Critical Care and Resuscitation最新文献

IF 1.7 4区医学 Q3 CRITICAL CARE MEDICINE

Critical Care and Resuscitation

Pub Date : 2026-01-01

引用次数: 0

IF 1.7 4区医学 Q3 CRITICAL CARE MEDICINE

Critical Care and Resuscitation

Pub Date : 2026-01-01

引用次数: 0

IF 1.7 4区医学 Q3 CRITICAL CARE MEDICINE

Critical Care and Resuscitation

Pub Date : 2026-01-01

引用次数: 0

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 实验室自动分析仪与现场血气机测量钠浓度的比较：一项针对大型成人重症监护病房人群的回顾性、多中心分析研究

IF 1.7 4区医学 Q3 CRITICAL CARE MEDICINE

Critical Care and Resuscitation

Pub Date : 2025-12-01 DOI: 10.1016/j.ccrj.2025.100149

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

Objective

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.

目的实验室钠值与现场动脉血气钠值的差异可能导致对结果的延迟解释和干预。我们研究了这两种技术之间的平均差异，并评估了一致程度。设计进行一项多中心、回顾性、观察性研究。研究对象为澳大利亚昆士兰州的12个重症监护病房，其中三级医院占入院人数的81%。在重症监护病房入院期间，至少有一次配对实验室钠和动脉血气测量的成年患者是本研究的一部分。主要结果测量包括实验室钠和护理点钠测量的平均差异，阳性差异表明实验室钠值高于动脉血气钠值。结果共纳入65,042例患者和224,383例配对样本。实验室钠和动脉血气钠的Bland-Altman平均差值为0.72 mmol/L(95%一致限[LoA]: 4.35)， Deming回归斜率为0.93(95%可信区间：0.92,0.94)，截断量为+10.07 （p < 0.001）。对低钠血症、低钠血症和高钠血症进行亚组分析，分别计算出1.53 mmol/L（4.21）、0.15 mmol/L（4.39）和- 1.02 mmol/L（5.37）的平均LoA差异（95% LoA）。严重高血糖患者与白蛋白正常患者的平均差异（95% LoA）为- 1.85 mmol/L（4.78）。对低钠血症和高钠血症样本中轻度、中度和重度亚组的分析显示，平均差异越来越大，重度低钠血症的平均差异为2.01 mmol/L (95% LoA: 8.08)，重度高钠血症的平均差异为- 4.7 mmol/L （95% LoA: 15.46）。结论监护点动脉血气钠测量结果显示成人重症监护病房患者血钠含量差异较小，且与配对实验室样本吻合较好。在中度至重度钠血症患者的实验室和护理点钠值互换结果时应谨慎，因为在治疗期间使用不同方法的连续测量不太可能在临床可接受的范围内。这在治疗患有严重低钠血症和诱发性高钠血症的患者群体时很重要，并且由于易于获取、可重复性和成本较低，通过即时检测可以更好地实现系列测量。

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引用次数: 0

Statistical analysis plan for the Australasian Resuscitation in sepsis evaluation: FLUid or vasopressors in emergency department sepsis (ARISE FLUIDS) trial 澳大利亚复苏在败血症评估中的统计分析计划：急诊科败血症中的液体或血管加压剂（ARISE FLUid）试验

IF 1.7 4区医学 Q3 CRITICAL CARE MEDICINE

Critical Care and Resuscitation

Pub Date : 2025-12-01 DOI: 10.1016/j.ccrj.2025.100157

Elissa M. Milford BSc, MBBS, PhD, FCICM , Stephen P.J. Macdonald BSc (Hons), MBChB, PhD, DCH, FRCP (Edin), FACEM , Ary Serpa-Neto MD, MSc, PhD, FCICM , Anthony Delaney FCICM, FACEM, PhD , Alisa M. Higgins PhD, MPH, BPhysio (Hons) , Belinda Howe RN, BAppSc (Nursing), CCCert, MPH , Sandra L. Peake FCICM, PhD , ARISE FLUIDS Investigators

Background

The optimal approach to haemodynamic resuscitation in patients with septic shock is uncertain and will be evaluated in The Australasian Resuscitation In Sepsis Evaluation: FLUid or vasopressors In emergency Department Sepsis (ARISE FLUIDS) trial.

Objective

The objective of this study was to describe the prespecified ARISE FLUIDS statistical analysis plan (SAP).

Design, setting, participants, and interventions

The ARISE FLUIDS trial is a 1000-participant international multicentre randomised controlled trial comparing restricted intravenous fluid volume and earlier introduction of vasopressors (vasopressor strategy) to larger initial intravenous fluid volume and later introduction of vasopressors if required (fluids strategy) in adults with early septic shock presenting to the emergency department in participating sites in Australia, New Zealand and Ireland.

Main outcome measures

The primary outcome is days alive and out of hospital at 90 days post randomisation, and the difference in medians between the two treatment groups will be estimated using a linear quantile mixed-effect regression model. Secondary outcomes include duration of survival censored at day 90, ventilator-, vasopressor-, and acute renal replacement–free days censored at day 28 and death or disability at 6 and 12 months

Conclusion

ARISE FLUIDS will compare the effects of a vasopressor vs. fluids strategy on days alive and out of hospital at 90 days in adults with early septic shock. The prespecified SAP is reported here to mitigate analysis bias.

背景：脓毒性休克患者血流动力学复苏的最佳方法尚不确定，将在澳大利亚败血症复苏评估：急诊科败血症（ARISE FLUid）试验中进行评估。目的描述预先设定的ARISE流体统计分析计划（SAP）。设计、环境、参与者和干预措施ARISE流体试验是一项有1000名参与者的国际多中心随机对照试验，比较澳大利亚各试验点急诊就诊的早期感染性休克成人的静脉输液量受限并早期引入血管加压剂（血管加压剂策略）与初始静脉输液量较大并在需要时再引入血管加压剂（液体策略）的情况。新西兰和爱尔兰。主要结局指标：主要结局指标为随机化后90天的存活天数和出院天数，使用线性分位数混合效应回归模型估计两个治疗组之间的中位数差异。次要结局包括第90天的生存时间，第28天无呼吸机、无血管加压剂和无急性肾代用品的天数，以及第6个月和第12个月的死亡或残疾。结论：arise流体将比较血管加压剂与液体策略对早期感染性休克成人存活天数和出院天数的影响。这里报告预先指定的SAP是为了减轻分析偏差。

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引用次数: 0

Redefining success: Incorporating long-term survival outcomes into routine benchmarking 重新定义成功：将长期生存结果纳入常规基准

IF 1.7 4区医学 Q3 CRITICAL CARE MEDICINE

Critical Care and Resuscitation

Pub Date : 2025-10-22 DOI: 10.1016/j.ccrj.2025.100138

Paul Secombe FCICM PhD, Edward Litton FCICM PhD, Shaila Chavan MSPH, Jennifer Hogan RN, Sue Huckson BAppSci RN, Tamishta Hensman FCICM MBBS, Chong Tien Goh FCICM MBBS, Craig Carr PH.D, Jason McClure FCICM MBBS, David Pilcher FCICM MBBS

引用次数: 0

Assessment of outcomes in postaneurysmal subarachnoid bleed patients admitted to the intensive care unit utilizing the subarachnoid haemorrhage international trialist clinicoradiological prediction model for dichotomised functional outcome and mortality 应用蛛网膜下腔出血国际临床放射学预测模型评估重症监护病房收治的动脉瘤术后蛛网膜下腔出血患者的预后和死亡率

IF 1.7 4区医学 Q3 CRITICAL CARE MEDICINE

Critical Care and Resuscitation

Pub Date : 2025-10-22 DOI: 10.1016/j.ccrj.2025.100126

David Mogg MBBS, BSc, MMed , James Walsham MBChB, FCICM

Objective

The objective of this study was to assess the Subarachnoid Haemorrhage International Trialist (SAHIT) prediction model in a tertiary adult intensive care unit (ICU) cohort when assessing patient outcomes against predicted outcomes, firstly by assessing the discrimination and validation of the model in the Princess Alexandra Hospital (PA) intensive care cohort and secondly comparing the predicted outcomes using the SAHIT model to the actual cohort outcomes using a Monte Carlo simulation.

Methods

Six logistic regression models designed by the SAHIT Collaboration Group were applied to the PA cohort considering early predictive factors such as clinical grade and treatment modality to predict the risk of both mortality and unfavourable outcome at 6 months according to the Glasgow Outcome Score. The six SAHIT logistic regression models were applied to a retrospectively collected cohort of aneurysmal subarachnoid patients who were admitted to the ICU, generating individual risk scores for mortality and poor functional outcome. Area under the curve (AUC) and calibration slope/intercept and Brier score were used to assess the strength of the model in interpreting the current data set. A Monte Carlo analysis was used to compare the actual mortality outcomes to the predicted outcomes to determine if the cohort performance was better or worse than predicted by the mortality model.

Results

Overall, the PA cohort actual mortality was higher than the predicted mortality rate based on the risk scores generated by the SAHIT models, demonstrated by Monte Carlo simulation using the SAHIT model risk scores. The core, neuroimaging, and full models for functional outcome produced AUCs of 0.719 (95% confidence interval [CI]: 0.55–0.84), 0.709 (95% CI: 0.55–0.83), and 0.738 (95% CI: 0.58–0.85). Regarding mortality, the respective AUCs were 0.684 (95% CI: 0.57–0.78), 0.678 (95% CI: 0.56–0.77), and 0.749 (95% CI: 0.64–0.84). Regarding calibration, there was modest calibration in general, with higher degrees of calibration in the fully functional outcome model.

Conclusion

The cohort outcomes for mortality occurred at a rate higher than the risk predictions suggested using the logistic regression created by the SAHITs. Applying the externally trained model provided adequate discrimination and modest calibration, yet underestimated risk when applied to the intensive care cohort, reflected in the probability density function analysis. Using the SAHIT models in this cohort may result in underestimation of mortality for the individual patient, and the accuracy of the model is not sufficient for individual patient prediction. These results challenge the appropriateness of using admission-based models for dynamic ICU populations and highlight the urgent need for critical care–specific prognostic tools.

本研究的目的是评估三级成人重症监护病房（ICU）队列中蛛网膜下腔出血国际试验（SAHIT）预测模型在评估患者预后与预测结果时的效果，首先评估该模型在亚历山德拉公主医院（PA）重症监护队列中的识别性和有效性，然后使用蒙特卡洛模拟将SAHIT模型的预测结果与实际队列结果进行比较。方法采用SAHIT协作组设计的6个logistic回归模型，考虑临床分级和治疗方式等早期预测因素，根据格拉斯哥预后评分（Glasgow outcome Score）预测6个月时的死亡风险和不良结局。将6个SAHIT logistic回归模型应用于回顾性收集的ICU收治的动脉瘤性蛛网膜下腔患者队列，生成死亡率和功能不良结局的个体风险评分。使用曲线下面积（AUC）、校准斜率/截距和Brier评分来评估模型在解释当前数据集方面的强度。使用蒙特卡罗分析比较实际死亡率结果与预测结果，以确定队列表现是否比死亡率模型预测的更好或更差。结果总体而言，PA队列的实际死亡率高于基于SAHIT模型风险评分的预测死亡率，使用SAHIT模型风险评分进行蒙特卡洛模拟。核心模型、神经影像学模型和功能预后的完整模型的auc分别为0.719（95%可信区间[CI]: 0.55-0.84）、0.709 （95% CI: 0.55-0.83）和0.738 （95% CI: 0.58-0.85）。关于死亡率，auc分别为0.684 （95% CI: 0.57-0.78）、0.678 （95% CI: 0.56-0.77）和0.749 （95% CI: 0.64-0.84）。关于校准，一般来说有适度的校准，在功能齐全的结果模型中有更高的校准程度。结论：队列结果的死亡率高于使用sahit创建的逻辑回归所提示的风险预测。应用外部训练的模型提供了充分的辨别和适度的校准，但在应用于重症监护队列时低估了风险，这反映在概率密度函数分析中。在该队列中使用SAHIT模型可能会导致对单个患者死亡率的低估，并且该模型的准确性不足以用于单个患者的预测。这些结果挑战了在动态ICU人群中使用基于入院的模型的适宜性，并强调了对重症护理特异性预后工具的迫切需要。

{"title":"Assessment of outcomes in postaneurysmal subarachnoid bleed patients admitted to the intensive care unit utilizing the subarachnoid haemorrhage international trialist clinicoradiological prediction model for dichotomised functional outcome and mortality","authors":"David Mogg MBBS, BSc, MMed , James Walsham MBChB, FCICM","doi":"10.1016/j.ccrj.2025.100126","DOIUrl":"10.1016/j.ccrj.2025.100126","url":null,"abstract":"<div><h3>Objective</h3><div>The objective of this study was to assess the Subarachnoid Haemorrhage International Trialist (SAHIT) prediction model in a tertiary adult intensive care unit (ICU) cohort when assessing patient outcomes against predicted outcomes, firstly by assessing the discrimination and validation of the model in the Princess Alexandra Hospital (PA) intensive care cohort and secondly comparing the predicted outcomes using the SAHIT model to the actual cohort outcomes using a Monte Carlo simulation.</div></div><div><h3>Methods</h3><div>Six logistic regression models designed by the SAHIT Collaboration Group were applied to the PA cohort considering early predictive factors such as clinical grade and treatment modality to predict the risk of both mortality and unfavourable outcome at 6 months according to the Glasgow Outcome Score. The six SAHIT logistic regression models were applied to a retrospectively collected cohort of aneurysmal subarachnoid patients who were admitted to the ICU, generating individual risk scores for mortality and poor functional outcome. Area under the curve (AUC) and calibration slope/intercept and Brier score were used to assess the strength of the model in interpreting the current data set. A Monte Carlo analysis was used to compare the actual mortality outcomes to the predicted outcomes to determine if the cohort performance was better or worse than predicted by the mortality model.</div></div><div><h3>Results</h3><div>Overall, the PA cohort actual mortality was higher than the predicted mortality rate based on the risk scores generated by the SAHIT models, demonstrated by Monte Carlo simulation using the SAHIT model risk scores. The core, neuroimaging, and full models for functional outcome produced AUCs of 0.719 (95% confidence interval [CI]: 0.55–0.84), 0.709 (95% CI: 0.55–0.83), and 0.738 (95% CI: 0.58–0.85). Regarding mortality, the respective AUCs were 0.684 (95% CI: 0.57–0.78), 0.678 (95% CI: 0.56–0.77), and 0.749 (95% CI: 0.64–0.84). Regarding calibration, there was modest calibration in general, with higher degrees of calibration in the fully functional outcome model.</div></div><div><h3>Conclusion</h3><div>The cohort outcomes for mortality occurred at a rate higher than the risk predictions suggested using the logistic regression created by the SAHITs. Applying the externally trained model provided adequate discrimination and modest calibration, yet underestimated risk when applied to the intensive care cohort, reflected in the probability density function analysis. Using the SAHIT models in this cohort may result in underestimation of mortality for the individual patient, and the accuracy of the model is not sufficient for individual patient prediction. These results challenge the appropriateness of using admission-based models for dynamic ICU populations and highlight the urgent need for critical care–specific prognostic tools.</div></div>","PeriodicalId":49215,"journal":{"name":"Critical Care and Resuscitation","volume":"27 4","pages":"Article 100126"},"PeriodicalIF":1.7,"publicationDate":"2025-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145365870","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}

引用次数: 0

Temperature profiles in adult intensive care unit patients treated for infection in a tertiary intensive care unit: A single-centre prospective observational cohort study 在三级重症监护病房接受感染治疗的成人重症监护病房患者的体温分布：一项单中心前瞻性观察队列研究

IF 1.7 4区医学 Q3 CRITICAL CARE MEDICINE

Critical Care and Resuscitation

Pub Date : 2025-10-22 DOI: 10.1016/j.ccrj.2025.100121

Bianca B. Crichton BHealSc , Allie Eathorne MAppStat , Julieann Coombes PhD , Chloe Edwards RN, MPH , Patricia M. Falleni RN, MA , Kevin B. Laupland MD, PhD , Diane M. Mackle RN, PhD , Manoj Saxena MBBCh, PhD , Jackson Smeed-Tauroa BHlth , Kyle C. White MBBS, MPH , Paul J. Young MBChB, PhD , Therapeutic Warming Investigator Group

Objective

The objective of this study was to evaluate temperature profiles in patients treated for infections in the intensive care unit (ICU) to establish the number of patients who might be eligible for a clinical trial of therapeutic warming.

Design, setting, and participants

A prospective observational study was conducted in a Wellington ICU over a 3-month period in 2024 including consecutive adult unplanned admissions and excluding those with brain injury or seizures.

Main outcome measures

We screened 200 eligible patients. Our primary outcome was the proportion of all unplanned ICU admission episodes where patients were treated for infection within 14 days in the ICU. Patients treated for an infection were divided into four groups (≥38.3 °C, ≥37.5–38.2 °C, 36–37.4 °C, and <36 °C) using their most recent temperature prior to the first antimicrobial in the ICU (or at admission for patients already on antimicrobials). A key physiological/process measure was the fever deficit, defined as the number of degree-hours <38.3 °C within 24, 48, and 72 h.

Results

A total of 43.3% of unplanned ICU admissions resulted in treatment of infection within 14 days. A total of nine of 123 patients had a body temperature ≥38.3 °C (7.3%) when first treated for infection in the ICU, while 94 of 123 patients (76.4%) had a body temperature <37.5 °C. Fever deficits over 24-, 48-, and 72-h periods increased by decreasing body temperature group with a high proportion of hours spent with a body temperature <38.3 °C in all groups.

Conclusion

A large number of patients treated for infection in the ICU may be able to be included in a trial evaluating induced hyperthermia.

目的本研究的目的是评估重症监护病房（ICU）感染患者的体温分布，以确定有资格进行治疗性升温临床试验的患者数量。设计、环境和参与者：一项前瞻性观察性研究于2024年在惠灵顿ICU进行，为期3个月，包括连续的成人意外入院，排除脑损伤或癫痫发作患者。我们筛选了200名符合条件的患者。我们的主要结局是所有非计划的ICU入院事件的比例，其中患者在ICU 14天内接受了感染治疗。根据患者在ICU首次使用抗菌药物前（或已使用抗菌药物的患者入院时）的最新体温，将接受感染治疗的患者分为四组（≥38.3°C、≥37.5-38.2°C、36 - 37.4°C和36°C）。一个关键的生理/过程测量是发热不足，定义为24、48和72 h内38.3°C的度小时数。结果共有43.3%的非计划ICU入院患者在14天内导致感染治疗。123例患者首次在ICU接受感染治疗时体温≥38.3°C的有9例（7.3%），体温≥37.5°C的有94例（76.4%）。在24、48和72小时内，体温降低组的发热不足增加，所有组体温保持在38.3°C的时间比例都很高。结论大量在ICU接受感染治疗的患者可以纳入诱导热疗的评估试验。

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引用次数: 0

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 六年的临床沟通干预，共同决策，以促进文件化的护理目标，危重患者的生命限制疾病

IF 1.7 4区医学 Q3 CRITICAL CARE MEDICINE

Critical Care and Resuscitation

Pub Date : 2025-10-17 DOI: 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.

目的探讨共享决策（SDM）方案的实施与危重症限制性疾病（LLI）患者护理目标的记录之间的关系。方法于2015年1月1日至2020年9月30日在澳大利亚某三级教学医院进行前瞻性纵向队列研究。纳入重症监护病房（ICU）的成年LLI患者。实施了由沟通培训、新的护理形式目标和临床支持组成的SDM计划。主要结局是有记录的SDM讨论的患者比例。次要结局包括患者治疗偏好和医院利用参数。结果共1178例LLI患者在研究期间入住ICU并纳入研究。引入SDM计划后，记录SDM讨论的患者比例从基线时的22%增加到第五年的68%，然后在研究的第六年增加到60%（调整后的优势比：1.49,95%置信区间：1.38-1.60;p < 0.0001）。有记录的SDM患者更可能是老年人，女性，体弱，并且有事先的护理计划。SDM讨论导致记录的恶化率更高（p < 0.0001）， ICU住院时间增加（3天vs. 2天，p < 0.0001），转介到姑息治疗服务（p = 0.002），死亡率更高。记录在案的SDM患者的死亡时间明显短于无SDM患者（12天vs 49天，p < 0.0001）。结论全面的临床沟通培训计划的实施与ICU中LLI患者共同决策讨论的记录增加有关，这与患者治疗偏好和死者医疗保健利用的变化相对应。需要进一步的研究来从患者及其家属的角度理解这些对话的影响。

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引用次数: 0

Building the future of ICU care: Is our digital foundation strong enough? A multicentre survey of Australian and New Zealand intensive care units 构建ICU护理的未来：我们的数字基础是否足够强大？澳大利亚和新西兰重症监护病房的多中心调查

IF 1.7 4区医学 Q3 CRITICAL CARE MEDICINE

Critical Care and Resuscitation

Pub Date : 2025-10-17 DOI: 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.

本研究的目的是评估澳大利亚和新西兰（ANZ）重症监护病房（icu）的数据相关资源、基础设施和能力。设计进行电子多中心调查。在2024年6月至10月之间设置anz ICUs。本研究纳入了澳大利亚和新西兰重症监护协会成人患者数据库和/或澳大利亚和新西兰儿科重症监护登记处的所有ANZ icu。干预措施：没有需要申报的。主要结果测量指标主要结果测量指标包括医疗记录类型、数字数据捕获和研究可用性、数字增强计划、人员配备和研究协作。结果209例icu中，112例（54%）有应答；13个儿科icu， 21个混合icu和78个成人icu，来自所有澳新银行辖区的回复。总体而言，59%的人使用纸质记录（5名儿科和61名混合/成人），28%的人使用数字化记录（7名儿科和24名混合/成人），59%的人使用电子健康记录（EHRs； 10名儿科和56名混合/成人），大多数电子健康记录是在过去十年引入的（76%）。在有电子病历的单位中，59%的人在电子病历中第一时间或每分钟收集数据，75%的人收集电子病历中关于患者人口统计、临床记录、实验室结果、药物、液体、床边监护仪和呼吸支持设备的数据。45%的icu聘用了数据管理人员，其中96%的icu能够提取数据用于审计，92%的icu能够提取数据用于研究。受访者表示对电子病历延迟实施和有限的数据提取机制感到失望。结论ANZ icu在数字健康采用、数据采集和数据管理资源方面存在显著差异。量化数字信息差异、改进数据提取和建立协作网络是支持跨单位研究和创新的关键步骤。

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