One-year survival and resource use after critical illness: impact of organ failure and residual organ dysfunction in a cohort study in Brazil

Differences in the relative importance of predictors of short- and long-term mortality among critically ill patients with cancer

OBJECTIVE

To identify the relative importance of several clinical variables present at intensive care unit admission on the short- and long-term mortality of critically ill patients with cancer after unplanned intensive care unit admission.

METHODS

This was a retrospective cohort study of patients with cancer with unplanned intensive care unit admission from January 2017 to December 2018. We developed models to analyze the relative importance of well-known predictors of mortality in patients with cancer admitted to the intensive care unit compared with mortality at 28, 90, and 360 days after intensive care unit admission, both in the full cohort and stratified by the type of cancer when the patient was admitted to the intensive care unit.

RESULTS

Among 3,592 patients, 3,136 (87.3%) had solid tumors, and metastatic disease was observed in 60.8% of those patients. A total of 1,196 (33.3%), 1,738 (48.4%), and 2,435 patients (67.8%) died at 28, 90, and 360 days, respectively. An impaired functional status was the greatest contribution to mortality in the short term for all patients and in the short and long term for the subgroups of patients with solid tumors. For patients with hematologic malignancies, the use of mechanical ventilation was the most important variable associated with mortality in all study periods. The SOFA score at admission was important for mortality prediction only for patients with solid metastatic tumors and hematological malignancies. The use of vasopressors and renal replacement therapy had a small importance in predicting mortality at every time point analyzed after the SOFA score was accounted for.

CONCLUSION

Healthcare providers must consider performance status, the use of mechanical ventilation, and the severity of illness when discussing prognosis, preferences for care, and end-of-life care planning with patients or their families during intensive care unit stays.

Rehabilitation and Social Determinants of Health in Critical Illness Recovery Literature: A Systematic Review

OBJECTIVES

Patients who survive critical illness navigate arduous and disparate recovery pathways that include referrals and participation in community-based rehabilitation services. Examining rehabilitation pathways during recovery is crucial to understanding the relationship on patient-centered outcomes. Furthermore, an understanding of social determinants of health (SDOH) in relation to outcomes and rehabilitation use will help ensure equitable access for future care. Therefore, there is a need to define and understand patient care pathways, specifically rehabilitation after discharge, through a SDOH lens after surviving a critical illness to improve long-term outcomes.

DATA SOURCES

MEDLINE, PubMed, Web of Science Core Collection (Clarivate), the CINAHL, and the Physiotherapy Evidence Database.

STUDY SELECTION AND DATA EXTRACTION

A systematic review of the literature was completed examining literature from inception to March 2024. Articles were included if post-hospital rehabilitation utilization was reported in adult patients who survived critical illness. Discharge disposition was examined as a proxy for rehabilitation pathways. Patients were grouped by patient diagnosis for grouped analysis and reporting of data. Two independent researchers reviewed manuscripts for inclusion and data were extracted by one reviewer using Covidence. Both reviewers used the Newcastle-Ottawa Scale to assess risk of bias.

DATA SYNTHESIS

Of 72 articles included, only four articles reported detailed rehabilitation utilization. The majority of the studies included were cohort studies (91.7%) with most articles using a retrospective design (56.9%). The most common patient population was acute respiratory diagnoses (51.4%). Most patients were discharged directly home from the hospital (75.4%). Race/ethnicity was the most frequently reported SDOH (43.1%) followed by insurance status (13.9%) and education (13.9%).

CONCLUSIONS

The small number of articles describing rehabilitative utilization allows for limited understanding of rehabilitation pathways following critical illness. The reporting of detailed rehabilitation utilization and SDOH are limited in the literature but may play a vital role in the recovery and outcomes of survivors of critical illness.

Patterns of Healthcare Resource Utilisation of Critical Care Survivors between 2006 and 2017 in Wales: A Population-Based Study

In this retrospective cohort study, we used the Secure Anonymised Information Linkage (SAIL) Databank to characterise and identify predictors of the one-year post-discharge healthcare resource utilisation (HRU) of adults who were admitted to critical care units in Wales between 1 April 2006 and 31 December 2017. We modelled one-year post-critical-care HRU using negative binomial models and used linear models for the difference from one-year pre-critical-care HRU. We estimated the association between critical illness and post-hospitalisation HRU using multilevel negative binomial models among people hospitalised in 2015. We studied 55,151 patients. Post-critical-care HRU was 11-87% greater than pre-critical-care levels, whereas emergency department (ED) attendances decreased by 30%. Age ≥50 years was generally associated with greater post-critical-care HRU; those over 80 had three times longer hospital readmissions than those younger than 50 (incidence rate ratio (IRR): 2.96, 95% CI: 2.84, 3.09). However, ED attendances were higher in those younger than 50. High comorbidity was associated with 22-62% greater post-critical-care HRU than no or low comorbidity. The most socioeconomically deprived quintile was associated with 24% more ED attendances (IRR: 1.24 [1.16, 1.32]) and 13% longer hospital stays (IRR: 1.13 [1.09, 1.17]) than the least deprived quintile. Critical care survivors had greater 1-year post-discharge HRU than non-critical inpatients, including 68% longer hospital stays (IRR: 1.68 [1.63, 1.74]). Critical care survivors, particularly those with older ages, high comorbidity, and socioeconomic deprivation, used significantly more primary and secondary care resources after discharge compared with their baseline and non-critical inpatients. Interventions are needed to ensure that key subgroups are identified and adequately supported.

Mechanisms of Post-critical Illness Cardiovascular Disease

Prolonged critical care stays commonly follow trauma, severe burn injury, sepsis, ARDS, and complications of major surgery. Although patients leave critical care following homeostatic recovery, significant additional diseases affect these patients during and beyond the convalescent phase. New cardiovascular and renal disease is commonly seen and roughly one third of all deaths in the year following discharge from critical care may come from this cluster of diseases. During prolonged critical care stays, the immunometabolic, inflammatory and neurohumoral response to severe illness in conjunction with resuscitative treatments primes the immune system and parenchymal tissues to develop a long-lived pro-inflammatory and immunosenescent state. This state is perpetuated by persistent Toll-like receptor signaling, free radical mediated isolevuglandin protein adduct formation and presentation by antigen presenting cells, abnormal circulating HDL and LDL isoforms, redox and metabolite mediated epigenetic reprogramming of the innate immune arm (trained immunity), and the development of immunosenescence through T-cell exhaustion/anergy through epigenetic modification of the T-cell genome. Under this state, tissue remodeling in the vascular, cardiac, and renal parenchymal beds occurs through the activation of pro-fibrotic cellular signaling pathways, causing vascular dysfunction and atherosclerosis, adverse cardiac remodeling and dysfunction, and proteinuria and accelerated chronic kidney disease.

Hospital re-admission after critical care survival: a systematic review and meta-analysis

Survivors of critical illness frequently require increased healthcare resources after hospital discharge. We undertook a systematic review and meta-analysis to assess hospital re-admission rates following critical care admission and to explore potential re-admission risk factors. We searched the MEDLINE, Embase and CINAHL databases on 05 March 2020. Our search strategy incorporated controlled vocabulary and text words for hospital re-admission and critical illness, limited to the English language. Two reviewers independently applied eligibility criteria and assessed quality using the Newcastle Ottawa Score checklist and extracted data. The primary outcome was acute hospital re-admission in the year after critical care discharge. Of the 8851 studies screened, 87 met inclusion criteria and 41 were used within the meta-analysis. The analysis incorporated data from 3,897,597 patients and 741,664 re-admission episodes. Pooled estimates for hospital re-admission after critical illness were 16.9% (95%CI: 13.3-21.2%) at 30 days; 31.0% (95%CI: 24.3-38.6%) at 90 days; 29.6% (95%CI: 24.5-35.2%) at six months; and 53.3% (95%CI: 44.4-62.0%) at 12 months. Significant heterogeneity was observed across included studies. Three risk factors were associated with excess acute care rehospitalisation one year after discharge: the presence of comorbidities; events during initial hospitalisation (e.g. the presence of delirium and duration of mechanical ventilation); and subsequent infection after hospital discharge. Hospital re-admission is common in survivors of critical illness. Careful attention to the management of pre-existing comorbidities during transitions of care may help reduce healthcare utilisation after critical care discharge. Future research should determine if targeted interventions for at-risk critical care survivors can reduce the risk of subsequent rehospitalisation.

Frailty assessed by administrative tools and mortality in patients with pneumonia admitted to the hospital and ICU in Wales

The ideal method of identifying frailty is uncertain, and data on long-term outcomes is relatively limited. We examined frailty indices derived from population-scale linked data on Intensive Care Unit (ICU) and hospitalised non-ICU patients with pneumonia to elucidate the influence of frailty on mortality. Longitudinal cohort study between 2010-2018 using population-scale anonymised data linkage of healthcare records for adults admitted to hospital with pneumonia in Wales. Primary outcome was in-patient mortality. Odds Ratios (ORs [95% confidence interval]) for age, hospital frailty risk score (HFRS), electronic frailty index (eFI), Charlson comorbidity index (CCI), and social deprivation index were estimated using multivariate logistic regression models. The area under the receiver operating characteristic curve (AUC) was estimated to determine the best fitting models. Of the 107,188 patients, mean (SD) age was 72.6 (16.6) years, 50% were men. The models adjusted for the two frailty indices and the comorbidity index had an increased odds of in-patient mortality for individuals with an ICU admission (ORs for ICU admission in the eFI model 2.67 [2.55, 2.79], HFRS model 2.30 [2.20, 2.41], CCI model 2.62 [2.51, 2.75]). Models indicated advancing age, increased frailty and comorbidity were also associated with an increased odds of in-patient mortality (eFI, baseline fit, ORs: mild 1.09 [1.04, 1.13], moderate 1.13 [1.08, 1.18], severe 1.17 [1.10, 1.23]. HFRS, baseline low, ORs: intermediate 2.65 [2.55, 2.75], high 3.31 [3.17, 3.45]). CCI, baseline < 1, ORs: '1-10' 1.15 [1.11, 1.20], > 10 2.50 [2.41, 2.60]). For predicting inpatient deaths, the CCI and HFRS based models were similar, however for longer term outcomes the CCI based model was superior. Frailty and comorbidity are significant risk factors for patients admitted to hospital with pneumonia. Frailty and comorbidity scores based on administrative data have only moderate ability to predict outcome.

Changes in the incidence and outcome of multiple organ failure in emergency non-cardiac surgical admissions: a 10-year retrospective observational study

BACKGROUND

During the past decades, epidemiologic data of independent predictors of multiple organ failure (MOF), incidence, and mortality have changed. The aim of the study was to assess the potential changes in the incidence and outcomes of MOF for one decade (2008-2017). In addition, resource utilization was considered.

METHODS

Patients were eligible for inclusion if they were adults, admitted to the ICU between January 1, 2008 and December 31, 2017, and had complete data sets regarding MOF. MOF was defined as organ failure separately with and without central nervous system (CNS) failure. The onset of MOF was defined as being early (≤48 h of ICU admission) and late (>48 h after ICU admission).

RESULTS

Of a total of 13,270 patients enclosed in this study, 44.6% of the patients developed MOF with and 31.4% without CNS failure. MOF-related mortality decreased in patients with (adjusted IRR 0.972 [95% CI 0.948 to 0.996], P=0.022) and without (adjusted IRR 0.957 [95% CI 0.931 to 0.983], P=0.0013) CNS failure. In addition, the incidence (adjusted IRR 0.970 [95% CI 0.950 to 0.991], P=0.006) and mortality (adjusted IRR 0.968 [95% CI 0.940 to 0.996], P=0.025) of early-onset MOF decreased, while the incidence and mortality of late-onset MOF remained constant. The length of ICU (P=0.024) and hospital (P=0.032) stays decreased while the length of mechanical ventilation remained constant (P=0.41).

CONCLUSIONS

Despite all improvements in intensive care during the last decades, the incidence of late-onset MOF remains a resource-intensive, morbid, and lethal condition. More research on etiologies, signs of organ failure, and where and when to start treatment is needed to improve the prognosis of late-onset MOF.

Long-term mortality in very old patients with cancer admitted to intensive care unit: A retrospective cohort study

BACKGROUND

Long-term outcomes of older patients referred to intensive care unit (ICU) are of paramount importance for care planning and counseling of patients and relatives.

METHODS

We performed a retrospective study with patients aged ≥80 years admitted to ICU from 2011 to 2017 in a cancer center. We performed two Cox proportional hazard regressions. In the first, we tested whether type of cancer (solid locoregional, solid metastatic or hematologic), Eastern Cooperative Oncology Group Performance Status (ECOG PS), and comorbidities [Charlson Comorbidity Index - CCI]) were associated with one-year mortality in all patients. In the second, we assessed whether delirium, use of vasopressors, mechanical ventilation, renal replacement therapy, and forgoing life-sustaining therapies were associated with one-year mortality in survivors to hospital discharge.

RESULTS

Of 763 patients included, 482 (62.3%) patients died at one year. Metastatic cancer was significantly associated with one-year mortality (HR = 1.97; CI 95%, 1.16-3.36), but hematologic cancer, CCI and ECOG PS were not. Among patients who survived to hospital discharge, delirium, use of vasopressors, mechanical ventilation, renal replacement therapy and decisions to forgo life-sustaining therapies in ICU were not associated with one-year mortality.

CONCLUSIONS

Metastatic disease at ICU admission was associated with one-year mortality in patients aged ≥80 years. Delirium, use of vasopressors, mechanical ventilation and renal replacement therapy and decisions to forgo life-sustaining therapies in ICU were not associated with one-year mortality among the patients discharged from hospital.

Avaliação psicológica de pacientes após a alta da unidade de terapia intensiva

A maioria dos pacientes sobrevive ao episódio de doença crítica, contudo, muitos deles podem desenvolver alterações psicológicas após a alta desta unidade. Dada a natureza dos cuidados intensivos e as condições clínicas da maioria dos pacientes esta pesquisa tem como objetivo descrever os resultados da avaliação psicológica de pacientes três meses após a alta dos cuidados críticos. Foram avaliados 160 pacientes, no entanto, devido ao comprometimento neurológico apenas 137 conseguiram responder à avaliação psicológica. Os instrumentos utilizados foram: Planilha para coleta de dados do prontuário, instrumento de avaliação de memórias de UTI, Impact of Event Scale-Revised (IES-R) e Escala Hospitalar de Ansiedade e Depressão (HADS). Os resultados revelaram que a identificação precoce das complicações inerentes ao tratamento crítico poderá trazer benefícios para a prevenção de alterações emocionais/físicas crônicas subsequentes.

Prevalence of organ failure and mortality among patients in the emergency department: a population-based cohort study

OBJECTIVES

The aim was to describe population-based incidence and emergency department-based prevalence and 1-year all-cause mortality of patients with new organ failure present at arrival.

DESIGN

This was a population-based cohort study of all citizens in four municipalities (population of 230 000 adults).

SETTING

Emergency department at Odense University Hospital, Denmark.

PARTICIPANTS

We included all adult patients who arrived from 1 April 2012 to 31 March 2015.

PRIMARY AND SECONDARY OUTCOME MEASURES

Organ failure was defined as a modified Sequential Organ Failure Assessment score≥2 within six possible organ systems: cerebral, circulatory, renal, respiratory, hepatic and coagulation.The primary outcome was prevalence of organ failure, and secondary outcomes were 0-7 days, 8-30 days and 31-365 days all-cause mortality.

RESULTS

We identified in total 175 278 contacts, of which 70 399 contacts were further evaluated for organ failure. Fifty-two per cent of these were women, median age 62 (IQR 42-77) years. The incidence of new organ failure was 1342/100 000 person-years, corresponding to 5.2% of all emergency department contacts.The 0-7-day, 8-30-day and 31-365-day mortality was 11.0% (95% CI: 10.2% to 11.8%), 5.6% (95% CI: 5.1% to 6.2%) and 13.2% (95% CI: 12.3% to 14.1%), respectively, if the patient had one or more new organ failures at first contact in the observation period, compared with 1.4% (95% CI: 1.3% to 1.6%), 1.2% (95% CI: 1.1% to 1.3%) and 5.2% (95% CI: 5.0% to 5.4%) for patients without. Seven-day mortality ranged from hepatic failure, 6.5% (95% CI: 4.9% to 8.6%), to cerebral failure, 33.8% (95% CI: 31.0% to 36.8%), the 8-30-day mortality ranged from cerebral failure, 3.9% (95% CI: 2.8% to 5.3%), to hepatic failure, 8.6% (95% CI: 6.6% to 10.8%) and 31-365-day mortality ranged from cerebral failure, 9.3% (95% CI: 7.6% to 11.2%), to renal failure, 18.2% (95% CI: 15.5% to 21.1%).

CONCLUSIONS

The study revealed an incidence of new organ failure at 1342/100 000 person-years and a prevalence of 5.2% of all emergency department contacts. One-year all-cause mortality was 29.8% among organ failure patients.

Risk Factors for 1-Year Mortality and Hospital Utilization Patterns in Critical Care Survivors: A Retrospective, Observational, Population-Based Data Linkage Study

OBJECTIVES

Clear understanding of the long-term consequences of critical care survivorship is essential. We investigated the care process and individual factors associated with long-term mortality among ICU survivors and explored hospital use in this group.

DESIGN

Population-based data linkage study using the Secure Anonymised Information Linkage databank.

SETTING

All ICUs between 2006 and 2013 in Wales, United Kingdom.

PATIENTS

We identified 40,631 patients discharged alive from Welsh adult ICUs.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Primary outcome was 365-day survival. The secondary outcomes were 30- and 90-day survival and hospital utilization in the 365 days following ICU discharge. Kaplan-Meier curves were plotted to compare survival rates. Cox proportional hazards regression models were used to determine risk factors of mortality. Seven-thousand eight-hundred eighty-three patients (19.4%) died during the 1-year follow-up period. In the multivariable Cox regression analysis, advanced age and comorbidities were significant determinants of long-term mortality. Expedited discharge due to ICU bed shortage was associated with higher risk. The rate of hospitalization in the year prior to the critical care admission was 28 hospitalized days/1,000 d; post critical care was 88 hospitalized days/1,000 d for those who were still alive; and 57 hospitalized days/1,000 d and 412 hospitalized days/1,000 d for those who died by the end of the study, respectively.

CONCLUSIONS

One in five ICU survivors die within 1 year, with advanced age and comorbidity being significant predictors of outcome, leading to high resource use. Care process factors indicating high system stress were associated with increased risk. More detailed understanding is needed on the effects of the potentially modifiable factors to optimize service delivery and improve long-term outcomes of the critically ill.

Nighttime intensive care unit discharge and outcomes: A propensity matched retrospective cohort study

Background

Nighttime ICU discharge, i.e., discharge from the ICU during the night hours, has been associated with increased readmission rates, hospital length of stay (LOS) and in-hospital mortality. We sought to determine the frequency of nighttime ICU discharge and identify whether nighttime ICU discharge is associated with worse outcomes in a private adult ICU located in Brazil.

Methods

Post hoc analysis of a cohort study addressing the effect of ICU readmissions on outcomes. This retrospective, single center, propensity matched cohort study was conducted in a medical-surgical ICU located in a private tertiary care hospital in São Paulo, Brazil. Based on time of transfer, patients were categorized into nighttime (7:00 pm to 6:59 am) and daytime (7:00 am to 6:59 pm) ICU discharge and were propensity-score matched at a 1:2 ratio. The primary outcome of interest was in–hospital mortality.

Results

Among 4,313 eligible patients admitted to the ICU between June 2013 and May 2015, 1,934 patients were matched at 1:2 ratio [649 (33.6%) nighttime and 1,285 (66.4%) daytime discharged patients]. The median (IQR) cohort age was 66 (51–79) years and SAPS III score was 43 (33–55). In-hospital mortality was 6.5% (42/649) in nighttime compared to 5.6% (72/1,285) in daytime discharged patients (OR, 1.17; 95% CI, 0.79 to 1.73; p = 0.444). While frequency of ICU readmission (OR, 0.95; 95% CI, 0.78 to 1.29; p = 0.741) and length of hospital stay did not differ between the groups, length of ICU stay was lower in nighttime compared to daytime ICU discharged patients [1 (1–3) days vs. 2 (1–3) days, respectively, p = 0.047].

Conclusion

In this propensity-matched retrospective cohort study, time of ICU discharge did not affect in-hospital mortality.

Prevalence and prognosis of acutely ill patients with organ failure at arrival to hospital: A systematic review

Introduction

Patients in an emergency department are diverse. Some are more seriously ill than others and some even arrive in multi-organ failure. Knowledge of the prevalence of organ failure and its prognosis in unselected patients is important from a diagnostic, hospital planning, and from a quality evaluation point of view, but is not reported systematically.

Objectives

To analyse the prevalence and prognosis of new onset organ failure in unselected acute patients at arrival to hospital.

Methods

A systematic review of studies of prevalence and prognosis of acutely ill patients with organ failure at arrival to hospital. We searched PubMed, Cochrane Library, Embase and Cinahl, and read references in included studies. Two authors decided independently on study eligibility and extracted data. Results were summarised qualitatively.

Results

Four studies were included with a total of 678,960 patients. The number of different organ failures reported in the studies ranged from one to six, and the settings were emergency departments and wards. The definitions of organ failure varied between studies. The prevalence of organ failure was 7%, 14%, 14%, and 23%, and in-hospital mortality was 5%, 11% and 15% respectively. The relative risk of in-hospital mortality for patients with organ failure compared to patients without organ failure varied from 2.58 to 8.65. Numbers of organ failures per 1,000 visits varied from 71 to 256.

Conclusion

The results of this review indicate that clinicians have good reasons to be alert when a patient arrives to the emergency department; as a state of organ failure seems both frequent and highly severe.

However, most studies identified were performed in patients after a diagnosis was established, and only very few studies were performed in unselected patients.

Systematic review registration number

PROSPERO: CRD42017060871.

Increased risk of death and readmission after hospital discharge of critically ill patients in a developing country: a retrospective multicenter cohort study

PURPOSE

To describe long-term mortality and hospital readmissions of patients admitted to Brazilian intensive care units (ICU).

METHODS

Retrospective cohort study of adult patients admitted to Brazilian hospitals affiliated to the Public Healthcare System from 10 state capitals. ICU patients were paired to non-ICU patients by frequency matching (ratio 1:2), according to postal code and admission semester. Hospitalization records were linked through deterministic linkage to national mortality data. Primary outcome was mortality up to 1 year. Other outcomes were mortality and readmissions at 30 and 90 days and 3 years. Multiple Cox regressions were used adjusting for age, sex, cancer diagnosis, type of hospital, and surgical status.

RESULTS

We included 324,594 patients (108,302 ICU and 216,292 non-ICU). ICU patients had increased hospital length of stay [9 (5-17) vs. 3 (1-6) days, p < 0.001] and mortality (18.5 vs. 3.6%, p < 0.001) versus non-ICU patients. One year after discharge, ICU patients were more frequently readmitted to hospital (25.4 vs. 17.4%, p < 0.001) and to ICU (31.4 vs. 7.3%, p < 0.001) than controls. Mortality up to 1 year was also higher for ICU patients (14.3 vs. 3.9%, p < 0.001). A significant interaction between surgical status and mortality was found, with adjusted hazard ratios (HRs) up to 1 year of 2.7 [95% confidence interval (CI) 2.5-2.9] for surgical patients, and 3.4 (95%CI 3.3-3.5) for medical patients. The risk for death and readmission diminished over time up to 3 years.

CONCLUSIONS

In a public healthcare system of a developing country, ICU patients have excessive long-term mortality and frequent readmissions. The ICU burden tended to reduce over time after hospital discharge.

Prognostic performance of Emergency Severity Index (ESI) combined with qSOFA score

OBJECTIVE

We conducted this study to investigate whether ESI combined with qSOFA score (ESI+qSOFA) predicts hospital outcome better than ESI alone in the emergency department (ED).

METHODS

This was a retrospective study for patients aged over 15years who visited an ED of a tertiary referral hospital from January 1st, 2015 to December 31st, 2015. We calculated and compared predictive performances of ESI alone and ESI+qSOFA for prespecified outcomes. The primary outcome was hospital mortality, and the secondary outcome was composite outcome of in-hospital mortality and ICU admission. We calculated in-hospital mortality rates by positive qSOFA in each subgroup divided according to ESI levels (1, 2, 3, 4+5).

RESULTS

43,748 patients were enrolled. The area under receiver-operating characteristics curves were higher in ESI+qSOFA than in ESI alone for both mortality and composite outcome (0.786 vs. 0.777, P<.001 for mortality; 0.778 vs. 0.774, P<.001 for composite outcome). In each subgroup divided by ESI levels, patients with positive qSOFA had significantly higher in-hospital mortality rate compared to those with negative qSOFA (20.4% vs. 14.7%, P=.117 in ESI level 1 subgroup; 11.3% vs. 2.7%, P=.001 in ESI level 2 subgroup; 2.3% vs. 0.4%, P<.001 in ESI level 3 subgroup; 0.0% vs. 0.0% in ESI level 4 or 5 subgroup).

CONCLUSION

The prognostic performance of ESI+qSOFA for in-hospital mortality was significantly higher than that of ESI alone. Within each subgroup, patients with positive qSOFA had higher in-hospital mortality compared to those with negative qSOFA.

Biomarkers as predictors of mortality in critically ill patients with solid tumors

Biochemical markers produced by the affected organ or body in response to disease have gained high clinical value due to assess disease development and being excellent predictors of morbidity and mortality. The aim of this study is to analyze different biochemical markers in critically cancer patients and to determine which of them can be used as predictors of mortality. This is a prospective, cross-sectional study conducted at a University Hospital in Porto Alegre - RS. Screening was done to include patients in the study. Serum biochemical markers obtained in the first 24 hours of Intensive Care Unit hospitalization were analyzed. A second review of medical records occurred after three months objected to identify death or Unit discharged. A sample of 130 individuals was obtained (control group n = 65, study group n = 65). In the multivariate model, serum magnesium values ​​OR = 3.97 (1.17; 13.5), presence of neoplasia OR = 2.68 (95% CI 1.13; 6.37) and absence of sepsis OR = 0.31 (95% CI 0.12; 0.79) were robust predictors of mortality. The association of solid tumors, sepsis presence and alteration in serum magnesium levels resulted in an increased chance of mortality in critically ill patients.

Characteristics and Outcomes of Intensive Care Unit Survivors: Experience of a Multidisciplinary Outpatient Clinic in a Teaching Hospital

OBJECTIVES

To describe the experience of an outpatient clinic with the multidisciplinary evaluation of intensive care unit survivors and to analyze their social, psychological, and physical characteristics in a low-income population and a developing country.

METHODS

Retrospective cohort study. Adult survivors from a general intensive care unit were evaluated three months after discharge in a post-intensive care unit outpatient multidisciplinary clinic over a period of 6 years (2008-2014) in a University Hospital in southern Brazil.

RESULTS

A total of 688 out of 1945 intensive care unit survivors received care at the clinic. Of these, 45.2% had psychological disorders (particularly depression), 49.0% had respiratory impairments (abnormal spirometry), and 24.6% had moderate to intense dyspnea during daily life activities. Patients experienced weight loss during hospitalization (mean=11.7%) but good recovery after discharge (mean gain=9.1%), and 94.6% were receiving nutrition orally. One-third of patients showed a reduction of peripheral muscular strength, and 5.7% had moderate to severe tetraparesis or tetraplegia. There was a significant impairment in quality of life (SF-36), particularly in the physical and emotional aspects and in functional capacity. The economic impacts on the affected families, which were mostly low-income families, were considerable. Most patients did not have full access to rehabilitation services, even though half of the families were receiving financial support from the government.

CONCLUSIONS

A significant number of intensive care unit survivors evaluated 3 months after discharge had psychological, respiratory, motor, and socioeconomic problems; these findings highlight that strategies aimed to assist critically ill patients should be extended to the post-hospitalization period and that this problem is particularly important in low-income populations.

Prevalence and prognosis of acutely ill patients with organ failure at arrival to hospital: protocol for a systematic review

BACKGROUND

Acutely ill patients are a heterogeneous group, and some of these suffer from organ failure. As the prognosis of organ failure improves with early treatment, it is important to identify these patients as early as possible. Most studies on organ failure have been performed in intensive care settings, or on selected groups of patients, where a high prevalence and mortality have been reported. Before patients arrive to the intensive care unit, or the general ward, most of them have passed through the emergency department (ED), where diagnosis and treatment has been initiated. The prevalence and prognosis of acutely ill patients, with organ failure, at arrival have been studied in some selected groups, but methods and results differ. This systematic review aims to identify, summarize, and analyze studies of prevalence and prognosis of new onset organ failure in acutely ill undifferentiated patients, at arrival to hospital. The result of the review will assist physicians working in an ED, when assessing patients' risk of organ failure and their associated prognosis.

METHODS

The information sources used are electronic databases, PubMed, Cochrane Library, EMBASE, and CINAHL; references in included studies and review articles; and authors' personal files. One author will perform the title and abstract screening and exclude obviously ineligible studies. By an independent full-text screening, two authors will decide on the eligibility for the remaining studies. Eligible studies will include an unselected group of acutely ill adult patients at arrival to hospital, with one or more organ failures (respiratory, renal, cerebral, circulatory, hepatic, or coagulation failure). Included studies will have assessed the prevalence or prognosis, defined as mortality or ICU transfer, of new onset organ failure. From included studies, bibliographical and study description data, patient characteristics, and data related to prevalence of organ failure and prognosis will be extracted. We will assess risk of bias in included studies using the Quality in Prognosis Studies tool for prognostic studies and the Newcastle-Ottawa Scale for observational studies. We expect heterogeneity and to conduct a qualitative synthesis of the results. If, however, heterogeneity is low, we will conduct a random effects meta-analysis stratified by basic study design.

DISCUSSION

This review will summarize and analyze studies of prevalence and prognosis of acutely ill patients, with organ failure at arrival to hospital, assist ED physicians assessing the risk of organ failure in unselected patients, and guide recommendations for further research.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42017060871.

Critical illness among adults with cystic fibrosis in Texas, 2004-2013: Patterns of ICU utilization, characteristics, and outcomes

Objective

Available reports on critically ill adults with cystic fibrosis (CF) suggest improving short-term outcomes. However, there is marked heterogeneity in reported findings, with studies mostly based on single-centered data, limiting generalizability. We sought to examine population-level patterns of demand for critical care resources, and the characteristics, resource utilization, and outcomes of ICU-managed adults with CF.

Methods

We used the Texas Inpatient Public Use Data File to identify ICU admissions with CF aged ≥18 years in Texas between 2004–2013. We examined ICU utilization at population level (using CF Foundation annual reports) and, among ICU admissions, socio-demographic characteristics, burden of comorbidities, organ failure, life-support utilization and hospital disposition. Linear regression and multilevel logistic regression were used to examine temporal trends and predictors of short-term mortality (hospital death and discharge to hospice), respectively.

Results

Of 9,579 hospitalizations of adults with CF, 1,249 (13%) were admitted to ICU. The incidence of ICU admission among adults with CF in Texas increased between 2004–2005 and 2012–2013 from 16.7 to 19.2 per 100 person-years (p = 0.0181), with ICU admissions aged ≥30 years accounting for 80.3% of the change. Among ICU admissions the following changes were noted between 2004–2005 and 2012–2013: any organ failure 30.2% vs. 56.3% (p = 0.0004), mechanical ventilation 11.5% vs. 19.2% (p = 0.0216), and hemodialysis 1.0% vs. 8.1% (p = 0.0007). Short-term mortality for the whole cohort and for those with mechanical ventilation was 11.4% and 41.8%, respectively, with corresponding home discharge among survivors 84% and 62.1%, respectively. Key predictors (adjusted odds ratios [aOR (95% CI)]) of short-term mortality included age ≥45 years (2.051 [1.231–3.415]), female gender (1.907 [1.237–2.941]), and mechanical ventilation (7.982 [5.001–12.739]).

Conclusions

Adults with CF had high and rising population-level burden of critical illness. Although ICU admissions were increasingly older and sicker, the majority survived hospitalization, with most discharged home, supporting short-term benefits of critical care in the present cohort.

Five-Year Mortality and Hospital Costs Associated with Surviving Intensive Care

RATIONALE

Survivors of critical illness experience significant morbidity, but the impact of surviving the intensive care unit (ICU) has not been quantified comprehensively at a population level.

OBJECTIVES

To identify factors associated with increased hospital resource use and to ascertain whether ICU admission was associated with increased mortality and resource use.

METHODS

Matched cohort study and pre/post-analysis using national linked data registries with complete population coverage. The population consisted of patients admitted to all adult general ICUs during 2005 and surviving to hospital discharge, identified from the Scottish Intensive Care Society Audit Group registry, matched (1:1) with similar hospital control subjects. Five-year outcomes included mortality and hospital resource use. Confounder adjustment was based on multivariable regression and pre/post within-individual analyses.

MEASUREMENTS AND MAIN RESULTS

Of 7,656 ICU patients, 5,259 survived to hospital discharge (5,215 [99.2%] matched to hospital control subjects). Factors present before ICU admission (comorbidities/pre-ICU hospitalizations) were stronger predictors of hospital resource use than acute illness factors. In the 5 years after the initial hospital discharge, compared with hospital control subjects, the ICU cohort had higher mortality (32.3% vs. 22.7%; hazard ratio, 1.33; 95% confidence interval, 1.22-1.46; P < 0.001), used more hospital resources (mean hospital admission rate, 4.8 vs. 3.3/person/5 yr), and had 51% higher mean 5-year hospital costs ($25,608 vs. $16,913/patient). Increased resource use persisted after confounder adjustment (P < 0.001) and using pre/post-analyses (P < 0.001). Excess resource use and mortality were greatest for younger patients without significant comorbidity.

CONCLUSIONS

This complete, national study demonstrates that ICU survivorship is associated with higher 5-year mortality and hospital resource use than hospital control subjects, representing a substantial burden on individuals, caregivers, and society.

Admission factors associated with intensive care unit readmission in critically ill oncohematological patients: a retrospective cohort study

Objective

The purpose of our study was to determine the admission factors associated with intensive care unit readmission among oncohematological patients.

Methods

Retrospective cohort study using an intensive care unit database from a tertiary oncological center. The participants included 1,872 critically ill oncohematological patients who were admitted to the intensive care unit from January 2012 to December 2014 and who were subsequently discharged alive. We used univariate and multivariate analysis to identify the admission risk factors associated with later intensive care unit readmission.

Results

One hundred seventy-two patients (9.2% of 1,872 oncohematological patients discharged alive from the intensive care unit) were readmitted after intensive care unit discharge. The readmitted patients were sicker compared with the non-readmitted group and had higher hospital mortality (32.6% versus 3.7%, respectively; p < 0.001). In the multivariate analysis, the independent risk factors for intensive care unit readmission were male sex (OR: 1.5, 95% CI: 1.07 - 2.12; p = 0.019), emergency surgery as the admission reason (OR: 2.91, 95%CI: 1.53 - 5.54; p = 0.001), longer hospital length of stay before intensive care unit transfer (OR: 1.02, 95%CI: 1.007 - 1.035; p = 0.003), and mechanical ventilation (OR: 2.31, 95%CI: 1.57 - 3.40; p < 0.001).

Conclusions

In this cohort of oncohematological patients, we identified some risk factors associated with intensive care unit readmission, most of which are not amenable to interventions. The identification of risk factors at intensive care unit discharge might be a promising approach.

Short- and long-term prognosis of critically-ill patients referred to the ICU from the Emergency Department of a tertiary hospital

BACKGROUND AND OBJECTIVE

A frequent source of critically-ill patients admitted to the ICU is the Emergency Department. It is essential to analyse the short-term prognosis of these patients, but also their evolution after their discharge from the hospital, since this is one of the major concerns of these patients. The aim of this study is to describe the epidemiological characteristics of patients admitted to the ICU from the Emergency Department and to analyse their outcome.

PATIENTS AND METHOD

This consisted of an observational prospective cohorts study which included 269 Emergency Department patients consecutively admitted to the ICU over an 18-month period. Factors associated with hospital mortality were presented as an odds ratio (OR) and factors associated with long-term mortality were presented as a hazard ratio (HR). A P-value lower than .05 was accepted as significant. The overall survival was analysed on the basis of the Kaplan-Meier curves.

RESULTS

Hospital mortality was 15%, ICU complications where the variables with the greatest impact on short-term mortality: acute renal failure (OR 22.7) and respiratory distress syndrome (OR 51.2). After hospital discharge, the cumulative mortality at 12, 24 and 36 months was 6, 11 and 15%, respectively. The degree of functional dependence (HR 3.7), cancer (HR 3.4) and arrhythmias (HR 2.4) were factors related to long-term mortality.

CONCLUSIONS

The short-term outcome of ICU patients is related to age and comorbidity, but more significantly to the characteristics of the acute illness. However, the long-term outcome is more closely associated with the patients' characteristics.

The Deyo-Charlson and Elixhauser-van Walraven Comorbidity Indices as predictors of mortality in critically ill patients

OBJECTIVES

Our primary objective was to compare the utility of the Deyo-Charlson Comorbidity Index (DCCI) and Elixhauser-van Walraven Comorbidity Index (EVCI) to predict mortality in intensive care unit (ICU) patients.

SETTING

Observational study of 2 tertiary academic centres located in Boston, Massachusetts.

PARTICIPANTS

The study cohort consisted of 59,816 patients from admitted to 12 ICUs between January 2007 and December 2012.

PRIMARY AND SECONDARY OUTCOME

For the primary analysis, receiver operator characteristic curves were constructed for mortality at 30, 90, 180, and 365 days using the DCCI as well as EVCI, and the areas under the curve (AUCs) were compared. Subgroup analyses were performed within different types of ICUs. Logistic regression was used to add age, race and sex into the model to determine if there was any improvement in discrimination.

RESULTS

At 30 days, the AUC for DCCI versus EVCI was 0.65 (95% CI 0.65 to 0.67) vs 0.66 (95% CI 0.65 to 0.66), p=0.02. Discrimination improved at 365 days for both indices (AUC for DCCI 0.72 (95% CI 0.71 to 0.72) vs AUC for EVCI 0.72 (95% CI 0.72 to 0.72), p=0.46). The DCCI and EVCI performed similarly across ICUs at all time points, with the exception of the neurosciences ICU, where the DCCI was superior to EVCI at all time points (1-year mortality: AUC 0.73 (95% CI 0.72 to 0.74) vs 0.68 (95% CI 0.67 to 0.70), p=0.005). The addition of basic demographic information did not change the results at any of the assessed time points.

CONCLUSIONS

The DCCI and EVCI were comparable at predicting mortality in critically ill patients. The predictive ability of both indices increased when assessing long-term outcomes. Addition of demographic data to both indices did not affect the predictive utility of these indices. Further studies are needed to validate our findings and to determine the utility of these indices in clinical practice.