The predictive value of brain natriuretic peptide or N-terminal pro-brain natriuretic peptide for weaning outcome in mechanical ventilation patients: Evidence from SROC

Predictors of weaning failure in ventilated intensive care patients: a systematic evidence map

BACKGROUND

Ventilator weaning is of great importance for intensive care patients in order to avoid complications caused by prolonged ventilation. However, not all patients succeed in weaning immediately. Their spontaneous breathing may be insufficient, resulting in extubation failure and the subsequent need for reintubation. To identify patients at high risk for weaning failure, a variety of potential predictors has already been examined in individual studies and meta-analyses over the last decades. However, an overview of all the predictors investigated is missing.

AIM

To provide an overview of empirically investigated predictors for weaning failure.

METHODS

A systematic evidence map was developed. To this end, we conducted a systematic search in the Medline, Cochrane, and CINAHL databases in December 2023 and added a citation search and a manual search in June 2024. Studies on predictors for weaning failure in adults ventilated in the intensive care unit were included. Studies on children, outpatients, non-invasive ventilation, or explanatory factors of weaning failure were excluded. Two reviewers performed the screening and data extraction independently. Data synthesis followed an inductive approach in which the predictors were thematically analyzed, sorted, and clustered.

RESULTS

Of the 1388 records obtained, 140 studies were included in the analysis. The 112 prospective and 28 retrospective studies investigated a total of 145 predictors. These were assigned to the four central clusters 'Imaging procedures' (n = 22), 'Physiological parameters' (n = 61), 'Scores and indices' (n = 53), and 'Machine learning models' (n = 9). The most frequently investigated predictors are the rapid shallow breathing index, the diaphragm thickening fraction, the respiratory rate, the P/F ratio, and the diaphragm excursion.

CONCLUSION

Predictors for weaning failure are widely researched. To date, 145 predictors have been investigated with varying intensity in 140 studies that are in line with the current weaning definition. It is no longer just individual predictors that are investigated, but more comprehensive assessments, indices and machine learning models in the last decade. Future research should be conducted in line with international weaning definitions and further investigate poorly researched predictors. Registration, Protocol: https://doi.org/10.17605/OSF.IO/2KDYU.

A time series driven model for early sepsis prediction based on transformer module

Sepsis remains a critical concern in intensive care units due to its high mortality rate. Early identification and intervention are paramount to improving patient outcomes. In this study, we have proposed predictive models for early sepsis prediction based on time-series data, utilizing both CNN-Transformer and LSTM-Transformer architectures. By collecting time-series data from patients at 4, 8, and 12 h prior to sepsis diagnosis and subjecting it to various network models for analysis and comparison. In contrast to traditional recurrent neural networks, our model exhibited a substantial improvement of approximately 20%. On average, our model demonstrated an accuracy of 0.964 (± 0.018), a precision of 0.956 (± 0.012), a recall of 0.967 (± 0.012), and an F1 score of 0.959 (± 0.014). Furthermore, by adjusting the time window, it was observed that the Transformer-based model demonstrated exceptional predictive capabilities, particularly within the earlier time window (i.e., 12 h before onset), thus holding significant promise for early clinical diagnosis and intervention. Besides, we employed the SHAP algorithm to visualize the weight distribution of different features, enhancing the interpretability of our model and facilitating early clinical diagnosis and intervention.

[Natriuretic peptides in intensive care medicine]

Natriuretic peptides must be interpreted in their clinical context, especially in intensive care medicine. This overview presents the diagnostic, prognostic, and therapeutic significance of B‑type natriuretic peptide (BNP) and N‑terminal pro B‑type natriuretic peptide (NT-proBNP) in patients with cardiac dysfunction, kidney failure, sepsis, pulmonary embolism, acute respiratory distress syndrome (ARDS), acute exacerbations of chronic obstructive pulmonary disease (AECOPD), and weaning from a respirator.

Serum cholinesterase as a new nutritional indicator for predicting weaning failure in patients

Aim

The objective of this study is to examine the correlation between patient serum cholinesterase (SCHE) concentration and weaning failure in the context of invasive mechanical ventilation (IMV), as well as to identify predictors of ventilator weaning failure. Additionally, this study investigates the potential relationship between SCHE and nutritional risk for developing more effective weaning strategies.

Method

A retrospective observational study was conducted. The sample was collected from 227 patients with IMV over 48 h who underwent SBT before weaning. Relevant experimental samples and data collection were analyzed at the time of patient admission and before the initiation of the SBT. The correlation between SCHE and weaning failure was determined by multifactorial logistic regression and propensity matching scores.

Results

Weaning was successful in 127 patients and failed in 100 patients. Depending on the difficulty of weaning, 55 of these patients had difficulty in weaning and 45 had long-term weaning. In the crude cohort, experimental data collected on the day of SBT showed that SCHE concentrations were higher in patients with successful weaning than in those with failed weaning (4,514 u/l vs. 3,190 u/l p < 0.01). The critical value for predicting weaning failure was SCHE 3,228 u/l (p < 0.01). Ventilator weaning failure was predicted by multifactorial logistic regression analysis of SCHE, heart rate, and PaO₂ before SBT, with SCHE predicting ventilator weaning failure (AUC 0.714; 95% CI 0.647-0.782) better than heart rate (AUC 0.618; 95% CI 0.545-0.690), PaO₂ (AUC 0.59; 95% CI 0.515-0.664). After propensity-matched scores, SCHE remained an independent predictor of weaning failure (p = 0.05). And the SCHE concentration was strongly correlated with the patient's weaning difficulties (p < 0.01). The Nutrition Risk in Critically Ill (NUTRIC) score was also significantly correlated with SCHE according to Spearman's correlation analysis (p < 0.01).

Conclusion

Our study revealed that the patients who experienced weaning failure exhibited lower SCHE values compared to those who successfully underwent weaning. Before spontaneous breathing trial (SBT), SCHE, heart rate, and PaO₂ were identified as independent predictors of weaning failure. Following propensity score matching (PSM), SCHE and heart rate remained independent predictors. Patients with SCHE levels below 3,228 u/l should undergo careful evaluation before weaning. Our findings suggest that malnutrition may be a contributing factor to weaning failure in patients.

The predictive value of pressure recording analytical method for the duration of mechanical ventilation in children undergoing cardiac surgery with an XGBoost-based machine learning model

Objective

Prolonged mechanical ventilation in children undergoing cardiac surgery is related to the decrease in cardiac output. The pressure recording analytical method (PRAM) is a minimally invasive system for continuous hemodynamic monitoring. To evaluate the postoperative prognosis, our study explored the predictive value of hemodynamic management for the duration of mechanical ventilation (DMV).

Methods

This retrospective study included 60 infants who underwent cardiac surgery. Cardiac index (CI), the maximal slope of systolic upstroke (dp/dt_max), and cardiac cycle efficiency (CCE) derived from PRAM were documented in each patient 0, 4, 8, and 12 h (T0, T1, T2, T3, and T4, respectively) after their admission to the intensive care unit (ICU). A linear mixed model was used to deal with the hemodynamic data. Correlation analysis, receiver operating characteristic (ROC), and a XGBoost machine learning model were used to find the key factors for prediction.

Results

Linear mixed model revealed time and group effect in CI and dp/dt_max. Prolonged DMV also have negative correlations with age, weight, CI at and dp/dt_max at T2. dp/dt_max outweighing CI was the strongest predictor (AUC of ROC: 0.978 vs. 0.811, p < 0.01). The machine learning model suggested that dp/dt_max at T2 ≤ 1.049 or < 1.049 in combination with CI at T0 ≤ 2.0 or >2.0 can predict whether prolonged DMV (AUC of ROC = 0.856).

Conclusion

Cardiac dysfunction is associated with a prolonged DMV with hemodynamic evidence. CI measured by PRAM immediately after ICU admission and dp/dt_max 8h later are two key factors in predicting prolonged DMV.

Elevated NT-proBNP levels are associated with CTP ischemic volume and 90-day functional outcomes in acute ischemic stroke: a retrospective cohort study

Objective

To investigate the impact of N-terminal pro-B-type natriuretic peptide (NT-proBNP) on CTP infarct core volume and poor 90-day functional outcomes in acute ischemic stroke (AIS).

Methods

A total of 403 hospitalized patients with AIS in the Stroke Center of the First Hospital Affiliated to Soochow University were enrolled from March 2018 to January 2021. The association between NT-proBNP and clinical outcomes in acute ischemic patients was assessed by logistic regression and adjusted for confounding factors. Also, subgroup analyses were conducted based on treatment decisions.

Results

NT-proBNP was positively correlated with CTP ischemic volume (p < 0.001), infarct core volume (p < 0.001), and ischemic penumbra volume (p < 0.001). Univariate analysis showed that the influence of NT-proBNP and functional outcomes were statistically significant in model 1 (p = 0.002). This phenomenon was persistent after adjusted for age, sex, and body mass index in model 2 (p = 0.011), adjusted for SBP, current smoking, family history of stroke, hypertension, and diabetes mellitus in model 3 (p < 0.001), and adjusted for TnI, D-dimer, PLT, Cr, TC, TG, HDL-C, treatment decisions, and NIHSS score in model 4 (p = 0.027). A high NT-proBNP was associated with a high 90-days mRS score among the total population, IV rt-PA, and standardized treatment groups, but not in IV rt-PA + EVT, EVT, and EVT/IV rt-PA + EVT groups.

Conclusion

Elevated NT-proBNP levels reveal large CTP infarct core volume and poor 90-day functional outcome in AIS. NT-pro BNP is an independent risk factor for functional outcomes.

The Combination Clinical Value of Plasma Brain Natriuretic Peptide and Serum HbAlc in the Diagnosis of Chronic Pulmonary Heart Disease

Objective. To analyze the combination clinical value of plasma brain natriuretic peptide and serum glycated hemoglobin (HbAlc) in chronic pulmonary heart disease. Methods. A total of 200 patients with chronic pulmonary heart disease admitted to our hospital from January 2021 to January 2022 were selected as the observation group, and 200 healthy subjects were selected as the control group during the same period. All subjects were examined by an ECG vector map and plasma BNP, and HbAlc levels were detected to analyze the value and clinical significance of each index in single diagnosis and combined diagnosis. Results. Plasma BNP and HbAlc levels in the observation group were significantly higher than those in the control group ( $P<0.05$ ). There were 154 BNP positive, 146 HbAlc positive, 164 parallel combined diagnosis positive, and 132 serial combined diagnosis positive. Sensitivity of series combination diagnosis was significantly higher than other indexes ( $P<0.05$ ); especially, parallel combination diagnosis was significantly higher than other indexes ( $P<0.05$ ). Besides, area under the ROC curve of parallel combination diagnosis and series combination diagnosis was significantly higher than that of each index alone diagnosis ( $P<0.05$ ). Conclusion. In the diagnosis of chronic pulmonary heart disease, the combination of plasma BNP and HbAlc can effectively improve the diagnostic specificity and sensitivity, as well as improve the area under the ROC curve.

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.