scholarly journals Nature and impact of in-hospital complications associated with persistent critical illness

2020 ◽  
Vol 22 (4) ◽  
pp. 378-387
Author(s):  
Boris Tseitkin ◽  
◽  
Johan Mårtensson ◽  
Glenn M Eastwood ◽  
Alastair Brown ◽  
...  
Keyword(s):  
Intensive Care ◽  
Critical Illness ◽  
Length Of Stay ◽  
Absolute Number ◽  
Hospital Length ◽  
Hospital Length Of Stay ◽  
Icu Length Of Stay ◽  
Study Results ◽  
Patients At Risk ◽  
Persistent Critical Illness

Background: Persistent critical illness (PerCI) is defined as an intensive care unit (ICU) admission lasting  10 days. The in-hospital complications associated with its development are poorly understood. Aims: To test whether PerCI is associated with a greater prevalence, rate and specific types of in-hospital complications. Methods: Single-centre, retrospective, observational case–control study. Results: We studied 1200 patients admitted to a tertiary ICU from 2010 to 2015. Median ICU length of stay was 16 days (interquartile range [IQR], 12–23) for PerCI patients v 2.3 days (IQR, 1.1–3.7) for controls, and median hospital length of stay was 41 days (IQR, 22–75) v 8 days (IQR, 4–17) respectively. A greater proportion of PerCI patients received acute renal replacement therapy (37% v 6.8%) or underwent reintubation (17% v 1%) and/or tracheostomy (36% v 0.6%); P < 0.0001. Despite these complications, PerCI patients had similar hospital mortality (29% v 27%; P = 0.53). PerCI patients experienced a greater absolute number of complications (12.1 v 4.0 complications per patient; P < 0.0001) but had fewer exposure-adjusted complications (202 v 272 complications per 1000 hospital bed-days; P < 0.001) and a particularly high overall prevalence of specific complications. Conclusions: PerCI patients experience a higher prevalence, but not a higher rate, of exposure-adjusted complications. Some of these complications appear amenable to prevention, helping to define intervention targets in patients at risk of PerCI. Funding: Austin Hospital Intensive Care Trust Fund.

Clinical and Economic Outcomes of Telemedicine Programs in the Intensive Care Unit: A Systematic Review and Meta-Analysis

2017 ◽  
Vol 33 (7) ◽  
pp. 383-393 ◽  
Author(s):  
Jing Chen ◽  
Dalong Sun ◽  
Weiming Yang ◽  
Mingli Liu ◽  
Shufan Zhang ◽  
...  
Keyword(s):  
Systematic Review ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Length Of Stay ◽  
Hospital Mortality ◽  
Meta Analysis ◽  
Hospital Length ◽  
Hospital Length Of Stay ◽  
Icu Length Of Stay ◽  
The Impact

Objective: To evaluate the impact of telemedicine programs in intensive care unit (Tele-ICU) on ICU or hospital mortality or ICU or hospital length of stay and to summarize available data on implementation cost of Tele-ICU. Methods: Controlled trails or observational studies assessing outcomes of interest were identified by searching 7 electronic databases from inception to July 2016 and related journals and conference literatures between 2000 and 2016. Two reviewers independently screened searched records, extracted data, and assessed the quality of included studies. Random-effect models were applied to meta-analyses and sensitivity analysis. Results: Nineteen of 1035 records fulfilled the inclusion criteria. The pooled effects demonstrated that Tele-ICU programs were associated with reductions in ICU mortality (15 studies; risk ratio [RR], 0.83; 95% confidence interval [CI], 0.72 to 0.96; P = .01), hospital mortality (13 studies; RR, 0.74; 95% CIs, 0.58 to 0.96; P = .02), and ICU length of stay (9 studies; mean difference [MD], −0.63; 95% CI, −0.28 to 0.17; P = .007). However, there is no significant association between the reduction in hospital length of stay and Tele-ICU programs. Summary data concerning costs suggested approximately US$50 000 to US$100 000 per Tele-ICU bed was required to implement Tele-ICU programs for the first year. Hospital costs of US$2600 reduction to US$5600 increase per patient were estimated using Tele-ICU programs. Conclusions: This systematic review and meta-analysis provided limited evidence that Tele-ICU approaches may reduce the ICU and hospital mortality, shorten the ICU length of stay, but have no significant effect in hospital length of stay. Implementation of Tele-ICU programs substantially costs and its long-term cost-effectiveness is still unclear.

scholarly journals Impact of early home psychotropic medication reinitiation on surrogate measures of intensive care unit delirium

2019 ◽  
Vol 9 (4) ◽  
pp. 263-268 ◽  
Author(s):  
Matthew Li ◽  
Mei H. Chang ◽  
Yeismel Miranda-Valdes ◽  
Kirsten Vest ◽  
Troy D. Kish
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Length Of Stay ◽  
Retrospective Chart Review ◽  
Hospital Length ◽  
Cost Of Care ◽  
Hospital Length Of Stay ◽  
Icu Length Of Stay ◽  
Significant Difference ◽  
Icu Delirium

Abstract Introduction Intensive care unit (ICU) delirium is a major contributing factor to increased mortality, length of stay, and cost of care. Psychotropic medications may often require extensive tapering to prevent withdrawal symptoms; during ICU admission, home psychotropics are frequently held which may precipitate acute drug withdrawal and subsequent delirium. Methods This is a single-center, observational, retrospective chart review. The primary endpoint was the total number of new-start antipsychotics used to treat ICU delirium. Secondary endpoints included use of restraints, ICU length of stay, and hospital length of stay. Results A total of 2334 charts were reviewed for inclusion; 55 patients were categorized into each group. There was no statistically significant difference in the requirement for new-start antipsychotics (P = 1.0), restraint use (P = .057), or ICU length of stay (P = .71). There was a statistically significant decrease in hospital length of stay (P = .048). Discussion Early reinitiation was associated with a decrease in hospital length of stay but was not associated with a decrease in the number of new-start antipsychotics, use of restraints, or ICU length of stay.

scholarly journals Timing and burden of persistent critical illnessin UK intensive care units: An observational cohort study

2021 ◽  
pp. 175114372110471
Author(s):  
David A Harrison ◽  
Ben C Creagh-Brown ◽  
Kathryn M Rowan
Keyword(s):  
Cohort Study ◽  
Intensive Care ◽  
Critical Illness ◽  
Length Of Stay ◽  
Observational Cohort Study ◽  
Adverse Outcomes ◽  
Admission Diagnosis ◽  
Icu Length Of Stay ◽  
Observational Cohort ◽  
Persistent Critical Illness

Background Persistent critical illness is a recognisable clinical syndrome defined conceptually as when the patient’s reason for being in the intensive care unit (ICU) is more related to their ongoing critical illness than their original reason for admission. Our objectives were: (1) to assess the day in ICU on which chronic factors (e.g., age, gender and comorbidities) were more predictive of survival than acute factors (e.g. admission diagnosis, physiological derangements) measured on the day of admission; (2) to assess the consistency of this finding across major patient subgroups and over time and (3) to compare case mix characteristics and outcomes for patients determined to develop persistent critical illness (based on ICU length of stay) with other patients. Methods Observational cohort study using a high-quality clinical database from the national clinical audit of adult critical care. 217 adult ICUs in England, Wales and Northern Ireland. 835,946 adult patients admitted to participating ICUs between 1 April 2009 and 31 March 2016. The main outcome measure was mortality at discharge from acute hospital. Results We fitted two statistical models (‘chronic’ and ‘acute’) and updated these based upon patients with an ICU length of stay of at least 1, 2, etc., up to 28 days. The discrimination of the chronic model first exceeded that of the acute model on day 11. Patients with longer stays (>10 days) comprised 9% of admissions but used 45% of ICU bed-days. After a mean ICU length of stay of 22 days and a subsequent 28 days in hospital, 30% died. Conclusions Persistent critical illness is commonly encountered in clinical practice and is associated with increased healthcare utilisation and adverse outcomes. Improvements in our understanding of the longer term outcomes and in the development of tools to aid prognostication are urgently required – for humane as well as health economic reasons.

scholarly journals Period-Prevalence and Risk Factors for Delirium in a Tertiary Referral ICU: A prospective cohort study

2021 ◽  
Vol 20 (3) ◽  
pp. 168-173
Author(s):  
FE Martinez ◽  
◽  
VW Ho ◽  
G Brogan ◽  
C Pickering ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care ◽  
Length Of Stay ◽  
Positive Association ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Hospital Length ◽  
Hospital Length Of Stay ◽  
Icu Length Of Stay ◽  
Treatment Data

Background: Delirium is common in intensive care and leads to increases in morbidity, mortality, Intensive Care Unit (ICU) length of stay, and hospital length of stay. Certain risk factors predict the appearance of delirium. Study Objectives: To determine the rates of delirium, the rate of risk factors, and their relationship to the occurrence of delirium in an adult ICU. Methods: Single-centre, prospective, observational study. Demographic and treatment data were collected. The Confusion Assessment Method for ICU (CAM-ICU) was performed twice daily to assess for delirium continuously during a 3-week period. Statistical analysis was used to determine the relationship between risk factors and the occurrence of delirium. Results: 86 patients were screened, 44 patients were included, and 260 patient-days were analyzed. The incidence of delirium was 42.9%, the prevalence of delirium in ICU was 50%. Urinary catheters and use of opioids were the most common factors with a positive association for occurrence of delirium. Exposure to daylight and sleeping for more than 4 hours at night were the factors most commonly associated with a lack of delirium. Conclusion: The rates of delirium in ICU were high and risk factors occurred frequently. Addressing modifiable risk factors, including the promotion of adequate sleep, could improve outcomes.

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.

Disagreement between emergency department admission diagnosis and hospital discharge diagnosis: mortality and morbidity

Diagnosis ◽  
2016 ◽  
Vol 3 (1) ◽  
pp. 23-30 ◽  
Author(s):  
James Eames ◽  
Arie Eisenman ◽  
Richard J. Schuster
Keyword(s):  
Emergency Department ◽  
Length Of Stay ◽  
Medical Center ◽  
Hospital Length ◽  
Hospital Length Of Stay ◽  
Admission Diagnosis ◽  
Mortality And Morbidity ◽  
Emergency Department Admission ◽  
Icu Length Of Stay ◽  
Discordant Group

AbstractPrevious studies have shown that changes in diagnoses from admission to discharge are associated with poorer outcomes. The aim of this study was to investigate how diagnostic discordance affects patient outcomes.: The first three digits of ICD-9-CM codes at admission and discharge were compared for concordance. The study involved 6281 patients admitted to the Western Galilee Medical Center, Naharyia, Israel from the emergency department (ED) between 01 November 2012 and 21 January 2013. Concordant and discordant diagnoses were compared in terms of, length of stay, number of transfers, intensive care unit (ICU) admission, readmission, and mortality.: Discordant diagnoses was associated with increases in patient mortality rate (5.1% vs. 1.5%; RR 3.35, 95% CI 2.43, 4.62; p<0.001), the number of ICU admissions (6.7% vs. 2.7%; RR 2.58, 95% CI 2.07, 3.32; p<0.001), hospital length of stay (3.8 vs. 2.5 days; difference 1.3 days, 95% CI 1.2, 1.4; p<0.001), ICU length of stay (5.2 vs. 3.8 days; difference 1.4 days, 95% CI 1.0, 1.9; p<0.001), and 30 days readmission (14.11% vs. 12.38%; RR 1.14, 95% CI 1.00, 1.30; p=0.0418). ED length of stay was also greater for the discordant group (3.0 vs. 2.9 h; difference 8.8 min; 95% CI 0.1, 0.2; p<0.001): These findings indicate discordant admission and discharge diagnoses are associated with increases in morbidity and mortality. Further research should identify modifiable causes of discordance.

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