outcomes of critically ill patients is crucial for health and government officials who are planning how to address local outbreaks. The factors associated with outcomes of critically ill patients with coronavirus disease 2019 (Covid-19) who required treatment in an intensive care unit (ICU) are yet to be determined. Methods: This was a retrospective registry-based case series of patients with laboratory-confirmed SARS-CoV-2 who were referred for ICU admission and treated in the ICUs of the 13 participating centers in Israel between 5 March and 27 April 2020. Demographic and clinical data including clinical management were collected and subjected to a multivariable analysis;primary outcome was mortality. Results: This study included 156 patients (median age = 72 years (range = 22-97 years));69% (108 of 156) were male. Eighty-nine percent (139 of 156) of patients had at least one comorbidity. One hundred three patients (66%) required invasive mechanical ventilation. As of 8 May 2020, the median length of stay in the ICU was 10 days (range = 0-37 days). The overall mortality rate was 56%;a multivariable regression model revealed that increasing age (OR = 1.08 for each year of age, 95%CI = 1.03-1.13), the presence of sepsis (OR = 1.08 for each year of age, 95%CI = 1.03-1.13), and a shorter ICU stay(OR = 0.90 for each day, 95% CI = 0.84-0.96) were independent prognostic factors. Conclusions: In our case series, we found lower mortality rates than those in exhausted health systems. The results of our multivariable model suggest that further evaluation is needed of antiviral and antibacterial agents in the treatment of sepsis and secondary infection.