The organisation of critical care for burn patients in the UK: epidemiology and comparison of mortality prediction models

This article by Toft-Petersen and colleagues was published on-line in Anaesthesia in May 2018.
In the UK, a network of specialist centres has been set up to provide critical care for burn patients. However, some burn patients are admitted to general intensive care units. Little is known about the casemix of these patients and how it compares with patients in specialist burn centres. It is not known whether burn-specific or generic risk prediction models perform better when applied to patients managed in intensive care units. We examined admissions for burns in the Case Mix Programme Database from April 2010 to March 2016. The casemix, activity and outcome in general and specialist burn intensive care units were compared and the fit of two burn-specific risk prediction models (revised Baux and Belgian Outcome in Burn Injury models) and one generic model (Intensive Care National Audit and Research Centre model) were compared. Patients in burn intensive care units had more extensive injuries compared with patients in general intensive care units (median (IQR [range]) burn surface area 16 (7-32 [0-98])% vs. 8 (1-18 [0-100])%, respectively) but in-hospital mortality was similar (22.8% vs. 19.0%, respectively). The discrimination and calibration of the generic Intensive Care National Audit and Research Centre model was superior to the revised Baux and Belgian Outcome in Burn Injury burn-specific models for patients managed on both specialist burn and general intensive care units.
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The Association of Age With Short-Term and Long-Term Mortality in Adults Admitted to the Intensive Care Unit

This article was published Journal of intensive care medicine October 2017 by Seethala et al
Background:  Based on the current literature, it is unclear whether advanced age itself leads to higher mortality in critically ill patients or whether it is due to the greater number of comorbidities in the elderly patients. We hypothesized that increasing age would increase the odds of short-term and long-term mortality after adjusting for baseline comorbidities in intensive care unit (ICU) patients.
Methods:  We performed a retrospective cohort study of 57 160 adults admitted to any ICU over 5 years at 2 academic tertiary care centers. Patients were divided into age-groups, 18 to 39, 40 to 59, 60 to 79, and ≥80. The primary outcomes were 30-day and 365-day mortality. Results were analyzed with multivariate logistic regression adjusting for demographics and the Elixhauser-van Walraven Comorbidity Index.
Results:  The adjusted 30-day mortality odds ratios (ORs) were 1.39 (95% confidence interval [CI]: 1.21-1.60), 2.00 (95% CI: 1.75-2.28), and 3.33 (95% CI: 2.90-3.82) for age-groups 40 to 59, 60 to 79, and ≥80, respectively, using the age-group 18 to 39 as the reference. The adjusted 365-day mortality ORs were 1.46 (95% CI: 1.32-1.61), 2.10 (95% CI: 1.91-2.31), and 2.96 (95% CI: 2.67-3.27).
Conclusions:  In critically ill patients, increasing age is associated with higher odds of short-term and long-term death after correcting for existing comorbidities.
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Risk Stratification in Pediatric Acute Respiratory Distress Syndrome

This study aims to describe the epidemiology of patients with PARDS across Asia and evaluate whether the Pediatric Acute Lung Injury Consensus Conference risk stratification accurately predicts outcome in PARDS | Critical Care Medicine

Objectives: The Pediatric Acute Lung Injury Consensus Conference developed a pediatric specific definition for acute respiratory distress syndrome (PARDS). In this definition, severity of lung disease is stratified into mild, moderate, and severe groups. We aim to describe the epidemiology of patients with PARDS across Asia and evaluate whether the Pediatric Acute Lung Injury Consensus Conference risk stratification accurately predicts outcome in PARDS.

 

Measurements and Main Results: Data on epidemiology, ventilation, adjunct therapies, and clinical outcomes were collected. Patients were followed for 100 days post diagnosis of PARDS. A total of 373 patients were included. There were 89 (23.9%), 149 (39.9%), and 135 (36.2%) patients with mild, moderate, and severe PARDS, respectively. The most common risk factor for PARDS was pneumonia/lower respiratory tract infection (309 [82.8%]). Higher category of severity of PARDS was associated with lower ventilator-free days (22 [17-25], 16 [0-23], 6 [0-19]; p < 0.001 for mild, moderate, and severe, respectively) and PICU free days (19 [11-24], 15 [0-22], 5 [0-20]; p < 0.001 for mild, moderate, and severe, respectively). Overall PICU mortality for PARDS was 113 of 373 (30.3%), and 100-day mortality was 126 of 317 (39.7%). After adjusting for site, presence of comorbidities and severity of illness in the multivariate Cox proportional hazard regression model, patients with moderate (hazard ratio, 1.88 [95% CI, 1.03-3.45]; p = 0.039) and severe PARDS (hazard ratio, 3.18 [95% CI, 1.68, 6.02]; p < 0.001) had higher risk of mortality compared with those with mild PARDS.

Conclusions: Mortality from PARDS is high in Asia. The Pediatric Acute Lung Injury Consensus Conference definition of PARDS is a useful tool for risk stratification.

Full reference: Wong, J, J-M. et al. (2017) Risk Stratification in Pediatric Acute Respiratory Distress Syndrome: A Multicenter Observational Study. Critical Care Medicine. Published online: July 26 2017

 

A comparison of pre ICU admission SIRS, EWS and q SOFA scores for predicting mortality and length of stay in ICU.

This research was published in the Journal of Critical Care May 2017 Volume 41 by Siddiqui et al

Introduction:  The 2015 sepsis definitions suggest using the quick SOFA score for risk stratification of sepsis patients among other changes in sepsis definition. Our aim was to validate the q sofa score for diagnosing sepsis and comparing it to traditional scores of pre ICU admission sepsis outcome prediction such as EWS and SIRS in our setting in order to predict mortality and length of stay.

Methods:  This was a retrospective cohort study. We retrospectively calculated the q sofa, SIRS and EWS scores of all ICU patients admitted with the diagnosis of sepsis at our center in 2015. This was analysed using STATA 12. Logistic regression and ROC curves were used for analysis in addition to descriptive analysis.

Results:  58 patients were included in the study. Based on our one year results we have shown that although q SOFA is more sensitive in predicting LOS in ICU of sepsis patients, the EWS score is more sensitive and specific in predicting mortality in the ICU of such patients when compared to q SOFA and SIRS scores.

Conclusion:  We find that in our setting, EWS is better than SIRS and q SOFA for predicting mortality and perhaps length of stay as well. The q Sofa score remains validated for diagnosis of sepsis.

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Characteristics and Outcome of Cancer Patients Admitted to the ICU

This study aims to describe trends in outcomes of cancer patients with an unplanned admission to the ICU between 1997 and 2013 and to identify risk factors for mortality of those admitted between 2009 and 2013 | Critical Care Medicine

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Design: Retrospective analysis.

Measurements and Main Results: In solid tumor patients admitted between 2009 and 2013, hospital mortality was 26.4%. Independent risk factors for hospital mortality were metastatic disease (odds ratio, 1.99), cardiopulmonary resuscitation before ICU admission (odds ratio, 1.63), Intensive Care National Audit & Research Centre Physiology score (odds ratio, 1.14), admission for gastrointestinal (odds ratio, 1.12), respiratory (odds ratio, 1.48) or neurological (odds ratio, 1.65) reasons, and previous ICU admission (odds ratio, 1.18). In patients with a hematological malignancy admitted between 2009 and 2013, hospital mortality was 53.6%. Independent risk factors for hospital mortality were age (odds ratio, 1.02), cardiopulmonary resuscitation before ICU admission (odds ratio, 1.90), Intensive Care National Audit & Research Centre Physiology Score (odds ratio, 1.12), admission for hematological (odds ratio, 1.48) or respiratory (odds ratio, 1.56) reasons, bone marrow transplant (odds ratio, 1.53), previous ICU admission (odds ratio, 1.43), and mechanical ventilation within 24 hours of admission (odds ratio, 1.33). Trend analysis showed a significant decrease in ICU and hospital mortality and length of stay between 1997 and 2013 despite little change in severity of illness during this time.

Conclusions: Between 1997 and 2013, the outcome of cancer patients with an unplanned admission to ICU improved significantly. Among those admitted between 2009 and 2013, independent risk factors for hospital mortality were age, severity of illness, previous cardiopulmonary resuscitation, previous ICU admission, metastatic disease, and admission for respiratory reasons.

Full reference: Ostermann, M. et al. (2107) Characteristics and Outcome of Cancer Patients Admitted to the ICU in England, Wales, and Northern Ireland and National Trends Between 1997 and 2013. Critical Care Medicine. Published online: 4th July 2017

Interventions affecting mortality in critically ill and perioperative patients

Martina, B.R. et al. Journal of Critical Care | Published online: 4 May 2017

Highlights: 

  • No systematic exploration of confounders in randomized controlled trials reporting a significant effect on mortality in critically ill patients has been performed.
  • Almost half of these trials were single centre and one third were not analysed according to the intention to treat principle, inflating effect size.
  • Blinded and/or multicentre design was associated with an increased number needed to treat/harm.
  • Major systematic biases exist and affect trial findings irrespective of the intervention being studied.

Read the full abstract here