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Background: The translation of evidence from clinical trials into practice is complex. One approach to facilitating this translation is to consider the 'implementability' of trials as they are designed and conducted. Implementability of trials refers to characteristics of the design, execution and reporting of a late-phase clinical trial that can influence the capacity for the evidence generated by that trial to be implemented. On behalf of the Australian Clinical Trials Alliance (ACTA), the national peak body representing networks of clinician researchers conducting investigator-initiated clinical trials, we conducted a pragmatic literature review to develop a concept map of implementability.Methods: Documents were included in the review if they related to the design, conduct and reporting of late-phase clinical trials; described factors that increased or decreased the capacity of trials to be implemented; and were published after 2009 in English. Eligible documents included systematic reviews, guidance documents, tools or primary studies (if other designs were not available). With an expert reference group, we developed a preliminary concept map and conducted a snowballing search based on known relevant papers and websites of key organisations in May 2019.Results: Sixty-five resources were included. A final map of 38 concepts was developed covering the domains of validity, relevance and usability across the design, conduct and reporting of a trial. The concepts drew on literature relating to implementation science, consumer engagement, pragmatic trials, reporting, research waste and other fields. No single resource addressed more than ten of the 38 concepts in the map.Conclusions: The concept map provides trialists with a tool to think through a range of areas in which practical action could enhance the implementability of their trials. Future work could validate the strength of the associations between the concepts identified and implementability of trials and investigate the effectiveness of steps to address each concept. ACTA will use this concept map to develop guidance for trialists in Australia.Trial Registration: This review did not include health-related outcomes and was therefore not eligible for registration in the PROSPERO register. [ABSTRACT FROM AUTHOR]

During the 2009 outbreak of pandemic (H1N1) 2009 influenza (pH1N1) in Australia, acute and convalescent serum specimens were collected from 33 patients with severe respiratory disease admitted to intensive care units. Using hemagglutination inhibition of pH1N1, 29 paired serum samples showed significant increases in specific antibody titers. Of these 29 patients, 18 had pH1N1 RNA detected by routine nucleic acid testing. These results indicate that up to onethird of pH1N1 cases may not have laboratory confirmation of infection unless serological testing is included for suspected cases. [ABSTRACT FROM AUTHOR]

The authors reflect on sustaining the research and health care in Australia through investigator networks and clinical trials. The authors state that Australians must continue to take advantage from a health system based from clinical trials evidence. The authors also mention the new funding model that can encourage research within the health care budget.

Objectives: To use clinically accessible tools to determine unit-level and individual patient factors associated with sound levels and sleep disruption in a range of representative ICUs.Design: A cross-sectional, observational study.Setting: Australian and New Zealand ICUs.Patients: All patients 16 years or over occupying an ICU bed on one of two Point Prevalence study days in 2015.Interventions: Ambient sound was measured for 1 minute using an application downloaded to a personal mobile device. Bedside nurses also recorded the total time and number of awakening for each patient overnight.Measurements and Main Results: The study included 539 participants with sound level recorded using an application downloaded to a personal mobile device from 39 ICUs. Maximum and mean sound levels were 78 dB (SD, 9) and 62 dB (SD, 8), respectively. Maximum sound levels were higher in ICUs with a sleep policy or protocol compared with those without maximum sound levels 81 dB (95% CI, 79-83) versus 77 dB (95% CI, 77-78), mean difference 4 dB (95% CI, 0-2), p < 0.001. There was no significant difference in sound levels regardless of single room occupancy, mechanical ventilation status, or illness severity. Clinical nursing staff in all 39 ICUs were able to record sleep assessment in 15-minute intervals. The median time awake and number of prolonged disruptions were 3 hours (interquartile range, 1-4) and three (interquartile range, 2-5), respectively.Conclusions: Across a large number of ICUs, patients were exposed to high sound levels and substantial sleep disruption irrespective of factors including previous implementation of a sleep policy. Sound and sleep measurement using simple and accessible tools can facilitate future studies and could feasibly be implemented into clinical practice. [ABSTRACT FROM AUTHOR]

Abstract: Aim: Determine current resuscitation practices and outcomes in patients presenting to the emergency department (ED) with sepsis and hypoperfusion or septic shock in Australia and New Zealand (ANZ). Methods: Three-month prospective, multi-centre, observational study of all adult patients with sepsis and hypoperfusion or septic shock in the ED of 32 ANZ tertiary-referral, metropolitan and rural hospitals. Results: 324 patients were enrolled (mean [SD] age 63.4 [19.2] years, APACHE II score 19.0 [8.2], 52.5% male). Pneumonia (n =138/324, 42.6%) and urinary tract infection (n =98/324, 30.2%) were the commonest sources of sepsis. Between ED presentation and 6hours post-enrolment (T6hrs), 44.4% (n =144/324) of patients received an intra-arterial catheter, 37% (n =120/324) a central venous catheter and 0% (n =0/324) a continuous central venous oxygen saturation (ScvO2) catheter. Between enrolment and T6hrs, 32.1% (n =104/324) received a vasopressor infusion, 7.4% (n =24/324) a red blood cell transfusion, 2.5% (n =8/324) a dobutamine infusion and 18.5% (n =60/324) invasive mechanical ventilation. Twenty patients (6.2%) were transferred from ED directly to the operating theatre, 36.4% (n =118/324) were admitted directly to ICU, 1.2% (n =4/324) died in the ED and 56.2% (n =182/324) were transferred to the hospital floor. Overall ICU admission rate was 52.4% (n =170/324). ICU and overall in-hospital mortality were 18.8% (n =32/170) and 23.1% (n =75/324) respectively. In-hospital mortality was not different between patients admitted to ICU (24.7%, n =42/170) and the hospital floor (21.4%, n =33/154). Conclusions: Management of ANZ patients presenting to ED with sepsis does not routinely include protocolised, ScvO2-directed resuscitation. In-hospital mortality compares favourably with reported mortality in international sepsis trials and nationwide surveys of resuscitation practices. [Copyright &y& Elsevier]

Objective: To compare the demographic and clinical features, management, and outcomes for patients admitted with COVID-19 to intensive care units (ICUs) during the first, second, and third waves of the pandemic in Australia., Design, Setting, and Participants: People aged 16 years or more admitted with polymerase chain reaction-confirmed COVID-19 to the 78 Australian ICUs participating in the Short Period Incidence Study of Severe Acute Respiratory Infection (SPRINT-SARI) Australia project during the first (27 February - 30 June 2020), second (1 July 2020 - 25 June 2021), and third COVID-19 waves (26 June - 1 November 2021)., Main Outcome Measures: Primary outcome: in-hospital mortality., Secondary Outcomes: ICU mortality; ICU and hospital lengths of stay; supportive and disease-specific therapies., Results: 2493 people (1535 men, 62%) were admitted to 59 ICUs: 214 during the first (9%), 296 during the second (12%), and 1983 during the third wave (80%). The median age was 64 (IQR, 54-72) years during the first wave, 58 (IQR, 49-68) years during the second, and 54 (IQR, 41-65) years during the third. The proportion without co-existing illnesses was largest during the third wave (41%; first wave, 32%; second wave, 29%). The proportion of ICU beds occupied by patients with COVID-19 was 2.8% (95% CI, 2.7-2.9%) during the first, 4.6% (95% CI, 4.3-5.1%) during the second, and 19.1% (95% CI, 17.9-20.2%) during the third wave. Non-invasive (42% v 15%) and prone ventilation strategies (63% v 15%) were used more frequently during the third wave than during the first two waves. Thirty patients (14%) died in hospital during the first wave, 35 (12%) during the second, and 281 (17%) during the third. After adjusting for age, illness severity, and other covariates, the risk of in-hospital mortality was similar for the first and second waves, but 9.60 (95% CI, 3.52-16.7) percentage points higher during the third than the first wave., Conclusion: The demographic characteristics of patients in intensive care with COVID-19 and the treatments they received during the third pandemic wave differed from those of the first two waves. Adjusted in-hospital mortality was highest during the third wave., (© 2022 The Authors. Medical Journal of Australia published by John Wiley & Sons Australia, Ltd on behalf of AMPCo Pty Ltd.)

Introduction: The aim of this study was to investigate current mobilization practice, strength at ICU discharge and functional recovery at 6 months among mechanically ventilated ICU patients., Method: This was a prospective, multi-centre, cohort study conducted in twelve ICUs in Australia and New Zealand. Patients were previously functionally independent and expected to be ventilated for >48 hours. We measured mobilization during invasive ventilation, sedation depth using the Richmond Agitation and Sedation Scale (RASS), co-interventions, duration of mechanical ventilation, ICU-acquired weakness (ICUAW) at ICU discharge, mortality at day 90, and 6-month functional recovery including return to work., Results: We studied 192 patients (mean age 58.1 ± 15.8 years; mean Acute Physiology and Chronic Health Evaluation (APACHE) (IQR) II score, 18.0 (14 to 24)). Mortality at day 90 was 26.6% (51/192). Over 1,351 study days, we collected information during 1,288 planned early mobilization episodes in patients on mechanical ventilation for the first 14 days or until extubation (whichever occurred first). We recorded the highest level of early mobilization. Despite the presence of dedicated physical therapy staff, no mobilization occurred in 1,079 (84%) of these episodes. Where mobilization occurred, the maximum levels of mobilization were exercises in bed (N = 94, 7%), standing at the bed side (N = 11, 0.9%) or walking (N = 26, 2%). On day three, all patients who were mobilized were mechanically ventilated via an endotracheal tube (N = 10), whereas by day five 50% of the patients mobilized were mechanically ventilated via a tracheostomy tube (N = 18)., Conclusions: Early mobilization of patients receiving mechanical ventilation was uncommon. More than 50% of patients discharged from the ICU had developed ICU-acquired weakness, which was associated with death between ICU discharge and day-90., Clinical Trial Registration: ClinicalTrials.gov NCT01674608. Registered 14 August 2012.

Introduction: There is conflicting data as to whether obesity is an independent risk factor for mortality in severe pandemic (H1N1) 2009 influenza (A(H1N1)pdm09). It is postulated that excess inflammation and cytokine production in obese patients following severe influenza infection leads to viral pneumonitis and/or acute respiratory distress syndrome., Methods: Demographic, laboratory and clinical data prospectively collected from obese and non-obese patients admitted to nine adult Australian intensive care units (ICU) during the first A(H1N1)pdm09 wave, supplemented with retrospectively collected data, were compared., Results: Of 173 patients, 100 (57.8%), 73 (42.2%) and 23 (13.3%) had body mass index (BMI) <30 kg/m(2), ≥30 kg/m(2) (obese) and ≥40 kg/m(2) (morbidly obese) respectively. Compared to non-obese patients, obese patients were younger (mean age 43.4 vs. 48.4 years, p = 0.035) and more likely to develop pneumonitis (61% vs. 44%, p = 0.029). Extracorporeal membrane oxygenation use was greater in morbidly obese compared to non-obese patients (17.4% vs. 4.7%, p = 0.04). Higher mortality rates were observed in non-obese compared to obese patients, but not after adjusting for severity of disease. C-reactive protein (CRP) levels and hospital length of stay (LOS) were similar. Amongst ICU survivors, obese patients had longer ICU LOS (median 11.9 vs. 6.8 days, p = 0.017). Similar trends were observed when only patients infected with A(H1N1)pdm09 were examined., Conclusions: Among patients admitted to ICU during the first wave of A(H1N1)pdm09, obese and morbidly obese patients with severe infection were more likely to develop pneumonitis compared to non-obese patients, but mortality rates were not increased. CRP is not an accurate marker of pneumonitis.

Background: There is uncertainty about which end points should be used for Phase II trials in critically ill patients., Objective: To systematically evaluate potential end points for Phase II trials in critically ill patients., Design and Setting: A report outlining a process of literature review and recommendations from a consensus meeting conducted on behalf of the Australian and New Zealand Intensive Care Society Clinical Trials Group (ANZICS CTG) in October 2011., Results and Conclusions: The consensus panel concluded that there are no adequately validated end points for Phase II trials in critically ill patients. However, the following were identified as potential Phase II end points: hospital-free days to Day 90, ICU-free days to Day 28, ventilator-free days to Day 28, cardiovascular support-free days to Day 28, and renal replacement therapy-free days to Day 28. We recommend that these end points be evaluated further.

Objective: To determine the accuracy of International classification of diseases, 10th revision, Australian modification (ICD-10-AM) codes in identifying severe sepsis in patients admitted from the emergency department (ED)., Design, Setting and Participants: A retrospective cohort study of ED patients transferred to the intensive care unit of a tertiary hospital within 24 hours of leaving ED, 2000- 2006., Main Outcome Measures: Clinical diagnosis of severe sepsis compared with diagnosis-based code (DB-C) categories based on ICD-10-AM codes in the Emergency Department Information Systems (EDIS) and Hospital Morbidity Data System (HMDS); sensitivity, specificity, positive predictive value (PPV) and negative predictive value of these databases., Results: In the study period, 1645 patients were transferred to the ICU from the ED, of whom 254 had severe sepsis. Single discharge ICD-10-AM codes recorded in the EDIS and the principal ICD-10-AM codes recorded in the HMDS that fell into D-BC categories for sepsis, pneumonia, viscous perforation, peritonitis, cholecystitis or cholangitis had a PPV of 85.0% (95% CI, 78.4%-91.6%; 96/113) and 88.2% (95%CI, 72.6%-82.6%; 112/127), respectively. The respective sensitivity was 37.8% (95% CI, 31.8%-43.8%) (96/254) and 44.1% (95% CI, 38.0-50.2) (112/254). In contrast, ICD-10-AM codes in the HMDS that code for infection and organ dysfunction had a PPV of 33.5% (95% CI, 30.0%-37.0%; 227/677) and sensitivity of 89.4% (95% CI, 85.6%-93.2%; 227/254)., Conclusion: ICD-10-AM codes recorded in the EDIS or HMD had limited utility for identifying severe sepsis in patients admitted to ICU from the ED.

Introduction: During the first winter of exposure, the H1N1 2009 influenza virus placed considerable strain on intensive care unit (ICU) services in Australia and New Zealand (ANZ). We assessed the impact of the H1N1 2009 influenza virus on ICU services during the second (2010) winter, following the implementation of vaccination., Methods: A prospective, cohort study was conducted in all ANZ ICUs during the southern hemisphere winter of 2010. Data on demographic and clinical characteristics, including vaccination status and outcomes, were collected. The characteristics of patients admitted during the 2010 and 2009 seasons were compared., Results: From 1 June to 15 October 2010, there were 315 patients with confirmed influenza A, of whom 283 patients (90%) had H1N1 2009 (10.6 cases per million inhabitants; 95% confidence interval (CI), 9.4 to 11.9) which was an observed incidence of 33% of that in 2009 (P < 0.001). The maximum daily ICU occupancy was 2.4 beds (95% CI, 1.8 to 3) per million inhabitants in 2010 compared with 7.5 (95% CI, 6.5 to 8.6) in 2009, (P < 0.001). The onset of the epidemic in 2010 was delayed by five weeks compared with 2009. The clinical characteristics were similar in 2010 and 2009 with no difference in the age distribution, proportion of patients treated with mechanical ventilation, duration of ICU admission, or hospital mortality. Unlike 2009 the incidence of critical illness was significantly greater in New Zealand (18.8 cases per million inhabitants compared with 9 in Australia, P < 0.001). Of 170 patients with known vaccination status, 26 (15.3%) had been vaccinated against H1N1 2009., Conclusions: During the 2010 ANZ winter, the impact of H1N1 2009 on ICU services was still appreciable in Australia and substantial in New Zealand. Vaccination failure occurred.

Objective: We aim to evaluate the incidence and outcome of acute kidney injury (AKI) among critically ill adult patients with H1N1 2009 infection., Design and Patients: From a prospectively collected influenza A (H1N1) 2009 bi-national, we identified 671 adult patients admitted to intensive care unit (ICU) from June 1 to August 31, 2009. Of these, 628 (93.6%) had admission and/or peak serum creatinine values during ICU stay. We defined AKI according to the creatinine criteria of the RIFLE classification., Results: Of 628 adult patients, 211 [33.6%, 95% confidence interval (CI) 29.8-37.4%] had AKI: 41 (6.5%) risk, 56 (8.9%) injury and 114 (18.2%) failure. Of all 211 AKI patients, 76 [36.0% (29.4-42.6%)] died in hospital (36.6% in risk, 25.0% in injury and 41.3% in failure group) compared with 33 of 408 (8.1%) patients without AKI. Among the 33 AKI patients treated with renal replacement therapy, 13 died (39.4%). Mechanical ventilation [odds ratio (OR) 3.62 (2.07-6.34)], any severe co-morbidity (OR 2.36, 95% CI 1.15-3.71), age (OR 1.02, 95% CI 1.01-1.03 per 1 year increase), and AKI (OR 6.69, 95% CI 4.25-10.55) were independently associated with hospital mortality., Conclusions: Acute kidney injury appears common in H1N1 2009 infected patients and is independently associated with an increased risk of hospital mortality.

The year 2009 was characterized by a pandemic with a new virus, the 2009 H1N1 influenza virus. This pandemic was responsible for thousands of deaths worldwide, many more hospital admissions, and thousands of admissions to intensive care units (ICUs). Among those admitted to ICUs, the pandemic was associated with a mortality of approximately 16%, a high incidence of acute lung injury and, in some cases, acute respiratory distress syndrome severe enough to require support with extracorporeal membrane oxygenation. As part of such a critical illness, a percentage of patients developed acute kidney injury (AKI) which complicated their clinical course and, in some patients, required support by renal replacement therapy. In a case series from Mexico, the incidence of severe AKI was reported in about 30% of the patients. Similarly, at the Austin Hospital, of 13 cases, 8 developed AKI with 3 being classified in the failure category of the RIFLE classification. Among the patients with AKI, hospital mortality was approximately 25%. Of the AKI patients, 3 (37.5%) received renal replacement therapy and, among these, 1 died. In a case of severe AKI and multi-organ failure from whom histological material was obtained, the renal histopathological findings were typical of acute tubular necrosis. One patient who suffered from hypoxic brain injury due to cardiac arrest at home secondary to H1N1 pneumonia became a kidney and liver donor. There was no evidence of viral infiltration on kidney biopsy and the recipient did not develop H1N1 infection., (2010 S. Karger AG, Basel.)