None.

Objective: To explore associations between frailty (Clinical Frailty Scale score of 5 or more) in very old patients in intensive care units (ICUs) and their clinical outcomes (mortality, discharge destination).

Background: A threshold Clinical Frailty Scale (CFS) of 5 (indicating mild frailty) has been proposed to guide ICU admission for UK patients with coronavirus disease 2019 (COVID-19) pneumonia. However, the impact of frailty on mortality with (non-COVID-19) pneumonia in critical illness is unknown. We examined the triage utility of the CFS in patients with pneumonia requiring ICU. Methods: We conducted a retrospective cohort study of adult patients admitted with pneumonia to 170 ICUs in Australia and New Zealand from January 1, 2018 to September 31, 2019. We classified patients as: non-frail (CFS 1e4) frail (CFS 5e8), mild/moderately frail (CFS 5e6),and severe/very severely frail (CFS 7e8). We evaluated mortality (primary outcome) adjusting for site, age, sex, mechanical ventilation, pneumonia type and illness severity. We also compared the proportion of ICU bed-days occupied between frailty categories. Results: 1852/5607 (33%) patients were classified as frail, including1291/3056 (42%) of patients aged >65 yr, who would potentially be excluded from ICU admission under UK-based COVID-19 triage guidelines. Only severe/very severe frailty scores were associated with mortality (adjusted odds ratio [aOR] for CFS¼7: 3.2; 95% confidence interval [CI]: 1.3e7.8; CFS¼8 [aOR: 7.2; 95% CI: 2.6e20.0]). These patients accounted for 7% of ICU bed days. Vulnerability (CFS¼4) and mild frailty (CFS¼5) were associated with a similar mortality risk (CFS¼4 [OR: 1.6; 95% CI: 0.7e3.8]; CFS¼5 [OR: 1.6; 95% CI: 0.7e3.9]). Conclusions: Patients with severe and very severe frailty account for relatively few ICU bed days as a result of pneumonia, whilst adjusted mortality analysis indicated little difference in risk between patients in vulnerable, mild, and moderate frailty categories. These data do not support CFS 5 to guide ICU admission for pneumonia.

An acute pulmonary embolism (aPE) is characterised by occlusion of one or more pulmonary arteries. Physiological disturbance may be minimal, but often cardiac output decreases as the right ventricle attempts to overcome increased afterload. Additionally, ventilation‐perfusion mismatches can develop in affected vascular beds, reducing systemic oxygenation. Incidence is reported at 50–75 per 100 000 in Australia and New Zealand, with 30‐day mortality rates ranging from 0.5% to over 20%. Incidence is likely to increase with the ageing population, increased survival of patients with comorbidities that are considered risk factors and improving sensitivity of imaging techniques. Use of clinical prediction scores, such as the Wells score, has assisted in clinical decision‐making and decreased unnecessary radiological investigations. However, imaging (i.e. computed tomography pulmonary angiography or ventilation‐perfusion scans) is still necessary for objective diagnosis. Anti‐coagulation remains the foundation of PE management. Haemodynamically unstable patients require thrombolysis unless absolutely contraindicated, while stable patients with right ventricular dysfunction or ischaemia should be aggressively anti‐coagulated. Stable patients with no right ventricular dysfunction can be discharged home early with anti‐coagulation and review. However, treatment should be case dependent with full consideration of the patient’s clinical state. Direct oral anti‐coagulants have become an alternative to vitamin K antagonists and are facilitating shorter hospital admissions. Additionally, duration of anti‐coagulation must be decided by considering any provoking factors, bleeding risk and comorbid state. Patients with truly unprovoked or idiopathic PE often require indefinite treatment, while in provoked cases it is typically 3 months with some patients requiring longer periods of 6–12 months.

Background Candidaemia is associated with high mortality. Variables associated with mortality have been published previously, but not developed into a risk predictive model for mortality. We sought to describe the current epidemiology of candidaemia in Australia, analyse predictors of 30-day all-cause mortality, and develop and validate a mortality risk predictive model. Methods Adults with candidaemia were studied prospectively over 12 months at eight institutions. Clinical and laboratory variables at time of blood culture-positivity were subject to multivariate analysis for association with 30-day all-cause mortality. A predictive score for mortality was examined by area under receiver operator characteristic curves and a historical data set was used for validation. Results The median age of 133 patients with candidaemia was 62 years; 76 (57%) were male and 57 (43%) were female. Co-morbidities included underlying haematologic malignancy ( n = 20; 15%), and solid organ malignancy in ( n = 25; 19%); 55 (41%) were in an intensive care unit (ICU). Non- albicans Candida spp . accounted for 61% of cases (81/133). All-cause 30-day mortality was 31%. A gastrointestinal or unknown source was associated with higher overall mortality than an intravascular or urologic source ( p < 0.01). A risk predictive score based on age > 65 years, ICU admission, chronic organ dysfunction, preceding surgery within 30 days, haematological malignancy, source of candidaemia and antibiotic therapy for ≥10 days stratified patients into < 20% or ≥ 20% predicted mortality. The model retained accuracy when validated against a historical dataset ( n = 741). Conclusions Mortality in patients with candidaemia remains high. A simple mortality risk predictive score stratifying patients with candidaemia into < 20% and ≥ 20% 30-day mortality is presented. This model uses information available at time of candidaemia diagnosis is easy to incorporate into decision support systems. Further validation of this model is warranted. Electronic supplementary material The online version of this article (10.1186/s12879-019-4065-5) contains supplementary material, which is available to authorized users.

No abstract

Australian New Zealand Clinical Trials Registry: ACTRN12615001327572.

Frailty is one of the major challenges for intensive care, affecting one-third of intensive care unit patients and being associated with a range of poor health outcomes. Determination of frailty in critical illness using the Clinical Frailty Scale has recently been adopted by the Australian and New Zealand Intensive Care Society, but it is not known whether this is able to be measured from the clinical record without interviewing patients or their relatives. The aims of this retrospective cohort study were to test whether a Clinical Frailty Scale score could be assigned in an intensive care unit population from the clinical record, and to assess the inter-rater reliability of frailty measured in this manner. A total of 144 patients were enrolled. Of these, 137 (95%) were able to have a Clinical Frailty Scale score assigned, and 22 (15%) were scored as frail (Clinical Frailty Scale ≥5). Cohen’s kappa coefficient for inter-rater reliability between assessors was 0.67, confirming substantial agreement. Consistent with other critically ill cohorts, frailty was associated on multivariate analysis with age, Charlson comorbidity score, dependence with activities of daily living, and limitation of medical treatment, indicating validity of this approach to frailty measurement. Our results imply that frailty measurement is possible and feasible from the intensive care unit clinical record, which is of importance as routine measurement and reporting of frailty in intensive care units in our region increases. Future work should seek to validate an assigned Clinical Frailty Scale score with that obtained directly from patients or their next of kin.