Assessment of the effectiveness of tocilizumab on mortality and progression to mechanical ventilation or intensive care in patients with COVID-19 admitted to a tertiary hospital

OBJECTIVES

The evidence for tocilizumab in the treatment of COVID-19 is contradictory, with some clinical trials showing benefits in regard to progression to mechanical ventilation (MV) and/or mortality. The aim of this study is to evaluate in real clinical practice the effectiveness of tocilizumab in treating COVID-19 and to identify prognostic factors for patient outcomes.

METHODS

This was an observational, retrospective study of COVID-19 patients treated with tocilizumab between March 2020 and February 2021 in a tertiary hospital. Variables were demographics, comorbidities, vital signs, analytical parameters, COVID-19 treatment, progression to MV, intensive care unit (ICU) admission, hospital stay, and mortality.

RESULTS

A total of 685 patients (64.7% men, median 68 years) were included. Overall mortality was 23.4% (14.2% in the first 14 days post-tocilizumab) and 93.3% in patients with MV and/or in the ICU at 14 days post-tocilizumab. In addition, 61.5% of discharges occurred during the same period. In patients who died, statistically significant differences were observed in the baseline analytical parameters of C-reactive protein (CRP), D-dimer and higher lactate dehydrogenase (LDH) (p<0.05).

CONCLUSIONS

In most patients the clinical results of tocilizumab were observed at 14 days post-administration and could benefit from earlier administration of treatment. Baseline levels of CRP, D-dimer and LDH could be prognostic factors for the evolution of the COVID-19 patient.

Trends in ICU Mortality From Coronavirus Disease 2019: A Tale of Three Surges

OBJECTIVES

To determine the association between time period of hospitalization and hospital mortality among critically ill adults with coronavirus disease 2019.

DESIGN

Observational cohort study from March 6, 2020, to January 31, 2021.

SETTING

ICUs at four hospitals within an academic health center network in Atlanta, GA.

PATIENTS

Adults greater than or equal to 18 years with coronavirus disease 2019 admitted to an ICU during the study period (i.e., Surge 1: March to April, Lull 1: May to June, Surge 2: July to August, Lull 2: September to November, Surge 3: December to January).

MEASUREMENTS AND MAIN RESULTS

Among 1,686 patients with coronavirus disease 2019 admitted to an ICU during the study period, all-cause hospital mortality was 29.7%. Mortality differed significantly over time: 28.7% in Surge 1, 21.3% in Lull 1, 25.2% in Surge 2, 30.2% in Lull 2, 34.7% in Surge 3 (p = 0.007). Mortality was significantly associated with 1) preexisting risk factors (older age, race, ethnicity, lower body mass index, higher Elixhauser Comorbidity Index, admission from a nursing home); 2) clinical status at ICU admission (higher Sequential Organ Failure Assessment score, higher d-dimer, higher C-reactive protein); and 3) ICU interventions (receipt of mechanical ventilation, vasopressors, renal replacement therapy, inhaled vasodilators). After adjusting for baseline and clinical variables, there was a significantly increased risk of mortality associated with admission during Lull 2 (relative risk, 1.37 [95% CI = 1.03-1.81]) and Surge 3 (relative risk, 1.35 [95% CI = 1.04-1.77]) as compared to Surge 1.

CONCLUSIONS

Despite increased experience and evidence-based treatments, the risk of death for patients admitted to the ICU with coronavirus disease 2019 was highest during the fall and winter of 2020. Reasons for this increased mortality are not clear.

Trends and Risk Factors of In-Hospital Mortality of Patients with COVID-19 in Germany: Results of a Large Nationwide Inpatient Sample

Unselected data of nationwide studies of hospitalized patients with COVID-19 are still sparse, but these data are of outstanding interest to avoid exceeding hospital capacities and overloading national healthcare systems. Thus, we sought to analyze seasonal/regional trends, predictors of in-hospital case-fatality, and mechanical ventilation (MV) in patients with COVID-19 in Germany. We used the German nationwide inpatient samples to analyze all hospitalized patients with a confirmed COVID-19 diagnosis in Germany between 1 January and 31 December in 2020. We analyzed data of 176,137 hospitalizations of patients with confirmed COVID-19-infection. Among those, 31,607 (17.9%) died, whereby in-hospital case-fatality grew exponentially with age. Overall, age ≥ 70 years (OR 5.91, 95%CI 5.70–6.13, p < 0.001), pneumonia (OR 4.58, 95%CI 4.42–4.74, p < 0.001) and acute respiratory distress syndrome (OR 8.51, 95%CI 8.12–8.92, p < 0.001) were strong predictors of in-hospital death. Most COVID-19 patients were treated in hospitals in urban areas (n = 92,971) associated with the lowest case-fatality (17.5%), as compared to hospitals in suburban (18.3%) or rural areas (18.8%). MV demand was highest in November/December 2020 (32.3%, 20.3%) in patients between the 6th and 8th age decade. In the first age decade, 78 of 1861 children (4.2%) with COVID-19-infection were treated with MV, and five of them died (0.3%). The results of our study indicate seasonal and regional variations concerning the number of COVID-19 patients, necessity of MV, and case fatality in Germany. These findings may help to ensure the flexible allocation of intensive care (human) resources, which is essential for managing enormous societal challenges worldwide to avoid overloaded regional healthcare systems.

Using data envelopment analysis to perform benchmarking in intensive care units

BACKGROUND

Studies using Data Envelopment Analysis to benchmark Intensive Care Units (ICUs) are scarce. Previous studies have focused on comparing efficiency using only performance metrics, without accounting for resources. Hence, we aimed to perform a benchmarking analysis of ICUs using data envelopment analysis.

METHODS

We performed a retrospective analysis on observational data of patients admitted to ICUs in Brazil (ORCHESTRA Study). The outputs in our data envelopment analysis model were the performance metrics: Standardized Mortality Ratio (SMR) and Standardized Resource Use (SRU); whereas the inputs consisted of three groups of variables that represented staffing patterns, structure, and strain, thus resulting in three models. We compared efficient and non-efficient units for each model. In addition, we compared our results to the efficiency matrix method and presented targets to each non-efficient unit.

RESULTS

We performed benchmarking in 93 ICUs and 129,680 patients. The median age was 64 years old, and mortality was 12%. Median SMR was 1.00 [interquartile range (IQR): 0.79-1.21] and SRU was 1.15 [IQR: 0.95-1.56]. Efficient units presented lower median physicians per bed ratio (1.44 [IQR: 1.18-1.88] vs. 1.7 [IQR: 1.36-2.00]) and nursing workload (168 hours [IQR: 168-291] vs 396 hours [IQR: 336-672]) but higher nurses per bed ratio (2.02 [1.16-2.48] vs. 1.71 [1.43-2.36]) compared to non-efficient units. Units from for-profit hospitals and specialized ICUs presented the best efficiency scores. Our results were mostly in line with the efficiency matrix method: the efficiency units in our models were mostly in the "most efficient" quadrant.

CONCLUSION

Data envelopment analysis provides managers the information needed to identify not only the outcomes to be achieved but what are the levels of resources needed to provide efficient care. Different perspectives can be achieved depending on the chosen variables. Its use jointly with the efficiency matrix can provide deeper understanding of ICU performance and efficiency.

Lessons learned from the rapid development of a statewide simulation model for predicting COVID-19's impact on healthcare resources and capacity

The first case of COVID-19 was detected in North Carolina (NC) on March 3, 2020. By the end of April, the number of confirmed cases had soared to over 10,000. NC health systems faced intense strain to support surging intensive care unit admissions and avert hospital capacity and resource saturation. Forecasting techniques can be used to provide public health decision makers with reliable data needed to better prepare for and respond to public health crises. Hospitalization forecasts in particular play an important role in informing pandemic planning and resource allocation. These forecasts are only relevant, however, when they are accurate, made available quickly, and updated frequently. To support the pressing need for reliable COVID-19 data, RTI adapted a previously developed geospatially explicit healthcare facility network model to predict COVID-19's impact on healthcare resources and capacity in NC. The model adaptation was an iterative process requiring constant evolution to meet stakeholder needs and inform epidemic progression in NC. Here we describe key steps taken, challenges faced, and lessons learned from adapting and implementing our COVID-19 model and coordinating with university, state, and federal partners to combat the COVID-19 epidemic in NC.

Lower blood pH as a strong prognostic factor for fatal outcomes in critically ill COVID-19 patients at an intensive care unit: A multivariable analysis

BACKGROUND

Data of critically ill COVID-19 patients are being evaluated worldwide, not only to understand the various aspects of the disease and to refine treatment strategies but also to improve clinical decision-making. For clinical decision-making in particular, prognostic factors of a lethal course of the disease would be highly relevant.

METHODS

In this retrospective cohort study, we analyzed the first 59 adult critically ill Covid-19 patients treated in one of the intensive care units of the University Medical Center Regensburg, Germany. Using uni- and multivariable regression models, we extracted a set of parameters that allowed for prognosing in-hospital mortality.

RESULTS

Within the cohort, 19 patients died (mortality 32.2%). Blood pH value, mean arterial pressure, base excess, troponin, and procalcitonin were identified as highly significant prognostic factors of in-hospital mortality. However, no significant differences were found for other parameters expected to be relevant prognostic factors, like low arterial partial pressure of oxygen or high lactate levels. In the multivariable logistic regression analysis, the pH value and the mean arterial pressure turned out to be the most influential prognostic factors for a lethal course.

Using machine learning for predicting intensive care unit resource use during the COVID-19 pandemic in Denmark

The COVID-19 pandemic has put massive strains on hospitals, and tools to guide hospital planners in resource allocation during the ebbs and flows of the pandemic are urgently needed. We investigate whether machine learning (ML) can be used for predictions of intensive care requirements a fixed number of days into the future. Retrospective design where health Records from 42,526 SARS-CoV-2 positive patients in Denmark was extracted. Random Forest (RF) models were trained to predict risk of ICU admission and use of mechanical ventilation after n days (n = 1, 2, …, 15). An extended analysis was provided for n = 5 and n = 10. Models predicted n-day risk of ICU admission with an area under the receiver operator characteristic curve (ROC-AUC) between 0.981 and 0.995, and n-day risk of use of ventilation with an ROC-AUC between 0.982 and 0.997. The corresponding n-day forecasting models predicted the needed ICU capacity with a coefficient of determination (R2) between 0.334 and 0.989 and use of ventilation with an R2 between 0.446 and 0.973. The forecasting models performed worst, when forecasting many days into the future (for large n). For n = 5, ICU capacity was predicted with ROC-AUC 0.990 and R2 0.928, and use of ventilator was predicted with ROC-AUC 0.994 and R2 0.854. Random Forest-based modelling can be used for accurate n-day forecasting predictions of ICU resource requirements, when n is not too large.

Efficacy and safety of direct-acting oral anticoagulants compared to vitamin K antagonists in COVID-19 outpatients with cardiometabolic diseases

BACKGROUND

It remains uncertain if prior use of oral anticoagulants (OACs) in COVID-19 outpatients with multimorbidity impacts prognosis, especially if cardiometabolic diseases are present. Clinical outcomes 30-days after COVID-19 diagnosis were compared between outpatients with cardiometabolic disease receiving vitamin K antagonist (VKA) or direct-acting OAC (DOAC) therapy at time of COVID-19 diagnosis.

METHODS

A study was conducted using TriNetX, a global federated health research network. Adult outpatients with cardiometabolic disease (i.e. diabetes mellitus and any disease of the circulatory system) treated with VKAs or DOACs at time of COVID-19 diagnosis between 20-Jan-2020 and 15-Feb-2021 were included. Propensity score matching (PSM) was used to balance cohorts receiving VKAs and DOACs. The primary outcomes were all-cause mortality, intensive care unit (ICU) admission/mechanical ventilation (MV) necessity, intracranial haemorrhage (ICH)/gastrointestinal bleeding, and the composite of any arterial or venous thrombotic event(s) at 30-days after COVID-19 diagnosis.

RESULTS

2275 patients were included. After PSM, 1270 patients remained in the study (635 on VKAs; 635 on DOACs). VKA-treated patients had similar risks and 30-day event-free survival than patients on DOACs regarding all-cause mortality, ICU admission/MV necessity, and ICH/gastrointestinal bleeding. The risk of any arterial or venous thrombotic event was 43% higher in the VKA cohort (hazard ratio 1.43, 95% confidence interval 1.03-1.98; Log-Rank test p = 0.029).

CONCLUSION

In COVID-19 outpatients with cardiometabolic diseases, prior use of DOAC therapy compared to VKA therapy at the time of COVID-19 diagnosis demonstrated lower risk of arterial or venous thrombotic outcomes, without increasing the risk of bleeding.

Relationship between the presence of dedicated doctors in rapid response systems and patient outcome: a multicenter retrospective cohort study

BACKGROUND

Rapid response systems (RRSs) improve patients' safety, but the role of dedicated doctors within these systems remains controversial. We aimed to evaluate patient survival rates and differences in types of interventions performed depending on the presence of dedicated doctors in the RRS.

METHODS

Patients managed by the RRSs of 9 centers in South Korea from January 1, 2016, through December 31, 2017, were included retrospectively. We used propensity score-matched analysis to balance patients according to the presence of dedicated doctors in the RRS. The primary outcome was in-hospital survival. The secondary outcomes were the incidence of interventions performed. A sensitivity analysis was performed with the subgroup of patients diagnosed with sepsis or septic shock.

RESULTS

After propensity score matching, 2981 patients were included per group according to the presence of dedicated doctors in the RRS. The presence of the dedicated doctors was not associated with patients' overall likelihood of survival (hazard ratio for death 1.05, 95% confidence interval [CI] 0.93‒1.20). Interventions, such as arterial line insertion (odds ratio [OR] 25.33, 95% CI 15.12‒42.44) and kidney replacement therapy (OR 10.77, 95% CI 6.10‒19.01), were more commonly performed for patients detected using RRS with dedicated doctors. The presence of dedicated doctors in the RRS was associated with better survival of patients with sepsis or septic shock (hazard ratio for death 0.62, 95% CI 0.39‒0.98) and lower intensive care unit admission rates (OR 0.53, 95% CI 0.37‒0.75).

CONCLUSIONS

The presence of dedicated doctors within the RRS was not associated with better survival in the overall population but with better survival and lower intensive care unit admission rates for patients with sepsis or septic shock.

Prospective validation of an 11-gene mRNA host response score for mortality risk stratification in the intensive care unit

Several clinical calculators predict intensive care unit (ICU) mortality, however these are cumbersome and often require 24 h of data to calculate. Retrospective studies have demonstrated the utility of whole blood transcriptomic analysis in predicting mortality. In this study, we tested prospective validation of an 11-gene messenger RNA (mRNA) score in an ICU population. Whole blood mRNA from 70 subjects in the Stanford ICU Biobank with samples collected within 24 h of Emergency Department presentation were used to calculate an 11-gene mRNA score. We found that the 11-gene score was highly associated with 60-day mortality, with an area under the receiver operating characteristic curve of 0.68 in all patients, 0.77 in shock patients, and 0.98 in patients whose primary determinant of prognosis was acute illness. Subjects with the highest quartile of mRNA scores were more likely to die in hospital (40% vs 7%, p < 0.01) and within 60 days (40% vs 15%, p = 0.06). The 11-gene score improved prognostication with a categorical Net Reclassification Improvement index of 0.37 (p = 0.03) and an Integrated Discrimination Improvement index of 0.07 (p = 0.02) when combined with Simplified Acute Physiology Score 3 or Acute Physiology and Chronic Health Evaluation II score. The test performed poorly in the 95 independent samples collected > 24 h after emergency department presentation. Tests will target a 30-min turnaround time, allowing for rapid results early in admission. Moving forward, this test may provide valuable real-time prognostic information to improve triage decisions and allow for enrichment of clinical trials.

Disentangling the clinical data chaos: User-centered interface system design for trauma centers

This paper presents a year-long study of our project, aiming at (1) understanding the work practices of clinical staff in trauma intensive care units (TICUs) at a trauma center, with respect to their usage of clinical data interface systems, and (2) developing and evaluating an intuitive and user-centered clinical data interface system for their TICU environments. Based on a long-term field study in an urban trauma center that involved observation-, interview-, and survey-based studies to understand our target users and their working environment, we designed and implemented MediSenseView as a working prototype. MediSenseView is a clinical-data interface system, which was developed through the identification of three core challenges of existing interface system use in a trauma care unit-device separation, usage inefficiency, and system immobility-from the perspectives of three staff groups in our target environment (i.e., doctors, clinical nurses and research nurses), and through an iterative design study. The results from our pilot deployment of MediSenseView and a user study performed with 28 trauma center staff members highlight their work efficiency and satisfaction with MediSenseView compared to existing clinical data interface systems in the hospital.

COVID-19: a simple statistical model for predicting intensive care unit load in exponential phases of the disease

One major bottleneck in the ongoing COVID-19 pandemic is the limited number of critical care beds. Due to the dynamic development of infections and the time lag between when patients are infected and when a proportion of them enters an intensive care unit (ICU), the need for future intensive care can easily be underestimated. To infer future ICU load from reported infections, we suggest a simple statistical model that (1) accounts for time lags and (2) allows for making predictions depending on different future growth of infections. We have evaluated our model for three heavily affected regions in Europe, namely Berlin (Germany), Lombardy (Italy), and Madrid (Spain). Before extensive containment measures made an impact, we first estimate the region-specific model parameters, namely ICU rate, time lag between infection, and ICU admission as well as length of stay in ICU. Whereas for Berlin, an ICU rate of 6%, a time lag of 6 days, and a stay of 12 days in ICU provide the best fit of the data, for Lombardy and Madrid the ICU rate was higher (18% and 15%) and the time lag (0 and 3 days) and the stay in ICU (3 and 8 days) shorter. The region-specific models are then used to predict future ICU load assuming either a continued exponential phase with varying growth rates (0-15%) or linear growth. By keeping the growth rates flexible, this model allows for taking into account the potential effect of diverse containment measures. Thus, the model can help to predict a potential exceedance of ICU capacity depending on future growth. A sensitivity analysis for an extended time period shows that the proposed model is particularly useful for exponential phases of the disease.

Liver disease and outcomes among COVID-19 hospitalized patients - A systematic review and meta-analysis

INTRODUCTION AND OBJECTIVES

The coronavirus disease 2019 (COVID-19) pandemic has been a challenge globally. In severe acute respiratory syndrome (SARS) epidemic 60% of patients had hepatic injury, due to phylogenetic similarities of the viruses it is assumed that COVID-19 is associated with acute liver injury. In this meta-analysis, we aim to study the occurrence and association of liver injury, comorbid liver disease and elevated liver enzymes in COVID-19 confirmed hospitalizations with outcomes.

MATERIALS AND METHODS

Data from observational studies describing comorbid chronic liver disease, acute liver injury, elevated aspartate aminotransferase (AST), alanine aminotransferase (ALT) levels and outcomes of COVID-19 hospitalized patients from December 1, 2019, to June 30, 2020 was extracted following PRISMA guidelines. Adverse outcomes were defined as admission to intensive care unit (ICU), oxygen saturation <90%, invasive mechanical ventilation (IMV), severe disease and in-hospital mortality. Odds ratio (OR) and 95% confidence interval (95% CI) were obtained.

RESULTS

24 studies with 12,882 confirmed COVID-19 patients were included. Overall prevalence of CM-CLD was 2.6%, COVID-19-ALI was 26.5%, elevated AST was 41.1% and elevated ALT was 29.1%. CM-CLD had no significant association with poor outcomes (pooled OR: 0.96; 95% CI: 0.71-1.29; p=0.78). COVID-19-ALI (1.68;1.04-2.70; p=0.03), elevated AST (2.98; 2.35-3.77; p<0.00001) and elevated ALT (1.85;1.49-2.29; p<0.00001) were significantly associated with higher odds of poor outcomes.

CONCLUSION

Our meta-analysis suggests that acute liver injury and elevated liver enzymes were significantly associated with COVID-19 severity. Future studies should evaluate changing levels of biomarkers amongst liver disease patients to predict poor outcomes of COVID-19 and causes of liver injury during COVID-19 infection.

Characterization of hospital airborne SARS-CoV-2

BACKGROUND

The mechanism for spread of SARS-CoV-2 has been attributed to large particles produced by coughing and sneezing. There is controversy whether smaller airborne particles may transport SARS-CoV-2. Smaller particles, particularly fine particulate matter (≤ 2.5 µm in diameter), can remain airborne for longer periods than larger particles and after inhalation will penetrate deeply into the lungs. Little is known about the size distribution and location of airborne SARS-CoV-2 RNA.

METHODS

As a measure of hospital-related exposure, air samples of three particle sizes (> 10.0 µm, 10.0-2.5 µm, and ≤ 2.5 µm) were collected in a Boston, Massachusetts (USA) hospital from April to May 2020 (N = 90 size-fractionated samples). Locations included outside negative-pressure COVID-19 wards, a hospital ward not directly involved in COVID-19 patient care, and the emergency department.

RESULTS

SARS-CoV-2 RNA was present in 9% of samples and in all size fractions at concentrations of 5 to 51 copies m-3. Locations outside COVID-19 wards had the fewest positive samples. A non-COVID-19 ward had the highest number of positive samples, likely reflecting staff congregation. The probability of a positive sample was positively associated (r = 0.95, p < 0.01) with the number of COVID-19 patients in the hospital. The number of COVID-19 patients in the hospital was positively associated (r = 0.99, p < 0.01) with the number of new daily cases in Massachusetts.

CONCLUSIONS

More frequent detection of positive samples in non-COVID-19 than COVID-19 hospital areas indicates effectiveness of COVID-ward hospital controls in controlling air concentrations and suggests the potential for disease spread in areas without the strictest precautions. The positive associations regarding the probability of a positive sample, COVID-19 cases in the hospital, and cases in Massachusetts suggests that hospital air sample positivity was related to community burden. SARS-CoV-2 RNA with fine particulate matter supports the possibility of airborne transmission over distances greater than six feet. The findings support guidelines that limit exposure to airborne particles including fine particles capable of longer distance transport and greater lung penetration.

Ventilator-associated pneumonia in critically ill patients with COVID-19

BACKGROUND

Pandemic COVID-19 caused by the coronavirus SARS-CoV-2 has a high incidence of patients with severe acute respiratory syndrome (SARS). Many of these patients require admission to an intensive care unit (ICU) for invasive ventilation and are at significant risk of developing a secondary, ventilator-associated pneumonia (VAP).

OBJECTIVES

To study the incidence of VAP and bacterial lung microbiome composition of ventilated COVID-19 and non-COVID-19 patients.

METHODS

In this retrospective observational study, we compared the incidence of VAP and secondary infections using a combination of microbial culture and a TaqMan multi-pathogen array. In addition, we determined the lung microbiome composition using 16S RNA analysis in a subset of samples. The study involved 81 COVID-19 and 144 non-COVID-19 patients receiving invasive ventilation in a single University teaching hospital between March 15th 2020 and August 30th 2020.

RESULTS

COVID-19 patients were significantly more likely to develop VAP than patients without COVID (Cox proportional hazard ratio 2.01 95% CI 1.14-3.54, p = 0.0015) with an incidence density of 28/1000 ventilator days versus 13/1000 for patients without COVID (p = 0.009). Although the distribution of organisms causing VAP was similar between the two groups, and the pulmonary microbiome was similar, we identified 3 cases of invasive aspergillosis amongst the patients with COVID-19 but none in the non-COVID-19 cohort. Herpesvirade activation was also numerically more frequent amongst patients with COVID-19.

CONCLUSION

COVID-19 is associated with an increased risk of VAP, which is not fully explained by the prolonged duration of ventilation. The pulmonary dysbiosis caused by COVID-19, and the causative organisms of secondary pneumonia observed are similar to that seen in critically ill patients ventilated for other reasons.

Clinical characteristics and outcomes of COVID-19 infected diabetic patients admitted in ICUs of the southern region of Bangladesh

BACKGROUND AND AIMS

Diabetes mellitus is highly prevalent among critical cases of coronavirus disease 2019 (COVID-19) with poor outcomes. This study aimed to describe the clinical characteristics and outcomes of COVID-19 patients with diabetes, admitted in the intensive care unit (ICU) of the southern region of Bangladesh.

METHODS

Epidemiological, clinical, laboratory, treatments, complications, and clinical outcomes data were extracted from electronic medical records of 168 COVID-19 patients admitted into ICU of two COVID-19 dedicated hospitals of Chattogram, Bangladesh and compared between diabetes (n = 88) and non-diabetes (n = 80) groups.

RESULTS

The prevalence of diabetes was high among 51-70 years old patients. All the diabetic patients had at least one other comorbidity, with a significantly higher incidence of hypertension (53.4% vs 27.5%, P < 0.05). Prevalence of male patients (74/88; 84.1%) was slightly higher among diabetic patients than the non-diabetic patients (60/80; 75%). Even though not significant, Kaplan-Meier survival curve showed that COVID-19 patients with diabetes had a shorter overall survival time than those without diabetes. In subgroup analysis, diabetic patients were classified into insulin-requiring and non-insulin-requiring groups based on their requirement of insulin during the stay in ICU. COVID-19 infected diabetic patients requiring insulin have high risk of disease progression and shorter survival time than the non-insulin required group.

CONCLUSIONS

Diabetes is an independent risk factor for the poor prognosis of COVID-19. More attention should be paid to the prevention and prompt treatment of diabetic patients, to maintain good glycaemic control especially those who require insulin therapy.

Hemodynamic and metabolic recovery in acute myocardial infarction-related cardiogenic shock is more rapid among patients presenting with out-of-hospital cardiac arrest

Background

Most studies in acute myocardial infarction complicated by cardiogenic shock (AMICS) include patients presenting with and without out-of-hospital cardiac arrest (OHCA). The aim was to compare OHCA and non-OHCA AMICS patients in terms of hemodynamics, management in the intensive care unit (ICU) and outcome.

Methods

From a cohort corresponding to two thirds of the Danish population, all patients with AMICS admitted from 2010–2017 were individually identified through patient records.

Results

A total of 1716 AMICS patients were identified of which 723 (42%) presented with OHCA. A total of 1532 patients survived to ICU admission. At the time of ICU arrival, there were no differences between OHCA and non-OHCA AMICS patients in variables commonly used in the AMICS definition (mean arterial pressure (MAP) (72mmHg vs 70mmHg, p = 0.12), lactate (4.3mmol/L vs 4.0mmol/L, p = 0.09) and cardiac output (CO) (4.6L/min vs 4.4L/min, p = 0.30)) were observed. However, during the initial days of ICU treatment OHCA patients had a higher MAP despite a lower need for vasoactive drugs, higher CO, SVO2 and lactate clearance compared to non-OHCA patients (p<0.05 for all). In multivariable analysis outcome was similar but cause of death differed significantly with hypoxic brain injury being leading cause in OHCA and cardiac failure in non-OHCA AMICS patients.

Conclusion

OHCA and non-OHCA AMICS patients initially have comparable metabolic and hemodynamic profiles, but marked differences develop between the groups during the first days of ICU treatment. Thus, pooling of OHCA and non-OHCA patients as one clinical entity in studies should be done with caution.

Can bioimpedance cardiography assess hemodynamic response to passive leg raising in critically ill patients: A STROBE-compliant study

Passive leg raising (PLR) is a convenient and reliable test to predict fluid responsiveness. The ability of thoracic electrical bioimpedance cardiography (TEB) to monitor changes of cardiac output (CO) during PLR is unknown.In the present study, we measured CO in 61 patients with shock or dyspnea by TEB and transthoracic echocardiography (TTE) during PLR procedure. Positive PLR responsiveness was defined as the velocity-time integral (VTI) ≥10% after PLR. TTE measured VTI in the left ventricular output tract. The predictive value of TEB parameters in PLR responders was tested. Furthermore, the agreement of absolute CO values between TEB and TTE measurements was assessed.Among the 61 patients, there were 28 PLR-responders and 33 non-responders. Twenty-seven patients were diagnosed with shock and 34 patients with dyspnea, with 55.6% (15/27) and 54.6% (18/34) non-responders, respectively. A change in TEB measured CO (ΔCO) ≥9.8% predicted PLR responders with 75.0% sensitivity and 78.8% specificity, the area under the receiver operating characteristic curve (AUROC) was 0.79. The Δd2Z/dt2 (a secondary derivative of the impedance wave) showed the best predictive value with AUROC of 0.90, the optimal cut point was -7.1% with 85.7% sensitivity and 87.9% specificity. Bias between TEB and TTE measured CO was 0.12 L/min, and the percentage error was 65.8%.TEB parameters had promising performance in predicting PLR responders, and the Δd2Z/dt2 had the best predictive value. The CO values measured by TEB were not interchangeable with TTE in critically ill settings.

Hospital and ICU patient volume per physician at peak of COVID pandemic: State-level estimates

BACKGROUND

In anticipation of patient surge due to COVID-19, many states are working to increase the available healthcare workforce. To help inform state policies and initiatives aimed at physician deployment during COVID-19, we used predictions of peak patient volume for hospitals and intensive care units (ICU) and regional physician workforce estimates to measure patient to physician ratios at the peak of the pandemic for each state.

METHODS

We estimated the number of potentially available physicians based on Medicare Part B billings for the care of hospitalized and critically ill patients in 2017, adjusted for attrition due to exposure to SARS-CoV-2 and relevant experience. We used estimates from the Institute of Health Metrics and Evaluation to determine the number of hospitalized and ICU patients expected at the peak of the pandemic in each state. We then determined the expected ratio of patients per physician for each state at the peak of the pandemic.

RESULTS

The median number of hospitalized patients per physician was 13 (low estimate) to 18 (high estimate). At the high estimate of hospitalized patients, 35 states would have a patient to physician ratio of more than 15:1 (patient to physician ratios above 15:1 have been associated with poor outcomes). For ICU patients, the median number of patients each physician would treat across states would be 8-11 patients. Nine states would experience patient to physician ratios above 15:1 at the higher end of estimates. Patient-physician ratios decreased if the available physician pool was broadened to include physicians without recent experience treating hospitalized patients, and physicians in surgical specialties with experience treating acutely hospitalized patients.

CONCLUSIONS/IMPLICATIONS

We estimate that most states will have sufficient physician capacity to manage hospitalized patients at the peak of the pandemic. However, at the high estimates of hospitalized patients, some Midwestern states will experience high patient to provider ratios that may adversely affect patient outcomes.

LEVEL OF EVIDENCE

State.

Effectiveness of remdesivir in patients with COVID-19 under mechanical ventilation in an Italian ICU

BACKGROUND

Remdesivir is a prodrug with in vitro activity against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Its clinical efficacy in patients with COVID-19 under mechanical ventilation remains to be evaluated.

METHODS

This study includes patients under mechanical ventilation with confirmed SARS-CoV-2 infection admitted to the ICU of Pesaro hospital between 29 February and 20 March 2020. During this period, remdesivir was provided on a compassionate use basis. Clinical characteristics and outcome of patients treated with remdesivir were collected retrospectively and compared with those of patients hospitalized in the same time period.

RESULTS

A total of 51 patients were considered, of which 25 were treated with remdesivir. The median (IQR) age was 67 (59-75.5) years, 92% were men and symptom onset was 10 (8-12) days before admission to ICU. At baseline, there was no significant difference in demographic characteristics, comorbidities and laboratory values between patients treated and not treated with remdesivir. Median follow-up was 52 (46-57) days. Kaplan-Meier curves showed significantly lower mortality among patients who had been treated with remdesivir (56% versus 92%, P < 0.001). Cox regression analysis showed that the Charlson Comorbidity Index was the only factor that had a significant association with higher mortality (OR 1.184; 95% CI 1.027-1.365; P = 0.020), while the use of remdesivir was associated with better survival (OR 3.506; 95% CI 1.768-6.954; P < 0.001).

CONCLUSIONS

In this study the mortality rate of patients with COVID-19 under mechanical ventilation is confirmed to be high. The use of remdesivir was associated with a significant beneficial effect on survival.

Burden of diabetes mellitus and its impact on COVID-19 patients: A meta-analysis of real-world evidence

BACKGROUND & AIMS

Coronavirus disease 2019 (COVID-19) spreads rapidly and within no time, it has been declared a pandemic by the World Health Organization. Evidence suggests diabetes to be a risk factor for the progression and poor prognosis of COVID-19. Therefore, we aimed to understand the pooled prevalence of diabetes in patients infected with COVID-19. We also aimed to compute the risk of mortality and ICU admissions in COVID-19 patients with and without diabetes.

METHODS

A comprehensive literature search was performed in PubMed to identify the articles reporting the diabetes prevalence and risk of mortality or ICU admission in COVID-19 patients. The primary outcome was to compute the pooled prevalence of diabetes in COVID-19 patients. Secondary outcomes included risk of mortality and ICU admissions in COVID-19 patients with diabetes compared to patients without diabetes.

RESULTS

This meta-analysis was based on a total of 23007 patients from 43 studies. The pooled prevalence of diabetes in patients infected with COVID-19 was found to be 15% (95% CI: 12%-18%), p = <0.0001. Mortality risk was found to be significantly higher in COVID-19 patients with diabetes as compared to COVID-19 patients without diabetes with a pooled risk ratio of 1.61 (95% CI: 1.16-2.25%), p = 0.005. Likewise, risk of ICU admission rate was significantly higher in COVID-19 patients with diabetes as compared to COVID-19 patients without diabetes with a pooled risk ratio of 1.88 (1.20%-2.93%), p = 0.006.

CONCLUSION

This meta-analysis found a high prevalence of diabetes and higher mortality and ICU admission risk in COVID-19 patients with diabetes.

The impact of metabolic syndrome on morbidity and mortality among intensive care unit admitted COVID-19 patients

BACKGROUND AND AIMS

Given the limited information describing the connection between metabolic syndrome (MetS) and Coronavirus Disease 2019 (COVID-19), we aimed to assess the impact of MetS on morbidity and mortality among COVID-19 patients.

METHODS

This retrospective cohort study was performed from 1st April to May 3, 2020 on 157 ICU-admitted COVID-19 patients in Shahid Modarres Hospital in Tehran, Iran. Patients' clinical, laboratory and radiological findings, and subsequent complications, were collected and compared between MetS and non-MetS groups.

RESULTS

74 of all cases had MetS. Among the MetS components, waist circumference (p-value = 0.006 for men; p-value<0.0001 for women), Triglycerides (p-value = 0.002), and Fasting Blood Sugar (p-value = 0.007) were significantly higher in MetS group; with no statistical difference found in HDL levels (p-value = 0.21 for men; p-value = 0.13 for women), systolic blood pressure(p-value = 0.07), and diastolic blood pressure (p-value = 0.18) between two groups. Length of ICU admission (p-value = 0.009), the need for invasive mechanical ventilation (p-value = 0.0001), respiratory failure (p-value = 0.0008), and pressure ulcers (p-value = 0.02) were observed significantly more in MetS group. The Odds Ratio (OR) of mortality with 0(OR = 0.3660), 1(OR = 0.5155), 2(OR = 0.5397), 3(OR = 1.9511), 4(OR = 5.7018), and 5(OR = 8.3740) MetS components showed an increased mortality risk as the components' count increased. The patient with BMI>40 (OR = 6.9368) had more odds of fatality comparing to those with BMI>35 (OR = 4.0690) and BMI>30 (OR = 2.5287). Furthermore, the waist circumference (OR = 8.31; p-value<0.0001) and fasting blood sugar (OR = 2.4588; p-value = 0.0245) were obtained by multivariate logistic regression as independent prognostic factors for mortality.

CONCLUSION

The findings suggest a strong relationship between having MetS and increased risk of severe complications and mortality among COVID-19 ICU-admitted patients.

A call for collaboration and consensus on training for endotracheal intubation in the medical intensive care unit

Endotracheal intubation (EI) is a potentially lifesaving but high-risk procedure in critically ill patients. While the ACGME mandates that trainees in pulmonary and critical care medicine (PCCM) achieve competence in this procedure, there is wide variation in EI training across the USA. One study suggests that 40% of the US PCCM trainees feel they would not be proficient in EI upon graduation. This article presents a review of the EI training literature; the recommendations of a national group of PCCM, anesthesiology, emergency medicine, and pediatric experts; and a call for further research, collaboration, and consensus guidelines.

Effect of school closures on mortality from coronavirus disease 2019: old and new predictions

OBJECTIVE

To replicate and analyse the information available to UK policymakers when the lockdown decision was taken in March 2020 in the United Kingdom.

DESIGN

Independent calculations using the CovidSim code, which implements Imperial College London's individual based model, with data available in March 2020 applied to the coronavirus disease 2019 (covid-19) epidemic.

SETTING

Simulations considering the spread of covid-19 in Great Britain and Northern Ireland.

POPULATION

About 70 million simulated people matched as closely as possible to actual UK demographics, geography, and social behaviours.

MAIN OUTCOME MEASURES

Replication of summary data on the covid-19 epidemic reported to the UK government Scientific Advisory Group for Emergencies (SAGE), and a detailed study of unpublished results, especially the effect of school closures.

RESULTS

The CovidSim model would have produced a good forecast of the subsequent data if initialised with a reproduction number of about 3.5 for covid-19. The model predicted that school closures and isolation of younger people would increase the total number of deaths, albeit postponed to a second and subsequent waves. The findings of this study suggest that prompt interventions were shown to be highly effective at reducing peak demand for intensive care unit (ICU) beds but also prolong the epidemic, in some cases resulting in more deaths long term. This happens because covid-19 related mortality is highly skewed towards older age groups. In the absence of an effective vaccination programme, none of the proposed mitigation strategies in the UK would reduce the predicted total number of deaths below 200 000.

CONCLUSIONS

It was predicted in March 2020 that in response to covid-19 a broad lockdown, as opposed to a focus on shielding the most vulnerable members of society, would reduce immediate demand for ICU beds at the cost of more deaths long term. The optimal strategy for saving lives in a covid-19 epidemic is different from that anticipated for an influenza epidemic with a different mortality age profile.

A nationwide study of the long-term prevalence of dementia and its risk factors in the Swedish intensive care cohort

BACKGROUND

Developing dementia is feared by many for its detrimental effects on cognition and independence. Experimental and clinical evidence suggests that sepsis is a risk factor for the later development of dementia. We aimed to investigate whether intensive care-treated sepsis is an independent risk factor for a later diagnosis of dementia in a large cohort of intensive care unit (ICU) patients.

METHODS

We identified adult patients admitted to an ICU in 2005 to 2015 and who survived without a dementia diagnosis 1 year after intensive care admission using the Swedish Intensive Care Registry, collecting data from all Swedish general ICUs. Comorbidity, the diagnosis of dementia and mortality, was retrieved from the Swedish National Patient Registry, the Swedish Dementia Registry, and the Cause of Death Registry. Sepsis during intensive care served as a covariate in an extended Cox model together with age, sex, and variables describing comorbidities and acute disease severity.

RESULTS

One year after ICU admission 210,334 patients were alive and without a diagnosis of dementia; of these, 16,115 (7.7%) had a diagnosis of sepsis during intensive care. The median age of the cohort was 61 years (interquartile range, IQR 43-72). The patients were followed for up to 11 years (median 3.9 years, IQR 1.7-6.6). During the follow-up, 6312 (3%) patients were diagnosed with dementia. Dementia was more common in individuals diagnosed with sepsis during their ICU stay (log-rank p < 0.001), however diagnosis of sepsis during critical care was not an independent risk factor for a later dementia diagnosis in an extended Cox model: hazard ratio (HR) 1.01 (95% confidence interval 0.91-1.11, p = 0.873). Renal replacement therapy and ventilator therapy during the ICU stay were protective. High age was a strong risk factor for later dementia, as was increasing severity of acute illness, although to a lesser extent. However, the severity of comorbidities and the length of ICU and hospital stay were not independent risk factors in the model.

CONCLUSION

Although dementia is more common among patients treated with sepsis in the ICU, sepsis was not an independent risk factor for later dementia in the Swedish national critical care cohort.

TRIAL REGISTRATION

This study was registered a priori with the Australian and New Zeeland Clinical Trials Registry (registration no. ACTRN12618000533291 ).

Improving the ability to predict hospital mortality among adults by combining two status epilepticus outcome scoring tools

OBJECTIVE

The goal of this study was to compare the predictive ability of the Status Epilepticus Severity Score (STESS), the Encephalitis-nonconvulsive status epilepticus (NCSE)-Diazepam resistance-Image abnormalities-Tracheal intubation (END-IT), and the combination of these two scoring tools to predict mortality among inhospital patients with status epilepticus (SE).

METHODS

A retrospective analysis was conducted of adult patients with SE who were admitted to the neurology department, the emergency department, and the intensive care unit from January 2013 to December 2017. The patients were divided into two groups: survivors and nonsurvivors. The STESS data were obtained when the patient arrived at the hospital, and the END-IT data were collected 24 h after patients were initially treated in the hospital. The ability of the scoring tools to predict death in patients with SE, alone or in combination, was evaluated.

RESULTS

A total of 123 patients with SE were included in the study, of which 22 died, for a mortality rate of 17.9%. The STESS and END-IT scores of nonsurvivors were both significantly higher than those of survivors (median STESS 4 vs. 2, p = 0.003; median END-IT 3 vs. 1, p < 0.001). The area under the receiver operating characteristic curve (AUC) was 0.698 for the STESS and 0.852 for the END-IT, and the cutoff values were 4 and 3, respectively. The AUC of the END-IT with the optimal cutoff value was larger than that of the STESS (p = 0.024). The sensitivity and specificity of combining the STESS and END-IT by the serial method (STESS ≥ 4∩END-IT ≥ 3) were 0.50 and 0.95, respectively, and the specificity was significantly higher than the STESS or END-IT (both p's < 0.001). The sensitivity and specificity of combining the STESS and END-IT by the parallel method (STESS ≥ 4⋃END-IT ≥ 3) were 0.91 and 0.53, respectively, and the sensitivity was higher than the STESS was (p = 0.016).

CONCLUSION

Our results indicated that the combined score of the STESS and END-IT systems was a better predictor of survival of patients with SE than the scores of either the STESS system or the END-IT system alone and that combining the scores may be considered to be a new method for early identification of patients for both good and bad outcomes.

Delirium risk prediction models for intensive care unit patients: A systematic review

OBJECTIVE

To systematically review the delirium risk prediction models for intensive care unit (ICU) patients.

METHODS

A systematic review was conducted. The Cochrane Library, PubMed, Ovid and Web of Science were searched to collect studies on delirium risk prediction models for ICU patients from database establishment to 31 March 2019. Two reviewers independently screened the literature according to the pre-determined inclusion and exclusion criteria, extracted the data and evaluated the risk of bias of the included studies using the CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies) checklist. A descriptive analysis was used to describe and summarise the data.

RESULTS

A total of six models were included. All studies reported the area under the receiver operating characteristic curve (AUROC) of the prediction models in the derivation and (or) validation datasets as over 0.7 (from 0.75 to 0.9). Five models reported calibration metrics. Decreased cognitive reserve and the Acute Physiology and Chronic Health Evaluation II (APACHE-II) score were the most commonly reported predisposing and precipitating factors, respectively, of ICU delirium among all models. The small sample size, lack of external validation and the absence of or unreported blinding method increased the risk of bias.

CONCLUSION

According to the discrimination and calibration statistics reported in the original studies, six prediction models may have moderate power in predicting ICU delirium. However, this finding should be interpreted with caution due to the risk of bias in the included studies. More clinical studies should be carried out to validate whether these tools have satisfactory predictive performance in delirium risk prediction for ICU patients.

Effect of Intensivist Communication in a Simulated Setting on Interpretation of Prognosis Among Family Members of Patients at High Risk of Intensive Care Unit Admission: A Randomized Trial

Importance

Discordance about prognosis between a patient's health care decision-making surrogate and the treating intensivist is common in the intensive care unit (ICU). Empowering families, friends, and caregivers of patients who are critically ill to make informed decisions about care is important, but it is unclear how best to communicate prognostic information to surrogates when a patient is expected to die.

Objective

To determine whether family members, who are often health care decision-making surrogates, interpret intensivists as being more optimistic when questions about prognosis in the ICU are answered indirectly.

Design, Setting, and Participants

This web-based randomized trial was conducted between September 27, 2019, and October 17, 2019, among a national sample of adult children, spouses, partners, or siblings of people with chronic obstructive pulmonary disease who were receiving long-term oxygen therapy. Participants were shown video vignettes depicting an intensivist answering a standardized question about the prognosis of a patient at high risk of death on day 3 of ICU admission. Participants were excluded if they had worked as a physician, nurse, or advanced health care practitioner. Data were analyzed from October 18, 2019, to November 12, 2019.

Interventions

Participants were randomized to view 1 of 4 intensivist communication styles in response to the question "What do you think is most likely to happen?": (1) a direct response (control), (2) an indirect response comparing the patient's condition with that of other patients, (3) an indirect response describing the patient's deteriorating physiological condition, or (4) redirection to a discussion of the patient's values and goals.

Main Outcomes and Measures

Participant responses to 2 questions: (1) "If you had to guess, what do you think the doctor thinks is the chance that your loved one will survive this hospitalization?" and (2) "What do you think are the chances that your loved one will survive this hospitalization?" answered using a 0% to 100% probability scale.

Results

Among 302 participants (median [interquartile range] age, 49 [38-59] years; 204 [68%] women) included in the trial, 165 (55%) were adult children of the individual with chronic obstructive pulmonary disease; 77 participants were randomized to view a direct response, 77 participants were randomized to view an indirect response referencing other patients, 68 participants were randomized to view an indirect response referencing physiological condition, and 80 participants were randomized to view a redirection response. Compared with participants who viewed a direct response, participants who viewed an indirect response referencing other patients (β = 10 [95% CI, 1-19]; P = .03), physiological condition (β = 10 [95% CI, 0-19]; P = .04), or redirection to a discussion of the patient's values and goals (β = 19 [95% CI, 10-28]; P < .001) perceived the intensivist to have a significantly more optimistic prognostic estimate.

Conclusions and Relevance

These findings suggest that family members interpret indirect or redirection responses to questions about prognosis in the ICU setting as more optimistic than direct responses.

Trial Registration

ClinicalTrials.gov Identifier: NCT04239209.

Monitoring Patient Respiratory Effort During Mechanical Ventilation: Lung and Diaphragm-Protective Ventilation

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2020. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2020. Further information about the Annual Update in Intensive Care and Emergency Medicine is available from http://www.springer.com/series/8901.

Physiology of the Respiratory Drive in ICU Patients: Implications for Diagnosis and Treatment

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2020. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2020. Further information about the Annual Update in Intensive Care and Emergency Medicine is available from http://www.springer.com/series/8901.

Artificial Intelligence in the Intensive Care Unit

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2020. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2020. Further information about the Annual Update in Intensive Care and Emergency Medicine is available from http://www.springer.com/series/8901.

Postoperative outcomes following pediatric intracranial electrode monitoring: A case for stereoelectroencephalography (SEEG)

BACKGROUND

For patients with medically refractory epilepsy, intracranial electrode monitoring can help identify epileptogenic foci. Despite the increasing utilization of stereoelectroencephalography (SEEG), the relative risks or benefits associated with the technique when compared with the traditional subdural electrode monitoring (SDE) remain unclear, especially in the pediatric population. Our aim was to compare the outcomes of pediatric patients who received intracranial monitoring with SEEG or SDE (grids and strips).

METHODS

We retrospectively studied 38 consecutive pediatric intracranial electrode monitoring cases performed at our institution from 2014 to 2017. Medical/surgical history and operative/postoperative records were reviewed. We also compared direct inpatient hospital costs associated with the two procedures.

RESULTS

Stereoelectroencephalography and SDE cohorts both showed high likelihood of identifying epileptogenic zones (SEEG: 90.9%, SDE: 87.5%). Compared with SDE, SEEG patients had a significantly shorter operative time (118.7 versus 233.4 min, P < .001) and length of stay (6.2 versus 12.3 days, P < .001), including days spent in the intensive care unit (ICU; 1.4 versus 5.4 days, P < .001). Stereoelectroencephalography patients tended to report lower pain scores and used significantly less narcotic pain medications (54.2 versus 197.3 mg morphine equivalents, P = .005). No complications were observed. Stereoelectroencephalography and SDE cohorts had comparable inpatient hospital costs (P = .47).

CONCLUSION

In comparison with subdural electrode placement, SEEG results in a similarly favorable clinical outcome, but with reduced operative time, decreased narcotic usage, and superior pain control without requiring significantly higher costs. The potential for an improved postoperative intracranial electrode monitoring experience makes SEEG especially suitable for pediatric patients.

The inability to walk unassisted at hospital admission as a valuable triage tool to predict hospital mortality in Rwandese patients with suspected infection

OBJECTIVE

To assess the value of the inability to walk unassisted to predict hospital mortality in patients with suspected infection in a resource-limited setting.

METHODS

This is a post hoc study of a prospective trial performed in rural Rwanda. Patients hospitalized because of a suspected acute infection and who were able to walk unassisted before this disease episode were included. At hospital presentation, the walking status was graded into: 1) can walk unassisted, 2) can walk assisted only, 3) cannot walk. Receiver operating characteristic (ROC) analyses and two-by-two tables were used to determine the sensitivity, specificity, negative and positive predictive values of the inability to walk unassisted to predict in-hospital death.

RESULTS

One-thousand-sixty-nine patients were included. Two-hundred-one (18.8%), 315 (29.5%), and 553 (51.7%) subjects could walk unassisted, walk assisted or not walk, respectively. Their hospital mortality was 0%, 3.8% and 6.3%, respectively. The inability to walk unassisted had a low specificity (20%) but was 100% sensitive (CI95%, 90-100%) to predict in-hospital death (p = 0.00007). The value of the inability to walk unassisted to predict in-hospital mortality (AUC ROC, 0.636; CI95%, 0.564-0.707) was comparable to that of the qSOFA score (AUC ROC, 0.622; CI95% 0.524-0.728). Fifteen (7.5%), 34 (10.8%) and 167 (30.2%) patients who could walk unassisted, walk assisted or not walk presented with a qSOFA score count ≥2 points, respectively (p<0.001). The inability to walk unassisted correlated with the presence of risk factors for death and danger signs, vital parameters, laboratory values, length of hospital stay, and costs of care.

CONCLUSIONS

Our results suggest that the inability to walk unassisted at hospital admission is a highly sensitive predictor of in-hospital mortality in Rwandese patients with a suspected acute infection. The walking status at hospital admission appears to be a crude indicator of disease severity.

Expectations, training and evaluation of intensive care staff to an interprofessional simulation course in Germany - Development of a relevant training concept

Objective: Increasingly, intensive care units (ICU) are operated by teams of physicians and nurses with specialist training in anaesthesia and intensive care. The aims of our study were to evaluate any prior experience, expectations and the requisites for interprofessional ICU simulation-based training (SBT), and to evaluate a newly designed training course incorporating these findings. Methods: The study was laid out as a cross-sectional study and is projected in three steps. First, questionnaires were sent out to ICU nurses and physicians from 15 different hospitals in a greater metropolitan area (> million citizens). Based upon this survey a one-day ICU simulator course designed for 12 participants (6 nurses and 6 physicians) was developed, with evaluation data from four subsequent courses being analysed. Results: In the survey 40% of nurses and 57% of the physicians had had prior exposure to SBT. Various course formats were explored with respect to duration, day of the week, and group composition. After completing the course, the majority deemed a full working day in interprofessional setting to be most appropriate (p<0.001). The scenarios were considered relevant and had a positive impact on communication, workflow and coping with stress. Conclusion: Currently SBT is not a mainstream tool used by German ICU teams for further education, and this lack of familiarity must be taken into consideration when preparing SBT courses for them. We developed a nontechnical skills training course for ICU teams which was undertaken in the setting of simulated clinical scenarios (pertinent to their work environment). The participants found the course's content to be relevant for their daily work, rated the course's impact on their workplace practices as being good and advocated for longer training sessions.

Antimicrobial de-escalation in critically ill patients: a position statement from a task force of the European Society of Intensive Care Medicine (ESICM) and European Society of Clinical Microbiology and Infectious Diseases (ESCMID) Critically Ill Patients Study Group (ESGCIP)

BACKGROUND

Antimicrobial de-escalation (ADE) is a strategy of antimicrobial stewardship, aiming at preventing the emergence of antimicrobial resistance (AMR) by decreasing the exposure to broad-spectrum antimicrobials. There is no high-quality research on ADE and its effects on AMR. Its definition varies and there is little evidence-based guidance for clinicians to use ADE in the intensive care unit (ICU).

METHODS

A task force of 16 international experts was formed in November 2016 to provide with guidelines for clinical practice to develop questions targeted at defining ADE, its effects on the ICU population and to provide clinical guidance. Groups of 2 experts were assigned 1-2 questions each within their field of expertise to provide draft statements and rationale. A Delphi method, with 3 rounds and an agreement threshold of 70% was required to reach consensus.

RESULTS

We present a comprehensive document with 13 statements, reviewing the evidence on the definition of ADE, its effects in the ICU population and providing guidance for clinicians in subsets of clinical scenarios where ADE may be considered.

CONCLUSION

ADE remains a topic of controversy due to the complexity of clinical scenarios where it may be applied and the absence of evidence to the effects it may have on antimicrobial resistance.

Referral and admission to intensive care: A qualitative study of doctors' practices in a Tanzanian university hospital

BACKGROUND

Intensive care is care for critically ill patients with potentially reversible conditions. Patient selection for intensive care should be based on potential benefit but since demand exceeds availability, rationing is needed. In Tanzania, the availability of Intensive Care Units (ICUs) is very limited and the practices for selecting patients for intensive care are not known. The aim of this study was to explore doctors' experiences and perceptions of ICU referral and admission processes in a university hospital in Tanzania.

METHODS

We performed a qualitative study using semi-structured interviews with fifteen doctors involved in the recent care of critically ill patients in university hospital in Tanzania. Inductive conventional content analysis was applied for the analysis of interview notes to derive categories and sub-categories.

RESULTS

Two main categories were identified, (i) difficulties with the identification of critically ill patients in the wards and (ii) a lack of structured triaging to the ICU. A lack of critical care knowledge and communication barriers were described as preventing identification of critically ill patients. Triaging to the ICU was affected by a lack of guidelines for admission, diverging ideas about ICU indications and contraindications, the lack of bed capacity in the ICU and non-medical factors such as a fear of repercussions.

CONCLUSION

Critically ill patients may not be identified in general wards in a Tanzanian university hospital and the triaging process for the admission of patients to intensive care is convoluted and not explicit. The findings indicate a potential for improved patient selection that could optimize the use of scarce ICU resources, leading to better patient outcomes.

The Impact of Postoperative Intensive Care Unit Admission on Postoperative Hospital Length of Stay and Costs: A Prespecified Propensity-Matched Cohort Study

BACKGROUND

In this prespecified cohort study, we investigated the influence of postoperative admission to the intensive care unit versus surgical ward on health care utilization among patients undergoing intermediate-risk surgery.

METHODS

Of adult surgical patients who underwent general anesthesia without an absolute indication for postoperative intensive care unit admission, 3530 patients admitted postoperatively to an intensive care unit were matched to 3530 patients admitted postoperatively to a surgical ward using a propensity score based on 23 important preoperative and intraoperative predictor variables. Postoperative hospital length of stay and hospital costs were defined as primary and secondary end points, respectively.

RESULTS

Among patients with low propensity for postoperative intensive care unit admission, initial triage to an intensive care unit was associated with increased postoperative length of stay (incidence rate ratio, 1.69 [95% CI, 1.59-1.79]; P < .001) and hospital costs (incidence rate ratio, 1.92 [95% CI, 1.81-2.03]; P < .001). By contrast, postoperative intensive care unit admission of patients with high propensity was associated with decreased postoperative length of stay (incidence rate ratio, 0.90 [95% CI, 0.85-0.95]; P < .001) and costs (incidence rate ratio, 0.92 [95% CI, 0.88-0.97]; P = .001). Decisions regarding postoperative intensive care unit resource utilization were influenced by individual preferences of anesthesiologists and surgeons.

CONCLUSIONS

In patients with an unclear indication for postoperative critical care, intensive care unit admission may negatively impact postoperative hospital length of stay and costs. Postoperative discharge disposition varies substantially based on anesthesia and surgical provider preferences but should optimally be driven by an objective assessment of a patient's status at the end of surgery.

Anatomy of resuscitative care unit: expanding the borders of traditional intensive care units

Resuscitation lacks a place in the hospital to call its own. Specialised intensive care units, though excellent at providing longitudinal critical care, often lack the flexibility to adapt to fluctuating critical care needs. We offer the resuscitative care unit as a potential solution to ensure that patients receive appropriate care during the most critical hours of their illnesses. These units offer an infrastructure for resuscitation and can meet the changing needs of their institutions.

Site of Death, Place of Care, and Health Care Transitions Among US Medicare Beneficiaries, 2000-2015

IMPORTANCE

End-of-life care costs are high and decedents often experience poor quality of care. Numerous factors influence changes in site of death, health care transitions, and burdensome patterns of care.

OBJECTIVE

To describe changes in site of death and patterns of care among Medicare decedents.

DESIGN, SETTING, AND PARTICIPANTS

Retrospective cohort study among a 20% random sample of 1 361 870 decedents who had Medicare fee-for-service (2000, 2005, 2009, 2011, and 2015) and a 100% sample of 871 845 decedents who had Medicare Advantage (2011 and 2015) and received care at an acute care hospital, at home or in the community, at a hospice inpatient care unit, or at a nursing home.

EXPOSURES

Secular changes between 2000 and 2015.

MAIN OUTCOMES AND MEASURES

Medicare administrative data were used to determine site of death, place of care, health care transitions, which are changes in location of care, and burdensome patterns of care. Burdensome patterns of care were based on health care transitions during the last 3 days of life and multiple hospitalizations for infections or dehydration during the last 120 days of life.

RESULTS

The site of death and patterns of care were studied among 1 361 870 decedents who had Medicare fee-for-service (mean [SD] age, 82.8 [8.4] years; 58.7% female) and 871 845 decedents who had Medicare Advantage (mean [SD] age, 82.1 [8.5] years; 54.0% female). Among Medicare fee-for-service decedents, the proportion of deaths that occurred in an acute care hospital decreased from 32.6% (95% CI, 32.4%-32.8%) in 2000 to 19.8% (95% CI, 19.6%-20.0%) in 2015, and deaths in a home or community setting that included assisted living facilities increased from 30.7% (95% CI, 30.6%-30.9%) in 2000 to 40.1% (95% CI, 39.9%-30.3% ) in 2015. Use of the intensive care unit during the last 30 days of life among Medicare fee-for-service decedents increased from 24.3% (95% CI, 24.1%-24.4%) in 2000 and then stabilized between 2009 and 2015 at 29.0% (95% CI, 28.8%-29.2%). Among Medicare fee-for-service decedents, health care transitions during the last 3 days of life increased from 10.3% (95% CI, 10.1%-10.4%) in 2000 to a high of 14.2% (95% CI, 14.0%-14.3%) in 2009 and then decreased to 10.8% (95% CI, 10.6%-10.9%) in 2015. The number of decedents enrolled in Medicare Advantage during the last 90 days of life increased from 358 600 in 2011 to 513 245 in 2015. Among decedents with Medicare Advantage, similar patterns in the rates for site of death, place of care, and health care transitions were observed.

CONCLUSIONS AND RELEVANCE

Among Medicare fee-for-service beneficiaries who died in 2015 compared with 2000, there was a lower likelihood of dying in an acute care hospital, an increase and then stabilization of intensive care unit use during the last month of life, and an increase and then decline in health care transitions during the last 3 days of life.

Antiepileptic drugs in critically ill patients

BACKGROUND

The incidence of seizures in intensive care units ranges from 3.3% to 34%. It is therefore often necessary to initiate or continue anticonvulsant drugs in this setting. When a new anticonvulsant is initiated, drug factors, such as onset of action and side effects, and patient factors, such as age, renal, and hepatic function, should be taken into account. It is important to note that the altered physiology of critically ill patients as well as pharmacological and nonpharmacological interventions such as renal replacement therapy, extracorporeal membrane oxygenation, and target temperature management may lead to therapeutic failure or toxicity. This may be even more challenging with the availability of newer antiepileptics where the evidence for their use in critically ill patients is limited.

MAIN BODY

This article reviews the pharmacokinetics and pharmacodynamics of antiepileptics as well as application of these principles when dosing antiepileptics and monitoring serum levels in critically ill patients. The selection of the most appropriate anticonvulsant to treat seizure and status epileptics as well as the prophylactic use of these agents in this setting are also discussed. Drug-drug interactions and the effect of nonpharmacological interventions such as renal replacement therapy, plasma exchange, and extracorporeal membrane oxygenation on anticonvulsant removal are also included.

CONCLUSION

Optimal management of antiepileptic drugs in the intensive care unit is challenging given altered physiology, polypharmacy, and nonpharmacological interventions, and requires a multidisciplinary approach where appropriate and timely assessment, diagnosis, treatment, and monitoring plans are in place.

The outcomes and prognostic factors of the patients with unplanned intensive care unit readmissions

This retrospective cohort study investigated the outcomes of patients with unplanned intensive care unit (ICU) readmission.All of the patients readmitted to ICU within 48 hours between 2010 and 2016 were enrolled.A total of 99 patients early readmitted to ICU were identified and their mean age of the patients was 68.8 ± 14.8 years. Respiratory failure was the most common cause of ICU readmission (n = 48, 48.5%), followed by acute myocardial ischemia or worsening heart failure (n = 25, 25.3%), sepsis (n = 22, 22.2%), gastrointestinal disease (n = 16, 16.2%), and neurologic disease (n = 11, 11.1%). The median length of stay in the ICU and hospital was 7 (IQR, 4-11.5) and 32 (IQR, 15.5-48.5) days, respectively. A total of 34 patients died during the hospital stay and the rate of in-hospital mortality was 34.3%. Patients with higher APACHE II scores (adjusted odds ratio [OR], 1.17; 95% CI, 1.02-1.33), underlying malignancy (adjusted OR, 4.70; 95% CI, 1.19-18.57), and cardiovascular organ dysfunction (adjusted OR, 5.14; 95% CI, 1.24-21.38) were more likely to die.The mortality rate of ICU readmission patients was high, especially for those with higher APACHE II score, underlying malignancy and cardiovascular organ dysfunction.

Evaluating the effect of delayed activation of rapid response teams on patient outcomes: a systematic review protocol

BACKGROUND

Rapid response teams have been widely adopted across the world. Although evidence for their efficacy is not clear, they remain a popular means to detect and react to patient deterioration. This may in part be due to there being no standardized approach to their usage or implementation. A key component of their ability to be effective is the speed of response.

OBJECTIVE

The objective of this review is to evaluate the effect of delayed response by rapid response teams on hospital mortality (primary), cardiac arrest, and intensive care transfer rates (secondary).

METHODS

This review will include randomized and non-randomized studies which examined the effect of delayed response times by rapid response teams on patient mortality, cardiac arrest, and intensive care unit admission rates. This review will include studies of adult patients who have experienced a rapid response team consultation. The search strategy will utilize a combination of keywords and MeSH terms. MEDLINE and Embase will be searched, as well as examining gray literature. Two reviewers will independently screen retrieved citations to determine if they meet inclusion criteria. Studies will be selected that provide information about the impact of response time on patient outcomes. Comparisons will be made between consults that arrive in a timely manner and consults that are delayed. Quality assessment of randomized studies will be conducted in accordance with guidelines from the Cochrane Handbook for Systematic Reviews of Interventions. Quality assessment of non-randomized studies will be based on the Risk of Bias in Non-randomized Studies-of Interventions (ROBINS-I) assessment tool. Results of the review will be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

DISCUSSION

This systematic review will identify and synthesize evidence around the impact of delayed response by rapid response teams on patient mortality, cardiac arrest, and intensive care transfer rates.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO Registration: CRD42017071842 .

Hematopoietic Stem Cell Transplant in Facilities Without Intensive Care Units in Japan

OBJECTIVES

Substantial numbers of patients after hematopoietic stem cell transplant need critical care. In Japan, however, data regarding the availability of an intensive care unit and intensivists at hospitals performing hematopoietic stem cell transplant are lacking. We aimed to investigate this issue using data from the 2014 Hematopoietic Cell Transplantation in Japan Annual Report of Nationwide Survey.

MATERIALS AND METHODS

We examined whether hospitals have intensive care unit facilities and whether these hospitals are authorized by the Japanese Society of Intensive Care Medicine to provide intensivist training. The number of hematopoietic cell transplantations at each hospital was collected from the Transplant Registry Unified Management Program by the Japanese Data Center for Hematopoietic Cell Transplantation.

RESULTS

Among 236 hospitals that perform hematopoietic stem cell transplants, 106 hospitals did not have intensive care units certified by the Japanese Society of Intensive Care Medicine. In patients who receive hematopoietic stem cell transplants with the highest mortality rate, 947 allogeneic transplants were performed at hospitals without this certification and 73 were performed at hospitals without intensive care units.

CONCLUSIONS

We found that a considerable number of hematopoietic stem cell transplants are performed at hospitals with insufficient availability of critical care facilities or physicians.