P3506A novel urinary biomarker predicts 1 year mortality after discharge from Intensive Care

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
Z Y Zhang ◽  
E Nkuipou-Kenfack ◽  
W Y Yang ◽  
B Mujaj ◽  
L Thijs ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Model Performance ◽  
Biologically Active ◽  
Support Vector ◽  
Charlson Score ◽  
Icu Mortality ◽  
Discovery Sample ◽  
Net Reclassification Improvement ◽  
Icu Discharge

Abstract Rationale Tools reflecting molecular processes predicting death after discharge from intensive care unit (ICU) are currently unavailable. Objectives To construct a urinary proteomic biomarker predicting 1-year post-ICU mortality. Methods In 1081 patients, enrolled in the French and European Outcome Registry in Intensive Care Unit (NCT01367093), the urinary proteome was measured at ICU discharge using capillary electrophoresis couple with mass spectrometry along with clinical variables; circulating biomarkers (NT-proBNP, hsTnT, biologically active adrenomedullin, soluble ST2, and NGAL) and urinary albumin were available in 886 patients. Measurements and main results In the discovery sample (60/256 deaths/survivors), support vector machine modelling identified ACM150, mainly consisting of collagen fragments, yielding an AUC of 0.676 (95% CI, 0.615–0.737). In the replication sample (151/608 deaths/survivors), AUC was 0.704 (0.659–0.750). While accounting for center and clinical risk factors, the hazard ratios in all available patients were 1.27 (1.18–1.37) for ACM150 (+1 SD), 1.20 (1.16–1.33) for the Charlson score (+1 point), and ≥1.30 (P≤0.0071) for the other biomarkers (+ 1 SD). Model performance assessed by adding ACM150 to a basic model including the aforementioned covariables, the Charlson score or any other biomarker confirmed the prognostic accuracy of ACM15 with significant increases (P≤0.0038) in integrated discrimination (≥ +0.50) and net reclassification improvement (≥ +53.7) and AUC (≥ +0.037). Interactome mapping (STRING) based on 72 sequenced peptides and 25 parental proteins gravitated around collagen nodes. Conclusions ACM150 is a urinary proteomic classifier predicting 1-year post-ICU mortality over and beyond other biomarkers and reflects dysregulation of collagen turnover as underlying pathophysiological process.

scholarly journals PERFORMANCE OF THE SEPSIS‑3 DEFINITIONS IN A MIDDLE INCOME COUNTRY INTENSIVE CARE UNIT

2021 ◽  
Vol 13 (1) ◽  
pp. e2021052
Author(s):  
Zied Hajjej ◽  
Kalthoum Ben Mahmoud ◽  
Aicha Rebai ◽  
Hedi Gharsallah ◽  
Iheb Labbene ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Septic Shock ◽  
Intensive Care ◽  
Middle Income Country ◽  
Income Country ◽  
Surgical Intensive Care Unit ◽  
Icu Mortality ◽  
Surgical Intensive Care ◽  
Middle Income ◽  
Icu Discharge

Background: Since the first publication, of 2016, Sepsis-3 definitions have not been universally accepted, rather, they have become a source of controversy. Because clinical and laboratory parameters used had been derived mainly from patients hospitalized in United States’ Intensive Care Units (ICU). Purpose: the aim of this study was to evaluate the performance of the Sepsis‑3 definitions for the prediction of ICU-mortality in a Tunisian ICU population as compared to 2003 Consensus Definitions (Sepsis-2 definitions) Methods: It was a retrospective study conducted in an 18-bed medical surgical intensive care unit at the military hospital of Tunis (Tunisia).  From January 2012 to January 2016, all patients admitted to the ICU for sepsis, severe sepsis or septic shock as defined according to 2003 Consensus Definitions (Sepsis-2 consensus) were eligible for this study. The new Sepsis-3 definition was secondly used to classify included patients. The primary area of interest was ICU mortality defined as death before ICU discharge Results: A total of 1080 patients were included during the recruitment period. . When the Sepsis-2 definitions were used there had been a difference in mortality only between septic shock and sepsis patients. While Sepsis-3 definitions show that mortality increased from 16 % among no-dysfunction-infected patients to 30 % among patients with qSOFA ≥ 2 and 44% or 46% for sepsis or septic shock patients, respectively. Conclusions: Sepsis-3 was better than sepsis-2 definitions at stratifying mortality among septic patients admitted to an ICU of a middle income country (Tunisia).

Characteristics and outcomes of palliative care patients in intensive care unit.

2014 ◽  
Vol 32 (31_suppl) ◽  
pp. 145-145
Author(s):  
Renata R. L. Fumis ◽  
Otavio Tavares Ranzani ◽  
Paulo Sergio Martins ◽  
Guilherme De Paula Pinto Schettino
Keyword(s):  
Intensive Care Unit ◽  
Palliative Care ◽  
Intensive Care ◽  
Icu Mortality ◽  
Icu Stay ◽  
Icu Length Of Stay ◽  
Icu Discharge ◽  
Oncologic Patients ◽  
Surgical Icu

145 Background: Despite the growing palliative care movement, most admissions still occur in Intensive Care Units. The aim of this study was to determine the frequency of palliative care patients admitted in an ICU and assessed their outcomes. Methods: This prospective study was conducted in a tertiary private hospital, in an adult medical-surgical ICU with 22-bed in São Paulo, Brazil. Patients or their family member with ICU stay ≥ 48 hours were invited to participate. They were excluded if they had no conditions to answer the questionnaire or if they refuse to participate. During ICU stay we analyzed through the medical records and questionnaire their clinical condition and their oncologic status. We called them by telephonic assessment to assess their survival. Results: From March 2011 to March 2013 a total of 576 ICU patients were analyzed; of these, 280 were oncologic patients and 95 were palliative care. Of total, the majority was male gender (57.8%), median age was 67[54-79] years, SAPS III score was 54±18.4 points, SOFA was 3.1±3.0 and ICU Length of stay (LOS) was 9.0±11.3 days. ICU mortality was 16.5%, 1-month mortality was 22% and 3-months cumulative mortality was 28.6%. We could observe that palliative care patients were in majority cancer patients (75%vs 43.4%,p<0.001), with metastatic disease(81.7 vs 36.3, p<0.001), had greater mean time of initial diagnosis(3.21±3.7 vs 2.17±2.5, p=0.009), had greater ICU LOS (14.2±16.2 days vs 7.96±9.8, p<0.001) greater mean SAPS III (68.5±16.0 vs p<0.001) and SOFA (4.81±3.2 vs 2.81±2.8, p<0.001) when compared with non palliative patients care. They also needed more mechanical ventilation (50.0%vs32.6%, p=0.001), tracheotomy (11.6%vs 5.0%,p=0.014) and vasopressors (54.7% vs 36.8,p=0.001). The ICU mortality was greater (32.6% vs 6.8%, p<0.001), 1-month (60.0% vs 14.0%, p<0.001) and 3-months (73.5% vs 19.1%). Conclusions: Palliative care suffers most in Intensive Care Unit and we observed a high mortality at 3-months after ICU discharge. We recommend more discussions before palliative care patient’s admissions in ICU to better provide them quality of life.

scholarly journals Families' perception, knowledge, and psychological stressors associated with transition of care from the intensive care unit

2019 ◽  
Vol 2 (1) ◽  
pp. 53-56
Author(s):  
Gustavo Ferrer ◽  
Chi Chan Lee ◽  
Monica Egozcue ◽  
Hector Vazquez ◽  
Melissa Elizee ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Health Care Providers ◽  
Family Members ◽  
Expected Improvement ◽  
Transition Of Care ◽  
Care Providers ◽  
Icu Discharge ◽  
Family Perceptions

Background: During the process of transition of care from the intensive care setting, clarity, and understanding are vital to a patient's outcome. A successful transition of care requires collaboration between health-care providers and the patient's family. The objective of this project was to assess the quality of continuity of care with regard to family perceptions, education provided, and psychological stress during the process. Methods: A prospective study conducted in a long-term acute care (LTAC) facility. On admission, family members of individuals admitted to the LTAC were asked to fill out a 15-item questionnaire with regard to their experiences from preceding intensive care unit (ICU) hospitalization. The setting was an LTAC facility. Patients were admitted to an LTAC after ICU admission. Results: Seventy-six participants completed the questionnaire: 38% expected a complete recovery, 61% expected improvement with disabilities, and 1.3% expected no recovery. With regard to the length of stay in the LTAC, 11% expected < 1 week, 26% expected 1 to 2 weeks, 21% expected 3 to 4 weeks, and 42% were not sure. Before ICU discharge, 33% of the participants expected the transfer to the LTAC. Also, 72% did not report a satisfactory level of knowledge regarding their family's clinical condition or medical services required; 21% did not receive help from family members; and 50% reported anxiety, 20% reported depression, and 29% reported insomnia. Conclusion: Families' perception of patients' prognosis and disposition can be different from what was communicated by the physician. Families' anxiety and emotional stress may precipitate this discrepancy. The establishment of optimal projects to eliminate communication barriers and educate family members will undoubtedly improve the quality of transition of care from the ICU.

scholarly journals Prospective validation of an 11-gene mRNA host response score for mortality risk stratification in the intensive care unit

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Andrew R. Moore ◽  
Jonasel Roque ◽  
Brian T. Shaller ◽  
Tola Asuni ◽  
Melissa Remmel ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Emergency Department ◽  
Intensive Care ◽  
Whole Blood ◽  
Messenger Rna ◽  
Emergency Department Presentation ◽  
Gene Score ◽  
Net Reclassification Improvement ◽  
Improvement Index ◽  
Gene Mrna

AbstractSeveral clinical calculators predict intensive care unit (ICU) mortality, however these are cumbersome and often require 24 h of data to calculate. Retrospective studies have demonstrated the utility of whole blood transcriptomic analysis in predicting mortality. In this study, we tested prospective validation of an 11-gene messenger RNA (mRNA) score in an ICU population. Whole blood mRNA from 70 subjects in the Stanford ICU Biobank with samples collected within 24 h of Emergency Department presentation were used to calculate an 11-gene mRNA score. We found that the 11-gene score was highly associated with 60-day mortality, with an area under the receiver operating characteristic curve of 0.68 in all patients, 0.77 in shock patients, and 0.98 in patients whose primary determinant of prognosis was acute illness. Subjects with the highest quartile of mRNA scores were more likely to die in hospital (40% vs 7%, p < 0.01) and within 60 days (40% vs 15%, p = 0.06). The 11-gene score improved prognostication with a categorical Net Reclassification Improvement index of 0.37 (p = 0.03) and an Integrated Discrimination Improvement index of 0.07 (p = 0.02) when combined with Simplified Acute Physiology Score 3 or Acute Physiology and Chronic Health Evaluation II score. The test performed poorly in the 95 independent samples collected > 24 h after emergency department presentation. Tests will target a 30-min turnaround time, allowing for rapid results early in admission. Moving forward, this test may provide valuable real-time prognostic information to improve triage decisions and allow for enrichment of clinical trials.

scholarly journals Cardiac function during COVID-19 intensive care unit hospitalisation - deformation analysis and outcomes

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
F Loncaric ◽  
JF Fernandes ◽  
M Sitges ◽  
B Stessel ◽  
J Dubois ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Cardiac Function ◽  
Deformation Analysis ◽  
P Value ◽  
Prognostic Information ◽  
Horizon 2020 ◽  
Cardiac Strain ◽  
Icu Discharge ◽  
Public Grant

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): Horizon 2020 European Commission Project H2020-MSCA-ITN-2016 Background Although the cardiac burden of COVID-19 has been demonstrated, follow-up imaging studies are scarce. The aim was to use speckle-tracking deformation imaging (STE) to prospectively assess cardiac function during intensive care unit (ICU) hospitalisation, comparing ventricular and atrial function of COVID-10 patients that died and those that were discharged. Methods In a single-centre, COVID-19 patients (n = 41) (71% male, aged 65 ± 11 years) were prospectively followed with echocardiography as part of ICU treatment. The left and right ventricles (LV, RV, respectively) were studied with STE in the 4-chamber cardiac view. The endpoint was defined as death or ICU discharge. Average values of the strain parameters from the first and final scans in the ICU, respectively, were calculated for the two outcome groups. Results Endpoint was not reached in 15% (n = 6) at the time of analysis. The remaining patients (n = 32) were 69% male, aged 66 (interquartile range (IQR) 60-72) years, and with an ICU mortality 26% (n = 9). The median spent in ICU was 24 (IQR 15-43) days. On average, echocardiography was performed three times during ICU hospitalisation, amounting to 103 examinations. The changes in cardiac strain are shown in Table 1. The change in LV longitudinal strain during ICU hospitalisation is shown in Figure 1. Conclusion Worsening of LV strain and lack of improvement of RV strain is linked to higher mortality in the ICU. The assessment of cardiac function might contain prognostic information in COVID-19 patients that are admitted to the ICU. Patients discharged from thee OCU (n = 23) Patients that died in the ICU (n = 9) P value Initial echo in the ICU LV strain, % (IQR) 18.00 (15.6-19.95) 14.4 (10.56-20.42) 0.158 RV strain, % (IQR) 16.00 (14.70-20.05) 15.50 (10.38-23.70) 0.712 Final echo before discharge LV strain, % (IQR) 17.35 (15.13-18.98) 13.20 (10.75-15.40) 0.007 RV strain, % (IQR) 17.65 (16.83-19.60) 15.75 (10.68-20.43) 0.438 ICU - intensive care unit; IQR-inter-quartile range Abstract Figure 1

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.

scholarly journals Intelligent Management of Sepsis in the Intensive Care Unit

2012 ◽  
pp. 1-16
Author(s):  
Vicent J. Ribas ◽  
Juan Carlos Ruiz-Rodríguez ◽  
Alfredo Vellido
Keyword(s):  
Intensive Care Unit ◽  
Logistic Regression ◽  
Intensive Care ◽  
Support Vector ◽  
Clinical Settings ◽  
Svm Model ◽  
Intelligent Management ◽  
Alternative Techniques ◽  
Research Challenge ◽  
Mortality Predictors

Sepsis is a transversal pathology and one of the main causes of death in the Intensive Care Unit (ICU). It has in fact become the tenth most common cause of death in western societies. Its mortality rates can reach up to 60% for Septic Shock, its most acute manifestation. For these reasons, the prediction of the mortality caused by Sepsis is an open and relevant medical research challenge. This problem requires prediction methods that are robust and accurate, but also readily interpretable. This is paramount if they are to be used in the demanding context of real-time decision making at the ICU. In this brief contribution, three different methods are presented. One is based on a variant of the well-known support vector machine (SVM) model and provides and automated ranking of relevance of the mortality predictors while the other two are based on logistic-regression and logistic regression over latent Factors. The reported results show that the methods presented outperform in terms of accuracy alternative techniques currently in use in clinical settings, while simultaneously assessing the relative impact of individual pathology indicators.

scholarly journals Association between early mobilization or rehabilitation and intensive care unit acquired weakness: A systematic review and meta-analysis of randomized controlled trials.

2020 ◽  
Author(s):  
Minghang Li ◽  
Mingyue Ding ◽  
Huanzhang Shao ◽  
Bingyu Qin ◽  
Xingwei Wang ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Meta Analysis ◽  
Early Mobilization ◽  
Standard Of Care ◽  
Cochrane Library ◽  
Care Group ◽  
China National Knowledge Infrastructure ◽  
Number Of Patients ◽  
Icu Discharge

Abstract Background The prognosis of intensive care unit acquired weakness (ICUAW) is poor and the treatment effect is not ideal. At present, some effective and safe early prevention means are urgently needed to reduce its incidence.This study evaluated the effectiveness and safety of early activities or rehabilitation in the prevention of ICUAW. Methods We searched for articles in five electronic databases, including PubMed, EMBASE, the Cochrane Library, the China National Knowledge Infrastructure (CNKI) and Wanfang Med Online. All publications until June, 2020 were searched. We have selected trials investigating early mobilization or rehabilitation as compared to standard of care in critically ill adults.The extracted data included adverse events, the number of patients with ICUAW, the length of stay in the ICU (ICU-LOS) the length of mechanical ventilation (MV) etc. Results The final results showed that compared with the usual care group, early mobilization or rehabilitation reduced the prevalence of ICUAW (RR, 0.73; [0.61, 0.87]; I2 = 44%; P = 0.0006), ICU-LOS (MD, − 1.47;[2.83, 0.10]; I2 = 56%; P = 0.04), length of MV (MD, − 1.96; [2.41, 1.51]; I2 = 0%; P = 0.00001), but the mortality (RR, 0.90; [0.62, 1.32]; I2 = 3%; P = 0.60) at ICU discharge was not associated. The subgroup analysis of ICUAW prevalence and ICU-LOS based on the intervention methods showed that early combined rehabilitation could reduce the prevalence of ICUAW (RR, 0.56; [0.43, 0.74]; I2 = 34%; P = 0.0001) and shorten the ICU-LOS (MD, − 2.21; [3.28, 0.97]; I2 = 23%; P = 0.0003). EGDM was not associated with a decrease in ICUAW prevalence (RR, 0.85; [0.65, 1.09]; I2 = 26%; P = 0.20), but it reduced the ICU-LOS (MD, − 2.27; [3.86, 0.68]; I2 = 0%; P = 0.005).Early in-bed cycling was not associated with reduced ICUAW prevalence(RR, 1.25; [0.73, 2.13]; I2 = 0%; P = 0.41) and ICU-LOS(MD, 2.27; [0.27, 4.80]; I2 = 0%; P = 0.08) . Conclusions Early mobilization or rehabilitation was associated with a shorter length of MV and ICU-LOS, but not mortality. Of course, not all early activities or forms of rehabilitation are effective. The early combined rehabilitation model is effective for the prevention of ICUAW. However, EGDM and early in-bed cycling were not effective in preventing ICUAW.

scholarly journals Development and Validation of Unplanned Extubation Prediction Models Using Intensive Care Unit Data: Comparative Machine Learning Study (Preprint)

2020 ◽  
Author(s):  
Sujeong Hur ◽  
Ji Young Min ◽  
Junsang Yoo ◽  
Kyunga Kim ◽  
Chi Ryang Chung ◽  
...  
Keyword(s):  
Machine Learning ◽  
Intensive Care Unit ◽  
Patient Safety ◽  
Intensive Care ◽  
Predictive Value ◽  
Prediction Models ◽  
Support Vector ◽  
Unplanned Extubation ◽  
Electronic Health Record Data ◽  
Icu Patients

BACKGROUND Patient safety in the intensive care unit (ICU) is one of the most critical issues, and unplanned extubation (UE) is considered as the most adverse event for patient safety. Prevention and early detection of such an event is an essential but difficult component of quality care. OBJECTIVE This study aimed to develop and validate prediction models for UE in ICU patients using machine learning. METHODS This study was conducted an academic tertiary hospital in Seoul. The hospital had approximately 2,000 inpatient beds and 120 intensive care unit (ICU) beds. The number of patients, on daily basis, was approximately 9,000 for the out-patient. The number of annual ICU admission was approximately 10,000. We conducted a retrospective study between January 1, 2010 and December 31, 2018. A total of 6,914 extubation cases were included. We developed an unplanned extubation prediction model using machine learning algorithms, which included random forest (RF), logistic regression (LR), artificial neural network (ANN), and support vector machine (SVM). For evaluating the model’s performance, we used area under the receiver operator characteristic curve (AUROC). Sensitivity, specificity, positive predictive value negative predictive value, and F1-score were also determined for each model. For performance evaluation, we also used calibration curve, the Brier score, and the Hosmer-Lemeshow goodness-of-fit statistic. RESULTS Among the 6,914 extubation cases, 248 underwent UE. In the UE group, there were more males than females, higher use of physical restraints, and fewer surgeries. The incidence of UE was more likely to occur during the night shift compared to the planned extubation group. The rate of reintubation within 24 hours and hospital mortality was higher in the UE group. The UE prediction algorithm was developed, and the AUROC for RF was 0.787, for LR was 0.762, for ANN was 0.762, and for SVM was 0.740. CONCLUSIONS We successfully developed and validated machine learning-based prediction models to predict UE in ICU patients using electronic health record data. The best AUROC was 0.787, which was obtained using RF. CLINICALTRIAL N/A

scholarly journals Primary brain tumor patients admitted to a US intensive care unit: a descriptive analysis

CNS Oncology ◽  
2021 ◽  
pp. CNS77
Author(s):  
Jennifer H Kang ◽  
Christa B Swisher ◽  
Evan D Buckley ◽  
James E Herndon ◽  
Eric S Lipp ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Brain Tumor ◽  
Hematological Malignancies ◽  
Descriptive Analysis ◽  
Primary Brain Tumor ◽  
Icu Mortality ◽  
Tumor Patients ◽  
Common Indication ◽  
Better Than

Purpose: To describe our population of primary brain tumor (PBT) patients, a subgroup of cancer patients whose intensive care unit (ICU) outcomes are understudied. Methods: Retrospective analysis of PBT patients admitted to an ICU between 2013 to 2018 for an unplanned need. Using descriptive analyses, we characterized our population and their outcomes. Results: Fifty-nine PBT patients were analyzed. ICU mortality was 19% (11/59). The most common indication for admission was seizures (n = 16, 27%). Conclusion: Our ICU mortality of PBT patients was comparable to other solid tumor patients and the general ICU population and better than patients with hematological malignancies. Further study of a larger population would inform guidelines for triaging PBT patients who would most benefit from ICU-level care.

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