Predicting success in weaning from mechanical ventilation

Ventilator Weaning and Extubation

Increasing evidence supports specific approaches to liberate patients from invasive ventilation including the use of liberation protocols, inspiratory assistance during spontaneous breathing trials (SBTs), early extubation of patients with chronic obstructive pulmonary disease to noninvasive ventilation, and prophylactic use of noninvasive support strategies after extubation. Additional research is needed to elucidate the best criteria to identify patients who are ready to undergo an SBT and to inform optimal screening frequency, the best SBT technique and duration, extubation assessments, and extubation decision-making. Additional clarity is also needed regarding the optimal timing to measure and report extubation success.

Comparison of the Recent ExPreS Score, WEANSNOW Score, and the Parsimonious HACOR Score as the Best Predictor of Weaning: An Externally Validated Prospective Observational Study

Background

Since weaning failure is multifactorial, comprehensive weaning scores encompassing not only the respiratory component but also nonrespiratory aspects are quintessential for successful weaning prediction.

Materials and methods

This was a single-center prospective observational study on 128 intensive care unit (ICU) patients undergoing spontaneous breathing trials (SBT). The extubation prediction score (ExPreS), heart rate, acidosis, consciousness, oxygenation, respiratory rate (HACOR), and weaning parameters, endotracheal tube size, arterial blood gas analysis, nutrition, secretions, neuromuscular affecting agents, obstructive airway problems and wakefulness (WEANSNOW) scores were compared for their diagnostic accuracy for successful weaning prediction.

Results

Out of 128 patients, 49 (38.3%) patients had weaning failure, and 79 (61.7%) had weaning success. The patients in the weaning failure group had significantly higher APACHE II scores, WEANSNOW scores, HACOR scores, MV days, and significantly lower ExPreS scores as compared to the successful weaning group. Multivariable regression analysis showed that ExPreS score p = 0.015, adjusted OR 0.960, 95% CI (0.929-0.992) and HACOR score p < 0.001, adjusted OR 1.357, 95% CI (1.176-1.567) were independent predictors of weaning failure. The HACOR score had an AUC of 0.830, cut-off ≥5, p < 0.001, sensitivity 76%, specificity 68%, diagnostic accuracy 70% to predict weaning failure. The ExPreS score had an AUC of 0.735, cut-off ≥69, p < 0.001, sensitivity of 70.9%, specificity of 69.4%, and diagnostic accuracy of 70.3% to predict weaning success. Both the HACOR and ExPreS scores were good models for predicting weaning outcomes (model quality 0.76 and 0.64 respectively).

Conclusion

The parsimonious HACOR score is comparable to the ExPreS score for the prediction of weaning outcomes in critically ill patients.

How to cite this article

Nayak G, Chaudhuri S, Ravindranath S, Todur P. Comparison of the Recent ExPreS Score, WEANSNOW Score, and the Parsimonious HACOR Score as the Best Predictor of Weaning: An Externally Validated Prospective Observational Study. Indian J Crit Care Med 2024;28(3):273-279.

Liberation from mechanical ventilation in critically ill patients: Korean Society of Critical Care Medicine Clinical Practice Guidelines

BACKGROUND

Successful liberation from mechanical ventilation is one of the most crucial processes in critical care because it is the first step by which a respiratory failure patient begins to transition out of the intensive care unit and return to their own life. Therefore, when devising appropriate strategies for removing mechanical ventilation, it is essential to consider not only the individual experiences of healthcare professionals, but also scientific and systematic approaches. Recently, numerous studies have investigated methods and tools for identifying when mechanically ventilated patients are ready to breathe on their own. The Korean Society of Critical Care Medicine therefore provides these recommendations to clinicians about liberation from the ventilator.

METHODS

Meta-analyses and comprehensive syntheses were used to thoroughly review, compile, and summarize the complete body of relevant evidence. All studies were meticulously assessed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) method, and the outcomes were presented succinctly as evidence profiles. Those evidence syntheses were discussed by a multidisciplinary committee of experts in mechanical ventilation, who then developed and approved recommendations.

RESULTS

Recommendations for nine PICO (population, intervention, comparator, and outcome) questions about ventilator liberation are presented in this document. This guideline includes seven conditional recommendations, one expert consensus recommendation, and one conditional deferred recommendation.

CONCLUSIONS

We developed these clinical guidelines for mechanical ventilation liberation to provide meaningful recommendations. These guidelines reflect the best treatment for patients seeking liberation from mechanical ventilation.

In vivocharacterization of the optical and hemodynamic properties of the human sternocleidomastoid muscle through ultrasound-guided hybrid near-infrared spectroscopies

Objective.In this paper, we present a detailedin vivocharacterization of the optical and hemodynamic properties of the human sternocleidomastoid muscle (SCM), obtained through ultrasound-guided near-infrared time-domain and diffuse correlation spectroscopies.Approach.A total of sixty-five subjects (forty-nine females, sixteen males) among healthy volunteers and thyroid nodule patients have been recruited for the study. Their SCM hemodynamic (oxy-, deoxy- and total hemoglobin concentrations, blood flow, blood oxygen saturation and metabolic rate of oxygen extraction) and optical properties (wavelength dependent absorption and reduced scattering coefficients) have been measured by the use of a novel hybrid device combining in a single unit time-domain near-infrared spectroscopy, diffuse correlation spectroscopy and simultaneous ultrasound imaging.Main results.We provide detailed tables of the results related to SCM baseline (i.e. muscle at rest) properties, and reveal significant differences on the measured parameters due to variables such as side of the neck, sex, age, body mass index, depth and thickness of the muscle, allowing future clinical studies to take into account such dependencies.Significance.The non-invasive monitoring of the hemodynamics and metabolism of the sternocleidomastoid muscle during respiration became a topic of increased interest partially due to the increased use of mechanical ventilation during the COVID-19 pandemic. Near-infrared diffuse optical spectroscopies were proposed as potential practical monitors of increased recruitment of SCM during respiratory distress. They can provide clinically relevant information on the degree of the patient's respiratory effort that is needed to maintain an optimal minute ventilation, with potential clinical application ranging from evaluating chronic pulmonary diseases to more acute settings, such as acute respiratory failure, or to determine the readiness to wean from invasive mechanical ventilation.

Rate of Change of Rapid Shallow Breathing Index and Extubation Outcome in Mechanically Ventilated Patients

Background

Rapid shallow breathing index (RSBI) has been widely used as a predictor of extubation outcome in mechanically ventilated patients. We hypothesize that the rate of change of RSBI between the beginning and end of a 120-minute spontaneous breathing trial (SBT) could be a better predictor of extubation outcome than a single RSBI measured at the end of SBT in mechanically ventilated patients. Methodology. In this prospective observational study, we enrolled 193 patients who met the inclusion criteria, of whom 33 patients were unable to tolerate a 120-minute SBT and were excluded from the study. The study population consisted of 160 patients, categorized into three subgroups: patients with normal lung (no reported history of respiratory diseases), patients with airway disease, and patients with parenchymal disease who completed 120 minutes of SBT on low levels of pressure support ventilation. RSBI was obtained from the ventilator display at the 5th and the 120th minutes of SBT. The rate of change of RSBI (RSBI 5-120) was calculated as (RSBI 2-RSBI 1)/RSBI 1 × 100. Receiver-operating characteristic (ROC) curves were plotted for RSBI 5-120 and RSBI 120 in all patients and among the three subgroups (normal group, airway group, and parenchymal group) to compare the superiority of their best thresholds in predicting extubation failure.

Results

The RSBI 5-120 threshold for extubation failure in the entire patient group was 23% with an overall accuracy of 88% (AUC = 0.933, sensitivity = 91%, and specificity = 86%) and the threshold of RSBI 120 for extubation failure in the entire patient group was 70 breaths/min/L with an overall accuracy of 82% (AUC = 0.899, sensitivity = 85%, and specificity = 81%). In patients in the normal lung group, the threshold of RSBI 5-120 was 22%, with an overall accuracy of 89% (AUC = 0.892, sensitivity = 87.5%, and specificity = 90%), and the RSBI 120 threshold was 70 breaths/min/L, with an overall accuracy of 89% (AUC = 0.956, sensitivity = 88%, and specificity = 90%). The RSBI 5-120 threshold in patients with airway disease was 25% with an accuracy of 86% (AUC = 0.892, sensitivity = 85%, and specificity = 86%) and the threshold of RSBI 120 was 73 breaths/min/L with an accuracy of 83% (AUC = 0.874, sensitivity = 85%, and specificity = 82%). In patients in the parenchymal disease group, the threshold of RSBI 5-120 was 24%, with an accuracy of 90% (AUC = 0.966, sensitivity = 92%, and specificity = 89%) and RSBI 120 threshold was 71 breaths/min/L, which was 88% accurate (AUC = 0.893, sensitivity = 85%, and specificity = 89%).

Conclusion

The rate of change of RSBI between the 5th and 120th minutes was moderately more accurate than the single value of RSBI measured at the 120th minute in predicting extubation outcome.

Comparison of the timed inspiratory effort index with the T-piece trial as a decision-making tool for extubation: a randomized controlled non-inferiority trial

The "timed inspiratory effort" (TIE) index, a new predictor of weaning outcome, normalizes the maximal inspiratory pressure with the time required to reach this value up to 60 s, incorporating the time domain into the assessment of inspiratory muscle function. The objective of this study was to determine whether the TIE predicts successful extubation at a similar rate as the T-piece trial with less time required. A non-inferiority randomized controlled trial was performed with ICU subjects eligible for weaning. The participants were allocated to the TIE or the T-piece groups. The primary outcome was successful weaning, and the main secondary outcome was ICU mortality. Eighty participants of each group were included in the final analysis. Time from the start of a successful test to effective extubation was significantly lower in the TIE group than in the T-piece group, 15 (10 to 24) vs 55 (40 to 75) min, P<0.001. In the Kaplan-Meier analysis, no significant differences were found in successful weaning (79.5 vs 82.5%, P=0.268) or survival rate (62.9 vs 53.8%, P=0.210) between the TIE and T-piece groups at the 30th day. In this preliminary study, the TIE index was not inferior to the T-piece trial as a decision-making tool for extubation and allowed a reduction in the decision time.

Clinical utility of diaphragmatic ultrasonography for mechanical ventilator weaning in adults: A study protocol for systematic review and meta-analysis

Background and Aims

Mechanical ventilation is associated with several risks, including barotrauma, ventilator-associated pneumonia, and ventilator-induced diaphragmatic dysfunction. A delay in weaning from mechanical ventilation increases these risks, and prolonged weaning has been shown to increase hospital mortality. Various tools have been used in clinical practice to predict successful weaning from mechanical ventilation; however, they have a low prognostic accuracy. The use of ultrasonography in intensive care units is an area of growing interest since it is a noninvasive, convenient, and safe modality. Since ultrasonography can provide real-time assessment of diaphragmatic morphology and function, it may have clinical utility in predicting successful mechanical ventilator weaning. This study aimed to describe a protocol to assess the effectiveness of diaphragmatic ultrasonography in the decision-making process for ventilator weaning in terms of its impact on clinical outcomes.

Methods

This systematic review of published analytical research will use an aggregative thematic approach according to the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols guidelines. We will perform a comprehensive search for studies on the MEDLINE, Embase, and Cochrane Central Register of Controlled Trials databases. Two authors will independently perform abstract and full-text screening and data extraction. Additionally, a meta-analysis and the risk of bias evaluation will be conducted, as appropriate.

Conclusion

Systematic reviews on the effectiveness of diaphragmatic ultrasonography in the decision-making process for ventilator weaning in terms of its impact on clinical outcomes are lacking. The results of this systematic review may serve as a basis for future clinical trials. Systematic review registration: This protocol was registered with the Open Science Framework: https://osf.io/cn8xf.

Predictive value of extubation failure by decrease in central venous oxygen saturation: A systematic review and meta-analysis

Background

The predictive power of extubation failure diagnosed by decrease in central venous oxygen saturation (ΔScvO2) varies by studies. Here we summarized the diagnostic value of extubation failure tested by ΔScvO2.

Methods

A comprehensive online search was performed to select potentially eligible studies that evaluated the predictive power of extubation failure tested by ΔScvO2. A manual search was also performed to identify additional studies. Data were extracted to calculate the pooled sensitivity, specificity, positive likelihood ratio (LR), negative LR, diagnostic odds ratio (DOR), and area under the receiver operating characteristic curve (AUC) to evaluate the predictive power of extubation failure.

Results

Overall, five studies including 353 patients were included in this review, of whom 105 (30%) were extubation failure. The cutoff values of ΔScvO2 varied across studies, ranging from 3.8% to 5.4%. Heterogeneity between studies was assessed with an overall Q = 0.007, I² = 0%, and P = 0.498. The pooled sensitivity and specificity for the overall population were 0.83 (95% CI: 0.74-0.90) and 0.88 (95% CI: 0.83-0.92), respectively. The pooled positive LR and negative LR were 7.2 (95%CI: 4.6-11.2) and 0.19 (95%CI: 0.12-0.31), respectively. The DOR was 38 (95% CI: 17-86). Overall, the pooled AUROC was 0.92 (95% CI: 0.90-0.94).

Conclusions

The ΔScvO2 performed well in predicting extubation failure in adult mechanical ventilation patients. Further studies with a larger data set and well-designed models are required to confirm the diagnostic accuracy and utility of ScvO2 in predicting extubation outcomes in mechanical ventilation patients.

Tests and Indices Predicting Extubation Failure in Children: A Systematic Review and Meta-analysis

INTRODUCTION

There is lack of consensus on what constitutes best practice when assessing extubation readiness in children. This systematic review aims to synthesize data from existing literature on pre-extubation assessments and evaluate their diagnostic accuracies in predicting extubation failure (EF) in children.

METHODS

A systematic search in PubMed, EMBASE, Web of Science, CINAHL, and Cochrane was performed from inception of each database to 15 July 2021. Randomized controlled trials or observational studies that studied the association between pre-extubation assessments and extubation outcome in the pediatric intensive care unit population were included. Meta-analysis was performed for studies that report diagnostic tests results of a combination of parameters.

RESULTS

In total, 41 of 11,663 publications screened were included (total patients, n = 8111). Definition of EF across studies was heterogeneous. Fifty-five unique pre-extubation assessments were identified. Parameters most studied were: respiratory rate (RR) (13/41, n = 1945), partial pressure of arterial carbon dioxide (10/41, n = 1379), tidal volume (13/41, n = 1945), rapid shallow breathing index (RBSI) (9/41, n = 1400), and spontaneous breathing trials (SBT) (13/41, n = 5652). Meta-analysis shows that RSBI, compliance rate oxygenation pressure (CROP) index, and SBT had sensitivities ranging from 0.14 to 0.57. CROP index had the highest sensitivity [0.57, 95% confidence interval (CI) 0.4-0.73] and area under curve (AUC, 0.98). SBT had the highest specificity (0.93, 95% CI 0.92-0.94).

CONCLUSIONS

Pre-extubation assessments studied thus far remain poor predictors of EF. CROP index, having the highest AUC, should be further explored as a predictor of EF. Standardizing the EF definition will allow better comparison of pre-extubation assessments.

Effects of aggressive and conservative strategies for mechanical ventilation liberation

BACKGROUND

The optimal approach for transitioning from strict lung protective ventilation to support modes of ventilation when patients determine their own respiratory rate and tidal volume remains unclear. While aggressive liberation from lung protective settings could expedite extubation and prevent harm from prolonged ventilation and sedation, conservative liberation could prevent lung injury from spontaneous breathing.

RESEARCH QUESTION

Should physicians take a more aggressive or conservative approach to liberation?

METHODS

Retrospective cohort study of mechanically ventilated patients from the Medical Information Mart for Intensive Care IV database (MIMIC-IV version 1.0) estimating effects of incremental interventions modifying the propensity for liberation to be more aggressive or conservative relative to usual care, with adjustment for confounding via inverse probability weighting. Outcomes included in-hospital mortality, ventilator free days, and ICU free days. Analysis was performed on the entire cohort as well as subgroups differentiated by PaO2/FiO2 ratio, and SOFA.

RESULTS

7433 patients were included. Strategies multiplying the odds of a first liberation relative to usual care at each hour had a large impact on time to first liberation attempt (43 h under usual care, 24 h (0.95 CI = [23,25]) with an aggressive strategy doubling liberation odds, and 74 h (0.95 CI = [69,78]) under a conservative strategy halving liberation odds). In the full cohort, we estimated aggressive liberation increased ICU-free days by 0.9 days (0.95 CI = [0.8,1.0]) and ventilator free days by 0.82 days (0.95 CI = [0.67,0.97]), but had minimal effect on mortality (only a 0.3% (0.95 CI = [-0.2%,0.8%]) difference between minimum and maximum rates). With baseline SOFA≥ 12 (n = 1355), aggressive liberation moderately increased mortality (58.5% [0.95 CI = (55.7%,61.2%)]) compared with conservative liberation (55.1% [0.95 CI = (51.6%,58.6%)]).

INTERPRETATION

Aggressive liberation may improve ventilator free and ICU free days with little impact on mortality in patients with SOFA score < 12. Trials are needed.

Identification of Distinct Clinical Phenotypes of Heterogeneous Mechanically Ventilated ICU Patients Using Cluster Analysis

This retrospective study aimed to derive the clinical phenotypes of ventilated ICU patients to predict the outcomes on the first day of ventilation. Clinical phenotypes were derived from the eICU Collaborative Research Database (eICU) cohort via cluster analysis and were validated in the Medical Information Mart for Intensive Care (MIMIC-IV) cohort. Four clinical phenotypes were identified and compared in the eICU cohort (n = 15,256). Phenotype A (n = 3112) was associated with respiratory disease, had the lowest 28-day mortality (16%), and had a high extubation success rate (~80%). Phenotype B (n = 3335) was correlated with cardiovascular disease, had the second-highest 28-day mortality (28%), and had the lowest extubation success rate (69%). Phenotype C (n = 3868) was correlated with renal dysfunction, had the highest 28-day mortality (28%), and had the second-lowest extubation success rate (74%). Phenotype D (n = 4941) was associated with neurological and traumatic diseases, had the second-lowest 28-day mortality (22%), and had the highest extubation success rate (>80%). These findings were validated in the validation cohort (n = 10,813). Additionally, these phenotypes responded differently to ventilation strategies in terms of duration of treatment, but had no difference in mortality. The four clinical phenotypes unveiled the heterogeneity of ICU patients and helped to predict the 28-day mortality and the extubation success rate.

An artificial intelligence system to predict the optimal timing for mechanical ventilation weaning for intensive care unit patients: A two-stage prediction approach

Background

For the intensivists, accurate assessment of the ideal timing for successful weaning from the mechanical ventilation (MV) in the intensive care unit (ICU) is very challenging.

Purpose

Using artificial intelligence (AI) approach to build two-stage predictive models, namely, the try-weaning stage and weaning MV stage to determine the optimal timing of weaning from MV for ICU intubated patients, and implement into practice for assisting clinical decision making.

Methods

AI and machine learning (ML) technologies were used to establish the predictive models in the stages. Each stage comprised 11 prediction time points with 11 prediction models. Twenty-five features were used for the first-stage models while 20 features were used for the second-stage models. The optimal models for each time point were selected for further practical implementation in a digital dashboard style. Seven machine learning algorithms including Logistic Regression (LR), Random Forest (RF), Support Vector Machines (SVM), K Nearest Neighbor (KNN), lightGBM, XGBoost, and Multilayer Perception (MLP) were used. The electronic medical records of the intubated ICU patients of Chi Mei Medical Center (CMMC) from 2016 to 2019 were included for modeling. Models with the highest area under the receiver operating characteristic curve (AUC) were regarded as optimal models and used to develop the prediction system accordingly.

Results

A total of 5,873 cases were included in machine learning modeling for Stage 1 with the AUCs of optimal models ranging from 0.843 to 0.953. Further, 4,172 cases were included for Stage 2 with the AUCs of optimal models ranging from 0.889 to 0.944. A prediction system (dashboard) with the optimal models of the two stages was developed and deployed in the ICU setting. Respiratory care members expressed high recognition of the AI dashboard assisting ventilator weaning decisions. Also, the impact analysis of with- and without-AI assistance revealed that our AI models could shorten the patients' intubation time by 21 hours, besides gaining the benefit of substantial consistency between these two decision-making strategies.

Conclusion

We noticed that the two-stage AI prediction models could effectively and precisely predict the optimal timing to wean intubated patients in the ICU from ventilator use. This could reduce patient discomfort, improve medical quality, and lower medical costs. This AI-assisted prediction system is beneficial for clinicians to cope with a high demand for ventilators during the COVID-19 pandemic.

To Wean or Not to Wean: A Practical Patient Focused Guide to Ventilator Weaning

Since the inception of critical care medicine and artificial ventilation, literature and research on weaning has transformed daily patient care in intensive care units (ICU). As our knowledge of mechanical ventilation (MV) improved, so did the need to study patient-ventilator interactions and weaning predictors. Randomized trials have evaluated the use of protocol-based weaning (vs. usual care) to study the duration of MV in ICUs, different techniques to conduct spontaneous breathing trials (SBT), and strategies to eventually extubate a patient whose initial SBT failed. Despite considerable milestones in the management of multiple diseases contributing to reversible respiratory failure, in the application of early rehabilitative interventions to preserve muscle integrity, and in ventilator technology that mitigates against ventilator injury and dyssynchrony, major barriers to successful liberation from MV persist. This review provides a broad encompassing view of weaning classification, causes of weaning failure, and evidence behind weaning predictors and weaning modes.

Liberation from Mechanical Ventilation: Established and New Insights

A substantial proportion of critically ill patients require ventilator support with the majority requiring invasive mechanical ventilation. Timely and safe liberation from invasive mechanical ventilation is a critical aspect of patient care in the intensive care unit (ICU) and is a top research priority for patients and clinicians. In this article, we discuss how to (1) identify candidates for liberation from mechanical ventilation, (2) conduct spontaneous breathing trials (SBTs), and (3) optimize patients for liberation from mechanical ventilation. We also discuss the roles for (4) extubation to noninvasive ventilation and (5) newer modes of mechanical ventilation during liberation from mechanical ventilation. We conclude that, though substantial progress has been made in identifying patients who are likely to be liberated (e.g., through the use of SBTs) and management strategies that speed liberation from the ventilator (e.g., protocolized SBTs, lighter sedation, and early mobilization), many important questions regarding liberation from mechanical ventilation in clinical practice remain unanswered.

The Feasibility of a Machine Learning Approach in Predicting Successful Ventilator Mode Shifting for Adult Patients in the Medical Intensive Care Unit

Background and Objectives: Traditional assessment of the readiness for the weaning from the mechanical ventilator (MV) needs respiratory parameters in a spontaneous breath. Exempted from the MV disconnecting and manual measurements of weaning parameters, a prediction model based on parameters from MV and electronic medical records (EMRs) may help the assessment before spontaneous breath trials. The study aimed to develop prediction models using machine learning techniques with parameters from the ventilator and EMRs for predicting successful ventilator mode shifting in the medical intensive care unit. Materials and Methods: A retrospective analysis of 1483 adult patients with mechanical ventilators for acute respiratory failure in three medical intensive care units between April 2015 and October 2017 was conducted by machine learning techniques to establish the predicting models. The input candidate parameters included ventilator setting and measurements, patients’ demographics, arterial blood gas, laboratory results, and vital signs. Several classification algorithms were evaluated to fit the models, including Lasso Regression, Ridge Regression, Elastic Net, Random Forest, Extreme Gradient Boosting (XGBoost), Support Vector Machine, and Artificial Neural Network according to the area under the Receiver Operating Characteristic curves (AUROC). Results: Two models were built to predict the success shifting from full to partial support ventilation (WPMV model) or from partial support to the T-piece trial (sSBT model). In total, 3 MV and 13 nonpulmonary features were selected for the WPMV model with the XGBoost algorithm. The sSBT model was built with 8 MV and 4 nonpulmonary features with the Random Forest algorithm. The AUROC of the WPMV model and sSBT model were 0.76 and 0.79, respectively. Conclusions: The weaning predictions using machine learning and parameters from MV and EMRs have acceptable performance. Without manual measurements, a decision-making system would be feasible for the continuous prediction of mode shifting when the novel models process real-time data from MV and EMRs.

Reintubation Summation Calculation: A Predictive Score for Extubation Failure in Critically Ill Patients

Objective

To derive and validate a multivariate risk score for the prediction of respiratory failure after extubation.

Patients and methods

We performed a retrospective cohort study of adult patients admitted to the intensive care unit from January 1, 2006, to December 31, 2015, who received mechanical ventilation for ≥48 h. Extubation failure was defined as the need for reintubation within 72 h after extubation. Multivariate logistic regression model coefficient estimates generated the Re-Intubation Summation Calculation (RISC) score.

Results

The 6,161 included patients were randomly divided into 2 sets: derivation (n = 3,080) and validation (n = 3,081). Predictors of extubation failure in the derivation set included body mass index <18.5 kg/m² [odds ratio (OR), 1.91; 95% CI, 1.12–3.26; P = 0.02], threshold of Glasgow Coma Scale of at least 10 (OR, 1.68; 95% CI, 1.31–2.16; P < 0.001), mean airway pressure at 1 min of spontaneous breathing trial <10 cmH₂O (OR, 2.11; 95% CI, 1.68–2.66; P < 0.001), fluid balance ≥1,500 mL 24 h preceding extubation (OR, 2.36; 95% CI, 1.87–2.96; P < 0.001), and total mechanical ventilation days ≥5 (OR, 3.94; 95% CI 3.04–5.11; P < 0.001). The C-index for the derivation and validation sets were 0.72 (95% CI, 0.70–0.75) and 0.72 (95% CI, 0.69–0.75). Multivariate logistic regression demonstrated that an increase of 1 in RISC score increased odds of extubation failure 1.6-fold (OR, 1.58; 95% CI, 1.47–1.69; P < 0.001).

Conclusion

RISC predicts extubation failure in mechanically ventilated patients in the intensive care unit using several clinically relevant variables available in the electronic medical record but requires a larger validation cohort before widespread clinical implementation.

Diaphragm ultrasound to predict weaning outcome: systematic review and meta-analysis

Proper timing for discontinuation of mechanical ventilation is of great importance, especially in patients with previous weaning failures. Different indices obtained by ultra-sonographic evaluation of the diaphragm muscle have improved determination of weaning success. The aim of the present systematic review was to evaluate and compare the accuracy of the diagnostic indices obtained by ultrasonographic examination, including diaphragm thickening fraction (DTF), diaphragmatic excursion (DE) and the rapid shallow breathing index (RSBI). A systematic literature search (Web of Science, MEDLINE, Embase and Google Scholar) was performed to identify original articles assessing diaphragm muscle features including excursion and thickening fraction. A total of 2738 citations were retrieved initially; available data of 19 cohort studies (1114 patients overall) were included in the meta-analysis, subdivided into groups based on the ultrasonographic examination type. Our results showed the superiority of the diagnostic accuracy of the DTF in comparison to the DE and the RSBI. Data on the combination of the different indices are limited. Diaphragmatic ultrasound is a cheap and feasible tool for diaphragm function evaluation. Moreover, DTF in the assessment of weaning outcome provides more promising outcomes, which should be evaluated more meti-culously in future randomised trials.

The Usefulness of the Rapid Shallow Breathing Index in Predicting Successful Extubation: A Systematic Review and Meta-analysis

BACKGROUND

Clinicians use several measures to ascertain whether individual patients will tolerate liberation from mechanical ventilation, including the rapid shallow breathing index (RSBI).

RESEARCH QUESTION

Given varied use of different thresholds, patient populations, and measurement characteristics, how well does RSBI predict successful extubation?

STUDY DESIGN AND METHODS

We searched six databases from inception through September 2019 and selected studies reporting the accuracy of RSBI in the prediction of successful extubation. We extracted study data and assessed quality independently and in duplicate.

RESULTS

We included 48 studies involving RSBI measurements of 10,946 patients. Pooled sensitivity for RSBI of < 105 in predicting extubation success was moderate (0.83 [95% CI, 0.78-0.87], moderate certainty), whereas specificity was poor (0.58 [95% CI, 0.49-0.66], moderate certainty) with diagnostic ORs (DORs) of 5.91 (95% CI, 4.09-8.52). RSBI thresholds of < 80 or 80 to 105 yielded similar sensitivity, specificity, and DOR. These findings were consistent across multiple subgroup analyses reflecting different patient characteristics and operational differences in RSBI measurement.

INTERPRETATION

As a stand-alone test, the RSBI has moderate sensitivity and poor specificity for predicting extubation success. Future research should evaluate its role as a permissive criterion to undergo a spontaneous breathing trial (SBT) for patients who are at intermediate pretest probability of passing an SBT.

TRIAL REGISTRY

PROSPERO; No.: CRD42020149196; URL: www.crd.york.ac.uk/prospero/.

Handgrip strength cutoff value predicting successful extubation in mechanically ventilated patients

Background

Handgrip strength (HGS) is an alternative tool to evaluate respiratory muscle function. HGS cutoff value indicating extubation success or failure has not been investigated. This study aimed to determine HGS cutoff value to predict successful extubation.

Methods

A prospective study was conducted. Patients requiring intubated mechanical ventilation with intubation ≥ 48 hours in medical wards were recruited. HGS test was performed at 10 minutes before and 30 minutes after spontaneous breathing trial (SBT). Rapid shallow breathing index (RSBI) was measured at 10 minutes before SBT.

Results

Ninety-three patients (58% men) were included. Mean age was 71.6 ± 15.2 years. Weaning failure rate was 6.5%. The area under the ROC curve of 0.84 for the best HGS cutoff value at 10 minutes before SBT was 12.7 kg, with 75.9% sensitivity and 83.3% specificity (P = 0.005). The best HSG cutoff value at 30 minutes after SBT was 14.9 kg, with the area under the ROC curve of 0.82, with 58.6% sensitivity and 83.3% specificity (P = 0.009). The best RSBI cutoff value was 43.5 breaths/min/L, with the area under the ROC curve of 0.46, 33.3% sensitivity and 66.6% specificity (P = 0.737).

Conclusions

HGS may be a predictive tool to guide extubation with better sensitivity and specificity than RSBI. A prospective study is needed to verify HGS test as adjunctive to RSBI in ventilator weaning protocol.

Validation of rapid shallow breathing index displayed by the ventilator compared to the standard technique in patients with readiness for weaning

BACKGROUND

Rapid shallow breathing index (RSBI) is the most commonly used parameter for predicting weaning outcome. Measurement of RSBI by Wright spirometer (RSBI_standard) is the standard method in routine clinical practice. Data specific to the accuracy and reliability of the RSBI value displayed by the ventilator (RSBI_vent) are scarce. Accordingly, this study aimed to evaluate the association between the average value of RSBI_vent at different time points and RSBI_standard, and to assess the accuracy and reliability of these two RSBI measurement techniques.

METHODS

This prospective cohort study included mechanically ventilated patients who were ready to wean. At the beginning of spontaneous breathing trial using the flow-by method, RSBI was measured by two different techniques at the same time, including: (1) Wright spirometer (breathing frequency/average tidal volume in 1 min) (RSBI_standard), and (2) the values displayed on the ventilator at 0, 15, 30, 45, and 60 s (RSBI_vent).

RESULTS

Forty-seven patients were enrolled. The RSBI_vent value was significantly higher than the RSBI_standard value for every comparison. According to Spearman's correlation coefficient (r) and intraclass correlation coefficient (ICC), the average value of RSBI from 5 time points (0, 15, 30, 45, and 60 s) showed the best correlation with the standard technique (r = 0.76 [P < 0.001], and ICC = 0.79 [95% CI 0.61-0.88], respectively). Bland-Altman plot also showed the best agreement between RSBI_standard and the RSBI_vent value averaged among 5 time points (mean difference - 17.1 breaths/min/L).

CONCLUSIONS

We found that the ventilator significantly overestimates the RSBI value compared to the standard technique by Wright spirometer. The average RSBI_vent value among 5 time points (0, 15, 30, 45, and 60 s) was found to best correlate with RSBI_standard.

Biosignal-Based Digital Biomarkers for Prediction of Ventilator Weaning Success

We evaluated new features from biosignals comprising diverse physiological response information to predict the outcome of weaning from mechanical ventilation (MV). We enrolled 89 patients who were candidates for weaning from MV in the intensive care unit and collected continuous biosignal data: electrocardiogram (ECG), respiratory impedance, photoplethysmogram (PPG), arterial blood pressure, and ventilator parameters during a spontaneous breathing trial (SBT). We compared the collected biosignal data's variability between patients who successfully discontinued MV (n = 67) and patients who did not (n = 22). To evaluate the usefulness of the identified factors for predicting weaning success, we developed a machine learning model and evaluated its performance by bootstrapping. The following markers were different between the weaning success and failure groups: the ratio of standard deviations between the short-term and long-term heart rate variability in a Poincaré plot, sample entropy of ECG and PPG, α values of ECG, and respiratory impedance in the detrended fluctuation analysis. The area under the receiver operating characteristic curve of the model was 0.81 (95% confidence interval: 0.70-0.92). This combination of the biosignal data-based markers obtained during SBTs provides a promising tool to assist clinicians in determining the optimal extubation time.

Predictors and outcomes of high-flow nasal cannula failure following extubation: A multicentre observational study

INTRODUCTION

Despite adhering to criteria for extubation, up to 20% of intensive care patients require re-intubation, even with use of post-extubation high-flow nasal cannula (HFNC). This study aims to identify independent predictors and outcomes of extubation failure in patients who failed post-extubation HFNC.

METHODS

We conducted a multicentre observational study involving 9 adult intensive care units (ICUs) across 5 public hospitals in Singapore. We included patients extubated to HFNC following spontaneous breathing trials. We compared patients who were successfully weaned off HFNC with those who failed HFNC (defined as re-intubation ≤7 days following extubation). Generalised additive logistic regression analysis was used to identify independent risk factors for failed HFNC.

RESULTS

Among 244 patients (mean age: 63.92±15.51 years, 65.2% male, median APACHE II score 23.55±7.35), 41 (16.8%) failed HFNC; hypoxia, hypercapnia and excessive secretions were primary reasons. Stroke was an independent predictor of HFNC failure (odds ratio 2.48, 95% confidence interval 1.83-3.37). Failed HFNC, as compared to successful HFNC, was associated with increased median ICU length of stay (14 versus 7 days, P<0.001), ICU mortality (14.6% versus 2.0%, P<0.001) and hospital mortality (29.3% versus 12.3%, P=0.006).

CONCLUSION

Post-extubation HFNC failure, especially in patients with stroke as a comorbidity, remains a clinical challenge and predicts poorer clinical outcomes. Our observational study highlights the need for future prospective trials to better identify patients at high risk of post-extubation HFNC failure.

Use of the Change in Weaning Parameters as a Predictor of Successful Re-Extubation

OBJECTIVE

Weaning parameters are well studied in patients undergoing first time extubation. Fewer data exists to guide re-extubation of patients who failed their first extubation attempt. It is reasonable to postulate that improved weaning parameters between the first and second extubation attempt would lead to improved rates of re-extubation success. To investigate, we studied a cohort of patients who failed their first extubation attempt and underwent a second attempt at extubation. We hypothesized that improvement in weaning parameters between the first and the second extubation attempt is associated with successful reextubation.

INTERVENTIONS

Rapid shallow breathing index (RSBI), maximum inspiratory pressure (MIP), vital capacity (VC), and the blood partial pressure of CO2 (PaCO2) were measured and recorded in the medical record prior to extubation along with demographic information. We examined the relationship between the change in extubation and re-extubation weaning parameters and re-extubation success.

MEASUREMENTS AND MAIN RESULTS

A total of 1283 adult patients were included. All weaning parameters obtained prior to re-extubation differed between those who were successful and those who required a second reintubation. Those with reextubation success had slightly lower PaCO2 values (39.5 ± 7.4 mmHg vs. 41.6 ± 9.1 mmHg, p = 0.0045) and about 13% higher vital capacity volumes (1021 ± 410 mL vs. 907 ± 396 mL, p = 0.0093). Lower values for RSBI (53 ± 32 breaths/min/L vs. 69 ± 42 breaths/min/L, p < 0.001) and MIP (-41 ± 12 cmH2O vs. -38 ± 13 cm H2O), p = 0.0225) were seen in those with re-extubation success. Multivariable logistical regression demonstrates lack of independent associated between the change in parameters between the 2 attempts and re-extubation success.

CONCLUSIONS

The relationship between the changes in extubation parameters through successive attempts is driven primarily by the value obtained immediately prior to re-extubation. These findings do not support waiting for an improvement in extubation parameters to extubate patients who failed a first attempt at extubation if extubation parameters are compatible with success.

Comparison of serratus anterior plane block with epidural and paravertebral block in critically ill trauma patients with multiple rib fractures

Background

Pain from rib fractures is associated with significant pulmonary morbidity. Epidural and paravertebral blocks (EPVBs) have been recommended as part of a multimodal approach to rib fracture pain, but their utility is often challenging in the trauma intensive care unit (ICU). The serratus anterior plane block (SAPB) has potential as an alternative approach for chest wall analgesia.

Methods

This retrospective study compared critically injured adults sustaining multiple rib fractures who had SAPB (n=14) to EPVB (n=25). Patients were matched by age, body mass index, American Society of Anesthesiology Physical Status, whether the patient required intubation, number of rib fractures and injury severity score. Outcome measures included hospital length of stay, ICU length of stay, preblock and post block rapid shallow breathing index (RSBI) in intubated patients, pain scores and morphine equivalent doses administered 24-hour preblock and post-block in non-intubated patients, and mortality.

Results

There were no demographic differences between the two groups after matching. Nearly all of the patients who received either SAPB or EPVB demonstrated a reduction in RSBI or pain scores. The preblock RSBI was higher in the serratus anterior plane block group, but there was no difference between any of the other outcome measures.

Discussion

This retrospective study of our institutional data suggests no difference in efficacy between the serratus anterior plane block and neuraxial block for traumatic rib fracture pain in critically ill patients, but the sample size was too small to show statistical equivalence. Serratus anterior plane block is technically easier to perform with fewer theoretical contraindications compared with traditional neuraxial block. Further study with prospective comparative trials is warranted.

Level of evidence

Retrospective matched cohort; Level IV.

A Reassessment of Weaning Parameters in Patients With Spontaneous Intracerebral Hemorrhage

Background and purpose

Patients with spontaneous intracerebral haemorrhage have significant morbidity and mortality. One aspect of their care is the need for mechanical ventilation. Extubating a patient safely and efficiently is important in advancing their care; however, traditional extubation criteria using the rapid shallow breathing index and negative inspiratory force do not predict success in these patients as well as they do in other intubated patients. This study aimed to evaluate these criteria in patients with spontaneous intracerebral haemorrhage to improve the extubation success rate.

Methods

We conducted a retrospective chart review of patients with spontaneous intracerebral haemorrhage (sICH) who underwent spontaneous breathing trials from 2018 to 2020. Twenty-nine patients met the inclusion criteria, and of these 29, 20 had a trial of extubation. Rapid shallow breathing index (RSBI), negative inspiratory force (NIF), and cuff leak were recorded to analyze breathing parameters at the time of extubation. Patients who required reintubation were noted.

Results

All trials of extubation required a cuff leak. Using RSBI, patients with values <105 or <85, as the only other extubation criteria, were associated with a 70.6% and 71.4% success rate, respectively. With RSBI <105 and NIF <-25 cm water, the success rate was 88.9%. Any patient with a cuff leak that had a NIF <-30 had a success rate of 100%, regardless of RSBI.

Conclusion

The RSBI was not a reliable isolated measure to predict 100% extubation success. Using a NIF <-30 predicts a 100% extubation success rate if a cuff leak is present. This demonstrates that the NIF may be a more useful metric in sICH patients, as it accounts for patient participation and innate ability to draw a breath spontaneously. Future studies are warranted to evaluate further and optimize the extubation criteria in these patients.

Enlargement of Intrathoracic Goiter with Unilateral Phrenic Nerve Paralysis Leading to Cardiopulmonary Arrest

As an intrathoracic goiter expands, it causes airway stenosis and phrenic nerve paralysis, and slight respiratory stimuli can trigger sudden life-threatening hypoventilation. A 78-year-old obese woman with a large intrathoracic goiter was found unconscious with agonal breathing in her room early in the morning. Cardiopulmonary resuscitation restored spontaneous circulation. She underwent surgical removal of the goiter; however, she required long-term mechanical ventilation because of atelectasis due to phrenic nerve paralysis. In patients with large intrathoracic goiters, difficulty breathing on exertion and diaphragm elevation on chest X-ray may be significant findings predicting future respiratory failure.

Thenar oxygen saturation (StO2) alterations during a spontaneous breathing trial predict extubation failure

Background

Weaning from mechanical ventilation (MV) is a cardiovascular stress test. Monitoring the regional oxygenation status has shown promising results in predicting the tolerance to spontaneously breathe in the process of weaning from MV. Our aim was to determine whether changes in skeletal muscle oxygen saturation (StO₂) measured by near-infrared spectroscopy (NIRS) on the thenar eminence during a vascular occlusion test (VOT) can be used to predict extubation failure from mechanical ventilation.

Methods

We prospectively studied 206 adult patients with acute respiratory failure receiving MV for at least 48 h from a 30-bed mixed ICU, who were deemed ready to wean by their physicians. Patients underwent a 30-min spontaneous breathing trial (SBT), and were extubated according to the local protocol. Continuous StO₂ was measured non-invasively on the thenar eminence. A VOT was performed prior to and at 30 min of the SBT (SBT₃₀). The rate of StO₂ deoxygenation (DeO₂), StO₂ reoxygenation (ReO₂) rate and StO₂ hyperemic response to ischemia (H_AUC) were calculated.

Results

Thirty-six of the 206 patients (17%) failed their SBT. The remainder 170 patients (83%) were extubated. Twenty-three of these patients (13.5%) needed reinstitution of MV within 24 h. Reintubated patients displayed a lower H_AUC at baseline, and higher relative changes in their StO₂ deoxygenation rate between baseline and SBT₃₀ (DeO₂ Ratio). A logistic regression-derived StO₂ score, combining baseline StO₂, H_AUC and DeO₂ ratio, showed an AUC of 0.84 (95% CI 0.74–0.91) for prediction of extubation failure.

Conclusions

Extubation failure was associated to baseline and dynamic StO₂ alterations during the SBT. Monitoring StO₂-derived parameters might be useful in predicting extubation outcome.

Interest of hand grip strength to predict outcome in mechanically ventilated patients

BACKGROUND

Weaning from mechanical ventilation is a crucial process for critically ill patients. Hand grip strength (HGS) is an assessment tool for respiratory muscle function to assist guidance of extubation.

OBJECTIVE

To evaluate HGS as a predictor for in-hospital clinical outcomes in mechanically ventilated patients.

METHODS

A prospective study was conducted. Patients requiring mechanical ventilation with tracheal intubation in medical wards and intensive care units were recruited. HGS, reintubation, number of ventilator-free days and mortality were recorded.

RESULTS

A total of 34 patients (52.9% men) were included. When compared to the non re-intubation group, the re-intubation group had significantly lower HGS at 10 min and 30 min after starting spontaneous breathing trial (7.6 ± 4.8 kg Vs 13.4 ± 6.5 kg, P = 0.045, and 8 ± 5.1 kg Vs 13.2 ± 5.7 kg, P = 0.047). Moreover, at 1 h and 48 h of post extubation, the re-intubation group had lower HGS than the non re-intubation group. HGS at 1 h of post extubation was positively correlated with ventilator-free day at 28 days (r = 0.34, P = 0.05). HGS did not differ between survival group and death group in hospital over time.

CONCLUSIONS

Hand grip strength may be a predictive tool for extubation failure in mechanically ventilated patients. Low strength corresponded to significantly increased re-intubation rate. Furthermore, this measurement could not predict in-hospital mortality.

Mechanical ventilation weaning issues can be counted on the fingers of just one hand: part 1

Although mechanical ventilation may be a patient’s vital ally during acute illness, it can quickly transform into an enemy during chronic conditions. The weaning process is the fundamental phase that enables the resumption of physiological respiratory function; however, it is also associated with a number of life-threatening complications, and a large percentage of critically ill patients never achieve airway device removal or require the resumption of mechanical ventilation just a few days post-weaning. Indeed, the weaning process is, at present, more of an art than a science. As such, there is urgent need for novel contributions from the scientific literature to abate the growing rates of morbidity and mortality associated with weaning failure. The physician attempting to wean a patient must integrate clinical parameters and common-sense criteria. Numerous studies have striven to identify single predictive factors of weaning failure and sought to standardize the weaning process, but the results are characterized by remarkable heterogeneity. Despite the lack of benchmarks, it is clear that the analysis of respiratory function must include a detailed overview of the five situations described below rather than a single aspect. The purpose of this two-part review is to provide a comprehensive description of these situations to clarify the “arena” physicians are entering when weaning critically ill patients from mechanical ventilation.

Preoperative expiratory and inspiratory muscle weakness to predict postoperative outcomes in patients undergoing elective cardiac surgery

BACKGROUND

Few studies have evaluated preoperative respiratory muscle strength as a risk factor for postoperative morbidity and mortality. The objective of this study was to evaluate the association of preoperative inspiratory muscle weakness (IMW) and preoperative expiratory muscle weakness (EMW) with duration of mechanical ventilation, length of stay in the intensive care unit (ICU), incidence of postoperative pulmonary complications (PPCs), and mortality in patients undergoing elective cardiac surgery.

MATERIALS AND METHODS

This was a prospective observational study. Patients admitted for elective cardiac surgery were recruited. Maximal inspiratory and expiratory pressure were measured before surgery. A multivariate regression model was used to adjust for possible confounding variables and test the association of IMW and EMW with the duration of mechanical ventilation, length of stay in the ICU, PPCs, and hospital mortality.

RESULTS

Two hundred and fifty-five patients were included in this study. The presence of IMW was associated with an increase in the duration of mechanical ventilation (P = .012). The presence of EMW was associated with a reduction in the incidence of PPCs (P = .005). IMW had no significant association with length of stay in the ICU, PPCs, or hospital mortality. EMW had no significant association with the duration of mechanical ventilation, length of stay in the ICU, or hospital mortality.

CONCLUSIONS

In patients undergoing elective cardiac surgery, preoperative IMW is associated with the duration of mechanical ventilation while preoperative EMW is associated with a decrease in PPCs.

Predicting weaning difficulty for planned extubation patients with an artificial neural network

This study aims to construct a neural network to predict weaning difficulty among planned extubation patients in intensive care units.This observational cohort study was conducted in eight adult ICUs in a medical center about adult patients experiencing planned extubation.The data of 3602 patients with planned extubation in ICUs of Chi-Mei Medical Center (from Dec. 2009 through Dec. 2011) was used to train and test an artificial neural network (ANN) model. The input features contain 47 clinical risk factors and the outputs are classified into three categories: simple, difficult, and prolonged weaning. A deep ANN model with four hidden layers of 30 neurons each was developed. The accuracy is 0.769 and the area under receiver operating characteristic curve for simple weaning, prolonged weaning, and difficult weaning are 0.910, 0.849, and 0.942 respectively.The results revealed that the ANN model achieved a good performance in prediction the weaning difficulty in planned extubation patients. Such a model will be helpful for predicting ICU patients' successful planned extubation.

Ventilatory equivalent for oxygen as an extubation outcome predictor: A pilot study

Introduction

Weaning predictors can help liberate patients in a timely manner from mechanical ventilation. Ventilatory equivalent for oxygen (VEqO₂), a surrogate for work of breathing and a measure of the efficiency of breathing, may be an important noninvasive alternative to other weaning predictors. Our study’s purpose was to observe any differences in VEqO₂ between extubation outcome groups.

Methods

Employing a metabolic cart, oxygen consumption (V^˙O₂), minute volume (VE), tidal volume (VT), and breathing frequency were recorded during a spontaneous breathing trial (SBT) to calculate VEqO₂ and the rapid shallow breathing index (RSBI) in 34 adult participants in the intensive care unit. Five-breath means of VEqO₂ and the RSBI collected throughout the SBT were examined between SBT pass and fail groups and extubation pass and fail groups using the Mann–Whitney U test with p < 0.05.

Results

Data from 31 participants were analyzed between SBT outcome groups. Data from 20 participants were examined for extubation outcome after a successful SBT. Median (interquartile range) VEqO₂ was not different between extubation groups. Participants who passed the SBT had a higher median VEqO₂ than those who did not at the midpoint (25.3 L/L V^˙O₂ [22–33 L/L V^˙O₂] vs. 23.7 L/L V^˙O₂ [18–24 L/L V^˙O₂], p = 0.035) and at the end (25.5 L/L V^˙O₂ [23–34 L/L V^˙O₂] vs. 21.3 L/L V^˙O₂ [20–24 L/L V^˙O₂], p = 0.017) of the SBT.

Discussion

VEqO₂ may show differences in SBT outcomes, but not differences between extubation outcomes. VEqO₂ may be able to detect differences in work during an SBT, but may not be able to predict change in workload in the respiratory system after extubation. The small sample size may also have prevented any differences in extubation outcomes to be shown.

Conclusion

VEqO₂ was higher in patients that passed their SBT. VEqO₂ was not useful in identifying extubation success or failure in adult mechanically ventilated patients.

Physiotherapist prediction of extubation outcome in the adult intensive care unit

Objective

Most patients requiring intubation and mechanical ventilation are extubated successfully at the first attempt; however, a minority experience extubation failure, which is associated with increased risk of ventilator‐associated pneumonia, prolonged intensive care unit (ICU) length of stay and mortality. Physiotherapists have expertise to assess cough strength, work of breathing, respiratory muscle strength, and respiratory secretion load, which are important factors in the outcome of extubation. Accurate prediction of extubation outcome could help to inform management plans pre‐extubation and postextubation. The primary objective of this service evaluation was to report the accuracy of physiotherapists' prediction of extubation outcome in the adult ICU.

Methods

A single‐centre case note review was undertaken. All subjects who received a physiotherapy assessment of extubation suitability prior to extubation between January and March 2016 in the adult ICU of a large teaching hospital in the United Kingdom were included. Assessment, by both specialist and nonspecialist physiotherapists—which included risk stratification of extubation failure as “high,” “moderate,” or “low”—was undertaken prior to extubation. Logistic regression analysis was performed to determine which pre‐extubation factors were predictive of extubation outcome.

Results

During the evaluation period, 68 subjects were extubated following a physiotherapy assessment. Physiotherapy risk stratification as “high risk” (OR 4; 95% confidence interval, CI, [1.312]; p=0.009) and “inappropriate” neurological status (OR 3.3; 95% CI [1.0410]; p=0.037) were the only pre‐extubation factors significantly associated with extubation failure. Assessment by specialist physiotherapists demonstrated greater sensitivity (100% vs. 22%) but lower specificity (68% vs. 95%) to detect extubation failure compared with the assessment performed by nonspecialist physiotherapists.

Conclusion

Patients classified as “high risk” of extubation failure by a physiotherapist are significantly more likely to fail extubation. Specialist physiotherapists should be involved in the decision to extubate patients in the adult ICU.

Optimising mechanical ventilation through model-based methods and automation

Mechanical ventilation (MV) is a core life-support therapy for patients suffering from respiratory failure or acute respiratory distress syndrome (ARDS). Respiratory failure is a secondary outcome of a range of injuries and diseases, and results in almost half of all intensive care unit (ICU) patients receiving some form of MV. Funding the increasing demand for ICU is a major issue and MV, in particular, can double the cost per day due to significant patient variability, over-sedation, and the large amount of clinician time required for patient management. Reducing cost in this area requires both a decrease in the average duration of MV by improving care, and a reduction in clinical workload. Both could be achieved by safely automating all or part of MV care via model-based dynamic systems modelling and control methods are ideally suited to address these problems. This paper presents common lung models, and provides a vision for a more automated future and explores predictive capacity of some current models. This vision includes the use of model-based methods to gain real-time insight to patient condition, improve safety through the forward prediction of outcomes to changes in MV, and develop virtual patients for in-silico design and testing of clinical protocols. Finally, the use of dynamic systems models and system identification to guide therapy for improved personalised control of oxygenation and MV therapy in the ICU will be considered. Such methods are a major part of the future of medicine, which includes greater personalisation and predictive capacity to both optimise care and reduce costs. This review thus presents the state of the art in how dynamic systems and control methods can be applied to transform this core area of ICU medicine.

A rapid shallow breathing index threshold of 85 best predicts extubation success in chronic obstructive pulmonary disease patients with hypercapnic respiratory failure

Background

The rapid shallow breathing index (RSBI) is used clinically to help predict a patient's likelihood of successful liberation from mechanical ventilation (MV). However, the traditional threshold (<105 breaths/min/L) may underperform in patients with chronic obstructive pulmonary disease (COPD). We sought to determine the optimal RSBI threshold for COPD patients to improve the diagnostic accuracy for predicting successful ventilator liberation.

Methods

This was a prospective observational multicenter study of COPD patients [according to Global initiative for Chronic Obstructive Lung Disease (GOLD) criteria] admitted to the Medical ICUs of eight academic medical centers. All patients were intubated for hypercapnic respiratory failure and met the American Thoracic Society/European Respiratory Society guidelines to participate in a weaning trial. Ventilator weaning was conducted according to a defined protocol. RSBI was measured through the ventilator after 120 minutes of spontaneous breathing trial (SBT).

Results

Ninety patients were included (39 males and 51 females). Forty-three patients (48%) were successfully extubated whereas 47 patients (52%) failed extubation. Significant differences were observed between groups for duration-of-intubation [duration of intubation (DoI); P<0.0001], spontaneous tidal volume (VT) (P=0.03), and the ratio of dynamic-to-static compliance (P=0.005). The RSBI threshold of ≤85 breaths/min/L performed best: area under curve (AUC) receiver operating characteristic (ROC) curves 0.91, sensitivity 95.6%, specificity 90.4%, positive predictive value (PPV) 95.5%, and negative predictive value (NPV) 90.6%., positive likelihood ratio (LR+) 5.48, negative likelihood ratio (LR-) 0.25, and the diagnostic accuracy 91.7%. In post-ROC analyses, DoI and hospital length-of-stay (LOS) did not impact performance.

Conclusions

In COPD patients intubated with hypercapnia, RSBI ≤85 breaths/min/L outperformed the widely used threshold <105 breaths/min/L, yielding a 95.5% probability of extubation success, independent of ventilation duration or hospital LOS.

The prognostic value of rapid shallow breathing index and physiologic dead space for weaning success in intensive care unit patients under mechanical ventilation

Background

Mechanical ventilation (MV) is a life-saving intervention that should be considered for patients with respiratory failure. This study was conducted to evaluate the predictive value of physiologic dead space for weaning success and compare it with rapid shallow breathing index (RSBI).

Materials and Methods

This cross-sectional study was conducted on 80 intensive care unit (ICU) patients who were under MV and candidate for weaning; among them, 68 patients experienced weaning success. RSBI was measured by dividing the respiratory rate by tidal volume. End-tidal CO₂ (PETCO₂) was obtained using caponometry, then dead-space was calculated as (VD/VT = (PaCO₂ - PETCO₂)/PaCO₂). PaCO₂ was also obtained from arterial blood gas recorded chart.

Results

Age, PaCO₂, PETCO₂, and RSBI were significantly different between those patients with and without weaning success (P < 0.05). RSBI ≤ 98 could predict the success of weaning with sensitivity 91.7%; specificity 76.5% and (AUC) area under the ROC curve (AUC = 0.87; 95% confidence interval [CI]: 0.78-0.94; P < 0.001). Dead space was not statistically significant prognostic index (AUC = 0.50; 95% CI: 0.31-0.69; P = 0.09).

Conclusion

In our study, RSBI was an effective predictive index for weaning success in ICU patients under MV, but dead space did not show significant predictive value. Further studies with larger sample sizes for providing more evidence are recommended.

Relationship between dynamic expiratory time constant tau(edyn) and parameters of breathing cycle in pressure support ventilation mode

Study of the relationship between ventilation parameters: monitored expiratory time constant - tau(edyn) and breathing - trigger frequency (f(trig)) and time of breathing cycle (T(cy)) are main goals of this article. Parameters were analyzed during last 4+/-2 h before weaning from ventilation in 66 patients ventilated in pressure support mode (PSV). We have found out, that there exist mathematical relationships, observed during adequate gas exchange, yet not described. Monitored parameters are represented by tau(edyn), f(trig) and T(cy). The analysis showed close negative correlation between T(cy) and f(trig) (R(2)=0.903). This implies that each increasing of tau(edyn) causes decreasing of f(trig) and vice versa. The calculation of regression equation between tau(edyn) and T(cy) outlined that T(cy) = 5.2625 * tau(edyn) + 0.1242 (R(2)=0.85). Regulation of respiratory cycles by the respiratory center in the brain is probably based on evaluation of tau(edyn) as the tau(edyn) probably represents a regulatory element and T(cy) regulated element. It can be assumed, that respiratory center can optimize the work of breathing in order to minimize energy in system patient + ventilator. The unique relationship, described above could be useful in clinical practice for development of new ventilation modes.

Variation of Risk Factors for Cause-Specific Reintubation: A Preliminary Study

Unexpected reintubation may occur, even if the risk factors are considered and a spontaneous breathing trial is successful. Reintubation is thought to be caused by various factors. Several studies have investigated the risk factors of reintubation, but most did not classify reintubation by cause. We retrospectively classified patients undergoing reintubation at intensive care unit by cause (respiratory insufficiency vs. nonrespiratory insufficiency) to examine the cause-specific risk factors of reintubation. A total of 262 patients were included; reintubation within 48 hours after extubation was performed in 12 patients (reintubation rate, 4.5%). After classification by cause of reintubation, the pressure of arterial oxygen to fractional inspired oxygen concentration (P/F) ratio exhibited a significant association with reintubation only in the respiratory insufficiency group (odds ratio (OR) 0.989, 95% confidence interval (CI) 0.980 to 0.999, p=0.036, and OR 0.989, 95% CI 0.979 to 0.999, p=0.026, in the univariate and multivariate analyses, respectively). In the propensity score analysis, a P/F ratio ≤ 200 may be a risk factor for reintubation in the respiratory insufficiency group (OR 7.811, 95% CI 1.345 to 45.367, p=0.022). In the nonrespiratory insufficiency group, intubation duration was significantly related to reintubation (OR 1.165, 95% CI 1.012 to 1.342, p=0.033, and OR 1.163, 95% CI 1.004 to 1.348, p=0.044, in the univariate and multivariate analyses, respectively). In conclusion, a low P/F ratio at extubation may be a risk factor for reintubation due to respiratory insufficiency. In the nonrespiratory insufficiency group, intubation duration may be significantly related to reintubation. The risk factors for reintubation may differ by the cause of reintubation. Further large-scale randomized controlled trials are required.

Predictors of early weaning failure from mechanical ventilation in critically ill patients after emergency gastrointestinal surgery: A retrospective study

Mechanical ventilation (MV) is the most common therapeutic modality used for critically ill patients. However, prolonged MV is associated with high morbidity and mortality. Therefore, it is important to avoid both premature extubation and unnecessary prolongation of MV. Although some studies have determined the predictors of early weaning success and failure, only a few have investigated these factors in critically ill surgical patients who require postoperative MV. The aim of this study was to evaluate predictors of early weaning failure from MV in critically ill patients who had undergone emergency gastrointestinal (GI) surgery.The medical records of 3327 adult patients who underwent emergency GI surgery between January 2007 and December 2016 were reviewed retrospectively. Clinical and laboratory parameters before surgery and within 2 days postsurgery were investigated.This study included 387 adult patients who required postoperative MV. A low platelet count (adjusted odds ratio [OR]: 0.995; 95% confidence interval [CI]: 0.991-1.000; P = .03), an elevated delta neutrophil index (DNI; adjusted OR: 1.025; 95% CI: 1.005-1.046; P = .016), a delayed spontaneous breathing trial (SBT; adjusted OR: 14.152; 95% CI: 6.571-30.483; P < .001), and the presence of postoperative shock (adjusted OR: 2.436; 95% CI: 1.138-5.216; P = .022) were shown to predict early weaning failure from MV in the study population.Delayed SBT, a low platelet count, an elevated DNI, and the presence of postoperative shock are independent predictors of early weaning failure from MV in critically ill patients after emergency GI surgery.

An Artificial Neural Network Model for Predicting Successful Extubation in Intensive Care Units

BACKGROUND

Successful weaning from mechanical ventilation is important for patients in intensive care units (ICUs). The aim was to construct neural networks to predict successful extubation in ventilated patients in ICUs.

METHODS

Data from 1/12/2009 through 31/12/2011 of 3602 patients with planned extubation in Chi-Mei Medical Center's ICUs was used to train and test an artificial neural network (ANN). The input was 37 clinical risk factors, and the output was a failed extubation prediction.

RESULTS

One hundred eighty-five patients (5.1%) had a failed extubation. Multivariate analyses revealed that failure was positively associated with therapeutic intervention scoring system (TISS) scores (odds ratio [OR]: 1.814; 95% Confidence Interval [CI]: 1.283⁻2.563), chronic hemodialysis (OR: 12.264; 95% CI: 8.556⁻17.580), rapid shallow breathing (RSI) (OR: 2.003; 95% CI: 1.378⁻2.910), and pre-extubation heart rate (OR: 1.705; 95% CI: 1.173⁻2.480), but negatively associated with pre-extubation PaO₂/FiO₂ (OR: 0.529; 95%: 0.370⁻0.750) and maximum expiratory pressure (MEP) (OR: 0.610; 95% CI: 0.413⁻0.899). A multilayer perceptron ANN model with 19 neurons in a hidden layer was developed. The overall performance of this model was F₁: 0.867, precision: 0.939, and recall: 0.822. The area under the receiver operating characteristic curve (AUC) was 0.85, which is better than any one of the following predictors: TISS: 0.58 (95% CI: 0.54⁻0.62; p < 0.001); 0.58 (95% CI: 0.53⁻0.62; p < 0.001); and RSI: 0.54 (95% CI: 0.49⁻0.58; p = 0.097).

CONCLUSIONS

The ANN performed well when predicting failed extubation, and it will help predict successful planned extubation.

Dynamic data monitoring improves predictive analytics for failed extubation in the ICU

OBJECTIVE

Predictive analytics monitoring that informs clinicians of the risk for failed extubation would help minimize both the duration of mechanical ventilation and the risk of emergency re-intubation in ICU patients. We hypothesized that dynamic monitoring of cardiorespiratory data, vital signs, and lab test results would add information to standard clinical risk factors.

METHODS

We report model development in a retrospective observational cohort admitted to either the medical or surgical/trauma ICU that were intubated during their ICU stay and had available physiologic monitoring data (n  =  1202). The primary outcome was removal of endotracheal intubation (i.e. extubation) followed within 48 h by reintubation or death (i.e. failed extubation). We developed a standard risk marker model based on demographic and clinical data. We also developed a novel risk marker model using dynamic data elements-continuous cardiorespiratory monitoring, vital signs, and lab values.

RESULTS

Risk estimates from multivariate predictive models in the 24 h preceding extubation were significantly higher for patients that failed. Combined standard and novel risk markers demonstrated good predictive performance in leave-one-out validation: AUC of 0.64 (95% CI: 0.57-0.69) and 1.6 alerts per week to identify 32% of extubations that will fail. Novel risk factors added significantly to the standard model.

CONCLUSION

Predictive analytics monitoring models can detect changes in vital signs, continuous cardiorespiratory monitoring, and laboratory measurements in both the hours preceding and following extubation for those patients destined for extubation failure.

Noninvasive ventilation in acute respiratory failure: which recipe for success?

Noninvasive positive-pressure ventilation (NPPV) to treat acute respiratory failure has expanded tremendously over the world in terms of the spectrum of diseases that can be successfully managed, the locations of its application and achievable goals.

The turning point for the successful expansion of NPPV is its ability to achieve the same physiological effects as invasive mechanical ventilation with the avoidance of the life-threatening risks correlated with the use of an artificial airway.

Cardiorespiratory arrest, extreme psychomotor agitation, severe haemodynamic instability, nonhypercapnic coma and multiple organ failure are absolute contraindications for NPPV. Moreover, pitfalls of NPPV reduce its rate of success; consistently, a clear plan of what to do in case of NPPV failure should be considered, especially for patients managed in unprotected setting. NPPV failure is likely to be reduced by the application of integrated therapeutic tools in selected patients handled by expert teams.

In conclusion, NPPV has to be considered as a rational art and not just as an application of science, which requires the ability of clinicians to both choose case-by-case the best “ingredients” for a “successful recipe” (i.e.patient selection, interface, ventilator, interface,etc.) and to avoid a delayed intubation if the ventilation attempt fails.

Central Venous Oxygen Saturation as a Predictor of a Successful Spontaneous Breathing Trial from Mechanical Ventilation: A Prospective, Nested Case-Control Study

Background:

Weaning from mechanical ventilation is a key element in the care of critically ill patients, and Spontaneous Breathing Trial (SBT) is a crucial step in this procedure. This nested case-control study aimed to evaluate whether central oxygen saturation (ScvO₂) values and their changes could independently predict the SBT outcome among mechanically ventilated patients.

Methods:

A prospective cohort of patients who were mechanically ventilated for at least 48hours and fulfilled the criteria of readiness to wean constituted the study population. All patients attempted a SBT and were then categorized in SBT success group and SBT failure group, based on a combination of criteria which indicated whether SBT was successful or not. Multivariate binary logistic regression analysis was utilized to indicate the independent predictors of SBT success, while the Receiver Operating Characteristic (ROC) curves were used to demonstrate the diagnostic accuracy of these independent predictors.

Results:

Seventy-seven patients 69(18-86) years old; 62.3% male) constituted the study population. SBT was successful among 63.6% of them. A decrease in ScvO₂ values (ΔScvO₂) < 4% between the beginning and the end of the trial independently predicted the successful outcome (OR=18.278; 95% CI=4.017-83.163), along with age, Hemoglobin concentration (Hb) and arterial oxygen saturation (SaO₂). Diagnostic accuracy for ΔScvO₂ alone (ROC area=0.715) was slightly superior to that of either SaO₂ (0.625) or Hb (0.685) to predict SBT success.

Conclusion:

ScvO₂ is an independent predictor of the weaning outcome and its evaluation may further facilitate the accurate categorization among those patients who pass or fail the SBT.