With more than 30 million documented infections and 1 million deaths worldwide, the coronavirus disease 2019 (COVID-19) pandemic continues unabated. The clinical spectrum of severe acute respiratory syndrome coronavirus (SARS-CoV) 2 infection ranges from asymptomatic infection to life-threatening and fatal disease. Current estimates are that approximately 20 million people globally have “recovered”; however, clinicians are observing and reading reports of patients with persistent severe symptoms and even substantial end-organ dysfunction after SARS-CoV-2 infection. Because COVID-19 is a new disease, much about the clinical course remains uncertain—in particular, the possible long-term health consequences, if any.

/pdf/long-term-health-consequences-of-covid-19-2y64egql5h.pdf

Long-term Health Consequences of COVID-19

OBJECTIVES To describe the frequency of co-occurring newly acquired cognitive impairment, disability in activities of daily livings, and depression among survivors of a critical illness and to evaluate predictors of being free of post-intensive care syndrome problems. DESIGN Prospective cohort study. SETTING Medical and surgical ICUs from five U.S. centers. PATIENTS Patients with respiratory failure or shock, excluding those with preexisting cognitive impairment or disability in activities of daily livings. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS At 3 and 12 months after hospital discharge, we assessed patients for cognitive impairment, disability, and depression. We categorized patients into eight groups reflecting combinations of cognitive, disability, and mental health problems. Using multivariable logistic regression, we modeled the association between age, education, frailty, durations of mechanical ventilation, delirium, and severe sepsis with the odds of being post-intensive care syndrome free. We analyzed 406 patients with a median age of 61 years and an Acute Physiology and Chronic Health Evaluation II of 23. At 3 and 12 months, one or more post-intensive care syndrome problems were present in 64% and 56%, respectively. Nevertheless, co-occurring post-intensive care syndrome problems (i.e., in two or more domains) were present in 25% at 3 months and 21% at 12 months. Post-intensive care syndrome problems in all three domains were present in only 6% at 3 months and 4% at 12 months. More years of education was associated with greater odds of being post-intensive care syndrome free (p < 0.001 at 3 and 12 mo). More severe frailty was associated with lower odds of being post-intensive care syndrome free (p = 0.005 at 3 mo and p = 0.048 at 12 mo). CONCLUSIONS In this multicenter cohort study, one or more post-intensive care syndrome problems were present in the majority of survivors, but co-occurring problems were present in only one out of four. Education was protective from post-intensive care syndrome problems and frailty predictive of the development of post-intensive care syndrome problems. Future studies are needed to understand better the heterogeneous subtypes of post-intensive care syndrome and to identify modifiable risk factors.

/pdf/co-occurrence-of-post-intensive-care-syndrome-problems-among-14pmq6hbs5.pdf

Co-Occurrence of Post-Intensive Care Syndrome Problems Among 406 Survivors of Critical Illness.

Background: 
After critical illness, new or worsening impairments in physical, cognitive, and/or mental health function are common among patients who have survived. Who should be screened for long-term impairments, what tools to use, and when remain unclear.

Objectives: 
Provide pragmatic recommendations to clinicians caring for adult survivors of critical illness related to screening for postdischarge impairments.

Participants: 
Thirty-one international experts in risk-stratification and assessment of survivors of critical illness, including practitioners involved in the Society of Critical Care Medicine’s Thrive Post-ICU Collaboratives, survivors of critical illness, and clinical researchers.

Design: 
Society of Critical Care Medicine consensus conference on post-intensive care syndrome prediction and assessment, held in Dallas, in May 2019. A systematic search of PubMed and the Cochrane Library was conducted in 2018 and updated in 2019 to complete an original systematic review and to identify pre-existing systematic reviews.

Meeting Outcomes: 
We concluded that existing tools are insufficient to reliably predict post-intensive care syndrome. We identified factors before (e.g., frailty, preexisting functional impairments), during (e.g., duration of delirium, sepsis, acute respiratory distress syndrome), and after (e.g., early symptoms of anxiety, depression, or post-traumatic stress disorder) critical illness that can be used to identify patients at high-risk for cognitive, mental health, and physical impairments after critical illness in whom screening is recommended. We recommend serial assessments, beginning within 2–4 weeks of hospital discharge, using the following screening tools: Montreal Cognitive Assessment test; Hospital Anxiety and Depression Scale; Impact of Event Scale-Revised (post-traumatic stress disorder); 6-minute walk; and/or the EuroQol-5D-5L, a health-related quality of life measure (physical function).

Conclusions: 
Beginning with an assessment of a patient’s pre-ICU functional abilities at ICU admission, clinicians have a care coordination strategy to identify and manage impairments across the continuum. As hospital discharge approaches, clinicians should use brief, standardized assessments and compare these results to patient’s pre-ICU functional abilities (“functional reconciliation”). We recommend serial assessments for post-intensive care syndrome-related problems continue within 2–4 weeks of hospital discharge, be prioritized among high-risk patients, using the identified screening tools to prompt referrals for services and/or more detailed assessments.

/pdf/society-of-critical-care-medicine-s-international-consensus-2y4sfgdzyr.pdf

Society of Critical Care Medicine's International Consensus Conference on Prediction and Identification of Long-Term Impairments After Critical Illness.

Objectives: Data are lacking regarding implementation of novel strategies such as follow-up clinics and peer support groups, to reduce the burden of postintensive care syndrome. We sought to discover enablers that helped hospital-based clinicians establish post-ICU clinics and peer support programs, and identify barriers that challenged them.

Design: Qualitative inquiry. The Consolidated Framework for Implementation Research was used to organize and analyze data.

Setting: Two learning collaboratives (ICU follow-up clinics and peer support groups), representing 21 sites, across three continents.

Subjects: Clinicians from 21 sites.

Measurement and Main Results: Ten enablers and nine barriers to implementation of “ICU follow-up clinics” were described. A key enabler to generate support for clinics was providing insight into the human experience of survivorship, to obtain interest from hospital administrators. Significant barriers included patient and family lack of access to clinics and clinic funding. Nine enablers and five barriers to the implementation of “peer support groups” were identified. Key enablers included developing infrastructure to support successful operationalization of this complex intervention, flexibility about when peer support should be offered, belonging to the international learning collaborative. Significant barriers related to limited attendance by patients and families due to challenges in creating awareness, and uncertainty about who might be appropriate to attend and target in advertising.

Conclusions: Several enablers and barriers to implementing ICU follow-up clinics and peer support groups should be taken into account and leveraged to improve ICU recovery. Among the most important enablers are motivated clinician leaders who persist to find a path forward despite obstacles.

/pdf/enablers-and-barriers-to-implementing-icu-follow-up-clinics-327pdkgbt8.pdf

Enablers and barriers to implementing ICU follow-up clinics and peer support groups following critical illness: The thrive collaboratives

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. 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). 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. 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.

/pdf/prevalence-of-post-intensive-care-syndrome-among-japanese-khucjwbbty.pdf

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

Rationale: Post–intensive care syndrome (PICS), defined as new or worsening impairment in cognition, mental health, or physical function after critical illness, is an important development in survivors. Although studies to date have focused on the frequency of these impairments, fundamental questions remain unanswered regarding the survivor experience and the impact of the critical illness event on survivor resilience and recovery.Objectives: To examine the association between resilience and neuropsychological and physical function and to contextualize these findings within the survivors’ recovery experience.Methods: We conducted a mixed-methods pilot investigation of resilience among 43 survivors from two medical intensive care units (ICUs) within an academic health-care system. We interviewed survivors to identify barriers to and facilitators of recovery in the ICU, on the medical ward, and at home, using qualitative methods. We used a telephone battery of standardized tests to examine resilience, neuro...

/pdf/resilience-in-survivors-of-critical-illness-in-the-context-i9puthof5x.pdf

Resilience in Survivors of Critical Illness in the Context of the Survivors’ Experience and Recovery

Crit Care Med 2015 • Volume 43 • Number 12 (Suppl.) Methods: Philips eICU Research Institute Database was queried to identify hospitals with both adult cardiac-surgical (CS) and mixed medical/surgical (MIXED) ICUs from 2007 to 2011. Pts admitted with DKA were excluded. In a multilevel linear regression model, the outcome was defined as percentage of days with avg daily glucose <100 mg/dL (POD-ADG<100) for individual unit stay. The change of the POD-ADG<100 per year (slope) from 2007 to 2009 was compared with the slope from 2009 to 2011, controlling for age, gender, admission diagnosis and APACHE score. The impact of local culture and physician specialty (CS vs. MIXED) were estimated by nested random-effects with variances partitioned to hospitals and ICUs. Results: 134,325 ICU pt stays from 13 large tertiary hospitals (26 ICUs) were included. Between 2007 and 2009, there was a significant increase in POD-ADG<100 (slope=0.99 per year, p<0.01). Although the average slope change at 2009 was not statistically significant (-0.58 per year, p=0.59), there were significant variations between ICUs (p<0.01). A single CS ICU showed significant reduction in POD-ADG<100 after 2009 (slope before/after 2009: 0.99 vs. -4.1 per year, p<0.01) while the mixed ICU from the same hospital showed no significant change in practice. Multilevel regression model estimated that 43% of variances in change of slope at 2009 between ICUs could be attributable to hospitals, leaving about half of variances to be explained by physician specialty and other residual ICU specific characteristics. Conclusions: Change in practice following NICESUGAR was modest. The large variability between hospitals and the presence of a single ICU demonstrating dramatic and immediate change suggests that local culture and leadership may have a prominent role in adoption of evidence.

321: post-intensive care syndrome, resilience, and health-related quality of life in icu survivors

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Renata Siruckova

Author Tools

Chat about Author

Papers

Resilience in Survivors of Critical Illness in the Context of the Survivors’ Experience and Recovery

321: post-intensive care syndrome, resilience, and health-related quality of life in icu survivors