Background
Invasive mechanical ventilation (IMV) is a life-saving procedure for patients with acute respiratory failure (ARF) [
1]. Approximately 10–20% of the patients who are extubated after a successful spontaneous breathing trial (SBT) require reintubation within 48–72 h [
2], which may be associated with prolonged mechanical ventilation, extended intensive care unit (ICU) and hospital stay, and increased mortality [
2,
3].
Various oxygenation therapies have been proposed to prevent reintubation in ARF due to several causes, including hypoxia, ventilatory insufficiency, and increased respiratory workload. Conventional oxygen therapy (COT) and noninvasive positive-pressure ventilation (NPPV) have been recommended as post-extubation respiratory support devices [
4‐
7]; recently, high-flow nasal cannula oxygenation (HFNC) has also been used as a prophylactic post-extubation respiratory support device to avoid reintubation [
8,
9].
NPPV has been reported to be effective in preventing reintubation after planned extubation in high-risk patients [
6,
7,
10,
11]. However, NPPV may increase the risk of complications, including aspiration pneumonia, interface intolerance, and patient discomfort [
12,
13]. HFNC can minimize the complications of NPPV by delivering high concentrations of humidified oxygen via a nasal cannula. However, contradictory results have been reported despite the large number of clinical trials [
14,
15].
Some systematic reviews and meta-analyses which compared two of the three respiratory support devices (COT, NPPV, and HFNC) [
16‐
20] have shown that in terms of reducing the rate of tracheal reintubation, HFNC was better than COT but equivalent to NPPV. Moreover, there were no significant differences between the therapies in terms of mortality rates. Although several studies have compared HFNC and NPPV with COT, few large-scale studies have compared HFNC with NPPV. Therefore, small sample sizes may have affected the results of systematic reviews.
Therefore, we performed a systematic review and network meta-analysis (NMA) to compare the effectiveness of three respiratory support devices in reducing mortality and reintubation rates by including studies that compared two of the three respiratory support devices (COT, NPPV, and HFNC) in patients who were intubated for ARF after scheduled extubation.
Methods
Protocol and registration
This systematic review was designed in accordance with the Preferred Reporting Items for Systematic review and Meta-Analyses (PRISMA) extension statements for reporting systematic reviews that incorporate NMA (Additional file
1: Table S1) [
21]. The review protocol was registered with PROSPERO (CRD42020139112).
Studies, participants, interventions/comparators, and outcomes
We included all reports of randomized controlled trials (RCTs) in English and Japanese regardless of publication status (e.g., published, unpublished, and academic abstracts). Randomized crossover, cluster randomized, and quasi-experiment trials were excluded. This meta-analysis included reviews of adult patients (age ≥ 16 years) who underwent IMV for more than 12 h due to ARF and were scheduled for extubation after a SBT. The definitions of acute hypoxic respiratory failure and SBT were individualized for each study. This meta-analysis excluded studies that included patients who underwent tracheostomies, experienced accidental extubation or self-extubation, those who experienced hypercapnia during SBT, and those who had do-not-resuscitate (DNR) orders. Studies in which more than half of the study population had acute chronic obstructive pulmonary disease (COPD) exacerbation, those that included patients with a postoperative status or who were being treated for trauma, and those that included patients with congestive heart failure were also excluded. We included RCTs that compared two of the three available respiratory support devices: (1) COT: low-flow nasal cannula, face mask, and venturi mask (no flow rate restriction); (2) NPPV: the type of mask, mode, duration of ventilation, and weaning methods were not limited; and (3) HFNC: no limitations on the flow rate or FIO2. The outcome measures evaluated were as follows: the primary outcome was the short-term mortality rate ([1] at the end of the follow-up period for each trial within 30 days, [2] at ICU discharge, and [3] at hospital discharge). Secondary outcomes included the reintubation rate within 72 h (reintubation included the need for intubation and NPPV) and post-extubation respiratory failure rate (the definition was individualized for each study).
Data sources and search details
We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE via PubMed, EMBASE, and Ichushi, a database of Japanese papers for eligible trials. We searched for ongoing trials in the World Health Organization International Clinical Trials Platform Search Portal. In cases of missing data, we attempted to contact the authors of each study. Searches were performed in December 2020. Details regarding search strategy and when the searches were performed are shown in Additional file
1: Table S2.
Study selection, data collection process, and data items
Two of the three physicians (YO, CN, and HY) screened the title, abstract, and full text during the first and second screenings for relevant studies and independently extracted data from eligible studies into standardized data forms. For abstract-only studies that could not be evaluated according to the eligibility criteria, we contacted the authors. Disagreements, if any, between two reviewers were resolved via discussion among themselves or with a third reviewer as necessary. Data extraction from identified studies during the second screening was also performed by two of the three physicians (YO, CN, and HY) using two tools: (1) the Cochrane Data Collection Form (RCTs only) [
22] and (2) Review Manager (RevMan) software V.5.3.5 [
23]. Disagreements, if any, were resolved in the same manner as for the screening process.
Risk of bias within individual studies
The risk of bias for primary outcomes was independently assessed by two of the three physicians (YO, CN, and HY) using the Cochrane Risk of Bias tool 1.0 [
24,
25]. Each bias was graded as “low risk,” “unclear risk,” or “high-risk.” Discrepancies between reviewers were resolved by mutual discussion.
Statistical analyses
A pairwise meta-analysis was performed by using RevMan 5.3 (RevMan 2014). Forest plots were used for the meta-analysis, and effect sizes are expressed as relative risk (RR) and weighted mean differences, both with 95% confidence intervals (CI), for categorical and continuous data, respectively. Outcome measures were pooled using a random-effect model to include study-specific effects in measures. A two-sided p value < 0.05 was considered significant.
Study heterogeneity between trials for each outcome was assessed by visual inspection of forest plots and with an
I2 statistic for quantifying inconsistency [
26] (RevMan;
I2: 0–40%, 30–60%, 50–90%, and 75–100% as minimal, moderate, substantial, and considerable heterogeneity, respectively). When heterogeneity was identified (
I2 > 50%), we investigated the reason and quantified it using the Chi-square test (
p value).
We planned to use a funnel plot, Begg’s adjusted rank correlation test, and Egger’s regression asymmetry test for the possibility of publication bias, if ≥ 10 studies were available (RevMan) [
27]. However, as < 10 studies were included for each outcome, we did not test for funnel plot asymmetry.
Data synthesis
A network plot was constructed to determine the number of studies and patients included in this meta-analysis. An NMA, using the netmeta 0.9–5 R-package (version 3.5.1), was performed using a frequentist-based approach with multivariate random-effect meta-analysis, and effect size was expressed as the RR (95% CI). Covariance between two estimates from the same study shows variance of data in the shared arm, as calculated in a multivariable meta-analysis performed using the GRADE Working Group Approach for an NMA.
Transitivity
The transitivity assumption underlying the NMA was evaluated by comparing the distribution of clinical and methodological variables that could act as effect modifiers across treatment comparisons.
Ranking
Ranking plots (rankograms) were constructed using the probability that a given treatment had the highest event rate for each outcome. The surface under the cumulative ranking curve (SUCRA), which is a simple transformation of the mean rank, was used to set the hierarchy of the treatments [
28] and was created using standard software (Stata 15.0, Stata, TX, USA).
Risk of bias across studies
Assessment of the risk of bias across studies followed considerations on pairwise meta-analysis. Conditions associated with “suspected” and “undetected” bias across studies were determined by the presence of publication bias as shown by direct comparison.
Indirectness
The indirectness of each study included in the network was evaluated according to its relevance to the research question, which consisted of the study population, interventions, outcomes, and study setting, and was classified as low, moderate, or high. Study-level judgments could be combined with the percentage contribution matrix.
Imprecision
The approach to imprecision comprised a comparison of the range of treatment effects included in the 95% CI with the range of equivalence. We assessed the heterogeneity of treatment effects for a clinically important risk ratio (< 0.8 or > 1.25) in CI.
Heterogeneity
To assess the amount of heterogeneity, we compared the posterior distribution of the estimated heterogeneity variance with its predictive distribution [
29]. The concordance between assessments based on CI and prediction intervals, which do and do not capture heterogeneity, respectively, was used to assess the importance of heterogeneity. We assessed the heterogeneity of treatment effects for a clinically important risk ratio of < 0.8 or > 1.25 in prediction intervals.
Assessment of inconsistency
The inconsistency of the network model was estimated from inconsistency factors and their uncertainty, and consistency was statistically evaluated using the design-by-treatment interaction test [
30]. For comparisons informed only by direct evidence, there was no disagreement between evidence sources, and thus, there was “no concern” for incoherence. If only indirect evidence was included, there was always “some concern.” “Major concern” was considered when the
p value of the design-by-treatment interaction test was < 0.01.
Discussion
In our NMA, there were no between-group differences in short-term mortality (groups: NPPV, HFNC, and COT). NPPV/HFNC use did not significantly lower the mortality risk compared to COT use. The SUCRA value of short-term mortality for HFNC was better than those for NPPV and COT. However, as a secondary outcome, the use of HFNC significantly lowered the reintubation risk relative to COT use but not NPPV use. In addition, the SUCRA values of the reintubation rate and post-extubation respiratory failure for HFNC, NPPV, and COT use showed that HFNC use was superior to NPPV and COT use.
When HFNC was compared to COT, differences in outcomes between previous pairwise systematic reviews and this NMA-based study were observed. A systematic review by Ni and colleagues showed that HFNC is associated with a lower reintubation rate than COT, despite no reduction in mortality rate [
16], which is identical to our study. Although a systematic review by Zhu et al. revealed that HFNC contributed to a reduction in post-extubation respiratory failure compared to that observed with COT, reductions in reintubation and mortality rates were not apparent [
17]. In the study by Zhu et al. and our NMA, the effect of HFNC differed in terms of the reintubation rate; however, this difference is likely attributable to the eligibility of included patients. We excluded RCTs that included > 50% of postoperative patients, whereas the study by Zhu et al. included all RCTs with postoperative patients (three RCTs;
n = 715) [
43]. In postoperative abdominal surgery patients, diaphragmatic dysfunction and decreased lung vital capacity can cause atelectasis, resulting in hypoxemic respiratory failure [
44]. Including patients with such different mechanisms of respiratory failure may increase patient heterogeneity and result in different outcomes compared to those observed with HFNC use and COT.
Herein, NPPV contributed to a reduction in the reintubation rate compared to that observed with COT, without reducing mortality, which is consistent with several previous pairwise systematic reviews comparing NPPV and COT use. Previous RCTs show that NPPV is more effective in reducing reintubation and mortality rates than COT in a high-risk group of patients with post-extubation respiratory failure, including COPD [
7,
45,
46]. However, Kondo et al. showed that NPPV decreased reintubation and mortality rates more effectively than COT despite the complete exclusion of patients with COPD from the study [
47]. In our study, we excluded studies in which patients with COPD constituted > 50% of the study population, as COPD is a risk factor for post-extubation respiratory failure [
48]. Thus, the abovementioned exclusion potentially caused a difference between the effectiveness of NPPV and COT in the systematic reviews included in the NMA.
Zhou et al. recently reported a systematic review using NMA that compared NPPV, HFNC, and COT in post-extubation patients [
49], but their inclusion criteria differ from ours. Zhou et al. included all studies with patients with COPD, whereas we excluded studies with > 50% COPD patients. Moreover, Zhou et al. showed that NPPV was associated with reductions in mortality and post-extubation respiratory failure rates compared to COT. COPD is a risk factor for reintubation after extubation and predisposes patients to hypercapnia during SBT [
46]. Thus, NPPV is more effective than COT for patients with hypercapnia after extubation [
50], which possibly led to differences in results between our study and that of Zhou et al. Furthermore, including trials with many patients with COPD potentially increased the patient heterogeneity. Therefore, we excluded trials where COPD patients accounted for > 50% of the study population. This study utilized a four-step approach for assessing the certainty of the NMA estimate developed by the GRADE Working Group [
51], whereas the study by Zhou et al. did not conduct a similar assessment. A systematic approach using the GRADE system is necessary for evaluating the quality of the evidence to assess whether the evidence is convincing or of low quality, thereby guiding subsequent decision making.
Implications
The results of our systematic review are useful for selecting an appropriate noninvasive oxygenation strategy for post-extubation patients because the use of NPPV or HFNC will prevent reintubation in a greater proportion of patients (66–69 patients per 1000) than the use of COT. Early weaning from IMV improves patient mortality, whereas reintubation significantly increases mortality risk [
3]. Therefore, it is important to choose an appropriate strategy to prevent reintubation after extubation. Both NPPV and HFNC are associated with a lower reintubation rate than COT; therefore, physicians can choose a strategy according to the patient’s respiratory physiology status and preference.
Limitations
Our systematic review using NMA has several limitations. First, we combined studies that included patients with different etiological conditions necessitating intubation, which may have increased the heterogeneity of the studies. Despite excluding RCTs with > 50% of patients with postoperative intubation and COPD, the inclusion of a fixed number of postoperative and COPD patients may have influenced the results. Second, we combined studies with different degrees of respiratory failure during the extubation of patients. The effect of NPPV and HFNC may differ depending on illness severity, and differences in severity may be an effect modifier. This NMA included other RCTs, with different characteristics, such as duration of intubation, risk factors for reintubation after extubation, and methods of SBT, which may also be effect modifiers. Third, because only one RCT directly compared NPPV and HFNC, there may not have been a significant difference due to insufficient sample size; there were no significant differences in mortality or post-extubation respiratory failure rates, but this may have been different if the sample size was larger. There was incoherence between direct and indirect estimation in the pairwise comparison of NPPV and HFNC, which led to a grading down of network estimation due to the lack of RCTs that directly compared NPPV and HFNC.
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