Search

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

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.

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.

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.

Fernando A. Bozza. Fundacao Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Documento produzido em parceria ou por autor vinculado a Fiocruz, mas nao consta a informacao no documento.

Detailed information on organization and process of care in intensive care units (ICU) in emerging countries is scarce. Here, we investigated the impact of organizational factors on the outcomes and resource use in a large sample of Brazilian ICUs. Retrospective cohort study of 59,693 patients (medical admissions, 67 %) admitted to 78 ICUs during 2013. We retrieved patients’ data from an ICU quality registry and surveyed ICUs regarding structure, organization, staffing patterns, and process of care. We used multilevel logistic regression analysis to identify factors associated with hospital mortality. Efficient resource use was assessed by estimating standardized resource use and mortality rates adjusted for the SAPS 3 score. ICUs were mostly medical-surgical (79 %) and located at private hospitals (86 %). Median nurse to bed ratio was 0.20 (IQR, 0.15–0.28) and board-certified intensivists were present 24/7 in 16 (21 %) of ICUs. Multidisciplinary rounds occurred in 67 (86 %) and daily checklists were used in 36 (46 %) ICUs. Most frequent protocols focused on sepsis management and prevention of healthcare-associated infections. Hospital mortality was 14.4 %. In multivariable analysis, the number of protocols was the only organizational characteristic associated with mortality [odds ratio = 0.944 (95 % CI 0.904–0.987)]. The effects of protocols were consistent across subgroups including surgical and medical patients as well as the SAPS 3 tertiles. We also observed a significant trend toward efficient resource use as the number of protocols increased. In emerging countries such as Brazil, organizational factors, including the implementation of protocols, are potential targets to improve patient outcomes and resource use in ICUs.

Contains fulltext : 182587.pdf (Publisher’s version ) (Closed access) Over the coming years, accelerating progress against cancer will be associated with an increased number of patients who require life-sustaining therapies for infectious or toxic chemotherapy-related events. Major changes include increased number of cancer patients admitted to the ICU with full-code status or for time-limited trials, increased survival and quality of life in ICU survivors, changing prognostic factors, early ICU admission for optimal monitoring, and use of noninvasive diagnostic and therapeutic strategies. In this review, experts in the management of critically ill cancer patients highlight recent changes in the use and the results of intensive care in patients with malignancies. They seek to put forward a standard of care for the management of these patients and highlight important updates that are required to care for them. The research agenda they suggest includes important studies to be conducted in the next few years to increase our understanding of organ dysfunction in this population and to improve our ability to appropriately use life-saving therapies or select new therapeutic approaches that are likely to improve outcomes. This review aims to provide more guidance for the daily management of patients with cancer, in whom outcomes are constantly improving, as is our global ability to fight against what is becoming the leading cause of mortality in industrialized and non-industrialized countries.

Cities are expanding rapidly in middle-income countries, but their supply of acute care services is unknown. We measured acute care services supply in seven cities of diverse economic background.In a cross-sectional study, we compared cities from two high-income (Boston, USA and Paris, France), three upper-middle-income (Bogota, Colombia; Recife, Brazil; and Liaocheng, China), and two lower-middle-income (Chennai, India and Kumasi, Ghana) countries. We collected standardized data on hospital beds, intensive care unit beds, and ambulances. Where possible, information was collected from local authorities. We expressed results per population (from United Nations) and per acute illness deaths (from Global Burden of Disease project).Supply of hospital beds where intravenous fluids could be delivered varied fourfold from 72.4/100,000 population in Kumasi to 241.5/100,000 in Boston. Intensive care unit (ICU) bed supply varied more than 45-fold from 0.4/100,000 population in Kumasi to 18.8/100,000 in Boston. Ambulance supply varied more than 70-fold. The variation widened when supply was estimated relative to disease burden (e.g., ICU beds varied more than 65-fold from 0.06/100 deaths due to acute illnesses in Kumasi to 4.11/100 in Bogota; ambulance services varied more than 100-fold). Hospital bed per disease burden was associated with gross domestic product (GDP) (R (2) = 0.88, p = 0.01), but ICU supply was not (R (2) = 0.33, p = 0.18). No city provided all requested data, and only two had ICU data.Urban acute care services vary substantially across economic regions, only partially due to differences in GDP. Cities were poor sources of information, which may hinder their future planning.

Fernando A. Bozza. Fundacao Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Documento produzido em parceria ou por autor vinculado a Fiocruz, mas nao consta a informacao no documento.

To evaluate the outcomes of patients with head and neck cancer and severe acute illnesses, and to identify characteristics associated with hospital mortality. Cohort study. Ten-bed medical–surgical oncologic intensive care unit (ICU). Consecutive patients admitted to the ICU over a 68-month period. None. Demographic, clinical and cancer-related data were collected. Multivariate logistic regression analysis was performed to identify predictive factors of hospital mortality. One hundred and twenty-one patients aged 63.3 ± 14.7 years were enrolled in the study. The main sites of primary tumor were oral cavity (30%), larynx (25%), pharynx (14%) and thyroid (9%). The main reasons for ICU admission were sepsis (37%) and acute respiratory failure (20%). The mean SAPS II score was 49.6 ± 17.8 points, and during ICU stay 100 (83%) patients received mechanical ventilation, 70 (58%), vasopressors, and 12 (10%), dialysis. The ICU, hospital and 6-month mortality rates were 39%, 56% and 72%, respectively. A performance status ≥ 2 [odds ratio (OR) = 5.17 (95% confidence interval, CI = 1.84–14.53)], advanced cancer (TNM stage IV) [OR = 3.80 (95% CI = 1.28–11.28)], and the number of organ failures [OR=2.87 (95% CI=1.83–4.50)] were associated with increased mortality in multivariate analysis. In conjunction with clinical judgment and taking into consideration the patient's preferences and values, the knowledge of these outcome predictors may be useful in helping physicians to identify patients who might benefit from the intensive care and to improve discussions on patients' prognosis.

To validate the SAPS 3 admission prognostic model in patients with cancer admitted to the intensive care unit (ICU).Cohort study.Ten-bed medical-surgical oncologic ICU.Nine hundred and fifty-two consecutive patients admitted over a 3-year period.None.Data were prospectively collected at admission of ICU. SAPS II and SAPS 3 scores with respective estimated mortality rates were calculated. Discrimination was assessed by area under receiver operating characteristic (AUROC) curves and calibration by Hosmer-Lemeshow goodness-of-fit test. The mean age was 58.3+/-23.1 years; there were 471 (49%) scheduled surgical, 348 (37%) medical and 133 (14%) emergency surgical patients. ICU and hospital mortality rates were 24.6% and 33.5%, respectively. The mean SAPS 3 and SAPS II scores were 52.3+/-18.5 points and 35.3+/-20.7 points, respectively. All prognostic models showed excellent discrimination (AUROCor=0.8). The calibration of SAPS II was poor (p0.001). However, the calibration of standard SAPS 3 and its customized equation for Central and South American (CSA) countries were appropriate (p0.05). SAPS II and standard SAPS 3 prognostic models tended somewhat to underestimate the observed mortality (SMR1). However, when the customized equation was used, the estimated mortality was closer to the observed mortality [SMR=0.95 (95% CI=0.84-1.07)]. Similar results were observed when scheduled surgical patients were excluded.The SAPS 3 admission prognostic model at ICU admission, in particular its customized equation for CSA, was accurate in our cohort of critically ill patients with cancer.

To evaluate the impact of two different comorbidity measures on the 6-month mortality of severely ill cancer patients.Prospective cohort study in a ten-bed oncological medical-surgical intensive care unit (ICU).A total of 772 consecutive patients were included over a 45-month period. The mean age was 57.6+/-16.4 years, and 642 (83%) patients had solid tumors.Data were collected on admission and during ICU stay. Comorbidities were evaluated using the Charlson Comorbidity Index (CCI) and the Adult Comorbidity Evaluation (ACE-27). The ICU, hospital, and 6-month mortality rates were 34%, 47%, and 58%, respectively. The most frequent comorbidities were hypertension (33%), diabetes mellitus (8%), and chronic pulmonary disease (7%). There were important differences between the two indices regarding the comorbidity evaluation. Using the ACE-27, 389 patients (50%) had comorbid ailments that were classified as mild (31%), moderate (14%), and severe (5%) according to the comorbidity severity. According to the CCI, 212 patients (27%) had a comorbidity, and their median score was 1 (1-2). In the multivariable Cox proportional hazard models only the presence of a severe comorbidity by the ACE-27 was associated with increased mortality. The CCI was not independently associated with the outcome. Other outcome predictors were older age, poor performance status, active cancer, need of mechanical ventilation, and severity of acute organ failures.Severe comorbidities must be considered in the outcome evaluation of ICU cancer patients. The ACE-27 seems to be a useful instrument for prognostic assessment in this population.

Delirium, a prevalent organ dysfunction in critically ill patients, is independently associated with increased morbidity. This last decade has witnessed an exponential growth in delirium research in hospitalized patients, including those critically ill, and this research has highlighted that delirium needs to be better understood mechanistically to help foster research that will ultimately lead to its prevention and treatment. In this invited, evidence-based paper, a multinational and interprofessional group of clinicians and researchers from within the fields of critical care medicine, psychiatry, pediatrics, anesthesiology, geriatrics, surgery, neurology, nursing, pharmacy, and the neurosciences sought to address five questions: (1) What is the current standard of care in managing ICU delirium? (2) What have been the major recent advances in delirium research and care? (3) What are the common delirium beliefs that have been challenged by recent trials? (4) What are the remaining areas of uncertainty in delirium research? (5) What are some of the top study areas/trials to be done in the next 10 years? Herein, we briefly review the epidemiology of delirium, the current best practices for management of critically ill patients at risk for delirium or experiencing delirium, identify recent advances in our understanding of delirium as well as gaps in knowledge, and discuss research opportunities and barriers to implementation, with the goal of promoting an integrated research agenda.

The aim of the present study was to validate the Simplified Acute Physiology Score II (SAPS II) and 3 (SAPS 3), the Mortality Probability Models III (MPM(0)-III), and the Cancer Mortality Model (CMM) in patients with cancer admitted to several intensive care units (ICU).Prospective multicenter cohort study.Twenty-eight ICUs in Brazil.Seven hundred and seventeen consecutive patients (solid tumors 93%; hematological malignancies 7%) included over a 2-month period.None.Discrimination was assessed by area under receiver operating characteristic (AROC) curves and calibration by Hosmer-Lemeshow goodness-of-fit test. The main reasons for ICU admission were postoperative care (57%), sepsis (15%) and respiratory failure (10%). The ICU and hospital mortality rates were 21 and 30%, respectively. When all 717 patients were evaluated, discrimination was superior for both SAPS II (AROC = 0.84) and SAPS 3 (AROC = 0.84) scores compared to CMM (AROC = 0.79) and MPM(0)-III (AROC = 0.71) scores (P0.05 in all comparisons). Calibration was better using CMM and the customized equation of SAPS 3 score for South American countries (CSA). MPM(0)-III, SAPS II and standard SAPS 3 scores underestimated mortality (standardized mortality ratio, SMR1), while CMM tended to overestimation (SMR = 0.48). However, using the SAPS 3 for CSA resulted in more precise estimations of the probability of death [SMR = 1.02 (95% confidence interval = 0.87-1.19)]. Similar results were observed when scheduled surgical patients were excluded.In this multicenter study, the customized equation of SAPS 3 score for CSA was found to be accurate in predicting outcomes in cancer patients requiring ICU admission.

To evaluate cortisol levels and prevalence of adrenal insufficiency in patients with severe community-acquired pneumonia (CAP).Retrospective cohort study in a 24-bed medical-surgical intensive care unit (ICU).Forty patients with severe CAP admitted to the ICU from March 2003 and May 2005.Random cortisol levels were measured up to 72 h after ICU admission. A threshold of 20 microg/dl was considered for the diagnosis of adrenal insufficiency. Median cortisol levels were 15.5 microg/dl (IQR 10.8-25.1), and 26 patients (65%) met the criteria for adrenal insufficiency. Other cutoff levels of cortisol were evaluated, and 30 patients (75%) had cortisol levels below 25 microg/dl and 19 (47.5%) had cortisol levels below 15 microg/dl. When only patients with septic shock (n=19) were evaluated, 12 (63%) had adrenal insufficiency.Relative adrenal insufficiency occurs in a high proportion of patients with severe CAP. This finding highlights the importance of measuring cortisol levels and may help explain the potential benefits of hydrocortisone infusion in these patients.

Dear editor: When challenged by a potentially life-threatening infection, intensivists are frequently inclined to prescribe adjunctive therapies with so called immunomodulating effects. However, the story of anti-inflammatory therapies in severe infections has been so far a story of disenchantment. Most of it may be ascribed to an incomplete knowledge of immune and acute phase responses. Corticosteroids have recently been caught in the midst of a huge controversy regarding their indication for severe sepsis. Despite clear evidence of anti-inflammatory effects and of clinical benefit in small single center trials, the alleged survival benefits were not subsequently confirmed by the CORTICUS study. In a paper published in Intensive Care Medicine, Dr Quispe-Laime et al. [1] report their findings regarding the use of corticosteroids in patients with H1N1 influenza A virus-associated acute lung injury. The authors found significant improvement in oxygenation and a relatively low mortality rate. However, we have several concerns regarding the study’s rationale, methodology, results and conclusions. Recent systematic reviews do not support the use of corticosteroids for severe community-acquired pneumonia. Recent experimental data showed no beneficial effect on acute respiratory distress syndrome caused by the H5N1 infection [2]. A review evaluating the effects of adjunctive therapies in SARS patients concluded that among 29 trials of systemic corticosteroids, 25 were inconclusive and four were associated with harm [3]. Also, the recent WHO guidelines disapprove the use of corticosteroids as they are ‘‘of unproven benefit and potentially harmful’’ for patients with H1N1 infection. Therefore, the use of corticosteroid as adjunctive therapy for patients with severe H1N1 infection should be viewed as experimental and with extreme caution. Therefore, we believe that according to the current rules from the International Committee of Medical Journal Editors, patients included in an evaluation of the potential benefits of corticosteroids as adjunctive therapy in H1N1 influenza A virus-associated acute lung injury should have been asked to give written informed-consent [1]. Even in the event of the use of corticosteroids as a rescue therapy for refractory or persistent ARDS, close supervision to identify potential harms frequently associated with corticosteroids should have been implemented. The present study has additional methodological shortcomings, namely a very small sample size of proven H1N1 infection; only eight patients! The small sample size and the lack of a control group (not treated with corticosteroids) preclude any sound conclusion on the hypothetical benefits of this therapy in H1N1 infection. Moreover, although the authors state that their mortality rate was low (15%), it is actually similar to the rates reported by the Canadian [4] and ANZICS [5] cohorts, where barely half of the patients received corticosteroids. In conclusion, we believe that data from this small case series from Quispe-Laime et al. [1] is, at best, a hypothesis-generating one and should not be translated into clinical practice. The assessment of the hypothetical beneficial role of corticosteroids in H1N1 infection should be done with a more careful methodology. This will avoid unnecessary risk and harm to highly susceptible patients.