Pub Date : 2026-03-01Epub Date: 2026-02-20DOI: 10.1016/j.ccrj.2026.100165
Nihal Kumta MB, BS, FANZCA, FCICM , Germaine M. Kenny PGcert (ICU), PGcert (health management) , Jason Meyer BN, MSc , James R. Winearls BSc, MB, BS, FRCP, FCICM , James McCullough MB, ChB, MMed, FCICM , Kiran Shekar MB, BS, PhD, FCICM, FCCCM , Jayshree Lavana MB, BS, MD(medicine), FCICM , Anand Krishnan MB, BS, FCICM , Kyle C. White MB, BS, MPH, FRACP, FCICM , David A. Cook MB, BS, PhD, FANZCA, FCICM , Christopher J. Joyce MB, ChB, PhD, FANZCA, FCICM
Objective
To describe the Queensland Adult ECMO Retrieval Service (QAERS) and assess observed mortality of patients retrieved and treated with ECMO, against benchmarks.
Design
Data was retrospectively collected from clinical and quality assurance databases at the three QAERS hospitals. Demographic data, diagnostic category, and hospital mortality were collected for patients referred to QAERS. Additional data was collected on patients receiving ECMO either before or after transport to a receiving hospital (ECMO patients), enabling calculation of RESP or SAVE scores. In ECMO patients with cardiogenic shock, individual risk of deaths were calculated by SAVE score. Monte Carlo analysis generated a discrete probability distribution function (PDF) of expected number of deaths, with 95 % confidence intervals (CI). The observed number of deaths was compared to this PDF. This was repeated for ECMO patients with respiratory failure, using RESP score.
Setting
ICUs in Queensland and Northern NSW.
Participants
All patients referred to QAERS from May 2017 to December 2023.
Main outcome measures
Predicted and observed mortality of ECMO patients with cardiogenic shock or respiratory failure.
Results
237 patients were referred. 135 were retrieved, with 77 transported on ECMO. 11 commenced ECMO after transfer, giving a total of 88 ECMO patients. 35 ECMO patients had cardiogenic shock and 53 had respiratory failure. 16 cardiogenic shock patients died (95 % CI of PDF 17–28). 7 respiratory failure patients died (95 % CI of PDF 8–19).
Conclusions
Observed mortality of patients retrieved and treated with ECMO was lower than mortality predicted by SAVE and RESP scores.
目的:描述昆士兰成人ECMO检索服务(QAERS),并根据基准评估ECMO检索和治疗患者的观察死亡率。设计:回顾性地从QAERS三家医院的临床和质量保证数据库中收集数据。收集转介QAERS的患者的人口统计数据、诊断类别和住院死亡率。在运送到接收医院之前或之后收集接受ECMO的患者(ECMO患者)的其他数据,从而计算RESP或SAVE评分。在合并心源性休克的ECMO患者中,通过SAVE评分计算个体死亡风险。蒙特卡罗分析生成预期死亡人数的离散概率分布函数(PDF),置信区间(CI)为95%。将观察到的死亡人数与该PDF进行比较。使用RESP评分对伴有呼吸衰竭的ECMO患者进行重复研究。环境:昆士兰和新南威尔士州北部的icu。参与者:2017年5月至2023年12月期间所有QAERS患者。主要结局指标:预测和观察心源性休克或呼吸衰竭的ECMO患者死亡率。结果:237例患者转诊。取出135例,经ECMO转运77例。11例转移后开始ECMO,共计88例。ECMO患者心源性休克35例,呼吸衰竭53例。16例心源性休克患者死亡(95% CI: PDF 17-28)。7例呼吸衰竭患者死亡(95% CI: PDF 8-19)。结论:ECMO患者的观察死亡率低于SAVE和RESP评分预测的死亡率。
{"title":"Queensland adult ECMO retrieval service: A description of the service and analysis of outcomes","authors":"Nihal Kumta MB, BS, FANZCA, FCICM , Germaine M. Kenny PGcert (ICU), PGcert (health management) , Jason Meyer BN, MSc , James R. Winearls BSc, MB, BS, FRCP, FCICM , James McCullough MB, ChB, MMed, FCICM , Kiran Shekar MB, BS, PhD, FCICM, FCCCM , Jayshree Lavana MB, BS, MD(medicine), FCICM , Anand Krishnan MB, BS, FCICM , Kyle C. White MB, BS, MPH, FRACP, FCICM , David A. Cook MB, BS, PhD, FANZCA, FCICM , Christopher J. Joyce MB, ChB, PhD, FANZCA, FCICM","doi":"10.1016/j.ccrj.2026.100165","DOIUrl":"10.1016/j.ccrj.2026.100165","url":null,"abstract":"<div><h3>Objective</h3><div>To describe the Queensland Adult ECMO Retrieval Service (QAERS) and assess observed mortality of patients retrieved and treated with ECMO, against benchmarks.</div></div><div><h3>Design</h3><div>Data was retrospectively collected from clinical and quality assurance databases at the three QAERS hospitals. Demographic data, diagnostic category, and hospital mortality were collected for patients referred to QAERS. Additional data was collected on patients receiving ECMO either before or after transport to a receiving hospital (ECMO patients), enabling calculation of RESP or SAVE scores. In ECMO patients with cardiogenic shock, individual risk of deaths were calculated by SAVE score. Monte Carlo analysis generated a discrete probability distribution function (PDF) of expected number of deaths, with 95 % confidence intervals (CI). The observed number of deaths was compared to this PDF. This was repeated for ECMO patients with respiratory failure, using RESP score.</div></div><div><h3>Setting</h3><div>ICUs in Queensland and Northern NSW.</div></div><div><h3>Participants</h3><div>All patients referred to QAERS from May 2017 to December 2023.</div></div><div><h3>Main outcome measures</h3><div>Predicted and observed mortality of ECMO patients with cardiogenic shock or respiratory failure.</div></div><div><h3>Results</h3><div>237 patients were referred. 135 were retrieved, with 77 transported on ECMO. 11 commenced ECMO after transfer, giving a total of 88 ECMO patients. 35 ECMO patients had cardiogenic shock and 53 had respiratory failure. 16 cardiogenic shock patients died (95 % CI of PDF 17–28). 7 respiratory failure patients died (95 % CI of PDF 8–19).</div></div><div><h3>Conclusions</h3><div>Observed mortality of patients retrieved and treated with ECMO was lower than mortality predicted by SAVE and RESP scores.</div></div>","PeriodicalId":49215,"journal":{"name":"Critical Care and Resuscitation","volume":"28 1","pages":"Article 100165"},"PeriodicalIF":1.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147327809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Non-invasive ventilation (NIV) and high-flow nasal cannula (HFNC) have been used to prevent reintubation. We aimed to describe the utilisation patterns and analyze temporal trends of NIV and HFNC after extubation.
Design
Retrospective multicenter cohort study using the Japanese Intensive care PAtient Database (JIPAD) from 2018 to 2022.
Setting
Facilities that consecutively registered cases in JIPAD during the study period.
Participants
We included adult patients (>18 years) who were receiving mechanical ventilation at the time of intensive care unit (ICU) admission, with a duration of mechanical ventilation of at least 24 h.
Interventions
None.
Main outcome measures
Temporal trends in the utilisation of NIV and HFNC after extubation over the 5-year study period.
Results
We included 12,687 eligible patients from 40 ICUs. Based on the Cochran–Armitage test, the proportion of patients receiving NIV decreased from the years 2018 to 2022 (6.7-3.9 %, P for trend <0.001), while that receiving HFNC significantly increased (15.9-28.0 %, P for trend <0.001). After multivariable adjustment (with 2018 as the reference year) and relative to oxygen therapy, the year 2022 was associated with a significant decrease in NIV (adjusted odds ratio, 0.67; 95 % confidence interval, 0.52-0.88) and a significant increase in HFNC (adjusted odds ratio, 1.89; 95 % confidence interval, 1.62-2.21).
Conclusions
We analysed over 12,000 patients in this retrospective multicenter cohort study. The proportion of HFNC use after extubation increased, while NIV use decreased, and these changes remained significant after multivariable analysis. Further research is warranted to clarify appropriate indications for NIV and HFNC after extubation.
{"title":"Temporal trends in post-extubation respiratory management and reintubation risk factors in Japan: A retrospective multicenter cohort study","authors":"Toshinori Maezawa MD , Masaaki Sakuraya MD, MPH , Akihiro Takaba MD","doi":"10.1016/j.ccrj.2026.100170","DOIUrl":"10.1016/j.ccrj.2026.100170","url":null,"abstract":"<div><h3>Objective</h3><div>Non-invasive ventilation (NIV) and high-flow nasal cannula (HFNC) have been used to prevent reintubation. We aimed to describe the utilisation patterns and analyze temporal trends of NIV and HFNC after extubation.</div></div><div><h3>Design</h3><div>Retrospective multicenter cohort study using the Japanese Intensive care PAtient Database (JIPAD) from 2018 to 2022.</div></div><div><h3>Setting</h3><div>Facilities that consecutively registered cases in JIPAD during the study period.</div></div><div><h3>Participants</h3><div>We included adult patients (>18 years) who were receiving mechanical ventilation at the time of intensive care unit (ICU) admission, with a duration of mechanical ventilation of at least 24 h.</div></div><div><h3>Interventions</h3><div>None.</div></div><div><h3>Main outcome measures</h3><div>Temporal trends in the utilisation of NIV and HFNC after extubation over the 5-year study period.</div></div><div><h3>Results</h3><div>We included 12,687 eligible patients from 40 ICUs. Based on the Cochran–Armitage test, the proportion of patients receiving NIV decreased from the years 2018 to 2022 (6.7-3.9 %, P for trend <0.001), while that receiving HFNC significantly increased (15.9-28.0 %, P for trend <0.001). After multivariable adjustment (with 2018 as the reference year) and relative to oxygen therapy, the year 2022 was associated with a significant decrease in NIV (adjusted odds ratio, 0.67; 95 % confidence interval, 0.52-0.88) and a significant increase in HFNC (adjusted odds ratio, 1.89; 95 % confidence interval, 1.62-2.21).</div></div><div><h3>Conclusions</h3><div>We analysed over 12,000 patients in this retrospective multicenter cohort study. The proportion of HFNC use after extubation increased, while NIV use decreased, and these changes remained significant after multivariable analysis. Further research is warranted to clarify appropriate indications for NIV and HFNC after extubation.</div></div>","PeriodicalId":49215,"journal":{"name":"Critical Care and Resuscitation","volume":"28 1","pages":"Article 100170"},"PeriodicalIF":1.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147357396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-19DOI: 10.1016/j.ccrj.2026.100169
Laurie Showler MBChB , Yasmine Ali Abdelhamid MBBS, PhD , Melissa J. Ankravs BPharm, MClinPharm , Jeremy Goldin MBBS, MM , Mark P. Plummer MBBS, PhD , Brianna Tascone BBiomed (Hons) , Kathleen Byrne RN, MNSc , Andrew Perkins BSc, RPSGT , Kirk Kee MBBS, PhD , Cara Moore MBBS , Barry Johnston MB, BCh, BAO, MBioethics , Jeffrey Presneill MBBS, MBiostat, PhD , Adam M. Deane MBBS, PhD
Objective
Patients in the intensive care unit (ICU) suffer from disturbed sleep and pharmacological sleep aids are frequently prescribed despite limited data on their efficacy. The objective of this study was to assess the effect of a single nocturnal dose of the benzodiazepine temazepam on sleep duration and quality in ICU patients.
Adult ICU patients whose treating clinician considered that a pharmacological sleep aid was indicated.
Interventions
A single weight- and age-adjusted dose of temazepam (10–30 mg) or a matching placebo was administered enterally at 21:00 h.
Main outcome measures
The primary outcome was total sleep time between 21:00 and 07:00 h by hourly structured nurse assessment. Secondary outcomes included the evaluation of sleep quality, independently determined by the bedside nurse and patient using the Richards-Campbell Sleep Questionnaire.
Results
Between October 2020 and May 2024, 56 patients received temazepam (n = 28) or placebo (n = 28). The mean (standard deviation) total sleep time with temazepam was 349 (120) vs. placebo 291 (124) minutes; difference = 57 min (95% confidence intervals: −11 to 130); p = 0.10. No differences in total Richards-Campbell Sleep Questionnaire sleep quality were observed when assessed by the nurse (57 (17) vs. 49 (23), p = 0.15) or by the patient (50 (28) vs. 51 (23), p = 0.70).
Conclusion
A single dose of temazepam was not observed to improve the duration or quality of nocturnal sleep for patients in the ICU.
Trial registration
Retrospectively registered with the Australian and New Zealand Clinical Trials Registry on 11th June 2021 (ACTRN 12621000742875).
{"title":"A pilot, parallel-group, blinded, placebo-controlled, randomiseD, pRagmatic clinical trial investigating the Effect of temazepAM on objective and subjective measures of sleep in critically ill patients (the DREAM trial)","authors":"Laurie Showler MBChB , Yasmine Ali Abdelhamid MBBS, PhD , Melissa J. Ankravs BPharm, MClinPharm , Jeremy Goldin MBBS, MM , Mark P. Plummer MBBS, PhD , Brianna Tascone BBiomed (Hons) , Kathleen Byrne RN, MNSc , Andrew Perkins BSc, RPSGT , Kirk Kee MBBS, PhD , Cara Moore MBBS , Barry Johnston MB, BCh, BAO, MBioethics , Jeffrey Presneill MBBS, MBiostat, PhD , Adam M. Deane MBBS, PhD","doi":"10.1016/j.ccrj.2026.100169","DOIUrl":"10.1016/j.ccrj.2026.100169","url":null,"abstract":"<div><h3>Objective</h3><div>Patients in the intensive care unit (ICU) suffer from disturbed sleep and pharmacological sleep aids are frequently prescribed despite limited data on their efficacy. The objective of this study was to assess the effect of a single nocturnal dose of the benzodiazepine temazepam on sleep duration and quality in ICU patients.</div></div><div><h3>Design</h3><div>Prospective, single-centre, blinded, placebo-controlled, parallel-group, randomised clinical trial.</div></div><div><h3>Setting</h3><div>A tertiary ICU in Australia.</div></div><div><h3>Participants</h3><div>Adult ICU patients whose treating clinician considered that a pharmacological sleep aid was indicated.</div></div><div><h3>Interventions</h3><div>A single weight- and age-adjusted dose of temazepam (10–30 mg) or a matching placebo was administered enterally at 21:00 h.</div></div><div><h3>Main outcome measures</h3><div>The primary outcome was total sleep time between 21:00 and 07:00 h by hourly structured nurse assessment. Secondary outcomes included the evaluation of sleep quality, independently determined by the bedside nurse and patient using the Richards-Campbell Sleep Questionnaire.</div></div><div><h3>Results</h3><div>Between October 2020 and May 2024, 56 patients received temazepam (n = 28) or placebo (n = 28). The mean (standard deviation) total sleep time with temazepam was 349 (120) vs. placebo 291 (124) minutes; difference = 57 min (95% confidence intervals: −11 to 130); p = 0.10. No differences in total Richards-Campbell Sleep Questionnaire sleep quality were observed when assessed by the nurse (57 (17) vs. 49 (23), p = 0.15) or by the patient (50 (28) vs. 51 (23), p = 0.70).</div></div><div><h3>Conclusion</h3><div>A single dose of temazepam was not observed to improve the duration or quality of nocturnal sleep for patients in the ICU.</div></div><div><h3>Trial registration</h3><div>Retrospectively registered with the Australian and New Zealand Clinical Trials Registry on 11th June 2021 (ACTRN 12621000742875).</div></div>","PeriodicalId":49215,"journal":{"name":"Critical Care and Resuscitation","volume":"28 1","pages":"Article 100169"},"PeriodicalIF":1.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147311714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-23DOI: 10.1016/j.ccrj.2025.100161
Bao N. Nguyen BOptom, PhD, Ella Stathis BSc(Hons), Bang V. Bui BSc(Optom), MOptom, PhD, Lauren N. Ayton BOptom, PhD, David B. Grayden BSc, BE(Hons), PhD, Sam E. John BE(Medical Electronics), ME(Electronics), PhD, Janine Stubbs BSc(Hons), MBiostat, PhD, Andrew Morokoff MBBS, PhD, FRACS, Olivia Gigli BBiomedSc(Hons), Brianna Tascone BBiomedSc(Hons), Ryan Nolan MBBS, BSc(Hons), MRCP(UK), Emily J. See MBBS, BMedSci, MSc(Oxon), PhD, FRACP, FCICM, Adam M. Deane MBBS, PhD, FRACP, FCICM, Yasmine Ali Abdelhamid MBBS, PhD, FRACP, FCICM
{"title":"Can intraocular pressure serve as a non-invasive surrogate marker for intracranial pressure following traumatic brain injury?","authors":"Bao N. Nguyen BOptom, PhD, Ella Stathis BSc(Hons), Bang V. Bui BSc(Optom), MOptom, PhD, Lauren N. Ayton BOptom, PhD, David B. Grayden BSc, BE(Hons), PhD, Sam E. John BE(Medical Electronics), ME(Electronics), PhD, Janine Stubbs BSc(Hons), MBiostat, PhD, Andrew Morokoff MBBS, PhD, FRACS, Olivia Gigli BBiomedSc(Hons), Brianna Tascone BBiomedSc(Hons), Ryan Nolan MBBS, BSc(Hons), MRCP(UK), Emily J. See MBBS, BMedSci, MSc(Oxon), PhD, FRACP, FCICM, Adam M. Deane MBBS, PhD, FRACP, FCICM, Yasmine Ali Abdelhamid MBBS, PhD, FRACP, FCICM","doi":"10.1016/j.ccrj.2025.100161","DOIUrl":"10.1016/j.ccrj.2025.100161","url":null,"abstract":"","PeriodicalId":49215,"journal":{"name":"Critical Care and Resuscitation","volume":"28 1","pages":"Article 100161"},"PeriodicalIF":1.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147424332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Discrepancies between laboratory sodium and point-of-care arterial blood gas sodium values may lead to delayed interpretation of, and intervention on, the results. We studied the mean difference between these two techniques and assessed the degree of agreement.
Design
A multicentre, retrospective, observational study was conducted.
Setting
Twelve intensive care units in Queensland, Australia, with tertiary-level hospitals accounting for 81% of admissions were included in the study.
Participants
Adult patients with at least one paired laboratory sodium and arterial blood gas measurement during their intensive care unit admission were a part of this study.
Main outcome measures
Main outcome measures included mean difference between laboratory sodium and point-of-care sodium measurement, with a positive difference demonstrating laboratory sodium values higher than arterial blood gas sodium values.
Results
A total of 65,042 patients with 224,383 paired samples were included in the analysis. The Bland–Altman mean difference of laboratory sodium and arterial blood gas sodium was 0.72 mmol/L (95% limit of agreement [LoA]: 4.35) with a Deming regression slope of 0.93 (95% confidence interval: 0.92, 0.94) and intercept +10.07 (p < 0.001). On subgroup analysis of hyponatraemia, eunatraemia and hypernatraemia a mean difference (95% LoA) of 1.53 mmol/L (4.21), 0.15 mmol/L (4.39), and −1.02 mmol/L (5.37), was calculated, respectively. Patients with severe hyperglycaemia and normal albumin had a mean difference (95% LoA) of −1.85 mmol/L (4.78). Analysis of mild, moderate, and severe subgroups within both hyponatraemic and hypernatraemic samples showed increasing mean differences, with severe hyponatraemia showing a mean difference of 2.01 mmol/L (95% LoA: 8.08) and severe hypernatraemia showing a mean difference of −4.7 mmol/L (95% LoA: 15.46).
Conclusions
Point-of-care arterial blood gas sodium measurements show small mean differences in eunatraemia and good agreement with paired laboratory samples in adult intensive care unit patients. Caution should be applied when interchanging results between laboratory and point-of-care sodium values in patients with moderate to severe dysnatraemia, as serial measurements using different methods during treatment are unlikely to be within a clinically acceptable range. This is important when caring for patient groups with severe hyponatraemia and induced hypernatraemia, and serial measurement may be better achieved with point-of-care testing due to a combination of ease of access, repeatability, and lower cost.
{"title":"A comparison of sodium concentration measured in laboratory autoanalyser versus point-of-care blood gas machine: A retrospective, multicentre, analytical study in a large adult intensive care unit population","authors":"Keegan Hunter BMedSc MD , Chris Anstey MBBS BSc MSc FANZCA FCICM PhD , Alexander Nesbitt BSc MBBS FCICM AFHEA , Karthik Venkatesh BMed MD FCICM , Dinesh Parmar MD FRCA FCICM , Amanda Corley RN PhD , Marissa Daniels MBBS , Jatinder Grewal FCICM, FANZCA, GchPOM , Kevin B. Laupland MD, PhD , Mahesh Ramanan BSc(Med) MBBS(Hons) MMed(Clin Epi) FCICM , Alexis Tabah MD FCICM , James McCullough MMed FCICM , Aashish Kumar MBBS FCICM , Antony G. Attokaran MBBS FCICM FRACP , Stephen Luke MBBS BSc(Hons) FCICM , Peter Garrett MBBS, BSc(Hons) FCICM FACEM FCEM , Stephen Whebell MBBS FCICM , Sebastiaan Blank FCICM , Philippa McIlroy BPhty (Hons) MBBS FCICM , Kyle C. White BSc MBBS MPH FCICM FRACP","doi":"10.1016/j.ccrj.2025.100149","DOIUrl":"10.1016/j.ccrj.2025.100149","url":null,"abstract":"<div><h3>Objective</h3><div>Discrepancies between laboratory sodium and point-of-care arterial blood gas sodium values may lead to delayed interpretation of, and intervention on, the results. We studied the mean difference between these two techniques and assessed the degree of agreement.</div></div><div><h3>Design</h3><div>A multicentre, retrospective, observational study was conducted.</div></div><div><h3>Setting</h3><div>Twelve intensive care units in Queensland, Australia, with tertiary-level hospitals accounting for 81% of admissions were included in the study.</div></div><div><h3>Participants</h3><div>Adult patients with at least one paired laboratory sodium and arterial blood gas measurement during their intensive care unit admission were a part of this study.</div></div><div><h3>Main outcome measures</h3><div>Main outcome measures included mean difference between laboratory sodium and point-of-care sodium measurement, with a positive difference demonstrating laboratory sodium values higher than arterial blood gas sodium values.</div></div><div><h3>Results</h3><div>A total of 65,042 patients with 224,383 paired samples were included in the analysis. The Bland–Altman mean difference of laboratory sodium and arterial blood gas sodium was 0.72 mmol/L (95% limit of agreement [LoA]: 4.35) with a Deming regression slope of 0.93 (95% confidence interval: 0.92, 0.94) and intercept +10.07 (p < 0.001). On subgroup analysis of hyponatraemia, eunatraemia and hypernatraemia a mean difference (95% LoA) of 1.53 mmol/L (4.21), 0.15 mmol/L (4.39), and −1.02 mmol/L (5.37), was calculated, respectively. Patients with severe hyperglycaemia and normal albumin had a mean difference (95% LoA) of −1.85 mmol/L (4.78). Analysis of mild, moderate, and severe subgroups within both hyponatraemic and hypernatraemic samples showed increasing mean differences, with severe hyponatraemia showing a mean difference of 2.01 mmol/L (95% LoA: 8.08) and severe hypernatraemia showing a mean difference of −4.7 mmol/L (95% LoA: 15.46).</div></div><div><h3>Conclusions</h3><div>Point-of-care arterial blood gas sodium measurements show small mean differences in eunatraemia and good agreement with paired laboratory samples in adult intensive care unit patients. Caution should be applied when interchanging results between laboratory and point-of-care sodium values in patients with moderate to severe dysnatraemia, as serial measurements using different methods during treatment are unlikely to be within a clinically acceptable range. This is important when caring for patient groups with severe hyponatraemia and induced hypernatraemia, and serial measurement may be better achieved with point-of-care testing due to a combination of ease of access, repeatability, and lower cost.</div></div>","PeriodicalId":49215,"journal":{"name":"Critical Care and Resuscitation","volume":"27 4","pages":"Article 100149"},"PeriodicalIF":1.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-10-17DOI: 10.1016/j.ccrj.2025.100133
Kristen S. Gibbons PhD , Renate Le Marsney MPH , Andrew Goodwin PhD , Rayna Reddy BSc , Patricia Gilholm PhD , David Pilcher MBBS, FCICM , Ben Gelbart MBBS, FRACP, FCICM, PhD , the Australian and New Zealand Intensive Care Society Paediatric Study Group (ANZICS PSG)
Objectives
The objective of this study was to assess data-related resources, infrastructure, and capabilities in Australia and New Zealand (ANZ) intensive care units (ICUs).
Design
Electronic multicentre survey was conducted.
Setting
ANZ ICUs between June and October 2024.
Participants
All ANZ ICUs contributing to the Australian and New Zealand Intensive Care Society Adult Patient Database and/or Australian and New Zealand Paediatric Intensive Care Registry were included in this study.
Interventions
There are none to declare.
Main outcome measures
The main outcome measures included types of medical records, digital data capture and research availability, digital enhancement plans, staffing, and research collaboration.
Results
Of 209 ICUs, 112 (54%) responded; 13 paediatric, 21 mixed, and 78 adult ICUs, with responses from all ANZ jurisdictions. Overall, 59% used paper records (5 paediatric and 61 mixed/adult), 28% digitised (7 paediatric and 24 mixed/adult), and 59% electronic health records (EHRs; 10 paediatric and 56 mixed/adult), with most EHRs introduced within the last decade (76%). In units with an EHR, 59% collected data secondly or minutely in the EHR and >75% collected EHR data on patient demographics, clinical notes, laboratory results, medications, fluids, bedside monitors, and respiratory support devices. Data Managers were employed within 45% of ICUs, with 96% able to extract data for audit and 92% for research. Respondents reported frustrations with delayed EHR implementation and limited data extraction mechanisms.
Conclusions
Substantial variability exists across ANZ ICUs in digital health adoption, data capture, and data management resources. Quantifying differences in digital information, improving data extraction, and building collaborative networks are key steps for supporting research and innovation across units.
{"title":"Building the future of ICU care: Is our digital foundation strong enough? A multicentre survey of Australian and New Zealand intensive care units","authors":"Kristen S. Gibbons PhD , Renate Le Marsney MPH , Andrew Goodwin PhD , Rayna Reddy BSc , Patricia Gilholm PhD , David Pilcher MBBS, FCICM , Ben Gelbart MBBS, FRACP, FCICM, PhD , the Australian and New Zealand Intensive Care Society Paediatric Study Group (ANZICS PSG)","doi":"10.1016/j.ccrj.2025.100133","DOIUrl":"10.1016/j.ccrj.2025.100133","url":null,"abstract":"<div><h3>Objectives</h3><div>The objective of this study was to assess data-related resources, infrastructure, and capabilities in Australia and New Zealand (ANZ) intensive care units (ICUs).</div></div><div><h3>Design</h3><div>Electronic multicentre survey was conducted.</div></div><div><h3>Setting</h3><div>ANZ ICUs between June and October 2024.</div></div><div><h3>Participants</h3><div>All ANZ ICUs contributing to the Australian and New Zealand Intensive Care Society Adult Patient Database and/or Australian and New Zealand Paediatric Intensive Care Registry were included in this study.</div></div><div><h3>Interventions</h3><div>There are none to declare.</div></div><div><h3>Main outcome measures</h3><div>The main outcome measures included types of medical records, digital data capture and research availability, digital enhancement plans, staffing, and research collaboration.</div></div><div><h3>Results</h3><div>Of 209 ICUs, 112 (54%) responded; 13 paediatric, 21 mixed, and 78 adult ICUs, with responses from all ANZ jurisdictions. Overall, 59% used paper records (5 paediatric and 61 mixed/adult), 28% digitised (7 paediatric and 24 mixed/adult), and 59% electronic health records (EHRs; 10 paediatric and 56 mixed/adult), with most EHRs introduced within the last decade (76%). In units with an EHR, 59% collected data secondly or minutely in the EHR and >75% collected EHR data on patient demographics, clinical notes, laboratory results, medications, fluids, bedside monitors, and respiratory support devices. Data Managers were employed within 45% of ICUs, with 96% able to extract data for audit and 92% for research. Respondents reported frustrations with delayed EHR implementation and limited data extraction mechanisms.</div></div><div><h3>Conclusions</h3><div>Substantial variability exists across ANZ ICUs in digital health adoption, data capture, and data management resources. Quantifying differences in digital information, improving data extraction, and building collaborative networks are key steps for supporting research and innovation across units.</div></div>","PeriodicalId":49215,"journal":{"name":"Critical Care and Resuscitation","volume":"27 4","pages":"Article 100133"},"PeriodicalIF":1.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145324281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-10-16DOI: 10.1016/j.ccrj.2025.100136
Maria de Freitas BM BS, BSc, BMedSci, Lucinda Roberts MBBS, Alexandra Cockroft MBChB, BSc, Graeme Duke MBBS, MD, FCICM, FANZCA
Objective
Evaluate the quality of documentation and delivery of EOLC in the Intensive Care Unit (ICU) during the COVID-19 pandemic and compare with a pre-pandemic audit.
Design
Retrospective clinical audit of medical records of patients who died in ICU during the COVID-19 pandemic, January 2021 to February 2022, using the Documentation and Evaluation of Care of Dying Equation (DECODE) survey tool.
Setting
Three metropolitan adult ICUs in Victoria, Australia.
Main outcomes
DECODE audit score, patient characteristics, demographics, end of life planning, quality of death indicators, management of dying.
Results
There were 194 deaths over a 14-month period. 2 cases were excluded. Patients wishes were documented in 83 (43%) cases. A total of 175 patients (91%) were receiving active treatment 24 h before death. A total of 166 deaths (86%) were expected and occurred a mean of 4.5 (IQR 2-9) days from admission to ICU. A total of 52 (27%) had palliative or symptom control care plans. The median DECODE score was 14 (IQR 12-15) with statistical variation across the three sites (p=0.001). Compared to pre pandemic audits, the DECODE score was higher (p=0.001) despite pandemic restrictions.
Conclusion
EOLC in ICU remains challenging due to diagnostic dilemmas, prognostic uncertainty, and short time-frames. Assessment of quality of EoLC care helps assess and possibly improve provision of care. The DECODE questionnaire provides a semi-objective measure of quality of care provided to the dying patient in ICU.
{"title":"Documentation and evaluation of care of dying patients","authors":"Maria de Freitas BM BS, BSc, BMedSci, Lucinda Roberts MBBS, Alexandra Cockroft MBChB, BSc, Graeme Duke MBBS, MD, FCICM, FANZCA","doi":"10.1016/j.ccrj.2025.100136","DOIUrl":"10.1016/j.ccrj.2025.100136","url":null,"abstract":"<div><h3>Objective</h3><div>Evaluate the quality of documentation and delivery of EOLC in the Intensive Care Unit (ICU) during the COVID-19 pandemic and compare with a pre-pandemic audit.</div></div><div><h3>Design</h3><div>Retrospective clinical audit of medical records of patients who died in ICU during the COVID-19 pandemic, January 2021 to February 2022, using the Documentation and Evaluation of Care of Dying Equation (DECODE) survey tool.</div></div><div><h3>Setting</h3><div>Three metropolitan adult ICUs in Victoria, Australia.</div></div><div><h3>Main outcomes</h3><div>DECODE audit score, patient characteristics, demographics, end of life planning, quality of death indicators, management of dying.</div></div><div><h3>Results</h3><div>There were 194 deaths over a 14-month period. 2 cases were excluded. Patients wishes were documented in 83 (43%) cases. A total of 175 patients (91%) were receiving active treatment 24 h before death. A total of 166 deaths (86%) were expected and occurred a mean of 4.5 (IQR 2-9) days from admission to ICU. A total of 52 (27%) had palliative or symptom control care plans. The median DECODE score was 14 (IQR 12-15) with statistical variation across the three sites (<em>p=0.001</em>). Compared to pre pandemic audits, the DECODE score was higher (<em>p=0.001</em>) despite pandemic restrictions.</div></div><div><h3>Conclusion</h3><div>EOLC in ICU remains challenging due to diagnostic dilemmas, prognostic uncertainty, and short time-frames. Assessment of quality of EoLC care helps assess and possibly improve provision of care. The DECODE questionnaire provides a semi-objective measure of quality of care provided to the dying patient in ICU.</div></div>","PeriodicalId":49215,"journal":{"name":"Critical Care and Resuscitation","volume":"27 4","pages":"Article 100136"},"PeriodicalIF":1.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145324280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-10-17DOI: 10.1016/j.ccrj.2025.100117
Georgia Peters BSc, MBBS (Hons), M Bioeth , Sharyn Milnes RN, GradCert CCN, GradCert Ed, GradDip AdEd, M Bioeth , Nicholas Simpson MBBS, FACEM, FCICM, PGDipEcho, GCHE , Olivia Gedye MBBS, FdnPallMed (cllinical) , Nima Kakho MBBS, FCICM , Charlie Corke MBBS, FCICM , Michael Bailey PhD, MSc, BSc (Hons) , Neil R. Orford MBBS, FCICM, FANZCA, PGDipEcho, PhD
Objective
Describe the association between the implementation of a shared decision-making (SDM) program and documentation of goals of care for critically ill patients with life-limiting illness (LLI).
Methods
A prospective longitudinal cohort study was conducted from 1st January 2015 to 30th September 2020 in an Australian tertiary teaching hospital. Adult patients with LLI admitted to the intensive care unit (ICU) were included. A SDM program consisting of communication training, a new goals of care form, and clinical support was implemented. The primary outcome was the proportion of patients with a documented SDM discussion. Secondary outcomes included patient treatment preferences and hospital utilisation parameters.
Results
A total of 1178 patients with LLI were admitted to the ICU during the study period and included in the study. Following the introduction of an SDM program, the proportion of patients with a documented SDM discussion increased from 22 % at baseline to a peak of 68 % at year five, then 60 % in year six of the study (adjusted odds ratio: 1.49, 95 % confidence interval: 1.38–1.60; p < 0.0001). Patients who had documented SDM were more likely to be older, female, frail, and have a prior advance care plan. SDM discussions resulted in higher rates of documented deterioration treatment preference plan (p < 0.0001), an increased ICU length of stay (3 vs. 2 days, p < 0.0001), referrals to palliative care services (p = 0.002), and a higher mortality rate. Time to death was significantly shorter in decedents with documented SDM compared to those without it (12 vs. 49 days, p < 0.0001).
Conclusion
The implementation of a comprehensive clinical communication training program was associated with increased documentation of shared decision-making discussions for patients in ICU with LLI, which corresponded with changes in patient treatment preferences and healthcare utilisation by decedents. Further research is required to understand the impact of these conversations from the perspective of patients and their families.
{"title":"Six years of a clinical communication intervention in shared decision-making to promote documentation of goals of care for critically ill patients with a life-limiting illness","authors":"Georgia Peters BSc, MBBS (Hons), M Bioeth , Sharyn Milnes RN, GradCert CCN, GradCert Ed, GradDip AdEd, M Bioeth , Nicholas Simpson MBBS, FACEM, FCICM, PGDipEcho, GCHE , Olivia Gedye MBBS, FdnPallMed (cllinical) , Nima Kakho MBBS, FCICM , Charlie Corke MBBS, FCICM , Michael Bailey PhD, MSc, BSc (Hons) , Neil R. Orford MBBS, FCICM, FANZCA, PGDipEcho, PhD","doi":"10.1016/j.ccrj.2025.100117","DOIUrl":"10.1016/j.ccrj.2025.100117","url":null,"abstract":"<div><h3>Objective</h3><div>Describe the association between the implementation of a shared decision-making (SDM) program and documentation of goals of care for critically ill patients with life-limiting illness (LLI).</div></div><div><h3>Methods</h3><div>A prospective longitudinal cohort study was conducted from 1st January 2015 to 30th September 2020 in an Australian tertiary teaching hospital. Adult patients with LLI admitted to the intensive care unit (ICU) were included. A SDM program consisting of communication training, a new goals of care form, and clinical support was implemented. The primary outcome was the proportion of patients with a documented SDM discussion. Secondary outcomes included patient treatment preferences and hospital utilisation parameters.</div></div><div><h3>Results</h3><div>A total of 1178 patients with LLI were admitted to the ICU during the study period and included in the study. Following the introduction of an SDM program, the proportion of patients with a documented SDM discussion increased from 22 % at baseline to a peak of 68 % at year five, then 60 % in year six of the study (adjusted odds ratio: 1.49, 95 % confidence interval: 1.38–1.60; p < 0.0001). Patients who had documented SDM were more likely to be older, female, frail, and have a prior advance care plan. SDM discussions resulted in higher rates of documented deterioration treatment preference plan (p < 0.0001), an increased ICU length of stay (3 vs. 2 days, p < 0.0001), referrals to palliative care services (p = 0.002), and a higher mortality rate. Time to death was significantly shorter in decedents with documented SDM compared to those without it (12 vs. 49 days, p < 0.0001).</div></div><div><h3>Conclusion</h3><div>The implementation of a comprehensive clinical communication training program was associated with increased documentation of shared decision-making discussions for patients in ICU with LLI, which corresponded with changes in patient treatment preferences and healthcare utilisation by decedents. Further research is required to understand the impact of these conversations from the perspective of patients and their families.</div></div>","PeriodicalId":49215,"journal":{"name":"Critical Care and Resuscitation","volume":"27 4","pages":"Article 100117"},"PeriodicalIF":1.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145324262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To determine whether type of consent model was associated with recruitment rate in critical care randomised clinical trials (RCT).
Data sources
PubMed was searched for relevant articles.
Study selection
Individual patient RCTs in critical care with a primary outcome of mortality published between 1990 and 2020 were included.
Data extraction
Two authors independently reviewed titles, abstracts, and full-text articles for eligibility, and data was entered into a structured custom database.
Data synthesis
186 RCTs were included, of which 141(75.8%) used a priori consent, while 45 (24.2%) used alternative consent models, including consent waiver and consent-to-continue. The alternate consent RCTs recruited significantly larger sample sizes (median 680 patients, IQR 300–2410) compared to the a priori group (350 patients, IQR 118–725) over similar recruitment periods (mean 3.06 years for both). The unadjusted mean weekly recruitment rate was significantly higher in the alternate consent group (mean difference +8.57 patients per week, 95% CI: 5.02–12.12). After adjustment for number of recruiting sites, diagnostic group of patients included, intervention type, investigator-initiated trial, and continent of primary trial sponsor, the alternate consent group still had a significantly higher mean weekly recruitment rate (mean difference +6.78 patients per week, 95% CI, 3.30–10.26). The proportion of RCTs that were ceased early and that reached target recruitment were similar between the two groups, as were rates of withdrawn consent.
Conclusion
Alternate consent models for critical care RCTs were associated with higher recruitment rates compared to a priori consent. A study-within-a-trial analysis may be required for definitive evaluation.
{"title":"The influence of consent models on recruitment rates in randomised trials in critical care: A systematic review","authors":"Mahesh Ramanan FCICM PhD , Aashish Kumar FCICM MBBS , Laurent Billot AStat MRes , John Myburgh FCICM PhD , Balasubramanian Venkatesh FCICM MD","doi":"10.1016/j.ccrj.2025.100119","DOIUrl":"10.1016/j.ccrj.2025.100119","url":null,"abstract":"<div><h3>Objectives</h3><div>To determine whether type of consent model was associated with recruitment rate in critical care randomised clinical trials (RCT).</div></div><div><h3>Data sources</h3><div>PubMed was searched for relevant articles.</div></div><div><h3>Study selection</h3><div>Individual patient RCTs in critical care with a primary outcome of mortality published between 1990 and 2020 were included.</div></div><div><h3>Data extraction</h3><div>Two authors independently reviewed titles, abstracts, and full-text articles for eligibility, and data was entered into a structured custom database.</div></div><div><h3>Data synthesis</h3><div>186 RCTs were included, of which 141(75.8%) used <em>a priori</em> consent, while 45 (24.2%) used alternative consent models, including consent waiver and consent-to-continue. The alternate consent RCTs recruited significantly larger sample sizes (median 680 patients, IQR 300–2410) compared to the <em>a priori</em> group (350 patients, IQR 118–725) over similar recruitment periods (mean 3.06 years for both). The unadjusted mean weekly recruitment rate was significantly higher in the alternate consent group (mean difference +8.57 patients per week, 95% CI: 5.02–12.12). After adjustment for number of recruiting sites, diagnostic group of patients included, intervention type, investigator-initiated trial, and continent of primary trial sponsor, the alternate consent group still had a significantly higher mean weekly recruitment rate (mean difference +6.78 patients per week, 95% CI, 3.30–10.26). The proportion of RCTs that were ceased early and that reached target recruitment were similar between the two groups, as were rates of withdrawn consent.</div></div><div><h3>Conclusion</h3><div>Alternate consent models for critical care RCTs were associated with higher recruitment rates compared to <em>a priori</em> consent. A study-within-a-trial analysis may be required for definitive evaluation.</div></div><div><h3>Registration</h3><div>PROSPERO Record ID: Record ID: <span><span>CRD42020215950</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":49215,"journal":{"name":"Critical Care and Resuscitation","volume":"27 4","pages":"Article 100119"},"PeriodicalIF":1.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145324182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}