Non-invasive Oxygenation Strategies for Reducing the Incidence of Pneumonia in Adult Patients with Acute Hypoxemic Respiratory Failure: A Systematic Review and Network Meta-analysis

doi:10.21203/rs.3.rs-5069185/v1

Background: In the current guidelines, the usage of non-invasive oxygenation strategies, such as non-invasive positive pressure ventilation (NPPV) and high-flow nasal oxygen (HFNO), for acute hypoxemic respiratory failure (AHRF) are unable to provide conclusive recommendations. We aimed to identify the most optimum respiratory management strategy reducing pneumonia in patients with AHRF.

Methods: We searched the four databases for eligible trials. Studies including adults with AHRF and randomized controlled trials comparing two different respiratory management methods (NPPV, HFNO, standard oxygen therapy [SOT], or invasive mechanical ventilation [IMV]) were reviewed. The primary outcome was the incidence of pneumonia. A network meta-analysis was performed a frequentist approach with a multivariate random-effects meta-analysis.

Results: We identified 14,263 unique articles, reviewed 126 full-text articles, and finally included 13 studies. Using IMV as the reference, NPPV (risk ratio [RR], 0.23; 95% confidence interval [CI], 0.11–0.51; moderate certainty) and HFNO (RR, 0.24; 95% CI, 0.09–0.64; moderate certainty) were significantly associated with a lower incidence of pneumonia. Compared with SOT, NPPV (RR, 0.55; 95% CI, 0.35–0.84; moderate certainty) but not HFNO (RR, 0.55; 95% CI 0.27–1.13; low certainty) was significantly associated with a lower incidence of pneumonia. The probability of being the best in reducing the incidence of pneumonia among all interventions was higher for NPPV and HFNO, followed by SOT, whereas IMV was the worst.

Conclusions: Our findings imply that NPPV and HFNO may be the most effective strategies for primary respiratory management in adults with AHRF to reduce pneumonia.

Pulmonology

acute hypoxemic respiratory failure

invasive mechanical ventilation

non-invasive positive pressure ventilation

high-flow nasal oxygen

pneumonia

network meta-analysis

ventilator-associated pneumonia

Acute hypoxemic respiratory failure (AHRF) is frequently found in critically ill patients and associated with high in-hospital mortality [1]. To reduce the complications associated with invasive mechanical ventilation (IMV), non-invasive oxygenation strategies, such as non-invasive positive pressure ventilation (NPPV) and high-flow nasal oxygen (HFNO), have been widely investigated in patients with AHRF. NPPV is recommended in patients with cardiogenic pulmonary edema [2] but not in patients with de novo AHRF [3], which includes acute respiratory distress syndrome (ARDS) and pneumonia as major causes. In a previous large observational study, the usage of NPPV for patients with severe ARDS may be associated with higher intensive care unit mortality [4]. On the other hand, although HFNO is preferred to manage patients with AHRF [5], the efficacy of HFNO has not been consistent among patients with de novo AHRF [6, 7]. Further research is required to understand the relative benefits and risks of each strategy.

A network meta-analysis (NMA) was recently conducted to compare the effectiveness of initial respiratory support in adult patients with de novo AHRF [8]. This NMA revealed that non-invasive oxygenation strategies were associated with a lower risk of death compared with standard oxygen therapy (SOT). However, no such comparisons were made between IMV and non-invasive oxygenation strategies. Additionally, the risk of adverse events associated with each treatment strategy was unclear in the NMA.

In this study, we aimed to identify the most optimum respiratory management strategy reducing pneumonia in patients with AHRF. We conducted an NMA to evaluate the associations of different respiratory management strategies (NPPV, HFNO, SOT, and IMV) with the incidence of pneumonia in adult patients with AHRF.

Protocol and registration

This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) extension statement for reviews incorporating network meta-analyses [9]. The protocol has been registered in protocols.io (Protocol integer ID 49629) [10].

Inclusion criteria

We included randomized controlled trials (RCTs) reported in English and Japanese, comparing two of the following four strategies: SOT (nasal cannula, facemask, and venturi mask with limitless flow rate), NPPV (mask type, ventilation mode, and methods of weaning were not limited), HFNO (flow rate and fraction of inspired oxygen were not limited), and IMV (mechanical ventilation via endotracheal intubation, not tracheostomy).

This review included adults (age ≥ 18 years) with AHRF, defined by any of the following criteria: new onset (< 7 days) of clinical signs (e.g., tachypnea), radiological signs (e.g. chest X-ray opacities), and hypoxemia. Hypoxemia was defined as the ratio of arterial oxygen partial pressure to fractional inspired oxygen below 300, arterial or percutaneous oxygen saturation < 94% in room air, PaO₂ < 60 mmHg in room air, or < 80 mmHg with oxygen.

The primary outcome was the incidence rate of pneumonia (ventilator-associated pneumonia (VAP), aspiration pneumonia, and nosocomial pneumonia were not limited). The secondary outcome was the incidence rate of VAP (VAP was defined in each study).

Exclusion criteria

Randomized crossover, cluster-randomized, or quasi-experimental trials were excluded. The current meta-analysis excluded studies in which more than half of the patients had congestive heart failure, acute exacerbation of chronic obstructive pulmonary disease (COPD), asthma attack, hypercapnia (PaCO₂ > 50 mmHg), respiratory failure due to post-extubation or trauma, post-surgical status, or do-not-resuscitate orders. We also excluded the studies which had limited intervention in the emergency department or pre-hospital care.

Search strategy

Databases used for the search of eligible trials were The Cochrane Central Register of Controlled Trials, MEDLINE via PubMed, EMBASE, and Ichushi, a database of Japanese research papers. Because this systematic review was planned for ARDS clinical practice guidelines 2021 in Japan [11], we also included studies on clinical questions about non-invasive oxygenation strategies in the guideline, using manual search. A literature search was performed on May 30, 2021. The terms used for database search showed in Appendices.

Study selection and data extraction

At the first screening, two of the five reviewers (HO, TM, SH, SK, and MS) screened the title and abstract. At the second screening, the full text for relevant studies was analysed and data were independently extracted from the included studies into standardized data forms. Disagreements were resolved by discussing with one of the three reviewers not involved in screening the studies. We also asked the original authors for additional details when necessary. After identifying studies in the second screening, we extracted the following study characteristics: methods, participants, interventions, and outcomes.

Network geometry

Network diagrams were constructed using the Confidence In Network Meta-Analysis (CINeMA) web application [12], to show the number of studies and patients included in the meta-analysis. We represented network geometry that treatments by nodes and head-to-head comparisons by lines connecting these nodes. The size of the node is proportional to the number of patients, while the thickness of the lines is proportional to the number of studies evaluating each treatment.

Quality assessment

The risk of bias of outcomes in the eligible studies was independently assessed by two of the five authors using the Cochrane Risk of Bias tool 2.0 [13] for the following seven domains: (a) random sequence generation, (b) allocation concealment, (c) blinding of participants and personnel, (d) blinding of outcome assessors, (e) incomplete outcome data, (f) selective outcome reporting, and (g) other sources of bias. Each domain of bias was graded as either “low risk,” “unclear risk,” or “high risk.” If there was a discrepancy between the two reviewers, an agreement was reached through discussion. Discrepancy checks were resolved by discussion with a third reviewer, as necessary. Each domain was evaluated in three categories: high risk, low risk, and some concerns.

Methods of direct comparison meta-analysis

A pairwise meta-analysis was performed using Review Manager version 5.3 [14]. Forest plots were used for meta-analysis, and the effect size was expressed as a risk ratio (RR) with 95% confidence interval (CI) for categorical data. Outcome measures were pooled using a random-effects model to analyse study-specific effects in the measures. A two-sided p-value < 0.05 was considered statistically significant for all analyses.

Methods of network comparison meta-analysis

An NMA was performed using a frequentist-based approach with multivariate random-effects meta-analysis, and the effect size was expressed as the RR (95% CI) using the CINeMA web application [12]. CINeMA is based on the framework that was developed by Salanti et al. [15] and modified by Nikolakopoulou et al. [16]. Six domains that influence the level of confidence of NMA results are: (a) within-study bias, (b) reporting bias, (c) indirectness, (d) imprecision, (e) heterogeneity, and (f) incoherence. The covariance between two estimates from the same study indicated the variance of data in the shared arm, as calculated in a multivariable meta-analysis performed for an NMA [17]. Transitivity was assessed in the incoherence domain using CINeMA. We constructed forest plots of the RR with 95% CI for each treatment strategy in the network.

Ranking plots (rankograms) were constructed based on 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 determine the treatment hierarchy. We calculated values of the SUCRA statistic using the mvmeta command in Stata 15.1 (StataCorp LLC, College Station, TX, USA) [18]. SUCRA is a percentage that shows how much effectiveness a treatment archives in comparison with a theoretical treatment that is always the best. The larger the SUCRA value, the better the rank of the treatment [19].

Assessments of the certainty of evidence

We evaluated the indirectness, classified as “no”, “some”, or “major” concern, of each study included in the NMA based on its relevance to the research question. The study-level judgments can be combined with a percentage contribution matrix. The approach to imprecision involved comparing 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 of < 0.8 or > 1.25 in prediction interval. Study heterogeneity among trials for each outcome was assessed by visually inspecting forest plots and with an I² statistic to quantify inconsistency [20]. Publication bias was visually assessed using a funnel plot [19]. The global inconsistency test with a fitting design-by-treatment model was used to identify the disagreement between the direct and indirect estimates as a measure of inconsistency [21]. The studies were categorized based on the p-value of the global design-by-treatment interaction test: “major concerns” (< 0.05), “some concerns” (0.05–0.10), and “no concerns” (> 0.10). Studies were also categorized as showing “major concerns” if the design-by-treatment interaction test statistic could not be computed due to the absence of closed loops in the network. The network estimate was rated considering the risk of bias, indirectness, imprecision, heterogeneity, publication bias, and inconsistency [22].

The search strategy identified 14,263 records. Based on the study selection process, 13 studies (1,254 participants; range, 40–310 participants) [7, 23–34] were included in this NMA (Fig. 1).

The included trials evaluated four different interventions. These included four out of six potential head-to-head comparisons for all types of pneumonia and three out of six potential head-to-head comparisons for VAP. Specifically, nine trials compared NPPV with SOT [7, 24–30, 32], one trial compared HFNO with SOT [7], three trials compared NPPV with IMV [23, 31, 33], and two trials compared NPPV with HFNO [7, 34]. No studies compared HFNO with IMV (Fig. 2).

Study characteristics and risk of bias assessment

The characteristics of each study included in the final meta-analysis dataset are summarized in Table 1. Three trials (23.1%) included immunocompromised patients [27, 29, 30]. Community-acquired pneumonia was the most common cause of AHRF in seven trials (53.8%) [7, 24, 26–28, 31, 32]. Table 2 shows the data for the risk of bias; all studies were judged to have major biased concerns for outcomes and high overall risk of bias.

Table 1

Summary of characteristics of the studies included in the network meta-analysis.
Source	Funding	Total No. of patients	Main reason for hypoxemic respiratory failure (main baseline risk factor)	Age, y	P/F	RR, /min	PaCO₂, mmHg	Main exposure	interface, NIV mode	Comparator	Outcomes of interest assessed
Antolnelli et al., 1998 [23].	Undisclosed	64	Mixed ARF (CPO 19%, atelectasis 25%)	54	120	39	40	noninvasive ventilation (N = 32)	face mask, pressure support	Invasive ventilation, tidal volume 10 ml/kg (N = 32)	Hospital mortality
Confalonieri et al., 1999 [24].	Undisclosed	56	CAP	64	175	37	49	noninvasive ventilation (N = 28)	face mask, pressure support	standard oxygen (N = 28)	2-month mortality, intubation
Antonelli et al., 2000 [25].	Undisclosed	40	Mixed ARF (ARDS 37.5%, atelectasis 25%)	67	NA	NA	40	noninvasive ventilation (N = 20)	face mask, pressure support	standard oxygen (N = 20)	Hospital mortality, intubation
Delcaux et al., 2000 [26].	Vital Signs Inc	123	Mixed ARF (CAP 54.5%)	58^a	144^a	33	36 ^a	noninvasive ventilation (N = 62)	face mask, CPAP	standard oxygen (N = 61)	Hospital mortality, intubation
Hilbert et al., 2001 [27].	Undisclosed	52	CAP in immunocompromised patients	49	139	36	38	noninvasive ventilation (N = 26)	face mask, pressure support	standard oxygen (N = 26)	Hospital mortality, intubation
Ferrer et al., 2003 [28].	Red GIRA, Red Respira, and Carburos Metalicos SA	105	Mixed ARF (CAP 32.4%, CPE 28.6%)	62	103	37	37	noninvasive ventilation (N = 51)	face mask, pressure support	standard oxygen (N = 54)	ICU mortality, intubation
Squadrone et al., 2010 [29].	Regione Piemonte (CEP AN RAN 07) and Ministero dell’Università (PRIN RANI 07)	40	Mixed ARF in immunocompromised patients	49	269	30	36	noninvasive ventilation (N = 20)	helmet, CPAP	standard oxygen (N = 20)	Hospital mortality, intubation
Zhan et al., 2012 [30].	Beijing Municipal Science and Technology Commission Program	40	ALI (immunocompromised 30%)	46	230	20	32	noninvasive ventilation (N = 21)	face mask, pressure support	standard oxygen (N = 19)	Hospital mortality, intubation
Frat et al., 2015 [7].	French Ministry of Health	310	Mixed ARF (CAP 63.5%)	60	155	33	35	noninvasive ventilation (N = 110)	face mask, pressure support	high-flow nasal oxygen (N = 106); standard oxygen (N = 94)	90-day mortality, intubation
Muncharaz et al., 2017 [31].	Undisclosed	65	Mixed ARF (CAP 63.1%)	62 ^a	97	36	44	noninvasive ventilation (N = 34)	face mask, pressure support	invasive ventilation, tidal volume 8–10 ml/kg (PBW), Ppl < 35 (N = 31)	Hospital mortality
He et al., 2019 [32].	National Natural Science Foundation of China	200	CAP	55	231	25	34	noninvasive ventilation (N = 102)	face mask, pressure support	standard oxygen (N = 98)	Hospital mortality, intubation
Awadallah et al., 2021 [33].	None	52	ARDS (pulmonary ARDS 50%)	52	94.5	NA	33	noninvasive ventilation (N = 26)	face mask, pressure support	invasive ventilation, tidal volume 6-7ml/kg (PBW), Ppl < 30 (N = 26)	Hospital mortality
Grieco et al., 2021 [34].	2017 Merck Sharp & Dohme SRL award	107	ARF in COVID-19 patients	65 ^a	102 ^a	28 ^a	34 ^a	noninvasive ventilation (N = 54)	helmet, pressure support	high-flow nasal oxygen (N = 55)	60-day mortality, intubation

a. Age was reported as median.

Abbreviations: ALI, acute lung injury; ARDS, acute respiratory distress syndrome; ARF, acute respiratory failure; CAP, community-acquired pneumonia; CPAP, continuous positive airway pressure; CPO, cardiopulmonary oedema; COPD, chronic obstructive pulmonary disease; COVID-19, coronavirus disease 2019; ICU, intensive care unit; NA, not available; NIV, noninvasive ventilation; P/F ratio, ratio of arterial oxygen partial pressure to fractional inspired oxygen; PaCO₂, partial pressure of arterial carbon dioxide; Ppl, plateau pressure; PBW, predicted body weight; RR, respiratory rate.

Table 2

Summary of risk of bias of the studies included in the network meta-analysis. Pneumonia
Source	Bias arising from the randomization process	Bias due to deviations from intended interventions	Bias due to missing outcome data	Bias in measurement of the outcome	Bias in selection of the reported result	Overall risk of bias
a) Pneumonia
Antolnelli et al., 1998 [22].	Some concerns	Some concerns	Low	High	Low	High
Confalonieri et al., 1999 [23].	Low	Some concerns	Low	High	Low	High
Antonelli et al., 2000 [24].	Low	Some concerns	Low	High	Low	High
Delcaux et al., 2000 [25].	Low	Some concerns	Some concerns	High	Low	High
Hilbert et al., 2001 [26].	Low	Some concerns	Low	High	Low	High
Ferrer et al., 2003 [27].	Low	Some concerns	Low	High	Low	High
Squadrone et al., 2010 [28].	Low	Some concerns	Low	High	Low	High
Zhan et al., 2012 [29].	Low	Some concerns	Low	High	Low	High
Frat et al., 2015 [7].	Low	Some concerns	Low	High	Low	High
Muncharaz et al., 2017 [30].	Low	Some concerns	Low	High	Low	High
He et al., 2019 [31].	Low	Some concerns	Low	High	Low	High
Awadallah et al., 2021 [32].	Some concerns	Some concerns	Low	High	Low	High
Grieco et al., 2021 [33].	Low	Some concerns	Low	High	Low	High
b) Ventilator-associated pneumonia
Antolnelli et al., 1998 [22].	Some concerns	Some concerns	Low	High	Low	High
Confalonieri et al., 1999 [23].	Low	Some concerns	Low	High	Low	High
Antonelli et al., 2000 [24].	Low	Some concerns	Low	High	Low	High
Hilbert et al., 2001 [26].	Low	Some concerns	Low	High	Low	High
Zhan et al., 2012 [29].	Low	Some concerns	Low	High	Low	High
Muncharaz et al., 2017 [30].	Low	Some concerns	Low	High	Low	High
Awadallah et al., 2021 [32].	Some concerns	Some concerns	Low	High	Low	High
Grieco et al., 2021 [33].	Low	Some concerns	Low	High	Low	High

Risk of pneumonia

Thirteen trials (1,254 patients) were included in the risk of pneumonia analysis. We did not rate down due to publication bias (funnel plot shown in Figure 3). However, we rated down considering heterogeneity and/or imprecision in the comparisons of HFNO vs. SOT, IMV vs. SOT, and NPPV vs. HFNO (Table 3). We also rated down in all comparisons because of the very serious risk of bias.

Table 3

Summary of the network meta-analysis and network estimate rating of pneumonia and ventilator-associated pneumonia.
Comparison	Direct estimate (95% CI)	Indirect estimate (95% CI)	P value	Network estimate (95% CI)	Rating
NPPV vs SOT	0.57 (0.37–0.88)	0.12 (0.01–1.93)	0.233	0.55 (0.35–0.84)	⨁⨁⨁◯ Moderate ^{a), b)}
HFNO vs SOT	0.44 (0.13–1.53)	0.62 (0.26–1.48)	0.233	0.55 (0.27–1.13)	⨁⨁◯◯ Low ^{a), b), c)}
IMV vs SOT	NA	2.33 (0.96–5.61)	0.233	2.33 (0.96–5.61)	⨁⨁◯◯ Low ^{a), b), c)}
NPPV vs IMV	0.23 (0.11–0.51)	NA	0.233	0.23 (0.11–0.51)	⨁⨁⨁◯ Moderate ^a)
HFNO vs IMV	NA	0.24 (0.09–0.64)	0.233	0.24 (0.09–0.64)	⨁⨁⨁◯ Moderate ^a)
NPPV vs HFNO	1.03 (0.55–1.92)	0.28 (0.01–7.30)	0.233	0.98 (0.53–1.81)	⨁⨁◯◯ Low ^{a), d)}
a) Very serious risk of bias, b) Serious heterogeneity, c) Serious imprecision, d) Very serious imprecision.
CI, confidence interval; HFNO, high-flow nasal oxygenation; IMV, invasive mechanical ventilation; NA, not applicable; NPPV, non-invasive positive pressure ventilation; SOT, standard oxygen therapy

In the current NMA, using SOT as the reference, NPPV (RR, 0.55; 95% CI, 0.35–0.84; moderate certainty) was significantly associated with a lower risk of pneumonia, while HFNO (RR, 0.55; 95% CI, 0.27–1.13; low certainty) was not associated with a statistically significant lower risk of pneumonia (Figure 4). Compared with IMV, NPPV (RR, 0.23; 95% CI, 0.11–0.51; moderate certainty) and HFNO (RR, 0.24; 95% CI, 0.09–0.64; moderate certainty) were associated with a significantly lower risk of pneumonia (Figure 4). There were no significant differences in the additional comparisons.

The ranking analysis revealed the following hierarchy regarding efficacy in reducing pneumonia: NPPV (SUCRA 87.3), followed by HFNO (SUCRA 70.5) and SOT (SUCRA 41.8), and finally, IMV (SUCRA 0.4) (Table 4). In summary, the probability of being the best strategy of reducing pneumonia among all the possible interventions was highest for NPPV, followed by HFNO.

Table 4

Results of network rank test for pneumonia in the network meta-analysis.
	NPPV	HFNO	IMV	SOT
Best	65.3%	31.6%	0.0%	3.1%
2nd	31.3%	48.6%	0.1%	20.0%
3rd	3.4%	19.5%	0.9%	76.2%
Worst	0.0%	0.3%	99.0%	0.7%
Mean rank	1.4	1.9	4.0	2.7
SUCRA	87.3	70.5	0.4	41.8
HFNO, high-flow nasal oxygenation; IMV, invasive mechanical ventilation; NPPV, non-invasive positive pressure ventilation; SUCRA, surface under the cumulative ranking; SOT, standard oxygen therapy

Risk of ventilator-associated pneumonia

Eight trials (476 patients) were included in the risk of VAP analysis. We did not rate down due to publication bias (funnel plot shown in Figure 5). However, very serious heterogeneity and/or imprecision was observed in several comparisons (Table 5). A very serious risk of bias and incoherence was observed for all comparisons, resulting in a rating down.

Table 5

Summary of the network meta-analysis and network estimate rating of ventilator-associated pneumonia.
Comparison	Direct estimate (95%CI)	Indirect estimate (95%CI)	P value	Network estimate (95%CI)	Rating
NPPV vs SOT	0.37 (0.14–0.97)	NA	NA	0.37 (0.14–0.97)	⨁◯◯◯ Very Low ^{a), b), c)}
HFNO vs SOT	NA	0.46 (0.15–1.44)	NA	0.46 (0.15–1.44)	⨁◯◯◯ Very Low ^{a), c), d)}
IMV vs SOT	NA	1.58 (0.48–5.26)	NA	1.58 (0.48–5.26)	⨁◯◯◯ Very Low ^{a), c), d)}
NPPV vs IMV	0.23 (0.11–0.47)	NA	NA	0.23 (0.11–0.47)	⨁⨁◯◯ Low ^{a), c)}
HFNO vs IMV	NA	0.29 (0.12–0.73)	NA	0.29 (0.12–0.73)	⨁⨁◯◯ Low ^{a), c), e)}
NPPV vs HFNO	0.79 (0.44–1.43)	NA	NA	0.79 (0.44–1.43)	⨁◯◯◯ Very low ^{a), c), d)}
a) Very serious risk of bias, b) Very serious heterogeneity, c) Very serious inconsistency, d) Very serious imprecision, e) Serious heterogeneity.
CI, confidence interval; HFNO, high-flow nasal oxygenation; IMV, invasive mechanical ventilation; NA, not applicable; NPPV, non-invasive positive pressure ventilation; SOT, standard oxygen therapy

In the current NMA, using SOT as the reference, NPPV (RR, 0.37; 95% CI, 0.14–0.97; low certainty) was significantly associated with a lower risk of VAP, while HFNO (RR, 0.46; 95% CI 0.15–1.44; low certainty) was not associated with a statistically significant lower risk of VAP (Figure 6). Compared with IMV, NPPV (RR, 0.23; 95% CI, 0.11–0.47; very low certainty) and HFNO (RR, 0.29; 95% CI, 0.12–0.73; very low certainty) were associated with a statistically significant lower risk of VAP (Figure 6). There were no significant differences in the additional comparisons.

The ranking analysis revealed the following hierarchy regarding efficacy in reducing VAP: NPPV (SUCRA 91.7), followed by HFNO (SUCRA 70.6), SOT (SUCRA 30.1), and IMV (SUCRA 7.7) (Table 3 and S3 Fig). As well the risk of pneumonia, the probability of being the best in reducing VAP among all the possible interventions was highest for NPPV, followed by HFNO.

Table 6

Results of network rank test for ventilator- associated pneumonia in the network meta-analysis.
	NPPV	HFNO	IMV	SOT
Best	75.5%	22.4%	0.0%	2.1%
2nd	24.0%	66.9%	0.1%	9.0%
3rd	0.5%	10.7%	22.9%	65.9%
Worst	0.0%	0.0%	77.0%	23.0%
Mean rank	1.2	1.9	3.8	3.1
SUCRA	91.7	70.6	7.7	30.1
HFNO, high-flow nasal oxygenation; IMV, invasive mechanical ventilation; NPPV, non-invasive positive pressure ventilation; SUCRA, surface under the cumulative ranking; SOT, standard oxygen therapy

The current NMA of RCTs for adults with AHRF revealed that, compared with SOT, NPPV decreased the risk of pneumonia and VAP. Using IMV as the reference, both NPPV and HFNO were associated with a lower risk of pneumonia and VAP. The ranking analyses suggested that NPPV was the best strategy for reducing pneumonia. This NMA is the first study to demonstrate that NPPV and HFNO can reduce the risk of pneumonia in patients with AHRF.

In various previous trials, including observational studies, the incidence of nosocomial infections such as VAP was lower in NPPV than in IMV for AHRF due to various etiologies. Gay performed a meta-analysis of 12 studies and reviewed the risk of pneumonia in patients with NPPV [35]. In this meta-analysis, the pneumonia rate was lower in NPPV than that in IMV and SOT, consistent with our results. Moreover, in three studies that included patients who initially failed NPPV and were then intubated, the pneumonia rate was lower in those who initially received NPPV than in those with immediate intubation. Regarding the risk reduction of pneumonia, the use of NPPV for AHRF in adults may be superior to IMV or SOT as initial therapy.

We found that using HFNO for AHRF may reduce the incidence of pneumonia compared to IMV. Although the sample size was inadequate due to the lack of RCTs that directly compared HFNO and IMV, we could evaluate the effects of HFNO versus those of IMV with indirect comparisons, complementing the limitations of the existing studies. This finding indicates the effectiveness of non-invasive oxygenation strategies compared to endotracheal intubation management. On the other hand, HFNO did not show the significant reduction of pneumonia when compared with SOT. This result is consistent with a recent systematic review by Lewis et al. [36], which included four studies (three of which did not overlap with the current NMA) that compared HFNO with SOT. Further evaluation is needed to provide conclusive recommendations, although HFNO is recommended for patients with AHRF compared with SOT [5].

NPPV has been proposed for the management of AHRF, with conflicting results [4,7,23,27,28]. Therefore, recent guidelines have been unable to provide conclusive recommendations regarding the use of NPPV in patients with de novo AHRF [3,37], while the use of HFNO is encouraged [5]. In our NMA, HFNO did not show a reduction in the rate of pneumonia and VAP compared with NPPV, consistent with a recent systematic review by Lewis comparing HFNO and NPPV [36]. Interestingly, ranking analyses using SUCRA suggested that NPPV was the best non-invasive oxygenation strategy for reducing pneumonia. In 2020, Ferreyro et al. reported an NMA in which the efficacy of non-invasive respiratory managements was compared with that of SOT among adult patients with AHRF, and helmet non-invasive ventilation was associated with a lower risk of mortality and intubation compared with HFNO [8]. While HFNO may be both acceptable and feasible to implement, compared to NPPV [5], it is necessary to verify which intervention has more clinical benefit especially for patients with de novo AHRF.

This study has several limitations. First, we included studies with patients with cardiopulmonary edema and COPD who had a low risk of NPPV failure. This may have contributed to the overestimate of the treatment effect of NPPV. The NMA assumption is that individual trials enrol similar populations, and the intervention protocol is similar across different studies. We excluded studies in which more than half of the patients had cardiopulmonary edema or COPD, as reported in the previous NMA [8]. Second, there was a concern about the primary studies included in our review regarding the lack of blinding of the treatment groups. Although this was unlikely to bias the assessment of hard outcomes, it may have contributed to performance bias. Third, network RR was estimated using only indirect evidence in some comparisons. Specifically, few studies have compared HFNO with other interventions. Further studies are required to obtain a higher certainty of evidence. Finally, ranking results should be evaluated with caution because they do not consider the certainty of the evidence. Although NPPV seemed to be the best strategy considering ranking probabilities, this result dose not imply a significant clinical difference between NPPV and HFNO.

This NMA demonstrates that NPPV and HFNO were significantly associated with a lower incidence of pneumonia, compared to IMV, and NPPV but not HFNO was significantly associated with a lower incidence of pneumonia, compared to SOT. Our findings imply that NPPV and HFNO may be better strategies for the primary respiratory management of adult patients with AHRF to reduce pneumonia. Further studies are required to obtain a higher certainty of evidence, particularly with HFNO as a comparator.

AHRF

acute hypoxemic respiratory failure

ARDS

acute respiratory distress syndrome

CI

confidence interval

COPD

chronic obstructive pulmonary disease

HFNO

high-flow nasal oxygen

IMV

invasive mechanical ventilation

NMA

network meta-analysis

RCT

Randomized controlled trial

RR

risk ratio

SOT

standard oxygen therapy

SUCRA

Surface under the cumulative ranking curve

VAP

ventilator-associated pneumonia.

Author contributions:

MS, SK, and SH designed the study, acquired data, performed statistical analyses, and interpreted the data. HO and TM conceived the study and acquired and interpreted the data. SK and SH conceived the acquisition of data. The first draft of the manuscript was written by SH, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Acknowledgements

We would thank all the members of the Japanese ARDS clinical practice guideline committee from the Japan Society for Respiratory Care and Rehabilitation, the Japanese Respiratory Society, and the Japanese Society of Intensive Care Medicine. We also appreciate the librarian Takaaki Suzuki at the Nara Medical University Library, the librarians at the Kyoto Prefectural University of Medicine for supporting our search strategies, and Editage (www.editage.com) for English language editing.

Vincent JL, Akça S, De Mendonça A et al (2002) The epidemiology of acute respiratory failure in critically ill patients(*). Chest 121:1602–1609. 10.1378/chest.121.5.1602
Berbenetz N, Wang Y, Brown J et al (2019) Non-invasive positive pressure ventilation (CPAP or bilevel NPPV) for cardiogenic pulmonary oedema. Cochrane Database Syst Rev 4:Cd005351. 10.1002/14651858.CD005351.pub4
Rochwerg B, Brochard L, Elliott MW et al (2017) Official ERS/ATS clinical practice guidelines: noninvasive ventilation for acute respiratory failure. Eur Respir J 50. 10.1183/13993003.02426-2016
Bellani G, Laffey JG, Pham T et al (2017) Noninvasive Ventilation of Patients with Acute Respiratory Distress Syndrome. Insights from the LUNG SAFE Study. Am J Respir Crit Care Med 195:67–77. 10.1164/rccm.201606-1306OC
Rochwerg B, Einav S, Chaudhuri D et al (2020) The role for high flow nasal cannula as a respiratory support strategy in adults: a clinical practice guideline. Intensive Care Med 46:2226–2237. 10.1007/s00134-020-06312-y
Azoulay E, Lemiale V, Mokart D et al (2018) Effect of High-Flow Nasal Oxygen vs Standard Oxygen on 28-Day Mortality in Immunocompromised Patients With Acute Respiratory Failure: The HIGH Randomized Clinical Trial. JAMA 320:2099–2107. 10.1001/jama.2018.14282
Frat JP, Thille AW, Mercat A et al (2015) High-flow oxygen through nasal cannula in acute hypoxemic respiratory failure. N Engl J Med 372:2185–2196. 10.1056/NEJMoa1503326
Ferreyro BL, Angriman F, Munshi L et al (2020) Association of Noninvasive Oxygenation Strategies With All-Cause Mortality in Adults With Acute Hypoxemic Respiratory Failure: A Systematic Review and Meta-analysis. JAMA 324:57–67. 10.1001/jama.2020.9524
Hutton B, Salanti G, Caldwell DM et al (2015) The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions: checklist and explanations. Ann Intern Med 162:777–784. 10.7326/m14-2385
Hokari S, Kimata S, Sakuraya M, Okano H, Masuyama T (2021) Pneumonia Associated with Invasive and Noninvasive Oxygenation Strategies for Acute Hypoxemic Respiratory Failure in Adults: A Systematic Review and Network Meta-analysis Protocol. Protocolsio https://dx.doi.org/10.17504/protocols.io.bup17505nvq17506. dx.doi.org/10.17504/protocols.io.bup5nvq6
Tasaka S, Ohshimo S, Takeuchi M et al (2022) ARDS clinical practice guideline 2021. Respiratory Invest 60:446–495. 10.1016/j.resinv.2022.05.003
Papakonstantinou T, Nikolakopoulou A, Higgins J, Egger M, Salanti G (2020) CINeMA: Software for semiautomated assessment of the confidence in the results of network meta-analysis. Campbell Syst Reviews 16:e1080. 10.1002/cl2.1080
Sterne JAC, Savović J, Page MJ et al (2019) RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ 366:l4898. 10.1136/bmj.l4898
RevMan 5 Download and installation. Secondary RevMan 5 download and installation (2014) Accessed: 23 April, 2021: https://community.cochrane.org/help/tools-and-software/revman-5/revman-5-download/installation
Chaimani A, Salanti G (2012) Using network meta-analysis to evaluate the existence of small-study effects in a network of interventions. Res synthesis methods 3:161–176. 10.1002/jrsm.57
Nikolakopoulou A, Higgins JPT, Papakonstantinou T et al (2020) CINeMA: An approach for assessing confidence in the results of a network meta-analysis. PLoS Med 17:e1003082. 10.1371/journal.pmed.1003082
Yepes-Nuñez JJ, Li SA, Guyatt G et al (2019) Development of the summary of findings table for network meta-analysis. J Clin Epidemiol 115:1–13. 10.1016/j.jclinepi.2019.04.018
Salanti G, Ades AE, Ioannidis JP (2011) Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial. J Clin Epidemiol 64:163–171. 10.1016/j.jclinepi.2010.03.016
Chaimani A, Higgins JP, Mavridis D, Spyridonos P, Salanti G (2013) Graphical tools for network meta-analysis in STATA. PLoS ONE 8:e76654. 10.1371/journal.pone.0076654
Higgins JP, Thompson SG (2002) Quantifying heterogeneity in a meta-analysis. Stat Med 21:1539–1558. 10.1002/sim.1186
Higgins JP, Jackson D, Barrett JK, Lu G, Ades AE, White IR (2012) Consistency and inconsistency in network meta-analysis: concepts and models for multi-arm studies. Res synthesis methods 3:98–110. 10.1002/jrsm.1044
Guyatt GH, Oxman AD, Kunz R et al (2011) GRADE guidelines 6. Rating the quality of evidence–imprecision. J Clin Epidemiol 64:1283–1293. 10.1016/j.jclinepi.2011.01.012
Antonelli M, Conti G, Rocco M et al (1998) A comparison of noninvasive positive-pressure ventilation and conventional mechanical ventilation in patients with acute respiratory failure. N Engl J Med 339:429–435. 10.1056/nejm199808133390703
Confalonieri M, Potena A, Carbone G, Porta RD, Tolley EA, Umberto Meduri G (1999) Acute respiratory failure in patients with severe community-acquired pneumonia. A prospective randomized evaluation of noninvasive ventilation. Am J Respir Crit Care Med 160:1585–1591. 10.1164/ajrccm.160.5.9903015
Antonelli M, Conti G, Bufi M et al (2000) Noninvasive ventilation for treatment of acute respiratory failure in patients undergoing solid organ transplantation: a randomized trial. JAMA 283:235–241. 10.1001/jama.283.2.235
Delclaux C, L'Her E, Alberti C et al (2000) Treatment of acute hypoxemic nonhypercapnic respiratory insufficiency with continuous positive airway pressure delivered by a face mask: A randomized controlled trial. JAMA 284:2352–2360. 10.1001/jama.284.18.2352
Hilbert G, Gruson D, Vargas F et al (2001) Noninvasive ventilation in immunosuppressed patients with pulmonary infiltrates, fever, and acute respiratory failure. N Engl J Med 344:481–487. 10.1056/nejm200102153440703
Ferrer M, Esquinas A, Leon M, Gonzalez G, Alarcon A, Torres A (2003) Noninvasive ventilation in severe hypoxemic respiratory failure: a randomized clinical trial. Am J Respir Crit Care Med 168:1438–1444. 10.1164/rccm.200301-072OC
Squadrone V, Massaia M, Bruno B et al (2010) Early CPAP prevents evolution of acute lung injury in patients with hematologic malignancy. Intensive Care Med 36:1666–1674. 10.1007/s00134-010-1934-1
Zhan Q, Sun B, Liang L et al (2012) Early use of noninvasive positive pressure ventilation for acute lung injury: a multicenter randomized controlled trial. Crit Care Med 40:455–460. 10.1097/CCM.0b013e318232d75e
Muncharaz AB, Bort MC, Asensio DB et al (2017) Non-invasive ventilation versus invasive mechanical ventilation in patients with hypoxemic acute respiratory failure in an intensive care unit. a randomized controlled study. Minerva Pneumologica 56:1–10. 10.23736/S0026-4954.16.01770-3
He H, Sun B, Liang L et al (2019) A multicenter RCT of noninvasive ventilation in pneumonia-induced early mild acute respiratory distress syndrome. Crit Care 23:300. 10.1186/s13054-019-2575-6
Awadallah M, Taha A, Sarhan T (2021) Cardiorespiratory changes and outcome during noninvasive and invasive mechanical ventilation in ARDS: a comparative study. Res Opin Anesth Intensive Care 8:6–12. 10.4103/roaic.roaic_15_19
Grieco DL, Menga LS, Cesarano M et al (2021) Effect of Helmet Noninvasive Ventilation vs High-Flow Nasal Oxygen on Days Free of Respiratory Support in Patients With COVID-19 and Moderate to Severe Hypoxemic Respiratory Failure: The HENIVOT Randomized Clinical Trial. JAMA 325:1731–1743. 10.1001/jama.2021.4682
Gay PC (2009) Complications of noninvasive ventilation in acute care. Respir Care 54:246–257
Lewis SR, Baker PE, Parker R, Smith AF (2021) High-flow nasal cannulae for respiratory support in adult intensive care patients. Cochrane Database Syst Rev 3(Cd010172). 10.1002/14651858.CD010172.pub3
Akashiba T, Ishikawa Y, Ishihara H et al (2017) The Japanese Respiratory Society Noninvasive Positive Pressure Ventilation (NPPV) Guidelines (second revised edition). Respiratory Invest 55:83–92. 10.1016/j.resinv.2015.11.007

The authors declare no competing interests.

Additionalfile1.docx

Non-invasive Oxygenation Strategies for Reducing the Incidence of Pneumonia in Adult Patients with Acute Hypoxemic Respiratory Failure: A Systematic Review and Network Meta-analysis

Status:

Version 1

Abstract

Figures

Introduction

Methods

Protocol and registration

Inclusion criteria

Exclusion criteria

Search strategy

Study selection and data extraction

Network geometry

Quality assessment

Methods of direct comparison meta-analysis

Methods of network comparison meta-analysis

Assessments of the certainty of evidence

Search results

Study characteristics and risk of bias assessment

Risk of pneumonia

Risk of ventilator-associated pneumonia

Discussion

Conclusions

Abbreviations

Declarations

Author contributions:

Acknowledgements

References

Additional Declarations

Supplementary Files

Status:

Version 1