Impact of Critical Illness on Resource Utilization: A Comparison of Use in the Year Before and After ICU Admission

Effect of mortality prediction models on resource use benchmarking of intensive care units

PURPOSE

Intensive care requires extensive resources. The ICUs' resource use can be compared using standardized resource use ratios (SRURs). We assessed the effect of mortality prediction models on the SRURs.

MATERIALS AND METHODS

We compared SRURs using different mortality prediction models: the recent Finnish Intensive Care Consortium (FICC) model and the SAPS-II model (n = 68,914 admissions). We allocated the resources to severity of illness strata using deciles of predicted mortality. In each risk and year stratum, we calculated the expected resource use per survivor from our modelling approaches using length of ICU stay and Therapeutic Intervention Scoring System (TISS) points.

RESULTS

Resource use per survivor increased from one length of stay (LOS) day and around 50 TISS points in the first decile to 10 LOS-days and 450 TISS in the tenth decile for both risk scoring systems. The FICC model predicted mortality risk accurately whereas the SAPS-II grossly overestimated the risk of death. Despite this, SRURs were practically identical and consistent.

CONCLUSIONS

SRURs provide a robust tool for benchmarking resource use within and between ICUs. SRURs can be used for benchmarking even if recently calibrated risk scores for the specific population are not available.

Post-intensive care syndrome and health-related quality of life in long-term survivors of cardiac arrest: a prospective cohort study

Patients discharged from intensive care are at risk for post-intensive care syndrome (PICS), which consists of physical, psychological, and/or neurological impairments. This study aimed to analyze PICS at 24 months follow-up, to identify potential risk factors for PICS, and to assess health-related quality of life in a long-term cohort of adult cardiac arrest survivors. This prospective cohort study included adult cardiac arrest survivors admitted to the intensive care unit of a Swiss tertiary academic medical center. The primary endpoint was the prevalence of PICS at 24 months follow-up, defined as impairments in physical (measured through the European Quality of Life 5-Dimensions-3-Levels instrument [EQ-5D-3L]), neurological (defined as Cerebral Performance Category Score > 2 or Modified Rankin Score > 3), and psychological (based on the Hospital Anxiety and Depression Scale and the Impact of Event Scale-Revised) domains. Among 107 cardiac arrest survivors that completed the 2-year follow-up, 46 patients (43.0%) had symptoms of PICS, with 41 patients (38.7%) experiencing symptoms in the physical domain, 16 patients (15.4%) in the psychological domain, and 3 patients (2.8%) in the neurological domain. Key predictors for PICS in multivariate analyses were female sex (adjusted odds ratio [aOR] 3.17, 95% CI 1.08 to 9.3), duration of no-flow interval during cardiac arrest (minutes) (aOR 1.17, 95% CI 1.02 to 1.33), post-discharge job-loss (aOR 31.25, 95% CI 3.63 to 268.83), need for ongoing psychological support (aOR 3.64, 95% CI 1.29 to 10.29) or psychopharmacologic treatment (aOR 9.49, 95% CI 1.9 to 47.3), and EQ-visual analogue scale (points) (aOR 0.88, 95% CI 0.84 to 0.93). More than one-third of cardiac arrest survivors experience symptoms of PICS 2 years after resuscitation, with the highest impairment observed in the physical and psychological domains. However, long-term survivors of cardiac arrest report intact health-related quality of life when compared to the general population. Future research should focus on appropriate prevention, screening, and treatment strategies for PICS in cardiac arrest patients.

Development and validation of a risk score to predict unplanned hospital readmissions in ICU survivors: A data linkage study

BACKGROUND

Intensive Care Unit (ICU) follow-up clinics are growing in popularity internationally; however, there is limited evidence as to which patients would benefit most from a referral to this service.

OBJECTIVES

The objective of this study was to develop and validate a model to predict which ICU survivors are most likely to experience an unplanned hospital readmission or death in the year after hospital discharge and derive a risk score capable of identifying high-risk patients who may benefit from referral to follow-up services.

METHODS

A multicentre, retrospective observational cohort study using linked administrative data from eight ICUs was conducted in the state of New South Wales, Australia. A logistic regression model was developed for the composite outcome of death or unplanned readmission in the 12 months after discharge from the index hospitalisation.

RESULTS

12,862 ICU survivors were included in the study, of which 5940 (46.2%) patients experienced unplanned readmission or death. Strong predictors of readmission or death included the presence of a pre-existing mental health disorder (odds ratio [OR]: 1.52, 95% confidence interval [CI]: 1.40-1.65), severity of critical illness (OR: 1.57, 95% CI: 1.39-1.76), and two or more physical comorbidities (OR: 2.39, 95% CI: 2.14-2.68). The prediction model demonstrated reasonable discrimination (area under the receiver operating characteristic curve: 0.68, 95% CI: 0.67-0.69) and overall performance (scaled Brier score: 0.10). The risk score was capable of stratifying patients into three distinct risk groups-high (64.05% readmitted or died), medium (45.77% readmitted or died), and low (29.30% readmitted or died).

CONCLUSIONS

Unplanned readmission or death is common amongst survivors of critical illness. The risk score presented here allows patients to be stratified by risk level, enabling targeted referral to preventative follow-up services.

Effects of education, income and employment on ICU and post-ICU survival - A nationwide Swedish cohort study of individual-level data with 1-year follow up

PURPOSE

The aim of this study was to examine relationships between education, income, and employment (socioeconomic status, SES) and intensive care unit (ICU) survival and survival 1 year after discharge from ICU (Post-ICU survival).

METHODS

Individual data from ICU patients were linked to register data of education level, disposable income, employment status, civil status, foreign background, comorbidities, and vital status. Associations between SES, ICU survival and 1-year post-ICU survival was analysed using Cox's regression.

RESULTS

We included 58,279 adults (59% men, median length of stay in ICU 4.0 days, median SAPS3 score 61). Survival rates at discharge from ICU and one year after discharge were 88% and 63%, respectively. Risk of ICU death (Hazard ratios, HR) was significantly higher in unemployed and retired compared to patients who worked prior to admission (1.20; 95% CI: 1.10-1.30 and 1.15; (1.07-1.24), respectively. There was no consistent association between education, income and ICU death. Risk of post-ICU death decreased with greater income and was roughly 16% lower in the highest compared to lowest income quintile (HR 0.84; 0.79-0.88). Higher education levels appeared to be associated with reduced risk of death during the first year after ICU discharge.

CONCLUSIONS

Significant relationships between low SES in the critically ill and increased risk of death indicate that it is important to identify and support patients with low SES to improve survival after intensive care. Studies of survival after critical illness need to account for participants SES.

Timely Cessation of Proton Pump Inhibitors in Critically Ill Patients Impacts Morbidity and Mortality: A Propensity Score-Matched Cohort Study

OBJECTIVE

Proton pump inhibitors (PPIs) are among the drugs most commonly used in critically ill patients. Although mainly applied temporarily for stress ulcer prophylaxis, their application is frequently not terminated. Potential adverse effects of PPI treatment could impact the outcome in case of unnecessary and, therefore, avoidable long-term continuation. We tested the hypotheses that nonindicated PPI therapy continued beyond hospital discharge is associated with increased morbidity, rehospitalization rate, and mortality.

DESIGN

Nationwide retrospective cohort study considering critically ill patients treated on German ICUs between January, 2017, and December, 2018 with a 2-year follow-up.

SETTING

A total of 591,207 patient datasets of a German healthcare insurer were screened.

PATIENTS

We identified 11,576 ICU patients who received PPI therapy for the first time during their index ICU stay without having an indication for its continuation.

INTERVENTIONS

The cohort was stratified into two groups: 1) patients without further PPI therapy and 2) patients with continuation of PPI therapy beyond 8 weeks after hospital discharge.

MEASUREMENTS AND MAIN RESULTS

Frequency of predescribed adverse events associated with PPI therapy, 1-year rehospitalization rate, and 2-year mortality were determined. The proportion of patients with continued PPI therapy without an objectifiable indication was 41.7% (4,825 of 11,576 patients). These patients had a 27% greater risk of pneumonia (odds ratio [OR] 1.27; 95% CI, 1.15-1.39; p < 0.001) and a 17% greater risk of cardiovascular events (OR 1.17; 95% CI, 1.08-1.26; p < 0.001). Continued PPI therapy was associated with a 34% greater risk of rehospitalization (OR 1.34; 95% CI, 1.23-1.47) and a nearly 20% greater 2-year mortality risk (hazard ratio 1.17; 95% CI, 1.08-1.27; p = 0.006).

CONCLUSIONS

These data demonstrate that an unnecessary continuation of PPI therapy after hospital discharge may significantly impact morbidity and mortality. To avoid potentially harmful overuse of a PPIs, intensivists should ensure timely cessation of a temporarily indicated PPI therapy.

Impacts of antipsychotic medication prescribing practices in critically ill adult patients on health resource utilization and new psychoactive medication prescriptions

BACKGROUND

Antipsychotic medications are commonly prescribed to critically ill adult patients and initiation of new antipsychotic prescriptions in the intensive care unit (ICU) increases the proportion of patients discharged home on antipsychotics. Critically ill adult patients are also frequently exposed to multiple psychoactive medications during ICU admission and hospitalization including benzodiazepines and opioid medications which may increase the risk of psychoactive polypharmacy following hospital discharge. The associated impact on health resource utilization and risk of new benzodiazepine and opioid prescriptions is unknown.

RESEARCH QUESTION

What is the burden of health resource utilization and odds of new prescriptions of benzodiazepines and opioids up to 1-year post-hospital discharge in critically ill patients with new antipsychotic prescriptions at hospital discharge?

STUDY DESIGN & METHODS

We completed a multi-center, propensity-score matched retrospective cohort study of critically ill adult patients. The primary exposure was administration of ≥1 dose of an antipsychotic while the patient was admitted in the ICU and ward with continuation at hospital discharge and a filled outpatient prescription within 1-year following hospital discharge. The control group was defined as no doses of antipsychotics administered in the ICU and hospital ward and no filled outpatient prescriptions for antipsychotics within 1-year following hospital discharge. The primary outcome was health resource utilization (72-hour ICU readmission, 30-day hospital readmission, 30-day emergency room visitation, 30-day mortality). Secondary outcomes were administration of benzodiazepines and/or opioids in-hospital and following hospital discharge in patients receiving antipsychotics.

RESULTS

1,388 propensity-score matched patients were included who did and did not receive antipsychotics in ICU and survived to hospital discharge. New antipsychotic prescriptions were not associated with increased health resource utilization or 30-day mortality following hospital discharge. There was increased odds of new prescriptions of benzodiazepines (adjusted odds ratio [aOR] 1.61 [95%CI 1.19-2.19]) and opioids (aOR 1.82 [95%CI 1.38-2.40]) up to 1-year following hospital discharge in patients continuing antipsychotics at hospital discharge.

INTERPRETATION

New antipsychotic prescriptions at hospital discharge are significantly associated with additional prescriptions of benzodiazepines and opioids in-hospital and up to 1-year following hospital discharge.

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.

A protocol for exploring patients' and support peoples' experiences after prolonged critical illness

BACKGROUND

Improved survival of critically ill people has increased the number of patients who experience an extended stay in intensive care units (ICU). Evidence suggests the complexities, vulnerabilities, and traumas created by critical illness are substantial for both patients and their support people with a number experiencing devastating impairments across multiple domains of health and function including physical, mental, cognitive, and social health. However, research on survivors predominantly focuses on those who have experienced a relatively short length of stay; only a limited number of studies seek to explore the experiences of survivors and their support people who have had a prolonged stay in intensive care.

AIMS AND OBJECTIVES

To describe the experiences of survivors of prolonged critical illness (invasively mechanically ventilated in ICU for ≥eight days) and their support people during the first 12 months following hospital discharge in New Zealand.

DESIGN

This research will be a multi-centre study recruiting from three intensive care units in New Zealand. A narrative inquiry methodology will be used to interview 6-8 former long stay patients and 6-8 support people of a former long stay patient. Each participant will be interviewed at 3-, 6-, 9-, and 12-months following hospital discharge.

METHODS

Data will be collected via narrative inquiry interviews. Data analysis will combine two theoretical frameworks: the Clandinin and Connelly narrative inquiry three-dimensional space and the Fairclough situation, discourse and context framework.

RESULTS

The phenomenon of investigation will be experiences after prolonged critical illness explored longitudinally across the first-year post-hospital discharge.

RELEVANCE TO CLINICAL PRACTICE

This protocol provides a methodological framework for exploring the lived experiences of survivors of prolonged critical illness and their support people. Data analysis will support understanding of the human journey of ICU survivorship and add to the body of knowledge on how to support post-ICU recovery in this population. The barriers and enablers of survivorship at the micro, meso, and macro levels of the health service will also be illuminated.

Six-Month Quality of Life in COVID-19 Intensive Care Unit Survivors

OBJECTIVES

Because there is increasing evidence of serious deterioration in long-term quality of life (QoL) in coronavirus 2019 (COVID-19) intensive care unit (ICU) survivors, the authors identified predictors of poor quality of life in these patients.

DESIGN

Prospective cohort study.

SETTING

Research hospital repurposed into a COVID-19 center.

PARTICIPANTS

Consecutive patients admitted in COVID-19 ICUs between March and June 2020.

INTERVENTIONS

An SF-36 questionnaire, which included physical and mental items, was used six months after patient's discharge.

MEASUREMENTS AND MAIN RESULTS

A total of 403 patients were managed in the ICU, with a hospital mortality of 181 of 403 (44.9%), and 16 (4.0%) patients died within six months. Among the 125 questionnaire responders, only 32.0% and 52% had a normal quality of life in terms of the physical and mental component of health. Multivariate analysis identified low-molecular-weight heparin treatment in the ICU as the only modifiable factor associated with an increase in physical component of QoL odds ratio (OR) 3.341 (95% confidence interval 1.298-8.599), p = 0.012, and age ≥52 years OR 0.223 and female sex OR 0.321 were significantly associated with a decrease in the physical component. Medical history of cerebrovascular insufficiency was significantly associated with a decrease in mental component of QoL OR 0.125, and the only factor associated with an increase in the mental health component was body mass index ≥27.6 kg/m² OR 7.466.

CONCLUSIONS

In COVID-19 ICU survivors the authors identified treatment with low- molecular-weight heparin as a predictor of improved physical component of QoL at 6 months.

Location and outcomes of rehospitalizations after critical illness in a single-payer healthcare system

PURPOSE

Unplanned rehospitalization at a hospital other than the initial hospital may contribute to poor outcomes. We examined the location of rehospitalizations and assessed outcomes following critical illness in a single-payer healthcare system.

MATERIALS AND METHODS

Population-based retrospective cohort study using linked datasets (2012-2017) from Ontario, Canada including adults (≥18 years) with an unplanned rehospitalization within 30-days after an index hospitalization that included an ICU stay with mechanical ventilation. Outcomes were the percentage of 30-day rehospitalizations at non-index hospitals, mortality and costs. We employed logistic regression and generalized linear models to assess associations.

RESULTS

There were 14,997 (16.4%) 30-day rehospitalizations. Of these 2765 (18.4%) occurred in a non-index hospital. Distance of home residence from the index hospital was the strongest predictor of a non-index rehospitalization (adjusted odds ratio (aOR) 8.40, 95%CI 7.05-10.01, highest vs. lowest distance quintile). Within 30-days of rehospitalization, deaths (aOR 0.91, 95%CI (0.80-1.04)) and total healthcare costs (adjusted relative risk 1.03 (1.00-1.06)), were similar for patients readmitted to the index or a non-index hospital.

CONCLUSION

Non-index rehospitalization within 30-days of initial discharge is common following critical illness. These rehospitalizations were not significantly associated with an increased risk of harm or higher costs in a single-payer healthcare system.

A Comparative Analysis of Hospital Triage Systems in the Geriatric Adult Trauma Patients: A Quality Improvement Pilot Study

BACKGROUND

The objective of our study is to compare the predicted hospital admission disposition based on the level of risk as determined by the modified Trauma-Specific Frailty Index (mTSFI) score with those determined by arbitrary decisions made based on the Emergency Severity Index (ESI) severity level.

METHODS

We surveyed 100 trauma patients ages 50 and older, admitted to a level 1 trauma center between April 2019 and July 2019. We retrospectively reviewed the hospital admission disposition of each patient under the ESI, which was then compared to the mTSFI-predicted hospital admission disposition. The mTSFI scores were calculated by surveying each patient. Statistical analysis was performed to identify any statistical significance of concordance and discordance when comparing the mTSFI and ESI.

RESULTS

The average age was 57.6 ± 4.2 years old in the non-geriatric group vs 76.3 ± 7.3 years old in the geriatric group. There was a male predominance in both groups (61% vs 69.5%). The mTSFI identified a higher percentage of triage discordance in the non-geriatric group (73%) compared to the geriatric cohort (53%) (95% difference CI, [39.6-40], P = .05).

DISCUSSION

Non-geriatric patients have higher recorded rate of frailty than previously recognized and screening should begin at age 50, not 65. The mTSFI may be an effective tool to appropriately triage adult trauma patients at increased risk due to frailty and may reduce in-hospital complications.

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.

Medication Changes and Diagnosis of New Chronic Illnesses in COVID-19 Intensive Care Unit Survivors

Background

Currently, there is limited literature on the impact of the COVID-19 infection on medications and medical conditions in COVID-19 intensive care unit (ICU) survivors. Our study is, to our knowledge, the first multicenter study to describe the prevalence of new medical conditions and medication changes at hospital discharge in COVID-19 ICU survivors.

Objective

To determine the number of medical conditions and medications at hospital admission compared to at hospital discharge in COVID-19 ICU survivors.

Methods

Retrospective multicenter observational study (7 ICUs) evaluated new medical conditions and medication changes at hospital discharge in patients with COVID-19 infection admitted to an ICU between March 1, 2020, to March 1, 2021. Patient and hospital characteristics, baseline and hospital discharge medication and medical conditions, ICU and hospital length of stay, and Charlson comorbidity index were collected. Descriptive statistics were used to describe patient characteristics and number and type of medical conditions and medications. Paired t-test was used to compare number of medical conditions and medications from hospital discharge to admission.

Results

Of the 973 COVID-19 ICU survivors, 67.4% had at least one new medical condition and 88.2% had at least one medication change. Median number of medical conditions (increased from 3 to 4, P < .0001) and medications (increased from 5 to 8, P < .0001) increased from admission to discharge. Most common new medical conditions at discharge were pulmonary disorders, venous thromboembolism, psychiatric disorders, infection, and diabetes. Most common therapeutic categories associated with medication change were cardiology, gastroenterology, pain, hematology, and endocrinology.

Conclusion and Relevance

Our study found that the number of medical conditions and medications increased from hospital admission to discharge. Our results provide additional data to help guide providers on using targeted approaches to manage medications and diseases in COVID-19 ICU survivors after hospital discharge.

Functional outcomes following critical illness: epidemiology, current management strategies and the future priorities

PURPOSE OF REVIEW

Intensive care unit (ICU) survivorship has gained significant attention over the course of the COVID-19 pandemic. In this review, we summarize the contemporary literature in relation to the epidemiology and management of post-ICU problems.

RECENT FINDINGS

Survivors of critical illness can have complex physical, social, emotional and cognitive needs in the months following hospital discharge. Emerging evidence has shown that pre-ICU characteristics such as educational attainment, alongside in-ICU factors such as delirium, may contribute to worsening outcomes. Evidence regarding the impact of post-ICU recovery services is evolving, but models such as post-ICU clinics and peer support programs are gaining rapid momentum.

SUMMARY

Future research should focus on modifiable risk factors and how identification and treatment of these can improve outcomes. Furthermore, rigorous evaluation of postacute critical care recovery services is necessary.

Post-Intensive Care Syndrome and Its New Challenges in Coronavirus Disease 2019 (COVID-19) Pandemic: A Review of Recent Advances and Perspectives

Intensive care unit survivors experience prolonged physical impairments, cognitive impairments, and mental health problems, commonly referred to as post-intensive care syndrome (PICS). Previous studies reported the prevalence, assessment, and prevention of PICS, including the ABCDEF bundle approach. Although the management of PICS has been advanced, the outbreak of coronavirus disease 2019 (COVID-19) posed an additional challenge to PICS. The prevalence of PICS after COVID-19 extensively varied with 28-87% of cases pertaining to physical impairments, 20-57% pertaining to cognitive impairments, and 6-60% pertaining to mental health problems after 1-6 months after discharge. Each component of the ABCDEF bundle is not sufficiently provided from 16% to 52% owing to the highly transmissible nature of the virus. However, new data are emerging about analgesia, sedation, delirium care, nursing care, early mobilization, nutrition, and family support. In this review, we summarize the recent data on PICS and its new challenge in PICS after COVID-19 infection.

Optimizing Critical Illness Recovery: Perspectives and Solutions From the Caregivers of ICU Survivors

Supplemental Digital Content is available in the text.

Objectives:

To understand the unmet needs of caregivers of ICU survivors, how they accessed support post ICU, and the key components of beneficial ICU recovery support systems as identified from a caregiver perspective.

Design:

International, qualitative study.

Subjects:

We conducted 20 semistructured interviews with a diverse group of caregivers in the United States, the United Kingdom, and Australia, 11 of whom had interacted with an ICU recovery program.

Setting:

Seven hospitals in the United States, United Kingdom, and Australia.

Interventions:

None.

Measurements and Main Results:

Content analysis was used to explore prevalent themes related to unmet needs, as well as perceived strategies to improve ICU outcomes. Post-ICU care was perceived to be generally inadequate. Desired caregiver support fell into two main categories: practical support and emotional support. Successful care delivery initiatives included structured programs, such as post discharge telephone calls, home health programs, post-ICU clinics, and peer support groups, and standing information resources, such as written educational materials and online resources.

Conclusions:

This qualitative, multicenter, international study of caregivers of critical illness survivors identified consistently unmet needs, means by which caregivers accessed support post ICU, and several care mechanisms identified by caregivers as supporting optimal ICU recovery.

Cardiovascular and Renal Disease in Chronic Critical Illness

With advances in critical care, patients who would have succumbed in previous eras now survive through hospital discharge. Many survivors suffer from chronic organ dysfunction and induced frailty, representing an emerging chronic critical illness (CCI) phenotype. Persistent and worsening cardiovascular and renal disease are primary drivers of the CCI phenotype and have pathophysiologic synergy, potentiating one another and generating a downward spiral of worsening disease and clinical outcomes manifest as cardio-renal syndromes. In addition to pharmacologic therapies (e.g., diuretics, beta adrenergic receptor blockers, angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, and blood pressure control), special consideration should be given to behavioral modifications that avoid the pitfalls of polypharmacy and suboptimal renal and hepatic dosing, to which CCI patients may be particularly vulnerable. Smoking cessation, dietary modifications (e.g., early high-protein nutrition and late low-sodium diets), and increased physical activity are advised. Select patients benefit from cardiac re-synchronization therapy or renal replacement therapy. Coordinated, patient-centered care bundles may improve compliance with standards of care and patient outcomes. Given the complex, heterogeneous nature of cardiovascular and renal disease in CCI and the dismal long-term outcomes, further research is needed to clarify pathophysiologic mechanisms of cardio-renal syndromes in CCI and develop targeted therapies.

Predictors of Early and Late Unplanned Intensive Care Unit Readmission: A Retrospective Cohort Study

PURPOSE

Intensive care unit (ICU) readmission is considered one of the major quality indicators of critical care. Reducing ICU readmission can improve patients' outcomes and optimize health resources, but there are limited data on the predictors of unplanned ICU readmission. This study aimed to identify the risk factors associated with unplanned ICU readmission within 48 hr (early) and after 48 hr (late) from ICU discharge.

DESIGN

Retrospective cohort study.

METHODS

Data were collected from patients' electronic medical records in a 24-bed medical ICU at a tertiary academic medical center in Busan, South Korea. Among all the patients admitted to the medical ICU (n = 1,033) between January 2015 and December 2017, 739 eligible patients were analyzed. A multivariable multinomial logistic regression model was conducted to identify predictors of ICU readmission.

FINDINGS

Out of the 739 patients analyzed, 66 (8.9%) were readmitted to the medical ICU: 13 (1.8%) as early readmission and 53 (7.1%) as late readmission. Two significant predictors were identified for early readmission: ICU admission from the ward (odds ratio [OR] = 4.14; 95% confidence interval [CI] 1.25, 13.67) and mechanical ventilation support >14 days (OR = 13.25; 95% CI 1.78, 98.89). For late ICU admission, there were four risk factors: ICU admission from the ward (OR = 2.69; 95% CI 1.44, 5.05), tracheostomy placement (OR = 3.58; 95% CI 1.49, 8.59), mechanical ventilation support >14 days (OR = 4.77; 95% CI 1.67, 13.63), and continuous renal replacement therapy (OR = 4.57; 95% CI 2.42, 8.63).

CONCLUSIONS

To prevent unplanned ICU readmission in patients at high risk, it is necessary to investigate further the role of clinical judgment and communication within the ICU clinical team and institutional-level support regarding ICU readmission events.

CLINICAL RELEVANCE

Both ICU nurses and nurses in post-ICU settings should be aware of the potential risk factors associated with early and late ICU readmission. Predictors and readmission strategies may be different for early and late readmissions. Prospective multicenter studies are needed to examine how these factors influence post-ICU outcomes.

Long-term outcomes after critical illness: recent insights

Intensive care survivors often experience post-intensive care sequelae, which are frequently gathered together under the term “post-intensive care syndrome” (PICS). The consequences of PICS on quality of life, health-related costs and hospital readmissions are real public health problems. In the present Viewpoint, we summarize current knowledge and gaps in our understanding of PICS and approaches to management.

The effect of postintensive care syndrome on the quality of life of intensive care unit survivors: A secondary analysis

BACKGROUND

Despite increasing interest in postintensive care syndrome and the quality of life of intensive care unit survivors, the empirical literature on the relationship between these two variables is limited.

OBJECTIVES

This study aimed to examine whether postintensive care syndrome predicts the quality of life of intensive care unit survivors.

METHODS

We analysed secondary data, which were collected as part of a larger cross-sectional study. The participants were recruited from six health institutions in Korea. The data of 496 survivors who had been admitted to an intensive care unit for at least 48 h during the past year were analysed. They responded to measures of postintensive care syndrome and quality of life.

RESULTS

The participants' mean physical and mental component summary scores (quality of life) were 40.08 ± 8.99 and 40.24 ± 11.19, respectively. Physical impairment (β = -0.48, p < 0.001), unemployment (β = -0.19, p < 0.001), low income (β = -0.11, p = 0.004), older age (β = -0.08, p = 0.039), and cognitive impairment (β = -0.11, p = 0.045) predicted lower physical component summary scores. Mental (β = -0.49, p < 0.001) and cognitive impairment (β = -0.14, p = 0.005) and low income (β = -0.09, p = 0.014) predicted mental component summary scores.

CONCLUSIONS

The participants reported poor physical and mental health-related quality of life. Postintensive care syndrome, unemployment, low income, and older age were the main predictors of poor quality of life. In addition, postintensive care syndrome was a stronger risk factor for poor quality of life than demographic characteristics and intensive care unit treatment factors.

Postcritical illness vulnerability

PURPOSE OF REVIEW

Critical illness survivorship is associated with new and worsening physical, cognitive, and emotional status. Survivors are vulnerable to further health set-backs, most commonly because of infection and exacerbation of chronic medical conditions. Awareness of survivors' challenges are important given the anticipated rise in critical illness survivors because of SARS-CoV-2 viral sepsis.

RECENT FINDINGS

Studies continue to document challenges of critical illness survivorship. Beyond the cognitive, physical, and mental health sequelae encompassed by postintensive case syndrome, patients commonly experience persistent immunosuppression, re-hospitalization, inability to resume prior employment, and reduced quality of life. Although recommended practices for enhancing recovery from sepsis are associated with better outcomes, only a minority of patients receive all recommended practices. ICU follow-up programs or peer support groups remain important interventions to learn about and address the multifaceted challenges of critical illness survivorship, but there is little evidence of benefit to date.

SUMMARY

Survivors of sepsis and critical illness commonly experience impaired health status, reduced quality of life, and inability to return to prior employment. Although the challenges of critical illness survivorship are increasingly well documented, there are relatively few studies on enhancing recovery. Future studies must focus on identifying best practices for optimizing recovery and strategies to promote their implementation.