The Association Between Prepandemic ICU Performance and Mortality Variation in COVID-19: A Multicenter Cohort Study of 35,619 Critically Ill Patients

BACKGROUND

During the COVID-19 pandemic, ICUs remained under stress and observed elevated mortality rates and high variations of outcomes. A knowledge gap exists regarding whether an ICU performing best during nonpandemic times would still perform better when under high pressure compared with the least performing ICUs.

RESEARCH QUESTION

Does prepandemic ICU performance explain the risk-adjusted mortality variability for critically ill patients with COVID-19?

STUDY DESIGN AND METHODS

This study examined a cohort of adults with real-time polymerase chain reaction-confirmed COVID-19 admitted to 156 ICUs in 35 hospitals from February 16, 2020, through December 31, 2021, in Brazil. We evaluated crude and adjusted in-hospital mortality variability of patients with COVID-19 in the ICU during the pandemic. Association of baseline (prepandemic) ICU performance and in-hospital mortality was examined using a variable life-adjusted display (VLAD) during the pandemic and a multivariable mixed regression model adjusted by clinical characteristics, interaction of performance with the year of admission, and mechanical ventilation at admission.

RESULTS

Thirty-five thousand six hundred nineteen patients with confirmed COVID-19 were evaluated. The median age was 52 years, median Simplified Acute Physiology Score 3 was 42, and 18% underwent invasive mechanical ventilation. In-hospital mortality was 13% and 54% for those receiving invasive mechanical ventilation. Adjusted in-hospital mortality ranged from 3.6% to 63.2%. VLAD in the most efficient ICUs was higher than the overall median in 18% of weeks, whereas VLAD was 62% and 84% in the underachieving and least efficient groups, respectively. The least efficient baseline ICU performance group was associated independently with increased mortality (OR, 2.30; 95% CI, 1.45-3.62) after adjusting for patient characteristics, disease severity, and pandemic surge.

INTERPRETATION

ICUs caring for patients with COVID-19 presented substantial variation in risk-adjusted mortality. ICUs with better baseline (prepandemic) performance showed reduced mortality and less variability. Our findings suggest that achieving ICU efficiency by targeting improvement in organizational aspects of ICUs may impact outcomes, and therefore should be a part of the preparedness for future pandemics.

Development and validation of a machine learning model to predict the use of renal replacement therapy in 14,374 patients with COVID-19

PURPOSE

To develop a model to predict the use of renal replacement therapy (RRT) in COVID-19 patients.

MATERIALS AND METHODS

Retrospective analysis of multicenter cohort of intensive care unit (ICU) admissions of Brazil involving COVID-19 critically adult patients, requiring ventilatory support, admitted to 126 Brazilian ICUs, from February 2020 to December 2021 (development) and January to May 2022 (validation). No interventions were performed.

RESULTS

Eight machine learning models' classifications were evaluated. Models were developed using an 80/20 testing/train split ratio and cross-validation. Thirteen candidate predictors were selected using the Recursive Feature Elimination (RFE) algorithm. Discrimination and calibration were assessed. Temporal validation was performed using data from 2022. Of 14,374 COVID-19 patients with initial respiratory support, 1924 (13%) required RRT. RRT patients were older (65 [53-75] vs. 55 [42-68]), had more comorbidities (Charlson's Comorbidity Index 1.0 [0.00-2.00] vs 0.0 [0.00-1.00]), had higher severity (SAPS-3 median: 61 [51-74] vs 48 [41-58]), and had higher in-hospital mortality (71% vs 22%) compared to non-RRT. Risk factors for RRT, such as Creatinine, Glasgow Coma Scale, Urea, Invasive Mechanical Ventilation, Age, Chronic Kidney Disease, Platelets count, Vasopressors, Noninvasive Ventilation, Hypertension, Diabetes, modified frailty index (mFI) and Gender, were identified. The best discrimination and calibration were found in the Random Forest (AUC [95%CI]: 0.78 [0.75-0.81] and Brier's Score: 0.09 [95%CI: 0.08-0.10]). The final model (Random Forest) showed comparable performance in the temporal validation (AUC [95%CI]: 0.79 [0.75-0.84] and Brier's Score, 0.08 [95%CI: 0.08-0.1]).

CONCLUSIONS

An early ML model using easily available clinical and laboratory data accurately predicted the use of RRT in critically ill patients with COVID-19. Our study demonstrates that using ML techniques is feasible to provide early prediction of use of RRT in COVID-19 patients.

Biomarkers: Are They Useful in Severe Community-Acquired Pneumonia?

Community acquired pneumonia (CAP) is a prevalent infectious disease often requiring hospitalization, although its diagnosis remains challenging as there is no gold standard test. In severe CAP, clinical and radiologic criteria have poor sensitivity and specificity, and microbiologic documentation is usually delayed and obtained in less than half of sCAP patients. Biomarkers could be an alternative for diagnosis, treatment monitoring and establish resolution. Beyond the existing evidence about biomarkers as an adjunct diagnostic tool, most evidence comes from studies including CAP patients in primary care or emergency departments, and not only sCAP patients. Ideally, biomarkers used in combination with signs, symptoms, and radiological findings can improve clinical judgment to confirm or rule out CAP diagnosis, and may be valuable adjunctive tools for risk stratification, differentiate viral pneumonia and monitoring the course of CAP. While no single biomarker has emerged as an ideal one, CRP and PCT have gathered the most evidence. Overall, biomarkers offer valuable information and can enhance clinical decision-making in the management of CAP, but further research and validation are needed to establish their optimal use and clinical utility.

Challenges for a broad international implementation of the current severe community-acquired pneumonia guidelines

Severe community-acquired pneumonia (sCAP) remains one of the leading causes of admission to the intensive care unit, thus consuming a large share of resources and is associated with high mortality rates worldwide. The evidence generated by clinical studies in the last decade was translated into recommendations according to the first published guidelines focusing on severe community-acquired pneumonia. Despite the advances proposed by the present guidelines, several challenges preclude the prompt implementation of these diagnostic and therapeutic measures. The present article discusses the challenges for the broad implementation of the sCAP guidelines and proposes solutions when applicable.

ICU registries: From tracking to fostering better outcomes

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National ICU Registries as Enablers of Clinical Research and Quality Improvement

OBJECTIVES

Clinical quality registries (CQRs) have been implemented worldwide by several medical specialties aiming to generate a better characterization of epidemiology, treatments, and outcomes of patients. National ICU registries were created almost 3 decades ago to improve the understanding of case-mix, resource use, and outcomes of critically ill patients. This narrative review describes the challenges, proposed solutions, and evidence generated by National ICU registries as facilitators for research and quality improvement.

DATA SOURCES

English language articles were identified in PubMed using phrases related to ICU registries, CQRs, outcomes, and case-mix.

STUDY SELECTION

Original research, review articles, letters, and commentaries, were considered.

DATA EXTRACTION

Data from relevant literature were identified, reviewed, and integrated into a concise narrative review.

DATA SYNTHESIS

CQRs have been implemented worldwide by several medical specialties aiming to generate a better characterization of epidemiology, treatments, and outcomes of patients. National ICU registries were created almost 3 decades ago to improve the understanding of case-mix, resource use, and outcomes of critically ill patients. The initial experience in European countries and in Oceania ensured that through locally generated data, ICUs could assess their performances by using risk-adjusted measures and compare their results through fair and validated benchmarking metrics with other ICUs contributing to the CQR. The accomplishment of these initiatives, coupled with the increasing adoption of information technology, resulted in a broad geographic expansion of CQRs as well as their use in quality improvement studies, clinical trials as well as international comparisons, and benchmarking for ICUs.

CONCLUSIONS

ICU registries have provided increased knowledge of case-mix and outcomes of ICU patients based on real-world data and contributed to improve care delivery through quality improvement initiatives and trials. Recent increases in adoption of new technologies (i.e., cloud-based structures, artificial intelligence, machine learning) will ensure a broader and better use of data for epidemiology, healthcare policies, quality improvement, and clinical trials.

Subsyndromal Delirium in Critically Ill Patients-Cognitive and Functional Long-Term Outcomes

Subsyndromal delirium (SSD) in the Intensive Care Unit (ICU) is associated with an increased morbidity with unknown post-discharge functional and cognitive outcomes. We performed a prospective multicenter study to analyze the mental status of patients during their first 72 h after ICU admission and its trajectory, with follow-ups at 3 and 6 months after hospital discharge. Amongst the 106 included patients, SSD occurred in 24.5% (n = 26) and was associated with the duration of mechanical ventilation (p = 0.003) and the length of the ICU stay (p = 0.002). After the initial 72 h, most of the SSD patients (30.8%) improved and no longer had SSD; 19.2% continued to experience SSD and one patient (3.8%) progressed to delirium. The post-hospital discharge survival rate for the SSD patients was 100% at 3 months and 87.5% at 6 months. At admission, 96.2% of the SSD patients were fully independent in daily living activities, 66.7% at 3-month follow-up, and 100% at 6-month follow-up. Most SSD patients demonstrated a cognitive decline from admission to 3-month follow-up and improved at 6 months (IQCODE-SF: admission 3.13, p < 0.001; 3 months 3.41, p = 0.019; 6 months 3.19, p = 0.194). We concluded that early SSD is associated with worse outcomes, mainly a transitory cognitive decline after hospital discharge at 3 months, with an improvement at 6 months. This highlights the need to prevent and identify this condition during ICU stays.

Trends in Intensive Care Admissions and Outcomes of Stroke Patients Over 10 Years in Brazil: Impact of the COVID-19 Pandemic

BACKGROUND

The coronavirus 2019 (COVID-19) pandemic affected stroke care worldwide. Data from low- and middle-income countries are limited.

RESEARCH QUESTION

What was the impact of the pandemic in ICU admissions and outcomes of patients with stroke, in comparison with trends over the last 10 years?

STUDY DESIGN AND METHODS

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 10 years; analysis of variable life-adjusted display (VLAD) during 2020; and a mixed-effects multivariable logistic regression model.

RESULTS

A total of 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 with 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 with 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 of age or younger, as compared with 2019.

INTERPRETATION

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.

Incidence, risk and impact of ICU readmission on patient outcomes and resource utilisation in tertiary level ICUs in Nepal: A cohort study

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.

Impact of Subsyndromal Delirium Occurrence and Its Trajectory during ICU Stay

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.

Incidence, risk and impact of unplanned ICU readmission on patient outcomes and resource utilisation in tertiary level ICUs in Nepal: A cohort study

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.

The resilient intensive care unit

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.

Hospital Length of Stay and 30-Day Mortality Prediction in Stroke: A Machine Learning Analysis of 17,000 ICU Admissions in Brazil

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.

What Is the Role of Steroids for Septic Shock in 2021?

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.

Evolving changes in mortality of 13,301 critically ill adult patients with COVID-19 over 8 months

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 27^th and October 28^th, 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.

A systematic review and meta-analysis of propofol versus midazolam sedation in adult intensive care (ICU) patients

PURPOSE

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.

METHODS

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).

RESULTS

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] p < 0.00001, 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] p < 0.0001, 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.

CONCLUSIONS

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.

Clinical course and outcomes of critically ill patients with COVID-19 infection: a systematic review

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.

Systemic Severity and Organ Dysfunction in Subarachnoid Hemorrhage: A Large Retrospective Multicenter Cohort Study

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.

Linking of global intensive care (LOGIC): An international benchmarking in critical care initiative

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.

Trends in clinical profiles, organ support use and outcomes of patients with cancer requiring unplanned ICU admission: a multicenter cohort study

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.

Structure and process associated with the efficiency of intensive care units in low-resource settings: An analysis of the CHECKLIST-ICU trial database

PURPOSE

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.

MATERIALS AND METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Identification of distinct clinical phenotypes in mechanically ventilated patients with acute brain dysfunction using cluster analysis

Acute brain dysfunction (ABD) is a frequent and severe syndrome occurring in critically ill patients and early identification of high-risk patients is paramount. In the present analysis, we propose a clinically applicable model for early phenotype identification of ABD at the bedside in mechanically ventilated patients, improving the recognition of patients with prolonged ABD.Prospective cohort with 629 mechanically ventilated patients in two medical-surgical intensive care units at academic centers. We applied cluster analysis to identify phenotypes using clinical and biological data. We then tested the association of phenotypes and its respective clinical outcomes. We performed a validation on a new cohort of patients select on subsequent patients admitted to the participants intensive care units.A model with 3 phenotypes best described the study population. A 4-variable model including medical admission, sepsis diagnosis, simplified acute physiologic score II and basal serum C-reactive protein (CRP) accurately classified each phenotype (area under curve 0.82; 95% CI, 0.79-0.86). Phenotype A had the shorter duration of ABD (median, 1 day), while phenotypes B and C had progressively longer duration of ABD (median, 3 and 6 days, respectively; P < .0001). There was an association between the duration of ABD and the baseline CRP levels and simplified acute physiology score II score (sensitivity and specificity of 80%). To increase the sensitivity of the model, we added CRP kinetics. By day 1, a CRP < 1.0 times the initial level was associated with a shorter duration of ABD (specificity 0.98).A model based on widely available clinical variables could provide phenotypes associated with the duration of ABD. Phenotypes with longer duration of ABD (phenotypes B and C) are characterized by more severe inflammation and by significantly worse clinical outcomes.

ICU staffing feature phenotypes and their relationship with patients' outcomes: an unsupervised machine learning analysis

PURPOSE

To study whether ICU staffing features are associated with improved hospital mortality, ICU length of stay (LOS) and duration of mechanical ventilation (MV) using cluster analysis directed by machine learning.

METHODS

The following variables were included in the analysis: average bed to nurse, physiotherapist and physician ratios, presence of 24/7 board-certified intensivists and dedicated pharmacists in the ICU, and nurse and physiotherapist autonomy scores. Clusters were defined using the partition around medoids method. We assessed the association between clusters and hospital mortality using logistic regression and with ICU LOS and MV duration using competing risk regression.

RESULTS

Analysis included data from 129,680 patients admitted to 93 ICUs (2014-2015). Three clusters were identified. The features distinguishing between the clusters were: the presence of board-certified intensivists in the ICU 24/7 (present in Cluster 3), dedicated pharmacists (present in Clusters 2 and 3) and the extent of nurse autonomy (which increased from Clusters 1 to 3). The patients in Cluster 3 exhibited the best outcomes, with lower adjusted hospital mortality [odds ratio 0.92 (95% confidence interval (CI), 0.87-0.98)], shorter ICU LOS [subhazard ratio (SHR) for patients surviving to ICU discharge 1.24 (95% CI 1.22-1.26)] and shorter durations of MV [SHR for undergoing extubation 1.61(95% CI 1.54-1.69)]. Cluster 1 had the worst outcomes.

CONCLUSION

Patients treated in ICUs combining 24/7 expert intensivist coverage, a dedicated pharmacist and nurses with greater autonomy had the best outcomes. All of these features represent achievable targets that should be considered by policy makers with an interest in promoting equal and optimal ICU care.

Factors associated with mortality in severe community-acquired pneumonia: A multicenter cohort study

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.

Role of organisational factors on the 'weekend effect' in critically ill patients in Brazil: a retrospective cohort analysis

INTRODUCTION

Higher mortality for patients admitted to intensive care units (ICUs) during the weekends has been occasionally reported with conflicting results that could be related to organisational factors. We investigated the effects of ICU organisational and staffing patterns on the potential association between weekend admission and outcomes in critically ill patients.

METHODS

We included 59 614 patients admitted to 78 ICUs participating during 2013. We defined 'weekend admission' as any ICU admission from Friday 19:00 until Monday 07:00. We assessed the association between weekend admission with hospital mortality using a mixed logistic regression model controlling for both patient-level (illness severity, age, comorbidities, performance status and admission type) and ICU-level (decrease in nurse/bed ratio on weekend, full-time intensivist coverage, use of checklists on weekends and number of institutional protocols) confounders. We performed secondary analyses in the subgroup of scheduled surgical admissions.

RESULTS

A total of 41 894 patients (70.3%) were admitted on weekdays and 17 720 patients (29.7%) on weekends. In univariable analysis, weekend admitted patients had higher ICU (10.9% vs 9.0%, P<0.001) and hospital (16.5% vs 13.5%, P<0.001) mortality. After adjusting for confounders, weekend admission was not associated with higher hospital mortality (OR 1.05, 95% CI 0.99 to 1.12, P=0.095). However, a 'weekend effect' was still observed in scheduled surgical admissions, as well as in ICUs not using checklists during the weekends. For unscheduled admissions, no 'weekend effect' was observed regardless of ICU's characteristics. For scheduled surgical admissions, a 'weekend effect' was present only in ICUs with a low number of implemented protocols and those with a reduction in the nurse/bed ratio and not applying checklists during weekends.

CONCLUSIONS

ICU organisational factors, such as decreased nurse-to-patient ratio, absence of checklists and fewer standardised protocols, may explain, in part, increases in mortality in patients admitted to the ICU mortality on weekends.

The intensive care delirium research agenda: a multinational, interprofessional perspective

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.

Outcomes of subsyndromal delirium in ICU: a systematic review and meta-analysis

Background

Subsyndromal delirium (SSD) is a frequent condition and has been commonly described as an intermediate stage between delirium and normal cognition. However, the true frequency of SSD and its impact on clinically relevant outcomes in the intensive care unit (ICU) remains unclear.

Methods

We performed a systematic search in PubMed, Embase, CINAHL, Cochrane Library, and PsychINFO, with no language restrictions, up to 1 October 2016 to identify publications that evaluated SSD in ICU patients.

Results

The six eligible studies were evaluated. SSD was present in 950 (36%) patients. Four studies evaluated only surgical patients. Four studies used the Intensive Care Delirium Screening Checklist (ICDSC) and two used the Confusion Assessment Method (CAM) score to diagnose SSD. The meta-analysis showed an increased hospital length of stay (LOS) in SSD patients (0.31, 0.12–0.51, p = 0.002; I² = 34%). Hospital mortality was described in two studies but it was not significant (hazard ratio 0.97, 0.61–1.55, p = 0.90 and 5% vs 9%, p = 0.05). The use of antipsychotics in SSD patients to prevent delirium was evaluated in two studies but it did not modify ICU LOS (6.5 (4–8) vs 7 (4–9) days, p = 0.66 and 2 (2–3) vs 3 (2–3) days, p = 0.517) or mortality (9 (26.5%) vs 7 (20.6%), p = 0.55).

Conclusions

SSD occurs in one-third of the ICU patients and has limited impact on the outcomes. The current literature concerning SSD is composed of small-sample studies with methodological differences, impairing a clear conclusion about the association between SSD and progression to delirium or worse ICU clinical outcomes.

Electronic supplementary material

The online version of this article (doi:10.1186/s13054-017-1765-3) contains supplementary material, which is available to authorized users.

Outcomes in Critically Ill Patients with Cancer-Related Complications

INTRODUCTION

Cancer patients are at risk for severe complications related to the underlying malignancy or its treatment and, therefore, usually require admission to intensive care units (ICU). Here, we evaluated the clinical characteristics and outcomes in this subgroup of patients.

MATERIALS AND METHODS

Secondary analysis of two prospective cohorts of cancer patients admitted to ICUs. We used multivariable logistic regression to identify variables associated with hospital mortality.

RESULTS

Out of 2,028 patients, 456 (23%) had cancer-related complications. Compared to those without cancer-related complications, they more frequently had worse performance status (PS) (57% vs 36% with PS≥2), active malignancy (95% vs 58%), need for vasopressors (45% vs 34%), mechanical ventilation (70% vs 51%) and dialysis (12% vs 8%) (P<0.001 for all analyses). ICU (47% vs. 27%) and hospital (63% vs. 38%) mortality rates were also higher in patients with cancer-related complications (P<0.001). Chemo/radiation therapy-induced toxicity (6%), venous thromboembolism (5%), respiratory failure (4%), gastrointestinal involvement (3%) and vena cava syndrome (VCS) (2%) were the most frequent cancer-related complications. In multivariable analysis, the presence of cancer-related complications per se was not associated with mortality [odds ratio (OR) = 1.25 (95% confidence interval, 0.94-1.66), P = 0.131]. However, among the individual cancer-related complications, VCS [OR = 3.79 (1.11-12.92), P = 0.033], gastrointestinal involvement [OR = 3.05 (1.57-5.91), P = <0.001] and respiratory failure [OR = 1.96(1.04-3.71), P = 0.038] were independently associated with in-hospital mortality.

CONCLUSIONS

The prognostic impact of cancer-related complications was variable. Although some complications were associated with worse outcomes, the presence of an acute cancer-related complication per se should not guide decisions to admit a patient to ICU.