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Persistent swallowing disorders after extubation in mechanically ventilated patients in ICU: a two-center prospective study.

ABSTRACT: BACKGROUND:Persistent 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. METHODS:We 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. RESULTS:Among 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. CONCLUSIONS:Based 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 REGISTRATION:The study is registered with Clinical Trials (NCT01360580).

SUBMITTER: Beduneau G

PROVIDER: S-EPMC7560673 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Persistent swallowing disorders after extubation in mechanically ventilated patients in ICU: a two-center prospective study.

Beduneau G G Souday V V Richard J C JC Hamel J F JF Carpentier D D Chretien J M JM Bouchetemble P P Laccoureye L L Astier A A Tanguy V V Mercat A A Beloncle F F Tamion F F

Annals of intensive care 20201014 1

<h4>Background</h4>Persistent 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.<h4>Methods</h4>We prospectively evaluated in patients requiring more than 7 days of invasive MV the incidence and characte ...[more]

PMID: 33052476

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Project description:Despite the best efforts of intensive care units (ICUs) professionals, the extubation failure rates in mechanically ventilated patients remain in the range of 5%-30%. Extubation failure is associated with increased risk of death and longer ICU stay. This study aimed to identify respiratory and non-respiratory parameters predictive of extubation outcome, and to use these predictors to develop and validate an "Extubation Predictive Score (ExPreS)" that could be used to predict likelihood of extubation success in patients receiving invasive mechanical ventilation (IMV). Derivation cohort was composed by patients aged ≥18 years admitted to the ICU and receiving IMV through an endotracheal tube for >24 hours. The weaning process followed the established ICU protocol. Clinical signs and ventilator parameters of patients were recorded during IMV, in the end phase of weaning in pressure support ventilation (PSV) mode, with inspiratory pressure of 7 cm H2O over the PEEP (positive end expiratory pressure). Patients who tolerated this ventilation were submitted to spontaneous breathing trial (SBT) with T-tube for 30 minutes. Those who passed the SBT and a subsequent cuff-leak test were extubated. The primary outcome of this study was extubation success at 48 hours. Parameters that showed statistically significant association with extubation outcome were further investigated using the receiver operating characteristics (ROC) analysis to assess their predictive value. The area under the curve (AUC) values were used to select parameters for inclusion in the ExPreS. Univariable logistic regression analysis and ROC analysis were performed to evaluate the performance of ExPreS. Patients' inclusion and statistical analyses for the prospective validation cohort followed the same criteria used for the derivation cohort and the decision to extubate was based on the ExPreS result. In the derivation cohort, a total of 110 patients were extubated: extubation succeeded in 101 (91.8%) patients and failed in 9 (8.2%) patients. Rapid shallow-breathing index (RSBI) in SBT, dynamic lung compliance, duration of IMV, muscle strength, estimated GCS, hematocrit, and serum creatinine were significantly associated with extubation outcome. These parameters, along with another parameter-presence of neurologic comorbidity-were used to create the ExPreS. The AUC value for the ExPreS was 0.875, which was higher than the AUCs of the individual parameters. The total ExPreS can range from 0 to 100. ExPreS ≥59 points indicated high probability of success (OR = 23.07), while ExPreS ≤44 points indicated low probability of success (OR = 0.82). In the prospective validation cohort, 83 patients were extubated: extubation succeeded in 81 (97.6%) patients and failed in 2 (2.4%) patients. The AUC value for the ExPreS in this cohort was 0.971. The multiparameter score that we propose, ExPreS, shows good accuracy to predict extubation outcome in patients receiving IMV in the ICU. In the prospective validation, the use of ExPreS decreased the extubation failure rate from 8.2% to 2.4%, even in a cohort of more severe patients.

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:IntroductionThe 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.MethodThis 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.ResultsWe 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).ConclusionsEarly 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.Clinical trial registrationClinicalTrials.gov NCT01674608. Registered 14 August 2012.

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.

Dataset Information

Persistent swallowing disorders after extubation in mechanically ventilated patients in ICU: a two-center prospective study.

Publications

Persistent swallowing disorders after extubation in mechanically ventilated patients in ICU: a two-center prospective study.

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