Prioritisation of ICU treatments for critically ill patients in a COVID-19 pandemic with scarce resources.

BACKGROUND: Relying on capacity increases and patient transfers to deal with the huge and continuous inflow of COVID-19 critically ill patients is a strategy limited by finite human and logistical resources. RATIONALE: Prioritising both critical care initiation and continuation is paramount to save the greatest number of lives. It enables to allocate scarce resources in priority to those with the highest probability of benefiting from them. It is fully ethical provided it relies on objective and widely shared criteria, thus preventing arbitrary decisions and guaranteeing equity. Prioritisation seeks to fairly allocate treatments, maximise saved lives, gain indirect life benefits from prioritising exposed healthcare and similar workers, give priority to those most penalised as a last resort, and apply similar prioritisation schemes to all patients. PRIORITISATION STRATEGY: Prioritisation schemes and their criteria are adjusted to the level of resource scarcity: strain (level A) or saturation (level B). Prioritisation yields a four level priority for initiation or continuation of critical care: P1-high priority, P2-intermediate priority, P3-not needed, P4-not appropriate. Prioritisation schemes take into account the patient's wishes, clinical frailty, pre-existing chronic condition, along with severity and evolution of acute condition. Initial priority level must be reassessed, at least after 48h once missing decision elements are available, at the typical turning point in the disease's natural history (ICU days 7 to 10 for COVID-19), and each time resource scarcity levels change. For treatments to be withheld or withdrawn, a collegial decision-making process and information of patient and/or next of kin are paramount. PERSPECTIVE: Prioritisation strategy is bound to evolve with new knowledge and with changes within the epidemiological situation.

Incidence and outcome of invasive candidiasis in intensive care units (ICUs) in Europe: results of the EUCANDICU project.

BACKGROUND: The objective of this study was to assess the cumulative incidence of invasive candidiasis (IC) in intensive care units (ICUs) in Europe. METHODS: A multinational, multicenter, retrospective study was conducted in 23 ICUs in 9 European countries, representing the first phase of the candidemia/intra-abdominal candidiasis in European ICU project (EUCANDICU). RESULTS: During the study period, 570 episodes of ICU-acquired IC were observed, with a cumulative incidence of 7.07 episodes per 1000 ICU admissions, with important between-center variability. Separated, non-mutually exclusive cumulative incidences of candidemia and IAC were 5.52 and 1.84 episodes per 1000 ICU admissions, respectively. Crude 30-day mortality was 42%. Age (odds ratio [OR] 1.04 per year, 95% CI 1.02-1.06, p < 0.001), severe hepatic failure (OR 3.25, 95% 1.31-8.08, p 0.011), SOFA score at the onset of IC (OR 1.11 per point, 95% CI 1.04-1.17, p 0.001), and septic shock (OR 2.12, 95% CI 1.24-3.63, p 0.006) were associated with increased 30-day mortality in a secondary, exploratory analysis. CONCLUSIONS: The cumulative incidence of IC in 23 European ICUs was 7.07 episodes per 1000 ICU admissions. Future in-depth analyses will allow explaining part of the observed between-center variability, with the ultimate aim of helping to improve local infection control and antifungal stewardship projects and interventions.

Assessment of white matter injury and outcome in severe brain trauma: a prospective multicenter cohort.

BACKGROUND: Existing methods to predict recovery after severe traumatic brain injury lack accuracy. The aim of this study is to determine the prognostic value of quantitative diffusion tensor imaging (DTI). METHODS: In a multicenter study, the authors prospectively enrolled 105 patients who remained comatose at least 7 days after traumatic brain injury. Patients underwent brain magnetic resonance imaging, including DTI in 20 preselected white matter tracts. Patients were evaluated at 1 yr with a modified Glasgow Outcome Scale. A composite DTI score was constructed for outcome prognostication on this training database and then validated on an independent database (n=38). DTI score was compared with the International Mission for Prognosis and Analysis of Clinical Trials Score. RESULTS: Using the DTI score for prediction of unfavorable outcome on the training database, the area under the receiver operating characteristic curve was 0.84 (95% CI: 0.75-0.91). The DTI score had a sensitivity of 64% and a specificity of 95% for the prediction of unfavorable outcome. On the validation-independent database, the area under the receiver operating characteristic curve was 0.80 (95% CI: 0.54-0.94). On the training database, reclassification methods showed significant improvement of classification accuracy (P < 0.05) compared with the International Mission for Prognosis and Analysis of Clinical Trials score. Similar results were observed on the validation database. CONCLUSIONS: White matter assessment with quantitative DTI increases the accuracy of long-term outcome prediction compared with the available clinical/radiographic prognostic score.

Is continuous subglottic suctioning cost-effective for the prevention of ventilator-associated pneumonia?

OBJECTIVE: To establish whether continuous subglottic suctioning (CSS) could be cost-effective. DESIGN: Cost-benefit analysis, based on a hypothetical replacement of conventional ventilation (CV) with CSS. SETTING: A surgical intensive care unit (SICU) of a tertiary care university hospital in France. PATIENTS: All consecutive patients receiving ventilation in the SICU in 2006. METHODS: Efficacy data for CSS were obtained from the literature and applied to the SICU of our hospital. Costs for CV and CSS were provided by the hospital pharmacy; costs for ventilator-associated pneumonia (VAP) were obtained from the literature. The cost per averted VAP episode was calculated, and a sensitivity analysis was performed on VAP incidence and on the number of tubes required for each patient. RESULTS: At our SICU in 2006, 416 patients received mechanical ventilation for 3,487 ventilation-days, and 32 VAP episodes were observed (7.9 episodes per 100 ventilated patients; incidence density, 9.2 episodes per 10,000 ventilation-days). Based on the hypothesis of a 29% reduction in the risk of VAP with CSS than CV, 9 VAP episodes could have been averted. The additional cost of CSS for 2006 was estimated to be €10,585.34. The cost per averted VAP episode was €1,176.15. Assuming a VAP cost of €4,387, a total of 3 averted VAP episodes would neutralize the additional cost. For a low VAP incidence of 6.6%, the cost per averted VAP would be €1,323. If each patient required 2 tubes during ventilation, the cost would be €1,383.69 per averted VAP episode. CONCLUSION: Replacement of CV with CSS was cost-effective even when assuming the most pessimistic scenario of VAP incidence and costs.

Validity of medical staff assessment at admission of patient's risk of nosocomial infection: a prospective study in a surgical intensive care unit.

OBJECTIVE: To evaluate the ability of a surgical intensive care unit (SICU) medical staff to assess at admission the individual risk of nosocomial infection (NI) during SICU stay in patients admitted for at least 48 h. DESIGN: Prospective observational study. SETTING: A tertiary-care university hospital. PATIENTS AND PARTICIPANTS: 201 admissions to the SICU from November 19, 2003, until April 16, 2004. MEASUREMENTS AND RESULTS: Assessment by medical staff at admission of each patient's estimated risk of NI (pneumonia, venous central catheter-related infection, symptomatic urinary tract infection, and bacteremia) during SICU hospitalization, in order to classify patients into four groups: NI risk very low or absent (group 1), low (group 2), high (group 3), very high or certain (group 4). NI was diagnosed via routine surveillance according to Centers for Disease Control case definitions. RESULTS: 154 patients were assessed; the percentage of patients with NI increased with estimated risk at admission, from 0% in group 1 to 14.3% in group 4. Positive predictive value of medical assessment varied from 8.4% to 14.5%, according to the cutoff value. Negative predictive value varied from 92.1% to 100%. CONCLUSION: Our study suggests that ICU physicians encounter a major difficulty when informing patients or patients' families about the risk of NI occurrence, as they cannot predict this risk accurately. This limitation should be explained to patients and their families.