Use of Intravenous Albumin: A Guideline From the International Collaboration for Transfusion Medicine Guidelines.

BACKGROUND: Albumin is used commonly across a wide range of clinical settings to improve hemodynamics, to facilitate fluid removal, and to manage complications of cirrhosis. The International Collaboration for Transfusion Medicine Guidelines developed guidelines for the use of albumin in patients requiring critical care, undergoing cardiovascular surgery, undergoing kidney replacement therapy, or experiencing complications of cirrhosis. METHODS: Cochairs oversaw the guideline development process and the panel included researchers, clinicians, methodologists, and a patient representative. The evidence informing this guideline arises from a systematic review of randomized clinical trials and systematic reviews, in which multiple databases were searched (inception through November 23, 2022). The panel reviewed the data and formulated the guideline recommendations using Grading of Recommendations Assessment, Development and Evaluation methodology. The guidelines were revised after public consultation. RESULTS: The panel made 14 recommendations on albumin use in adult critical care (three recommendations), pediatric critical care (one recommendation), neonatal critical care (two recommendations), cardiovascular surgery (two recommendations), kidney replacement therapy (one recommendation), and complications of cirrhosis (five recommendations). Of the 14 recommendations, two recommendations had moderate certainty of evidence, five recommendations had low certainty of evidence, and seven recommendations had very low certainty of evidence. Two of the 14 recommendations suggested conditional use of albumin for patients with cirrhosis undergoing large-volume paracentesis or with spontaneous bacterial peritonitis. Twelve of 14 recommendations did not suggest albumin use in a wide variety of clinical situations where albumin commonly is transfused. CONCLUSIONS: Currently, few evidence-based indications support the routine use of albumin in clinical practice to improve patient outcomes. These guidelines provide clinicians with actionable recommendations on the use of albumin.

Association between first-week propofol administration and long-term outcomes of critically ill mechanically ventilated patients: A retrospective cohort study.

BACKGROUND & AIM: Propofol is commonly used in ICUs, but its long-term effects have not been thoroughly studied. In vitro studies suggest it may harm mitochondrial function, potentially affecting clinical outcomes. This study aimed to investigate the association between substantial propofol sedation and clinical outcomes in critically ill patients. METHODS: We conducted a single-centre cohort study of critically ill, mechanically ventilated (≥7 days) adults to compare patients who received a substantial dose of propofol (cumulative >500 mg) during the first week of ICU admission with those who did not. The primary outcome was the association between substantial propofol administration and 6-month mortality, adjusted for relevant covariates. Subanalyses were performed for administration in the early (day 1-3) and late (day 4-7) acute phases of critical illness due to the metabolic changes in this period. Secondary outcomes included tracheostomy need and duration, length of ICU and hospital stay (LOS), discharge destinations, ICU, hospital, and 3-month mortality. RESULTS: A total of 839 patients were enrolled, with 73.7 % receiving substantial propofol administration (substantial propofol dose group). Six-month all-cause mortality was 32.4 %. After adjusting for relevant variables, we found no statistically significant difference in 6-month mortality between both groups. There were also no significant differences in secondary outcomes. CONCLUSION: Our study suggests that substantial propofol administration during the first week of ICU stay in the least sick critically ill, mechanically ventilated adult patients is safe, with no significant associations found with 6-month mortality, ICU or hospital LOS, differences in discharge destinations or need for tracheostomy.

Rapid Response to Remdesivir in Hospitalised COVID-19 Patients: A Propensity Score Weighted Multicentre Cohort Study.

INTRODUCTION: Remdesivir is a registered treatment for hospitalised patients with COVID-19 that has moderate clinical effectiveness. Anecdotally, some patients' respiratory insufficiency seemed to recover particularly rapidly after initiation of remdesivir. In this study, we investigated if this rapid improvement was caused by remdesivir, and which patient characteristics might predict a rapid clinical improvement in response to remdesivir. METHODS: This was a multicentre observational cohort study of hospitalised patients with COVID-19 who required supplemental oxygen and were treated with dexamethasone. Rapid clinical improvement in response to treatment was defined by a reduction of at least 1 L of supplemental oxygen per minute or discharge from the hospital within 72 h after admission. Inverse probability of treatment-weighted logistic regression modelling was used to assess the association between remdesivir and rapid clinical improvement. Secondary endpoints included in-hospital mortality, ICU admission rate and hospitalisation duration. RESULTS: Of 871 patients included, 445 were treated with remdesivir. There was no influence of remdesivir on the occurrence of rapid clinical improvement (62% vs 61% OR 1.05, 95% CI 0.79-1.40; p = 0.76). The in-hospital mortality was lower (14.7% vs 19.8% OR 0.70, 95% CI 0.48-1.02; p = 0.06) for the remdesivir-treated patients. Rapid clinical improvement occurred more often in patients with low C-reactive protein (≤ 75 mg/L) and short duration of symptoms prior to hospitalisation (< 7 days) (OR 2.84, 95% CI 1.07-7.56). CONCLUSION: Remdesivir generally does not increase the incidence of rapid clinical improvement in hospitalised patients with COVID-19, but it might have an effect in patients with short duration of symptoms and limited signs of systemic inflammation.

Macronutrient intake and outcomes of ICU patients with refeeding hypophosphatemia.

BACKGROUND: Normocaloric vs. calorie-restricted feeding in Intensive Care Unit (ICU) patients with refeeding hypophosphatemia (RH) is associated with increased mortality rates. Until now, only total energy provision has been studied. Data on individual macronutrients (proteins, lipids, and carbohydrates) and clinical outcomes are lacking. This study evaluates associations between macronutrient intake among RH patients during the first week of ICU admission and clinical outcomes. METHODS: A single-centre retrospective observational cohort study was conducted among prolonged mechanically ventilated RH ICU patients. The primary outcome was the association of separate macronutrient intakes during the first week of ICU admission with 6-month mortality, adjusted for relevant variables. Other parameters included ICU-, hospital- and 3-month mortality, mechanical ventilation duration and length of ICU and hospital stay. Macronutrient intakes were subsequently analyzed during day 1-3 and day 4-7 of ICU admission. RESULTS: In total, 178 RH patients were included. Six-month all-cause mortality was 29.8%. Higher protein intake during days 1-3 of ICU admission (>0.71 g/kg∗day; HR 2.224, 95%CI 1.261-3.923, p = 0.006), higher age (HR 1.040, 95%CI 1.015-1.066, p = 0.002) and higher APACHE II scores on ICU admission (HR 1.086, 95%CI 1.034-1.140, p = 0.001) were associated with increased 6-month mortality. No differences in other outcomes were observed. CONCLUSION: High protein - not carbohydrate or lipid - intake during the first three days of ICU admission in patients with RH is associated with increased 6-month mortality, but not short-term outcomes. We hypothesize a time-dependent and dose-response relationship between protein intake and mortality in refeeding hypophosphatemia ICU patients, although additional (randomized controlled) studies are needed to confirm this hypothesis.

Identifying and Predicting Postoperative Infections Based on Readily Available Electronic Health Record Data.

Identification of postoperative infections based on retrospective patient data is currently done using manual chart review. We used a validated, automated labelling method based on registrations and treatments to develop a high-quality prediction model (AUC 0.81) for postoperative infections.

Platelet Transfusion before CVC Placement in Patients with Thrombocytopenia.

BACKGROUND: Transfusion guidelines regarding platelet-count thresholds before the placement of a central venous catheter (CVC) offer conflicting recommendations because of a lack of good-quality evidence. The routine use of ultrasound guidance has decreased CVC-related bleeding complications. METHODS: In a multicenter, randomized, controlled, noninferiority trial, we randomly assigned patients with severe thrombocytopenia (platelet count, 10,000 to 50,000 per cubic millimeter) who were being treated on the hematology ward or in the intensive care unit to receive either one unit of prophylactic platelet transfusion or no platelet transfusion before ultrasound-guided CVC placement. The primary outcome was catheter-related bleeding of grade 2 to 4; a key secondary outcome was grade 3 or 4 bleeding. The noninferiority margin was an upper boundary of the 90% confidence interval of 3.5 for the relative risk. RESULTS: We included 373 episodes of CVC placement involving 338 patients in the per-protocol primary analysis. Catheter-related bleeding of grade 2 to 4 occurred in 9 of 188 patients (4.8%) in the transfusion group and in 22 of 185 patients (11.9%) in the no-transfusion group (relative risk, 2.45; 90% confidence interval [CI], 1.27 to 4.70). Catheter-related bleeding of grade 3 or 4 occurred in 4 of 188 patients (2.1%) in the transfusion group and in 9 of 185 patients (4.9%) in the no-transfusion group (relative risk, 2.43; 95% CI, 0.75 to 7.93). A total of 15 adverse events were observed; of these events, 13 (all grade 3 catheter-related bleeding [4 in the transfusion group and 9 in the no-transfusion group]) were categorized as serious. The net savings of withholding prophylactic platelet transfusion before CVC placement was $410 per catheter placement. CONCLUSIONS: The withholding of prophylactic platelet transfusion before CVC placement in patients with a platelet count of 10,000 to 50,000 per cubic millimeter did not meet the predefined margin for noninferiority and resulted in more CVC-related bleeding events than prophylactic platelet transfusion. (Funded by ZonMw; PACER Dutch Trial Register number, NL5534.).

A simulation of skin mitochondrial Po2 in circulatory shock.

Circulatory shock is the inadequacy to supply mitochondria with enough oxygen to sustain aerobic energy metabolism. A novel noninvasive bedside measurement was recently introduced to monitor the mitochondrial oxygen tension in the skin (mitoPo2). As the most downstream marker of oxygen balance in the skin, mitoPo2 may provide additional information to improve shock management. However, a physiological basis for the interpretation of mitoPo2 values has not been established yet. In this paper, we developed a mathematical model of skin mitoPo2 using a network of parallel microvessels, based on Krogh's cylinder model. The model contains skin blood flow velocity, heterogeneity of blood flow, hematocrit, arteriolar oxygen saturation, and mitochondrial oxygen consumption as major variables. The major results of the model show that normal physiological mitoPo2 is in the range of 40-60 mmHg. The relationship of mitoPo2 with skin blood flow velocity follows a logarithmic growth curve, reaching a plateau at high skin blood flow velocity, suggesting that oxygen balance remains stable while peripheral perfusion declines. The model shows that a critical range exists where mitoPo2 rapidly deteriorates if skin perfusion further decreases. The model intuitively shows how tissue hypoxia could occur in the setting of septic shock, due to the profound impact of microcirculatory disturbance on mitoPo2, even at sustained cardiac output. MitoPo2 is the result of a complex interaction between all factors of oxygen delivery and microcirculation. This mathematical framework can be used to interpret mitoPo2 values in shock, with the potential to enhance personalized clinical trial design.NEW & NOTEWORTHY This is the first paper to simulate mitochondrial oxygen tension in skin in circulatory shock. The relationships of mitoPo2 with parameters of (microcirculatory) oxygen delivery aid in the understanding of noninvasive bedside measurement of mitoPo2 values and show that mitochondrial oxygen tension is two orders of magnitude higher than classically assumed. The model can be used to enhance clinical trial design investigating mitoPo2 as a resuscitation target in circulatory shock.

Microcirculatory alterations in critically ill COVID-19 patients analyzed using artificial intelligence.

BACKGROUND: The sublingual microcirculation presumably exhibits disease-specific changes in function and morphology. Algorithm-based quantification of functional microcirculatory hemodynamic variables in handheld vital microscopy (HVM) has recently allowed identification of hemodynamic alterations in the microcirculation associated with COVID-19. In the present study we hypothesized that supervised deep machine learning could be used to identify previously unknown microcirculatory alterations, and combination with algorithmically quantified functional variables increases the model's performance to differentiate critically ill COVID-19 patients from healthy volunteers. METHODS: Four international, multi-central cohorts of critically ill COVID-19 patients and healthy volunteers (n = 59/n = 40) were used for neuronal network training and internal validation, alongside quantification of functional microcirculatory hemodynamic variables. Independent verification of the models was performed in a second cohort (n = 25/n = 33). RESULTS: Six thousand ninety-two image sequences in 157 individuals were included. Bootstrapped internal validation yielded AUROC(CI) for detection of COVID-19 status of 0.75 (0.69-0.79), 0.74 (0.69-0.79) and 0.84 (0.80-0.89) for the algorithm-based, deep learning-based and combined models. Individual model performance in external validation was 0.73 (0.71-0.76) and 0.61 (0.58-0.63). Combined neuronal network and algorithm-based identification yielded the highest externally validated AUROC of 0.75 (0.73-0.78) (P < 0.0001 versus internal validation and individual models). CONCLUSIONS: We successfully trained a deep learning-based model to differentiate critically ill COVID-19 patients from heathy volunteers in sublingual HVM image sequences. Internally validated, deep learning was superior to the algorithmic approach. However, combining the deep learning method with an algorithm-based approach to quantify the functional state of the microcirculation markedly increased the sensitivity and specificity as compared to either approach alone, and enabled successful external validation of the identification of the presence of microcirculatory alterations associated with COVID-19 status.

Predicting responders to prone positioning in mechanically ventilated patients with COVID-19 using machine learning.

BACKGROUND: For mechanically ventilated critically ill COVID-19 patients, prone positioning has quickly become an important treatment strategy, however, prone positioning is labor intensive and comes with potential adverse effects. Therefore, identifying which critically ill intubated COVID-19 patients will benefit may help allocate labor resources. METHODS: From the multi-center Dutch Data Warehouse of COVID-19 ICU patients from 25 hospitals, we selected all 3619 episodes of prone positioning in 1142 invasively mechanically ventilated patients. We excluded episodes longer than 24 h. Berlin ARDS criteria were not formally documented. We used supervised machine learning algorithms Logistic Regression, Random Forest, Naive Bayes, K-Nearest Neighbors, Support Vector Machine and Extreme Gradient Boosting on readily available and clinically relevant features to predict success of prone positioning after 4 h (window of 1 to 7 h) based on various possible outcomes. These outcomes were defined as improvements of at least 10% in PaO2/FiO2 ratio, ventilatory ratio, respiratory system compliance, or mechanical power. Separate models were created for each of these outcomes. Re-supination within 4 h after pronation was labeled as failure. We also developed models using a 20 mmHg improvement cut-off for PaO2/FiO2 ratio and using a combined outcome parameter. For all models, we evaluated feature importance expressed as contribution to predictive performance based on their relative ranking. RESULTS: The median duration of prone episodes was 17 h (11-20, median and IQR, N = 2632). Despite extensive modeling using a plethora of machine learning techniques and a large number of potentially clinically relevant features, discrimination between responders and non-responders remained poor with an area under the receiver operator characteristic curve of 0.62 for PaO2/FiO2 ratio using Logistic Regression, Random Forest and XGBoost. Feature importance was inconsistent between models for different outcomes. Notably, not even being a previous responder to prone positioning, or PEEP-levels before prone positioning, provided any meaningful contribution to predicting a successful next proning episode. CONCLUSIONS: In mechanically ventilated COVID-19 patients, predicting the success of prone positioning using clinically relevant and readily available parameters from electronic health records is currently not feasible. Given the current evidence base, a liberal approach to proning in all patients with severe COVID-19 ARDS is therefore justified and in particular regardless of previous results of proning.

Immune Determinants of Viral Clearance in Hospitalised COVID-19 Patients: Reduced Circulating Naïve CD4+ T Cell Counts Correspond with Delayed Viral Clearance.

Virus-specific cellular and humoral responses are major determinants for protection from critical illness after SARS-CoV-2 infection. However, the magnitude of the contribution of each of the components to viral clearance remains unclear. Here, we studied the timing of viral clearance in relation to 122 immune parameters in 102 hospitalised patients with moderate and severe COVID-19 in a longitudinal design. Delayed viral clearance was associated with more severe disease and was associated with higher levels of SARS-CoV-2-specific (neutralising) antibodies over time, increased numbers of neutrophils, monocytes, basophils, and a range of pro-inflammatory cyto-/chemokines illustrating ongoing, partially Th2 dominating, immune activation. In contrast, early viral clearance and less critical illness correlated with the peak of neutralising antibodies, higher levels of CD4 T cells, and in particular naïve CD4+ T cells, suggesting their role in early control of SARS-CoV-2 possibly by proving appropriate B cell help. Higher counts of naïve CD4+ T cells also correlated with lower levels of MIF, IL-9, and TNF-beta, suggesting an indirect role in averting prolonged virus-induced tissue damage. Collectively, our data show that naïve CD4+ T cell play a critical role in rapid viral T cell control, obviating aberrant antibody and cytokine profiles and disease deterioration. These data may help in guiding risk stratification for severe COVID-19.

INCIDENCE, RISK FACTORS, AND OUTCOME OF SUSPECTED CENTRAL VENOUS CATHETER-RELATED INFECTIONS IN CRITICALLY ILL COVID-19 PATIENTS: A MULTICENTER RETROSPECTIVE COHORT STUDY.

ABSTRACT: Background: Aims of this study were to investigate the prevalence and incidence of catheter-related infection, identify risk factors, and determine the relation of catheter-related infection with mortality in critically ill COVID-19 patients. Methods: This was a retrospective cohort study of central venous catheters (CVCs) in critically ill COVID-19 patients. Eligible CVC insertions required an indwelling time of at least 48 hours and were identified using a full-admission electronic health record database. Risk factors were identified using logistic regression. Differences in survival rates at day 28 of follow-up were assessed using a log-rank test and proportional hazard model. Results: In 538 patients, a total of 914 CVCs were included. Prevalence and incidence of suspected catheter-related infection were 7.9% and 9.4 infections per 1,000 catheter indwelling days, respectively. Prone ventilation for more than 5 days was associated with increased risk of suspected catheter-related infection; odds ratio, 5.05 (95% confidence interval 2.12-11.0). Risk of death was significantly higher in patients with suspected catheter-related infection (hazard ratio, 1.78; 95% confidence interval, 1.25-2.53). Conclusions: This study shows that in critically ill patients with COVID-19, prevalence and incidence of suspected catheter-related infection are high, prone ventilation is a risk factor, and mortality is higher in case of catheter-related infection.

Assess and validate predictive performance of models for in-hospital mortality in COVID-19 patients: A retrospective cohort study in the Netherlands comparing the value of registry data with high-granular electronic health records.

PURPOSE: To assess, validate and compare the predictive performance of models for in-hospital mortality of COVID-19 patients admitted to the intensive care unit (ICU) over two different waves of infections. Our models were built with high-granular Electronic Health Records (EHR) data versus less-granular registry data. METHODS: Observational study of all COVID-19 patients admitted to 19 Dutch ICUs participating in both the national quality registry National Intensive Care Evaluation (NICE) and the EHR-based Dutch Data Warehouse (hereafter EHR). Multiple models were developed on data from the first 24 h of ICU admissions from February to June 2020 (first COVID-19 wave) and validated on prospective patients admitted to the same ICUs between July and December 2020 (second COVID-19 wave). We assessed model discrimination, calibration, and the degree of relatedness between development and validation population. Coefficients were used to identify relevant risk factors. RESULTS: A total of 1533 patients from the EHR and 1563 from the registry were included. With high granular EHR data, the average AUROC was 0.69 (standard deviation of 0.05) for the internal validation, and the AUROC was 0.75 for the temporal validation. The registry model achieved an average AUROC of 0.76 (standard deviation of 0.05) in the internal validation and 0.77 in the temporal validation. In the EHR data, age, and respiratory-system related variables were the most important risk factors identified. In the NICE registry data, age and chronic respiratory insufficiency were the most important risk factors. CONCLUSION: In our study, prognostic models built on less-granular but readily-available registry data had similar performance to models built on high-granular EHR data and showed similar transportability to a prospective COVID-19 population. Future research is needed to verify whether this finding can be confirmed for upcoming waves.

Development and validation of an early warning model for hospitalized COVID-19 patients: a multi-center retrospective cohort study.

BACKGROUND: Timely identification of deteriorating COVID-19 patients is needed to guide changes in clinical management and admission to intensive care units (ICUs). There is significant concern that widely used Early warning scores (EWSs) underestimate illness severity in COVID-19 patients and therefore, we developed an early warning model specifically for COVID-19 patients. METHODS: We retrospectively collected electronic medical record data to extract predictors and used these to fit a random forest model. To simulate the situation in which the model would have been developed after the first and implemented during the second COVID-19 'wave' in the Netherlands, we performed a temporal validation by splitting all included patients into groups admitted before and after August 1, 2020. Furthermore, we propose a method for dynamic model updating to retain model performance over time. We evaluated model discrimination and calibration, performed a decision curve analysis, and quantified the importance of predictors using SHapley Additive exPlanations values. RESULTS: We included 3514 COVID-19 patient admissions from six Dutch hospitals between February 2020 and May 2021, and included a total of 18 predictors for model fitting. The model showed a higher discriminative performance in terms of partial area under the receiver operating characteristic curve (0.82 [0.80-0.84]) compared to the National early warning score (0.72 [0.69-0.74]) and the Modified early warning score (0.67 [0.65-0.69]), a greater net benefit over a range of clinically relevant model thresholds, and relatively good calibration (intercept = 0.03 [- 0.09 to 0.14], slope = 0.79 [0.73-0.86]). CONCLUSIONS: This study shows the potential benefit of moving from early warning models for the general inpatient population to models for specific patient groups. Further (independent) validation of the model is needed.

Incidence of transfusion-related acute lung injury temporally associated with solvent/detergent plasma use in the ICU: A retrospective before and after implementation study.

BACKGROUND: Transfusion-related acute lung injury (TRALI) is a severe complication of plasma transfusion, though the use of solvent/detergent pooled plasma (SDP) has nearly eliminated reported TRALI cases. The goal of this study was to investigate the incidence of TRALI in intensive care units (ICU) following the replacement of quarantined fresh frozen plasma (qFFP) by SDP. STUDY DESIGN AND METHODS: A retrospective multicenter observational before-after cohort study was performed during two 6-month periods, before (April-October 2014) and after the introduction of SDP (April-October 2015), accounting for a washout period. A full chart review was performed for patients who received ≥1 plasma units and developed hypoxemia within 24 h. RESULTS: During the study period, 8944 patients were admitted to the ICU. Exactly 1171 quarantine fresh frozen plasma (qFFP) units were transfused in 376 patients, and respectively, 2008 SDP units to 396 patients after implementation. Ten TRALI cases occurred during the qFFP and nine cases occurred during the SDP period, in which plasma was transfused. The incidence was 0.85% (CI95%: 0.33%-1.4%) per unit qFFP and 0.45% (CI95%: 0.21%-0.79%, p = 0.221) per SDP unit. One instance of TRALI occurred after a single SDP unit. Mortality was 70% for patients developing TRALI in the ICU compared with 22% in patients receiving at least one plasma transfusion. CONCLUSION: Implementation of SDP lowered the incidence of TRALI in which plasma products were implicated, though not significantly. Clinically diagnosed TRALI can still occur following SDP transfusion. Developing TRALI in the ICU was associated with high mortality rates, therefore, clinicians should remain vigilant.

Predicting organ functioning with and without blood transfusion in critically ill patients with anemia.

BACKGROUND: To develop a model for the prediction of the (most likely) effect of red blood cell (RBC) transfusion on subsequent organ functioning in nonbleeding critically ill patients with hemoglobin concentrations between 6 and 9 g/dL. STUDY DESIGN AND METHODS: We conducted a retrospective cohort study using electronic health care data of nonbleeding patients admitted between November 2004 and May 2016 at the intensive care unit (ICU) of the Leiden University Medical Center, The Netherlands. We analyzed the associations between transfusion (yes/no) and next-day SOFA scores (Sequential Organ Failure Assessment-as a measure for organ functioning) for all observed combinations of hemoglobin values (between 6 and 9 g/dL) and concurrent clinical variables. RESULTS: Data of 6425 ICU admission of 5756 critically ill patients with 28,702 hemoglobin values between 6 and 9 g/dL (transfusion decision moments) of which 22.1% were followed by a transfusion were analyzed. The adjusted average difference between the next-day SOFA score of transfused versus not-transfused patients was 0.08 (95% confidence interval [CI] -0.03 to 0.18). At singular transfusion decision moments, the score predicted a beneficial effect of transfusion on next-day SOFA score for some subgroups and medical conditions and a harmful effect in other occasions. CONCLUSIONS: Among these critically ill patients with hemoglobin concentrations between 6 and 9 g/dL the population average effect of transfusion on the next SOFA score was negligible. Further, our results support caution in clinical decision-making regarding transfusion of critical ill, nonbleeding ICU patients.

Immunoglobulin G1 Fc glycosylation as an early hallmark of severe COVID-19.

BACKGROUND: Immunoglobulin G1 (IgG1) effector functions are impacted by the structure of fragment crystallizable (Fc) tail-linked N-glycans. Low fucosylation levels on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S) protein-specific IgG1 has been described as a hallmark of severe coronavirus disease 2019 (COVID-19) and may lead to activation of macrophages via immune complexes thereby promoting inflammatory responses, altogether suggesting involvement of IgG1 Fc glycosylation modulated immune mechanisms in COVID-19. METHODS: In this prospective, observational single center cohort study, IgG1 Fc glycosylation was analyzed by liquid chromatography-mass spectrometry following affinity capturing from serial plasma samples of 159 SARS-CoV-2 infected hospitalized patients. FINDINGS: At baseline close to disease onset, anti-S IgG1 glycosylation was highly skewed when compared to total plasma IgG1. A rapid, general reduction in glycosylation skewing was observed during the disease course. Low anti-S IgG1 galactosylation and sialylation as well as high bisection were early hallmarks of disease severity, whilst high galactosylation and sialylation and low bisection were found in patients with low disease severity. In line with these observations, anti-S IgG1 glycosylation correlated with various inflammatory markers. INTERPRETATION: Association of low galactosylation, sialylation as well as high bisection with disease severity and inflammatory markers suggests that further studies are needed to understand how anti-S IgG1 glycosylation may contribute to disease mechanism and to evaluate its biomarker potential. FUNDING: This project received funding from the European Commission's Horizon2020 research and innovation program for H2020-MSCA-ITN IMforFUTURE, under grant agreement number 721815, and supported by Crowdfunding Wake Up To Corona, organized by the Leiden University Fund.

Prolonged activation of nasal immune cell populations and development of tissue-resident SARS-CoV-2-specific CD8+ T cell responses following COVID-19.

Systemic immune cell dynamics during coronavirus disease 2019 (COVID-19) are extensively documented, but these are less well studied in the (upper) respiratory tract, where severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replicates1-6. Here, we characterized nasal and systemic immune cells in individuals with COVID-19 who were hospitalized or convalescent and compared the immune cells to those seen in healthy donors. We observed increased nasal granulocytes, monocytes, CD11c+ natural killer (NK) cells and CD4+ T effector cells during acute COVID-19. The mucosal proinflammatory populations positively associated with peripheral blood human leukocyte antigen (HLA)-DRlow monocytes, CD38+PD1+CD4+ T effector (Teff) cells and plasmablasts. However, there was no general lymphopenia in nasal mucosa, unlike in peripheral blood. Moreover, nasal neutrophils negatively associated with oxygen saturation levels in blood. Following convalescence, nasal immune cells mostly normalized, except for CD127+ granulocytes and CD38+CD8+ tissue-resident memory T cells (TRM). SARS-CoV-2-specific CD8+ T cells persisted at least 2 months after viral clearance in the nasal mucosa, indicating that COVID-19 has both transient and long-term effects on upper respiratory tract immune responses.

Predictors for extubation failure in COVID-19 patients using a machine learning approach.

INTRODUCTION: Determining the optimal timing for extubation can be challenging in the intensive care. In this study, we aim to identify predictors for extubation failure in critically ill patients with COVID-19. METHODS: We used highly granular data from 3464 adult critically ill COVID patients in the multicenter Dutch Data Warehouse, including demographics, clinical observations, medications, fluid balance, laboratory values, vital signs, and data from life support devices. All intubated patients with at least one extubation attempt were eligible for analysis. Transferred patients, patients admitted for less than 24 h, and patients still admitted at the time of data extraction were excluded. Potential predictors were selected by a team of intensive care physicians. The primary and secondary outcomes were extubation without reintubation or death within the next 7 days and within 48 h, respectively. We trained and validated multiple machine learning algorithms using fivefold nested cross-validation. Predictor importance was estimated using Shapley additive explanations, while cutoff values for the relative probability of failed extubation were estimated through partial dependence plots. RESULTS: A total of 883 patients were included in the model derivation. The reintubation rate was 13.4% within 48 h and 18.9% at day 7, with a mortality rate of 0.6% and 1.0% respectively. The grandient-boost model performed best (area under the curve of 0.70) and was used to calculate predictor importance. Ventilatory characteristics and settings were the most important predictors. More specifically, a controlled mode duration longer than 4 days, a last fraction of inspired oxygen higher than 35%, a mean tidal volume per kg ideal body weight above 8 ml/kg in the day before extubation, and a shorter duration in assisted mode (< 2 days) compared to their median values. Additionally, a higher C-reactive protein and leukocyte count, a lower thrombocyte count, a lower Glasgow coma scale and a lower body mass index compared to their medians were associated with extubation failure. CONCLUSION: The most important predictors for extubation failure in critically ill COVID-19 patients include ventilatory settings, inflammatory parameters, neurological status, and body mass index. These predictors should therefore be routinely captured in electronic health records.

Some Patients Are More Equal Than Others: Variation in Ventilator Settings for Coronavirus Disease 2019 Acute Respiratory Distress Syndrome.

OBJECTIVES: As coronavirus disease 2019 is a novel disease, treatment strategies continue to be debated. This provides the intensive care community with a unique opportunity as the population of coronavirus disease 2019 patients requiring invasive mechanical ventilation is relatively homogeneous compared with other ICU populations. We hypothesize that the novelty of coronavirus disease 2019 and the uncertainty over its similarity with noncoronavirus disease 2019 acute respiratory distress syndrome resulted in substantial practice variation between hospitals during the first and second waves of coronavirus disease 2019 patients. DESIGN: Multicenter retrospective cohort study. SETTING: Twenty-five hospitals in the Netherlands from February 2020 to July 2020, and 14 hospitals from August 2020 to December 2020. PATIENTS: One thousand two hundred ninety-four critically ill intubated adult ICU patients with coronavirus disease 2019 were selected from the Dutch Data Warehouse. Patients intubated for less than 24 hours, transferred patients, and patients still admitted at the time of data extraction were excluded. MEASUREMENTS AND MAIN RESULTS: We aimed to estimate between-ICU practice variation in selected ventilation parameters (positive end-expiratory pressure, Fio2, set respiratory rate, tidal volume, minute volume, and percentage of time spent in a prone position) on days 1, 2, 3, and 7 of intubation, adjusted for patient characteristics as well as severity of illness based on Pao2/Fio2 ratio, pH, ventilatory ratio, and dynamic respiratory system compliance during controlled ventilation. Using multilevel linear mixed-effects modeling, we found significant (p ≤ 0.001) variation between ICUs in all ventilation parameters on days 1, 2, 3, and 7 of intubation for both waves. CONCLUSIONS: This is the first study to clearly demonstrate significant practice variation between ICUs related to mechanical ventilation parameters that are under direct control by intensivists. Their effect on clinical outcomes for both coronavirus disease 2019 and other critically ill mechanically ventilated patients could have widespread implications for the practice of intensive care medicine and should be investigated further by causal inference models and clinical trials.

Video-assisted placement of enteral feeding tubes using the Integrated Real-Time Imaging System (IRIS)-technology in critically ill patients.

INTRODUCTION: In critically ill patients, nasogastric (NG) and nasojejunal (NJ) feeding tube placements are standard procedures. However, about 1.9% of blind tube insertions are malpositioned in the tracheopulmonary system, whereas guided procedures may result in a significant delay in nutritional delivery. Guided methods, such as Cortrak and fluoroscopy, have success rates of 82.6-85% and 93% respectively. The current study aims to investigate the performance of video-assisted feeding tube placement in the post-pyloric position using Integrated Real Time Imaging System (IRIS-) technology. METHODS: A prospective cohort study in patients requiring enteral feeding was conducted in a mixed medical-surgical intensive care unit (ICU). The primary outcome was the post-pyloric placement of IRIS feeding tubes, as confirmed by X-ray. Secondary study objectives included gastric placement, ease of use and adverse events. RESULTS: Thirty-one feeding tubes were placed using IRIS-technology; one patient was excluded for analysis due to protocol violation. One procedure was terminated due to significant bleeding (epistaxis) and desaturation. Only eighteen (58%) feeding tubes were placed in post-pyloric position (including two past the ligament of Treitz). In subjects who needed post-pyloric placement due gastroparesis, IRIS was mostly unsuccessful (success rate of 25%). However, when gastric placement was the primary objective, 96.8% of tubes were correctly placed. During insertion, tracheal visualization occurred in 27% of cases, and the IRIS feeding tube was repositioned early in the procedure without causing patient harm. CONCLUSIONS: Real-time video-assisted post-pyloric feeding tube placement in critically ill ICU patients was only successful in 58% of cases and therefore currently cannot be recommended for this indication. However, a high success rate (96.8%) for gastric placement was achieved. IRIS tube placement detected tracheal misplacement immediately and had few adverse events.