Background: Critically ill patients with COVID-19 are prone to develop severe acute kidney injury (AKI), defined as KDIGO (Kidney Disease Improving Global Outcomes) stages 2 or 3. However, data are limited in these patients. We aimed to report the incidence, risk factors, and prognostic impact of severe AKI in critically ill patients with COVID-19 admitted to the intensive care unit (ICU) for acute respiratory failure. Methods: A retrospective monocenter study including adult patients with laboratory-confirmed severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection admitted to the ICU for acute respiratory failure. The primary outcome was to identify the incidence and risk factors associated with severe AKI (KDIGO stages 2 or 3). Results: Overall, 110 COVID-19 patients were admitted. Among them, 77 (70%) required invasive mechanical ventilation (IMV), 66 (60%) received vasopressor support, and 9 (8.2%) needed extracorporeal membrane oxygenation (ECMO). Severe AKI occurred in 50 patients (45.4%). In multivariable logistic regression analysis, severe AKI was independently associated with age (odds ratio (OR) = 1.08 (95% CI (confidence interval): 1.03–1.14), p = 0.003), IMV (OR = 33.44 (95% CI: 2.20–507.77), p = 0.011), creatinine level on admission (OR = 1.04 (95% CI: 1.008–1.065), p = 0.012), and ECMO (OR = 11.42 (95% CI: 1.95–66.70), p = 0.007). Inflammatory (interleukin-6, C-reactive protein, and ferritin) or thrombotic (D-dimer and fibrinogen) markers were not associated with severe AKI after adjustment for potential confounders. Severe AKI was independently associated with hospital mortality (OR = 29.73 (95% CI: 4.10–215.77), p = 0.001) and longer hospital length of stay (subhazard ratio = 0.26 (95% CI: 0.14–0.51), p < 0.001). At the time of hospital discharge, 74.1% of patients with severe AKI who were discharged alive from the hospital recovered normal or baseline renal function. Conclusion: Severe AKI was common in critically ill patients with COVID-19 and was not associated with inflammatory or thrombotic markers. Severe AKI was an independent risk factor of hospital mortality and hospital length of stay, and it should be rapidly recognized during SARS-CoV-2 infection.

Coronavirus disease (COVID-19) caused by the new coronavirus SARS-CoV-2 has hit the world as a global pandemic of an unprecedented scale. COVID-19 has become one of the major causes of death worldwide. It is estimated that around 5% of cases are critically ill, requiring intensive care unit (ICU) admission. As of June 29, 2020, United Arab Emirates counts 47,797 cases, with 313 deaths [1]. The observed ICU mortality rate of COVID-19 is highly variable [2-5]. Also, no studies have reported the ICU outcomes of COVID-19 critically ill patients in the United Arab Emirates. The aim was to compare the published ICU case series [2-6], including ours, to understand the reasons for the differences in ICU mortality and if it is related to different ICU management of these patients (different rates of mechanical ventilation). The institutional Ethics Committee of Cleveland Clinic Abu Dhabi approved the study (number: A-2020-035), and a waiver of informed consent was obtained. Series of ICU patients with confirmed COVID-19 infection from published cohorts were included [2-6]. Regarding our study, all consecutive adult patients admitted to our ICU between March 31 and May 10, 2020, with confirmed SARS-CoV-2 infection (virus detected by a real time reverse transcriptase-polymerase chain reaction assay of a nasopharyngeal sample) were included. De-identified data from the electronic medical record were collected. Continuous variables are expressed as mean AE SD or as median [interquartile range], and proportions were used for categorical variables. Five ICU cohorts from four different countries (China, USA, Italy, and Spain) [2-6] were included along with our case series. The mean/median age was comparable between all these reported cohorts (60-64 years) except for our report, which was lower (51 AE 13 years) (Table 1). SOFA score was similar in Atlanta and Vitoria cohorts, but was higher than observed in our study. APACHE II score was comparable between the different reports (Table 1). Mechanical ventilation (MV) rate in our patients was the same as in Seattle and Atlanta reports (75% and 76%, respectively), but higher than in the Wuhan series (42%), and lower than in Lombardy and Vitoria series (89% and 94%, respectively) (Table 1). Prone position rate was comparable in the USA, China, and Italy cohorts ($27%), higher in the Spain report (49%), but much higher in our study (79%). The use of extracorporeal membrane oxygenation (ECMO) was similar in our and Wuhan reports (11%), but much higher than in the other cohorts (Table 1). The mortality rate in Wuhan and Seattle were much higher (61% and 50%, respectively) compared with the other reported ICU cohorts ranging from 26% to 33% (Table 1 and Fig. 1). The mortality rate among patients who required MV was not reported in the

(1) Background: There are limited data regarding the efficacy of convalescent plasma (CP) in critically ill patients admitted to the intensive care unit (ICU) due to coronavirus disease 2019 (COVID-19). We aimed to determine whether CP is associated with better clinical outcome among these patients. (2) Methods: A retrospective single-center study including adult patients with laboratory-confirmed SARS-CoV-2 infection admitted to the ICU for acute respiratory failure. The primary outcome was time to clinical improvement, within 28 days, defined as patient discharged alive or reduction of 2 points on a 6-point disease severity scale. (3) Results: Overall, 110 COVID-19 patients were admitted. Thirty-two patients (29%) received CP; among them, 62.5% received at least one CP with high neutralizing antibody titers (≥1:160). Clinical improvement occurred within 28 days in 14 patients (43.7%) of the CP group vs. 48 patients (61.5%) in the non-CP group (hazard ratio (HR): 0.75 (95% CI: 0.41–1.37), p = 0.35). After adjusting for potential confounding factors, CP was not independently associated with time to clinical improvement (HR: 0.53 (95% CI: 0.23–1.22), p = 0.14). Additionally, the average treatment effects of CP, calculated using the inverse probability weights (IPW), was not associated with the primary outcome (−0.14 days (95% CI: −3.19–2.91 days), p = 0.93). Hospital mortality did not differ between CP and non-CP groups (31.2% vs. 19.2%, p = 0.17, respectively). Comparing CP with high neutralizing antibody titers to the other group yielded the same findings. (4) Conclusions: In this study of life-threatening COVID-19 patients, CP was not associated with time to clinical improvement within 28 days, or hospital mortality.

Objectives: There are limited data regarding the efficacy of methylprednisolone in patients with acute respiratory distress syndrome (ARDS) due to coronavirus disease 2019 (COVID-19) requiring invasive mechanical ventilation. We aimed to determine whether methylprednisolone is associated with increases in the number of ventilator-free days (VFDs) among these patients. Design: Retrospective single-center study. Setting: Intensive care unit. Patients: All patients with ARDS due to confirmed SARS-CoV-2 infection and requiring invasive mechanical ventilation between 1 March and 29 May 2020 were included. Interventions: None. Measurements and Main Results: The primary outcome was ventilator-free days (VFDs) for the first 28 days. Defined as being alive and free from mechanical ventilation. The primary outcome was analyzed with competing-risks regression based on Fine and Gray’s proportional sub hazards model. Death before day 28 was considered to be the competing event. A total of 77 patients met the inclusion criteria. Thirty-two patients (41.6%) received methylprednisolone. The median dose was 1 mg·kg−1 (IQR: 1–1.3 mg·kg−1) and median duration for 5 days (IQR: 5–7 days). Patients who received methylprednisolone had a mean 18.8 VFDs (95% CI, 16.6–20.9) during the first 28 days vs. 14.2 VFDs (95% CI, 12.6–16.7) in patients who did not receive methylprednisolone (difference, 4.61, 95% CI, 1.10–8.12, p = 0.001). In the multivariable competing-risks regression analysis and after adjusting for potential confounders (ventilator settings, prone position, organ failure support, severity of the disease, tocilizumab, and inflammatory markers), methylprednisolone was independently associated with a higher number of VFDs (subhazards ratio: 0.10, 95% CI: 0.02–0.45, p = 0.003). Hospital mortality did not differ between the two groups (31.2% vs. 28.9%, p = 0.82). Hospital length of stay was significantly shorter in the methylprednisolone group (24 days [IQR: 15–41 days] vs. 37 days [IQR: 23–52 days], p = 0.046). The incidence of positive blood cultures was higher in patients who received methylprednisolone (37.5% vs. 17.8%, p = 0.052). However, 81% of patients who received methylprednisolone also received tocilizumab. The number of days with hyperglycemia was similar in the two groups. Conclusions: Methylprednisolone was independently associated with increased VFDs and shortened hospital length of stay. The combination of methylprednisolone and tocilizumab was associated with a higher rate of positive blood cultures. Further trials are needed to evaluate the benefits and safety of methylprednisolone in moderate or severe COVID-19 ARDS.

Patient–ventilator dyssynchrony is a mismatch between the patient’s respiratory efforts and mechanical ventilator delivery. Dyssynchrony can occur at any phase throughout the respiratory cycle. There are different types of dyssynchrony with different mechanisms and different potential management: trigger dyssynchrony (ineffective efforts, autotriggering, and double triggering); flow dyssynchrony, which happens during the inspiratory phase; and cycling dyssynchrony (premature cycling and delayed cycling). Dyssynchrony has been associated with patient outcomes. Thus, it is important to recognize and address these dyssynchronies at the bedside. Patient–ventilator dyssynchrony can be detected by carefully scrutinizing the airway pressure–time and flow–time waveforms displayed on the ventilator screens along with assessing the patient’s comfort. Clinicians need to know how to depict these dyssynchronies at the bedside. This review aims to define the different types of dyssynchrony and then discuss the evidence for their relationship with patient outcomes and address their potential management.