The Long-Term Impact of Frailty After an Intensive Care Unit Admission Due to Chronic Obstructive Pulmonary Disease.

Rationale: Frailty is an increasingly recognized aspect of chronic obstructive pulmonary disease (COPD). The impact of frailty on long-term survival after admission to an intensive care unit (ICU) due to an exacerbation of COPD has not been described. Objective: The objective was to quantify the impact of frailty on time to death up to 4 years after admission to the ICU in Australia and New Zealand for an exacerbation of COPD. Methods: We performed a multicenter retrospective cohort study of adult patients admitted to 179 ICUs with a primary diagnosis of an exacerbation of COPD using the Australian and New Zealand Intensive Care Society Adult Patient Database from January 1, 2018, through December 31, 2020, in New Zealand, and March 31, 2022, in Australia. Frailty was measured using the clinical frailty scale (CFS). The primary outcome was survival up to 4 years after ICU admission. The secondary outcome was readmission to the ICU due to an exacerbation of COPD. Measurements and Main Results: We examined 7126 patients of which 3859 (54.1%) were frail (CFS scores of 5-8). Mortality in not-frail individuals versus frail individuals at 1 and 4 years was 19.8% versus 40.4%, and 56.8% versus 77.3% respectively (both p<0.001). Frailty was independently associated with a shorter time to death (adjusted hazard ratio 1.66; 95% confidence interval 1.54-1.80).There was no difference in the proportion of survivors with or without frailty who were readmitted to the ICU during a subsequent hospitalization. Conclusions: Frailty was independently associated with poorer long-term survival in patients admitted to the ICU with an exacerbation of COPD.

Sex Differences in Vital Organ Support Provided to ICU Patients.

OBJECTIVES: Critically ill women may receive less vital organ support than men but the mortality impact of this differential treatment remains unclear. We aimed to quantify sex differences in vital organ support provided to adult ICU patients and describe the relationship between sex, vital organ support, and mortality. DESIGN: In this retrospective observational study, we examined the provision of invasive ventilation (primary outcome), noninvasive ventilation, vasoactive medication, renal replacement therapy, extracorporeal membrane oxygenation (ECMO), or any one of these five vital organ supports in women compared with men. We performed logistic regression investigating the association of sex with each vital organ support, adjusted for illness severity, diagnosis, preexisting treatment limitation, year, and hospital. We performed logistic regression for hospital mortality adjusted for the same variables, stratified by vital organ support (secondary outcome). SETTING AND PATIENTS: ICU admissions in the Australia and New Zealand Intensive Care Society Adult Patient Database 2018-2021. This registry records admissions from 90% of ICUs in the two nations. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We examined 699,535 ICU admissions (43.7% women) to 199 ICUs. After adjustment, women were less likely than men to receive invasive ventilation (odds ratio [OR], 0.64; 99% CI, 0.63-0.65) and each other organ support except ECMO. Women had lower adjusted hospital mortality overall (OR, 0.94; 99% CI, 0.91-0.97). Among patients who did not receive any organ support, women had significantly lower adjusted hospital mortality (OR, 0.82; 99% CI, 0.76-0.88); among patients who received any organ support women and men were equally likely to die (OR, 1.01; 99% CI, 0.97-1.04). CONCLUSIONS: Women received significantly less vital organ support than men in ICUs in Australia and New Zealand. However, our findings suggest that women may not be harmed by this conservative approach to treatment.

Epidemiology of Intensive Care Patients Classified as a Third Sex in Australia and New Zealand.

BACKGROUND: Patient sex affects treatment and outcomes in critical illness. Previous studies of sex differences in critical illness compared female and male patients. In this study, we describe the group of patients classified as a third sex admitted to ICUs in Australia and New Zealand. RESEARCH QUESTION: What are the admission characteristics and outcomes of ICU patients classified as belonging to a third sex group compared with patients classified as female or male? STUDY DESIGN AND METHODS: Retrospective observational study of admissions to 200 ICUs, recorded in the Australian and New Zealand Intensive Care Society's Adult Patient Database from 2018 to 2022. We undertook mixed effect logistic regression to compare hospital mortality across the sex groups, adjusted for illness severity, diagnosis, treatment limitation, year, and hospital. RESULTS: We examined 892,161 admissions, of whom 525 (0.06%) were classified as third sex. Patients classified as third sex were represented across all diagnostic categories, jurisdictions, and hospital types. On average, they were younger than the groups classified as female (59.2 ± 20.0 vs 61.3 ± 18.4 years; P = .02) or male (63.2 ± 16.7 years; P < .001), respectively. Patients classified as third sex were more likely to be admitted after orthopedic surgery (10.1% third sex admissions [95% CI, 7.7%-13.0%]; 6.2% female [95% CI, 6.1%-6.3%]; 4.8% male [95% CI, 4.7%-4.9%]) and drug overdose (8.8% third sex admissions [95% CI, 6.5%-11.5%]; 4.2% female [95% CI, 4.1%-4.2%]; 3.1% male [95% CI, 3.0%-3.1%]). There was no difference in the adjusted hospital mortality of patients classified as third sex compared with the other groups. INTERPRETATION: Patients classified as third sex composed a small minority group of adult ICU patients. This group had a different diagnostic case mix but similar outcomes to the groups classified as female or male. Further characterizing a third sex group will require improved processes for recording sex and gender in health records.

Thirty years of ANZICS CORE: A clinical quality success story.

In 2023, the Australian and New Zealand Intensive Care Society (ANZICS) Registry run by the Centre for Outcomes and Resources Evaluation (CORE) turns 30 years old. It began with the Adult Patient Database, the Australian and New Zealand Paediatric Intensive Care Registry, and the Critical Care Resources Registry, and it now includes Central Line Associated Bloodstream Infections Registry, the Extra-Corporeal Membrane Oxygenation Database, and the Critical Health Resources Information System. The ANZICS Registry provides comparative case-mix reports, risk-adjusted clinical outcomes, process measures, and quality of care indicators to over 200 intensive care units describing more than 200 000 adult and paediatric admissions annually. The ANZICS CORE outlier management program has been a major contributor to the improved patient outcomes and provided significant cost savings to the healthcare sector. Over 200 peer-reviewed papers have been published using ANZICS Registry data. The ANZICS Registry was a vital source of information during the COVID-19 pandemic. Upcoming developments include reporting of long-term survival and patient-reported outcome and experience measures.

Measuring the Impact of ICU Strain on Mortality, After-Hours Discharge, Discharge Delay, Interhospital Transfer, and Readmission in Australia With the Activity Index.

OBJECTIVES: ICU resource strain leads to adverse patient outcomes. Simple, well-validated measures of ICU strain are lacking. Our objective was to assess whether the "Activity index," an indicator developed during the COVID-19 pandemic, was a valid measure of ICU strain. DESIGN: Retrospective national registry-based cohort study. SETTING: One hundred seventy-five public and private hospitals in Australia (June 2020 through March 2022). SUBJECTS: Two hundred seventy-seven thousand seven hundred thirty-seven adult ICU patients. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Data from the Australian and New Zealand Intensive Care Society Adult Patient Database were matched to the Critical Health Resources Information System. The mean daily Activity index of each ICU (census total of "patients with 1:1 nursing" + "invasive ventilation" + "renal replacement" + "extracorporeal membrane oxygenation" + "active COVID-19," divided by total staffed ICU beds) during the patient's stay in the ICU was calculated. Patients were categorized as being in the ICU during very quiet (Activity index < 0.1), quiet (0.1 to < 0.6), intermediate (0.6 to < 1.1), busy (1.1 to < 1.6), or very busy time-periods (≥ 1.6). The primary outcome was in-hospital mortality. Secondary outcomes included after-hours discharge from the ICU, readmission to the ICU, interhospital transfer to another ICU, and delay in discharge from the ICU. Median Activity index was 0.87 (interquartile range, 0.40-1.24). Nineteen thousand one hundred seventy-seven patients died (6.9%). In-hospital mortality ranged from 2.4% during very quiet to 10.9% during very busy time-periods. After adjusting for confounders, being in an ICU during time-periods with higher Activity indices, was associated with an increased risk of in-hospital mortality (odds ratio [OR], 1.49; 99% CI, 1.38-1.60), after-hours discharge (OR, 1.27; 99% CI, 1.21-1.34), readmission (OR, 1.18; 99% CI, 1.09-1.28), interhospital transfer (OR, 1.92; 99% CI, 1.72-2.15), and less delay in ICU discharge (OR, 0.58; 99% CI, 0.55-0.62): findings consistent with ICU strain. CONCLUSIONS: The Activity index is a simple and valid measure that identifies ICUs in which increasing strain leads to progressively worse patient outcomes.

The impact of body mass index on long-term survival after ICU admission due to COVID-19: A retrospective multicentre study.

Objective: The impact of obesity on long-term survival after intensive care unit (ICU) admission with severe coronavirus disease 2019 (COVID-19) is unclear. We aimed to quantify the impact of obesity on time to death up to two years in patients admitted to Australian and New Zealand ICUs. Design: Retrospective multicentre study. Setting: 92 ICUs between 1st January 2020 through to 31st December 2020 in New Zealand and 31st March 2022 in Australia with COVID-19, reported in the Australian and New Zealand Intensive Care Society adult patient database. Participants: All patients with documented height and weight to estimate the body mass index (BMI) were included. Obesity was classified patients according to the World Health Organization recommendations. Interventions and main outcome measures: The primary outcome was survival time up to two years after ICU admission. The effect of obesity on time to death was assessed using a Cox proportional hazards model. Confounders were acute illness severity, sex, frailty, hospital type and jurisdiction for all patients. Results: We examined 2,931 patients; the median BMI was 30.2 (IQR 25.6-36.0) kg/m2. Patients with a BMI ≥30 kg/m2 were younger (median [IQR] age 57.7 [46.2-69.0] vs. 63.0 [50.0-73.6]; p < 0.001) than those with a BMI <30 kg/m2. Most patients (76.6%; 2,244/2,931) were discharged alive after ICU admission. The mortality at two years was highest for BMI categories <18.5 kg/m2 (35.4%) and 18.5-24.9 kg/m2 (31.1%), while lowest for BMI ≥40 kg/m2 (14.5%). After adjusting for confounders and with BMI 18.5-24.9 kg/m2 category as a reference, only the BMI ≥40 kg/m2 category patients had improved survival up to 2 years (hazard ratio = 0.51; 95%CI: 0.34-0.76). Conclusions: The obesity paradox appears to exist beyond hospital discharge in critically ill patients with COVID-19 admitted in Australian and New Zealand ICUs. A BMI ≥40 kg/m2 was associated with a higher survival time of up to two years.

Incidence of death or disability at 6 months after extracorporeal membrane oxygenation in Australia: a prospective, multicentre, registry-embedded cohort study.

BACKGROUND: Extracorporeal membrane oxygenation (ECMO) is an invasive procedure used to support critically ill patients with the most severe forms of cardiac or respiratory failure in the short term, but long-term effects on incidence of death and disability are unknown. We aimed to assess incidence of death or disability associated with ECMO up to 6 months (180 days) after treatment. METHODS: This prospective, multicentre, registry-embedded cohort study was done at 23 hospitals in Australia from Feb 15, 2019, to Dec 31, 2020. The EXCEL registry included all adults (≥18 years) in Australia who were admitted to an intensive care unit (ICU) in a participating centre at the time of the study and who underwent ECMO. All patients who received ECMO support for respiratory failure, cardiac failure, or cardiac arrest during their ICU stay were eligible for this study. The primary outcome was death or moderate-to-severe disability (defined using the WHO Disability Assessment Schedule 2.0, 12-item survey) at 6 months after ECMO initiation. We used Fisher's exact test to compare categorical variables. This study is registered with ClinicalTrials.gov, NCT03793257. FINDINGS: Outcome data were available for 391 (88%) of 442 enrolled patients. The primary outcome of death or moderate-to-severe disability at 6 months was reported in 260 (66%) of 391 patients: 136 (67%) of 202 who received veno-arterial (VA)-ECMO, 60 (54%) of 111 who received veno-venous (VV)-ECMO, and 64 (82%) of 78 who received extracorporeal cardiopulmonary resuscitation (eCPR). After adjustment for age, comorbidities, Acute Physiology and Chronic Health Evaluation (APACHE) IV score, days between ICU admission and ECMO start, and use of vasopressors before ECMO, death or moderate-to-severe disability was higher in patients who received eCPR than in those who received VV-ECMO (VV-ECMO vs eCPR: risk difference [RD] -32% [95% CI -49 to -15]; p<0·001) but not VA-ECMO (VA-ECMO vs eCPR -8% [-22 to 6]; p=0·27). INTERPRETATION: In our study, only a third of patients were alive without moderate-to-severe disability at 6 months after initiation of ECMO. The finding that disability was common across all areas of functioning points to the need for long-term, multidisciplinary care and support for surviving patients who have had ECMO. Further studies are needed to understand the 180-day and longer-term prognosis of patients with different diagnoses receiving different modes of ECMO, which could have important implications for the selection of patients for ECMO and management strategies in the ICU. FUNDING: The National Health and Medical Research Council of Australia.

Variation in Bed-to-Physician Ratios During Weekday Daytime Hours in ICUs in Australia and New Zealand.

OBJECTIVES: To determine common "bed-to-physician" ratios during weekday hours across ICUs and assess factors associated with variability in this ratio. DESIGN: Retrospective cohort study. SETTING: All ICUs in Australia/New Zealand that participated in a staffing survey administered in 2017-2018. PATIENTS: ICU admissions from 2016 to 2018. METHODS: We linked survey data with patient-level data. We defined: 1) bed-to-intensivist ratio as the number of usually available ICU beds divided by the number of onsite weekday daytime intensivists; and 2) bed-to-physician ratio as the number of available ICU beds divided by the total number of physicians (intensivists + nonintensivists, including trainees). We calculated the median and interquartile range (IQR) of bed-to-intensivist ratio and bed-to-physician ratios during weekday hours. We assessed variability in each by type of hospital and ICU and by severity of illness of patients, defined by the predicted hospital mortality. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of the 123 (87.2%) of Australia/New Zealand ICUs that returned staffing surveys, 114 (92.7%) had an intensivist present during weekday daytime hours, and 116 (94.3%) reported at least one nonintensivist physician. The median bed-to-intensivist ratio was 8.0 (IQR, 6.0-11.4), which decreased to a bed-to-physician ratio of 3.0 (IQR, 2.2-4.9). These ratios varied with mean severity of illness of the patients in the unit. The median bed-to-intensivist ratio was highest (13.5) for ICUs with a mean predicted mortality > 2-4%, and the median bed-to-physician ratio was highest (5.7) for ICUs with a mean predicted mortality of > 4-6%. Both ratios decreased and plateaued in ICUs with a mean predicted mortality for patients greater than 8% (median bed-to-intensivist ratio range, 6.8-8.0, and bed-to-physician ratio range of 2.4-2.7). CONCLUSIONS: Weekday bed-to-physician ratios in Australia/New Zealand ICUs are lower than the bed-to-intensivist ratios and have a relatively fixed ratio of less than 3 for units taking care of patients with a higher average severity of illness. These relationships may be different in other countries or healthcare systems.

Sex Differences in Mortality of ICU Patients According to Diagnosis-related Sex Balance.

Rationale: Women have worse outcomes than men in several conditions more common in men, including cardiac surgery and burns. Objectives: To describe the relationship between sex balance within each diagnostic group of ICU admissions, defined as the percentage of patients who were women, and hospital mortality of women compared with men with that same diagnosis. Methods: We studied ICU patients in the Australian and New Zealand Intensive Care Society's Adult Patient Database (2011-2020). We performed mixed effects logistic regression for hospital mortality adjusted for sex, illness severity, ICU lead time, admission year, and hospital site. We compared sex balance with the adjusted hospital mortality of women compared with men for each diagnosis using weighted linear regression. Measurements and Main Results: There were 1,450,782 admissions (42.1% women), with no difference in the adjusted hospital mortality of women compared with men overall (odds ratio, 0.99; 99% confidence interval [CI], 0.97 to 1). As the percentage of women within each diagnosis increased, the adjusted mortality of women compared with men with that same diagnosis decreased (regression coefficient, -0.015; 99% CI; -0.020 to -0.011; P < 0.001), and the illness severity of women compared with men at ICU admission decreased (regression coefficient, -0.0026; 99% CI, -0.0035 to -0.0018; P < 0.001). Conclusions: Sex balance in diagnostic groups was inversely associated with both the adjusted mortality and illness severity of women compared with men. In diagnoses with relatively few women, women were more likely than men to die. In diagnoses with fewer men, men were more likely than women to die.

A prediction model to determine the untapped lung donor pool outside of the DonateLife network in Victoria.

Lung transplantation is limited by a lack of suitable lung donors. In Australia, the national donation organisation (DonateLife) has taken a major role in optimising organ donor identification. However, the potential outside the DonateLife network hospitals remains uncertain. We aimed to create a prediction model for lung donation within the DonateLife network and estimate the untapped lung donors outside of the DonateLife network. We reviewed all deaths in the state of Victoria's intensive care units using a prospectively collected population-based intensive care unit database linked to organ donation records. A logistic regression model derived using patient-level data was developed to characterise the lung donors within DonateLife network hospitals. Consequently, we estimated the expected number of lung donors in Victorian hospitals outside the DonateLife network and compared the actual number. Between 2014 and 2018, 291 lung donations occurred from 8043 intensive care unit deaths in DonateLife hospitals, while only three lung donations occurred from 1373 ICU deaths in non-DonateLife hospitals. Age, sex, postoperative admission, sepsis, neurological disease, trauma, chronic respiratory disease, lung oxygenation and serum creatinine were factors independently associated with lung donation. A highly discriminatory prediction model with area under the receiver operator characteristic curve of 0.91 was developed and accurately estimated the number of lung donors. Applying the model to non-DonateLife hospital data predicted only an additional five lung donors. This prediction model revealed few additional lung donor opportunities outside the DonateLife network, and the necessity of alternative and novel strategies for lung donation. A donor prediction model could provide a useful benchmarking tool to explore organ donation potential across different jurisdictions, hospitals and transplanting centres.

Genomic dissection of Klebsiella pneumoniae infections in hospital patients reveals insights into an opportunistic pathogen.

Klebsiella pneumoniae is a major cause of opportunistic healthcare-associated infections, which are increasingly complicated by the presence of extended-spectrum beta-lactamases (ESBLs) and carbapenem resistance. We conducted a year-long prospective surveillance study of K. pneumoniae clinical isolates in hospital patients. Whole-genome sequence (WGS) data reveals a diverse pathogen population, including other species within the K. pneumoniae species complex (18%). Several infections were caused by K. variicola/K. pneumoniae hybrids, one of which shows evidence of nosocomial transmission. A wide range of antimicrobial resistance (AMR) phenotypes are observed, and diverse genetic mechanisms identified (mainly plasmid-borne genes). ESBLs are correlated with presence of other acquired AMR genes (median n = 10). Bacterial genomic features associated with nosocomial onset are ESBLs (OR 2.34, p = 0.015) and rhamnose-positive capsules (OR 3.12, p < 0.001). Virulence plasmid-encoded features (aerobactin, hypermucoidy) are observed at low-prevalence (<3%), mostly in community-onset cases. WGS-confirmed nosocomial transmission is implicated in just 10% of cases, but strongly associated with ESBLs (OR 21, p < 1 × 10-11). We estimate 28% risk of onward nosocomial transmission for ESBL-positive strains vs 1.7% for ESBL-negative strains. These data indicate that K. pneumoniae infections in hospitalised patients are due largely to opportunistic infections with diverse strains, with an additional burden from nosocomially-transmitted AMR strains and community-acquired hypervirulent strains.

The Relationship between Frailty and Mechanical Ventilation: A Population-based Cohort Study.

Rationale: Frailty in critically ill patients is associated with higher mortality and prolonged length of stay; however, little is known about the impact on the duration of mechanical ventilation. Objectives: To identify the relationship between frailty and total duration of mechanical ventilation and the interaction with patients' age. Methods: This retrospective population-based cohort study was performed using data submitted to the Australian and New Zealand Intensive Care Society Adult Patient Database between 2017 and 2020. We analyzed adult critically ill patients who received invasive mechanical ventilation within the first 24 hours of intensive care unit admission. Results: Of 59,319 available patients receiving invasive mechanical ventilation, 8,331 (14%) were classified as frail. Patients with frailty had longer duration of mechanical ventilation compared with patients without frailty. Duration of mechanical ventilation increased with higher frailty score. Patients with frailty had longer intensive care unit and hospital stay with higher mortality than patients without frailty. After adjustment for relevant covariates in multivariate analyses, frailty was significantly associated with a reduced probability of cessation of invasive mechanical ventilation (adjusted hazard ratio, 0.57 [95% confidence interval, 0.51-0.64]; P < 0.001). Sensitivity and subgroup analyses suggested that frailty could prolong mechanical ventilation in survivors, and the relationship was especially strong in younger patients. Conclusions: Frailty score was independently associated with longer duration of mechanical ventilation and contributed to identifying patients who were less likely to be liberated from mechanical ventilation. The impact of frailty on ventilation time varied with age and was most apparent for younger patients.

An Audit of Lung Donor Pool: Optimal Current Donation Strategies and the Potential of Novel Time-Extended Donation After Circulatory Death Donation.

BACKGROUND: In Australia, increased organ donation and subsequent lung transplantation (LTx) rates have followed enhanced donor identification, referral and management, as well as the introduction of a donation after circulatory death (DCD) pathway. However, the number of patients waiting for LTx still continues to exceed the number of lung donors and the search for further suitable donors is critical. METHODS: All 2014-2018 Victorian DonateLife hospital deaths after intensive care unit (ICU) admission were analysed retrospectively to quantify unrecognised lung donors using current criteria, as well as novel time-extended (90 mins-24 hrs post-withdrawal) DCD lung donors. RESULTS: Using standard lung donor eligibility criteria, we identified 473 potential lung donors and a further 122 time-extended DCD potential lung donors among 3,538 patients meeting general eligibility criteria. Detailed review of end-of-life discussions with patient families and the reasons why they were not offered donation revealed several categories of additional lung donors-traditional lung donors missed in current practice (n=2); hepatitis C infected lung donors potentially treatable with direct-acting antivirals (n=14), time-extended DCD lung donors (n=60); donor lungs potentially suitable for transplant with use of ex-vivo lung perfusion (EVLP) (n=7). CONCLUSION: While the number of lung donor opportunities missed under existing DonateLife donor identification and management processes was limited, a time-extended DCD lung donation pathway could substantially expand the lung donor pool. The use of hepatitis C infected donors, and the possibility of EVLP to solve donor graft assessment or logistic issues, could also provide small additional lung donor opportunities.

Association of patient-to-intensivist ratio with hospital mortality in Australia and New Zealand.

PURPOSE: The impact of intensivist workload on intensive care unit (ICU) outcomes is incompletely described and assessed across healthcare systems and countries. We sought to examine the association of patient-to-intensivist ratio (PIR) with hospital mortality in Australia/New Zealand (ANZ) ICUs. METHODS: We conducted a retrospective study of adult admissions to ANZ ICUs (August 2016-June 2018) using two cohorts: "narrow", based on previously used criteria including restriction to ICUs with a single daytime intensivist; and "broad", refined by individual ICU daytime staffing information. The exposure was average daily PIR and the outcome was hospital mortality. We used summary statistics to describe both cohorts and multilevel multivariable logistic regression models to assess the association of PIR with mortality. In each, PIR was modeled using restricted cubic splines to allow for non-linear associations. The broad cohort model included non-PIR physician and non-physician staffing covariables. RESULTS: The narrow cohort of 27,380 patients across 67 ICUs (predicted mortality: median 1.2% [IQR 0.4-1.4%]; mean 5.9% [sd 13.2%]) had a median PIR of 10.1 (IQR 7-14). The broad cohort of 91,206 patients across 73 ICUs (predicted mortality: 1.9% [0.6-6.5%]; 7.6% [14.9%]) had a median PIR of 7.8 (IQR 5.8-10.2). We found no association of PIR with mortality in either the narrow (PIR 1st spline term odds ratio [95% CI]: 1 [0.94, 1.06], Wald testing of spline terms p = 0.61) or the broad (1.02 [0.97, 1.07], p = 0.4) cohort. CONCLUSION: We found no association of PIR with hospital mortality across ANZ ICUs. The low cohort predicted mortality may limit external validity.

Genomic surveillance of antimicrobial resistant bacterial colonisation and infection in intensive care patients.

BACKGROUND: Third-generation cephalosporin-resistant Gram-negatives (3GCR-GN) and vancomycin-resistant enterococci (VRE) are common causes of multi-drug resistant healthcare-associated infections, for which gut colonisation is considered a prerequisite. However, there remains a key knowledge gap about colonisation and infection dynamics in high-risk settings such as the intensive care unit (ICU), thus hampering infection prevention efforts. METHODS: We performed a three-month prospective genomic survey of infecting and gut-colonising 3GCR-GN and VRE among patients admitted to an Australian ICU. Bacteria were isolated from rectal swabs (n = 287 and n = 103 patients ≤2 and > 2 days from admission, respectively) and diagnostic clinical specimens between Dec 2013 and March 2014. Isolates were subjected to Illumina whole-genome sequencing (n = 127 3GCR-GN, n = 41 VRE). Multi-locus sequence types (STs) and antimicrobial resistance determinants were identified from de novo assemblies. Twenty-three isolates were selected for sequencing on the Oxford Nanopore MinION device to generate completed reference genomes (one for each ST isolated from ≥2 patients). Single nucleotide variants (SNVs) were identified by read mapping and variant calling against these references. RESULTS: Among 287 patients screened on admission, 17.4 and 8.4% were colonised by 3GCR-GN and VRE, respectively. Escherichia coli was the most common species (n = 36 episodes, 58.1%) and the most common cause of 3GCR-GN infection. Only two VRE infections were identified. The rate of infection among patients colonised with E. coli was low, but higher than those who were not colonised on admission (n = 2/33, 6% vs n = 4/254, 2%, respectively, p = 0.3). While few patients were colonised with 3GCR- Klebsiella pneumoniae or Pseudomonas aeruginosa on admission (n = 4), all such patients developed infections with the colonising strain. Genomic analyses revealed 10 putative nosocomial transmission clusters (≤20 SNVs for 3GCR-GN, ≤3 SNVs for VRE): four VRE, six 3GCR-GN, with epidemiologically linked clusters accounting for 21 and 6% of episodes, respectively (OR 4.3, p = 0.02). CONCLUSIONS: 3GCR-E. coli and VRE were the most common gut colonisers. E. coli was the most common cause of 3GCR-GN infection, but other 3GCR-GN species showed greater risk for infection in colonised patients. Larger studies are warranted to elucidate the relative risks of different colonisers and guide the use of screening in ICU infection control.

Associations Between Socioeconomic Status, Patient Risk, and Short-Term Intensive Care Outcomes.

OBJECTIVES: To investigate the association of socioeconomic status as measured by the average socioeconomic status of the area where a person resides on short-term mortality in adults admitted to an ICU in Queensland, Australia. DESIGN: Secondary data analysis using de-identified data from the Australian and New Zealand Intensive Care Society Centre for Outcome and Resource Evaluation linked to the publicly available area-level Index of Relative Socioeconomic Advantage and Disadvantage from the Australian Bureau of Statistics. SETTING: Adult ICUs from 35 hospitals in Queensland, Australia, from 2006 to 2015. PATIENTS: A total of 218,462 patient admissions. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The outcome measure was inhospital mortality. The main study variable was decile of Index of Relative Socioeconomic Advantage and Disadvantage. The overall crude inhospital mortality was 7.8%; 9% in the most disadvantaged decile and 6.9% in the most advantaged decile (p < 0.001). Increasing socioeconomic disadvantage was associated with increasing severity of illness as measured by Acute Physiology and Chronic Health Evaluation III score, admission with a diagnosis of sepsis or trauma, cardiac, respiratory, renal, and hepatic comorbidities, and remote location. Increasing socioeconomic advantage was associated with elective surgical admission, hematological and oncology comorbidities, and admission to a private hospital (all p < 0.001). After excluding patients admitted after elective surgery, in the remaining 106,843 patients, the inhospital mortality was 13.6%, 13.3% in the most disadvantaged, and 14.1% in the most advantaged. There was no trend in mortality across deciles of socioeconomic status after excluding elective surgery patients. In the logistic regression model adjusting for severity of illness and diagnosis, there was no statistically significant difference in the odds ratio of inhospital mortality for the most disadvantaged decile compared with other deciles. This suggests variables used for risk adjustment may lie on the causal pathway between socioeconomic status and outcome in ICU patients. CONCLUSIONS: Socioeconomic status as defined as Index of Relative Socioeconomic Advantage and Disadvantage of the area in which a patient lives was associated with ICU admission diagnosis, comorbidities, severity of illness, and crude inhospital mortality in this study. Socioeconomic status was not associated with inhospital mortality after excluding elective surgical patients or when adjusted for severity of illness and admission diagnosis. Commonly used measures for risk adjustment in intensive care improve understanding of the pathway between socioeconomic status and outcomes.

Annual prevalence, characteristics, and outcomes of intensive care patients with skin or soft tissue infections in Australia and New Zealand: A retrospective cohort study between 2006-2017.

BACKGROUND: There are limited published data on the epidemiology of skin and soft tissue infections (SSTIs) requiring intensive care unit (ICU) admission. This study intended to describe the annual prevalence, characteristics, and outcomes of critically ill adult patients admitted to the ICU for an SSTI. METHODS: This was a registry-based retrospective cohort study, using data submitted to the Australian and New Zealand Intensive Care Society Adult Patient Database for all admissions with SSTI between 2006 and 2017. The inclusion criteria were as follows: primary diagnosis of SSTI and age ≥16 years. The exclusion criteria were as follows: ICU readmissions (during the same hospital admission) and transfers from ICUs from other hospitals. The primary outcome was in-hospital mortality, and the secondary outcomes were ICU mortality and length of stay (LOS) in the ICU and hospital with independent predictors of outcomes. RESULTS: Admissions due to SSTI accounted for 10 962 (0.7%) of 1 470 197 ICU admissions between 2006 and 2017. Comorbidities were present in 25.2% of the study sample. The in-hospital mortality was 9% (991/10 962), and SSTI necessitating ICU admission accounted for 0.07% of in-hospital mortality of all ICU admissions between 2006 and 2017. Annual prevalence of ICU admissions for SSTI increased from 0.4% to 0.9% during the study period, but in-hospital mortality decreased from 16.1% to 6.8%. The median ICU LOS was 2.1 days (interquartile range = 3.4), and the median hospital LOS was 12.1 days (interquartile range = 20.6). ICU LOS remained stable between 2006 and 2017 (2.0-2.1 days), whereas hospital LOS decreased from 15.7 to 11.2 days. Predictors for in-hospital mortality included Australian and New Zealand Risk of Death scores [odds ratio (OR): 1.07; confidence interval (CI) (1.05, 1.09); p < 0.001], any comorbidity except diabetes [OR: 2.00; CI (1.05, 3.79); p = 0.035], and admission through an emergency response call [OR: 2.07; CI (1.03, 4.16); p = 0.041]. CONCLUSIONS: SSTIs are uncommon as primary ICU admission diagnosis. Although the annual prevalence of ICU admissions for SSTI has increased, in-hospital mortality and hospital LOS have decreased over the last decade.

Improving the predictability of time to death in controlled donation after circulatory death lung donors.

Although the use of donation after circulatory death (DCD) donors has increased lung transplant activity, 25-40% of intended DCD donors do not convert to actual donation because of no progression to asystole in the required time frame after withdrawal of cardiorespiratory support (WCRS). No studies have specifically focussed on DCD lung donor progression. This retrospective study reviewed intended DCD lung donors to make a prediction model of the likelihood of progression to death using logistic regression and classification and regression tree (CART). Between 2014 and 2018, 159 of 334 referred DCD donors were accepted, with 100 progressing to transplant, while 59 (37%) did not progress. In logistic regression, a length of ICU stay ≤ 5 days, severe infra-tentorial brain damage on imaging and use of vasopressin were related with the progression to actual donation. CART modelling of the likelihood of death within 90-minute post-WCRS provided prediction with a sensitivity of 1.00 and positive predictive value of 0.56 in the validation data set. In the nonprogressed DCD group, 26 died within 6 h post-WCRS. Referral received early after ICU admission, with nonspontaneous ventilatory mode, deep coma and severe infra-tentorial damage were relevant predictors. The CART model is useful to exclude DCD donor candidates with low probability of progression.

Acidemia subtypes in critically ill patients: An international cohort study.

PURPOSE: To study the prevalence, characteristic, outcome, and acid-base biomarker predictors of outcome for different acidemia subtypes. METHODS: We used national intensive care databases from three countries and classified acidemia subtypes as metabolic (standard base excess [SBE] < -2 mEq/L only), respiratory (PaCO2 > 42 mmHg only), and combined (both SBE < -2 mEq/L and PaCO2 > 42 mmHg) based on blood gas analysis in the first 24 h after ICU admission. To investigate acid-base predictors for hospital mortality, we applied the area under the receiver operating characteristic curve approach. RESULTS: We screened 643,689 ICU patients (2014-2018) and detected acidemia in 57.8%. The most common subtype was metabolic (42.9%), followed by combined (30.3%) and respiratory (25.9%). Combined acidemia had a mortality of 12.7%, compared with 11% for metabolic and 5.5% for respiratory. For combined acidemia, the best predictor of hospital mortality was pH. However, for metabolic or respiratory acidemia, it was SBE or PaCO2, respectively. CONCLUSIONS: In ICU patients with acidemia, mortality differs according to subtype and is highest in the combined subtype. Best acid-base predictors of mortality also differ according to subtype with best performance for pH in combined, SBE in metabolic, and PaCO2 in respiratory acidemia.

Expert consensus statements for the management of COVID-19-related acute respiratory failure using a Delphi method.

BACKGROUND: Coronavirus disease 2019 (COVID-19) pandemic has caused unprecedented pressure on healthcare system globally. Lack of high-quality evidence on the respiratory management of COVID-19-related acute respiratory failure (C-ARF) has resulted in wide variation in clinical practice. METHODS: Using a Delphi process, an international panel of 39 experts developed clinical practice statements on the respiratory management of C-ARF in areas where evidence is absent or limited. Agreement was defined as achieved when > 70% experts voted for a given option on the Likert scale statement or > 80% voted for a particular option in multiple-choice questions. Stability was assessed between the two concluding rounds for each statement, using the non-parametric Chi-square (χ2) test (p < 0·05 was considered as unstable). RESULTS: Agreement was achieved for 27 (73%) management strategies which were then used to develop expert clinical practice statements. Experts agreed that COVID-19-related acute respiratory distress syndrome (ARDS) is clinically similar to other forms of ARDS. The Delphi process yielded strong suggestions for use of systemic corticosteroids for critical COVID-19; awake self-proning to improve oxygenation and high flow nasal oxygen to potentially reduce tracheal intubation; non-invasive ventilation for patients with mixed hypoxemic-hypercapnic respiratory failure; tracheal intubation for poor mentation, hemodynamic instability or severe hypoxemia; closed suction systems; lung protective ventilation; prone ventilation (for 16-24 h per day) to improve oxygenation; neuromuscular blocking agents for patient-ventilator dyssynchrony; avoiding delay in extubation for the risk of reintubation; and similar timing of tracheostomy as in non-COVID-19 patients. There was no agreement on positive end expiratory pressure titration or the choice of personal protective equipment. CONCLUSION: Using a Delphi method, an agreement among experts was reached for 27 statements from which 20 expert clinical practice statements were derived on the respiratory management of C-ARF, addressing important decisions for patient management in areas where evidence is either absent or limited. TRIAL REGISTRATION: The study was registered with Clinical trials.gov Identifier: NCT04534569.