Journal of the Intensive Care Society最新文献

Background: Identifying women at highest or lowest risk of perinatal intensive care unit (ICU) admission may enable clinicians to risk stratify women antenatally so that enhanced care or elective admission to ICU may be considered or excluded in birthing plans. We aimed to develop a statistical model to predict the risk of maternal ICU admission.

Methods: We studied 762,918 pregnancies between 2005 and 2018. Predictive models were constructed using multivariable logistic regression. The primary outcome was ICU admission. Additional analyses were performed to allow inclusion of delivery-related factors. Predictors were selected following expert consultation and reviewing literature, resulting in 13 variables being included in the primary analysis: demographics, prior health status, obstetric history and pregnancy-related factors. A complete case analysis was performed. K-fold cross validation was used to mitigate against overfitting.

Results: Complete data were available for 578,310 pregnancies, of whom 1087 were admitted to ICU (0.19%). Model performance was fair (area under the ROC curve = 0.66). A comparatively high cut-point of ⩾0.6% for ICU admission risk resulted in a negative predictive value (NPV) of 99.8% (specificity 97.8%) but positive predictive value (PPV) of 0.8% (sensitivity 9.1%). Models including delivery-related factors demonstrated superior discriminative performance.

Conclusions: Our model for maternal ICU admission has an acceptable discriminative performance. The low frequency of ICU admission and resulting low PPV indicates that the model would be unlikely to be useful as a 'rule-in' test for pre-emptive consideration of ICU admission. Its potential for improving efficiency in screening as a 'rule-out' test remains uncertain.

Introduction: Up to 20% of patients with traumatic brain injury (TBI) develop acute respiratory distress syndrome (ARDS), which is associated with increased odds of mortality. Guideline-based treatment for ARDS includes "lung protective" ventilation strategies, some of which are in opposition to "brain protective" strategies used for ventilation with patients with TBI. We conducted a scoping review of ventilation management strategies with clinical outcomes among patients with TBI and ARDS.

Methods: We searched three databases (MEDLINE, Embase, Web of Science) using a systematic search strategy. We included any studies of patients with TBI and ARDS with ventilation strategies including PEEP, oxygenation, prone positioning, recruitment maneuvers, pulmonary vasodilators (e.g., nitric oxide), high frequency oscillatory ventilation (HFOV), and extracorporeal membrane oxygenation (ECMO). All clinical outcomes were included. Extracted data included details about sample (age, gender), study design, inclusion/exclusion criteria, intervention details, and outcomes.

Results: The search returned 10,514 articles, 35 of which met final inclusion criteria. Interventions studied included ECMO (n = 13 articles), HFOV (n = 4), PEEP interventions (n = 3), prone positioning (n = 3), vasodilators (n = 4), and other lung recruitment maneuvers (n = 9). No randomized controlled trials were identified; studies were mostly case reports (n = 18/35, 51%) and series (n = 7/35, 20%), with some cohort studies (n = 5/35, 14%) and non-randomized experimental trials (n = 5/35, 14%), all at single institutions. Outcomes included physiologic changes (e.g., change in cerebrodynamics or hemodynamics with intervention) and clinical outcomes such as mortality, complications, or neurologic recovery. Five studies (14%) included pediatric patients.

Discussion: In this scoping review of ventilatory strategies for patients with concurrent TBI and ARDS, we found variation in heterogeneity of study design, interventions, and outcomes. Studies were mostly case report/series and observational studies, seriously limiting our ability to draw conclusions about effectiveness of interventions. Targeted areas of further research are discussed.

Background: The psychological impact of surviving an admission to an intensive care unit (ICU) with COVID-19 is uncertain. The objective of the study was to assess the prevalence of anxiety, depression and post-traumatic stress disorder (PTSD) symptoms in ICU survivors treated for COVID-19 infection, and identify risk factors for psychological distress.

Methods: This observational study was conducted at 52 ICUs in the United Kingdom. Participants, treated for COVID-19 infection during an ICU admission of ⩾24 h, were recruited post-ICU discharge. Self-report questionnaires were completed at 3, 6 and/or 12 months. Symptoms of anxiety and depression were identified using the Hospital Anxiety and Depression Scale. PTSD was assessed using the Impact of Events Scale-6. Demographic, clinical, physical and psychosocial factors were considered as putative predictors of psychological distress.

Results: 1620 patients provided consent and 1258 (77.7%) responded to at least one questionnaire, with responses at 3 months (N = 426), 6 months (N = 656) and 12 months (N = 1050) following ICU admission. The following prevalence rates were found at 3, 6 and 12 months, respectively: anxiety in 28.8% (95% CI 24.6-33.1), 30.4% (95% CI 27.0-33.8) and 29.3% (95% CI 26.5-32.1); depression in 25.1% (21.0-29.3), 25.9% (22.7-29.3) and 24.0% (21.5-26.6); and PTSD in 43.5% (38.8-48.2), 44.3% (40.6-48.0) and 43.2% (40.2-46.1) of patients. Risk factors for psychological distress included a previous mental health diagnosis, unemployment or being on sick leave, and a history of asthma or COPD.

Conclusion: Clinically significant symptoms of anxiety, depression and PTSD were common and persisted up to 12 months post-ICU discharge.

Background: Dying and death in critical care settings can have particularly negative implications for the bereavement experience of family members, family interaction and the wellbeing of critical care staff. This study explored critical care staff perspectives of dying, death and bereavement in this context, and their role related to patients and their families, adopting a multidisciplinary perspective.

Method: This study employed a descriptive exploratory qualitative design, using reflexive thematic analysis to interpret the data. Semi-structured interviews were conducted with 15 critical care staff from hospitals in the Republic of Ireland. Most participants were female (n = 11), with four male participants. Professional disciplines included nursing, dietetics, physiotherapy, anaesthesiology and medicine.

Results: Key findings included supporting a 'nice death' for patients and their families, the challenges critical care staff experience, the need for better supports in critical care, and the need for change in current bereavement support provision given the diversity evident in the modern Irish population.

Conclusion: This study suggests that the unique challenges faced by staff and families throughout the dying process may benefit from the development of additional psychological, educational, and infrastructural supports. Inconsistencies in supports across critical care units in Ireland were also identified. Future research should complement the current study and examine family members' experience of the dying process in critical care and their perspectives on supports provided.

Background: Understanding the degree to which patients are actively involved, confident and capable of engaging with self-management and rehabilitation could be an initial step in guiding individualised supportive strategies for people after critical illness.

Aims: To assess the levels of active involvement with self management among ICU survivors using the Patient Activation Measure (PAM), explore associations between patient characteristics and PAM results, and investigate its relationship with patients' support needs at key transition points during the recovery process.

Methods: Eligible participants received both the PAM and Support Needs After Critical care (SNAC) questionnaires by post. The return of the completed questionnaires was considered as consent to participate. Ethical approval was obtained (17/NI/0236). Descriptive statistics were used to summarise the data and Pearson's coefficient for correlations between variables.

Findings: There were 200 completed PAM and SNAC questionnaires. PAM scores showed that levels of active involvement with self management fell into level 1 (n = 64; disengaged and overwhelmed, low confidence to self manage) and 2 (n = 70; still struggling), with considerably less participants achieving scores in level 3 (n = 51; taking action) and 4 (n = 15; pushing further). Lower patient activation levels were associated with higher support needs (r = -0.16, p = 0.02).

Conclusion: We found that patient activation levels are low implying low knowledge, skills and confidence to self-manage after critical illness, and also that patients have support needs at various timepoints during recovery. Future research should focus on a longitudinal study to track changes in activation and support needs in the same patients over time and identify effective strategies to optimise recovery after critical illness.

Background: Survivors of intensive care unit (ICU) admission experience significant deficits in health-related quality of life due to long-term physical, psychological, and cognitive sequelae of critical illness, which may persist for many years. There has been a proliferation of post-hospital interventions in recent years which aim to support ICU-survivors, however there is currently limited evidence to inform optimal approach. We therefore aimed to synthesise factors which impacted the implementation of these interventions from the perspective of healthcare providers, patients, and their carers, and to compare different intervention designs.

Methods: We conducted a systematic review and synthesis of qualitative evidence using four databases (MEDLINE, EMBASE, CINAHL and Web of Science) which were searched from inception to May 2024. The extraction and synthesis of factors which impacted intervention implementation was informed by the domains of the Consolidated Framework for Implementation Research (CFIR) and Template for Intervention Description and Replication (TIDieR) checklist.

Results: Thirty-seven studies were included, reporting on a range of interventions including follow-up clinics and rehabilitation programmes. We identified some overarching principles and specific intervention component and design factors which may support in the design of future strategies to improve outcomes for ICU survivors. For each intervention characteristic, various patient, staff, and setting factors were found to impact implementation. Considering how the intervention will rely on and integrate with existing outpatient and community resources is likely to be important.

Conclusion: This review provides a framework to future research examining the optimal approach to supporting ICU survivor recovery following hospital discharge.

Background: Acute kidney injury (AKI) within the intensive care unit (ICU) is common but evidence is limited on longer-term renal outcomes. We aimed to model the trend of kidney function in ICU survivors using estimated glomerular filtration rate (eGFR), comparing those with and without AKI, and investigate potential risk factors associated with eGFR decline.

Methods: This observational cohort study included all patients aged 16 or older admitted to two general adult ICUs in Scotland between 1st July 2015 and 30th June 2018 who survived to 30 days following hospital discharge. Baseline serum creatinine and subsequent values were used to identify patients with AKI and calculate eGFR following hospital discharge. Mixed effects modelling was used to control for repeated measures and to allow inclusion of several exploratory variables.

Results: 3649 patients were included, with 1252 (34%) experiencing in-ICU AKI. Patients were followed up for up to 2000 days with a median 21 eGFR measurements. eGFR declined at a rate of -1.9 ml/min/1.73m²/year (p-value < 0.001) in the overall ICU survivor cohort. Patients with AKI experienced an accelerated rate of post-ICU eGFR decline of -2.0 ml/min/1.73m²/year compared to a rate of -1.83 ml/min/1.73m²/year in patients who did not experience AKI (p-value 0.007). Pre-existing diabetes or liver disease and in-ICU vasopressor support were associated with accelerated eGFR decline regardless of AKI experience.

Conclusions: ICU survivors experienced a decline in kidney function beyond that which would be expected regardless of in-ICU AKI. Long-term follow-up is warranted in ICU survivors to monitor kidney function and reduce morbidity and mortality.

Background: The COVID-19 pandemic challenged both research and clinical teams in critical care to collaborate on research solutions to new clinical problems. Although an effective, nationally coordinated response helped facilitate critical care research, reprioritisation of research efforts towards COVID-19 studies had significant consequences for existing and planned research activity in critical care.

Aims: Our aim was to explore the impact of the COVID-19 pandemic research prioritisation policies and practices on critical care research funded prior to the pandemic, the conduct of pandemic research, and implications for ongoing and future critical care research.

Methods: We undertook a descriptive qualitative study recruiting research-active clinician researchers and research delivery team members working in critical care. We conducted digitally recorded, semi-structured interviews in 2021-2022. Framework Analysis was used to analyse the data.

Results: We interviewed 22 participants comprising principal investigators, senior trial coordinators and research delivery nurses from across the UK. Six themes were identified: Unit, organisational and national factors; Study specific factors; Resources; Individual/clinician factors; Family/patient factors; Contextual factors. These themes explained how a nationally coordinated response during the pandemic affected individuals, studies and wider organisations in managing the research response in critical care, highlighting future implications for critical care research.

Conclusion: Harnessing the collective response seen in the COVID-19 pandemic in critical care could better support integration of research activity into routine critical care activities. Future endeavours should focus on workforce preparations, contingency planning, strategies for study prioritisation and integration of research as part of the continuum of clinical care.

Background: Animal-assisted interventions (AAI) can provide psychological support to critical care patients during their intensive care unit (ICU) admission. However, there are currently no data on AAI services across UK ICUs. The current study therefore aims to (i) determine how many ICUs in the UK offer services, (ii) characterise available services and (iii) explore and review local documentation for service oversight.

Methods: A service evaluation comprising two parts; a national survey of UK ICU's, analysed using descriptive statistics, and review of local service oversight documents, analysed using a framework approach.

Results: Responses from 74 sites (/242, 30.6%) were included in survey analysis. AAI services were present at 32 sites (/74, 43.2%), of which 30 offered animal-assisted activity services alone and 2 offered both animal-assisted activity and animal-assisted therapy services. Animal-assisted activity services were typically delivered on a weekly basis, lasting 30-60 min and with dogs the sole animal employed. Concern over infection prevention and control was the most common barrier to service provision, as well as a lack of supporting evidence. Sixteen sites provided 27 oversight documents for analysis, that highlighted unique and shared responsibilities between critical care staff and animal therapy handlers, including aspects of administration, welfare and infection control.

Conclusion: From a small sample, AAI services were available in less than half of ICUs. Empirical value of interventions is countered by current lack of definitive evidence of effectiveness, which should be addressed before wider implementation of AAI services and the associated resource requirements, is undertaken.

Background: Advanced age is an independent risk factor for poor outcomes following aneurysmal subarachnoid haemorrhage (SAH). However, Australian data are lacking. Our aim was to evaluate outcomes for older patients admitted to an Australian intensive care unit for management of aneurysmal SAH.

Methods: We conducted a single centre retrospective observational study looking at adult patients admitted with aneurysmal SAH to an Intensive Care Unit (ICU) over a 10-year period. Patients were grouped by age; <70 years, 70-79 years, ⩾80 years, and were of sufficient complexity to be unsuitable for our neurosurgical high-dependency unit. The primary outcome was in-hospital mortality. Secondary outcomes were ICU and hospital length of stay, and discharge destination.

Results: Of 372 patients admitted to ICU with aneurysmal SAH, 302 (82%) were younger (<70 years), 46 (12%) were septuagenarians and 24 (6%) were octogenarians. There were no differences between clinical or radiological grade of aneurysmal SAH between age cohorts. When compared to the patients younger than 70 years, there was increased odds of dying for those 70-79 and ⩾80 years (70-79: OR 1.98, 95% CI 0.93, 4.20 p = 0.077; ⩾80: OR 4.01, 95% CI 1.55, 10.35 p = 0.004). There were no associations between age and duration of admission. Only 6% of patients aged ⩾70 years were discharged home alive.

Conclusion: It was uncommon for patients over 70 years of age who present with a SAH to be discharged home from hospital, and those aged ⩾80 are four times more likely to die in hospital than younger patients.