Impact of delayed admission to intensive care units on mortality of critically ill patients: a cohort study

Length-of-Stay in the Emergency Department and In-Hospital Mortality: A Systematic Review and Meta-Analysis

The effect of emergency department (ED) length of stay (EDLOS) on in-hospital mortality (IHM) remains unclear. The aim of this systematic review and meta-analysis was to determine the association between EDLOS and IHM. We searched the PubMed, Medline, Embase, Web of Science, Cochrane Controlled Register of Trials, CINAHL, PsycInfo, and Scopus databases from their inception until 14−15 January 2022. We included studies reporting the association between EDLOS and IHM. A total of 11,337 references were identified, and 52 studies (total of 1,718,518 ED patients) were included in the systematic review and 33 in the meta-analysis. A statistically significant association between EDLOS and IHM was observed for EDLOS over 24 h in patients admitted to an intensive care unit (ICU) (OR = 1.396, 95% confidence interval [CI]: 1.147 to 1.701; p < 0.001, I2 = 0%) and for low EDLOS in non-ICU-admitted patients (OR = 0.583, 95% CI: 0.453 to 0.745; p < 0.001, I2 = 0%). No associations were detected for the other cut-offs. Our findings suggest that there is an association between IHM low EDLOS and EDLOS exceeding 24 h and IHM. Long stays in the ED should not be allowed and special attention should be given to patients admitted after a short stay in the ED.

Implementation of a medical intensive care team in the emergency department of a tertiary medical center in the USA

OBJECTIVE

Critically ill patients boarding in the ED have higher mortality rates. Several strategies have been implemented to deliver care to boarding patients. Our institution opted for a strategy consisting on deploying an Intensive Care team in the ED. This article reports outcomes before-and-after implementation of that team.

METHODS

On November 2020, a Medical Intensive Care Team was deployed in the ED. The team performed consultations for ICU patients boarding in the ED. A retrospective analysis of critically ill patients arriving to the ED before-and-after team implementation was performed. Outcome data were reviewed. Direct hospitalization costs per patient, and direct costs per department were assessed. Wilcoxon rank sum and Chisq-test were utilized to compare differences pre- and post-implementation. Multivariate analyses to model outcomes toward pre- and post-implementation and other variables were performed.

RESULTS

1,828 and 3,272 patients were included in the pre- and post-intervention groups. ICU LOS (days) pre- and post-intervention were 3 (1,6) and 3 (1,6), respectively (p = 0.41). ICU readmission rates were 6.7% pre-intervention and 7.4% post-intervention (p = 0.37). Total direct costs were US$ 19,928 (11,006, 37,815) and US$ 15,795 (9016, 28,993), respectively (p < 0.01). Multivariate analysis showed no association between team deployment and ICU LOS or readmission. However, there was association between its implementation and hospitalization cost reduction per patient of US$ 7,171.

CONCLUSION

The implementation of a Medical Intensive Care team in the ED is not associated with a reduction of ICU LOS or ICU readmission. Nevertheless, its implementation is associated with a reduction of hospitalization costs.

Risk Factors for Longer Pediatric Intensive Care Unit Length of Stay Among Children Who Required Escalation of Care Within 24 Hours of Admission

OBJECTIVE

Children who require early escalation of care (EOC) to the pediatric intensive care unit (PICU) after floor admission have higher mortality and increased hospital length of stay (LOS) as compared with direct emergency department (ED) admissions. This study was designed to identify subgroups of patients within this cohort (EOC to PICU within 24 hours of hospital admission) who have worse outcomes (actual PICU LOS [aLOS] > predicted PICU LOS [pLOS]).

METHODS

This was a retrospective single-center cohort study. Patients who required EOC to PICU from January 2015 to December 2019 within 24 hours of admission were included. Postoperative patients, missing cause of EOC, and mortality were excluded. Predicted LOS was calculated based on Pediatric Risk of Mortality scores. Patients with aLOS > pLOS (group A) were compared with patients with aLOS ≤ pLOS (group B). Multivariable logistic regression was performed to adjust for confounders.

RESULTS

Of 587 patients transferred to PICU after hospital admission during the study period, 286 patients met the study criteria (group A, n = 69; group B, n = 217). The 2 groups were similar in age, race, the severity of illness, and ED vitals and therapies. A higher proportion of patients in group B had EOC ≤ 6 hours of admission (51.1% vs 36.2%, P = 0.03), and a higher proportion in group A required Mechanical ventilation (56% vs 34%, P = 0.01). On multivariable regression, patients who required EOC to PICU after 6 hours after admission (adjusted odds ratio, 2.27; 95% confidence interval [CI] 1.2, 4.0), p,<0.01) and patients admitted to the floor from referral hospitals (adjusted odds ratio, 1.8; 95% confidence interval, 1.0-3.2), P = 0.04) had higher risk of greater than PLOS.

CONCLUSIONS

Among patients who required EOC to PICU, risk factors associated with aLOS > pLOS were patients who required EOC to PICU longer than 6 hours after admission to the hospital and patients admitted to the floor as a transfer from referral hospitals.

Examination of Impact of After-Hours Admissions on Hospital Resource Use, Patient Outcomes, and Costs

Background. Nighttime and weekends in hospital and intensive care unit (ICU) contexts are thought to present a greater risk for adverse events than daytime admissions. Although some studies exist comparing admission time with patient outcomes, the results are contradictory. No studies currently exist comparing costs with the time of admission. We investigated the differences in-hospital mortality, ICU length of stay, ICU mortality, and cost between daytime and nighttime admissions. Methods. All adult patients (≥18 years of age) admitted to a large academic medical-surgical ICU between 2011 and 2015 were included. Admission cohorts were defined as daytime (8:00–16:59) or nighttime (17:00–07:59). Student’s t-tests and chi-squared tests were used to test for associations between days spent in the ICU, days on mechanical ventilation, comorbidities, diagnoses, and cohort membership. Regression analysis was used to test for associations between patient and hospitalization characteristics and in-hospital mortality and total ICU costs. Results. The majority of admissions occurred during nighttime hours (69.5%) with no difference in the overall Elixhauser comorbidity score between groups ( $p=0.22$ ). Overall ICU length of stay was 7.96 days for daytime admissions compared to 7.07 days ( $p=0.001$ ) for patients admitted during nighttime hours. Overall mortality was significantly higher in daytime admissions (22.5% vs 20.6, $p=0.012$ ); however, ICU mortality was not different. The average MODS was 2.9 with those admitted during the daytime having a significantly higher MODS (3.0, $p=0.046$ ). Total ICU cost was significantly higher for daytime admissions ( $p=0.003$ ). Adjusted ICU mortality was similar in both groups despite an increased rate of adverse events for nighttime admissions. Daytime admissions were associated with increased cost. There was no difference in all hospital total cost or all hospital direct cost between groups. These findings are likely due to the higher severity of illness in daytime admissions. Conclusion. Daytime admissions were associated with a higher severity of illness, mortality rate, and ICU cost. To further account for the effect of staffing differences during off-hours, it may be beneficial to compare weekday and weeknight admission times with associated mortality rates.

The magnitude of mortality and its determinants in Ethiopian adult intensive care units: A systematic review and meta-analysis

Introduction

Despite mortality in intensive care units being a global burden, it is higher in low-resource countries, including Ethiopia. A sufficient number of evidence is not yet established regarding mortality in the intensive care unit and its determinants. This study intended to determine the prevalence of ICU mortality and its determinants in Ethiopia.

Methods

PubMed, Google Scholar, The Cochrane Library, HINARI, and African Journals Online (AJOL) databases were systematically explored for potentially eligible studies on mortality prevalence and determinants reported by studies done in Ethiopia. Using a Microsoft Excel spreadsheet, two reviewers independently screen, select, review, and extract data for further analysis using STATA/MP version 17. A meta-analysis using a random-effects model was performed to calculate the pooled prevalence and odds ratio with a 95% confidence interval. In addition, using study region and sample size, subgroup analysis was also performed.

Results

9799 potential articles were found after removing duplicates and screening for eligibility, 14 were reviewed. Ethiopia's pooled national prevalence of adult intensive care unit mortality was 39.70% (95% CI: 33.66, 45.74). Mechanical ventilation, length of staying more than two weeks, GCS below 9, and acute respiratory distress syndrome were major predictors of mortality in intensive care units of Ethiopia.

Conclusion

Mortality in adult ICU is high in Ethiopia. We strongly recommend that all health care professionals and other stakeholders should act to decrease the high mortality among critically ill patients in Ethiopia.

National Survey: How Do We Approach the Patient at Risk of Clinical Deterioration outside the ICU in the Spanish Context?

BACKGROUND

Anticipating and avoiding preventable intrahospital cardiac arrest and clinical deterioration are important priorities for international healthcare systems and institutions. One of the internationally followed strategies to improve this matter is the introduction of the Rapid Response Systems (RRS). Although there is vast evidence from the international community, the evidence reported in a Spanish context is scarce.

METHODS

A nationwide cross-sectional research consisting of a voluntary 31-question online survey was performed. The Spanish Society of Intensive, Critical and Coronary Care Medicine (SEMICYUC) supported the research.

RESULTS

We received 62 fully completed surveys distributed within 13 of the 17 regions and two autonomous cities of Spain. Thirty-two of the participants had an established Rapid Response Team (RRT). Common frequency on measuring vital signs was at least once per shift but other frequencies were contemplated (48.4%), usually based on professional criteria (69.4%), as only 12 (19.4%) centers used Early Warning Scores (EWS) or automated alarms on abnormal parameters. In the sample, doctors, nurses (55%), and other healthcare professionals (39%) could activate the RRT via telephone, but only 11.3% of the sample enacted this at early signs of deterioration. The responders on the RRT are the Intensive Care Unit (ICU), doctors, and nurses, who are available 24/7 most of the time. Concerning the education and training of general ward staff and RRT members, this varies from basic to advanced and specific-specialized level, simulating a growing educational methodology among participants. A great number of participants have emergency resuscitation equipment (drugs, airway adjuncts, and defibrillators) in their general wards. In terms of quality improvement, only half of the sample registered RRT activity indicators. In terms of the use of communication and teamwork techniques, the most used is clinical debriefing in 29 centers.

CONCLUSIONS

In terms of the concept of RRS, we found in our context that we are in the early stages of the establishment process, as it is not yet a generalized concept in most of our hospitals. The centers that have it are in still in the process of maturing the system and adapting themselves to our context.

Refusal of beds and triage of patients admitted to intensive care units in Brazil: a cross-sectional national survey

OBJECTIVE

To obtain data on bed refusal in intensive care units in Brazil and to evaluate the use of triage systems by professionals.

METHODS

A cross-sectional survey. Using the Delphi methodology, a questionnaire was created contemplating the objectives of the study. Physicians and nurses enrolled in the research network of the Associação de Medicina Intensiva Brasileira (AMIBnet) were invited to participate. A web platform (SurveyMonkey®) was used to distribute the questionnaire. The variables in this study were measured in categories and expressed as proportions. The chi-square test or Fisher's exact test was used to verify associations. The significance level was set at 5%.

RESULTS

In total, 231 professionals answered the questionnaire, representing all regions of the country. The national intensive care units had an occupancy rate of more than 90% always or frequently for 90.8% of the participants. Among the participants, 84.4% had already refused admitting patients to the intensive care unit due to the capacity of the unit. Half of the Brazilian institutions (49.7%) did not have triage protocols for admission to intensive beds.

CONCLUSIONS

Bed refusal due to high occupancy rates is common in Brazilian intensive care units. Even so, half of the services in Brazil do not adopt protocols for triage of beds.

Obstetrics and Gynecology Emergency Department Activity during Lockdown in a Teaching Hospital, Hub Center, for COVID-19

Background

The lockdown related to the SARS-CoV-2 pandemic has imposed profound changes in the interaction of the population with hospitals and emergency departments. The main aim of this research was to evaluate the impact of lockdown on the activity of obstetrics and gynecology emergency department (OGED) in a teaching hospital, hub center, for COVID-19.

Methods

The study considers all visits to the OGED with their different triage color codes that represent the clinical severity of each case (from the most severe to the least one: red, yellow, green, white). Data were selected through the “PSNet” triage program and collected anonymously. We analyzed frequency distributions of the variables separately for each woman and calculated mean and standard deviations for continuous variables. We then analyzed the association between factors and outcomes for categorical variables (expressed as a number and percentage of the total) using the chi-square test (χ2). The level of significance was established with p < 0.05. Statistical analysis was performed using SPSS Statistics V20.0. Given the fact that the study has a retrospective observational nature and it is based on an anonymous routine database, approval by the Local Ethics Committee was not necessary.

Results

The relative decrease of patients presenting to OGED in 2020 was −50.96%. The percentage of nonpregnant women was significantly lower in 2020 compared to 2019 (p ≤ 0.0001; Δ = −79.46%). Regarding the obstetric group, we saw an important decrease of visits in 2020 compared to 2019 (p < 0.0001; Δ = −40%). The prevalence of yellow codes was significantly higher in 2020 (Δ = +29.72%), while that of white (Δ = −61.58%) and green (Δ = −52.22%) codes was significantly lower (p ≤ 0.0001). Comparing the diagnoses at discharge, we could highlight significant reductions in 2020 for more than one diagnosis: bleeding (p ≤ 0.0001; Δ = −70.42%), pain (p ≤ 0.0001; Δ = −81.22%), urinary diseases (p = 0.004; Δ = −75.64%), and gastrointestinal diseases (p ≤ 0.0001; Δ = −87.50%).

Conclusions

An evident change emerged in relation to the dynamics between the local obstetrical and gynecological population, and OGED resources. The COVID‐19 lockdown greatly reduced the rate of admission to OGED without time-related obstetric and gynecological complications. The reduction of admissions suggests a more appropriate use of the ED by patients that may inspire future policies for the implementation of emergency services.

Early Prediction of All-Cause Clinical Deterioration in General Wards Patients: Development and Validation of a Biomarker-Based Machine Learning Model Derived From Rapid Response Team Activations

OBJECTIVE

The aim of the study is to evaluate the performance of a biomarker-based machine learning (ML) model (not including vital signs) derived from reviewed rapid response team (RRT) activations in predicting all-cause deterioration in general wards patients.

DESIGN

This is a retrospective single-institution study. All consecutive adult patients' cases on noncritical wards identified by RRT calls occurring at least 24 hours after patient admission, between April 2018 and June 2020, were included. The cases were reviewed and labeled for clinical deterioration by a multidisciplinary expert consensus panel. A supervised learning approach was adopted based on a set of biomarkers and demographic data available in the patient's electronic medical record (EMR).

SETTING

The setting is a 250-bed tertiary university hospital with a basic EMR, with adult (>18 y) patients on general wards.

PATIENTS

The study analyzed the cases of 514 patients for which the RRT was activated. Rapid response teams were extracted from the hospital telephone log data. Two hundred eighteen clinical deterioration cases were identified in these patients after expert chart review and complemented by 146 "nonevent" cases to build the training and validation data set.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The best performance was achieved with the random forests algorithm, with a maximal area under the receiver operating curve of 0.90 and F1 score of 0.85 obtained at prediction time T0-6h, slightly decreasing but still acceptable (area under the receiver operating curve, >0.8; F1 score, >0.75) at T0-42h. The system outperformed most classical track-and-trigger systems both in terms of prediction performance and prediction horizon.

CONCLUSIONS

In hospitals with a basic EMR, a biomarker-based ML model could be used to predict clinical deterioration in general wards patients earlier than classical track-and-trigger systems, thus enabling appropriate clinical interventions for patient safety and improved outcomes.

The Impact of a Machine Learning Early Warning Score on Hospital Mortality: A Multicenter Clinical Intervention Trial

OBJECTIVES

To determine the impact of a machine learning early warning risk score, electronic Cardiac Arrest Risk Triage (eCART), on mortality for elevated-risk adult inpatients.

DESIGN

A pragmatic pre- and post-intervention study conducted over the same 10-month period in 2 consecutive years.

SETTING

Four-hospital community-academic health system.

PATIENTS

All adult patients admitted to a medical-surgical ward.

INTERVENTIONS

During the baseline period, clinicians were blinded to eCART scores. During the intervention period, scores were presented to providers. Scores greater than or equal to 95th percentile were designated high risk prompting a physician assessment for ICU admission. Scores between the 89th and 95th percentiles were designated intermediate risk, triggering a nurse-directed workflow that included measuring vital signs every 2 hours and contacting a physician to review the treatment plan.

MEASUREMENTS AND MAIN RESULTS

The primary outcome was all-cause inhospital mortality. Secondary measures included vital sign assessment within 2 hours, ICU transfer rate, and time to ICU transfer. A total of 60,261 patients were admitted during the study period, of which 6,681 (11.1%) met inclusion criteria (baseline period n = 3,191, intervention period n = 3,490). The intervention period was associated with a significant decrease in hospital mortality for the main cohort (8.8% vs 13.9%; p < 0.0001; adjusted odds ratio [OR], 0.60 [95% CI, 0.52-0.71]). A significant decrease in mortality was also seen for the average-risk cohort not subject to the intervention (0.49% vs 0.26%; p < 0.05; adjusted OR, 0.53 [95% CI, 0.41-0.74]). In subgroup analysis, the benefit was seen in both high- (17.9% vs 23.9%; p = 0.001) and intermediate-risk (2.0% vs 4.0 %; p = 0.005) patients. The intervention period was also associated with a significant increase in ICU transfers, decrease in time to ICU transfer, and increase in vital sign reassessment within 2 hours.

CONCLUSIONS

Implementation of a machine learning early warning score-driven protocol was associated with reduced inhospital mortality, likely driven by earlier and more frequent ICU transfer.

Predictors and outcome of time to presentation among critically ill paediatric patients at Emergency Department of Muhimbili National Hospital, Dar es Salaam, Tanzania

Background

Mortality among under-five children in Tanzania remains high. While early presentation for treatment increases likelihood of survival, delays to care are common and factors causing delay to presentation among critically ill children are unknown. In this study delay was defined as presentation to the emergency department of tertially hospital i.e. Muhimbili National Hospital, more than 48 h from the onset of the index illness.

Methodology

This was a prospective cohort study of critically ill children aged 28 days to 14 years attending emergency department at Muhimbili National Hospital in Tanzania from September 2019 to January 2020. We documented demographics, time to ED presentation, ED interventions and 30-day outcome. The primary outcome was the association of delay with mortality and secondary outcomes were predictors of delay among critically ill paediatric patients.

Logistic regression and relative risk were calculated to measure the strength of the predictor and the relationship between delay and mortality respectively.

Results

We enrolled 440 (59.1%) critically ill children, their median age was 12 [IQR = 9–60] months and 63.9% were males. The median time to Emergency Department arrival was 3 days [IQR = 1–5] and more than half (56.6%) of critically ill children presented to Emergency Department in > 48 h whereby being an infant, self-referral and belonging to poor family were independent predictors of delay. Infants and those referred from other facilities had 2.4(95% CI 1.4–4.0) and 1.8(95% CI 1.1–2.8) times increased odds of presenting late to the Emergency Department respectively. The overall 30-day in-hospital mortality was 26.5% in which those who presented late were 1.3 more likely to die than those who presented early (RR = 1.3, CI: 0.9–1.9). Majority died > 24 h of Emergency Department arrival (P-value = 0.021).

Conclusion

The risk of in-hospital mortality among children who presented to the ED later than 48 h after onset of illness was 1.3 times higher than for children who presented earlier than 48 h. It could be anywhere from 10% lower to 90% higher than the point estimate. However, the effect size was statistically not significant since the confidence interval included the null value Qualitative and time-motion studies are needed to evaluate the care pathway of critically ill pediatric patients to identify preventable delays in care.

Is the Critical Care Resuscitation Unit Sustainable: A 5-Year Experience of a Beneficial and Novel Model

Background. The 6-bed critical care resuscitation unit (CCRU) is a unique and specialized intensive care unit (ICU) that streamlines the interhospital transfer (IHT—transfer between different hospitals) process for a wide range of patients with critical illness or time-sensitive disease. Previous studies showed the unit successfully increased the number of ICU admissions while reducing the time of transfer in the first year of its establishment. However, its sustainability is unknown. Methods. This was a descriptive retrospective analysis of adult, non-trauma patients who were transferred to an 800-bed quaternary medical center. Patients transferred to our medical center between January 1, 2014 and December 31, 2018 were eligible. We used interrupted time series (ITS) and descriptive analyses to describe the trend and compare the transfer process between patients who were transferred to the CCRU versus those transferred to other adult inpatient units. Results. From 2014 to 2018, 50,599 patients were transferred to our medical center; 31,582 (62%) were non-trauma adults. Compared with the year prior to the opening of the CCRU, ITS showed a significant increase in IHT after the establishment of the CCRU. The CCRU received a total of 7,788 (25%) IHTs during this period or approximately 20% of total transfers per year. Most transfers (41%) occurred via ground. Median and interquartile range [IQR] of transfer times to other ICUs (156 [65–1027] minutes) were longer than the CCRU (46 [22–139] minutes, $P<0.001$ ). For the CCRU, the most common accepting services were cardiac surgery (16%), neurosurgery (11%), and emergency general surgery (10%). Conclusions. The CCRU increases the overall number of transfers to our institution, improves patient access to specialty care while decreasing transfer time, and continues to be a sustainable model over time. Additional research is needed to determine if transferring patients to the CCRU would continue to improve patients’ outcomes and hospital revenue.

Modified Early Warning Score vs Cardiac Arrest Risk Triage Score for Prediction of Cardiopulmonary Arrest: A Case-Control Study

Background

Delayed transfer to the intensive care unit (ICU) contributes to increased mortality. Clinical tools, developed to shorten this delay, are especially useful in hospitals where the ideal healthcare provider-to-patient ratio is not met. This study aimed to validate and compare the accuracy of the well-accepted modified early warning score (MEWS) and the newer cardiac arrest risk triage (CART) score in the Philippine setting.

Patients and methods

This case-control study involved 82 adult patients admitted to the Philippine Heart Center. Patients who had cardiopulmonary (CP) arrest at the wards and those transferred to the ICU were included. Vital signs and alert-verbal-pain-unresponsive (AVPU) scales were recorded from recruitment until 48 hours prior to CP arrest or ICU transfer. The MEWS and CART scores were computed at specific time points and compared using measures of validity.

Results

The highest accuracy was obtained by the CART score with a cut-off of ≥12 at 8 hours prior to CP arrest or ICU transfer, with a specificity of 80.43% and sensitivity of 66.67%. At this time point, the MEWS with a cut-off of ≥3 had a specificity of 78.26% but a lower sensitivity of 58.33%. The area under the curve (AUC) analysis revealed that these differences were not statistically significant.

Conclusion

We recommend an MEWS threshold of 3 and a CART score threshold of 12 to help identify patients at risk for clinical deterioration. The CART score had comparable accuracy to the MEWS, but the latter's computation may be easier.

How to cite this article

Tan ADA, Permejo CC, Torres MCD. Modified Early Warning Score vs Cardiac Arrest Risk Triage Score for Prediction of Cardiopulmonary Arrest: A Case-Control Study. Indian J Crit Care Med 2022;26(7):780-785.

Outcomes in patients requiring intensive care unit (ICU) admission after emergency laparotomy - a retrospective study

Purpose

Outcomes after emergency laparotomy (EL) are poor. These patients are often admitted to an intensive care unit (ICU). This study explored outcomes in patients who were admitted to an ICU within 48 h after EL.

Materials and Methods

This retrospective single‐center registry study included all patients over 16 years of age that underwent an EL and were admitted to an ICU within 48 h after surgery in Oulu University Hospital, Finland between January 2005 and May 2015. Survival was followed until the end of 2019.

Results

We included 525 patients. Hospital mortality was 13.3%, 30‐day mortality was 17.3%, 90‐day mortality was 24.2%, 1‐year mortality was 33.0%, and 5‐year mortality was 59.4%. Survivors were younger (57 [45–70] years) than the non‐survivors (73 [62–80] years; p < .001). According to the Cox regression model, death during the follow‐up was associated with age, APACHE II‐score, lower postoperative CRP levels and platelet count of the first postoperative day, and the admission from the post‐anesthesia care unit (PACU) to the ICU instead of direct ICU admission.

Conclusion

Age, high APACHE II‐score, low CRP and platelet count, and admission from the PACU to the ICU associated with mortality after EL in patients admitted to an ICU within 48 h after EL.

Patient Deterioration on General Care Units: A Concept Analysis

Patient deterioration is a phenomenon that occurs from the inability to recognize it or respond to a change in condition. Despite the published reports on recognizing a deteriorating patient on general care floors, a gap remains in the ability of nurses to describe the concept, affecting patient outcomes. Walker and Avant's approach was applied to analyze patient deterioration. The aim of this article was to explore and clarify the meaning of patient deterioration and identify attributes, antecedents, and consequences. The defining attributes were compared to early warning scores. An operational definition was developed and its value to nurses established.

Prioritization of ICU beds with renal replacement therapy support by court order and mortality in a Brazilian metropolitan area

The shortage of intensive care unit (ICU) resources, including equipment and supplies for renal replacement therapy (RRT), is a critical problem in several countries. This study aimed to assess hospital mortality and associated factors in patients treated in public hospitals of the Federal District, Brazil, who requested admission to ICU with renal replacement therapy support (ICU-RRT) in court. Retrospective cohort study that included 883 adult patients treated in public hospitals of the Federal District who requested ICU-RRT admission in court from January 2017 to December 2018. ICU-RRT was denied to 407 patients, which increased mortality (OR 3.33, 95% CI 2.39–4.56, p ≪ 0.01), especially in patients with priority level I/II (OR 1.02, 95% CI 1.01–1.04, p ≪ 0.01). Of the requests made in court, 450 were filed by patients with priority levels III/IV, and 44.7% of these were admitted to ICU-RRT. In admitted patients, priority level III priority level I/II was associated with a low mortality (OR 0.47, 95% CI 0.32–0.69, p < 0.01), and not. The admission of patients classified as priority levels III/IV to ICU-RRT considerably jeopardized the admission of patients with priority levels I/II to these settings. The results found open new avenues for organizing public policies and improving ICU-RRT triage.

Delayed Admission to the Intensive Care Unit and Mortality of Critically Ill Adults: Systematic Review and Meta-analysis

Delayed admission of patients to the intensive care unit (ICU) is increasing worldwide and can be followed by adverse outcomes when critical care treatment is not provided timely. This systematic review and meta-analysis appraised and synthesized the published literature about the association between delayed ICU admission and mortality of adult patients. Articles published from inception up to August 2021 in English-language, peer-reviewed journals indexed in CINAHL, PubMed, Scopus, Cochrane Library, and Web of Science were searched by using key terms. Delayed ICU admission constituted the intervention, while mortality for any predefined time period was the outcome. Risk for bias was evaluated with the Newcastle-Ottawa Scale and additional criteria. Study findings were synthesized qualitatively, while the odds ratios (ORs) for mortality with 95% confidence intervals (CIs) were combined quantitatively. Thirty-four observational studies met inclusion criteria. Risk for bias was low in most studies. Unadjusted mortality was reported in 33 studies and was significantly higher in the delayed ICU admission group in 23 studies. Adjusted mortality was reported in 18 studies, and delayed ICU admission was independently associated with significantly higher mortality in 13 studies. Overall, pooled OR for mortality in case of delayed ICU admission was 1.61 (95% CI 1.44-1.81). Interstudy heterogeneity was high (I² = 66.96%). According to subgroup analysis, OR for mortality was remarkably higher in postoperative patients (OR, 2.44, 95% CI 1.49-4.01). These findings indicate that delayed ICU admission is significantly associated with mortality of critically ill adults and highlight the importance of providing timely critical care in non-ICU settings.

A biomarker panel for risk of early respiratory failure following hematopoietic cell transplantation

This study identified and validated ST2, WFDC2, IL-6, and TNFR1 as risk biomarkers for RF and related mortality post-HCT.

Plasma biomarkers associated with respiratory failure (RF) following hematopoietic cell transplantation (HCT) have not been identified. Therefore, we aimed to validate early (7 and 14 days post-HCT) risk biomarkers for RF. Using tandem mass spectrometry, we compared plasma obtained at day 14 post-HCT from 15 patients with RF and 15 patients without RF. Six candidate proteins, from this discovery cohort or identified in the literature, were measured by enzyme-linked immunosorbent assay in day-7 and day-14 post-HCT samples from the training (n = 213) and validation (n = 119) cohorts. Cox proportional-hazard analyses with biomarkers dichotomized by Youden’s index, as well as landmark analyses to determine the association between biomarkers and RF, were performed. Of the 6 markers, Stimulation-2 (ST2), WAP 4-disulfide core domain protein 2 (WFDC2), interleukin-6 (IL-6), and tumor necrosis factor receptor 1 (TNFR1), measured at day 14 post-HCT, had the most significant association with an increased risk for RF in the training cohort (ST2: hazard ratio [HR], 4.5, P = .004; WFDC2: HR, 4.2, P = .010; IL-6: HR, 6.9, P < .001; and TFNR1: HR, 6.1, P < .001) and in the validation cohort (ST2: HR, 23.2, P = .013; WFDC2: HR, 18.2, P = .019; IL-6: HR, 12.2, P = .014; and TFNR1: HR, 16.1, P = .001) after adjusting for the conditioning regimen. Using cause-specific landmark analyses, including days 7 and 14, high plasma levels of ST2, WFDC2, IL-6, and TNFR1 were associated with an increased HR for RF in the training and validation cohorts. These biomarkers were also predictive of mortality from RF. ST2, WFDC2, IL-6 and TNFR1 levels measured early posttransplantation improve risk stratification for RF and its related mortality.

Initiation of a Lung Protective Ventilation Strategy in the Emergency Department: Does an Emergency Department-Based ICU Make a Difference?

BACKGROUND:

Lung protective ventilation (LPV) is a key component in the management of acute respiratory distress syndrome and other acute respiratory pathology. Initiation of LPV in the emergency department (ED) is associated with improved patient-centered and system outcomes, but adherence to LPV among ED patients is low. The impact of an ED-based ICU (ED-ICU) on LPV adherence is not known.

METHODS:

This single-center, retrospective, cohort study analyzed rates of adherence to a multifaceted LPV strategy pre- and post-implementation of an ED-ICU. LPV strategy components included low tidal volume ventilation, avoidance of severe hyperoxia and high plateau pressures, and positive end-expiratory pressure settings in alignment with best-evidence recommendations. The primary outcome was adherence to the LPV strategy at time of ED departure.

RESULTS AND CONCLUSIONS:

A total of 561 ED visits were included in the analysis, of which 60.0% received some portion of their emergency care in the ED-ICU. Adherence to the LPV strategy was statistically significantly higher in the ED-ICU cohort compared with the pre-ED-ICU cohort (65.8% vs 41.4%; p < 0.001) and non-ED-ICU cohort (65.8% vs 43.1%; p < 0.001). Among the ED-ICU cohort, 92.8% of patients received low tidal volume ventilation. Care in the ED-ICU was also associated with shorter ICU and hospital length of stay. These findings suggest improved patient and resource utilization outcomes for mechanically ventilated ED patients receiving care in an ED-ICU.

Selection bias in estimating the relationship between prolonged ED boarding and mortality in emergency critical care patients

OBJECTIVES

Studies have found that prolonged boarding time for intensive care unit (ICU) patients in the emergency department (ED) is associated with higher in-hospital mortality. However, these studies introduced selection bias by excluding patients with ICU admission orders who were downgraded and never arrived in the ICU. Consequently, they may overestimate mortality in prolonged ED boarders.

METHODS

This was a retrospective cohort study at a single center covering the period from August 14, 2015 to August 13, 2019. Adult ED patients with medical ICU admission orders and at least 6 hours of subsequent critical care in either the ED or the ICU were included. Patients were classified as having either prolonged (>6 hours) or non-prolonged (≤6 hours) ED boarding. Downgraded patients were identified, and mortality was compared, both including and excluding downgraded patients.

RESULTS

Of 1862 patients, 612 (32.9%) had prolonged boarding; at 6 hours after ICU admission order entry, they were still in the ED. The remaining 1250 (67.1%) had non-prolonged boarding; at 6 hours after the ICU admission order entry, they were already in the ICU. In-hospital mortality in the non-prolonged boarding group was 18.9%. In the prolonged boarding group, 296 (48.4%) patients were downgraded in the ED and never arrived in the ICU. Including these ED downgrades, the mortality in the prolonged boarding group was 13.4% (risk difference -5.5%, 95% confidence interval [CI] -8.9% to -2.0%, P = 0.0031). When we excluded downgrades, the mortality in the prolonged boarding group increased to 17.4% (risk difference -1.5%, 95% CI -6.2% to 3.2%, P = 0.5720). The lower mortality in the prolonged group was attributable to lower severity of illness (mean emergency critical care SOFA [eccSOFA] difference: -0.8, 95% CI -1.1 to -0.4, P < 0.0001).

CONCLUSIONS

Excluding critical care patients who were downgraded in the ED leads to selection bias and overestimation of mortality among prolonged ED boarders.

Emergency department length of stay and outcomes of emergency department-based intensive care unit patients

OBJECTIVE

Emergency department (ED) boarding of patients who are critically ill is associated with poor outcomes. ED-based intensive care units (ED-ICUs) may mitigate the risks of ED boarding. We sought to analyze the impact of ED length of stay (LOS) before transfer to an ED-ICU on patient outcomes.

METHODS

We retrospectively analyzed adult ED patients managed in the ED-ICU at a US medical center. Bivariate and multivariable linear regressions tested ED LOS as a predictor of inpatient ICU and hospital LOS, and separate bivariate and multivariable logistic regressions tested ED LOS as a predictor of inpatient ICU admission, 48-hour mortality, and hospital mortality. Multivariable analyses' covariates were age, sex, Charlson Comorbidity Index (CCI), Emergency Severity Index, and eSimplified Acute Physiology Score (eSAPS3).

RESULTS

We included 5859 ED visits with subsequent care in the ED-ICU. Median age, CCI, eSAPS3, ED LOS, and ED-ICU LOS were 62 years (interquartile range [IQR], 48-73 years), 5 (IQR, 2-8), 46 (IQR, 36-56), 3.6 hours (IQR, 2.5-5.3 hours), and 8.5 hours (IQR, 5.3-13.4 hours), respectively, and 46.3% were women. Bivariate analyses showed negative associations of ED LOS with hospital LOS (β = -3.4; 95% confidence interval [CI], -5.9 to -1.0), inpatient ICU admission (odds ratio [OR], 0.86, 95% CI, 0.84-0.88), 48-hour mortality (OR, 0.89; 95% CI, 0.82-0.98), and hospital mortality (OR, 0.89; 95% CI, 0.85-0.92), but no association with inpatient ICU LOS. Multivariable analyses showed a negative association of ED LOS with inpatient ICU admission (OR, 0.91; 95% CI, 0.88-0.93), but no associations with other outcomes.

CONCLUSIONS

We observed no significant associations between ED LOS before ED-ICU transfer and worsened outcomes, suggesting an ED-ICU may mitigate the risks of ED boarding of patients who are critically ill.

Using sequence clustering to identify clinically relevant subphenotypes in patients with COVID-19 admitted to the intensive care unit

OBJECTIVE

The novel coronavirus disease 2019 (COVID-19) has heterogenous clinical courses, indicating that there might be distinct subphenotypes in critically ill patients. Although prior research has identified these subphenotypes, the temporal pattern of multiple clinical features has not been considered in cluster models. We aimed to identify temporal subphenotypes in critically ill patients with COVID-19 using a novel sequence cluster analysis and associate them with clinically relevant outcomes.

MATERIALS AND METHODS

We analyzed 1036 confirmed critically ill patients with laboratory-confirmed SARS-COV-2 infection admitted to the Mount Sinai Health System in New York city. The agglomerative hierarchical clustering method was used with Levenshtein distance and Ward's minimum variance linkage.

RESULTS

We identified four subphenotypes. Subphenotype I (N = 233 [22.5%]) included patients with rapid respirations and a rapid heartbeat but less need for invasive interventions within the first 24 hours, along with a relatively good prognosis. Subphenotype II (N = 418 [40.3%]) represented patients with the least degree of ailments, relatively low mortality, and the highest probability of discharge from the hospital. Subphenotype III (N = 259 [25.0%]) represented patients who experienced clinical deterioration during the first 24 hours of intensive care unit admission, leading to poor outcomes. Subphenotype IV (N = 126 [12.2%]) represented an acute respiratory distress syndrome trajectory with an almost universal need for mechanical ventilation.

CONCLUSION

We utilized the sequence cluster analysis to identify clinical subphenotypes in critically ill COVID-19 patients who had distinct temporal patterns and different clinical outcomes. This study points toward the utility of including temporal information in subphenotyping approaches.

Evaluation of time to death after admission to an intensive care unit and factors associated with mortality: A retrospective longitudinal study

Background

Among nonsurvivors admitted to the intensive care unit (ICU), some present early mortality while other patients, despite having a favorable evolution regarding the initial disease, die later due to complications related to hospitalization. This study aims to identify factors associated with the time until death after admission to an ICU of a university hospital.

Methods

Retrospective longitudinal study that included adult patients admitted to the ICU between January 1, 2008, and December 31, 2017. Nonsurviving patients were divided into groups according to the length of time from admission to the ICU until death: Early (0-5 days), intermediate (6-28 days), and late (>28 days). Patients were considered septic if they had this diagnosis on admission to the ICU. Simple linear regression analysis was performed to evaluate the association between time to death over the years of the study. Multivariate cox regression was used to assess risk factors for the outcome in the ICU.

Results

In total, 6596 patients were analyzed. Mortality rate was 32.9% in the ICU. Most deaths occurred in the early (42.8%) and intermediate periods (47.9%). Patients with three or more dysfunctions on admission were more likely to die early (P < 0.001). The diagnosis of sepsis was associated with a higher mortality rate. The multivariate analysis identified age >60 years (hazard ratio [HR] 1.009), male (HR 1.192), mechanical ventilation (HR 1.476), dialysis (HR 2.297), and sequential organ failure assessment >6 (HR 1.319) as risk factors for mortality.

Conclusion

We found a higher proportion of early and intermediate deaths in the study period. The presence of three or more organ dysfunctions at ICU admission was associated with early death. The diagnosis of sepsis evident on ICU admission was associated with higher mortality.

Critical care management of chimeric antigen receptor T-cell therapy recipients

Chimeric antigen receptor (CAR) T-cell therapy is a promising immunotherapeutic treatment concept that is changing the treatment approach to hematologic malignancies. The development of CAR T-cell therapy represents a prime example for the successful bench-to-bedside translation of advances in immunology and cellular therapy into clinical practice. The currently available CAR T-cell products have shown high response rates and long-term remissions in patients with relapsed/refractory acute lymphoblastic leukemia and relapsed/refractory lymphoma. However, CAR T-cell therapy can induce severe life-threatening toxicities such as cytokine release syndrome, neurotoxicity, or infection, which require rapid and aggressive medical treatment in the intensive care unit setting. In this review, the authors provide an overview of the state-of-the-art in the clinical management of severe life-threatening events in CAR T-cell recipients. Furthermore, key challenges that have to be overcome to maximize the safety of CAR T cells are discussed.

Reducing Avoidable Transfer Delays in the Pediatric Intensive Care Unit for Status Asthmaticus Patients

INTRODUCTION

Status asthmaticus (acute severe asthma) is one of the most common reasons for Pediatric Intensive Care Unit (PICU) admission. Accordingly, ensuring optimal throughput for patients admitted with status asthmaticus is essential for optimizing PICU capacity. Few studies specifically address effective methods to reduce delays related to PICU discharge. This project aimed to identify and reduce avoidable delays in PICU discharge for status asthmaticus patients.

METHODS

This quality improvement project focused on reducing transfer delays for status asthmaticus patients admitted to the PICU at a freestanding academic children's hospital. We standardized the transfer criteria, identified barriers to an efficient transfer, and implemented multidisciplinary interventions. The primary aim was to decrease the average duration from fulfilling the transfer criteria to PICU discharge by 15% from the baseline within 8 months of implementation. The balancing measure was readmissions to the PICU for asthma exacerbations within 24 hours from PICU discharge.

RESULTS

The analysis included 623 patients. Following interventions, the time from fulfilling transfer criteria to PICU discharge decreased from 9.8 hours to 6.8 hours, a 30.6% reduction from baseline. Improvements were sustained for 6 months. In the preintervention group, three patients were readmitted to the PICU within 24 hours of transferring out of the PICU, but no patient was readmitted during the postintervention period.

CONCLUSIONS

Standardizing transfer criteria and implementing multidisciplinary strategies can reduce avoidable PICU discharge delays for patients with status asthmaticus. The application of a similar approach could potentially reduce avoidable delays for other conditions in the PICU.

Association between pre-intensive care unit (ICU) hospital length of stay and ICU outcomes in a resource-limited setting

Background

Previous studies demonstrated higher mortality for patients with a longer pre-intensive care unit (ICU) hospital length of stay (LOS), in well-resourced settings.

Objectives

The study aimed to determine the association between pre-ICU hospital LOS and ICU outcomes in a resource-limited setting. We hypothesised that longer pre-ICU hospital LOS would be associated with higher ICU mortality.

Methods

This was a retrospective cohort study measuring the association between pre-ICU hospital LOS and ICU outcomes using data extracted from a regional hospital ICU in KwaZulu-Natal, South Africa. Consecutive ICU admissions of all patients (medical and surgical) older than 18 years were included during the study period September 2014 to August 2018. A corrected sample size of 2 040 patients was identified. Multivariable logistic regression was used to assess the primary outcome of ICU mortality, and multivariable Cox proportional hazard regression was used for the secondary outcome of ICU LOS.

Results

The median pre-ICU hospital LOS was 1 day (interquartile range (IQR) 0 - 2 days). The median length of ICU stay was 2.4 days (IQR 1.1 - 4.8 days) and the observed ICU mortality was 16% (n=327/2 040). Pre-ICU hospital LOS was not associated with ICU mortality in the unadjusted (odds ratio (OR) 1.00; 95% confidence interval (CI) 0.98 - 1.02; p=0.68; n=2 040) and fully adjusted logistic regression models (OR 1.00; 95% CI 0.98 - 1.03; p=0.90; n=1 981) using a complete case analysis for missing patient-level covariates. In Cox proportional hazard models, there was no association between pre-ICU hospital LOS and ICU LOS (hazard ratio 1.00; 95% CI 0.98 - 1.03; p=0.72; n=1 967), including when stratified by admission source.

Conclusion

Pre-ICU hospital LOS was not associated with either ICU mortality or ICU LOS in a resource-limited setting. Future studies should aim to include multicentre data and evaluate long-term outcomes.

Contributions of the study

The study was conducted in a resource-limited setting and found no association between prolonged LOS pre-ICU and patient outcomes. Several potential explanations for this observation have been explored. This important subject is pertinent to the appropriate use of limited resources and encourages future studies to evaluate this association and to consider longer-term outcomes (e.g. 30-day mortality) in future findings.

Sepsis in Burns-Lessons Learnt from Developments in the Management of Septic Shock

After surviving the acute phase of resuscitation, septic shock is the cause of death in the majority of burn patients. Therefore, the management of septic shock is a cornerstone in modern burn care. Whereas sepsis therapy in general has undergone remarkable developments in the past decade, the management of septic shock in burn patients still has a long way to go. Instead, the differences of burn patients with septic shock versus general patients have been emphasized and thus, burn patients were excluded in every sepsis study which are the basis for modern sepsis therapy. However, due to the lack of evidence in burn patients, the standards of procedure for general sepsis therapy have been adopted in burn care. This review identifies the differences of burn patients with sepsis versus other septic patients and summarizes the scientific basis for modern sepsis therapy in general ICU patients and burn patients. Consequently, the results in general sepsis research should be transferred to burn care, which means the implementation of effective screening, early resuscitation, and efficient antimicrobial treatment. Therefore, on the basis of past developments and in the light of the current update of the Surviving Sepsis Campaign guidelines, this review introduces the "Burn SOFA score" and the "3 H's of burn sepsis" as a screening tool for early sepsis recognition in burn patients.

Profile of referrals to an intensive care unit from a regional hospital emergency centre in KwaZulu-Natal

Introduction

The objective was to describe the clinical characteristics, disease profile and outcome of patients referred from a regional hospital Emergency Centre (EC) to the Intensive Care Unit (ICU).

Methods

A retrospective review was performed using data extracted from the Integrated Critical Care Electronic Database (iCED). Data were extracted from the database with respect to patient characteristics, Society of Critical Care Medicine (SCCM) grading, and outcome of the ICU referral. Modified early warning scores (MEWS) were calculated from EC referral data.

Results

There were a total of 2187 referrals. Of these, 56.3% (1231/2187) were male. The mean age of referrals was 36 years. Of the referred patients, 41.5% (907/2187) were initially accepted for admission. A further 378 patients were accepted for admission after a follow up ICU review. Medical conditions accounted for the majority of patient referrals, followed by general surgery and trauma. Most patients initially accepted to ICU were classified as SCCM I and II and had a mean MEWS of 4. Almost half of the patients experienced a delay in admission, most commonly due to a lack of ICU bed availability. ICU mortality was 13.6% for patients admitted from the EC.

Discussion

The EC population referred to the ICU was young with a high burden of medical and trauma conditions. Decisions to accept patients to ICU are limited by available resources, and there was a need to apply ICU triage criteria. Delays in the transfer of ICU patients from the EC increase the workload and contribute to EC crowding.

Demand for Intensive Care beds and patient classification according to the priority criterion

OBJECTIVE

to assess the demand for Intensive Care Unit beds as well as the classification of the patients for admission, according to the priority system.

METHOD

a retrospective and cross-sectional study, developed from January2014 to December2018 in two Intensive Care Units for adults of a university hospital. The sample consisted of the requests for vacancies according to the priority system(scale from 1 to 4, where 1 is the highest priority and 4 is no priority), registered in the institution's electronic system.

RESULTS

a total of 8,483 vacancies were requested, of which 4,389(51.7%) were from unitB. The highest percentage in unitA was of Priority2 patients(32.6%); and Priority1 was prevalent in unitB(45.4%). The median lead time between request and admission to unitA presented a lower value for priority1 patients(2h57) and a higher value for priority4 patients(11h24); in unitB, priority4 patients presented shorter time(5h54) and priority3 had longer time(11h54). 40.5% of the requests made to unitA and 48.5% of those made to unitB were fulfilled, with 50.7% and 48.5% of these patients being discharged from the units, respectively.

CONCLUSION

it is concluded that the demand for intensive care beds was greater than their availability. Most of the patients assisted were priorities1 and2, although a considerable percentage of those classified as priorities3 and4 is observed.

Developing machine learning models to personalize care levels among emergency room patients for hospital admission

Objective

To develop prediction models for intensive care unit (ICU) vs non-ICU level-of-care need within 24 hours of inpatient admission for emergency department (ED) patients using electronic health record data.

Materials and Methods

Using records of 41 654 ED visits to a tertiary academic center from 2015 to 2019, we tested 4 algorithms—feed-forward neural networks, regularized regression, random forests, and gradient-boosted trees—to predict ICU vs non-ICU level-of-care within 24 hours and at the 24th hour following admission. Simple-feature models included patient demographics, Emergency Severity Index (ESI), and vital sign summary. Complex-feature models added all vital signs, lab results, and counts of diagnosis, imaging, procedures, medications, and lab orders.

Results

The best-performing model, a gradient-boosted tree using a full feature set, achieved an AUROC of 0.88 (95%CI: 0.87–0.89) and AUPRC of 0.65 (95%CI: 0.63–0.68) for predicting ICU care need within 24 hours of admission. The logistic regression model using ESI achieved an AUROC of 0.67 (95%CI: 0.65–0.70) and AUPRC of 0.37 (95%CI: 0.35–0.40). Using a discrimination threshold, such as 0.6, the positive predictive value, negative predictive value, sensitivity, and specificity were 85%, 89%, 30%, and 99%, respectively. Vital signs were the most important predictors.

Discussion and Conclusions

Undertriaging admitted ED patients who subsequently require ICU care is common and associated with poorer outcomes. Machine learning models using readily available electronic health record data predict subsequent need for ICU admission with good discrimination, substantially better than the benchmarking ESI system. The results could be used in a multitiered clinical decision-support system to improve ED triage.

Outcome Differences Between Direct Admissions to the PICU From ED and Escalations From Floor

OBJECTIVES

To compare the outcomes (mortality and ICU length of stay) of patients with direct admissions to the PICU from the emergency department [ED]) versus as an escalation of care from the floor.

METHODS

A retrospective cohort study with a secondary analysis of registry data. Patient demographics and outcome variables collected from January 1, 2015, to December 31, 2019, were obtained from the Virtual Pediatric Systems database. Patients with a source of admission other than the hospital's ED or pediatric floor were excluded. Multivariable regression analysis controlling for age groups, sex, race, diagnostic categories, and severity of illness (Pediatric Index of Mortality III), with clustering for sites, was performed.

RESULTS

A total of 209 695 patients from 121 sites were included in the analysis. A total of 154 716 (73.7%) were admitted directly from the ED, and 54 979 were admitted (26.2%) as an escalation of care from the floor. Two groups differed in age and race distribution, medical complexity, diagnostic categories, and severity of illness. After controlling for measured confounders, patients with floor escalations had higher mortality (2.78% vs 1.95%; P < .001), with an odds ratio of 1.71 (95% CI 1.5 to 1.9) and longer PICU length of stay (4.9 vs 3.6 days; P < .001). The rates of most of the common ICU procedures and their durations were also significantly higher in patients with an escalation of care.

CONCLUSIONS

Compared with direct admissions to the PICU from the ED, patients who were initially triaged to the pediatric floor and then require escalation to the PICU have worse outcomes. Further research is needed to explore the potential causes of this difference.

Association between delay in intensive care unit admission and the host response in patients with community-acquired pneumonia

Background

A delay in admission to the intensive care unit (ICU) of patients with community-acquired pneumonia (CAP) has been associated with an increased mortality. Decisions regarding interventions and eligibility for immune modulatory therapy are often made at the time of admission to the ICU. The primary aim of this study was to compare the host immune response measured upon ICU admission in CAP patients admitted immediately from the emergency department (direct ICU admission) with those who were transferred within 72 h after admission to the general ward (delayed ICU admission).

Methods

Sixteen host response biomarkers providing insight in pathophysiological mechanisms implicated in sepsis and blood leukocyte transcriptomes were analysed in patients with CAP upon ICU admission in two tertiary hospitals in the Netherlands.

Results

Of 530 ICU admissions with CAP, 387 (73.0%) were directly admitted and 143 (27.0%) had a delayed admission. Patients with a delayed ICU admission were more often immunocompromised (35.0 versus 21.2%, P = .002) and had more malignancies (23.1 versus 13.4%, P = .011). Shock was more present in patients who were admitted to the ICU directly (46.6 versus 33.6%, P = .010). Delayed ICU admission was not associated with an increased hospital mortality risk (hazard ratio 1.25, 95% CI 0.89–1.78, P = .20). The plasma levels of biomarkers (n = 297) reflecting systemic inflammation, endothelial cell activation and coagulation activation were largely similar between groups, with exception of C-reactive protein, soluble intercellular adhesion molecule-1 and angiopoietin-1, which were more aberrant in delayed admissions compared to direct ICU admissions. Blood leukocyte transcriptomes (n = 132) of patients with a delayed ICU admission showed blunted innate and adaptive immune response signalling when compared with direct ICU admissions, as well as decreased gene expression associated with tissue repair and extracellular matrix remodelling pathways.

Conclusions

Blood leukocytes of CAP patients with delayed ICU admission show evidence of a more immune suppressive phenotype upon ICU admission when compared with blood leukocytes from patients directly transferred to the ICU.

Trial registration: Molecular Diagnosis and Risk Stratification of Sepsis (MARS) project, ClinicalTrials.gov identifier NCT01905033.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13613-021-00930-5.

Intensive Care Unit prioritization: The impact of ICU bed availability on mortality in critically ill patients who requested ICU admission in court in a Brazilian cohort

PURPOSE

To assess hospital mortality in patients who requested ICU admission in court due to the scarcity of ICU beds in the Brazilian public health system and the consequences of these judicial litigations.

MATERIAL AND METHODS

Retrospective cohort study that included adult patients from the public health system of the Federal District, Brazil, who claimed ICU admission in court from January 2017 to December 2019.

RESULTS

Of the 1752 patients, 1031 were admitted to ICU (58.8%). Hospital mortality was 61.1% (1071/1752). Of the requests, 768 (43.8%) were made by patients with priority levels III or IV, resulting in the ICU admission of 33.9% of these patients. Denial of ICU admission (p < 0.001) increased mortality. ICU admission reduced hospital mortality in patients classified as priority level I (p < 0.001), priority level II (p < 0.001), and priority level III (p < 0.001), but not as priority level IV (p = 0.619).

CONCLUSION

A large proportion of patients was denied ICU admission and it was associated with an increased mortality. A considerable portion of the ICU-admitted patients were classified as priority level III and IV, impairing the ICU admission of patients with priority level I which are the ones with the greatest benefit from it.

A Target for Increased Mortality Risk in Critically Ill Patients: The Concept of Perpetuity

Background: Emergency medicine is acuity-based and focuses on time-sensitive treatments for life-threatening diseases. Prolonged time in the emergency department, however, is associated with higher mortality in critically ill patients. Thus, we explored management after an acuity-based intervention, which we call perpetuity, as a potential mechanism for increased risk. To explore this concept, we evaluated the impact of each hour above a lung-protective tidal volume on risk of mortality. Methods: This cohort analysis includes all critically ill, non-trauma, adult patients admitted to two academic EDs between 1 November 2013 and 30 April 2017. Cox models with time-varying covariates were developed with time in perpetuity as a time-varying covariate, defined as hours above 8 mL/kg ideal body weight, adjusted for covariates. The primary outcome was the time to in-hospital death. Results: Our analysis included 2025 patients, 321 (16%) of whom had at least 1 h of perpetuity time. A partial likelihood-ratio test comparing models with and without hours in perpetuity was statistically significant (χ²(3) = 13.83, p = 0.0031). There was an interaction between age and perpetuity (Relative risk (RR) 0.9995; 95% Confidence interval (CI₉₅): 0.9991–0.9998). For example, for each hour above 8 mL/kg ideal body weight, a 20-year-old with 90% oxygen saturation has a relative risk of death of 1.02, but a 40-year-old with 90% oxygen saturation has a relative risk of 1.01. Conclusions: Perpetuity, illustrated through the lens of mechanical ventilation, may represent a target for improving outcomes in critically ill patients, starting in the emergency department. Research is needed to evaluate the types of patients and interventions in which perpetuity plays a role.

Association of delayed time in the emergency department with the clinical outcomes for critically ill patients

BACKGROUND

Previous studies have shown the association of waiting time in the emergency department with the prognosis of critically ill patients, but these studies linking the waiting time to clinical outcomes have been inconsistent and limited by small sample size.

AIM

To determine the relationship between the waiting time in the emergency department and the clinical outcomes for critically ill patients in a large sample population.

DESIGN

A retrospective cohort study of 13 634 patients.

METHODS

We used the Medical Information Mart for Intensive Care III database. Multivariable logistic regression was used to determine the independent relationships of the in-hospital mortality rate with the delayed time and different groups. Interaction and stratified analysis were conducted to test whether the effect of delayed time differed across various subgroups.

RESULTS

After adjustments, the in-hospital mortality in the ≥6 h group increased by 38.1% (OR 1.381, 95% CI 1.221-1.562). Moreover, each delayed hour was associated independently with a 1.0% increase in the risk of in-hospital mortality (OR 1.010, 95% CI 1.008-1.010). In the stratified analysis, intensive care unit (ICU) types, length of hospital stay, length of ICU stay, simplified acute physiology score II and diagnostic category were found to have interactions with ≥6 h group in in-hospital mortality.

CONCLUSIONS

In this large retrospective cohort study, every delayed hour was associated with an increase in mortality. Furthermore, clinicians should be cautious of patients diagnosed with sepsis, liver/renal/metabolic diseases, internal hemorrhage and cardiovascular disease, and if conditions permit, they should give priority to transferring to the corresponding ICUs.

The Japanese Clinical Practice Guidelines for Management of Sepsis and Septic Shock 2020 (J-SSCG 2020)

The Japanese Clinical Practice Guidelines for Management of Sepsis and Septic Shock 2020 (J-SSCG 2020), a Japanese-specific set of clinical practice guidelines for sepsis and septic shock created as revised from J-SSCG 2016 jointly by the Japanese Society of Intensive Care Medicine and the Japanese Association for Acute Medicine, was first released in September 2020 and published in February 2021. An English-language version of these guidelines was created based on the contents of the original Japanese-language version. The purpose of this guideline is to assist medical staff in making appropriate decisions to improve the prognosis of patients undergoing treatment for sepsis and septic shock. We aimed to provide high-quality guidelines that are easy to use and understand for specialists, general clinicians, and multidisciplinary medical professionals. J-SSCG 2016 took up new subjects that were not present in SSCG 2016 (e.g., ICU-acquired weakness [ICU-AW], post-intensive care syndrome [PICS], and body temperature management). The J-SSCG 2020 covered a total of 22 areas with four additional new areas (patient- and family-centered care, sepsis treatment system, neuro-intensive treatment, and stress ulcers). A total of 118 important clinical issues (clinical questions, CQs) were extracted regardless of the presence or absence of evidence. These CQs also include those that have been given particular focus within Japan. This is a large-scale guideline covering multiple fields; thus, in addition to the 25 committee members, we had the participation and support of a total of 226 members who are professionals (physicians, nurses, physiotherapists, clinical engineers, and pharmacists) and medical workers with a history of sepsis or critical illness. The GRADE method was adopted for making recommendations, and the modified Delphi method was used to determine recommendations by voting from all committee members.As a result, 79 GRADE-based recommendations, 5 Good Practice Statements (GPS), 18 expert consensuses, 27 answers to background questions (BQs), and summaries of definitions and diagnosis of sepsis were created as responses to 118 CQs. We also incorporated visual information for each CQ according to the time course of treatment, and we will also distribute this as an app. The J-SSCG 2020 is expected to be widely used as a useful bedside guideline in the field of sepsis treatment both in Japan and overseas involving multiple disciplines.

An emergency department-based intensive care unit is associated with decreased hospital length of stay for upper gastrointestinal bleeding

INTRODUCTION

Upper gastrointestinal bleeding (UGIB) is associated with substantial morbidity, mortality, and intensive care unit (ICU) utilization. Initial risk stratification and disposition from the Emergency Department (ED) can prove challenging due to limited data points during a short period of observation. An ED-based ICU (ED-ICU) may allow more rapid delivery of ICU-level care, though its impact on patients with UGIB is unknown.

METHODS

A retrospective observational study was conducted at a tertiary U.S. academic medical center. An ED-ICU (the Emergency Critical Care Center [EC3]) opened in February 2015. Patients presenting to the ED with UGIB undergoing esophagogastroduodenoscopy within 72 h were identified and analyzed. The Pre- and Post-EC3 cohorts included patients from 9/2/2012-2/15/2015 and 2/16/2015-6/30/2019.

RESULTS

We identified 3788 ED visits; 1033 Pre-EC3 and 2755 Post-EC3. Of Pre-EC3 visits, 200 were critically ill and admitted to ICU [Cohort A]. Of Post-EC3 visits, 682 were critically ill and managed in EC3 [Cohort B], whereas 61 were critically ill and admitted directly to ICU without care in EC3 [Cohort C]. The mean interval from ED presentation to ICU level care was shorter in Cohort B than A or C (3.8 vs 6.3 vs 7.7 h, p < 0.05). More patients in Cohort B received ICU level care within six hours of ED arrival (85.3 vs 52.0 vs 57.4%, p < 0.05). Mean hospital length of stay (LOS) was shorter in Cohort B than A or C (6.2 vs 7.3 vs 10.0 days, p < 0.05). In the Post-EC3 cohort, fewer patients were admitted to an ICU (9.3 vs 19.4%, p < 0.001). The rate of floor admission with transfer to ICU within 24 h was similar. No differences in absolute or risk-adjusted mortality were observed.

CONCLUSION

For critically ill ED patients with UGIB, implementation of an ED-ICU was associated with reductions in rate of ICU admission and hospital LOS, with no differences in safety outcomes.

Patient characteristics and outcomes associated with adherence to the low PEEP/FIO2 table for acute respiratory distress syndrome

It remains uncertain how best to set positive end-expiratory pressure (PEEP) for mechanically ventilated patients with the acute respiratory distress syndrome (ARDS). Among patients on low tidal volume ventilation (LTVV), we investigated if further adherence to the low PEEP/FIO2 (inspired oxygen fraction) table would be associated with better survival compared to nonadherence. Patients with ARDS, admitted directly from the Emergency Department to our 20-bed Medical Intensive Care Unit (ICU) from August 2016 to July 2017, were retrospectively studied. To determine adherence to the low PEEP/FIO2 table, PEEP and FIO2 12 h after ICU admission were used, to reflect ventilator adjustments by ICU clinicians after initial stabilization. Logistic regression was used to analyze hospital mortality as an outcome with adherence to the low PEEP/FIO2 as the key independent variable, adjusted for age, APACHE II score, initial P/F ratio and initial systolic blood pressure. 138 patients with ARDS were analysed. Overall adherence to the low PEEP/FIO2 table was 75.4%. Among patients on LTVV, nonadherence to the low PEEP/FIO2 table was associated with increased mortality compared to adherence (adjusted odds ratio 4.10, 95% confidence interval 1.68–9.99, P = 0.002). Patient characteristics at baseline were not associated with adherence to the low PEEP/FIO2 table.

Prolonged Length of Stay in the Emergency Department and Mortality in Critically Ill Elderly Patients with Infections: A Retrospective Multicenter Study

Background

This study aimed at investigating whether the length of stay (LOS) in the emergency department (ED) is associated with mortality in elderly patients with infections admitted to the intensive care unit (ICU). Delayed admission to the ICU may be associated with adverse clinical outcomes in elderly patients with infections.

Methods

This was a retrospective study conducted with subjects over 65 years of age admitted to the ICU from 5 EDs. We recorded demographic data, clinical findings, initial laboratory results, and ED LOS. Outcomes were all-cause in-hospital mortality and hospital LOS. A multivariable regression model was applied to identify factors predictive of mortality.

Results

A total of 439 patients admitted to the ICU via the ED were included in this study, 132 (30.1%) of whom died in the hospital. The median (IQR) age was 78 (73, 83) years. In multivariable analysis, a history of malignancy (OR: 3.76; 95% CI: 1.88–7.52; p < 0.001), high lactate level (OR: 1.13; 95% CI: 1.01–1.27; p=0.039), and ED LOS (OR: 1.01; 95% CI: 1.00–1.02; p=0.039) were independent risk factors for all-cause in-hospital admission. Elderly patients with an ED LOS >12 hours had a longer hospital LOS (p=0.018), and those with an ED LOS > 24 hours had a longer hospital LOS and higher mortality rate (p=0.044,  p=0.008).

Conclusions

This study shows that prolonged ED LOS is independently associated with all-cause in-hospital mortality in elderly patients with infections requiring ICU admission. ED LOS should be considered in strategies to prevent adverse outcomes in elderly patients with infections who visit the ED.

Increased time from physiological derangement to critical care admission associates with mortality

Background

Rapid response systems aim to achieve a timely response to the deteriorating patient; however, the existing literature varies on whether timing of escalation directly affects patient outcomes. Prior studies have been limited to using ‘decision to admit’ to critical care, or arrival in the emergency department as ‘time zero’, rather than the onset of physiological deterioration. The aim of this study is to establish if duration of abnormal physiology prior to critical care admission [‘Score to Door’ (STD) time] impacts on patient outcomes.

Methods

A retrospective cross-sectional analysis of data from pooled electronic medical records from a multi-site academic hospital was performed. All unplanned adult admissions to critical care from the ward with persistent physiological derangement [defined as sustained high National Early Warning Score (NEWS) > / = 7 that did not decrease below 5] were eligible for inclusion. The primary outcome was critical care mortality. Secondary outcomes were length of critical care admission and hospital mortality. The impact of STD time was adjusted for patient factors (demographics, sickness severity, frailty, and co-morbidity) and logistic factors (timing of high NEWS, and out of hours status) utilising logistic and linear regression models.

Results

Six hundred and thirty-two patients were included over the 4-year study period, 16.3% died in critical care. STD time demonstrated a small but significant association with critical care mortality [adjusted odds ratio of 1.02 (95% CI 1.0–1.04, p = 0.01)]. It was also associated with hospital mortality (adjusted OR 1.02, 95% CI 1.0–1.04, p = 0.026), and critical care length of stay. Each hour from onset of physiological derangement increased critical care length of stay by 1.2%. STD time was influenced by the initial NEWS, but not by logistic factors such as out-of-hours status, or pre-existing patient factors such as co-morbidity or frailty.

Conclusion

In a strictly defined population of high NEWS patients, the time from onset of sustained physiological derangement to critical care admission was associated with increased critical care and hospital mortality. If corroborated in further studies, this cohort definition could be utilised alongside the ‘Score to Door’ concept as a clinical indicator within rapid response systems.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13054-021-03650-1.

Managing admission and discharge processes in intensive care units

The intensive care unit (ICU) is one of the most crucial and expensive resources in a health care system. While high fixed costs usually lead to tight capacities, shortages have severe consequences. Thus, various challenging issues exist: When should an ICU admit or reject arriving patients in general? Should ICUs always be able to admit critical patients or rather focus on high utilization? On an operational level, both admission control of arriving patients and demand-driven early discharge of currently residing patients are decision variables and should be considered simultaneously. This paper discusses the trade-off between medical and monetary goals when managing intensive care units by modeling the problem as a Markov decision process. Intuitive, myopic rule mimicking decision-making in practice is applied as a benchmark. In a numerical study based on real-world data, we demonstrate that the medical results deteriorate dramatically when focusing on monetary goals only, and vice versa. Using our model, we illustrate the trade-off along an efficiency frontier that accounts for all combinations of medical and monetary goals. Coming from a solution that optimizes monetary costs, a significant reduction of expected mortality can be achieved at little additional monetary cost.

Boarding of Critically Ill Patients in the Emergency Department

Supplemental Digital Content is available in the text.

Objectives:

Emergency department boarding is the practice of caring for admitted patients in the emergency department after hospital admission, and boarding has been a growing problem in the United States. Boarding of the critically ill has achieved specific attention because of its association with poor clinical outcomes. Accordingly, the Society of Critical Care Medicine and the American College of Emergency Physicians convened a Task Force to understand the implications of emergency department boarding of the critically ill. The objective of this article is to review the U.S. literature on (1) the frequency of emergency department boarding among the critically ill, (2) the outcomes associated with critical care patient boarding, and (3) local strategies developed to mitigate the impact of emergency department critical care boarding on patient outcomes.

Data Sources and Study Selection:

Review article.

Data Extraction and Data Synthesis:

Emergency department–based boarding of the critically ill patient is common, but no nationally representative frequency estimates has been reported. Boarding literature is limited by variation in the definitions used for boarding and variation in the facilities studied (boarding ranges from 2% to 88% of ICU admissions). Prolonged boarding in the emergency department has been associated with longer duration of mechanical ventilation, longer ICU and hospital length of stay, and higher mortality. Health systems have developed multiple mitigation strategies to address emergency department boarding of critically ill patients, including emergency department-based interventions, hospital-based interventions, and emergency department–based resuscitation care units.

Conclusions:

Emergency department boarding of critically ill patients was common and was associated with worse clinical outcomes. Health systems have generated a number of strategies to mitigate these effects. A definition for emergency department boarding is proposed. Future work should establish formal criteria for analysis and benchmarking of emergency department–based boarding overall, with subsequent efforts focused on developing and reporting innovative strategies that improve clinical outcomes of critically ill patients boarded in the emergency department.

The Use of Head-Worn Displays for Vital Sign Monitoring in Critical and Acute Care: Systematic Review

Background

Continuous monitoring of patient vital signs may improve patient outcomes. Head-worn displays (HWDs) can provide hands-free access to continuous vital sign information of patients in critical and acute care contexts and thus may reduce instances of unrecognized patient deterioration.

Objective

The purpose of the study is to conduct a systematic review of the literature to evaluate clinical, surrogate, and process outcomes when clinicians use HWDs for continuous patient vital sign monitoring.

Methods

The review was registered with PROSPERO (CRD42019119875) and followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines. A literature search was conducted for articles published between January 1995 and June 2020 using the following databases: PubMed, Embase, CINAHL, PsycINFO, and Web of Science. Overall, 2 reviewers independently screened titles and abstracts and then assessed the full text of the articles. Original research articles that evaluated the clinical, surrogate, or process outcomes of head-mounted displays for continuous vital sign monitoring in critical care or acute care contexts were included.

Results

Of the 214 records obtained, 15 (7%) articles met the predefined criteria and were included in this review. Of the 15 studies, 7 (47%) took place in a clinical context, whereas the remainder took place in a simulation environment. In 100% (7/7) of the studies that evaluated gaze behavior, changes were found in gaze direction with HWDs. Change detection improvements were found in 67% (2/3) of the studies evaluating changes in the participants’ ability to detect changes in vital signs. Of the 10 studies assessing the ease of use of the HWD, most participants of 7 (70%) studies reported that the HWD was easy to use. In all 6 studies in which participants were asked if they would consider using the HWD in their practice, most participants responded positively, but they often suggested improvements on the HWD hardware or display design. Of the 7 studies conducted in clinical contexts, none reported any clinical outcomes.

Conclusions

Although there is limited and sometimes conflicting evidence about the benefits of HWDs from certain surrogate and process outcomes, evidence for clinical outcomes is lacking. Recommendations are to employ user-centered design when developing HWDs, perform longitudinal studies, and seek clinical outcomes.

Trial Registration

PROSPERO International Prospective Register of Systematic Reviews CRD42019119875; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=119875

Survival and predictors of mortality among patients admitted to the intensive care units in southern Ethiopia: A multi-center cohort study

BACKGROUND

The burden of life-threatening conditions requiring intensive care units has grown substantially in low-income countries related to an emerging pandemic, urbanization, and hospital expansion. The rate of ICU mortality varied from region to region in Ethiopia. However, the body of evidence on ICU mortality and its predictors is uncertain. This study was designed to investigate the pattern of disease and predictors of mortality in Southern Ethiopia.

METHODS

After obtaining ethical clearance from the Institutional Review Board (IRB), a multi-center cohort study was conducted among three teaching referral hospital ICUs in Ethiopia from June 2018 to May 2020. Five hundred and seventeen Adult ICU patients were selected. Data were entered in Statistical Package for Social Sciences version 22 and STATA version 16 for analysis. Descriptive statistics were run to see the overall distribution of the variables. Chi-square test and odds ratio were determined to identify the association between independent and dependent variables. Multivariate analysis was conducted to control possible confounders and identify independent predictors of ICU mortality.

RESULTS

The mean (±SD) of the patients admitted in ICU was 34.25(±5.25). The overall ICU mortality rate was 46.8%. The study identified different independent predictors of mortality. Patients with cardiac arrest were approximately 12 times more likely to die as compared to those who didn't, AOR = 11.9(95% CI:6.1 to 23.2).

CONCLUSION

The overall mortality rate in ICU was very high as compared to other studies in Ethiopia as well as globally which entails a rigorous activity from different stakeholders.