Key findings
This meta-analysis supports the validity of the relative variation of BNP (DBNP%) during a SBT as an incremental test after clinical indices to inform the likelihood of successful liberation from MV in adults. This meta-analysis also demonstrated high accuracy using a pooled AUROC of DBNP% for studies that excluded SBT failure from the liberation failure analysis. Combining absolute and relative variation irrespective of inclusion or exclusion of SBT failure in the liberation failure analysis showed high sensitivity and specificity for predicting successful liberation. The data from DBNP, BNP-pre and BNP-post were currently insufficient to support their additive use in clinical practice.
These are important findings given the limited predictive ability of clinical indices of SBT, which are considered the best available assessment. In studies, SBT misclassified patients in 10-20% of cases(14,23). While reinsertion of the endotracheal tube was mostly without immediate difficulty, there was greater risk of morbidity and mortality arising from a failed attempt at liberation from MV(1). More accurate alternative tests, such as BNP, may lead to decreased failure of initial attempts, and improved patient outcomes. This possibility has been recognized as early as 2008 in two methods of analysis: as an incremental test to clinical indices during SBT(3), or as an alternate test(24). These two approaches are well represented in the studies in this meta-analysis. The first subset of studies (n=8) included SBT failure in the analysis of the liberation failure group; this in effect assesses BNP as an alternative test to clinical indices SBT. This method has a potential decreased accuracy as compared to excluding those patients that failed the SBT from the analysis, and who may have a higher chance of successful liberation. The second subset of studies (n=9) excluded SBT failure from the analysis of the liberation failure group: this in effect assesses BNP as an incremental test to clinical indices of SBT. The major benefit in this case is the potential reclassification of patients for whom liberation may have been attempted, but may have failed. This distinction is important to determine the optimal use of BNP in assessment for liberation of mechanical ventilation. In our view, the two ways in which SBT failure is incorporated in the analysis should ideally be pooled and analysed separately. However; we expected limited data and pooled them for further analysis as planned in the protocol. Similarly, the different types of BNP measures (DBNP, DeltaBNP%, BNP-pre and BNP-post) should not be pooled, as some address a variation while others address a point value at a specific time. The only exception in which BNP measures could be pooled would be be DBNP and DBNP% given the possibility that baseline BNP level may not be relevant in the case of variation during a SBT. The studies that can be pooled together are thus extremely limited.
Most of the data that could be pooled related to variation of BNP during SBT (DBNP and DBNP%). The analysis described represent the extent of what could be analyzed rigorously. In order to increase the breadth of our analyses, we pooled DBNP and DBNP% for studies that excluded SBT failure from the analysis of the liberation failure group. The Moses-Littenberg summary ROC analysis showed high accuracy in this case. This summary ROC analysis was mostly driven by DBNP% (3 out of 4 studies, 148 out of 178 patients). The AUROC of DBNP% for studies that excluded SBT failure from the analysis of the liberation failure group supports the initial findings and provides numerical evidence of high accuracy (0.92 [0.88-0.97], I2 0%). This represents the most robust combination of measure and method of analysis obtained from the data.
Unfortunately, the data was insufficient to perform sensitivity and specificity estimates for this specific combination of measure and method of analysis. The closest approximation could be obtained by a bi-variate analysis using pooled data of DBNP and DBNP%, regardless of inclusion or exclusion of the SBT failure group from the liberation failure analysis. The sensitivity and specificity obtained were high [0.889 (0.831-0.929) and 0.828 (0.730-0.896), respectively]. It is important to note that these results were mostly driven by SBT failure exclusion groups (4 out of 5 studies; 248 out of 278 patients), and DBNP% (4 out of 5 studies; 178 out of 278 patients). This closely approximates the prior analysis performed on DBNP% for studies that excluded SBT failure from the analysis. We of course acknowledge that these are not the exact test characteristics for this specific measure and methods of analysis.
There were insufficient studies to analyse DBNP, BNP-pre and BNP-post separately as an incremental test (i.e., excluding SBT failure from the liberation failure analysis) or an alternate test (i.e., including SBT failure from the liberation failure analysis). Pooling studies of both methods of analysis for each BNP measure appears to support a high accuracy in these cases. The obvious limitation is the inability to determine if it is of better use as an incremental or alternate test. Additionally, for BNP-pre and BNP-post, the studies were not reported as strongly positive as DBNP and DBNP%. Furthermore, it is difficult to determine a superior measure or method, as only two studies compared measurements head-to-head. Both Cheng et al(25) and Martini et al(26) compared DBNP and DBNP%, and both studies suggest DBNP% is superior. No other inferences can be made on this point.
From a clinical standpoint, using these measures requires using a specific threshold for dichotomization between likelihood of liberation success versus failure (Table 1). This was determined this through ROC curve analysis of best sensitivity, specificity, positive and negative predictive values and diagnostic accuracy. No pre-specified threshold was studied prospectively in any study. Studies of DBNP% had the most data with a threshold above 13.4-20% (n=4) predicting liberation failure, if both BNP types (BNP and NT-ProBNP) were pooled. The other BNP measures had 3 or less studies for each BNP type and measure combination (Table 1). Unfortunately, a specific threshold for the BNP measure to discriminate liberation failure from success could not be meta-analysed.
In balance, the analyses performed suggest that BNP performs best if used as a relative BNP variation on a group of patients who have successfully passed a SBT by clinical criteria in adults. The other measures were likely useful, but the data does not allow determination of the best method by which to use them, and they thus cannot be recommended. There is a pauciy data in pediatric cases that limits any conclusion.
Limitations
As described above, the heterogeneity of BNP measurements and approaches for analysis limited our ability to perform pooled analysis; we thus pooled to be able to perform some analyses, acknowledging that this may decrease the reliability and applicability of our results. As we were limited by the data provided, we were unable to stratify by etiology of ICU admission. We opted to combine both general ICU populations and specific ICU subgroups to capture enough data to perform the AUROC analyses. The bi-variate analysis and Moses-Littenberg analyses were unaffected by this choice as all studies included were of a mixed ICU population. We believe that this makes our results more applicable to a general ICU practice. We however cannot reasonably comment on applicability for specific ICU subgroups as each population was represented by a single study.
There are several confounders to the accuracy of BNP testing. Heart disease (and specifically depressed left ventricular ejection fraction) and renal failure can significantly alter BNP kinetics. Unfortunately, these patient characteristics were inconsistently included or excluded across studies. In the case of renal failure, the distinction between acute and chronic renal failure was also poor. In balance, renal function was normal in most studies, and at most mildly impaired in the rest. As for heart disease, the definitions were variable. The etiology of respiratory failure has an impact on the accuracy of BNP: delirium, traumatic brain injury, inability to clear secretions or stridor, amongst others, limit the accuracy of BNP as they may not lead to a change in BNP measurements. A low number of studies that were included in this review attempted to limit this impact by excluding stridor and TBI from the analysis. Unfortunately, capturing clearance of secretions or delirium as the cause of respiratory failure is understanbly difficult and was not done in any study. Another limitation is the lack of studies that directly compared the accuracy of a successful SBT by clinical indices and by BNP measure. In this instance, a patient that has passed a SBT by clinical indices may fail by BNP measure, leading to a delay in extubating a patient that would have succeded. Unfortunately, the relative accuracies were not directly assessed in any study.
Finally, the quality of studies (as defined by QUADAS-2) uniformally ranked as at risk of bias, except for one(27). The main issue was lack of transparency regarding blinding of physicians to the BNP test. In our opinion, this is not a critical flaw, as the decision to extubate patients was most often based on clinical SBT criteria in all studies.
Implications for Clinical, Policy and Research
Research on mechanical ventilation liberation is complex and would benefit from greater standardization. Successful liberation from mechanical ventilation appears well-defined and this is reflected in the studies collected. Liberation failure, on the other hand, has a variable definition amongst studies, mostly relating to the inclusion or exclusion of SBT failure. Regardless of its importance for applicability of alternative or incremental testing, the terms used require standardization to facilitate research.
Additional data is needed tostrengthen BNP as a liberation tool. We consider that this should take the form of a comparative study of BNP as an alternative or an incremental tool to the clinical indices after an SBT. This study would ideally take the form of an assessment of DBNP and DBNP%, and compare inclusion versus exclusion of SBT in the analyzed subgroups. This would allow determination of whether BNP is superior to SBT on its own or simply incremental.
The potential benefits of improved tools to inform greater likelihood of success or failure of liberation from MV have far-reaching implications. On top of reclassifying individuals after initial assessment with clinical indices, this may allow stratification of the risk of failure. Such a stratification may help better determine targets for optimization (such as further volume de-escalation), better identification of the need for post-extubation therapies (such as high-flow oxygen therapy and BiPAP), and need for prolonged ICU observation. Clinical risk scores on this basis could be developed to aid in management of these patients after extubation.