scholarly journals Early detection, prevention, and mitigation of critical illness outside intensive care settings

2016 ◽  
Vol 11 ◽  
pp. S5-S10 ◽  
Author(s):  
Gabriel J. Escobar ◽  
R. Phillip Dellinger
Keyword(s):  
Intensive Care ◽  
Critical Illness ◽  
Early Detection

scholarly journals Healthcare trajectories before and after critical illness: population-based insight on diverse patients clusters

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Youenn Jouan ◽  
Leslie Grammatico-Guillon ◽  
Noémie Teixera ◽  
Claire Hassen-Khodja ◽  
Christophe Gaborit ◽  
...  
Keyword(s):  
Septic Shock ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Critical Illness ◽  
Length Of Stay ◽  
Population Based ◽  
Hospital Length Of Stay ◽  
Healthcare Use ◽  
Icu Admission ◽  
Icu Discharge

Abstract Background The post intensive care syndrome (PICS) gathers various disabilities, associated with a substantial healthcare use. However, patients’ comorbidities and active medical conditions prior to intensive care unit (ICU) admission may partly drive healthcare use after ICU discharge. To better understand retative contribution of critical illness and PICS—compared to pre-existing comorbidities—as potential determinant of post-critical illness healthcare use, we conducted a population-based evaluation of patients’ healthcare use trajectories. Results Using discharge databases in a 2.5-million-people region in France, we retrieved, over 3 years, all adult patients admitted in ICU for septic shock or acute respiratory distress syndrome (ARDS), intubated at least 5 days and discharged alive from hospital: 882 patients were included. Median duration of mechanical ventilation was 11 days (interquartile ranges [IQR] 8;20), mean SAPS2 was 49, and median hospital length of stay was 42 days (IQR 29;64). Healthcare use (days spent in healthcare facilities) was analyzed 2 years before and 2 years after ICU admission. Prior to ICU admission, we observed, at the scale of the whole study population, a progressive increase in healthcare use. Healthcare trajectories were then explored at individual level, and patients were assembled according to their individual pre-ICU healthcare use trajectory by clusterization with the K-Means method. Interestingly, this revealed diverse trajectories, identifying patients with elevated and increasing healthcare use (n = 126), and two main groups with low (n = 476) or no (n = 251) pre-ICU healthcare use. In ICU, however, SAPS2, duration of mechanical ventilation and length of stay were not different across the groups. Analysis of post-ICU healthcare trajectories for each group revealed that patients with low or no pre-ICU healthcare (which represented 83% of the population) switched to a persistent and elevated healthcare use during the 2 years post-ICU. Conclusion For 83% of ARDS/septic shock survivors, critical illness appears to have a pivotal role in healthcare trajectories, with a switch from a low and stable healthcare use prior to ICU to a sustained higher healthcare recourse 2 years after ICU discharge. This underpins the hypothesis of long-term critical illness and PICS-related quantifiable consequences in healthcare use, measurable at a population level.

scholarly journals The Post-ICU presentation screen (PICUPS) and rehabilitation prescription (RP) for intensive care survivors part II: Clinical engagement and future directions for the national Post-Intensive care Rehabilitation Collaborative

2021 ◽  
pp. 175114372098870
Author(s):  
Zudin Puthucheary ◽  
Craig Brown ◽  
Evelyn Corner ◽  
Sarah Wallace ◽  
Julie Highfield ◽  
...  
Keyword(s):  
Intensive Care ◽  
Critical Illness ◽  
Inpatient Rehabilitation ◽  
Service Evaluation ◽  
Language Therapy ◽  
Initial Development ◽  
Related Data ◽  
Acute Hospitals ◽  
Rehabilitation Needs ◽  
Post Intensive Care Syndrome

Background Many Intensive Care Unit (ICU) survivors suffer from a multi- system disability, termed the post-intensive care syndrome. There is no current national coordination of either rehabilitation pathways or related data collection for them. In the last year, the need for tools to systematically identify the multidisciplinary rehabilitation needs of severely affected COVID-19 survivors has become clear. Such tools offer the opportunity to improve rehabilitation for all critical illness survivors through provision of a personalised Rehabilitation Prescription (RP). The initial development and secondary refinement of such an assessment and data tools is described in the linked paper. We report here the clinical and workforce data that was generated as a result. Methods Prospective service evaluation of 26 acute hospitals in England using the Post-ICU Presentation Screen (PICUPS) tool and the RP. The PICUPS tool comprised items in domains of a) Medical and essential care, b) Breathing and nutrition; c) Physical movement and d) Communication, cognition and behaviour. Results No difference was seen in total PICUPS scores between patients with or without COVID-19 (77 (IQR 60-92) vs. 84 (IQR 68-97); Mann-Whitney z = −1.46, p = 0.144. A network analysis demonstrated that requirements for physiotherapy, occupational therapy, speech and language therapy, dietetics and clinical psychology were closely related and unaffected by COVID-19 infection status. A greater proportion of COVID-19 patients were referred for inpatient rehabilitation (13% vs. 7%) and community-based rehabilitation (36% vs.15%). The RP informed by the PICUPS tool generally specified a greater need for multi-professional input when compared to rehabilitation plans instituted. Conclusions The PICUPS tool is feasible to implement as a screening mechanism for post-intensive care syndrome. No differences are seen in the rehabilitation needs of patients with and without COVID-19 infection. The RP could be the vehicle that drives the professional interventions across the transitions from acute to community care. No single discipline dominates the rehabilitation requirements of these patients, reinforcing the need for a personalised RP for critical illness survivors.

Role of Procalcitonin in Early Detection of Infections in Acute on Chronic Liver Failure in Liver Intensive Care

2016 ◽  
Vol 6 ◽  
pp. S7
Author(s):  
Swapnil Dhampalwar ◽  
Aamritangsu Borkakoty ◽  
Sunil Taneja ◽  
Ajay Duseja ◽  
Radha K. Dhiman ◽  
...  
Keyword(s):  
Intensive Care ◽  
Early Detection ◽  
Liver Failure ◽  
Chronic Liver ◽  
Chronic Liver Failure

488: DESCRIBING POST-INTENSIVE CARE SYNDROME IN PEDIATRIC SURVIVORS OF CRITICAL ILLNESS

2016 ◽  
Vol 44 (12) ◽  
pp. 198-198
Author(s):  
Christopher Schneller ◽  
Briseyda Morales ◽  
Laura Campbell ◽  
Meredith Bone
Keyword(s):  
Intensive Care ◽  
Critical Illness ◽  
Post Intensive Care Syndrome

scholarly journals Antibiotic use and impact on outcome from bacteraemic critical illness: the BActeraemia Study in Intensive Care (BASIC)

2010 ◽  
Vol 65 (6) ◽  
pp. 1276-1285 ◽  
Author(s):  
A. Corona ◽  
G. Bertolini ◽  
J. Lipman ◽  
A. P. Wilson ◽  
M. Singer
Keyword(s):  
Intensive Care ◽  
Critical Illness ◽  
Antibiotic Use

scholarly journals Intensive Care Unit Capacity Strain and Outcomes of Critical Illness in a Resource-Limited Setting: A 2-Hospital Study in South Africa

2018 ◽  
Vol 35 (10) ◽  
pp. 1104-1111 ◽  
Author(s):  
George L. Anesi ◽  
Nicole B. Gabler ◽  
Nikki L. Allorto ◽  
Carel Cairns ◽  
Gary E. Weissman ◽  
...  
Keyword(s):  
South Africa ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Critical Illness ◽  
Primary Outcome ◽  
Resource Limited Setting ◽  
Icu Mortality ◽  
Icu Admission ◽  
Resource Limited ◽  
Limited Setting

Objective: To measure the association of intensive care unit (ICU) capacity strain with processes of care and outcomes of critical illness in a resource-limited setting. Methods: We performed a retrospective cohort study of 5332 patients referred to the ICUs at 2 public hospitals in South Africa using the country’s first published multicenter electronic critical care database. We assessed the association between multiple ICU capacity strain metrics (ICU occupancy, turnover, census acuity, and referral burden) at different exposure time points (ICU referral, admission, and/or discharge) with clinical and process of care outcomes. The association of ICU capacity strain at the time of ICU admission with ICU length of stay (LOS), the primary outcome, was analyzed with a multivariable Cox proportional hazard model. Secondary outcomes of ICU triage decision (with strain at ICU referral), ICU mortality (with strain at ICU admission), and ICU LOS (with strain at ICU discharge), were analyzed with linear and logistic multivariable regression. Results: No measure of ICU capacity strain at the time of ICU admission was associated with ICU LOS, the primary outcome. The ICU occupancy at the time of ICU admission was associated with increased odds of ICU mortality (odds ratio = 1.07, 95% confidence interval: 1.02-1.11; P = .004), a secondary outcome, such that a 10% increase in ICU occupancy would be associated with a 7% increase in the odds of ICU mortality. Conclusions: In a resource-limited setting in South Africa, ICU capacity strain at the time of ICU admission was not associated with ICU LOS. In secondary analyses, higher ICU occupancy at the time of ICU admission, but not other measures of capacity strain, was associated with increased odds of ICU mortality.

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