Background: Patients infected with severe acute respiratory syndrome coronavirus (SARS-CoV-2) can develop severe illness necessitating intensive care admission. Critically ill patients are susceptible for the development of secondary bacterial infections. Due to a combination of virus- and drug-induced immunosuppression, critically ill patients with corona virus disease 2019 (COVID-19) may even have a higher risk of developing a secondary infection. These secondary infections can aggravate the severity of illness and increase the risk of death. Further research on secondary infections in COVID-19 patients is essential. Therefore, the objective of this study was to investigate the incidence and associated risk factors of secondary bacterial infections and to identify the most common groups of pathogens in critically ill COVID-19 patients. Methods: This mono-center, retrospective observational cohort study was performed at the intensive care unit (ICU) of the Jessa Hospital, Hasselt, Belgium. All adult COVID-19 patients admitted to the ICU from 13th March 2020 until 17th October 2020, were eligible for inclusion in the study. Data from the resulting 116 patients were prospectively entered into a customized database. The resulting database was retrospectively reviewed to investigate three types of secondary bacterial infections (secondary pneumonia, bloodstream infections of unknown origin, catheter-related sepsis). Results: Of 94 included patients, 68% acquired at least one of the studied secondary bacterial infections during their ICU stay. Almost two thirds of patients (65.96%, n = 62) acquired a secondary pneumonia, whereas 29.79% (n = 28) acquired a bacteremia of unknown origin and a smaller proportion of patients (14.89%, n = 14) acquired a catheter-related sepsis. Male gender (P = 0.05), diabetes mellitus (P = 0.03) and the cumulative dose of corticosteroids (P = 0.004) were associated with increased risk of secondary bacterial infection. The most common pathogens detected in the cultures of patients with secondary pneumonia were Gram-negative bacilli. Bacteremia of unknown origin and catheter-related sepsis were mostly caused by Gram-positive cocci. Conclusion: This study confirms that the incidence of secondary bacterial infections is very high in critically ill COVID-19 patients. These patients are at highest risk of developing secondary pneumonia. Male gender, a history of diabetes mellitus and the administration of corticosteroids were associated with increased risk of secondary bacterial infection.

Background: Acute kidney injury (AKI) has been reported as a frequent complication of critical COVID-19. We aimed to evaluate the occurrence of AKI and use of kidney replacement therapy (KRT) in critical COVID-19, to assess patient and kidney outcomes and risk factors for AKI and differences in outcome when the diagnosis of AKI is based on urine output (UO) or on serum creatinine (sCr). Methods: Multicenter, retrospective cohort analysis of patients with critical COVID-19 in seven large hospitals in Belgium. AKI was defined according to KDIGO within 21 days after ICU admission. Multivariable logistic regression analysis was used to explore the risk factors for developing AKI and to assess the association between AKI and ICU mortality. Results: Of 1286 patients, 85.1% had AKI, and KRT was used in 9.8%. Older age, obesity, a higher APACHE II score and use of mechanical ventilation at day 1 of ICU stay were associated with an increased risk for AKI. After multivariable adjustment, all AKI stages were associated with ICU mortality. AKI was based on sCr in 40.1% and UO in 81.5% of patients. All AKI stages based on sCr and AKI stage 3 based on UO were associated with ICU mortality. Persistent AKI was present in 88.6% and acute kidney disease (AKD) in 87.6%. Rapid reversal of AKI yielded a better prognosis compared to persistent AKI and AKD. Kidney recovery was observed in 47.4% of surviving AKI patients. Conclusions: Over 80% of critically ill COVID-19 patients had AKI. This was driven by the high occurrence rate of AKI defined by UO criteria. All AKI stages were associated with mortality (NCT04997915).

Traditionally, major complications and unanticipated admission/readmission rates were used to assess outcome after day surgery. However, in view of the relative absence of major complications the quality of recovery (QOR) should be considered one of the principal endpoints after day surgery. In our study, the level of QOR is defined by a combination of the Global Surgical Recovery (GSR) Index and the Quality of Life (QOL). The aim of this study was to analyze prevalence and predictors of QOR after day surgery on the fourth postoperative day. Elective patients scheduled for day surgery from November 2008 to April 2010 were enrolled in a prospective cohort study. Outcome parameters were measured by using questionnaire packages at 2 time points: 1 week preoperatively and 4 days postoperatively. Primary outcome parameter is the QOR and is defined as good if the GSR index >80% as well as the postoperative QOL is unchanged or improved as compared with baseline. QOR is defined as poor if both the GSR index ≤ 80% and if the postoperative QOL is decreased as compared with baseline. QOR is defined as intermediate in all other cases. Three logistic regression analyses were performed to determine predictors for poor QOR after day surgery. A total of 1118 patients were included. A good QOR was noted in 17.3% of patients, an intermediate QOR in 34.8%, and a poor QOR in 47.8% 4 days after day surgery. The best predictor for poor QOR after day surgery was type of surgery. Other predictors were younger age, work status, and longer duration of surgery. A history of previous surgery, expected pain (by the patient) and high long-term surgical fear were significant predictors of poor QOR in only 1 of 3 prediction models. The QOR at home 4 days after day surgery was poor in the majority of patients and showed a significant procedure-specific variation. Patients at risk for poor QOR can be identified during the preoperative period based on type of surgery, age, work status, and the duration of the surgery.

Background. Severity scoring systems are inherent to ICU practice for multiple purposes. Acute Physiology and Chronic Health Evaluation (APACHE) scoring systems are designed for ICU mortality prediction. This study aims to validate APACHE IV in COVID-19 patients admitted to the ICU. Methods. All COVID-19 patients admitted to the ICU between March 13, 2020, and October 17, 2020, were retrospectively analyzed. APACHE II and APACHE IV scores as well as SOFA scores were calculated within 24 hours after admission. Discrimination for mortality of all three scoring systems was assessed by receiver operating characteristic curves. Youden index was determined for the scoring system with the best discriminative performance. The Hosmer–Lemeshow goodness-of-fit test was used to assess calibration. All analyses were performed for both the overall population as in a subgroup treated with anti-Xa adjusted dosages of LMWHs. Results. 116 patients were admitted to our ICU during the study period. 13 were excluded for various reasons, leaving 103 patients in the statistical analysis of the overall population. 57 patients were treated with anti-Xa adjusted prophylactic dosages of LMWH and were supplementary analyzed in a subgroup analysis. APACHE IV had the best discriminative power of the three scoring systems, both in the overall population (APACHE IV ROC AUC 0.67 vs. APACHE II ROC AUC 0.63) as in the subgroup (APACHE IV ROC AUC 0.82 vs. APACHE II ROC AUC 0.7). This model exhibits good calibration. Hosmer–Lemeshow values for APACHE IV were 0.9234 for the overall population and 0.8017 for the subgroup. Calibration values of the APACHE II score were 0.1394 and 0.6475 for the overall versus subgroup, respectively. Conclusions. APACHE IV provided the best discrimination and calibration of the considered scoring systems in critically ill COVID-19 patients, both in the overall group and in the subgroup with anti-Xa adjusted LMWH doses. Only in the subgroup analysis, discriminative abilities of APACHE IV were very good. This trial is registered with NCT04713852.

Corona virus disease 2019 (COVID-19) has been associated with a wide range of divergent pathologies, and risk of severe disease is reported to be increased by a similarly broad range of co-morbidities. The present study investigated blood metabolites in order to elucidate how infection with severe acute respiratory syndrome coronavirus 2 can lead to such a variety of pathologies and what common ground they share. COVID-19 patient blood samples were taken at hospital admission in two Belgian patient cohorts, and a third cohort that included longitudinal samples was used for additional validation (total n=581). A total of 251 blood metabolite measures and ratios were assessed using nuclear magnetic resonance spectroscopy and tested for association to disease severity. In line with the varied effects of severe COVID-19, the range of severity-associated biomarkers was equally broad and included increased inflammatory markers (glycoprotein acetylation), amino acid concentrations (increased leucine and phenylalanine), increased lipoprotein particle concentrations (except those of very low density lipoprotein, VLDL), decreased cholesterol levels (except in large HDL and VLDL), increased triglyceride levels (only in IDL and LDL), fatty acid levels (decreased poly-unsaturated fatty acid, increased mono-unsaturated fatty acid) and decreased choline concentration, with association sizes comparable to those of routine clinical chemistry metrics of acute inflammation. Our results point to systemic metabolic biomarkers for COVID-19 severity that make strong targets for further fundamental research into its pathology (e.g. phenylalanine and omega-6 fatty acids).