Development of an ICU discharge instrument predicting psychological morbidity: a multinational study

Potential risk factors for reduced quality of life and increased health care utilization in ARDS survivors: results from the multicenter cohort study DACAPO

AIM

To analyze the association of individual pre-ICU risk factors (obesity, physical and mental comorbidity, smoking status) on the long-term recovery process in survivors of the acute respiratory distress syndrome (ARDS; outcomes: health related quality of life, health care utilization; measured at 12, 24, and 36 months after ICU discharge).

FINDINGS

Results show a possible causal link between pre-ICU risk factors and subsequent recovery of survivors of ARDS, especially with regard to mental health related quality of life.

PURPOSE

Identifying relevant pre-existing risk factors, such as mental health problems, will enable the identification of at-risk patients, thus aiding in the improvement of long-term healthcare for survivors of critical illness.

Depressive symptoms over time among survivors after critical illness: A systematic review and meta-analysis

OBJECTIVE

Critical illness survivors frequently experience various degrees of depressive symptoms, which hinder their recovery and return to daily life. However, substantial variability in the prevalence of depressive symptoms has been reported among critical illness survivors. The exact prevalence remains uncertain.

METHODS

A systematic search was performed in PubMed, Embase, CINAHL, and PsycINFO from inception to August 2023 for observational studies that reported depressive symptoms in adult critical illness survivors. The random-effects model was used to estimate the prevalence of depressive symptoms. Subgroup analysis and meta-regression were conducted to explore potential moderators of heterogeneity. Study quality was evaluated using the Joanna Briggs Institute's tool and the GRADE approach.

RESULTS

Fifty-two studies with 24,849 participants met the inclusion criteria. Overall prevalence estimate of depressive symptoms was 21.1% (95% CI, 18.3-24.1%). The prevalence of depressive symptoms remains stable over time. Point prevalence estimates were 21.3% (95% CI, 9.9-35.4%), 19.9% (95% CI, 14.6-25.9%), 18.5% (95% CI, 9.6-29.2%), 21.0% (95% CI, 16.8-25.5%), and 22.6% (95% CI, 14.4-31.8%) at <3, 3, 6, 12, and > 12 months after discharge from intensive care unit (ICU), respectively.

CONCLUSIONS

Depressive symptoms may impact 1 in 5 adult critically ill patients within 1 year or more following ICU discharge. An influx of rehabilitation service demand is expected, and risk stratification to make optimal clinical decisions is essential. More importantly, to propose measures for the prevention and improvement of depressive symptoms in patients after critical care, given the continuous, dynamic management of ICU patients, including ICU stay, transition to general wards, and post-hospital.

Prediction of Long-Term Physical, Mental, and Cognitive Problems Following Critical Illness: Development and External Validation of the PROSPECT Prediction Model

OBJECTIVES

ICU survivors often suffer from long-lasting physical, mental, and cognitive health problems after hospital discharge. As several interventions that treat or prevent these problems already start during ICU stay, patients at high risk should be identified early. This study aimed to develop a model for early prediction of post-ICU health problems within 48 hours after ICU admission.

DESIGN

Prospective cohort study in seven Dutch ICUs.

SETTING/PATIENTS

ICU patients older than 16 years and admitted for greater than or equal to 12 hours between July 2016 and March 2020.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Outcomes were physical problems (fatigue or ≥ 3 new physical symptoms), mental problems (anxiety, depression, or post-traumatic stress disorder), and cognitive impairment. Patient record data and questionnaire data were collected at ICU admission, and after 3 and 12 months, of 2,476 patients. Several models predicting physical, mental, or cognitive problems and a composite score at 3 and 12 months were developed using variables collected within 48 hours after ICU admission. Based on performance and clinical feasibility, a model, PROSPECT, predicting post-ICU health problems at 3 months was chosen, including the predictors of chronic obstructive pulmonary disease, admission type, expected length of ICU stay greater than or equal to 2 days, and preadmission anxiety and fatigue. Internal validation using bootstrapping on data of the largest hospital ( n = 1,244) yielded a C -statistic of 0.73 (95% CI, 0.70-0.76). External validation was performed on data ( n = 864) from the other six hospitals with a C -statistic of 0.77 (95% CI, 0.73-0.80).

CONCLUSIONS

The developed and externally validated PROSPECT model can be used within 48 hours after ICU admission for identifying patients with an increased risk of post-ICU problems 3 months after ICU admission. Timely preventive interventions starting during ICU admission and follow-up care can prevent or mitigate post-ICU problems in these high-risk patients.

Accounting for Competing Events When Evaluating Long-Term Outcomes in Survivors of Critical Illness

The clinical trajectory of survivors of critical illness after hospital discharge can be complex and highly unpredictable. Assessing long-term outcomes after critical illness can be challenging because of possible competing events, such as all-cause death during follow-up (which precludes the occurrence of an event of particular interest). In this perspective, we explore challenges and methodological implications of competing events during the assessment of long-term outcomes in survivors of critical illness. In the absence of competing events, researchers evaluating long-term outcomes commonly use the Kaplan-Meier method and the Cox proportional hazards model to analyze time-to-event (survival) data. However, traditional analytical and modeling techniques can yield biased estimates in the presence of competing events. We present different estimands of interest and the use of different analytical approaches, including changes to the outcome of interest, Fine and Gray regression models, cause-specific Cox proportional hazards models, and generalized methods (such as inverse probability weighting). Finally, we provide code and a simulated dataset to exemplify the application of the different analytical strategies in addition to overall reporting recommendations.

Construction of a risk prediction model for detecting postintensive care syndrome-mental disorders

BACKGROUND

Postintensive care syndrome (PICS) has adverse multidimensional effects on nearly half of the patients discharged from ICU. Mental disorders such as anxiety, depression and post-traumatic stress disorder (PTSD) are the most common psychological problems for patients with PICS with harmful complications. However, developing prediction models for mental disorders in post-ICU patients is an understudied problem.

AIMS

To explore the risk factors of PICS mental disorders, establish the prediction model and verify its prediction efficiency.

STUDY DESIGN

In this cohort study, data were collected from 393 patients hospitalized in the ICU of a tertiary hospital from April to September 2022. Participants were randomly assigned to modelling and validation groups using a 7:3 ratio. Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was performed to select the predictors, multiple logistic regression analysis was used to establish the risk prediction model, and a dynamic nomogram was developed. The Hosmer-Lemeshow (HL) test was performed to determine the model's goodness of fit. The area under the receiver operating characteristic (ROC) curve was used to evaluate the model's prediction efficiency.

RESULTS

The risk factors of mental disorders were Sepsis-related organ failure assessment (SOFA) score, Charlson comorbidity index (CCI), delirium duration, ICU depression score and ICU sleep score. The HL test revealed that p = .249, the area under the ROC curve = 0.860, and the corresponding sensitivity and specificity were 84.8% and 71.0%, respectively. The area under the ROC curve of the verification group was 0.848. A mental disorders dynamic nomogram for post-ICU patients was developed based on the regression model.

CONCLUSIONS

The prediction model provides a reference for clinically screening patients at high risk of developing post-ICU mental disorders, to enable the implementation of timely preventive management measures.

RELEVANCE TO CLINICAL PRACTICE

The dynamic nomogram can be used to systematically monitor various factors associated with mental disorders. Furthermore, nurses need to develop and apply accurate nursing interventions that consider all relevant variables.

Screening tools for post-intensive care syndrome and post-traumatic symptoms in intensive care unit survivors: A scoping review

BACKGROUND

Evidence suggests that intensive care unit (ICU) survivors often suffer long-term complications such as post-intensive care syndrome (PICS) and post-traumatic stress disorder (PTSD) from critical illness and ICU stay. PICS and PTSD affect both ICU survivors and their families, which overburdens the healthcare systems. Lack of evidence on the comparative psychometric properties of assessment tools is a major barrier in evidence-based screening for post-ICU symptomatology and health-related quality of life.

OBJECTIVES

We aimed to identify existing tools for screening PTSD and PICS in ICU survivors and their families and to examine evidence on the validity, reliability, sensitivity, and specificity of existing tools, as reflected in published peer-reviewed studies.

METHOD

A scoping review based on literature searches (CINAHL, MEDLINE, EMBASE, PsycINFO, Scopus, Health and Psychosocial Instruments, Dissertations and Theses Global, and Google Scholar) and predefined eligibility criteria was conducted according to current scoping review guidelines.

FINDINGS

We identified 44 studies reporting on the development and assessment of psychometric properties of PICS/PTSD in ICU survivors or families globally. We identified five tools addressing all three aspects of PICS manifestations, one tool for both physical and mental aspects of PICS, and fivefive tools for quality-of-life assessment in ICU survivors. Altogether, 25 tools assess only one aspect of PICS: five for cognitive impairment, seven for physical impairment, and 13 for mental health impairment and PTSD in ICU survivors. However, only two tools were found for PICS-family assessment. Other findings include (i) unclear validity and often limited feasibility of tools, (ii) low diagnostic accuracy of cognitive assessment tools, and (iii) evidence of appropriate psychometric properties and feasibility of psychological health assessment tools.

CONCLUSION

These results have implications for the selection and implementation of the assessment methods as a means for promoting meaningful patient-centred clinical outcomes to minimise long-term sequelae, reduce the rate of rehospitalisation, and optimise recovery after ICU discharge.

Evaluation of a health and social care programme to improve outcomes following critical illness: a multicentre study

RATIONALE

At present, clinicians aiming to support patients through the challenges after critical care have limited evidence to base interventions.

OBJECTIVES

Evaluate a multicentre integrated health and social care intervention for critical care survivors. A process evaluation assessed factors influencing the programme implementation.

METHODS

This study evaluated the impact of the Intensive Care Syndrome: Promoting Independence and Return to Employment (InS:PIRE) programme. We compared patients who attended this programme with a usual care cohort from the same time period across nine hospital sites in Scotland. The primary outcome was health-related quality of life (HRQoL) measured via the EuroQol 5-dimension 5-level instrument, at 12 months post hospital discharge. Secondary outcome measures included self-efficacy, depression, anxiety and pain.

RESULTS

137 patients who received the InS:PIRE intervention completed outcome measures at 12 months. In the usual care cohort, 115 patients completed the measures. The two cohorts had similar baseline demographics. After adjustment, there was a significant absolute increase in HRQoL in the intervention cohort in relation to the usual care cohort (0.12, 95% CI 0.04 to 0.20, p=0.01). Patients in the InS:PIRE cohort also reported self-efficacy scores that were 7.7% higher (2.32 points higher, 95% CI 0.32 to 4.31, p=0.02), fewer symptoms of depression (OR 0.38, 95% CI 0.19 to 0.76, p=0.01) and similar symptoms of anxiety (OR 0.58, 95% CI 0.30 to 1.13, p=0.11). There was no significant difference in overall pain experience. Key facilitators for implementation were: integration with inpatient care, organisational engagement, flexibility to service inclusion; key barriers were: funding, staff availability and venue availability.

CONCLUSIONS

This multicentre evaluation of a health and social care programme designed for survivors of critical illness appears to show benefit at 12 months following hospital discharge.

Understanding Patients' Perceived Health After Critical Illness: Analysis of Two Prospective, Longitudinal Studies of ARDS Survivors

BACKGROUND

Perceived health is one of the strongest determinants of subjective well-being, but it has received little attention among survivors of ARDS.

RESEARCH QUESTION

How well do self-reported measures of physical, emotional, and social functioning predict perceived overall health (measured using the EQ-5D visual analog scale [EQ-5D-VAS]) among adult survivors of ARDS? Are demographic features, comorbidity, or severity of illness correlated with perceived health after controlling for self-reported functioning?

STUDY DESIGN AND METHODS

We analyzed the ARDSNet Long Term Outcomes Study (ALTOS) and Improving Care of Acute Lung Injury Patients (ICAP) Study, two longitudinal cohorts with a total of 823 survivors from 44 US hospitals, which prospectively assessed survivors at 6 and 12 months after ARDS. Perceived health, evaluated using the EQ-5D-VAS, was predicted using ridge regression and self-reported measures of physical, emotional, and social functioning. The difference between observed and predicted perceived health was termed perspective deviation (PD). Correlations between PD and demographics, comorbidities, and severity of illness were explored.

RESULTS

The correlation between observed and predicted EQ-5D-VAS scores ranged from 0.68 to 0.73 across the two cohorts and time points. PD ranged from -80 to +34 and was more than the minimum clinically important difference for 52% to 55% of survivors. Neither demographic features, comorbidity, nor severity of illness were correlated strongly with PD, with |r| < 0.25 for all continuous variables in both cohorts and time points. The correlation between PD at 6- and 12-month assessments was weak (ALTOS: r = 0.22, P < .001; ICAP: r = 0.20, P = .02).

INTERPRETATION

About half of survivors of ARDS showed clinically important differences in actual perceived health vs predicted perceived health based on self-reported measures of functioning. Survivors of ARDS demographic features, comorbidities, and severity of illness were correlated only weakly with perceived health after controlling for measures of perceived functioning, highlighting the challenge of predicting how individual patients will respond psychologically to new impairments after critical illness.

Processing Intensive Care Unit Treatment Experiences: A Thematic Analysis of a Diary Intervention

Survivors of the intensive care unit (ICU) report an aggregate of burdensome memories. ICU diaries have been proposed to address the psychological impact of ICU treatment. Twenty-six participants wrote about their ICU experiences in three successive sessions, while in the second session, they were presented with a dairy derived from their medical records. Using inductive thematic analysis in the first and third narratives, we explore how participants initially describe their ICU experience and how they process it after the intervention. Participants described a martyrdom experience, including being emotionally distressed, disorientated, and physically trapped that provoked a quest for any available interpersonal support. A vacuum-like state permeated their existence, impacted their sense-making ability, and the proximity to death uniquely characterized this experience. After intervention, participants made small but significant changes in their written narratives. They appeared to reorganize their recollections, reestablish self-continuity by integrating their ICU experiences, and authored restitution narratives.

Caregiver burden and emotional wellbeing in informal caregivers to ICU survivors-A prospective cohort study

BACKGROUND

Informal caregivers to intensive care unit (ICU) survivors may develop post-intensive care syndrome family (PICS-F), including depression, anxiety and post-traumatic stress (PTS). Our primary aim was to investigate associations between caregiver burden in informal caregivers cohabiting with ICU survivors and patients' physical and psychological outcomes.

METHODS

A prospective, multicentre cohort study in four ICUs in Sweden. Adults cohabiting with ICU patients included in a previous study were eligible for inclusion. Three months post-ICU, informal caregivers received questionnaires assessing caregiver burden, health-related quality of life (HRQL) and symptoms of depression, anxiety and PTS. In parallel, patients reported their three-month physical and psychological status via validated questionnaires. The primary outcome of this study was to compare caregiver burden in informal caregivers to patients with and without adverse physical and psychological outcomes 3 months post-ICU. Secondary outcomes were correlations between caregiver burden and informal caregivers' mental HRQL.

RESULTS

Among 62 included informal caregivers, 55 (89%) responded to the follow-up questionnaires. Caregiver burden was higher among informal caregivers to patients with an adverse outcome, compared to informal caregivers to patients without an adverse outcome, caregiver burden scale score mean (±standard deviation) 52 (11) and 41 (13) respectively (p = 0.003). There was strong negative correlation between caregiver burden and informal caregivers' mental HRQL (r_s -0.74, p < 0.001).

CONCLUSION

Informal caregivers to ICU survivors with adverse physical or psychological outcome experience a higher caregiver burden. A higher caregiver burden correlates with worse caregiver mental HRQL. ICU follow-up programs should consider screening and follow-up of informal caregivers for mental health problems.

Posttraumatic stress phenomena in critical illness and intensive care survivors

The intensive care unit (ICU) within a hospital is typically thought of as a place for the provision of patient care for a life-threatening emergency. Less frequently do we consider it an integral part of disaster response. The COVID-19 pandemic is a public health disaster that has caused surges of critically ill patients requiring treatment in intensive care units (ICUs). However, it is important to bear in mind that survival of a critical illness can come at a cost, including to mental health. Being critically ill and requiring life-saving treatments is extremely stressful, and survivors frequently have substantial decrements in physical functioning, cognition, and emotional health. Remarkably, one in five critical illness survivors has clinically significant symptoms of posttraumatic stress disorder (PTSD). Risk factors, or markers of risk, include prior anxiety and depression, high doses of sedative medications in the intensive care unit (ICU), memories of nightmare-like experiences in the ICU, and emotional distress in early recovery. As with PTSD in other contexts, social support is a protective factor. ICU follow-up clinics, in-ICU psychological interventions, ICU diaries, post-ICU telephonic and computer-based cognitive-behavioral interventions, and virtual reality interventions all show promise in preventing long-term PTSD in critical illness survivors, perhaps particularly in those with substantial emotional distress in early recovery. However, awareness regarding this problem is still growing, as are changes to post-ICU care delivery. Hopefully, improved awareness on the part of the psychiatric community will help with recovery from the COVID-19 pandemic disaster.

Which criteria is a better predictor of ICU admission in trauma patients? An artificial neural network approach

PURPOSE

One of the most critical concerns in the intensive care unit (ICU) section is identifying the best criteria for entering patients to this part. This study aimed to predict the best compatible criteria for entering trauma patients in the ICU section.

METHOD

The present study was a historical cohort study. The data were collected from 2448 trauma patients referring to Shahid Rajaee Hospital between January 2015 and January 2017 in Shiraz, Iran. The artificial neural network (ANN) models with cross-validation and logistic regression (LR) with a backward method was used for data analysis. The final analysis was performed on a total of 958 patients who were transferred to the ICU section.

RESULTS

Based on the present results, the motor component of the GCS score at each cutoff point had the highest importance. The results also showed better performance for the AUC and accuracy rate for ANN compared with LR.

CONCLUSION

The most critical indicators in predicting the optimal use of ICU services in this study were the Motor component of the GCS. Results revealed that the ANN had a better performance than the LR in predicting the main outcomes of the traumatic patients in both the accuracy and AUC index. Trauma section surgeons and ICU specialists will benefit from this study's results and can assist them in making decisions to predict the patient outcomes before entering the ICU.

Prediction Models for Physical, Cognitive, and Mental Health Impairments After Critical Illness: A Systematic Review and Critical Appraisal

Supplemental Digital Content is available in the text.

Objectives:

Improved ability to predict impairments after critical illness could guide clinical decision-making, inform trial enrollment, and facilitate comprehensive patient recovery. A systematic review of the literature was conducted to investigate whether physical, cognitive, and mental health impairments could be predicted in adult survivors of critical illness.

Data Sources:

A systematic search of PubMed and the Cochrane Library (Prospective Register of Systematic Reviews ID: CRD42018117255) was undertaken on December 8, 2018, and the final searches updated on January 20, 2019.

Study Selection:

Four independent reviewers assessed titles and abstracts against study eligibility criteria. Studies were eligible if a prediction model was developed, validated, or updated for impairments after critical illness in adult patients. Discrepancies were resolved by consensus or an independent adjudicator.

Data Extraction:

Data on study characteristics, timing of outcome measurement, candidate predictors, and analytic strategies used were extracted. Risk of bias was assessed using the Prediction model Risk Of Bias Assessment Tool.

Data Synthesis:

Of 8,549 screened studies, three studies met inclusion. All three studies focused on the development of a prediction model to predict (1) a mental health composite outcome at 3 months post discharge, (2) return-to-pre-ICU functioning and residence at 6 months post discharge, and (3) physical function 2 months post discharge. Only one model had been externally validated. All studies had a high risk of bias, primarily due to the sample size, and statistical methods used to develop and select the predictors for the prediction published model.

Conclusions:

We only found three studies that developed a prediction model of any post-ICU impairment. There are several opportunities for improvement for future prediction model development, including the use of standardized outcomes and time horizons, and improved study design and statistical methodology.

Prevalence of post-intensive care syndrome among Japanese intensive care unit patients: a prospective, multicenter, observational J-PICS study

Background

Many studies have compared quality of life of post-intensive care syndrome (PICS) patients with age-matched population-based controls. Many studies on PICS used the 36-item Short Form (SF-36) health survey questionnaire version 2, but lack the data for SF-36 values before and after intensive care unit (ICU) admission. Thus, clinically important changes in the parameters of SF-36 are unknown. Therefore, we determined the frequency of co-occurrence of PICS impairments at 6 months after ICU admission. We also evaluated the changes in SF-36 subscales and interpreted the patients’ subjective significance of impairment.

Methods

A prospective, multicenter, observational cohort study was conducted in 16 ICUs across 14 hospitals in Japan. Adult ICU patients expected to receive mechanical ventilation for > 48 h were enrolled, and their 6-month outcome was assessed using the questionnaires. PICS definition was based on the physical status, indicated by the change in SF-36 physical component score (PCS) ≥ 10 points; mental status, indicated by the change in SF-36 mental component score (MCS) ≥ 10 points; and cognitive function, indicated by the worsening of Short-Memory Questionnaire (SMQ) score and SMQ score at 6 months < 40. Multivariate logistic regression model was used to identify the factors associated with PICS occurrence. The patients’ subjective significance of physical and mental symptoms was assessed using the 7-scale Global Assessment Rating to evaluate minimal clinically important difference (MCID).

Results

Among 192 patients, 48 (25%) died at 6 months. Among the survivors at 6 months, 96 patients responded to the questionnaire; ≥ 1 PICS impairment occurred in 61 (63.5%) patients, and ≥ 2 occurred in 17 (17.8%) patients. Physical, mental, and cognitive impairments occurred in 32.3%, 14.6% and 37.5% patients, respectively. Population with only mandatory education was associated with PICS occurrence (odds ratio: 4.0, 95% CI 1.1–18.8, P = 0.029). The MCID of PCS and MCS scores was 6.5 and 8.0, respectively.

Conclusions

Among the survivors who received mechanical ventilation, 64% had PICS at 6 months; co-occurrence of PICS impairments occurred in 20%. PICS was associated with population with only mandatory education. Future studies elucidating the MCID of SF-36 scores among ICU patients and standardizing the PICS definition are required.

Trial registration UMIN000034072.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13054-021-03501-z.

Approaches to Addressing Post-Intensive Care Syndrome among Intensive Care Unit Survivors. A Narrative Review

Critical illness can be lethal and devastating to survivors. Improvements in acute care have increased the number of intensive care unit (ICU) survivors. These survivors confront a range of new or worsened health states that collectively are commonly denominated post-intensive care syndrome (PICS). These problems include physical, cognitive, psychological, and existential aspects, among others. Burgeoning interest in improving long-term outcomes for ICU survivors has driven an array of potential interventions to improve outcomes associated with PICS. To date, the most promising interventions appear to relate to very early physical rehabilitation. Late interventions within aftercare and recovery clinics have yielded mixed results, although experience in heart failure programs suggests the possibility that very early case management interventions may help improve intermediate-term outcomes, including mortality and hospital readmission. Predictive models have tended to underperform, complicating study design and clinical referral. The complexity of the health states associated with PICS suggests that careful and rigorous evaluation of multidisciplinary, multimodality interventions-tied to the specific conditions of interest-will be required to address these important problems.

ICU discharge screening for prediction of new-onset physical disability-A multinational cohort study

BACKGROUND

Methods to identify patients at risk for incomplete physical recovery after intensive care unit (ICU) stay are lacking. Our aim was to develop a method for prediction of new-onset physical disability at ICU discharge.

METHODS

Multinational prospective cohort study in 10 general ICUs in Sweden, Denmark, and the Netherlands. Adult patients with an ICU stay ≥12 hours were eligible for inclusion. Sixteen candidate predictors were analyzed with logistic regression for associations with the primary outcome; new-onset physical disability 3 months post-ICU, defined as a ≥10 score reduction in the Barthel Index (BI) compared to baseline.

RESULTS

Of the 572 included patients, follow-up data are available on 78% of patients alive at follow-up. The incidence of new-onset physical disability was 19%. Univariable and multivariable modeling rendered one sole predictor for the outcome: physical status at ICU discharge, assessed with the five first items of the Chelsea critical care physical assessment tool (CPAx) (odds ratio 0.87, 95% confidence interval (CI) 0.81-0.93), a higher score indicating a lower risk, with an area under the receiver operating characteristics curve of 0.68 (95% CI 0.61-0.76). Negative predictive value for a low-risk group (CPAx score >18) was 0.88, and positive predictive value for a high-risk group (CPAx score ≤18) was 0.32.

CONCLUSION

The ICU discharge assessment described in this study had a moderate AUC but may be useful to rule out patients unlikely to need physical interventions post-ICU. For high-risk patients, research to determine post-ICU risk factors for an incomplete rehabilitation is mandated.