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A widely adopted COS for intensive care patients will be an important development for use locally and regionally, but its development should also consider its application to the wider global ICU context. We read with interest the article by Kjær et al1 where they outline their proposed methods to develop a core outcome set (COS) for general intensive care unit (ICU) patients in Denmark. Development of a core outcome set for general intensive care unit patients - Need for a broader context?. [Extracted from the article]

Patients with cancer are at increased risk for sepsis as a consequence of immunosuppression. The hospital mortality remains elevated and it could be attributed to antibiotic failure because of the presence of multiresistant pathogens. Once the patient is critically ill, the use of the American Thoracic Society/Infectious Diseases Society of America classification does not seem very useful in the assessment of outcomes and the choice of antimicrobials. In critically ill patients, the characteristics of clinical response to antibiotics are usually inaccurate and occur late in the course of disease. So, the sequential evaluation of C-reactive protein-ratio is useful in the early identification of patients with antibiotic failure. To achieve safe and efficient antimicrobial therapy, we proposed an algorithm that may aid clinicians in their decision-making process. [ABSTRACT FROM AUTHOR]

Introduction: Contemporary information on mechanical ventilation (MV) use in emerging countries is limited. Moreover, most epidemiological studies on ventilatory support were carried out before significant developments, such as lung protective ventilation or broader application of non-invasive ventilation (NIV). We aimed to evaluate the clinical characteristics, outcomes and risk factors for hospital mortality and failure of NIV in patients requiring ventilatory support in Brazilian intensive care units (ICU). Methods: In a multicenter, prospective, cohort study, a total of 773 adult patients admitted to 45 ICUs over a twomonth period requiring invasive ventilation or NIV for more than 24 hours were evaluated. Causes of ventilatory support, prior chronic health status and physiological data were assessed. Multivariate analysis was used to identifiy variables associated with hospital mortality and NIV failure. Results: Invasive MV and NIV were used as initial ventilatory support in 622 (80%) and 151 (20%) patients. Failure with subsequent intubation occurred in 54% of NIV patients. The main reasons for ventilatory support were pneumonia (27%), neurologic disorders (19%) and non-pulmonary sepsis (12%). ICU and hospital mortality rates were 34% and 42%. Using the Berlin definition, acute respiratory distress syndrome (ARDS) was diagnosed in 31% of the patients with a hospital mortality of 52%. In the multivariate analysis, age (odds ratio (OR), 1.03; 95% confidence interval (CI), 1.01 to 1.03), comorbidities (OR, 2.30; 95% CI, 1.28 to 3.17), associated organ failures (OR, 1.12; 95% CI, 1.05 to 1.20), moderate (OR, 1.92; 95% CI, 1.10 to 3.35) to severe ARDS (OR, 2.12; 95% CI, 1.01 to 4.41), cumulative fluid balance over the first 72 h of ICU (OR, 2.44; 95% CI, 1.39 to 4.28), higher lactate (OR, 1.78; 95% CI, 1.27 to 2.50), invasive MV (OR, 2.67; 95% CI, 1.32 to 5.39) and NIV failure (OR, 3.95; 95% CI, 1.74 to 8.99) were independently associated with hospital mortality. The predictors of NIV failure were the severity of associated organ dysfunctions (OR, 1.20; 95% CI, 1.05 to 1.34), ARDS (OR, 2.31; 95% CI, 1.10 to 4.82) and positive fluid balance (OR, 2.09; 95% CI, 1.02 to 4.30). Conclusions: Current mortality of ventilated patients in Brazil is elevated. Implementation of judicious fluid therapy and a watchful use and monitoring of NIV patients are potential targets to improve outcomes in this setting. [ABSTRACT FROM AUTHOR]

The prevalence of vancomycin-resistant enterococci (VRE) colonization or infection in the hospital setting has increased globally. Many previous studies had analysed the risk factors for acquiring VRE, based on cross-sectional studies or prevalent cases. However, the actual incidence of and risk factors for VRE remain unclear. The present study was conducted in order to clarify the incidence of and risk factors for VRE in the intensive care unit (ICU). From 1st April 2008 to 31st March 2009, all patients admitted to a surgical ICU (SICU) were put on active surveillance for VRE. The surveillance cultures, obtained by rectal swab, were taken on admission, weekly while staying in the SICU, and on discharge from the SICU. A total of 871 patients were screened. Among them, 34 were found to carry VRE before their admission to the SICU, and 47 acquired VRE during their stay in the SICU, five of whom developed VRE infections. The incidence of newly acquired VRE during ICU stay was 21.9 per 1000 patient-days (95% confidence interval [CI], 16.4-29.1). Using multivariate analysis by logistic regression, we found that the length of ICU stay was an independent risk factor for new acquisition of VRE. In contrast, patients with prior exposure to first-generation cephalosporin were significantly less likely to acquire VRE. Strategies to reduce the duration of ICU stay and prudent usage of broad-spectrum antibiotics are the keys to controlling VRE transmission. [ABSTRACT FROM AUTHOR]

Background: Treatment of septic shock relies on appropriate antimicrobial therapy. Current culture based methods deliver final results after days, which may delay potentially lifesaving adjustments in antimicrobial therapy. This study was undertaken to compare PCR with blood culture results under routine conditions regarding 1. impact on antimicrobial therapy, and 2. time to result, in patients with presumed sepsis. Methodology/Principal Findings: This was an observational study in a 50 beds ICU of a university hospital. In 245 patients with suspected sepsis, 311 concomitant blood cultures and blood for multiplex PCR (VYOO®) were obtained. 45 of 311 blood cultures (14.5%) and 94 of 311 PCRs (30.1%) were positive. However, blood culture or microbiological sampling from the presumed site of infection rarely confirmed PCR results and vice versa. Median time to positivity and interquartile range were 24.2 (18.0, 27.5) hours for the PCR and 68 (52.2, 88.5) hours for BC (p<0.01). PCR median time to result was dependent on technician availability (53.5 hours on Saturdays, 7.2 hours under optimal logistic conditions). PCR results showed good correlation with procalcitonin (p<0.001). In 34% of patients with positive PCRs antimicrobial therapy was considered inadequate according to assessment of clinical arbitrators including 5 patients with vancomycin-resistant enterococci (VRE), 3 cases with multiresistant staphylococci, and 4 patients with fungi. Conclusions: The results of this observational study support the hypothesis that PCR results are available faster, are more frequently positive, and may result in earlier adjustment of antimicrobial therapy. However, shorter time to result can only be fully exploited when the laboratory is adequately staffed for a 24 hour/7 day service, or when point of care/automated assay systems become available. [ABSTRACT FROM AUTHOR]

Introduction: Community-acquired pneumonia (CAP) requiring intensive care unit (ICU) admission remains a severe medical condition, presenting ICU mortality rates reaching 30%. The aim of this study was to assess the value of different patterns of C-reactive protein (CRP)-ratio response to antibiotic therapy in patients with severe CAP requiring ICU admission as an early maker of outcome.Methods: In total, 191 patients with severe CAP were prospectively included and CRP was sampled every other day from D1 to D7 of antibiotic prescription. CRP-ratio was calculated in relation to D1 CRP concentration. Patients were classified according to an individual pattern of CRP-ratio response with the following criteria: fast response - when D5 CRP was less than or equal to 0.4 of D1 CRP concentration; slow response - when D5 CRP was > 0.4 and D7 less than or equal to 0.8 of D1 CRP concentration; nonresponse - when D7 CRP was > 0.8 of D1 CRP concentration. Comparison between ICU survivors and non-survivors was performed.Results: CRP-ratio from D1 to D7 decreased faster in survivors than in non-survivors (p = 0.01). The ability of CRP-ratio by D5 to predict ICU outcome assessed by the area under the ROC curve was 0.73 (95% Confidence Interval, 0.64 - 0.82). By D5, a CRP concentration above 0.5 of the initial level was a marker of poor outcome (sensitivity 0.81, specificity 0.58, positive likelihood ratio 1.93, negative likelihood ratio 0.33). The time-dependent analysis of CRP-ratio of the three patterns (fast response n = 66; slow response n = 81; nonresponse n = 44) was significantly different between groups (p < 0.001). The ICU mortality rate was considerably different according to the patterns of CRP-ratio response: fast response 4.8%, slow response 17.3% and nonresponse 36.4% (p < 0.001).Conclusions: In severe CAP, sequential evaluation of CRP-ratio was useful in the early identification of patients with poor outcome. The evaluation of CRP-ratio pattern of response to antibiotics during the first week of therapy was useful in the recognition of the individual clinical evolution. [ABSTRACT FROM AUTHOR]

The article presents the authors' perspective on the role of corticosteroids as adjunctive therapy for severe infections. Citing various clinical trials, they contend that the use of corticosteroids for severe infections remains to be clarified. They assert that its use in Pneumocystis pneumonia and in bacterial meningitis may be recommended, and its possibile use for severe early acute respiratory distress syndrome (ARDS) and severe community-acquired pneumonia.

Intensive care has become important for the treatment of patients with cancer. However, the prognosis of these patients is considered poor a priori and decisions to admit a patient with cancer to the intensive care unit (ICU) are still source of controversy between oncologists and intensivists. The outcome of severely ill cancer patients does not depend solely on the causes that determine the admission to the ICU, but it also depends on cancer- and anticancer-related characteristics, such as performance status and cancer status. The decision-making process of ICU admission and of the appropriateness of advanced life-support requires a thorough evaluation of these characteristics and of the expectancies and wishes of patients and family members. A better understanding of such parameters may be helpful to avoid forgoing intensive care to patients who can potentially benefi t from it. [ABSTRACT FROM AUTHOR]

Several letters to the editor are presented in response the article "Hydrocortisone therapy for patients with multiple trauma," by A. Roquilly, P. J. Mahe, P. Seguin and colleagues in volume 305, 2011 issue.

Take-home message After more than 40 years, ICU scoring systems remain the mainstem of ICU performance evaluation. Many national ICU registries including those in the United Kingdom [[4]], Italy, Australia, and New Zealand (leveraging previous illness severity scores) developed, updated, and recalibrated their own mortality prediction models to ensure better ICU performance evaluation and benchmarking. Four decades of prognostic scores in intensive care Intensive care units (ICUs) are people- and technology-intensive environments where timely and wise use of advanced monitoring and life support is crucial to revert or avoid life-threatening conditions. Initiatives such as the Linking of Global Intensive Care (LOGIC) consortium of national ICU Registries and The Global Open Source Severity of Illness Score (GOSSIS) are currently working on effective ways to provide international comparisons of ICUs by using both existing scoring systems and creating new ones [[13], [15]]. [Extracted from the article]

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. [ABSTRACT FROM AUTHOR]

Regardless, our findings reinforce that standard severity of illness scores should be used with caution for mortality prognostication or benchmarking of ICU performance in COVID-19 patients. 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. [Extracted from the article]

Guidet et al. [[1]] in an interesting paper demonstrated higher mortality of critically ill patients aged > 80 years admitted to the intensive care unit (ICU) during the first phase of the pandemic of coronavirus disease 2019 (COVID-19) compared to those with respiratory failure before the pandemic. Increased 30-days mortality in very old ICU patients with COVID-19 compared to patients with respiratory failure without COVID-19. The pandemic disrupted ICU organization and negatively affected the outcomes of COVID and non-COVID patients [[3]]. [Extracted from the article]

Severe sepsis is a major challenge for clinicians caring for acutely ill patients. For many years, several biomarkers have been tested and proposed to improve the ability not only to diagnose but also to anticipate clinical response to antibiotics. Despite the availability of many sophisticated and novel biomarkers, current evidence demonstrates that C-reactive protein (CRP), a well-known and relatively inexpensive biomarker, is useful in the clinical setting. The sequential evaluation of plasma CRP concentrations in patients with severe sepsis and the interpretation of its patterns may allow assessments of individual prognosis and response to treatment. [ABSTRACT FROM AUTHOR]

Severe community-acquired pneumonia is a major cause of admission to intensive care units and its mortality rates remain exceedingly high. In the search for adjunctive therapies, clinicians who were encouraged by available, though limited, evidence prescribed steroids in most patients with severe sepsis or septic shock, including those with community-acquired pneumonia. Current evidence demonstrates that, whereas corticosteroids should not be routinely employed as adjuvant therapy for severe community-acquired pneumonia, there is sufficient equipoise to continue studying the use of corticosteroids. [ABSTRACT FROM AUTHOR]

The letter discusses the importance of data in improving intensive care unit (ICU) management in low-resource settings (LRS). The authors highlight the role of ICU registries in collecting real-world data on critically ill patients, which can aid in implementing quality improvement programs and reducing care variation. They provide examples of successful ICU registries in middle-income countries and emphasize the need for sustainable funding and capacity building to support these initiatives. The letter concludes by emphasizing the importance of data-driven culture and international efforts to improve care delivery in LRS. [Extracted from the article]

Background and Purpose: 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. Methods: 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. Results: 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 < 0.0001). Conclusions: nSAPS-3 and nSOFA scores were independently associated with in-hospital mortality after SAH. The addition of these scores improved early prediction of hospital mortality in our cohort and should be integrated to other specific prognostic indices in the early assessment of SAH. [ABSTRACT FROM AUTHOR]

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 < 0.001).Conclusion: Age and mortality rates have declined over the first 8 months of the pandemic. The use of NIRS as the first respiratory support measure was associated with survival, but causal inference is limited by the observational nature of our data. [ABSTRACT FROM AUTHOR]

Background: 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.Methods: 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.Results: 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).Conclusions: 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. [ABSTRACT FROM AUTHOR]

Purpose: Parametric regression models have been the main statistical method for identifying average treatment effects. Causal machine learning models showed promising results in estimating heterogeneous treatment effects in causal inference. Here we aimed to compare the application of causal random forest (CRF) and linear regression modelling (LRM) to estimate the effects of organisational factors on ICU efficiency., Methods: A retrospective analysis of 277,459 patients admitted to 128 Brazilian and Uruguayan ICUs over three years. ICU efficiency was assessed using the average standardised efficiency ratio (ASER), measured as the average of the standardised mortality ratio (SMR) and the standardised resource use (SRU) according to the SAPS-3 score. Using a causal inference framework, we estimated and compared the conditional average treatment effect (CATE) of seven common structural and organisational factors on ICU efficiency using LRM with interaction terms and CRF., Results: The hospital mortality was 14 %; median ICU and hospital lengths of stay were 2 and 7 days, respectively. Overall median SMR was 0.97 [IQR: 0.76,1.21], median SRU was 1.06 [IQR: 0.79,1.30] and median ASER was 0.99 [IQR: 0.82,1.21]. Both CRF and LRM showed that the average number of nurses per ten beds was independently associated with ICU efficiency (CATE [95 %CI]: -0.13 [-0.24, -0.01] and -0.09 [-0.17,-0.01], respectively). Finally, CRF identified some specific ICUs with a significant CATE in exposures that did not present a significant average effect., Conclusion: In general, both methods were comparable to identify organisational factors significantly associated with CATE on ICU efficiency. CRF however identified specific ICUs with significant effects, even when the average effect was nonsignificant. This can assist healthcare managers in further in-dept evaluation of process interventions to improve ICU efficiency., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Importance: Despite its implementation in several countries, there has not been a randomized clinical trial to assess whether telemedicine in intensive care units (ICUs) could improve clinical outcomes of critically ill patients., Objective: To determine whether an intervention comprising daily multidisciplinary rounds and monthly audit and feedback meetings performed by a remote board-certified intensivist reduces ICU length of stay (LOS) compared with usual care., Design, Setting, and Participants: A parallel cluster randomized clinical trial with a baseline period in 30 general ICUs in Brazil in which daily multidisciplinary rounds performed by board-certified intensivists were not routinely available. All consecutive adult patients (aged ≥18 years) admitted to the participating ICUs, excluding those admitted due to justice-related issues, were enrolled between June 1, 2019, and April 7, 2021, with last follow-up on July 6, 2021., Intervention: Remote daily multidisciplinary rounds led by a board-certified intensivist through telemedicine, monthly audit and feedback meetings for discussion of ICU performance indicators, and provision of evidence-based clinical protocols., Main Outcomes and Measures: The primary outcome was ICU LOS at the patient level. Secondary outcomes included ICU efficiency, in-hospital mortality, incidence of central line-associated bloodstream infections, ventilator-associated events, catheter-associated urinary tract infections, ventilator-free days at 28 days, patient-days receiving oral or enteral feeding, patient-days under light sedation, and rate of patients with oxygen saturation values under that of normoxemia, assessed using generalized linear mixed models., Results: Among 17 024 patients (1794 in the baseline period and 15 230 in the intervention period), the mean (SD) age was 61 (18) years, 44.7% were female, the median (IQR) Sequential Organ Failure Assessment score was 6 (2-9), and 45.5% were invasively mechanically ventilated at admission. The median (IQR) time under intervention was 20 (16-21) months. Mean (SD) ICU LOS, adjusted for baseline assessment, did not differ significantly between the tele-critical care and usual care groups (8.1 [10.0] and 7.1 [9.0] days; percentage change, 8.2% [95% CI, -5.4% to 23.8%]; P = .24). Results were similar in sensitivity analyses and prespecified subgroups. There were no statistically significant differences in any other secondary or exploratory outcomes., Conclusions and Relevance: Daily multidisciplinary rounds conducted by a board-certified intensivist through telemedicine did not reduce ICU LOS in critically ill adult patients., Trial Registration: ClinicalTrials.gov Identifier: NCT03920501.