Dataset Information

Early mobilization and recovery in mechanically ventilated patients in the ICU: a bi-national, multi-centre, prospective cohort study.

ABSTRACT: The aim of this study was to investigate current mobilization practice, strength at ICU discharge and functional recovery at 6 months among mechanically ventilated ICU patients.This was a prospective, multi-centre, cohort study conducted in twelve ICUs in Australia and New Zealand. Patients were previously functionally independent and expected to be ventilated for >48 hours. We measured mobilization during invasive ventilation, sedation depth using the Richmond Agitation and Sedation Scale (RASS), co-interventions, duration of mechanical ventilation, ICU-acquired weakness (ICUAW) at ICU discharge, mortality at day 90, and 6-month functional recovery including return to work.We studied 192 patients (mean age 58.1?±?15.8 years; mean Acute Physiology and Chronic Health Evaluation (APACHE) (IQR) II score, 18.0 (14 to 24)). Mortality at day 90 was 26.6% (51/192). Over 1,351 study days, we collected information during 1,288 planned early mobilization episodes in patients on mechanical ventilation for the first 14 days or until extubation (whichever occurred first). We recorded the highest level of early mobilization. Despite the presence of dedicated physical therapy staff, no mobilization occurred in 1,079 (84%) of these episodes. Where mobilization occurred, the maximum levels of mobilization were exercises in bed (N?=?94, 7%), standing at the bed side (N?=?11, 0.9%) or walking (N?=?26, 2%). On day three, all patients who were mobilized were mechanically ventilated via an endotracheal tube (N?=?10), whereas by day five 50% of the patients mobilized were mechanically ventilated via a tracheostomy tube (N?=?18).Early mobilization of patients receiving mechanical ventilation was uncommon. More than 50% of patients discharged from the ICU had developed ICU-acquired weakness, which was associated with death between ICU discharge and day-90.ClinicalTrials.gov NCT01674608. Registered 14 August 2012.

SUBMITTER: TEAM Study Investigators

PROVIDER: S-EPMC4342087 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Early mobilization and recovery in mechanically ventilated patients in the ICU: a bi-national, multi-centre, prospective cohort study.

Hodgson Carol C Bellomo Rinaldo R Berney Susan S Bailey Michael M Buhr Heidi H Denehy Linda L Harrold Megan M Higgins Alisa A Presneill Jeff J Saxena Manoj M Skinner Elizabeth E Young Paul P Webb Steven S

Critical care (London, England) 20150226

<h4>Introduction</h4>The aim of this study was to investigate current mobilization practice, strength at ICU discharge and functional recovery at 6 months among mechanically ventilated ICU patients.<h4>Method</h4>This was a prospective, multi-centre, cohort study conducted in twelve ICUs in Australia and New Zealand. Patients were previously functionally independent and expected to be ventilated for >48 hours. We measured mobilization during invasive ventilation, sedation depth using the Richmon ...[more]

PMID: 25715872

Similar Datasets

Project description:BackgroundThis systematic review and meta-analysis aimed to determine the effectiveness of systematic early mobilization in improving muscle strength and physical function in mechanically ventilated intensive care unit (ICU) patients.MethodsWe conducted a two-stage systematic literature search in MEDLINE, EMBASE and the Cochrane Library until January 2019 for randomized controlled trials (RCTs) examining the effects of early mobilization initiated within 7 days after ICU admission compared with late mobilization, standard early mobilization or no mobilization. Priority outcomes were Medical Research Council Sum Score (MRC-SS), incidence of ICU-acquired weakness (ICUAW), 6-min walk test (6MWT), proportion of patients reaching independence, time needed until walking, SF-36 Physical Function Domain Score (PFS) and SF-36 Physical Health Component Score (PCS). Meta-analysis was conducted where sufficient comparable evidence was available. We evaluated the certainty of evidence according to the GRADE approach.ResultsWe identified 12 eligible RCTs contributing data from 1304 participants. Two RCTs were categorized as comparing systematic early with late mobilization, nine with standard early mobilization and one with no mobilization. We found evidence for a benefit of systematic early mobilization compared to late mobilization for SF-36 PFS (MD 12.3; 95% CI 3.9-20.8) and PCS (MD 3.4; 95% CI 0.01-6.8), as well as on the proportion of patients reaching independence and the time needed to walking, but not for incidence of ICUAW (RR 0.62; 95% CI 0.38-1.03) or MRC-SS. For systematic early compared to standard early mobilization, we found no statistically significant benefit on MRC-SS (MD 5.8; 95% CI - 1.4 to 13.0), incidence of ICUAW (RR 0.90; 95% CI 0.63-1.27), SF-36 PFS (MD 8.1; 95% CI - 15.3 to 31.4) or PCS (MD - 2.4; 95% CI - 6.1 to 1.3) or other priority outcomes except for change in 6MWT from baseline. Generally, effects appeared stronger for systematic early compared to late mobilization than to standard early mobilization. We judged the certainty of evidence for all outcomes as very low to low.ConclusionThe evidence regarding a benefit of systematic early mobilization remained inconclusive. However, our findings indicate that the larger the difference in the timing between the intervention and the comparator, the more likely an RCT is to find a benefit for early mobilization.Study registrationPROSPERO (CRD42019122555).

Project description:BackgroundPersistent swallowing disorders (SD) are non-pulmonary complications of mechanical ventilation (MV). However, there are few clinical studies on persistent SD in critically ill patients undergoing tracheal intubation for MV. The aim of the present study was to assess the incidence and characteristics of clinical manifestations associated with persistent SD.MethodsWe prospectively evaluated in patients requiring more than 7 days of invasive MV the incidence and characteristics of clinical manifestations related to persistent SD. For this purpose, quality of swallowing was assessed within 24 h after extubation by an experienced physical therapist not directly involved in patient management. Swallowing assessment consisted in a specific standardized test combining a swallowing test and a full clinical evaluation of the cranial nerves involved in swallowing. In patients with SD on the first test, a second test was done within 48 h in order to discriminate between transient and persistent SD.ResultsAmong the 482 patients mechanically ventilated more than 7 days, 138 were enrolled in this study. The first test performed 24 h after extubation revealed SD in 35 patients (25%). According to the second test performed 48 h later, SD were considered transient in 21 (15%) and persistent in 14 (10%) cases. Patients with persistent SD were older (66 ± 16 vs 58 ± 15 years), had lower bodyweight at admission (76 ± 15 vs 87 ± 23 kg) and received less often neuromuscular blocking agents (36% vs 66%) compared to patients without or with only transient SD. Patients with persistent SD had longer duration of Intensive Care Unit (ICU) stay after first extubation and longer delay to oral feeding than patients without or with only transient SD, respectively, 11 ± 9 vs 7 ± 6 days and 23 ± 33 vs 5 ± 7 days.ConclusionsBased on a specific standardized clinical test, 25% of patients mechanically ventilated more than 7 days exhibited clinical manifestations of SD. However, SD were considered as persistent after extubation in only 10% of them. Persistent SD were associated with longer duration of ICU stay after extubation and longer time of enteral feeding.Trial registrationThe study is registered with Clinical Trials (NCT01360580).

Project description:BackgroundICU patients undergoing invasive mechanical ventilation experience cognitive decline associated with their critical illness and its management. The early detection of different cognitive phenotypes might reveal the involvement of diverse pathophysiological mechanisms and help to clarify the role of the precipitating and predisposing factors. Our main objective is to identify cognitive phenotypes in critically ill survivors 1 month after ICU discharge using an unsupervised machine learning method, and to contrast them with the classical approach of cognitive impairment assessment. For descriptive purposes, precipitating and predisposing factors for cognitive impairment were explored.MethodsA total of 156 mechanically ventilated critically ill patients from two medical/surgical ICUs were prospectively studied. Patients with previous cognitive impairment, neurological or psychiatric diagnosis were excluded. Clinical variables were registered during ICU stay, and 100 patients were cognitively assessed 1 month after ICU discharge. The unsupervised machine learning K-means clustering algorithm was applied to detect cognitive phenotypes. Exploratory analyses were used to study precipitating and predisposing factors for cognitive impairment.ResultsK-means testing identified three clusters (K) of patients with different cognitive phenotypes: K1 (n = 13), severe cognitive impairment in speed of processing (92%) and executive function (85%); K2 (n = 33), moderate-to-severe deficits in learning-memory (55%), memory retrieval (67%), speed of processing (36.4%) and executive function (33.3%); and K3 (n = 46), normal cognitive profile in 89% of patients. Using the classical approach, moderate-to-severe cognitive decline was recorded in 47% of patients, while the K-means method accurately classified 85.9%. The descriptive analysis showed significant differences in days (p = 0.016) and doses (p = 0.039) with opioid treatment in K1 vs. K2 and K3. In K2, there were more women, patients were older and had more comorbidities (p = 0.001) than in K1 or K3. Cognitive reserve was significantly (p = 0.001) higher in K3 than in K1 or K2.ConclusionOne month after ICU discharge, three groups of patients with different cognitive phenotypes were identified through an unsupervised machine learning method. This novel approach improved the classical classification of cognitive impairment in ICU survivors. In the exploratory analysis, gender, age and the level of cognitive reserve emerged as relevant predisposing factors for cognitive impairment in ICU patients.Trial registrationClinicalTrials.gov Identifier:NCT02390024; March 17,2015.

Project description:OBJECTIVES:In the contemporary ICU, mechanically ventilated patients may not have arterial blood gas measurements available at relevant timepoints. Severity criteria often depend on arterial blood gas results. Retrospective studies suggest that nonlinear imputation of PaO2/FIO2 from SpO2/FIO2 is accurate, but this has not been established prospectively among mechanically ventilated ICU patients. The objective was to validate the superiority of nonlinear imputation of PaO2/FIO2 among mechanically ventilated patients and understand what factors influence the accuracy of imputation. DESIGN:Simultaneous SpO2, oximeter characteristics, receipt of vasopressors, and skin pigmentation were recorded at the time of a clinical arterial blood gas. Acute respiratory distress syndrome criteria were recorded. For each imputation method, we calculated both imputation error and the area under the curve for patients meeting criteria for acute respiratory distress syndrome (PaO2/FIO2 ? 300) and moderate-severe acute respiratory distress syndrome (PaO2/FIO2 ? 150). SETTING:Nine hospitals within the Prevention and Early Treatment of Acute Lung Injury network. PATIENTS:We prospectively enrolled 703 mechanically ventilated patients admitted to the emergency departments or ICUs of participating study hospitals. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:We studied 1,034 arterial blood gases from 703 patients; 650 arterial blood gases were associated with SpO2 less than or equal to 96%. Nonlinear imputation had consistently lower error than other techniques. Among all patients, nonlinear had a lower error (p < 0.001) and higher (p < 0.001) area under the curve (0.87; 95% CI, 0.85-0.90) for PaO2/FIO2 less than or equal to 300 than linear/log-linear (0.80; 95% CI, 0.76-0.83) imputation. All imputation methods better identified moderate-severe acute respiratory distress syndrome (PaO2/FIO2 ? 150); nonlinear imputation remained superior (p < 0.001). For PaO2/FIO2 less than or equal to 150, the sensitivity and specificity for nonlinear imputation were 0.87 (95% CI, 0.83-0.90) and 0.91 (95% CI, 0.88-0.93), respectively. Skin pigmentation and receipt of vasopressors were not associated with imputation accuracy. CONCLUSIONS:In mechanically ventilated patients, nonlinear imputation of PaO2/FIO2 from SpO2/FIO2 seems accurate, especially for moderate-severe hypoxemia. Linear and log-linear imputations cannot be recommended.

Project description:BackgroundMechanical ventilation (MV) is vital for critically ill ICU patients but carries significant mortality risks. This study aims to develop a predictive model to estimate hospital mortality among MV patients, utilizing comprehensive health data to assist ICU physicians with early-stage alerts.MethodsWe developed a Machine Learning (ML) framework to predict hospital mortality in ICU patients receiving MV. Using the MIMIC-III database, we identified 25,202 eligible patients through ICD-9 codes. We employed backward elimination and the Lasso method, selecting 32 features based on clinical insights and literature. Data preprocessing included eliminating columns with over 90% missing data and using mean imputation for the remaining missing values. To address class imbalance, we used the Synthetic Minority Over-sampling Technique (SMOTE). We evaluated several ML models, including CatBoost, XGBoost, Decision Tree, Random Forest, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Logistic Regression, using a 70/30 train-test split. The CatBoost model was chosen for its superior performance in terms of accuracy, precision, recall, F1-score, AUROC metrics, and calibration plots.ResultsThe study involved a cohort of 25,202 patients on MV. The CatBoost model attained an AUROC of 0.862, an increase from an initial AUROC of 0.821, which was the best reported in the literature. It also demonstrated an accuracy of 0.789, an F1-score of 0.747, and better calibration, outperforming other models. These improvements are due to systematic feature selection and the robust gradient boosting architecture of CatBoost.ConclusionThe preprocessing methodology significantly reduced the number of relevant features, simplifying computational processes, and identified critical features previously overlooked. Integrating these features and tuning the parameters, our model demonstrated strong generalization to unseen data. This highlights the potential of ML as a crucial tool in ICUs, enhancing resource allocation and providing more personalized interventions for MV patients.

Project description:BackgroundIn most countries, patients receiving mechanical ventilation (MV) are treated in intensive care units (ICUs). However, in some countries, including Japan, many patients on MV are not treated in ICUs. There are insufficient epidemiological data on these patients. Here, we sought to describe the epidemiology of patients on MV in Japan by comparing and contrasting patients on MV treated in ICUs and in non-ICU settings. A preliminary comparison of patient outcomes between ICU and non-ICU patients was a secondary objective.MethodsData on adult patients receiving MV for at least 3 days in ICUs or non-ICU settings from April 2010 through March 2012 were obtained from the Quality Indicator/Improvement Project, a voluntary data-administration project covering more than 400 acute-care hospitals in Japan. We excluded patients with cancer-related diagnoses. Patient demographic data and the critical care provided were compared between groups.ResultsOver the study period, 17,775 patients on MV were treated only in non-ICU settings, whereas 20,516 patients were treated at least once in ICUs (46.4% vs. 53.6%). Average age was higher in non-ICU patients than in ICU patients (72.8 vs. 70.2, P?<?0.001). Mean number of ventilation days was greater in non-ICU patients (11.7 vs. 9.5, P?<?0.001). Hospital mortality was higher in non-ICU patients (41.4% vs. 38.8%, P?<?0.001). Standard critical care (e.g., arterial line placement, enteral nutrition, and stress-ulcer prevention) was provided significantly less often in non-ICU patients. Multivariate analysis showed that ICU admission significantly decreased hospital mortality (adjusted odds ratio 0.713, 95% CI 0.676 to 0.753).ConclusionsA large proportion of Japanese patients on MV were treated in non-ICU settings. Analysis of administrative data indicated preliminarily that hospital mortality rates in these patients were higher in non-ICU settings than in ICUs. Prospective analyses comparing non-ICU and ICU patients on MV by severity scoring are needed.

Project description:BackgroundBiomarkers can be used to detect the presence of endothelial and/or alveolar epithelial injuries in case of ARDS. Angiopoietin-2 (Ang-2), soluble intercellular adhesion molecule-1 (ICAM-1), vascular cell adhesion protein-1 (VCAM-1), P-selectin and E-selectin are biomarkers of endothelial injury, whereas the receptor for advanced glycation end-products (RAGE) reflects alveolar epithelial injury. The aims of this study were to evaluate whether the plasma concentration of the above-mentioned biomarkers was different 1) in survivors and non-survivors of COVID-19-related ARDS and 2) in COVID-19-related and classical ARDS.MethodsThis prospective study was performed in two COVID-19-dedicated Intensive Care Units (ICU) and one non-COVID-19 ICU at Ferrara University Hospital. A cohort of 31 mechanically ventilated patients with COVID-19 ARDS and a cohort of 11 patients with classical ARDS were enrolled. Ang-2, ICAM-1, VCAM-1, P-selectin, E-selectin and RAGE were determined with a bead-based multiplex immunoassay at three time points: inclusion in the study (T1), after 7 ± 2 days (T2) and 14 ± 2 days (T3). The primary outcome was to evaluate the plasma trend of the biomarker levels in survivors and non-survivors. The secondary outcome was to evaluate the differences in respiratory mechanics variables and gas exchanges between survivors and non-survivors. Furthermore, we compared the plasma levels of the biomarkers at T1 in patients with COVID-19-related ARDS and classical ARDS.ResultsIn COVID-19-related ARDS, the plasma levels of Ang-2 and ICAM-1 at T1 were statistically higher in non-survivors than survivors, (p = 0.04 and p = 0.03, respectively), whereas those of P-selectin, E-selectin and RAGE did not differ. Ang-2 and ICAM-1 at T1 were predictors of mortality (AUROC 0.650 and 0.717, respectively). At T1, RAGE and P-selectin levels were higher in classical ARDS than in COVID-19-related ARDS. Ang-2, ICAM-1 and E-selectin were lower in classical ARDS than in COVID-19-related ARDS (all p < 0.001).ConclusionsCOVID-19 ARDS is characterized by an early pulmonary endothelial injury, as detected by Ang-2 and ICAM-1. COVID-19 ARDS and classical ARDS exhibited a different expression of biomarkers, suggesting different pathological pathways. Trial registration NCT04343053 , Date of registration: April 13, 2020.

Dataset Information

Early mobilization and recovery in mechanically ventilated patients in the ICU: a bi-national, multi-centre, prospective cohort study.

Publications

Early mobilization and recovery in mechanically ventilated patients in the ICU: a bi-national, multi-centre, prospective cohort study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets