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Despite recent advances in the field, the association between subsyndromal delirium (SSD) in the ICU and poor outcomes is not entirely clear. We performed a retrospective multicentric observational study analyzing mental status during the first 72 h of ICU stay. Of the 681 patients included, SSD occurred in 22.7%. Considering the worst cognitive assessment during the first 72 h, 233 (34%) patients had normal mental status, 124 (18%) patients had SSD and 324 (48%) patients had delirium or coma. SSD was not independently associated with an increased risk of death when compared with normal mental status (OR 95%IC 1.0 vs. 1.35 [0.73–1.49], p = 0.340), but was associated with a longer ICU LOS (7.0 (4–12) vs. 4 (3–8) days, p < 0.001). SSD patients who deteriorated to delirium or coma (21%) had a longer ICU LOS in comparison with those who improved or maintained mental status (8 (5–11) vs. 6 (4–8) days, p = 0.025), but did not have an increase in mortality. The main factors associated with the progression from SSD to delirium or coma were the use of mechanical ventilation, the use of intravenous benzodiazepines and a baseline APACHE II score > 23 points. Our findings support the association of SSD with increased ICU LOS, but not with ICU mortality. Monitoring the trajectory of SSD early at ICU admission can help to identify patients with increased risk of conversion from SSD to delirium or coma.

Rationale: Acute respiratory failure (ARF) is associated with high mortality in immunocompromised patients, particularly when invasive mechanical ventilation is needed. Therefore, noninvasive oxygenation/ventilation strategies have been developed to avoid intubation, with uncertain impact on mortality, especially when intubation is delayed. Objectives: We sought to report trends of survival over time in immunocompromised patients receiving invasive mechanical ventilation. The impact of delayed intubation after failure of noninvasive strategies was also assessed. Methods: Systematic review and meta-analysis using individual data (IPD) of studies which focused on immunocompromised adult patients with ARF requiring invasive mechanical ventilation. Studies published in English were identified through PubMed, Web of science, and Cochrane Central (2008-2018). IPD were requested to corresponding authors for all identified studies. We used mixed-effect models to estimate the effect of delayed intubation on hospital mortality and described mortality rates over time. Measurements and main results: 11087 patients were included (24 studies, 3 controlled trials and 21 cohorts), of whom 7736 (74%) were intubated within 24h of ICU admission (early intubation). Crude mortality rate was 53.2%. Adjusted survivals improved over time (from 1995 to 2017, OR for hospital mortality per year: 0.96[0.95-0.97]). For each elapsed day between ICU admission and intubation, mortality was higher (OR:1.38[1.26-1.52], p

Purpose Clinical characteristics and management of COVID-19 patients have evolved during the pandemic, potentially changing their outcomes. We analyzed the associations of changes in mortality rates with clinical profiles and respiratory support strategies in COVID-19 critically ill patients. Methods A multicenter cohort of RT-PCR-confirmed COVID-19 patients admitted at 126 Brazilian intensive care units between February 27th and October 28th, 2020. Assessing temporal changes in deaths, we identified distinct time periods. We evaluated the association of characteristics and respiratory support strategies with 60-day in-hospital mortality using random-effects multivariable Cox regression with inverse probability weighting. Results Among the 13,301 confirmed-COVID-19 patients, 60-day in-hospital mortality was 13%. Across four time periods identified, younger patients were progressively more common, non-invasive respiratory support was increasingly used, and the 60-day in-hospital mortality decreased in the last two periods. 4188 patients received advanced respiratory support (non-invasive or invasive), from which 42% underwent only invasive mechanical ventilation, 37% only non-invasive respiratory support and 21% failed non-invasive support and were intubated. After adjusting for organ dysfunction scores and premorbid conditions, we found that younger age, absence of frailty and the use of non-invasive respiratory support (NIRS) as first support strategy were independently associated with improved survival (hazard ratio for NIRS first [95% confidence interval], 0.59 [0.54–0.65], p

Objectives Coronavirus disease 19 (COVID-19) is a major cause of hospital admission and represents a challenge for patient management during intensive care unit (ICU) stay. We aimed to describe the clinical course and outcomes of COVID-19 pneumonia in critically ill patients. Methods We performed a systematic search of peer-reviewed publications in MEDLINE, EMBASE and the Cochrane Library up to 15th August 2020. Preprints and reports were also included if they met the inclusion criteria. Study eligibility criteria were full-text prospective, retrospective or registry-based publications describing outcomes in patients admitted to the ICU for COVID-19, using a validated test. Participants were critically ill patients admitted in the ICU with COVID-19 infection. Results From 32 articles included, a total of 69 093 patients were admitted to the ICU and were evaluated. Most patients included in the studies were male (76 165/128 168, 59%, 26 studies) and the mean patient age was 56 (95%CI 48.5–59.8) years. Studies described high ICU mortality (21 145/65 383, 32.3%, 15 studies). The median length of ICU stay was 9.0 (95%CI 6.5–11.2) days, described in five studies. More than half the patients admitted to the ICU required mechanical ventilation (31 213/53 465, 58%, 23 studies) and among them mortality was very high (27 972/47 632, 59%, six studies). The duration of mechanical ventilation was 8.4 (95%CI 1.6–13.7) days. The main interventions described were the use of non-invasive ventilation, extracorporeal membrane oxygenation, renal replacement therapy and vasopressors. Conclusions This systematic review, including approximately 69 000 ICU patients, demonstrates that COVID-19 infection in critically ill patients is associated with great need for life-sustaining interventions, high mortality, and prolonged length of ICU stay.

PURPOSE OF REVIEW: This review aims to evaluate the evidence and recommendations for the prescription of corticosteroids as adjunctive therapy in patients with severe community-acquired pneumonia. RECENT FINDINGS: Corticosteroids have been prescribed with the objective to attenuate the marked and persistent activation of the immune system. However, some causes of community-acquired pneumonia, namely viral, are associated with unexpected low levels of cytokines and depressed cellular immunity. As a result, several recent randomized controlled trials and large prospective observational studies repeatedly showed that corticosteroids had no impact on survival, and in some types of pneumonia like influenza, its use was associated with potential harmful effects like invasive aspergillosis. Apart from this, adverse effects, namely hyperglycemia, superinfections and increased length-of-stay, were frequent findings in the corticosteroid-treated patients. SUMMARY: According to the current evidence, corticosteroids are recommended in Pneumocystis jiroveci pneumonia in HIV-infected patients and recommendations are against its use in influenza. In all other forms of severe community-acquired pneumonia, with the exclusion of SARS-CoV-2 pneumonia, the strength of the evidence does not support the safe and widespread use of corticosteroids as adjunctive therapy. Further studies are needed to identify subgroups of severe community-acquired pneumonia that can benefit or not from corticosteroids.

The digitalization of the Intensive Care Unit (ICU) led to an increasing amount of clinical data being collected at the bedside. The term "Big Data" can be used to refer to the analysis of these datasets that collect enormous amount of data of different origin and format. Complexity and variety define the value of Big Data. In fact, the retrospective analysis of these datasets allows to generate new knowledge, with consequent potential improvements in the clinical practice. Despite the promising start of Big Data analysis in medical research, which has seen a rising number of peer-reviewed articles, very limited applications have been used in ICU clinical practice. A close future effort should be done to validate the knowledge extracted from clinical Big Data and implement it in the clinic. In this article, we provide an introduction to Big Data in the ICU, from data collection and data analysis, to the main successful examples of prognostic, predictive and classification models based on ICU data. In addition, we focus on the main challenges that these models face to reach the bedside and effectively improve ICU care.

Acute physiologic derangements and multiple organ dysfunction are common after subarachnoid hemorrhage. We aimed to evaluate the simplified acute physiology score 3 (SAPS-3) and the sequential organ failure assessment (SOFA) scores for the prediction of in-hospital mortality in a large multicenter cohort of SAH patients. This was a retrospective analysis of prospectively collected data from 45 ICUs in Brazil, during 2014 and 2015. Patients admitted with non-traumatic subarachnoid hemorrhage (SAH) were included. Clinical and outcome data were retrieved from an electronic ICU quality registry. SAPS-3 and SOFA scores, without the neurological components (i.e., nSAPS-3 and nSOFA, respectively) were recorded, as well as the World Federation of Neurological Surgeons (WFNS) scale. We used multilevel logistic regression analysis to identify factors associated with in-hospital mortality. We evaluated performance using the area under the receiver operating characteristic curve (AUROC), as well as calibration belts and precision–recall plots. The study included 997 patients, from which 426 (43%) had poor clinical grade (WFNS 4 or 5) and in-hospital mortality was 34%. Median nSAPS-3 and nSOFA score at admission were 46 (IQR: 38–55) and 2 (0–5), respectively. Non-survivors were older, had higher nSAPS-3 and nSOFA, and more often poor grade. After adjustment for age, poor grade and withdrawal of life sustaining therapies, multivariable analysis identified nSAPS-3 and nSOFA score as independent clinical predictors of in-hospital mortality. The AUROC curve that included nSAPS-3 and nSOFA scores significantly improved the already good discrimination and calibration of age and WFNS to predict in-hospital mortality (AUROC: 0.89 for the full final model vs. 0.85 for age and WFNS; P

Purpose: To customize and externally validate the recently proposed Simplified Mortality Score for the ICU (SMS-ICU, a simple score for 90-day mortality that has no need for ancillary testing results) for in-hospital mortality and to compare its performance to SAPS 3. Material and methods: We used data from two distinct large cohorts of adult Brazilian patients with unplanned ICU admissions to perform a first-level customization (43,017 patients admitted to 78 ICUs) of the original SMS-ICU score for in-hospital mortality and, sequentially, externally validate it (313,365 patients admitted to 99 ICUs). Performance of SMS-ICU was assessed through measurements of discrimination and calibration and compared with SAPS 3. Results: In the validation cohort, median SMS-ICU was 13 (IQR 8-16) points and median SAPS 3 was 44 (IQR 36-51). Discrimination of SMS-ICU was good (AUC 0.817; 95% CI 0.814-0.819) but slightly lower than of SAPS 3 (AUC 0.845; 95% CI 0.843-0.848;). The customized SMS-ICU predictions were comparable to SAPS 3 in terms of calibration. Conclusion: In this external validation of the SMS-ICU in a large Brazilian cohort, we observed good discrimination of SMS-ICU and acceptable calibration after first-level customization. SMS-ICU can be used as a measure of illness severity for acutely admitted ICU patients in clinical studies.

To describe international variation in interprofessional rounds in intensive care units (ICUs).Survey of ICU clinicians on their practices and perceptions of rounds using societal mailing lists and social media.Out of 2402 respondents, 1752 (72.8%) use rounds. Teams are mostly composed of intensivists, nurses and medical trainees. The majority of rounds (57.5%) last2 h, and North Americans report the highest rates of rounds allowing family attendance (92.4%). Shorter rounds (1-2 h, OR 0.67, 0.52-0.86, p 0.01;1 h, OR 0.72, 0.53-0.97, p = 0.03), and strategies such as designating a person for writing (OR 0.73, 0.57-0.95, p = 0.01), and designating a person to assist other patients (OR 0.75, 0.57-0.98, p = 0.04) are associated with a lower perception of negative outcomes. Using daily goals during rounds is associated with a higher perception of positive outcomes (OR 1.85, 1.17-2.90, p 0.01).Three-quarters of respondents perform rounds, and models of rounds are heterogeneous, creating challenges for future studies on improving rounds. Respondents reporting better outcomes also experience shorter rounds, and adopt strategies such as discussion of daily goals, and designation individuals for writing or assisting other patients during rounds.

Background The COVID-19 pandemic tested the capacity of intensive care units (ICU) to respond to a crisis and demonstrated their fragility. Unsurprisingly, higher than usual mortality rates, lengths of stay (LOS), and ICU-acquired complications occurred during the pandemic. However, worse outcomes were not universal nor constant across ICUs and significant variation in outcomes was reported, demonstrating that some ICUs could adequately manage the surge of COVID-19. Methods In the present editorial, we discuss the concept of a resilient Intensive Care Unit, including which metrics can be used to address the capacity to respond, sustain results and incorporate new practices that lead to improvement. Results We believe that a resiliency analysis adds a component of preparedness to the usual ICU performance evaluation and outcomes metrics to be used during the crisis and in regular times. Conclusions The COVID-19 pandemic demonstrated the need for a resilient health system. Although this concept has been discussed for health systems, it was not tested in intensive care. Future studies should evaluate this concept to improve ICU organization for standard and pandemic times.

The coronavirus 2019 (COVID-19) pandemic affected stroke care worldwide. Data from low- and middle-income countries is limited.What was the impact of the pandemic in intensive care admissions and outcomes of patients with stroke, in comparison to trends over the last ten years?Retrospective cohort study including prospectively collected data from 165 ICUs in Brazil between 2011 and 2020. We analyzed clinical characteristics and mortality over a period of 10 years and evaluated the impact of the pandemic on stroke outcomes using the following approach: analyses of admissions for ischemic and hemorrhagic strokes and trends in in-hospital mortality over ten years; analysis of variable life-adjusted display (VLAD) during 2020; and a mixed-effects multivariable logistic regression model.17,115 stroke admissions were analyzed, from which 13,634 were ischemic and 3,481 were hemorrhagic. In-hospital mortality was lower after ischemic stroke as compared to hemorrhagic (9% vs. 24%, respectively). Changes in VLAD across epidemiological weeks of 2020 showed that the rise in COVID-19 cases was accompanied by increased mortality, mainly after ischemic stroke. In logistic regression mixed models, mortality was higher in 2020 compared to 2019, 2018, and 2017 in patients with ischemic stroke, namely in those without altered mental status. In hemorrhagic stroke, the increased mortality in 2020 was observed in patients 50 years or younger, as compared to 2019.Hospital outcomes of stroke admissions worsened during the COVID-19 pandemic, interrupting a trend of improvements in survival rates over 10 years. This effect was more pronounced during the surge of COVID-19 ICU admissions affecting predominantly patients with ischemic stroke without coma, and young patients with hemorrhagic stroke.

Background: Readmissions to Intensive Care Units (ICUs) result in increased morbidity, mortality, and ICU resource utilisation (e.g. prolonged mechanical ventilation), and as such, is a widely utilised metric of quality of critical care. Most of the evidence on incidence, characteristics, associated risk factors and attributable outcomes of unplanned readmission to ICU are from studies performed in high-income countries This study explores the determinants of risk attributable to unplanned ICU readmission in four ICUs in Kathmandu, Nepal. Methods: The registry-embedded eCRF reported data on case mix, severity of illness, in-ICU interventions (including organ support), ICU outcome, and readmission characteristics. Data were captured in all adult patients admitted between September 2019 and February 2021. Population and ICU encounter characteristics were compared between those with and without readmission. Independent risk factors for readmission were assessed using univariate analysis. Results: In total 2955 patients were included in the study. Absolute unplanned ICU readmission rate was 5.69 % (n=168) for all four ICUs. Median time from ICU discharge to readmission was 3 days (IQR=8,1). Of those readmitted, 29.17% (n=49) were discharged at night following their index admission. ICU mortality was higher following readmission to ICU(p=0.016) and mortality was increased further in patients whose primary index discharge was at night(p= 0.019). Primary diagnosis, age, and use of organ support in the first 24hrs of index admission were all independently attributable risk factors for readmission. Conclusions: Unplanned ICU readmission rates were adversely associated with significantly poorer outcomes, increased ICU resource utilisation. Clinical and organisational characteristics influenced risk of readmission and outcome.

Purpose of review Critical care registries are synonymous with measurement of outcomes following critical illness. Their ability to provide longitudinal data to enable benchmarking of outcomes for comparison within units over time, and between units, both regionally and nationally is a key part of the evaluation of quality of care and ICU performance as well as a better understanding of case-mix. This review aims to summarize literature on outcome measures currently being reported in registries internationally, describe the current strengths and challenges with interpreting existing outcomes and highlight areas where registries may help improve implementation and interpretation of both existing and new outcome measures. Recent findings Outcomes being widely reported through ICU registries include measures of survival, events of interest, patient-reported outcomes and measures of resource utilization (including cost). Despite its increasing adoption, challenges with quality of reporting of outcomes measures remain. Measures of short-term survival are feasible but those requiring longer follow-ups are increasingly difficult to interpret given the evolving nature of critical care in the context of acute and chronic disease management. Furthermore, heterogeneity in patient populations and in healthcare organisations in different settings makes use of outcome measures for international benchmarking at best complex, requiring substantial advances in their definitions and implementation to support those seeking to improve patient care. Summary Digital registries could help overcome some of the current challenges with implementing and interpreting ICU outcome data through standardization of reporting and harmonization of data. In addition, ICU registries could be instrumental in enabling data for feedback as part of improvement in both patient-centred outcomes and in service outcomes; notably resource utilization and efficiency.

Hospital length of stay and mortality are associated with resource use and clinical severity, respectively, in patients admitted to the intensive care unit (ICU) with acute stroke. We proposed a structured data-driven methodology to develop length of stay and 30-day mortality prediction models in a large multicenter Brazilian ICU cohort.We analyzed data from 130 ICUs from 43 Brazilian hospitals. All consecutive adult patients admitted with stroke (ischemic or nontraumatic hemorrhagic) to the ICU from January 2011 to December 2020 were included. Demographic data, comorbidities, acute disease characteristics, organ support, and laboratory data were retrospectively analyzed by a data-driven methodology, which included seven different types of machine learning models applied to training and test sets of data. The best performing models, based on discrimination and calibration measures, are reported as the main results. Outcomes were hospital length of stay and 30-day in-hospital mortality.Of 17,115 ICU admissions for stroke, 16,592 adult patients (13,258 ischemic and 3334 hemorrhagic) were analyzed; 4298 (26%) patients had a prolonged hospital length of stay ( 14 days), and 30-day mortality was 8% (n = 1392). Prolonged hospital length of stay was best predicted by the random forests model (Brier score = 0.17, area under the curve = 0.73, positive predictive value = 0.61, negative predictive value = 0.78). Mortality prediction also yielded the best discrimination and calibration through random forests (Brier score = 0.05, area under the curve = 0.90, positive predictive value = 0.66, negative predictive value = 0.94). Among the 20 strongest contributor variables in both models were (1) premorbid conditions (e.g., functional impairment), (2) multiple organ dysfunction parameters (e.g., hypotension, mechanical ventilation), and (3) acute neurological aspects of stroke (e.g., Glasgow coma scale score on admission, stroke type).Hospital length of stay and 30-day mortality of patients admitted to the ICU with stroke were accurately predicted through machine learning methods, even in the absence of stroke-specific data, such as the National Institutes of Health Stroke Scale score or neuroimaging findings. The proposed methods using general intensive care databases may be used for resource use allocation planning and performance assessment of ICUs treating stroke. More detailed acute neurological and management data, as well as long-term functional outcomes, may improve the accuracy and applicability of future machine-learning-based prediction algorithms.

Background Excess morbidity and mortality following critical illness is increasingly attributed to potentially avoidable complications occurring as a result of complex ICU management (Berenholtz et al., J Crit Care 17:1-2, 2002; De Vos et al., J Crit Care 22:267-74, 2007; Zimmerman J Crit Care 1:12-5, 2002). Routine measurement of quality indicators (QIs) through an Electronic Health Record (EHR) or registries are increasingly used to benchmark care and evaluate improvement interventions. However, existing indicators of quality for intensive care are derived almost exclusively from relatively narrow subsets of ICU patients from high-income healthcare systems. The aim of this scoping review is to systematically review the literature on QIs for evaluating critical care, identify QIs, map their definitions, evidence base, and describe the variances in measurement, and both the reported advantages and challenges of implementation. Method We searched MEDLINE, EMBASE, CINAHL, and the Cochrane libraries from the earliest available date through to January 2019. To increase the sensitivity of the search, grey literature and reference lists were reviewed. Minimum inclusion criteria were a description of one or more QIs designed to evaluate care for patients in ICU captured through a registry platform or EHR adapted for quality of care surveillance. Results The search identified 4780 citations. Review of abstracts led to retrieval of 276 full-text articles, of which 123 articles were accepted. Fifty-one unique QIs in ICU were classified using the three components of health care quality proposed by the High Quality Health Systems (HQSS) framework. Adverse events including hospital acquired infections (13.7%), hospital processes (54.9%), and outcomes (31.4%) were the most common QIs identified. Patient reported outcome QIs accounted for less than 6%. Barriers to the implementation of QIs were described in 35.7% of articles and divided into operational barriers (51%) and acceptability barriers (49%). Conclusions Despite the complexity and risk associated with ICU care, there are only a small number of operational indicators used. Future selection of QIs would benefit from a stakeholder-driven approach, whereby the values of patients and communities and the priorities for actionable improvement as perceived by healthcare providers are prioritized and include greater focus on measuring discriminable processes of care.

Background: Unplanned readmissions to Intensive Care Units (ICUs) result in increased morbidity, mortality, and ICU resource utilisation (e.g. prolonged mechanical ventilation), and as such, is a widely utilised metric of quality of critical care. Most of the evidence on incidence, characteristics, associated risk factors and attributable outcomes of unplanned readmission to ICU are from studies performed in high-income countries This study explores the determinants of risk attributable to unplanned ICU readmission in four ICUs in Kathmandu, Nepal. Methods: The registry-embedded eCRF reported data on case mix, severity of illness, in-ICU interventions (including organ support), ICU outcome, and readmission characteristics. Data were captured in all adult patients admitted between September 2019 and February 2021. Population and ICU encounter characteristics were compared between those with and without readmission. Independent risk factors for readmission were assessed using univariate analysis. Results: In total 2948 patients were included in the study. Absolute unplanned ICU readmission rate was 5.60 % (n=165) for all four ICUs. Median time from ICU discharge to readmission was 3 days (IQR=8,1). Of those readmitted, 29.7% (n=49) were discharged at night following their index admission. ICU mortality was higher following readmission to ICU(p=0.016) and mortality was increased further in patients whose primary index discharge was at night(p= 0.019). Primary diagnosis, age, and use of organ support in the first 24hrs of index admission were all independently attributable risk factors for readmission. Conclusions: Unplanned ICU readmission rates were adversely associated with significantly poorer outcomes, increased ICU resource utilisation. Clinical and organisational characteristics influenced risk of readmission and outcome.

Corticosteroids have been used for decades in the adjunctive treatment of severe infections in intensive care. The most frequent scenario in intensive care is in septic shock, where low doses of glucocorticoids appear to restore vascular responsiveness to norepinephrine. There is a strong body of evidence suggesting that hydrocortisone reduces time on vasopressor, and may modulate the immune response. In this review, we explore the current evidence supporting the use of corticosteroids in septic shock, its benefits, and potential harms. In addition to landmark clinical trials, we will also describe new frontiers for the use of corticosteroids in septic shock which should be explored in future studies.

Objective Describe characteristics and outcomes of CAP admitted to public ICUs in Brazil. Methods Retrospective cohort study in 4 Tertiary Public Hospitals in Rio de Janeiro, Brazil during 2016. Patients admitted to ICUs with a diagnosis of community-acquired pneumonia were included. Clinical and outcomes data were collected from Epimed Monitor System. Results From 7902 admissions, 802 patients (10, 1%) were included and analyzed. Main source of admission was the emergency department (78, 3%). Median age was 66 (IQR 54–77) years, SAPS3 71(IQR 58–83) and SOFA D1 9(IQR 5–12) points. 67% of patients needed invasive mechanical ventilation, 12% hemodialysis. 47% required vasopressors. ICU and hospital mortality were 55.9% and 66.5% respectively. In a multivariate analysis, malnutrition [OR 2.28(1.21–4.3)], septic shock at admission [OR 1.95(1.39–2.75)], AIDS [3.04(1.16–7.93]), invasive mechanical ventilation [5.07(5.54–7.27)], age > 65 years [2.07(1.48–2.90)] and LOS >1 day before ICU admission [1.90(1.34–2.71)] were associated with increased mortality. Conclusion CAP is associated with high mortality in patients admitted to public ICUs in Brazil. The current findings may help improve resource allocation and should aim at improving access to ICU care since delayed admission was associated with increased hospital mortality.

Severity of illness scores are used for benchmarking and assessment of adjusted mortality in intensive care units (ICU). Te Acute Physiology and Chronic Health Evaluation (APACHE) and the Simplifed Acute Physiology Score (SAPS) 3 scores were recently evaluated in ICU patients with coronavirus disease 2019 (COVID-19) with conficting fndings. While in the cohorts from United Kingdom and United States ICU scores underestimated the actual mortality and poorly stratifed disease severity, analyses from Austria using the SAPS-3 with frst-level customization suggested satisfactory performance. In this study, we aimed to evaluate the performance of SAPS-3 to predict hospital mortality in a large cohort of COVID-19 patients admitted to ICUs in Brazil.

Coronavirus disease 19 (COVID-19) has posed unprecedented healthcare system challenges, some of which will lead to transformative change. It is obvious to healthcare workers and policymakers alike that an effective critical care surge response must be nested within the overall care delivery model. The COVID-19 pandemic has highlighted key elements of emergency preparedness. These include having national or regional strategic reserves of personal protective equipment, intensive care unit (ICU) devices, consumables and pharmaceuticals, as well as effective supply chains and efficient utilization protocols. ICUs must also be prepared to accommodate surges of patients and ICU staffing models should allow for fluctuations in demand. Pre-existing ICU triage and end-of-life care principles should be established, implemented and updated. Daily workflow processes should be restructured to include remote connection with multidisciplinary healthcare workers and frequent communication with relatives. The pandemic has also demonstrated the benefits of digital transformation and the value of remote monitoring technologies, such as wireless monitoring. Finally, the pandemic has highlighted the value of pre-existing epidemiological registries and agile randomized controlled platform trials in generating fast, reliable data. The COVID-19 pandemic is a reminder that besides our duty to care, we are committed to improve. By meeting these challenges today, we will be able to provide better care to future patients. ispartof: INTENSIVE CARE MEDICINE vol:47 issue:3 pages:282-291 ispartof: location:United States status: published

The length of stay (LOS) in the intensive care unit (ICU) is one of the most commonly used metrics for quality of care. Despite its potential limitations, ICU LOS is easy to measure, reproducible and can be used as a proxy for resource use, costs, and efficiency.(1) Moreover, it is a patientcentered outcome; therefore, it is of interest to multiple stakeholders, such as patients and families, managers, payors, and ICU personnel. However, in most circumstances, the ICU LOS is used retrospectively to assess ICU efficiency or to understand patients with a long LOS and, thus, elevated costs of care. Therefore, patient LOS prediction at ICU admission could help coordinate care, implement preventive measures, and better communicate with managers, payors, and families, setting realistic expectations.

The extraordinary pace of research on coronavirus disease 2019 (COVID-19) has been one of the major success stories of the pandemic. Therapeutic trials involving thousands of patients, which usually take years to complete, have been reported in a matter of months. National and international registries and networks have reported on tens of thousands of patients in near real time. However, there have also been many challenges: hundreds of trials have been underpowered, duplicated, or of poor quality; excessive bureaucracy has complicated study initiation; and only a small percentage of eligible patients worldwide have been enrolled in studies, while many others have been treated with off-label, unproven therapies. All of this has been complicated by an “infodemic” of low-quality medical information, accelerated by social media. info:eu-repo/semantics/publishedVersion

RESUMO Objetivo: Construir um modelo de custo-efetividade para comparar o uso de propofol com o de midazolam em pacientes críticos adultos sob uso de ventilação mecânica. Métodos: Foi construído um modelo de árvore decisória para pacientes críticos submetidos à ventilação mecânica, o qual foi analisado sob a perspectiva do sistema privado de saúde no Brasil. O horizonte temporal foi o da internação na unidade de terapia intensiva. Os desfechos foram custo-efetividade por hora de permanência na unidade de terapia intensiva evitada e custo-efetividade por hora de ventilação mecânica evitada. Foram obtidos os dados do modelo a partir de metanálise prévia. Assumiu-se que o custo da medicação estava incluído nos custos da unidade de terapia intensiva. Conduziram-se análises univariada e de sensibilidade probabilística. Resultados: Pacientes mecanicamente ventilados em uso de propofol tiveram diminuição de sua permanência na unidade de terapia intensiva e na duração da ventilação mecânica, respectivamente, em 47,97 horas e 21,65 horas. Com o uso de propofol, ocorreu redução média do custo de U$2.998,971 em comparação ao uso do midazolam. A custo-efetividade por hora de permanência na unidade de terapia intensiva evitada e por hora de ventilação mecânica evitada foi dominante, respectivamente, em 94,40% e 80,8% do tempo. Conclusão: Ocorreu diminuição significante do custo associado ao uso de propofol, no que se refere à permanência na unidade de terapia intensiva e à duração da ventilação mecânica para pacientes críticos adultos. ABSTRACT Objective: To build a cost-effectiveness model to compare the use of propofol versus midazolam in critically ill adult patients under mechanical ventilation. Methods: We built a decision tree model for critically ill patients submitted to mechanical ventilation and analyzed it from the Brazilian private health care system perspective. The time horizon was that of intensive care unit hospitalization. The outcomes were cost-effectiveness per hour of intensive care unit stay avoided and cost-effectiveness per hour of mechanical ventilation avoided. We retrieved data for the model from a previous meta-analysis. We assumed that the cost of medication was embedded in the intensive care unit cost. We conducted univariate and probabilistic sensitivity analyses. Results: Mechanically ventilated patients using propofol had their intensive care unit stay and the duration of mechanical ventilation decreased by 47.97 hours and 21.65 hours, respectively. There was an average cost reduction of US$ 2,998.971 for propofol when compared to midazolam. The cost-effectiveness per hour of intensive care unit stay and mechanical ventilation avoided were dominant 94.40% and 80.8% of the time, respectively. Conclusion: There was a significant reduction in costs associated with propofol use related to intensive care unit stay and duration of mechanical ventilation for critically ill adult patients.

International audience; Benchmarking is a common and effective method for measuring and analyzing ICU performance. With the existence of national registries, objective information can now be obtained to allow benchmarking of ICU care within and between countries. The present manuscript briefly describes the current status of benchmarking in healthcare and critical care and presents the LOGIC project, an initiative to promote international benchmarking for intensive care units. Currently 13 registries have joined LOGIC. We showed large differences in the utilization of ICU as well as resources and in outcomes. Despite the need for careful interpretation of differences due to variation in definitions and limited risk adjustment, LOGIC is a growing worldwide initiative that allows access to insightful epidemiologic data from ICUs in multiple databases and registries.

Background: The impact of neutropenia in critically ill immunocompromised patients admitted in a context of acute respiratory failure (ARF) remains uncertain. The primary objective was to assess the prognostic impact of neutropenia on outcomes of these patients. Secondary objective was to assess etiology of ARF according to neutropenia. Methods: We performed a post hoc analysis of a prospective multicenter multinational study from 23 ICUs belonging to the Nine-I network. Between November 2015 and July 2016, all adult immunocompromised patients with ARF admitted to the ICU were included in the study. Adjusted analyses included: (1) a hierarchical model with center as random effect; (2) propensity score (PS) matched cohort; and (3) adjusted analysis in the matched cohort. Results: Overall, 1481 patients were included in this study of which 165 had neutropenia at ICU admission (11%). ARF etiologies distribution was significantly different between neutropenic and non-neutropenic patients, main etiologies being bacterial pneumonia (48% vs 27% in neutropenic and non-neutropenic patients, respectively). Initial oxygenation strategy was standard supplemental oxygen in 755 patients (51%), high-flow nasal oxygen in 165 (11%), non-invasive ventilation in 202 (14%) and invasive mechanical ventilation in 359 (24%). Before adjustment, hospital mortality was significantly higher in neutropenic patients (54% vs 42%; p = 0.006). After adjustment for confounder and center effect, neutropenia was no longer associated with outcome (OR 1.40, 95% CI 0.93–2.11). Similar results were observed after matching (52% vs 46%, respectively; p = 0.35) and after adjustment in the matched cohort (OR 1.04; 95% CI 0.63–1.72). Conclusion: Neutropenia at ICU admission is not associated with hospital mortality in this cohort of critically ill immunocompromised patients admitted for ARF. In neutropenic patients, main ARF etiologies are bacterial and fungal infections., SCOPUS: ar.j, info:eu-repo/semantics/published

Compare outcomes of adult patients admitted to ICU- length of ICU stay, length of mechanical ventilation (MV), and time until extubation- according to the use of propofol versus midazolam.We searched MEDLINE, EMBASE, LILACS, and Cochrane databases to retrieve RCTs that compared propofol and midazolam used as sedatives in adult ICU patients. We applied a random-effects, meta-analytic model in all calculations. We applied the Cochrane collaboration tool and GRADE. We separated patients into two groups: acute surgical patients (hospitalization up to 24 h) and critically-ill patients (hospitalization over 24 h and whose articles mostly mix surgical, medical and trauma patients).Globally, propofol was associated with a reduced MV time of 4.46 h (MD: -4.46 [95% CI -7.51 to -1.42] p = 0.004, I2 = 63%, 6 studies) and extubation time of 7.95 h (MD: -7.95 [95% CI -9.86 to -6.03] p0.00001, I2 = 98%, 16 studies). Acute surgical patients sedation with propofol compared to midazolam was associated with a reduced ICU stay of 5.07 h (MD: -5.07 [95% CI -8.68 to -1.45] p = 0.006, I2 = 41%, 5 studies), MV time of 4.28 h (MD: -4.28; [95% CI -4.62 to -3.94] p0.0001, I2 = 0%, 3 studies), extubation time of 1.92 h (MD: -1.92; [95% CI -2.71 to -1.13] p = 0.00001, I2 = 89%, 9 studies). In critically-ill patients sedation with propofol compared to midazolam was associated with a reduced extubation time of 32.68 h (MD: -32.68 [95% CI -48.37 to -16.98] p = 0.0001, I2 = 97%, 9 studies). GRADE was very low for all outcomes.Sedation with propofol compared to midazolam is associated with improved clinical outcomes in ICU, with reduced ICU stay MV time and extubation time in acute surgical patients and reduced extubation time in critically-ill patients.

The delivery of critical care is a major challenge for developing countries [1]. The inequity of access to an ICU bed, heterogeneous triage policies, a low staff/patient ratio and suboptimal adherence to evidence-based practices contribute to disproportionally high mortality of sepsis and acute respiratory distress syndrome in these countries [2,3,4,5]. In addition, limited step-down and specialized ward beds’ availability further widens the gap between critical and non-critical care inside hospitals. As the COVID-19 pandemic spreads through the world, developing countries are challenged with the surge of pneumonia cases where up to 30% of all hospitalized cases will require ICU admission [6]. In August 2020, Brazil is a hotspot of COVID-19 with more than 100,000 deaths. Other Latin American countries such as Mexico, Peru, Colombia, and Chile are also among the 10 countries with most cases worldwide. Several factors seem to have contributed to the dramatic progress of the epidemic in the country. Initial measures of social distancing were adopted at the beginning of the epidemic in several states. However, the lack of central coordination and, at a certain point, the denial of the pandemic by a populist government meant that more effective measures such as lockdown were not adopted whereas use of unproven therapies such as hydroxychloroquine was encouraged. Also, the low availability of tests and progression towards the interior and peripheries of large cities made the epidemic hard to control causing overwhelming hospitals and ICUs.

Purpose: To describe trends in outcomes of cancer patients with unplanned admissions to intensive-care units (ICU) according to cancer type, organ support use, and performance status (PS) over an 8-year period. Methods: We retrospectively analyzed prospectively collected data from all cancer patients admitted to 92 medical–surgical ICUs from July/2011 to June/2019. We assessed trends in mortality through a Bayesian hierarchical model adjusted for relevant clinical confounders and whether there was a reduction in ICU length-of-stay (LOS) over time using a competing risk model. Results: 32,096 patients (8.7% of all ICU admissions; solid tumors, 90%; hematological malignancies, 10%) were studied. Bed/days use by cancer patients increased up to more than 30% during the period. Overall adjusted mortality decreased by 9.2% [95% credible interval (CI), 13.1–5.6%]. The largest reductions in mortality occurred in patients without need for organ support (9.6%) and in those with need for mechanical ventilation (MV) only (11%). Smallest reductions occurred in patients requiring MV, vasopressors, and dialysis (3.9%) simultaneously. Survival gains over time decreased as PS worsened. Lung cancer patients had the lowest decrease in mortality. Each year was associated with a lower sub-hazard for ICU death [SHR 0.93 (0.91–0.94)] and a higher chance of being discharged alive from the ICU earlier [SHR 1.01 (1–1.01)]. Conclusion: Outcomes in critically ill cancer patients improved in the past 8 years, with reductions in both mortality and ICU LOS, suggesting improvements in overall care. However, outcomes remained poor in patients with lung cancer, requiring multiple organ support and compromised PS.

Objectives: To test whether differences in both general and sepsis-specific patient characteristics explain the observed differences in sepsis mortality between countries, using two national critical care (ICU) databases. Design: Cohort study. Setting: We analyzed 62 and 164 ICUs in Brazil and England, respectively. Patients: Twenty-two–thousand four-hundred twenty-six adult ICU admissions from January 2013 to December 2013. Interventions: None. Measurements and Main Results: After harmonizing relevant variables, we merged the first ICU episode of adult medical admissions from Brazil (ORganizational CHaractEeriSTics in cRitical cAre study) and England (Intensive Care National Audit & Research Centre Case Mix Programme). Sepsis-3 definition was used, and the primary outcome was hospital mortality. We used multilevel logistic regression models to evaluate the impact of country (Brazil vs England) on mortality, after adjustment for general (age, sex, comorbidities, functional status, admission source, time to admission) and sepsis-specific (site of infection, organ dysfunction type and number) patient characteristics. Of medical ICU admissions, 13.2% (4,505/34,150) in Brazil and 30.7% (17,921/58,316) in England met the sepsis definition. The Brazil cohort was older, had greater prevalence of severe comorbidities and dependency compared with England. Respiratory was the most common infection site in both countries. The most common organ dysfunction was cardiovascular in Brazil (41.2%) and respiratory in England (85.8%). Crude hospital mortality was similar (Brazil 41.4% vs England 39.3%; odds ratio, 1.12 [0.98–1.30]). After adjusting for general patient characteristics, there was an important change in the point-estimate of the odds ratio (0.88 [0.75–1.02]). However, after adjusting for sepsis-specific patient characteristics, the direction of effect reversed again with Brazil having higher risk-adjusted mortality (odds ratio, 1.22 [1.05–1.43]). Conclusions: Patients with sepsis admitted to ICUs in Brazil and England have important differences in general and sepsis-specific characteristics, from source of admission to organ dysfunctions. We show that comparing crude mortality from sepsis patients admitted to the ICU between countries, as currently performed, is not reliable and that the adjustment for both general and sepsis-specific patient characteristics is essential for valid international comparisons of mortality amongst sepsis patients admitted to critical care units. Drs. Rowan and Soares are senior authors. † In memoriam. The views expressed in this publication are those of the author(s) and not necessarily those of the National Health Service, the National Institute for Health Research or the Department of Health. Drs. Ranzani and Shankar-Hari are equal contributors. Dr. Ranzani did data analyses. Drs. Ranzani and Shankar-Hari wrote the first draft of the article. Drs. Harrison, Rabello, Salluh, Rowan, and Soares led data collection. Dr. Rabello died during the peer-review process of this article. All authors unanimously agreed on her fundamental contribution for this study. All authors conceptualized and designed the study, interpreted data, and critically revised the article. Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s website (http://journals.lww.com/ccmjournal). The original ORganizational CHaractEeriSTics in cRitical cAre study was supported by the National Council for Scientific and Technological Development (Grant number 304240/2014-1), Carlos Chagas Filho Foundation for Research Support of the State of Rio de Janeiro and by departmental funds from the D’Or Institute for Research and Education. The Case Mix Programme is a subscription-based, national quality assessment program. The current study was funded internally by Intensive Care National Audit & Research Centre. The funding sources had no role in the design, conduct or analyses of the study. Dr. Shankar-Hari is supported by the National Institute for Health Research Clinician Scientist Award (NIHR-CS-2016-16-011). Dr. Soares disclosed that he is founder and equity shareholder at Epimed Solutions. The remaining authors have disclosed that they do not have any potential conflicts of interest. For information regarding this article, E-mail: otavioranzani@usp.br Copyright © by 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.

Given the rapidly changing nature of COVID-19, clinicians and policy makers require urgent review and summary of the literature, and synthesis of evidence-based guidelines to inform practice. The WHO advocates for rapid reviews in these circumstances. The purpose of this rapid guideline is to provide recommendations on the organizational management of intensive care units caring for patients with COVID-19 including: planning a crisis surge response; crisis surge response strategies; triage, supporting families, and staff. Electronic supplementary material The online version of this article (10.1007/s00134-020-06092-5) contains supplementary material, which is available to authorized users.

Characteristics of structure and process impact ICU performance and the outcomes of critically ill patients. We sought to identify organizational characteristics associated with efficient ICUs in low-resource settings.This is a secondary analysis of a multicenter cluster-randomized clinical trial in Brazil (CHECKLIST-ICU). Efficient units were defined by standardized mortality ratio (SMR) and standardized resource use (SRU) lower than the overall medians and non-efficient otherwise. We used a regularized logistic regression model to evaluate associations between organizational factors and efficiency.From 118 ICUs (13,635 patients), 47 units were considered efficient and 71 non-efficient. Efficient units presented lower incidence rates (median[IQR]) of central line-associated bloodstream infections (4.95[0.00-22.0] vs 6.29[0.00-25.6], p = .04), utilization rates of mechanical ventilation (0.41[0.07-0.73] vs 0.58[0.19-0.82], p .001), central venous catheter (0.67[0.15-0.98] vs 0.78[0.33-0.98], p = .04), and indwelling urinary catheter (0.62[0.22-0.95] vs 0.76[0.32-0.98], p .01) than non-efficient units. The reported active surveillance of ventilator-associated pneumonia (OR = 1.72; 95%CI, 1.16-2.57) and utilization of central venous catheters (OR = 1.94; 95%CI, 1.32-2.94) were associated with efficient ICUs.In low-resource settings, active surveillance of nosocomial infections and the utilization of invasive devices were associated with efficiency, supporting the management and evaluation of performance indicators as a starting point for improvement in ICU.

Submitted by DSpace Unilasalle (dspace@unilasalle.edu.br) on 2021-09-10T23:12:37Z No. of bitstreams: 1 The role of steroids in severe CAP.pdf: 232136 bytes, checksum: fc65c7581dcec5c29d337042cb681d4c (MD5) Made available in DSpace on 2021-09-10T23:12:37Z (GMT). No. of bitstreams: 1 The role of steroids in severe CAP.pdf: 232136 bytes, checksum: fc65c7581dcec5c29d337042cb681d4c (MD5) Previous issue date: 2020 Community-acquired pneumonia (CAP) is a leading cause of morbidity and mortality despite adequate antibiotic therapy. It is the single most common cause of infection-related mortality in the United States. An exaggerated host inflammatory response can potentially be harmful to both the lung and host, and has been associated with treatment failure and mortality. Modulation of inflammatory response may, therefore, be theoretically beneficial. The anti–inflammatory and immunosuppressive effects of steroids seem an attractive therapeutic option in severe CAP patients. Available datapoint to overall shorter time to clinical stability and decreased length-of-stay in CAP patients, with a potential mortality benefit in severe CAP. The level of evidence is, however, low to moderate regarding mortality due to high heterogeneity and insufficient power of data. Furthermore, steroids were deleterious in influenza pneumonia and in patients with pneumococcal pneumonia data suggest a lack of efficacy and potential harm. Both European and American guidelines recommend not using corticosteroids in CAP. Patients who might benefit and those that can be harmed from steroids remain to be clearly identified, as does the ideal steroid for CAP patients, based on pharmacokinetic and pharmacodynamic properties. It is essential for future studies to avoid the same methodological bias present in the available data so that high-quality evidence on the true role of steroids in CAP can be provided.

Background Several studies were published to validate the quick Sepsis-related Organ Failure Assessment (qSOFA), namely in comparison with the systemic inflammatory response syndrome (SIRS) criteria. We performed a systematic review and meta-analysis with the aim of comparing the qSOFA and SIRS in patients outside the ICU. Methods We searched MEDLINE, CINAHL, and the Web of Science database from February 23, 2016 until June 30, 2017 to identify full-text English-language studies published after the Sepsis-3 publication comparing the qSOFA and SIRS and their sensitivity or specificity in diagnosing sepsis, as well as hospital and ICU length of stay and hospital mortality. Data extraction from the selected studies followed the recommendations of the Meta-analyses of Observational Studies in Epidemiology group and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Results From 4,022 citations, 10 studies met the inclusion criteria. Pooling all the studies, a total of 229,480 patients were evaluated. The meta-analysis of sensitivity for the diagnosis of sepsis comparing the qSOFA and SIRS was in favor of SIRS (risk ratio [RR], 1.32; 95% CI, 0.40-2.24; P Conclusions The SIRS was significantly superior to the qSOFA for sepsis diagnosis, and the qSOFA was slightly better than the SIRS in predicting hospital mortality. The association of both criteria could provide a better model to initiate or escalate therapy in patients with sepsis. Systematic Review Registration PROSPERO CRD42017067645.

Nosocomial pneumonia is a frequent and severe nosocomial infection divided in two distinct groups: hospital-acquired pneumonia and ventilator-associated pneumonia (VAP). In this context, the VAP is notoriously difficult to diagnose clinically, resulting from the lack of a 'gold standard' method of diagnosis.The use of biomarkers may potentially improve the early diagnosis of infections allowing earlier and better identification and treatment. An exhausting list of biomarkers has been studied and although far from perfect, procalcitonin (PCT) and C-reactive protein (CRP) are the most studied biomarkers used in clinical practice. Data coming from literature suggests the use of PCT for VAP prognosis and as a based algorithm tool for the reduction of duration of pneumonia therapy, as well as, the use of the CRP dynamics to the early prediction of VAP and the response to the antibiotics.The evidence for the use of biomarkers to diagnose nosocomial pneumonia as a stand-alone tool is low to moderate. Improved performance for both PCT and CRP can be obtained by using them in association with clinical features or scoring systems but prospective studies are still needed to validate this hypothesis.