Antimicrobial prescription in severe COVID-19 and CAP: a matched case-control study.

BACKGROUND: In severe coronavirus diseases 2019 (COVID-19), a high and potentially excessive use of antimicrobials for suspected bacterial co-infection and intensive care unit (ICU)-acquired infections has been repeatedly reported. OBJECTIVES: To compare an ICU cohort of community-acquired pneumonia (CAP) with a cohort of severe COVID-19 pertaining to co-infections, ICU-acquired infections and associated antimicrobial consumption. METHODS: We retrospectively compared a cohort of CAP patients with a cohort of COVID-19 patients matched according to organ failure, ICU length of stay (LOS) and ventilation days. Patient data such as demographics, infection focus, probability and severity, ICU severity scores and ICU and in-hospital mortality, days of antimicrobial therapy (DOT) and number of antimicrobial prescriptions, using an incremental scale, were registered and analysed. The total number of cultures (sputum, urinary, blood cultures) was collected and corrected for ICU LOS. FINDINGS: CAP patients (n = 148) were matched to COVID-19 patients (n = 74). Significantly less sputum cultures (68.2% versus 18.9%, P < 0.05) and bronchoalveolar lavages (BAL) (73.7% versus 36.5%, P < 0.05) were performed in COVID-19 patients. Six (8.1%) COVID-19 patients were diagnosed with a co-infection. Respectively, 58 of 148 (39.2%) CAP and 38 of 74 (51.4%) COVID-19 patients (P = 0.09) developed ICU-acquired infections. Antimicrobial distribution, both in the number of prescriptions and DOT, was similar in both cohorts. CONCLUSIONS: We found a low rate of microbiologically confirmed bacterial co-infection and a high rate of ICU-acquired infections in COVID-19 patients. Infection probabilities, antimicrobial prescriptions and DOT were comparable with a matched CAP cohort.

Saturable elimination of piperacillin in critically ill patients: implications for continuous infusion.

The study aimed to evaluate saturation of piperacillin elimination in critically ill adult patients. Seventeen critically ill adult patients received continuous and intermittent infusion of piperacillin/tazobactam. Piperacillin plasma concentrations (n = 217) were analysed using population pharmacokinetic (PopPK) modelling. Post-hoc simulations were performed to evaluate the type I error rate associated with the study. Unseen data were used to validate the final model. The mean error (ME) and root mean square error (RMSE) were calculated as a measure of bias and imprecision, respectively. A PopPK model with parallel linear and non-linear elimination best fitted the data. The median and 95% confidence interval (CI) for the model parameters drug clearance (CL), volume of central compartment (V), volume of peripheral compartment (Vp) and intercompartmental clearance (Q) were 9 (7.69-11) L/h, 6.18 (4.93-11.2) L, 11.17 (7.26-12) L and 15.61 (12.66-23.8) L/h, respectively. The Michaelis-Menten constant (Km) and the maximum elimination rate for Michaelis-Menten elimination (Vmax) were estimated without population variability in the model to avoid overfitting and inflation of the type I error rate. The population estimates for Km and Vmax were 37.09 mg/L and 353.57 mg/h, respectively. The bias (ME) was -20.8 (95% CI -26.2 to -15.4) mg/L, whilst imprecision (RMSE) was 49.2 (95% CI 41.2-56) mg/L. In conclusion, piperacillin elimination is (partially) saturable. Moreover, the population estimate for Km lies within the therapeutic window and therefore saturation of elimination should be accounted for when defining optimum dosing regimens for piperacillin in critically ill patients.

Outcome in patients perceived as receiving excessive care across different ethical climates: a prospective study in 68 intensive care units in Europe and the USA.

PURPOSE: Whether the quality of the ethical climate in the intensive care unit (ICU) improves the identification of patients receiving excessive care and affects patient outcomes is unknown. METHODS: In this prospective observational study, perceptions of excessive care (PECs) by clinicians working in 68 ICUs in Europe and the USA were collected daily during a 28-day period. The quality of the ethical climate in the ICUs was assessed via a validated questionnaire. We compared the combined endpoint (death, not at home or poor quality of life at 1 year) of patients with PECs and the time from PECs until written treatment-limitation decisions (TLDs) and death across the four climates defined via cluster analysis. RESULTS: Of the 4747 eligible clinicians, 2992 (63%) evaluated the ethical climate in their ICU. Of the 321 and 623 patients not admitted for monitoring only in ICUs with a good (n = 12, 18%) and poor (n = 24, 35%) climate, 36 (11%) and 74 (12%), respectively were identified with PECs by at least two clinicians. Of the 35 and 71 identified patients with an available combined endpoint, 100% (95% CI 90.0-1.00) and 85.9% (75.4-92.0) (P = 0.02) attained that endpoint. The risk of death (HR 1.88, 95% CI 1.20-2.92) or receiving a written TLD (HR 2.32, CI 1.11-4.85) in patients with PECs by at least two clinicians was higher in ICUs with a good climate than in those with a poor one. The differences between ICUs with an average climate, with (n = 12, 18%) or without (n = 20, 29%) nursing involvement at the end of life, and ICUs with a poor climate were less obvious but still in favour of the former. CONCLUSION: Enhancing the quality of the ethical climate in the ICU may improve both the identification of patients receiving excessive care and the decision-making process at the end of life.

Validity analysis of a unique infection surveillance system in the intensive care unit by analysis of a data warehouse built through a workflow-integrated software application.

BACKGROUND: An electronic decision support programme was developed within the intensive care unit (ICU) that provides an overview of all infection-related patient data, and allows ICU physicians to add clinical information during patient rounds, resulting in prospective compilation of a database. AIM: To assess the validity of computer-assisted surveillance (CAS) of ICU-acquired infection performed by analysis of this database. METHODS: CAS was compared with prospective paper-based surveillance (PBS) for ICU-acquired respiratory tract infection (RTI), bloodstream infection (BSI) and urinary tract infection (UTI) over four months at a 36-bed medical and surgical ICU. An independent panel reviewed the data in the case of discrepancy between CAS and PBS. FINDINGS: PBS identified 89 ICU-acquired infections (13 BSI, 18 UTI, 58 RTI) and CAS identified 90 ICU-acquired infections (14 BSI, 17 UTI, 59 RTI) in 876 ICU admissions. There was agreement between CAS and PBS on 13 BSI (100 %), 14 UTI (77.8 %) and 42 RTI (72.4 %). Overall, there was agreement on 69 infections (77.5%), resulting in a kappa score of 0.74. Discrepancy between PBS and CAS was the result of capture error in 11 and 14 infections, respectively. Interobserver disagreement on probability (13 RTI) and focus (two RTI, one UTI) occurred for 16 episodes. The time required to collect information using CAS is less than 30% of the time required when using PBS. CONCLUSION: CAS for ICU-acquired infection by analysis of a database built through daily workflow is a feasible surveillance method and has good agreement with PBS. Discrepancy between CAS and PBS is largely due to interobserver variability.