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

Analyzing key elements of breathing patterns, deriving remaining variables, and identifying cutoff values in individuals with chronic respiratory disease and healthy subjects

BACKGROUND

Pulmonary physiology encompasses intricate breathing patterns (BPs), characterized by breathing frequency (Bf), volumes, and flows. The complexities intensify in the presence of interstitial lung disease (ILD) and chronic obstructive pulmonary disease (COPD), especially during exercise. This study seeks to identify pivotal factors driving changes among these variables and establish cutoff values, comparing their efficacy in differentiating BPs to traditional methods, specifically a breathing reserve (BR) of 30% and a Bf of 50 bpm.

METHODS

Screening 267 subjects revealed 23 with ILD, 126 with COPD, 33 healthy individuals, and the exclusion of 85 subjects. Lung function tests and ramp-pattern cardiopulmonary exercise testing (CPET) were conducted, identifying crucial BP elements. Changes were compared between groups at peak exercise. The area under the receiver operating characteristic curve (AUC) analysis determined cutoff values.

RESULTS

Inspiratory time (TI) remained constant at peak exercise for all subjects (two-group comparisons, all p=NS). Given known differences in expiratory time (TE) and tidal volume (VT) among ILD, COPD, and healthy states, constant TI could infer patterns for Bf, total breathing cycle time (TTOT=60/Bf), I:E ratio, inspiratory duty cycle (IDC, TI/TTOT), rapid shallow breathing index (Bf/VT), tidal inspiratory and expiratory flows (VT/TI and VT/TE), and minute ventilation (V̇E=Bf×VT) across conditions. These inferences aligned with measurements, with potential type II errors causing inconsistencies. RSBI of 23 bpm/L and VT/TI of 104 L/min may differentiate ILD from control, while V̇E of 54 L/min, BR of 30%, and VT/TE of 108 may differentiate COPD from control. BR of 21%, TE of 0.99 s, and IDC of .45 may differentiate ILD from COPD. The algorithm outperformed traditional methods (AUC 0.84-0.91 versus 0.59-0.90).

CONCLUSION

The quasi-fixed TI, in conjunction with TE and VT, proves effective in inferring time-related variables of BPs. The findings have the potential to significantly enhance medical education in interpreting cardiopulmonary exercise testing. Moreover, the study introduces a novel algorithm for distinguishing BPs among individuals with ILD, COPD, and those who are healthy.

Electrical Impedance Tomography as a monitoring tool during weaning from mechanical ventilation: an observational study during the spontaneous breathing trial

BACKGROUND

Prolonged weaning from mechanical ventilation is associated with poor clinical outcome. Therefore, choosing the right moment for weaning and extubation is essential. Electrical Impedance Tomography (EIT) is a promising innovative lung monitoring technique, but its role in supporting weaning decisions is yet uncertain. We aimed to evaluate physiological trends during a T-piece spontaneous breathing trail (SBT) as measured with EIT and the relation between EIT parameters and SBT success or failure.

METHODS

This is an observational study in which twenty-four adult patients receiving mechanical ventilation performed an SBT. EIT monitoring was performed around the SBT. Multiple EIT parameters including the end-expiratory lung impedance (EELI), delta Tidal Impedance (ΔZ), Global Inhomogeneity index (GI), Rapid Shallow Breathing Index (RSBIEIT), Respiratory Rate (RREIT) and Minute Ventilation (MVEIT) were computed on a breath-by-breath basis from stable tidal breathing periods.

RESULTS

EELI values dropped after the start of the SBT (p < 0.001) and did not recover to baseline after restarting mechanical ventilation. The ΔZ dropped (p < 0.001) but restored to baseline within seconds after restarting mechanical ventilation. Five patients failed the SBT, the GI (p = 0.01) and transcutaneous CO2 (p < 0.001) values significantly increased during the SBT in patients who failed the SBT compared to patients with a successful SBT.

CONCLUSION

EIT has the potential to assess changes in ventilation distribution and quantify the inhomogeneity of the lungs during the SBT. High lung inhomogeneity was found during SBT failure. Insight into physiological trends for the individual patient can be obtained with EIT during weaning from mechanical ventilation, but its role in predicting weaning failure requires further study.

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.

Lung Ultrasound Score as a Predictor of Failure to Wean COVID-19 Elderly Patients off Mechanical Ventilation: A Prospective Observational Study

Background

The lung ultrasound score was developed for rapidly assessing the extent of lung ventilation, and it can predict failure to wean various types of patients off mechanical ventilation. Whether it is also effective for COVID-19 patients is unclear.

Methods

This single-center, prospective, observational study was conducted to assess the ability of the 12-region lung ultrasound score to predict failure to wean COVID-19 patients off ventilation. In parallel, we assessed whether right hemidiaphragmatic excursion or previously published predictors of weaning failure can apply to these patients. Predictive ability was assessed in terms of the area under the receiver operating characteristic curve (AUC).

Results

The mean age of the 35 patients in the study was (75 ± 9) years and 12 patients (37%) could not be weaned off mechanical ventilation. The lung ultrasound score predicted these failures with an AUC of 0.885 (95% CI 0.770-0.999, p < 0.001), and a threshold score of 10 provided specificity of 72.7% and sensitivity of 92.3%. AUCs were lower for previously published predictors of weaning failure, and right hemidiaphragmatic excursion did not differ significantly between the two groups.

Conclusion

The lung ultrasound score can accurately predict failure to wean critically ill COVID-19 patients off mechanical ventilation, whereas assessment of right hemidiaphragmatic excursion does not appear helpful in this regard.

Trial Registration

https://clinicaltrials.gov/ct2/show/NCT05706441.

Rapid shallow breathing index predicting extubation outcomes: A systematic review and meta-analysis

OBJECTIVE

This meta-analysis aimed to assess the predictive value of the rapid shallow breathing index for extubation outcomes.

METHODOLOGY

We conducted a systematic review of literature (inception to March 2023) and a meta-analysis. Statistical analysis was performed using Meta-Disc 1.4 software, RevMan 5.4 software and Stata 14.0 software to evaluate the predictive value of RSBI for extubation outcomes.

RESULTS

A total of 1,987 studies were retrieved, and after applying the inclusion criteria, 79 studies were included in the final analysis, involving 13,170 patients undergoing mechanical ventilation. The random-effects model was employed for statistical analysis. The summary receiver operating characteristic curves (SROC) area under the curve (AUC) was 0.8144. The pooled sensitivity was 0.60 (95% CI: 0.59, 0.61), the pooled specificity was 0.68 (95% CI: 0.66, 0.70).

CONCLUSIONS

The Rapid Shallow Breathing Index demonstrated moderate accuracy, poor pooled sensitivity and specificity in predicting successful extubation, however the study does not present adequate data to support or reject the use of this tool as a single parameter that predicts extubation outcome. Future studies should explore the combination of The Rapid Shallow Breathing Index with other indicators and clinical experience to improve the success rate of extubation and reduce the risk of extubation failure.

IMPLICATIONS FOR CLINICAL PRACTICE

Premature and delayed extubation in mechanically ventilated patients can have a negative impact on prognosis and prolong hospital stay. The Rapid Shallow Breathing Index is a simple, cost-effective, and easily monitored objective evaluation index, which can be used to predict the outcome of extubation, especially in primary hospitals. Our study comprehensively evaluated the value of this tool in predicting extubation outcomes, which can help clinicians combine subjective experience with objective indicators to improve the accuracy of extubation time decisions.

Predicting extubation in patients with traumatic cervical spinal cord injury using the diaphragm electrical activity during a single maximal maneuver

BACKGROUND

The unsuccessful extubation in patients with traumatic cervical spinal cord injuries (CSCI) may result from impairment diaphragm function and monitoring of diaphragm electrical activity (EAdi) can be informative in guiding extubation. We aimed to evaluate whether the change of EAdi during a single maximal maneuver can predict extubation outcomes in CSCI patients.

METHODS

This is a retrospective study of CSCI patients requiring mechanical ventilation in the ICU of a tertiary hospital. A single maximal maneuver was performed by asking each patient to inhale with maximum strength during the first spontaneous breathing trial (SBT). The baseline (during SBT before maximal maneuver), maximum (during the single maximal maneuver), and the increase of EAdi (ΔEAdi, equal to the difference between baseline and maximal) were measured. The primary outcome was extubation success, defined as no reintubation after the first extubation and no tracheostomy before any extubation during the ICU stay.

RESULTS

Among 107 patients enrolled, 50 (46.7%) were extubated successfully at the first SBT. Baseline EAdi, maximum EAdi, and ΔEAdi were significantly higher, and the rapid shallow breathing index was lower in patients who were extubated successfully than in those who failed. By multivariable logistic analysis, ΔEAdi was independently associated with successful extubation (OR 2.03, 95% CI 1.52-3.17). ΔEAdi demonstrated high diagnostic accuracy in predicting extubation success with an AUROC 0.978 (95% CI 0.941-0.995), and the cut-off value was 7.0 μV.

CONCLUSIONS

The increase of EAdi from baseline SBT during a single maximal maneuver is associated with successful extubation and can help guide extubation in CSCI patients.

Is diaphragm ultrasound better than rapid shallow breathing index for predicting weaning in critically ill elderly patients?

Introduction

Prolonged weaning is associated with worse clinical outcomes in elderly patients. Beside traditional rapid shallow breathing index (RSBI), diaphragm ultrasound is a promising technique to evaluate the weaning process. We aimed to perform diaphragm ultrasonography for predicting the weaning process and its relation with frailty in the critically ill elderly population.

Materials and Methods

We enrolled thirthy-two patients over 65 years of age who were mechanically ventilated for at least 48 hours. Thickness of diaphragm and excursion were evaluated within 48 h of intubation and during spontaneous breathing trial (SBT). Clinical parameters, frailty, diaphragm ultrasound results were compared according to the weaning status.

Results

Mean age (standard deviation) was 79.3 ± 7.9 years, and 18 (56.3%) patients were classified as weaning failure. Diaphragmatic excursion during SBT was the only statistically significant parameter associated with weaning failure [2.37 cm (0.67) vs 1.43 cm (0.15), p= 0.0359]. There was no statistically significant difference regarding RSBI between the groups [70.5 (46) vs 127.5 (80), p= 0.09]. Baseline thickness of diaphragm and excursion at SBT were moderately correlated with frailty.

Conclusion

Ultrasound can be used to show diaphragm dysfunction in the elderly frail population, and a multifactorial approach to the extubation process may include ultrasound instead of using traditional RSBI alone.

How I Teach: Liberation from Mechanical Ventilation

Liberation from mechanical ventilation is one of the most important decisions in the intensive care unit (ICU), as extubation failure is associated with worse outcomes. Determining readiness to extubate can be challenging in complex patients and lead to provider stress. Here, we provide our approach to teaching liberation from mechanical ventilation for learners in the ICU. We use a case-based didactic session that purposefully introduces ambiguous cases without a clear answer, utilizing aspects of both cognitive load theory and adult learning theories.

Effect of a Japanese Version of the Burns Wean Assessment Program e-Learning Materials on Ventilator Withdrawal for Intensive Care Unit Nurses

BACKGROUND

No assessment tool for predicting ventilator withdrawal success is currently available in Japan. Thus, an accessible and valid assessment tool to address this issue is needed. The Burns Wean Assessment Program (BWAP) has been validated as a reliable predictor of ventilator withdrawal outcomes. However, nurses must be familiar with this tool to ensure its efficient utilization in clinical settings.

PURPOSE

This study was designed to examine the effect of a 26-item Japanese version of BWAP (J-BWAP) e-learning materials on ventilator withdrawal in a sample of intensive care unit nurses in Japan.

METHODS

The BWAP was translated into Japanese, checked, and verified as the J-BWAP. Nonrandomized intensive care unit nurses from six hospitals were assigned to three groups, including Intervention Group 1 (e-learning in one session), Intervention Group 2 (e-learning over three sessions during 1 week), and the control group. The participants underwent pretests and posttests using web-based, simulated patients. The primary outcome measure was the difference in online pretest and posttest total scores among the two intervention groups and the control group. The feasibility of the J-BWAP and its e-learning materials was evaluated using four frameworks: acceptability, demand, implementation, and adaptation.

RESULTS

Of the 48 participants in the study, 32 completed the posttest and were included in the analysis (dropout rate: 33.3%). The difference between pretest and posttest scores was significantly higher in the intervention groups than the control group (2 vs. -1, p = .0191) and in Intervention Group 2 than the control group (2.0 vs. -0.5, p = .049). The feasibility frameworks for the J-BWAP and its e-learning materials were mostly positive.

CONCLUSIONS/IMPLICATIONS FOR PRACTICE

The development of the J-BWAP and training nurses using e-learning were shown to be feasible in this study. The J-BWAP contents are appropriate for predicting the outcome of mechanical ventilation withdrawal. The J-BWAP has the potential to become a common tool among Japanese medical professionals after the contents are further simplified for daily application in clinical practice. Subsequent studies should verify the reliability and validity of this tool and test the real-world utility of the J-BWAP using randomized controlled trials in Japanese clinical settings.

Static Respiratory System Compliance as a Predictor of Extubation Failure in Patients with Acute Respiratory Failure

PURPOSE

Ventilator weaning protocols rely in part on objective indices to best predict extubation failure in the critically ill. We investigated static respiratory system compliance (RC) as a predictor of extubation failure, in comparison to extubation readiness using rapid shallow breathing index (RSBI).

MATERIAL AND METHODS

This was a cross-sectional, multi-institutional study of mechanically ventilated patients admitted between 12/01/2017 and 12/01/2019. All patients older than 18 years with a documented spontaneous breathing trial and extubation trial were included. RC and RSBI were calculated prior to the extubation trial. The primary outcome was extubation failure-defined as need for reintubation within 72 h from time of extubation.

RESULTS

Of the 2263 patients, 55.8% were males with a mean age of 68 years. The population consisted mostly of Caucasians (73%) and African Americans (20.4%). 274 (12.1%) patients required reintubation within 72 h. On multivariate logistic regression after adjusting for age, sex, body mass index (BMI), admission Sequential Organ Failure Assessment (SOFA) score, number of ventilator days, and the P/F ratio on the day of extubation, RC remained the strongest predictor for extubation failure at 24 h (aOR 1.45; 95% CI 1.00-2.10) and 72 h (aOR 1.58; 95% CI 1.15-2.17). There was no significant association between RSBI and extubation failure at 24 (aOR 1.00; 95% CI 0.99-1.01) or at 72 h (aOR 1.00; 95% CI 0.99-1.01).

CONCLUSION

RC measured on the day of extubation is a promising physiological discriminant to potentially risk stratify patients with acute respiratory failure for extubation readiness. We recommend further validation studies in prospective cohorts.

Developing a machine-learning model for real-time prediction of successful extubation in mechanically ventilated patients using time-series ventilator-derived parameters

Background

Successful weaning from mechanical ventilation is important for patients admitted to intensive care units. However, models for predicting real-time weaning outcomes remain inadequate. Therefore, this study aimed to develop a machine-learning model for predicting successful extubation only using time-series ventilator-derived parameters with good accuracy.

Methods

Patients with mechanical ventilation admitted to the Yuanlin Christian Hospital in Taiwan between August 2015 and November 2020 were retrospectively included. A dataset with ventilator-derived parameters was obtained before extubation. Recursive feature elimination was applied to select the most important features. Machine-learning models of logistic regression, random forest (RF), and support vector machine were adopted to predict extubation outcomes. In addition, the synthetic minority oversampling technique (SMOTE) was employed to address the data imbalance problem. The area under the receiver operating characteristic (AUC), F1 score, and accuracy, along with the 10-fold cross-validation, were used to evaluate prediction performance.

Results

In this study, 233 patients were included, of whom 28 (12.0%) failed extubation. The six ventilatory variables per 180 s dataset had optimal feature importance. RF exhibited better performance than the others, with an AUC value of 0.976 (95% confidence interval [CI], 0.975-0.976), accuracy of 94.0% (95% CI, 93.8-94.3%), and an F1 score of 95.8% (95% CI, 95.7-96.0%). The difference in performance between the RF and the original and SMOTE datasets was small.

Conclusion

The RF model demonstrated a good performance in predicting successful extubation in mechanically ventilated patients. This algorithm made a precise real-time extubation outcome prediction for patients at different time points.

The ratio of respiratory rate to diaphragm thickening fraction for predicting extubation success

BACKGROUND

Several parameters are used to predict successful extubation but their accuracy varies among studies. We hypothesized that combining conventional and diaphragmatic parameters would be more effective than using just one. Our primary objective was to evaluate the performance of the respiratory rate in relation to the diaphragm thickening fraction (RR/DTF) ratio to predict the success of extubation.

METHODS

We enrolled 130 adult patients who required invasive mechanical ventilation, planned to be extubated, and used a spontaneous breathing trial (SBT) in the intensive care unit from July 2020 to April 2022. We measured the conventional parameters and the diaphragmatic parameters 2 h after SBT. The RR/DTF was calculated by dividing the respiratory rate (RR) by the diaphragm thickening fraction (DTF). The definition of weaning success is successful extubation within 48 h.

RESULTS

Of 130 patients, 8 patients (6.2%) were reintubated within 48 h. The RR/DTF was significantly lower in the successful extubation group than in the extubation failure group (right hemidiaphragm; 0.47 (0.33-0.64) vs 1.1 (0.6-2.32), p < 0.001 and left hemidiaphragm; 0.45 (0.31-0.65) vs 0.78 (0.48-1.75), p < 0.001). The right RR/DTF using a cut-off point at ≤ 0.81 had a sensitivity of 87.7%, a specificity of 75%, and areas under the receiver operating characteristic curve (AUROC) of 0.762 for predicting successful extubation (p = 0.013). The sensitivity, specificity, and AUROC for predicting extubation success of right DTF at a cut-off point of ≥ 26.2% were 84.3%, 62.5%, and 0.775, respectively (p = 0.009).

CONCLUSION

The RR/DTF ratio is a promising tool for predicting extubation outcome. Additionally, using RR/DTF was more reliable than conventional or diaphragmatic parameters alone in predicting extubation success.

Effects of Mechanical Ventilator Weaning Education on ICU Nurses and Patient Outcomes: A Scoping Review

BACKGROUND

Assessment of mechanical ventilator (MV) weaning is a complex process that requires education for nurses. This scoping review aimed to clarify the effects of MV weaning education on intensive care unit nurses and patient outcomes.

METHOD

Four databases were searched. The inclusion criteria were studies on MV weaning education for nurses, outcome measures for patients or nurses, and quantitative research.

RESULTS

In total, 663 studies were identified. The criteria for a full review (n = 15) were educational protocols (n = 13) and the Burns Wean Assessment Program (n = 2). Patient outcomes determined the MV duration. The weaning protocol was convenient for nurses. Nevertheless, their clinical judgment skills must be improved, regardless of the availability of a protocol. Education is crucial for producing positive outcomes.

CONCLUSION

Education for nurses on MV weaning showed shortened MV duration. No significant effects were found for other outcomes. [J Contin Educ Nurs. 2023;54(4):185-192.].

Pendelluft as a predictor of weaning in critically ill patients: An observational cohort study

Objective: Weaning failure is associated with adverse clinical outcomes. This study aimed to evaluate the accuracy of pendelluft during the spontaneous breathing trials (SBT) as a predictor of weaning outcome of patients with mechanical ventilation.

Methods: An observational cohort study included 60 critically ill patients who were eligible for extubation. Pendelluft and electrical activity of the diaphragm (Edi) were monitored at baseline and every 10 minutes for the first 30 min of SBT denoted as T0, T1, T2, and T3. The pendelluft was measured using electrical impedance tomography (EIT), and Edi parameters were collected by Edi catheter. Patients were followed up after extubation and were divided into success group and failure group. Pendelluft, Edi parameters, respiratory parameters, and clinical outcomes such as intensive care units (ICU) stay, mortality, and 28-day ventilator-free days were compared between the two groups. Receiver operating characteristic (ROC) curves were constructed to evaluate the ability of pendelluft to predict weaning outcome.

Results: Fifty patients (50/60) were successfully weaned from the machine and 10 (10/60) failed, with weaning failure rate of 16.7%. Respiratory parameters such as rapid shallow breathing index (RSBI), respiratory rate (RR) and Edi parameters such as maximum value of Edi (Edimax), Edi variation between a maximum and minimum(ΔEdi) in the failure group were higher than those in the success group. The ICU stay and the 28-day ventilator-free days in the failure group were significantly longer than those in the success group. The 28-day mortality rate was higher in the failure group. The pendelluft mainly occurred in the early stage of SBT. Ventral pendelluft and total pendelluft in the failure group were higher than those in the success group at T1. Edimax and ΔEdi were positively correlated with pendelluft. The area under ROC curve (AUC) showed moderate predictive ability for ventral pendelluft in predicting weaning failure at T1 (AUC 0.76, 95% CI 0.58–0.94, cut-off value &gt; 3% global tidal variation).

Conclusion: Pendelluft is one of the factors leading to weaning failure, which may be related to diaphragm function. Measuring pendelluft volume maybe helpful to predict weaning.

The risk factors of reintubation in intensive care unit patients on mechanical ventilation: A systematic review and meta-analysis

OBJECTIVE

To assess risk factors of reintubation in intensive care unit patients on mechanical ventilation.

METHODOLOGY

We conducted a systematic review of literature (inception to May 2022) and a meta-analysis. Data are reported as pooled odds ratios for categorical variables and mean differences for continuous variables.

RESULTS

A total of 2459 studies were retrieved of which 38 studies were included in a meta-analysis involving 22,304 patients. Risk factors identified were: older age, higher APACHE II scores, COPD, pneumonia, shock, low SaO₂, low PaO₂, low PaO₂/FiO₂, low hemoglobin, low albumin, high brain natriuretic peptide, low pH, high respiratory rate, low tidal volume, a higher rapid shallow breathing index, a lower vital capacity, a higher number of spontaneous breathing trials, prolonged length of mechanical ventilation, weak cough, a reduced patient's cough peak flow and positive cuff leak test. Subgroup analysis showed that risk factors substantially overlap when reintubation was considered within 48 hours or within 72 hours after extubation.

CONCLUSIONS

We identified 21 factors associated with increased risk for reintubation. These allow to recognize the patient at high risk for reintubation at an early stage. Future studies may combine these factors to develop comprehensive predictive algorithms allowing appropriate vigilance.

Comprehensive breathing variability indices enhance the prediction of extubation failure in patients on mechanical ventilation

BACKGROUND AND OBJECTIVE

Despite the numerous studies on extubation readiness assessment for patients who are invasively ventilated in the intensive care unit, a 10-15% extubation failure rate persists. Although breathing variability has been proposed as a potential predictor of extubation failure, it is mainly assessed using simple statistical metrics applied to basic respiratory parameters. Therefore, the complex pattern of breathing variability conveyed by continuous ventilation waveforms may be underexplored.

METHODS

Here, we aimed to develop novel breathing variability indices to predict extubation failure among invasively ventilated patients. First, breath-to-breath basic and comprehensive respiratory parameters were computed from continuous ventilation waveforms 1 h before extubation. Subsequently, the basic and advanced variability methods were applied to the respiratory parameter sequences to derive comprehensive breathing variability indices, and their role in predicting extubation failure was assessed. Finally, after reducing the feature dimensionality using the forward search method, the combined effect of the indices was evaluated by inputting them into the machine learning models, including logistic regression, random forest, support vector machine, and eXtreme Gradient Boosting (XGBoost).

RESULTS

The coefficient of variation of the dynamic mechanical power per breath (CV-MPd[J/breath]) exhibited the highest area under the receiver operating characteristic curve (AUC) of 0.777 among the individual indices. Furthermore, the XGBoost model obtained the best AUC (0.902) by combining multiple selected variability indices.

CONCLUSIONS

These results suggest that the proposed novel breathing variability indices can improve extubation failure prediction in invasively ventilated patients.

SPECKLE TRACKING QUANTIFICATION PARASTERNAL INTERCOSTAL MUSCLE LONGITUDINAL STRAIN TO PREDICT WEANING OUTCOMES: A MULTICENTRIC OBSERVATIONAL STUDY

ABSTRACT

Background: The purpose of this study was to determine the feasibility, reliability, and reproducibility of parasternal intercostal muscle longitudinal strain (LSim) quantification by speckle tracking and the value of maximal LSim to predict weaning outcomes. Methods: This study was divided into three phases. Phases 1 and 2 comprehended prospective observational programs to evaluate the feasibility, reliability, and repeatability of speckle tracking to assess LSim in healthy subjects and mechanically ventilated patients. Phase 3 was a multicenter retrospective study to evaluate the value of maximal LSim, intercostal muscle thickening fraction (TFim), diaphragmatic thickening fraction, diaphragmatic excursion, and rapid shallow breathing index to predict weaning outcomes. Results: A total of 25 healthy subjects and 20 mechanically ventilated patients were enrolled in phases 1 and 2, respectively. Maximal LSim was easily accessible, and the intraoperator reliability and interoperator reliability were excellent in eupnea, deep breathing, and mechanical ventilation. The intraclass correlation coefficient ranged from 0.85 to 0.96. Moreover, 83 patients were included in phase 3. The areas under the receiver operating characteristic curve of maximal LSim, TFim, diaphragmatic thickening fraction, diaphragmatic excursion, and rapid shallow breathing index were 0.91, 0.79, 0.71, 0.70, and 0.78 for the prediction of successful weaning, respectively. The best cutoff values of LSim and TFim were >-6% (sensitivity, 100%; specificity, 64.71%) and <7.6% (sensitivity, 100%; specificity, 50.98%), respectively. Conclusions: The quantification of LSim by speckle tracking was easily achievable in healthy subjects and mechanically ventilated patients and presented a higher predictive value for weaning success compared with conventional weaning parameters. Trial registration no. ChiCTR2100049817.

Comparison of assessment of diaphragm function using speckle tracking between patients with successful and failed weaning: a multicentre, observational, pilot study

Background

Diaphragmatic ultrasound has been increasingly used to evaluate diaphragm function. However, current diaphragmatic ultrasound parameters provide indirect estimates of diaphragmatic contractile function, and the predictive value is controversial. Two-dimensional (2D) speckle tracking is an effective technology for measuring tissue deformation and can be used to measure diaphragm longitudinal strain (DLS) to assess diaphragm function. The purpose of this study was to determine the feasibility and reproducibility of DLS quantification by 2D speckle tracking and to determine whether maximal DLS could be used to predict weaning outcomes.

Methods

This study was performed in the intensive care unit of two teaching hospitals, and was divided into two studies. Study A was a prospective study to evaluate the feasibility, reliability, and repeatability of speckle tracking in assessing DLS in healthy subjects and mechanically ventilated patients. Study B was a multicentre retrospective study to assess the use of maximal DLS measured by speckle tracking in predicting weaning outcomes.

Results

Twenty-five healthy subjects and twenty mechanically ventilated patients were enrolled in Study A. Diaphragmatic speckle tracking was easily accessible. The intra- and interoperator reliability were good to excellent under conditions of eupnoea, deep breathing, and mechanical ventilation. The intraclass correlation coefficient (ICC) ranged from 0.78 to 0.95. Ninety-six patients (fifty-nine patients were successfully weaned) were included in Study B. DLS exhibited a fair linear relationship with both the diaphragmatic thickening fraction (DTF) (R2 = 0.73, p < 0.0001) and diaphragmatic excursion (DE) (R2 = 0.61, p < 0.0001). For the prediction of successful weaning, the areas under the ROC curves of DLS, diaphragmatic thickening fraction DTF, RSBI, and DE were 0.794, 0.794, 0.723, and 0.728, respectively. The best cut-off value for predicting the weaning success of DLS was less than -21%, which had the highest sensitivity of 89.19% and specificity of 64.41%.

Conclusions

Diaphragmatic strain quantification using speckle tracking is easy to obtain in healthy subjects and mechanically ventilated patients and has a high predictive value for mechanical weaning. However, this method offers no advantage over RSBI. Future research should assess its value as a predictor of weaning.

Trial registration

This study was registered in the Chinese Clinical Trial Register (ChiCTR), ChiCTR2100049816. Registered 10 August 2021. http://www.chictr.org.cn/showproj.aspx?proj=131790

Diaphragmatic ultrasonography-based rapid shallow breathing index for predicting weaning outcome during a pressure support ventilation spontaneous breathing trial

Background

The optimum timing to wean is crucial to avoid negative outcomes for mechanically ventilated patients. The rapid shallow breathing index (RSBI), a widely used weaning index, has limitations in predicting weaning outcomes. By replacing the tidal volume of the RSBI with diaphragmatic excursion (DE) and diaphragm thickening fraction (DTF) assessed by ultrasonography, we calculated two weaning indices, the diaphragmatic excursion rapid shallow breathing index (DE-RSBI, respiratory rate [RR]/DE) and the diaphragm thickening fraction rapid shallow breathing index (DTF-RSBI, RR/DTF). The aim of this study was to evaluate the predictive values of DTF-RSBI, DE-RSBI and traditional RSBI in weaning failure.

Methods

This prospective observational study included patients undergoing mechanical ventilation (MV) for > 48 h and who were readied for weaning. During a pressure support ventilation (PSV) spontaneous breathing trial (SBT), right hemidiaphragmatic excursion and DTF were measured by bedside ultrasonography as well as RSBI. Weaning failure was defined as: (1) failing the SBT and (2) SBT success but inability to maintain spontaneous breathing for more than 48 h without noninvasive or invasive ventilation. A receiver operator characteristic (ROC) curve was used for analyzing the diagnostic accuracy of RSBI, DE-RSBI, and DTF-RSBI.

Results

Of the 110 patients studied, 37 patients (33.6%) failed weaning. The area under the ROC (AUROC) curves for RSBI, DE-RSBI, and DTF-RSBI for predicting failed weaning were 0.639, 0.813, and 0.859, respectively. The AUROC curves for DE-RSBI and DTF-RSBI were significantly higher than for RSBI (P = 0.004 and P < 0.001, respectively). The best cut-off values for predicting failed weaning were RSBI > 51.2 breaths/min/L, DE-RSBI > 1.38 breaths/min/mm, and DTF-RSBI > 78.1 breaths/min/%.

Conclusions

In this study, two weaning indices determined by bedside ultrasonography, the DE-RSBI (RR/DE) and DTF-RSBI (RR/DTF), were shown to be more accurate than the traditional RSBI (RR/VT) in predicting weaning outcome during a PSV SBT.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-02133-5.

Machine learning for predicting successful extubation in patients receiving mechanical ventilation

Ventilator liberation is one of the most critical decisions in the intensive care unit; however, prediction of extubation failure is difficult, and the proportion thereof remains high. Machine learning can potentially provide a breakthrough in the prediction of extubation success. A total of seven studies on the prediction of extubation success using machine learning have been published. These machine learning models were developed using data from electronic health records, 8–78 features, and algorithms such as artificial neural network, LightGBM, and XGBoost. Sensitivity ranged from 0.64 to 0.96, specificity ranged from 0.73 to 0.85, and area under the receiver operating characteristic curve ranged from 0.70 to 0.98. The features deemed most important included duration of mechanical ventilation, PaO₂, blood urea nitrogen, heart rate, and Glasgow Coma Scale score. Although the studies had limitations, prediction of extubation success by machine learning has the potential to be a powerful tool. Further studies are needed to assess whether machine learning prediction reduces the incidence of extubation failure or prolongs the duration of ventilator use, thereby increasing tracheostomy and ventilator-related complications and mortality.

Respiratory distress observation scales to predict weaning outcome

Background

Whether dyspnea is present before starting a spontaneous breathing trial (SBT) and whether it may affect the outcome of the SBT is unknown. Mechanical Ventilation—Respiratory Distress Observation Scale (MV-RDOS) has been proposed as a reliable surrogate of dyspnea in non-communicative intubated patients. In the present study, we sought (1) to describe the evolution of the MV-RDOS during a SBT and (2) to investigate whether MV-RDOS can predict the outcome of the SBT.

Methods

Prospective, single-center study in a twenty-two bed ICU in a tertiary center. Patients intubated since more 48 h who had failed a first SBT were eligible if they meet classical readiness to wean criteria. The MV-RDOS was assessed before, at 2-min, 15-min and 30-min (end) of the SBT. The presence of clinically important dyspnea was inferred by a MV-RDOS value ≥  2.6.

Results

Fifty-eight patients (age 63 [51–70], SAPS II 66 [51–76]; med [IQR]) were included. Thirty-three (57%) patients failed the SBT, whose 18 (55%) failed before 15-min. Twenty-five (43%) patients successfully passed the SBT. A MV-RDOS ≥ 2.6 was present in ten (17%) patients before to start the SBT. All these ten patients subsequently failed the SBT. A MV-RDOS ≥ 2.6 at 2-min predicted a SBT failure with a 51% sensibility and a 88% specificity (AUC 0.741 95% confidence interval [CI] 0.616–0.866, p = 0.002). Best cut-off value at 2-min was 4.3 and predicted SBT failure with a 27% sensibility and a 96% specificity.

Conclusion

Despite patients met classical readiness to wean criteria, respiratory distress assessed with the MV-RDOS was frequent at the beginning of SBT. Measuring MV-RDOS before to initiate a SBT could avoid undue procedure and reduce patient’s exposure to unnecessary mechanical ventilation weaning failure and distress.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13054-022-04028-7.

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 Contribution of Chest X-Ray to Predict Extubation Failure in Mechanically Ventilated Patients Using Machine Learning-Based Algorithms

To evaluate the contribution of a preextubation chest X-ray (CXR) to identify the risk of extubation failure in mechanically ventilated patients.

What is new in respiratory monitoring?

This paper provides a review of a selection of papers published in the Journal of Clinical Monitoring and Computing in 2020 and 2021 highlighting what is new within the field of respiratory monitoring. Selected papers cover work in pulse oximetry monitoring, acoustic monitoring, respiratory system mechanics, monitoring during surgery, electrical impedance tomography, respiratory rate monitoring, lung ultrasound and detection of patient-ventilator asynchrony.

Weaning critically ill patients from mechanical ventilation: a protocol from a multicenter retrospective cohort study

BACKGROUND

Mechanical ventilation (MV) is an important lifesaving method in intensive care unit (ICU). Prolonged MV is associated with ventilator associated pneumonia (VAP) and other complications. However, premature weaning from MV may lead to higher risk of reintubation or mortality. Therefore, timely and safe weaning from MV is important. In addition, identification of the right patient and performing a suitable weaning process is necessary. Although several guidelines about weaning have been reported, compliance with these guidelines is unknown. Therefore, the aim of this study is to explore the variation of weaning in China, associations between initial MV reason and clinical outcomes, and factors associated with weaning strategies using a multicenter cohort.

METHODS

This multicenter retrospective cohort study will be conducted at 17 adult ICUs in China, that included patients who were admitted in this 17 ICUs between October 2020 and February 2021. Patients under 18 years of age and patients without the possibility for weaning will be excluded. The questionnaire information will be registered by a specific clinician in each center who has been evaluated and qualified to carry out the study.

DISCUSSION

In a previous observational study of weaning in 17 ICUs in China, weaning practices varies nationally. Therefore, a multicenter retrospective cohort study is necessary to be conducted to explore the present weaning methods used in China.

TRIAL REGISTRATION

Chinese Clinical Trial Registry (ChiCTR) (No. ChiCTR2100044634).