Stenotrophomonas maltophilia pneumonia in critical COVID-19 patients.

Stenotrophomonas maltophilia, an environmental aerobic non-fermentative Gram-negative bacilli, has gained attention in many nosocomial outbreaks. COVID-19 patients in intensive care unit have extended hospital stay and are severely immunosuppressed. This study aimed to determine the prevalence and risk factors of S. maltophilia pneumonia in critical COVID-19 patients. A total of 123 COVID-19 patients in ICU admitted between March 2020 and March 2021 were identified from the authors' institutional database and assessed for nosocomial pneumonia. Demographic data and factors predisposing to S. maltophilia pneumonia were collected and analyzed. The mean age was 66 ± 13 years and 74% were males. Median APACHE and SOFA scores were 13 (IQR = 8-19) and 4 (3-6), respectively. The Median NEWS2 score was 6 (Q1 = 5; Q3 = 8). The Median ICU stay was 12 (Q1 = 7; Q3 = 22) days. S. maltophilia was found in 16.3% of pneumonia patients, leading to a lengthier hospital stay (34 vs. 20 days; p < 0.001). Risk factors for S. maltophilia pneumonia included previous treatment with meropenem (p < 0.01), thrombopenia (p = 0.034), endotracheal intubation (p < 0.001), foley catheter (p = 0.009) and central venous catheter insertion (p = 0.016). S. maltophilia nosocomial pneumonia is frequent in critical COVID-19 patients. Many significant risk factors should be addressed to reduce its prevalence and negative impact on outcomes.

Prognostic predictors for mortality of patients with COVID-19 in an intensive care unit.

INTRODUCTION: Fatality due to COVID-19 continues to be a challenge. Timely identification of critical COVID-19 patients is crucial for their close clinical follow-up and treatment. We aimed to identify the mortality predictors of critical COVID-19 patients. METHODOLOGY: We analyzed medical records of 232 out of 300 patients with COVID-19 hospitalized in the intensive care unit (ICU) whose medical records were available in the hospital database. Non-survivors and survivors were compared for parameters. Medical records of demographics, comorbidities, radiological signs, respiratory support, and laboratory tests on the first day of ICU admission were included. The durations of ICU stay and hospitalization were also evaluated. RESULTS: The patients with Acute Physiology and Chronic Health Evaluation II (APACHE-II) score above 28.5 and the patients with blood urea nitrogen (BUN) above 45.5 mg/dL were significantly more mortal (95% CI: 0.701, p = 0.0001; 95% CI: 0.599, p = 0.022; respectively). Partial oxygen pressure/fraction of inspired oxygen (P/F) ratio below 110.5 mmHg was a predictor for mortality (95% CI: 0.397, p = 0.018). Older age, smoking, crazy paving pattern on computed tomography (CT), and short duration of hospitalization were also predictors of mortality. The patients requiring invasive mechanical ventilation were significantly more mortal whereas the patients requiring high flow oxygen and non-invasive ventilation were significantly more likely to survive. CONCLUSIONS: We recommend evaluating APACHE-II score, BUN value, P/F ratio, age, smoking status, radiological signs on CT, length of hospitalization and modality of respiratory support upon ICU admission to identify critical patients with poor prognoses.

Procalcitonin and High APACHE (Acute Physiological and Chronic Health Evaluation) Level Are Associated with the Course of Acute Kidney Injury in Patients with SARS-CoV-2.

Background: Acute kidney injury (AKI) is associated with poor outcomes in patients infected with SARS-CoV-2. Sepsis, direct injury to kidney cells by the virus, and severe systemic inflammation are mechanisms implicated in its development. We investigated the association between inflammatory markers (C-reactive protein, procalcitonin, D-dimer, lactate dehydrogenase, and ferritin) in patients infected with SARS-CoV-2 and the development of AKI. Methods: A prospective cohort study performed at the Civil Hospital (Dr. Juan I. Menchaca) Guadalajara, Mexico, included patients aged >18 years with a diagnosis of SARS-CoV-2 pneumonia confirmed by RT-PCR and who did or did not present with AKI (KDIGO) while hospitalized. Biomarkers of inflammation were recorded, and kidney function was estimated using the CKD-EPI formula. Results: 291 patients were included (68% males; average age, 57 years). The incidence of AKI was 40.5% (118 patients); 21% developed stage 1 AKI, 6% developed stage 2 AKI, and 14% developed stage 3 AKI. The development of AKI was associated with higher phosphate (p = 0.002) (RR 1.39, CI 95% 1.13-1.72), high procalcitonin levels at hospital admission (p = 0.005) (RR 2.09, CI 95% 1.26-3.50), and high APACHE scores (p = 0.011) (RR 2.0, CI 95% 1.17-3.40). The survival analysis free of AKI according to procalcitonin levels and APACHE scores demonstrated a lower survival in patients with procalcitonin >0.5 ng/ml (p = 0.001) and APACHE >15 points (p = 0.004). Conclusions: Phosphate, high procalcitonin levels, and APACHE levels >15 were predictors of AKI development in patients hospitalized with COVID-19.

Risk stratification of patients with acute respiratory distress syndrome complicated with sepsis using lactate trajectories.

BACKGROUND: No consensus has been reached on an optimal blood lactate evaluation system although several approaches have been reported in the literature in recent years. A group-based trajectory modeling (GBTM) method could better stratify patients with acute respiratory distress syndrome (ARDS) complicated with sepsis in the intensive care unit (ICU). PATIENTS AND METHODS: 760 patients from the comprehensive ICU of Tianjin Medical University General Hospital with ARDS complicated with sepsis were eligible for analysis. Serial serum lactate levels were measured within 48 h of admission. In addition to the GBTM lactate groups, the initial lactate, peak lactate level, the area under the curve of serial lactate (lactate AUC), and lactate clearance were also considered for comparison. The short- and long-term outcomes were the 30- and 90-day mortality, respectively. RESULTS: Three lactate groups were identified based on GBTM, with group 3 exhibiting the worse short- [hazard ratio (HR) for 30-day mortality: 2.96, 95% confidence interval (CI) 1.79-4.87, P < 0.001] and long term (HR for 90-day mortality: 3.49, 95% CI 2.06-5.89, P < 0.001) outcomes followed by group 2 (HR for 30-day mortality: 2.05, 95% CI 1.48-2.84, P < 0.001 and HR for 90-day mortality: 1.99, 95% CI 1.48-2.67, P < 0.001). GBTM lactate groups exhibited significantly improved diagnostic performance of initial lactate + SOFA scores/APACHE II scores models. Based on the multivariable fractional polynomial interaction (MFPI) approach, GBTM lactate groups could better differentiate high-risk patients than the initial lactate groups in short- and long-term outcomes. CONCLUSIONS: To the best of our knowledge, this is the first report that GBTM-based serial blood lactate evaluations significantly improve the diagnostic capacity of traditional critical care evaluation systems and bring many advantages over previously documented lactate evaluation systems.

Comparison of patient characteristics and long-term mortality between transferred and non-transferred COVID-19 patients in Dutch intensive care units: A national cohort study.

BACKGROUND: COVID-19 patients were often transferred to other intensive care units (ICUs) to prevent that ICUs would reach their maximum capacity. However, transferring ICU patients is not free of risk. We aim to compare the characteristics and outcomes of transferred versus non-transferred COVID-19 ICU patients in the Netherlands. METHODS: We included adult COVID-19 patients admitted to Dutch ICUs between March 1, 2020 and July 1, 2021. We compared the patient characteristics and outcomes of non-transferred and transferred patients and used a Directed Acyclic Graph to identify potential confounders in the relationship between transfer and mortality. We used these confounders in a Cox regression model with left truncation at the day of transfer to analyze the effect of transfers on mortality during the 180 days after ICU admission. RESULTS: We included 10,209 patients: 7395 non-transferred and 2814 (27.6%) transferred patients. In both groups, the median age was 64 years. Transferred patients were mostly ventilated at ICU admission (83.7% vs. 56.2%) and included a larger proportion of low-risk patients (70.3% vs. 66.5% with mortality risk <30%). After adjusting for age, APACHE IV mortality probability, BMI, mechanical ventilation, and vasoactive medication use, the hazard of mortality during the first 180 days was similar for transferred patients compared to non-transferred patients (HR [95% CI] = 0.99 [0.91-1.08]). CONCLUSIONS: Transferred COVID-19 patients are more often mechanically ventilated and are less severely ill compared to non-transferred patients. Furthermore, transferring critically ill COVID-19 patients in the Netherlands is not associated with mortality during the first 180 days after ICU admission.

Ability of IMPROVE and IMPROVE-DD scores to predict outcomes in patients with severe COVID-19: a prospective observational study.

In this study we aimed to evaluate the ability of IMPROVE and IMPROVE-DD scores in predicting in-hospital mortality in patients with severe COVID-19. This prospective observational study included adult patients with severe COVID-19 within 12 h from admission. We recorded patients' demographic and laboratory data, Charlson comorbidity index (CCI), SpO2 at room air, acute physiology and chronic health evaluation II (APACHE II), IMPROVE score and IMPROVE-DD score. In-hospital mortality and incidence of clinical worsening (the need for invasive mechanical ventilation, vasopressors, renal replacement therapy) were recorded. Our outcomes included the ability of the IMPROVE and IMPROVE-DD to predict in-hospital mortality and clinical worsening using the area under receiver operating characteristic curve (AUC) analysis. Multivariate analysis was used to detect independent risk factors for the study outcomes. Eighty-nine patients were available for the final analysis. The IMPROVE and IMPROVE-DD score showed the highest ability for predicting in-hospital mortality (AUC [95% confidence intervals {CI}] 0.96 [0.90-0.99] and 0.96 [0.90-0.99], respectively) in comparison to other risk stratification tools (APACHE II, CCI, SpO2). The AUC (95% CI) for IMPROVE and IMPROVE-DD to predict clinical worsening were 0.80 (0.70-0.88) and 0.79 (0.69-0.87), respectively. Using multivariate analysis, IMPROVE-DD and SpO2 were the only predictors for in-hospital mortality and clinical worsening. In patients with severe COVID-19, high IMPROVE and IMOROVE-DD scores showed excellent ability to predict in-hospital mortality and clinical worsening. Independent risk factors for in-hospital mortality and clinical worsening were IMPROVE-DD and SpO2.

COVID-19 Time of Intubation Mortality Evaluation (C-TIME): A system for predicting mortality of patients with COVID-19 pneumonia at the time they require mechanical ventilation.

BACKGROUND: An accurate system to predict mortality in patients requiring intubation for COVID-19 could help to inform consent, frame family expectations and assist end-of-life decisions. RESEARCH OBJECTIVE: To develop and validate a mortality prediction system called C-TIME (COVID-19 Time of Intubation Mortality Evaluation) using variables available before intubation, determine its discriminant accuracy, and compare it to acute physiology and chronic health evaluation (APACHE IVa) and sequential organ failure assessment (SOFA). METHODS: A retrospective cohort was set in 18 medical-surgical ICUs, enrolling consecutive adults, positive by SARS-CoV 2 RNA by reverse transcriptase polymerase chain reaction or positive rapid antigen test, and undergoing endotracheal intubation. All were followed until hospital discharge or death. The combined outcome was hospital mortality or terminal extubation with hospice discharge. Twenty-five clinical and laboratory variables available 48 hours prior to intubation were entered into multiple logistic regression (MLR) and the resulting model was used to predict mortality of validation cohort patients. Area under the receiver operating curve (AUROC) was calculated for C-TIME, APACHE IVa and SOFA. RESULTS: The median age of the 2,440 study patients was 66 years; 61.6 percent were men, and 50.5 percent were Hispanic, Native American or African American. Age, gender, COPD, minimum mean arterial pressure, Glasgow Coma scale score, and PaO2/FiO2 ratio, maximum creatinine and bilirubin, receiving factor Xa inhibitors, days receiving non-invasive respiratory support and days receiving corticosteroids prior to intubation were significantly associated with the outcome variable. The validation cohort comprised 1,179 patients. C-TIME had the highest AUROC of 0.75 (95%CI 0.72-0.79), vs 0.67 (0.64-0.71) and 0.59 (0.55-0.62) for APACHE and SOFA, respectively (Chi2 P<0.0001). CONCLUSIONS: C-TIME is the only mortality prediction score specifically developed and validated for COVID-19 patients who require mechanical ventilation. It has acceptable discriminant accuracy and goodness-of-fit to assist decision-making just prior to intubation. The C-TIME mortality prediction calculator can be freely accessed on-line at https://phoenixmed.arizona.edu/ctime.

Predict models for prolonged ICU stay using APACHE II, APACHE III and SAPS II scores: A Japanese multicenter retrospective cohort study.

Prolonged ICU stays are associated with high costs and increased mortality. Thus, early prediction of such stays would help clinicians to plan initial interventions, which could lead to efficient utilization of ICU resources. The aim of this study was to develop models for predicting prolonged stays in Japanese ICUs using APACHE II, APACHE III and SAPS II scores. In this multicenter retrospective cohort study, we analyzed the cases of 85,558 patients registered in the Japanese Intensive care Patient Database between 2015 and 2019. Prolonged ICU stay was defined as an ICU stay of >14 days. Multivariable logistic regression analyses were performed to develop three predictive models for prolonged ICU stay using APACHE II, APACHE III and SAPS II scores, respectively. After exclusions, 79,620 patients were analyzed, 2,364 of whom (2.97%) experienced prolonged ICU stays. Multivariable logistic regression analyses showed that severity scores, BMI, MET/RRT, postresuscitation, readmission, length of stay before ICU admission, and diagnosis at ICU admission were significantly associated with higher risk of prolonged ICU stay in all models. The present study developed predictive models for prolonged ICU stay using severity scores. These models may be helpful for efficient utilization of ICU resources.

Relationship between no-visitation policy and the development of delirium in patients admitted to the intensive care unit.

BACKGROUND: Due to the severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) pandemic, many hospitals imposed a no-visitation policy for visiting patients in hospitals to prevent the transmission of SARS-CoV-2 among visitors and patients. The objective of this study was to investigate the association between the no-visitation policy and delirium in intensive care unit (ICU) patients. METHODS: This was a single-center, before-after comparative study. Patients were admitted to a mixed medical-surgical ICU from September 6, 2019 to October 18, 2020. Because no-visitation policy was implemented on February 26, 2020, we compared patients admitted after this date (after phase) with the patients admitted before the no-visitation policy (before phase) was implemented. The primary outcome was the incidence of delirium during the ICU stay. Cox regression was used for the primary analysis and was calculated using hazard ratios (HRs) and 95% confidence intervals (CIs). Covariates were age, sex, APACHE II, dementia, emergency surgery, benzodiazepine, and mechanical ventilation use. RESULTS: Of the total 200 patients consecutively recruited, 100 were exposed to a no-visitation policy. The number of patients who developed delirium during ICU stay during the before phase and the after phase were 59 (59%) and 64 (64%), respectively (P = 0.127). The adjusted HR of no-visitation policy for the number of days until the first development of delirium during the ICU stay was 0.895 (0.613-1.306). CONCLUSION: The no-visitation policy was not associated with the development of delirium in ICU patients.

Factors influencing death in COVID-19 patients treated in the ICU: a single-centre, cross-sectional study.

BACKGROUND: This single-centre study investigated factors influencing death in coronavirus disease 2019 (COVID-19) patients treated in an intensive care unit (ICU). METHODS: Data of 113 consecutive patients with a severe form of COVID-19 infection, who completed their ICU stay in a large COVID-19-dedicated hospital in the Silesian Region of Poland during one year of the pandemic (between 10 March, 2020 and 10 March, 2021), were reviewed. Comprehensive comparison of all available ICU pre-admission, admission and treatment variables was performed. Variables that independently influenced ICU death were identified. RESULTS: ICU mortality in the whole group was 64.6%. Mean age was higher in non-survivors (64.6 ± 9.5 vs. 60.0 ± 12.8 years, P = 0.036), but the distribution of sex and body mass index was similar in both groups. Non-survivors had a marginally higher mean Charlson Comorbidity Index (5.9 ± 3.6 vs. 4.5 ± 4.1 points, P = 0.063), and significantly higher mean Clinical Frailty Score (4.8 ± 1.5 vs. 3.9 ± 1.4 points, P = 0.004), admission APACHE II score (22.9 ± 7.9 vs. 19.1 ± 7.8 points, P = 0.017) and SAPS II score (62.1 ± 18.1 vs. 54.0 ± 16.7 points, P = 0.023). Factors that independently influenced ICU death were limited to: admission total protein 2.0 ng mL-1 (OR = 11.3, P = 0.026) and lactate level > 2.0 mmol L-1 (OR = 4.2, P = 0.003) as well as Clinical Frailty Score ≥ 5 points (OR = 3.1, P = 0.021). CONCLUSIONS: The presence of low total protein, frailty and increased procalcitonin and lactate levels at ICU admission are associated with ICU death in patients with severe COVID-19 infection.

Mortality prediction of patients in intensive care units using machine learning algorithms based on electronic health records.

Improving predictive models for intensive care unit (ICU) inpatients requires a new strategy that periodically includes the latest clinical data and can be updated to reflect local characteristics. We extracted data from all adult patients admitted to the ICUs of two university hospitals with different characteristics from 2006 to 2020, and a total of 85,146 patients were included in this study. Machine learning algorithms were trained to predict in-hospital mortality. The predictive performance of conventional scoring models and machine learning algorithms was assessed by the area under the receiver operating characteristic curve (AUROC). The conventional scoring models had various predictive powers, with the SAPS III (AUROC 0.773 [0.766-0.779] for hospital S) and APACHE III (AUROC 0.803 [0.795-0.810] for hospital G) showing the highest AUROC among them. The best performing machine learning models achieved an AUROC of 0.977 (0.973-0.980) in hospital S and 0.955 (0.950-0.961) in hospital G. The use of ML models in conjunction with conventional scoring systems can provide more useful information for predicting the prognosis of critically ill patients. In this study, we suggest that the predictive model can be made more robust by training with the individual data of each hospital.

Mortality estimation using APACHE and CT scores with stepwise linear regression method in COVID-19 intensive care unit: A retrospective study.

BACKGROUND: COVID-19 is a disease with high mortality worldwide, and which parameters that affect mortality in intensive care are still being investigated. This study aimed to show the factors affecting mortality in COVID-19 intensive care patients and write a model that can predict mortality. METHODS: The data of 229 patients in the COVID-19 intensive care unit were scanned. Laboratory tests, APACHE, SOFA, and GCS values were recorded. CT scores were calculated with chest CTs. The effects of these data on mortality were examined. The effects of the variables were modeled using the stepwise regression method. RESULTS: While the mean age of female (30.14%) patients was 69.1 ± 12.2, the mean age of male (69.86%) patients was 66.9 ± 11.5. The mortality rate was 69.86%. Age, CRP, D-dimer, creatinine, procalcitonin, APACHE, SOFA, GCS, and CT score were significantly different in the deceased patients than the survival group. When we attempted to create a model using stepwise linear regression analysis, the appropriate model was achieved at the fourth step. Age, CRP, APACHE, and CT score were included in the model, which has the power to predict mortality with 89.9% accuracy. CONCLUSION: Although, when viewed individually, there is a significant difference in parameters such as creatinine, procalcitonin, D-dimer, GCS, and SOFA score, the probability of mortality can be estimated by knowing only the age, CRP, APACHE, and CT scores. These four simple parameters will help clinicians effectively use resources in treatment.

[Clinical Characteristics and outcomes of adults with COVID-19 admitted to a Pediatric Intensive Care Unit]. / Características y resultados clínicos de adultos graves hospitalizados por COVID-19 en una Unidad de Cuidados Intensivos Pediátricos.

OBJECTIVE: To describe a cohort of critically ill adult patients suffering from COVID-19, admitted to a pediatric intensive care unit managed by a pediatric intensive care team (ICU-MP). PATIENTS AND METHOD: Retrospective observational study of adults admitted to the ICU-MP due to COVID-19 from May 11 to July 26, 2020. Demographic, clinical, biochemical, ventilatory support characteris tics, and complications were recorded. Disease severity was characterized by Acute Physiology and Chronic Health Evaluation II score (APACHE II) using data from the first 24 hours of admission to the ICU-MP. RESULTS: Ninety-three patients over 18 years with suspected or confirmed COVID-19 were admitted to the ICU-MP. The median age was 60.3 years (SD 13.9), and 59 (63.4%) patients were male. Eighty-two (88.1%) patients had at least 1 medical comorbidity. The median APACHE II score was 9.4 points (SD 5.6). Fifty-one (54.8%) patients were invasively ventilated, for a median of 13.7 days (SD 17.9). Inotropic support was used in 45 (48%) patients. Thirty-three (35.5%) patients presented acute kidney injury (AKI) and 14 (15.1%) patients received continuous renal replacement therapy. Twenty-nine (31.2%) patients had healthcare-associated infections. The median ICU-MP stay was 10.8 days (SD 11.8). 25 (26.9%) patients died, ten of them (40%) had adequacy of thera peutic effort. CONCLUSIONS: The mortality rate of critically ill patients with COVID-19 is high. Older patients (> 70 years), those who require invasive mechanical ventilation and who develop AKI are at increased risk of death. Although this is not a comparative study, our mortality rate and complica tions seem to be similar to those reported in adult case series.

Mortality Predictive Value of APACHE II and SOFA Scores in COVID-19 Patients in the Intensive Care Unit.

Background: COVID-19 pandemic has become a global dilemma since December 2019. Are the standard scores, such as acute physiology and chronic health evaluation (APACHE II) and sequential organ failure assessment (SOFA) score, accurate for predicting the mortality rate of COVID-19 or the need for new scores? We aimed to evaluate the mortality predictive value of APACHE II and SOFA scores in critically ill COVID-19 patients. Methods: In a cohort study, we enrolled 204 confirmed COVID-19 patients admitted to the intensive care units at the Imam Khomeini hospital complex. APACHE II on the first day and daily SOFA scoring were performed. The primary outcome was the mortality rate in the nonsurvived and survived groups, and the secondary outcome was organ dysfunction. Two groups of survived and nonsurvived patients were compared by the chi-square test for categorical variables and an independent sample t-test for continuous variables. We used logistic regression models to estimate the mortality risk of high APACHE II and SOFA scores. Result: Among 204 severe COVID-19 patients, 114 patients (55.9%) expired and 169 patients (82.8%) had at least one comorbidity that 103 (60.9%) of them did not survive (P=0.002). Invasive mechanical ventilation and its duration were significantly different between survived and nonsurvived groups (P ≤ 0.001 and P=0.002, respectively). Mean APACHE II and mean SOFA scores were significantly higher in the nonsurvived than in the survived group (14.4 ± 5.7 vs. 9.5 ± 5.1, P ≤ 0.001, 7.3 ± 3.1 vs. 3.1 ± 1.1, P ≤ 0.001, respectively). The area under the curve was 89.5% for SOFA and 73% for the APACHE II score. Respiratory diseases and malignancy were risk factors for the mortality rate (P=0.004 and P=0.007, respectively) against diabetes and hypertension. Conclusion: The daily SOFA was a better mortality predictor than the APACHE II in critically ill COVID-19 patients. But they could not predict death with high accuracy. We need new scoring with consideration of the prognostic factors and daily evaluation of changes in clinical conditions.

Differences and Similarities Among COVID-19 Patients Treated in Seven ICUs in Three Countries Within One Region: An Observational Cohort Study.

OBJECTIVES: To investigate healthcare system-driven variation in general characteristics, interventions, and outcomes in coronavirus disease 2019 (COVID-19) patients admitted to the ICU within one Western European region across three countries. DESIGN: Multicenter observational cohort study. SETTING: Seven ICUs in the Euregio Meuse-Rhine, one region across Belgium, The Netherlands, and Germany. PATIENTS: Consecutive COVID-19 patients supported in the ICU during the first pandemic wave. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Baseline demographic and clinical characteristics, laboratory values, and outcome data were retrieved after ethical approval and data-sharing agreements. Descriptive statistics were performed to investigate country-related practice variation. From March 2, 2020, to August 12, 2020, 551 patients were admitted. Mean age was 65.4 ± 11.2 years, and 29% were female. At admission, Acute Physiology and Chronic Health Evaluation II scores were 15.0 ± 5.5, 16.8 ± 5.5, and 15.8 ± 5.3 (p = 0.002), and Sequential Organ Failure Assessment scores were 4.4 ± 2.7, 7.4 ± 2.2, and 7.7 ± 3.2 (p < 0.001) in the Belgian, Dutch, and German parts of Euregio, respectively. The ICU mortality rate was 22%, 42%, and 44%, respectively (p < 0.001). Large differences were observed in the frequency of organ support, antimicrobial/inflammatory therapy application, and ICU capacity. Mixed-multivariable logistic regression analyses showed that differences in ICU mortality were independent of age, sex, disease severity, comorbidities, support strategies, therapies, and complications. CONCLUSIONS: COVID-19 patients admitted to ICUs within one region, the Euregio Meuse-Rhine, differed significantly in general characteristics, applied interventions, and outcomes despite presumed genetic and socioeconomic background, admission diagnosis, access to international literature, and data collection are similar. Variances in healthcare systems' organization, particularly ICU capacity and admission criteria, combined with a rapidly spreading pandemic might be important drivers for the observed differences. Heterogeneity between patient groups but also healthcare systems should be presumed to interfere with outcomes in coronavirus disease 2019.

Are we aware of COVID-19-related acute kidney injury in intensive care units?

OBJECTIVE: Coronavirus disease-19 (COVID-19) primarily affects the respiratory system. In some cases, the heart, kidney, liver, circulatory system, and nervous system are also affected. COVID-19-related acute kidney injury (AKI) occurs in more than 20% of hospitalized patients and more than 50% of patients in the intensive care unit (ICU). In this study, we aimed to review the prevalence of COVID-19-related acute kidney injury, risk factors, hospital and ICU length of stay, the need for renal replacement therapy. We also examined the effect of AKI on mortality in patients in the ICU that we treated during a 1-year period. PATIENTS AND METHODS: The files of patients with COVID-19 (n=220) who were treated in our ICU between March 21st, 2020, and June 1st, 2021, were analyzed retrospectively. Demographic data of the patients, laboratory data, and treatments were examined. Patients were divided into two groups, group I patients without AKI and, group II patients with AKI. The patients with AKI were evaluated according to the theKidney Disease Improving Global Outcomes (KDIGO) classification and were graded. RESULTS: Of the 220 patients included in the study, 89 were female and 131 were male. The mean age of patients with AKI (70.92±11.28 years) was statistically significantly higher than among those without AKI (58.87±13.63 years) (p<0.001). In patients with AKI, ICU length of stay, Acute Physiology and Chronic Health Evaluation (APACHE) II scores, initial lactate levels, need for mechanical ventilation, duration of mechanical ventilation, and secondary infection rates were found to be statistically significantly higher. Discharge rates from the ICU in patients without AKI were statistically higher (75.3% vs. 26.6%), and mortality rates were significantly higher in patients with AKI (67.8% vs. 14.3%). CONCLUSIONS: Various studies conducted have shown that patients with COVID-19 are at risk for AKI, and this is closely related to age, sex, and disease severity. The presence of AKI in patients with COVID-19 increases mortality, and this is more evident in patients hospitalized in the ICU. In our study, the prevalence of AKI was higher in older patients with high APACHE II scores and initial lactate levels. Comorbidities such as hypertension, chronic kidney disease, and coronary artery disease in patients with AKI were higher than in those without AKI.

Renal histopathology in critically ill patients with Septic Acute Kidney Injury(S-AKI).

PURPOSE: To describe the kidney histopathology of patients with S-AKI and correlate the histological findings with AKI severity, presence of septic shock, and the degree of multiple organic dysfunction (MOD) using the SOFA score. MATERIALS AND METHODS: This was a prospective, observational, and analytical study of a cohort of critically ill patients with S-AKI who died from sepsis at the "Hospital Español" intensive care unit (ICU). Kidney necropsies were performed within 2 h after death. RESULTS: We considered twenty (20) patients, with all of them exhibiting S-AKI stage 3 at the same time. In renal histopathology analysis, nonspecific tubulointerstitial (TI) lesions were found in almost all patients (95%). The more frequently found nonspecific TI lesions involved leukocyte infiltration (85%). Necrotic TI lesions were found in 6 patients (30%), and necrotic tubular cell casts were the most frequent lesions (50% of patients). It was not possible to demonstrate an association between the presence of necrotic TI lesions and factors such as the APACHE II score, the global SOFA score, ICU stays, AKI length and renal replacement therapy (RRT). CONCLUSIONS: The main histopathological findings in kidney necropsies in patients with S-AKI KDIGO 3, showed nonspecific TI lesions, and TI necrosis was only observed in 30% of the cases; therefore, S-AKI cannot be considered to be synonymous with acute tubular necrosis (ATN).

Association Between Pandemic Coronavirus Disease 2019 Public Health Measures and Reduction in Critical Care Utilization Across ICUs in Alberta, Canada.

OBJECTIVES: The coronavirus disease 2019 pandemic has disrupted critical care services across the world. In anticipation of surges in the need for critical care services, governments implemented "lockdown" measures to preserve and create added critical care capacity. Herein, we describe the impact of lockdown measures on the utilization of critical care services and patient outcomes compared with nonlockdown epochs in a large integrated health region. DESIGN: This was a population-based retrospective cohort study. SETTING: Seventeen adult ICUs across 14 acute care hospitals in Alberta, Canada. PATIENTS: All adult (age ≥ 15 yr) patients admitted to any study ICU. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The main exposure was ICU admission during "lockdown" occurring between March 16, 2020, and June 30, 2020. This period was compared with two nonpandemic control periods: "year prior" (March 16, 2019, to June 30, 2019) and "pre lockdown" immediately prior (November 30, 2019, to March 15, 2020). The primary outcome was the number of ICU admissions. Secondary outcomes included the following: daily measures of ICU utilization, ICU duration of stay, avoidable delay in ICU discharge, and occupancy; and patient outcomes. Mixed multilevel negative binomial regression and interrupted time series regression were used to compare rates of ICU admissions between periods. Multivariable regressions were used to compare patient outcomes between periods. During the lockdown, there were 3,649 ICU admissions (34.1 [8.0] ICU admissions/d), compared with 4,125 (38.6 [9.3]) during the prelockdown period and 3,919 (36.6 [8.7]) during the year prior. Mean bed occupancy declined significantly during the lockdown compared with the nonpandemic periods (78.7%, 95.9%, and 96.4%; p < 0.001). Avoidable ICU discharge delay also decreased significantly (42.0%, 53.2%, and 58.3%; p < 0.001). During the lockdown, patients were younger, had fewer comorbid diseases, had higher acuity, and were more likely to be medical admissions compared with the nonpandemic periods. Adjusted ICU and hospital mortality and ICU and hospital lengths of stay were significantly lower during the lockdown compared with nonpandemic periods. CONCLUSIONS: The coronavirus disease 2019 lockdown resulted in substantial changes to ICU utilization, including a reduction in admissions, occupancy, patient lengths of stay, and mortality.

High serum nitrates levels in non-survivor COVID-19 patients.

OBJECTIVE: Higher blood nitrate and nitrite levels have been found in coronavirus disease 2019 (COVID-19) patients than in healthy subjects. The present study explores the potential association between serum nitrate levels and mortality in COVID-19 patients. DESIGN: A prospective observation study was carried out. SETTING: Eight Intensive Care Units (ICUs) from 6 hospitals in the Canary Islands (Spain). PATIENTS: COVID-19 patients admitted to the ICU. INTERVENTIONS: Determination of serum nitrate levels at ICU admission. MAIN VARIABLE OF INTEREST: Mortality at 30 days. RESULTS: Non-surviving (n=11) compared to surviving patients (n=42) showed higher APACHE-II (p<0.001) and SOFA scores (p=0.004), and higher serum nitrate levels (p=0.001). Logistic regression analyses showed serum nitrate levels to be associated to 30-day mortality after controlling for SOFA (OR=1.021; 95%CI=1.006-1.036; p=0.01) or APACHE-II (OR=1.023; 95%CI=1.006-1.041; p=0.01). There were no differences in the area under the curve (AUC) for mortality prediction by serum nitrate levels (AUC=83%; 95%CI=73-92%; p<0.001), APACHE II (AUC=85%; 95%CI=75-96%; p<0.001) and SOFA (AUC=78%; 95%CI=63-92%; p=0.005) based on the DeLong method. The Kaplan-Meier analysis found patients with serum nitrates levels>68.4µmol/l to have a higher mortality rate (hazard ratio=138.8; 95%CI=22.3-863.9; p<0.001). CONCLUSIONS: The main novel finding was the association between serum nitrate levels and mortality in COVID-19 patients controlling for the SOFA or APACHE-II scores, though larger studies are needed to confirm this observation.

Comparison of confirmed and probable COVID-19 patients in the intensive care unit during the normalization period.

The decrease in social distance together with the normalization period as of June 1, 2020 in our country caused an increase in the number of COVID 19 patients. Our aim was to compare the demographic features, clinical courses and outcomes of confirmed and probable coronavirus disease 2019 (COVID-19) patients admitted to our intensive care unit (ICU) during the normalization period. Critically ill 128 COVID-19 patients between June 1 - December 2, 2020 were analyzed retrospectively. The mean age was 69.7±15.5y (61.7% male). Sixty-one patients (47.7%) were confirmed. Dyspnea (75.0%) was the most common symptom and hypertension (71.1%) was the most common comorbidity. The mean Acute Physiology and Chronic Health Evaluation System (APACHE II) score; Glasgow Coma Score (GCS); Sequential Organ Failure Assessment (SOFA) scores on ICU admission were 17.4 ± 8.2, 12.3 ± 3.9 and 5.9 ± 3.4, respectively. 101 patients (78.1%) received low flow oxygen, 48 had high flow oxygen therapy (37.5%) and 59 (46.1%) had invasive mechanical ventilation. 53 patients (41.4%) had vasopressor therapy and 30 (23.4%) patients had renal replacement therapy (RRT) due to acute kidney injury (AKI). Confirmed patients were more tachypneic (p=0.005) and more hypoxemic than probable patients (p<0.001). Acute respiratory distress syndrome (ARDS) and AKI were more common in confirmed patients than probable (both p<0.001). Confirmed patients had higher values of hemoglobin, C- reactive protein, fibrinogen, D-dimer than probables (respectively, p=0.028, 0.006, 0.000, 0.019). The overall mortality was higher in confirmed patients (p=0.209, 52.6% vs 47.4%). Complications are more common among confirmed COVID-19 patients admitted to ICU. The mortality rate of confirmed COVID-19 patients admitted to the ICU was found to be higher than probable patients. Mortality of confirmed cases were higher than prediction of APACHE-II scoring system.