Assessment of risk factors for in-hospital mortality after intensive care unit discharge

Problems in care and avoidability of death after discharge from intensive care: a multi-centre retrospective case record review study

BACKGROUND

Over 138,000 patients are discharged to hospital wards from intensive care units (ICUs) in England, Wales and Northern Ireland annually. More than 8000 die before leaving hospital. In hospital-wide populations, 6.7-18% of deaths have some degree of avoidability. For patients discharged from ICU, neither the proportion of avoidable deaths nor the reasons underlying avoidability have been determined. We undertook a retrospective case record review within the REFLECT study, examining how post-ICU ward care might be improved.

METHODS

A multi-centre retrospective case record review of 300 consecutive post-ICU in-hospital deaths, between January 2015 and March 2018, in 3 English hospitals. Trained multi-professional researchers assessed the degree to which each death was avoidable and determined care problems using the established Structured Judgement Review method.

RESULTS

Agreement between reviewers was good (weighted Kappa 0.77, 95% CI 0.64-0.88). Discharge from an ICU for end-of-life care occurred in 50/300 patients. Of the remaining 250 patients, death was probably avoidable in 20 (8%, 95% CI 5.0-12.1) and had some degree of avoidability in 65 (26%, 95% CI 20.7-31.9). Common problems included out-of-hours discharge from ICU (168/250, 67.2%), suboptimal rehabilitation (167/241, 69.3%), absent nutritional planning (76/185, 41.1%) and incomplete sepsis management (50/150, 33.3%).

CONCLUSIONS

The proportion of deaths in hospital with some degree of avoidability is higher in patients discharged from an ICU than reported in hospital-wide populations. Extrapolating our findings suggests around 550 probably avoidable deaths occur annually in hospital following ICU discharge in England, Wales and Northern Ireland. This avoidability occurs in an elderly frail population with complex needs that current strategies struggle to meet. Problems in post-ICU care are rectifiable but multi-disciplinary.

TRIAL REGISTRATION

ISRCTN14658054.

After-Hours/Nighttime Transfers Out of the Intensive Care Unit and Patient Outcomes: A Systematic Review and Meta-Analysis

PURPOSE

We evaluated the effects of after-hours/nighttime patient transfers out of the ICU on patient outcomes, by performing a systematic review and meta-analysis (PROSPERO CRD 42017074082).

DATA SOURCES

MEDLINE, PubMed, EMBASE, Google Scholar, CINAHL, and the Cochrane Library from 1987-November 2019. Conference abstracts from the Society of Critical Care Medicine, American Thoracic Society, CHEST, Critical Care Canada Forum, and European Society of Intensive Care Medicine from 2011-2019.

DATA EXTRACTION

Observational or randomized studies of adult ICU patients were selected if they compared after-hours transfer out of the ICU to daytime transfer on patient outcomes. Case reports, case series, letters, and reviews were excluded. Study year, country, design, co-variates for adjustment, definitions of after-hours, mortality rates, ICU readmission rates, and hospital length of stay (LOS) were extracted.

DATA SYNTHESIS

We identified 3,398 studies. Thirty-one observational studies (1,418,924 patients) were selected for the systematic review and meta-analysis. Included studies had varying definitions of after-hours, with the after-hours period starting anytime between 16:00-22:00 and ending between 06:00-09:00. Approximately 16% of transfers occurred after-hours. After-hours transfers were associated with increased in-hospital mortality for both unadjusted (odds ratio [OR] 1.51, 95% confidence interval [CI] 1.30-1.75, I² = 96%, number of studies [n] = 26, P < 0.001, low certainty) and adjusted (OR 1.32, 95% CI 1.25-1.38, I ² = 33%, n = 10, P < 0.001, low certainty) data, compared to daytime transfers. They were also associated with increased ICU readmission (pooled unadjusted OR 1.28, 95% CI 1.18-1.38, I² = 85%, n = 17, P < 0.001, low certainty) and longer hospital LOS (standardized mean difference 0.13, 95% CI 0.09-0.18, I ² = 93%, n = 9, P < 0.001, low certainty), compared to daytime transfers.

CONCLUSIONS

After-hours transfers out of the ICU are associated with increased in-hospital mortality, ICU readmission, and hospital LOS, across many settings. While the certainty of evidence is low, future research is needed to reduce the number and effects of after-hours transfers.

Does delaying discharge from intensive care until after tracheostomy removal affect 30-day mortality? Propensity score matched cohort study

OBJECTIVE

To investigate the short-term mortality effect of discharge from an intensive care unit (ICU) with a tracheostomy in place in comparison to delaying discharge until after tracheostomy removal.

DESIGN

A propensity score matched cohort study using data from the TracMan study.

SETTING

Seventy-two UK ICUs taking part in the TracMan study, a randomised controlled trial comparing early tracheostomy (within 4 days of critical care admission) with deferred tracheostomy (after 10 days if still indicated).

PARTICIPANTS

622 patients who underwent a tracheostomy while in the TracMan study between November 2004 and November 2008. 144 patients left ICU with a tracheostomy. 999 days of observation from 294 patients were included in the control pool.

INTERVENTIONS

We matched patients discharged with a tracheostomy in place 1:1 with patients who remained in an ICU until either their tracheostomy was removed or they died with the tracheostomy in place. Propensity models were developed according to discharge destination, accounting for likely confounding factors.

PRIMARY OUTCOME MEASURE

The primary outcome was 30-day mortality from the matching day. For the 'discharged with a tracheostomy' group, this was death within 30 days after the discharge day. For the 'remained in ICU' group, this was death within 30 days after the matched day.

RESULTS

22 (15.3%) patients who left ICU with a tracheostomy died within 30 days compared with 26 (18.1%) who remained in ICU (relative risk 0.98, 95% CI 0.43 to 2.23).

CONCLUSION

Keeping patients on an ICU to provide tracheostomy care was not found to affect mortality. Tracheostomy presence may indicate a higher risk of mortality due to underlying diseases and conditions rather than posing a risk in itself.The TracMan trial was registered on the ISRCTN database (ISRCTN28588190).

Protocol for a mixed-methods exploratory investigation of care following intensive care discharge: the REFLECT study

INTRODUCTION

A substantial number of patients discharged from intensive care units (ICUs) subsequently die without leaving hospital. It is unclear how many of these deaths are preventable. Ward-based management following discharge from ICU is an area that patients and healthcare staff are concerned about. The primary aim of REFLECT (Recovery Following Intensive Care Treatment) is to develop an intervention plan to reduce in-hospital mortality rates in patients who have been discharged from ICU.

METHODS AND ANALYSIS

REFLECT is a multicentre mixed-methods exploratory study examining ward care delivery to adult patients discharged from ICU. The study will be made up of four substudies. Medical notes of patients who were discharged from ICU and subsequently died will be examined using a retrospective case records review (RCRR) technique. Patients and their relatives will be interviewed about their post-ICU care, including relatives of patients who died in hospital following ICU discharge. Staff involved in the care of patients post-ICU discharge will be interviewed about the care of this patient group. The medical records of patients who survived their post-ICU stay will also be reviewed using the RCRR technique. The analyses of the substudies will be both descriptive and use a modified grounded theory approach to identify emerging themes. The evidence generated in these four substudies will form the basis of the intervention development, which will take place through stakeholder and clinical expert meetings.

ETHICS AND DISSEMINATION

Ethical approval has been obtained through the Wales Research and Ethics Committee 4 (17/WA/0107). We aim to disseminate the findings through international conferences, international peer-reviewed journals and social media.

TRIAL REGISTRATION NUMBER

ISRCTN14658054.

suPAR in the assessment of post intensive care unit prognosis: a pilot study

OBJECTIVE

To determine the performance of soluble urokinase-type plasminogen activator receptor upon intensive care unit discharge to predict post intensive care unit mortality.

METHODS

A prospective observational cohort study was conducted during a 24-month period in an 8-bed polyvalent intensive care unit. APACHE II, SOFA, C-reactive protein, white cell count and soluble urokinase-type plasminogen activator receptor on the day of intensive care unit discharge were collected from patients who survived intensive care unit admission.

RESULTS

Two hundred and two patients were included in this study, 29 patients (18.6%) of whom died after intensive care unit discharge. Nonsurvivors were older and more seriously ill upon intensive care unit admission with higher severity scores, and nonsurvivors required extended use of vasopressors than did survivors. The area under the receiver operating characteristics curves of SOFA, APACHE II, C-reactive protein, white cell count, and soluble urokinase-type plasminogen activator receptor at intensive care unit discharge as prognostic markers of hospital death were 0.78 (95%CI 0.70 - 0.86); 0.70 (95%CI 0.61 - 0.79); 0.54 (95%CI 0.42 - 0.65); 0.48 (95%CI 0.36 - 0.58); and 0.68 (95%CI 0.58 - 0.78), respectively. SOFA was independently associated with a higher risk of in-hospital mortality (OR 1.673; 95%CI 1.252 - 2.234), 28-day mortality (OR 1.861; 95%CI 1.856 - 2.555) and 90-day mortality (OR 1.584; 95%CI 1.241 - 2.022).

CONCLUSION

At intensive care unit discharge, soluble urokinase-type plasminogen activator receptor is a poor predictor of post intensive care unit prognosis.

Out-of-hours discharge from intensive care, in-hospital mortality and intensive care readmission rates: a systematic review and meta-analysis

PURPOSE

Discharge from an intensive care unit (ICU) out of hours is common. We undertook a systematic review and meta-analysis to explore the association between time of discharge and mortality/ICU readmission.

METHODS

We searched Medline, Embase, Web of Knowledge, CINAHL, the Cochrane Library and OpenGrey to June 2017. We included studies reporting in-hospital mortality and/or ICU readmission rates by ICU discharge "out-of-hours" and "in-hours". Inclusion was limited to patients aged ≥ 16 years discharged alive from a non-specialist ICU to a lower level of hospital care. Studies restricted to specific diseases were excluded. We assessed study quality using the Newcastle Ottowa Scale. We extracted published data, summarising using a random-effects meta-analysis.

RESULTS

Our searches identified 1961 studies. We included unadjusted data from 1,191,178 patients from 18 cohort studies (presenting data from 1994 to 2014). "Out of hours" had multiple definitions, beginning between 16:00 and 22:00 and ending between 05:59 and 09:00. Patients discharged out of hours had higher in-hospital mortality [relative risk (95% CI) 1.39 (1.24, 1.57) p < 0.0001] and readmission rates [1·30 (1.19, 1.42), p < 0.001] than patients discharged in hours. Heterogeneity was high (I2 90.1% for mortality and 90.2% for readmission), resulting from differences in effect size rather than the presence of an effect.

CONCLUSIONS

Out-of-hours discharge from an ICU is strongly associated with both in-hospital death and ICU readmission. These effects persisted across all definitions of "out of hours" and across healthcare systems in different geographical locations. Whether these increases in mortality and readmission result from patient differences, differences in care, or a combination remains unclear.

Long-term treated intensive care patients outcomes: the one-year mortality rate, quality of life, health care use and long-term complications as reported by general practitioners

BACKGROUND

The purpose of this study was to determine the one-year mortality rate and its predictors regarding long-term intensive care-treated patients together with their health-related quality of life (HRQL), place of living, healthcare use and long-term complication characteristics after intensive care unit (ICU) discharge.

METHODS

A retrospective cohort study was performed in a 20-bed mixed ICU. The patients that were treated for more than 72 h between 2007 and 2012 were included in this study. The one-year mortality rate was calculated, and the characteristics of the ICU survivors that died within one year after ICU discharge were further analysed. For all patients, the Dutch version of the SF-36 questionnaire was used to assess their current HRQL. The results were compared with a normal population. Additionally, patients were questioned about their place of living, and their general practitioners (GPs) were questioned about the patients' possible long-term complications.

RESULTS

Seven hundred and forty patients were included in this study, and their one-year mortality rate was 28 %, of which half died within the first week after ICU discharge. The one-year mortality rate predictors included age at the time of ICU admission, APACHE IV-predicted mortality score, number of comorbidities and ICU re-admissions. The ICU survivor HRQL was significantly lower compared with the normal population. Half of the patients did not return to their pre-hospital place of living, and numerous possible long-term complications were reported, particularly decreased tolerance, chronic fatigue and processing problems of relatives.

CONCLUSIONS

One-year mortality rate of long-term ICU-treated patient was 28 %, and this was predicted by age, disease severity, comorbidities and ICU re-admissions. The ICU survivors reported a lower HRQL, and a minority of these patients returned home directly after hospital discharge; however, GPs reported numerous possible long-term complications.

Out-of-hours discharge from intensive care, in-hospital mortality and intensive care readmission rates: a systematic review protocol

BACKGROUND

Most patients are discharged from an intensive care unit with an expectation that they will survive their hospital stay, yet these patients have high subsequent in-hospital mortality. Patients are frequently discharged from an intensive care unit to a lower level of hospital care in the evenings and at night (out-of-hours). By affecting the care that patients receive, out-of-hours discharge may alter post-intensive care in-hospital mortality rates.

METHODS/DESIGN

Two searches will be conducted-the first a general search for all factors associated with post-intensive care in-hospital mortality and a second focused specifically on out-of-hours discharges. Searches will be performed in multiple databases, including Medline, Embase, Web of Knowledge, Cumulative Index of Nursing and Allied Health Literature (CINAHL) and the Cochrane Library. OpenGrey will also be searched, to ensure any unpublished 'grey' data are accessed. Language and date restrictions will not be applied. Assessment for inclusion and data extraction will be undertaken by two independent reviewers. Methodological quality will be assessed using the ACROBAT-NRSI tool. The primary outcome measure will be post-intensive care in-hospital mortality. To provide a clearer picture of this problem, studies reporting readmission to the intensive care unit (ICU) will also be included, even in the absence of report of in-hospital mortality. The primary outcome data will be synthesised and summarised using a random-effects meta-analysis. Where possible, subgroup meta-analyses will assess associated factors such as discharge destination, palliative care discharges and severity of illness scores.

DISCUSSION

To the best of our knowledge, a systematic review of the association of out-of-hours discharge with in-hospital mortality has never been undertaken. Synthesis of the available information is important because out-of-hours discharge remains common and, if associated with post-intensive care unit mortality, is highly amenable to system change.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42014010321.

A meta-analysis to derive literature-based benchmarks for readmission and hospital mortality after patient discharge from intensive care

Introduction

We sought to derive literature-based summary estimates of readmission to the ICU and hospital mortality among patients discharged alive from the ICU.

Methods

We searched MEDLINE, Embase, CINAHL and the Cochrane Central Register of Controlled Trials from inception to March 2013, as well as the reference lists in the publications of the included studies. We selected cohort studies of ICU discharge prognostic factors that in which readmission to the ICU or hospital mortality among patients discharged alive from the ICU was reported. Two reviewers independently abstracted the number of patients readmitted to the ICU and hospital deaths among patients discharged alive from the ICU. Fixed effects and random effects models were used to estimate the pooled cumulative incidence of ICU readmission and the pooled cumulative incidence of hospital mortality.

Results

The analysis included 58 studies (n = 2,073,170 patients). The majority of studies followed patients until hospital discharge (n = 46 studies) and reported readmission to the ICU (n = 46 studies) or hospital mortality (n = 49 studies). The cumulative incidence of ICU readmission was 4.0 readmissions (95% confidence interval (CI), 3.9 to 4.0) per 100 patient discharges using fixed effects pooling and 6.3 readmissions (95% CI, 5.6 to 6.9) per 100 patient discharges using random effects pooling. The cumulative incidence of hospital mortality was 3.3 deaths (95% CI, 3.3 to 3.3) per 100 patient discharges using fixed effects pooling and 6.8 deaths (95% CI, 6.1 to 7.6) per 100 patient discharges using random effects pooling. There was significant heterogeneity for the pooled estimates, which was partially explained by patient, institution and study methodological characteristics.

Conclusions

Using current literature estimates, for every 100 patients discharged alive from the ICU, between 4 and 6 patients on average will be readmitted to the ICU and between 3 and 7 patients on average will die prior to hospital discharge. These estimates can inform the selection of benchmarks for quality metrics of transitions of patient care between the ICU and the hospital ward.

Impact of infection on admission and of the process of care on mortality of patients admitted to the Intensive Care Unit: the INFAUCI study

A prospective, cohort, clinical, observational study was performed in 14 Intensive Care Units (ICUs) to evaluate the contemporary epidemiology, morbi-mortality and determinants of outcome of the population with an infection on admission. All 3766 patients admitted during a consecutive 12-month period were screened. Their median age was 63 [26-83], 61.1% were male and 69.8% had significant comorbidities. On admission to the ICU 1652 patients (43.9%) had an infection, which was community acquired in 68.2% (one-fifth with healthcare-associated criteria) and ward-acquired in the others. Roughly half presented to the ICU with septic shock. As much as 488 patients with community-acquired infections were deemed stable enough to be first admitted to the ward, but had similar mortality to unstable patients directly admitted to the ICU (35.9% vs. 35.1%, p 0.78). Only 48.3% of this infected population had microbiological documentation and almost one-quarter received inappropriate initial antibiotic therapy. This, along with comorbidities, was a main determinant of mortality. Overall, infected patients on admission had higher mortality both in the ICU (28.0% vs. 19.9%, p <0.001) and in the hospital (38.2% vs. 27.5%, p <0.001) and even after being discharged to the ward (14.2% vs. 9.6%, p <0.001). Also, patients not infected on admission who acquired an infection in the ICU, had an increased risk of dying in the hospital (odds ratio 1.41 [1.12-1.83]). Consequently, infection, regardless of its place of acquisition, was associated with increased mortality. Improving the process of care, especially first-line antibiotic appropriateness, and preventing ICU-acquired infections, may lead to better outcomes.

Eosinopenia as a predictor of unexpected re-admission and mortality after intensive care unit discharge

Predicting unexpected intensive care unit (ICU) re-admission and mortality after critical illness is difficult. This study assessed the associations between eosinopenia on the day of ICU discharge and outcomes after critical illness. This retrospective cohort study involved a total of 1446 critically ill patients who survived their first ICU admission between January 2009 and March 2010 in a multidisciplinary ICU in Western Australia. Eosinopenia was defined as eosinophil count <0.01×109/l and the date of censor for survival was 31 October 2011. Of the 1446 patients included in the study, 106 patients (7.3%) were re-admitted to the ICU during the same hospitalisation and 178 patients died (12.3%) after ICU discharge. Eosinopenia at ICU discharge occurred in 130 patients (9.7%) and was more common among those who were subsequently re-admitted (18.6 vs 8.6%) or died after ICU discharge (22.5 vs 7.5%). Eosinopenia remained associated with ICU re-admission (odds ratio 2.50, 95% confidence interval 1.38-4.50; P=0.002) and post-ICU mortality (hazard ratio 2.65, 95% confidence interval 1.77-3.98; P=0.001) after adjusting for age, gender, nocturnal discharge, neutrophil count at ICU discharge, elective surgical admission, Sequential Organ Failure Assessment scores, Acute Physiology and Chronic Health Evaluation II predicted mortality and chronic medical diseases. Eosinopenia at ICU discharge explained about 8.4% of the variability and was the third most important factor in explaining the variability in survival after ICU discharge. In summary, eosinopenia at ICU discharge was associated with an increased risk of unexpected ICU re-admission and post-ICU mortality.

C-reactive protein/albumin ratio predicts 90-day mortality of septic patients

Introduction

Residual inflammation at ICU discharge may have impact upon long-term mortality. However, the significance of ongoing inflammation on mortality after ICU discharge is poorly described. C-reactive protein (CRP) and albumin are measured frequently in the ICU and exhibit opposing patterns during inflammation. Since infection is a potent trigger of inflammation, we hypothesized that CRP levels at discharge would correlate with long-term mortality in septic patients and that the CRP/albumin ratio would be a better marker of prognosis than CRP alone.

Methods

We evaluated 334 patients admitted to the ICU as a result of severe sepsis or septic shock who were discharged alive after a minimum of 72 hours in the ICU. We evaluated the performance of both CRP and CRP/albumin to predict mortality at 90 days after ICU discharge. Two multivariate logistic models were generated based on measurements at discharge: one model included CRP (Model-CRP), and the other included the CRP/albumin ratio (Model-CRP/albumin).

Results

There were 229 (67%) and 111 (33%) patients with severe sepsis and septic shock, respectively. During the 90 days of follow-up, 73 (22%) patients died. CRP/albumin ratios at admission and at discharge were associated with a poor outcome and showed greater accuracy than CRP alone at these time points (p = 0.0455 and p = 0.0438, respectively). CRP levels and the CRP/albumin ratio were independent predictors of mortality at 90 days (Model-CRP: adjusted OR 2.34, 95% CI 1.14–4.83, p = 0.021; Model-CRP/albumin: adjusted OR 2.18, 95% CI 1.10–4.67, p = 0.035). Both models showed similar accuracy (p = 0.2483). However, Model-CRP was not calibrated.

Conclusions

Residual inflammation at ICU discharge assessed using the CRP/albumin ratio is an independent risk factor for mortality at 90 days in septic patients. The use of the CRP/albumin ratio as a long-term marker of prognosis provides more consistent results than standard CRP values alone.