# Meta-regression analysis of high-frequency ventilation vs conventional ventilation in infant respiratory distress syndrome

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## Abstract

### Objective

There is considerable heterogeneity among randomized trials comparing high-frequency ventilation (HFV) with conventional mechanical ventilation (CMV) in premature neonates with respiratory distress syndrome. We investigated what factors explained differences in outcome among these trials.

### Design

Meta-regression analysis of 15 randomized trials.

### Measurements and results

Variables were extracted to explain heterogeneity: year of publication; use of Sensormedics 3100A ventilator for HFV; time on CMV prior to start of study; gestational age; use of surfactant; high lung volume strategy in HFV; and lung protective ventilation strategy in CMV and baseline risk. Chronic lung disease (CLD) and death or CLD were outcome measures. Relative risk ratios were calculated to estimate effect sizes of explanatory variables on reported relative risks. Adjusted estimates of relative risk ratios of high lung volume strategy and lung protective ventilation strategy were 0.42 (95% CI 0.06–2.48) and 2.02 (95% CI 0.18–23.12) for CLD, respectively. The effect of gestational age was less pronounced (RRR = 1.17 (95% CI 0.16–8.32) for CLD, respectively). Use of Sensormedics and prior time on CMV had the smallest effects [RRR = 0.96 (95% CI 0.47–1.94) and RRR = 0.85 (95% CI 0.58–1.24) for CLD, respectively)]. The same results applied to CLD or death as outcome.

### Conclusions

Variation in ventilation strategies that were used in trials comparing HFV with CMV in premature neonates offered the most likely explanation for the observed differences in the outcome of these trials compared with other explanatory factors.

## Keywords

Conventional mechanical ventilation High-frequency ventilation Meta-regression analysis Respiratory distress syndrome Infant## Introduction

High-frequency ventilation (HFV) has been compared with conventional mechanical ventilation (CMV) since the 1980s. In HFV, patients are ventilated with small tidal volumes, even smaller than the dead space of their airways, at high frequencies, normally between 5 and 10 Hz. Because HFV combines high mean airway pressures with small tidal volumes, this technique of ventilation has been regarded by some to be the most optimal form in patients with infant respiratory distress syndrome (IRDS), adult respiratory distress syndrome (ARDS), and other forms of severe lung disease [1].

- 1.
The observed regression of the cumulative relative risks to the level of unity was due to publication bias.

- 2.
Use of the Sensormedics ventilator resulted in better results in HFV treated patients.

- 3.
A prolonged ventilation on CMV before initiating HFV treatment could reduce the benefits of HFV.

- 4.
In subgroups of more premature neonates with lower birth weight with a higher susceptibility for CLD, HFV could result in better pulmonary outcome.

- 5.
With outcome rates increasingly representing more severe disease, HFV could have an increasing advantage over CMV [9, 10]; therefore, we used meta-regression analysis to better estimate relative treatment effects through adjustments for factors that could explain trial heterogeneity.

## Methods

Trials were included based on a previous meta-analysis that we had conducted [4]. The same search strategy, as well as the same inclusion and exclusion criteria as in our previous meta-analysis, were used for an update, yielding two more studies that could be included for this meta-regression analysis. Validity of studies was assessed by criteria published by Jadad et al. [11]. The validity was generally deemed as high with adequate allocation concealment in all trials. Blinding of treatment was not possible due to the nature of the interventions.

Data extraction was performed as has been reported in our previous meta-analysis. The following outcome measures were used: mortality, chronic lung disease (CLD) as defined by supplemental oxygen need or ventilator dependency at the age of 30–36 weeks post-menstrual. A number of explanatory variables were extracted as well: year of publication; type of ventilator used for HFV (Sensormedics 3100A ventilator versus other); ventilation strategies applied in the HFV and CMV treatment groups were obtained as previously described [4]; time on CMV before study initiation; gestational age and birth weight; and outcome rates in the control population were taken as proxy for baseline disease severity in the source population. The Sensormedics ventilator was singled out because previous research suggested better performance compared with other oscillator ventilators [2, 4].

### Statistical analysis

All data were extracted according to the intention-to-treat principle. The number of patients surviving without chronic lung disease was subtracted from the total number of randomized patients in each treatment arm to calculate the composite outcome of death or CLD. To calculate the risk of CLD, the number of surviving patients was put in the denominator. Publication bias was assessed by visual appraisal of symmetry of funnel plots and performing rank tests. Smaller studies could show different results than larger studies which could suggest publication bias, but in fact was caused by systematic differences among studies; therefore, an analysis of publication bias stratified for ventilation strategies was performed to determine whether the observed association between the inverse of the standard error with the risk ratio was confounded by ventilation strategies. Meta-regression analysis was used to evaluate other hypotheses. The dependent variables, RR of CLD and RR of CLD or death, were natural log transformed to linearize the regression models. Individual studies were weighted by inverse variances of relative risks of outcomes of interest so that the more precise studies had more influence in the analysis. Firstly, linear regression analyses were applied to explanatory variables. Secondly, linear regression analyses with continuous covariates were conducted stratified by HLVS, LPVS, and use of surfactant. Finally, multivariable linear regression analyses were performed to calculate adjusted contributions of different explanatory variables of rivalling hypotheses to changes in RR. The relative effects of covariates were evaluated by relative risk ratios (RRR). A relative risk ratio quantifies the relative change in RR that is associated with a specified change of a covariate. For continuous variables the RRR was calculated for the ranges of minimum and maximum values of covariates that were reported in trials. For example, the RRR for year of publication was calculated by using the range between the publication year of the first year and the publication year of the last included trial. The RRR for year of publication thus estimates the relative change in RR due to the difference in years of publication between the first and last trials. All analyses were conducted using SPSS 12.0.1 for Windows software (SPSS, Chicago, Ill.) and Excel (Microsoft, Redmond, Wash.).

## Results

For the analyses 15 studies were available that specified either CLD in survivors or death or CLD as outcome measures [2, 3, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24]. In 11 trials a high frequency oscillatory ventilator was used [2, 3, 12, 13, 16, 17, 19, 20, 22, 23, 24], in 7 of these trials this was the SensorMedics ventilator [2, 12, 13, 17, 22, 23]. Two studies used a high-frequency jet ventilator [14, 15] and in two studies a high-frequency flow interrupter ventilator was used [18, 21]. In the HFV group a total of 1141 patients were included for the outcome of CLD with 373 events and a total of 1457 patients with 671 events for the outcome death or CLD. In the CMV group a total 1159 patients were reported for the outcome of CLD with 428 events and a total of 1473 patients with 730 events for the outcome death or CLD. A forest plot of these trials can be found in the Electronic Supplement.

Study characteristics

Reference | Year | Time on CMV | Age | Birth weight | SensorM | HLVS | LPVS | Surf | CLD lnRR | Weight | Death or CLD lnRR | Weight | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|

[12] | 1992 | 9.0 | 28 | 1.100 | Y | Y | N | N | -1.29 | 0.01 | -0.58 | 0.01 | ||||||||||||

[13] | 1996 | 3.0 | 31 | 1.500 | Y | Y | N | Y | -0.67 | 0.04 | -0.55 | 0.02 | ||||||||||||

[14] | 1996 | 7.2 | 27 | 0.950 | N | N | N | Y | 0.02 | 0.01 | -0.23 | 0.10 | ||||||||||||

[15] | 1997 | 8.0 | 27 | 1.020 | N | Y | N | Y | -0.70 | 0.03 | 0.48 | 0.03 | ||||||||||||

[16] | 1998 | 1.0 | 28 | 1.100 | N | N | N | Y | 0.00 | 0.00 | 0.31 | 0.00 | ||||||||||||

[17] | 1999 | 26 | 0.850 | Y | Y | N | Y | -1.03 | 0.01 | -0.74 | 0.01 | |||||||||||||

[18] | 1999 | 0.5 | 27 | 0.870 | N | Y | Y | Y | 0.09 | 0.06 | 0.01 | 0.04 | ||||||||||||

[19] | 2001 | 2.6 | 26 | 0.840 | Y | Y | Y | Y | -0.98 | 0.02 | -0.59 | 0.02 | ||||||||||||

[20] | 2001 | 0.3 | 28 | 0.990 | N | Y | Y | Y | -0.20 | 0.05 | -0.06 | 0.05 | ||||||||||||

[2] | 2002 | 2.7 | 26 | 0.850 | Y | Y | Y | Y | -0.06 | 0.16 | -0.22 | 0.13 | ||||||||||||

[3] | 2002 | 1.0 | 26 | 0.850 | N | Y | Y | Y | -0.01 | 0.54 | -0.02 | 0.60 | ||||||||||||

[23] | 2003 | 1.0 | 29 | 1.200 | Y | Y | Y | Y | 0.32 | 0.03 | 0.27 | 0.04 | ||||||||||||

[22] | 2003 | 14.0 | 27 | 0.980 | Y | Y | Y | Y | -0.04 | 0.05 | ||||||||||||||

[21] | 2003 | 26 | 0.726 | N | Y | Y | Y | 0.10 | 0.05 | 0.09 | 0.03 | |||||||||||||

[24] | 2005 | 0.3 | 27 | 0.880 | N | Y | Y | Y | -1.44 | 0.01 | -1.20 | 0.00 |

*p*-value of 0.112. A stratified analysis of publication bias is indicated by different colors in Fig. 1. To visually evaluate publication bias within subgroups of ventilation strategy, the distribution of trials round the corresponding colored lines (mean effect size within subgroup) was assessed. Stratification by ventilation strategy (HLVS and LPVS vs either no HLVS and/or no LPVS) showed

*p*-values of 0.456 and 0.851, respectively, indicating less evidence of publication bias. The distribution of stratified studies round the lines of pooled estimates showed less asymmetry (Fig. 1). Publication bias for the composite outcome of death or CLD was less likely with a

*p*-value of 0.329. Stratified analysis showed

*p*-values of 0.677 and 1.000.

Univariable linear regression analysis

95% confidence interval | 95% confidence interval | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|

Crude B | Sig. | Lower | Upper | RRR | Lower | Upper | ||||||||

boundary | boundary | boundary | boundary | |||||||||||

| ||||||||||||||

| ||||||||||||||

Year | 0.09 | 0.025 | 0.01 | 0.16 | 3.13 | 1.18 | 8.27 | |||||||

SensorM | -0.17 | 0.351 | -0.55 | 0.21 | 0.84 | 0.58 | 1.24 | |||||||

(no to yes) | ||||||||||||||

TimeCMV | -0.09 | 0.055 | -0.19 | 0.00 | 0.44 | 0.19 | 1.02 | |||||||

Age | -0.08 | 0.237 | -0.23 | 0.06 | 0.66 | 0.32 | 1.36 | |||||||

Weight | -0.76 | 0.163 | -1.87 | 0.35 | 0.54 | 0.22 | 1.33 | |||||||

HLVS | -0.11 | 0.883 | -1.74 | 1.52 | 0.89 | 0.17 | 4.57 | |||||||

LPVS | 0.64 | 0.009 | 0.19 | 1.10 | 1.91 | 1.21 | 3.00 | |||||||

Surf | 1.21 | 0.168 | -0.59 | 3.00 | 3.34 | 0.56 | 20.03 | |||||||

CMV | -0.18 | 0.774 | -1.53 | 1.17 | 0.90 | 0.42 | 1.92 | |||||||

| ||||||||||||||

Year | 0.05 | 0.096 | -0.01 | 0.12 | 2.01 | 0.86 | 4.65 | |||||||

SensorM | -0.17 | 0.132 | -0.39 | 0.06 | 0.85 | 0.67 | 1.06 | |||||||

TimeCMV | -0.01 | 0.590 | -0.05 | 0.03 | 0.92 | 0.65 | 1.29 | |||||||

Age | -0.02 | 0.733 | -0.13 | 0.10 | 0.91 | 0.52 | 1.61 | |||||||

Weight | -0.22 | 0.611 | -1.16 | 0.71 | 0.84 | 0.40 | 1.77 | |||||||

HLVS | -0.37 | 0.698 | -2.44 | 1.69 | 0.69 | 0.09 | 5.45 | |||||||

LPVS | 0.19 | 0.275 | -0.18 | 0.56 | 1.21 | 0.84 | 1.76 | |||||||

Surf | 0.52 | 0.289 | -0.51 | 1.56 | 1.69 | 0.60 | 4.75 | |||||||

CMV | -0.02 | 0.963 | -0.91 | 0.87 | 0.99 | 0.60 | 1.63 | |||||||

| ||||||||||||||

| ||||||||||||||

Year | 0.00 | 0.971 | -0.23 | 0.22 | 0.96 | 0.05 | 17.34 | |||||||

TimeCMV | -0.05 | 0.698 | -0.34 | 0.25 | 0.66 | 0.05 | 8.75 | |||||||

Age | 0.04 | 0.727 | -0.22 | 0.30 | 1.22 | 0.33 | 4.49 | |||||||

Weight | 0.41 | 0.693 | -1.99 | 2.81 | 1.38 | 0.20 | 9.44 | |||||||

| ||||||||||||||

Year | 0.01 | 0.846 | -0.15 | 0.17 | 1.20 | 0.15 | 9.72 | |||||||

TimeCMV | 0.00 | 0.819 | -0.05 | 0.04 | 0.96 | 0.65 | 1.43 | |||||||

Age | 0.06 | 0.406 | -0.10 | 0.21 | 1.34 | 0.61 | 2.92 | |||||||

Weight | 0.55 | 0.396 | -0.89 | 1.99 | 1.55 | 0.49 | 4.90 |

Year of publication was not related to change in relative risk of CLD in the subgroup of studies with HLVS, LPVS and concomitant use of surfactant (RRR = 0.96). There was only a small increase in relative risk for death or CLD (RRR = 1.20; Fig. 2; Table 2). Opposite effects of gestational age (RRR = 1.22 for CLD and 1.38 for death or CLD vs RRR = 0.66 for CLD and 0.91 for death or CLD, respectively) and birth weight were detected in the subgroup analysis (Fig. 4; Table 2). Prior time on CMV exerted less effect on outcome compared with the crude analysis, RRR = 0.66 for CLD and 0.96 for death or CLD and RRR = 0.44 for CLD and 0.92 for death or CLD in the adjusted and crude analyses, respectively (Fig. 3; Table 2).

Multivariable linear regression analysis

Adjusted | 95% confidence interval | 95% confidence interval | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|

B | Sig. | Lower boundary | Upper boundary | RRR | Lower boundary | Upper boundary | ||||||||

| ||||||||||||||

| ||||||||||||||

(Constant) | -0.66 | 0.900 | -13.03 | 11.70 | ||||||||||

SensorM | -0.04 | 0.884 | -0.75 | 0.66 | 0.96 | 0.47 | 1.94 | |||||||

TimeCMV | -0.02 | 0.903 | -0.38 | 0.34 | 0.85 | 0.04 | 19.22 | |||||||

Age | 0.03 | 0.850 | -0.36 | 0.42 | 1.17 | 0.16 | 8.32 | |||||||

HLVS | -0.88 | 0.306 | -2.80 | 1.04 | 0.42 | 0.06 | 2.84 | |||||||

LPVS | 0.70 | 0.506 | -1.73 | 3.14 | 2.02 | 0.18 | 23.12 | |||||||

| ||||||||||||||

(Constant) | -1.86 | 0.412 | -7.22 | 3.49 | ||||||||||

SensorM | -0.17 | 0.309 | -0.55 | 0.21 | 0.85 | 0.58 | 1.24 | |||||||

TimeCMV | 0.01 | 0.722 | -0.05 | 0.06 | 1.07 | 0.68 | 1.69 | |||||||

Age | 0.08 | 0.299 | -0.09 | 0.25 | 1.47 | 0.62 | 3.47 | |||||||

HLVS | -0.88 | 0.407 | -3.38 | 1.62 | 0.42 | 0.03 | 5.06 | |||||||

LPVS | 0.68 | 0.127 | -0.28 | 1.65 | 1.98 | 0.76 | 5.19 | |||||||

| ||||||||||||||

| ||||||||||||||

(Constant) | 0.07 | 0.904 | -1.21 | 1.35 | ||||||||||

SensorM | -0.06 | 0.698 | -0.38 | 0.26 | 0.94 | 0.69 | 1.30 | |||||||

HLVS | -0.81 | 0.203 | -2.14 | 0.52 | 0.44 | 0.12 | 1.68 | |||||||

LPVS | 0.72 | 0.011 | 0.21 | 1.23 | 2.06 | 1.23 | 3.43 | |||||||

| ||||||||||||||

(Constant) | ||||||||||||||

SensorM | -0.11 | 0.318 | -0.33 | 0.12 | 0.90 | 0.72 | 1.13 | |||||||

HLVS | -0.79 | 0.363 | -2.66 | 1.08 | 0.45 | 0.07 | 2.93 | |||||||

LPVS | 0.46 | 0.089 | -0.09 | 1.01 | 1.59 | 0.92 | 2.74 |

A sensitivity analysis was conducted by fitting a second model (model B) with the most important variables, HLVS and LPVS, combined with whether or not a Sensormedics ventilator was used. The reported RRRs were comparable to those in the first model. Type of ventilator did not have a large effect compared with ventilation strategies (RRR = 0.94 and RRR = 0.90). The HLVS was associated with a decrease of the RRs comparing HFV with CMV (RRR = 0.44 and RRR = 0.45), while LPVS increased the RRs to the line of no effect (RRR = 2.06 and RRR = 1.59).

## Discussion

Our meta-regression analysis showed a clear trend of decreasing differences in pulmonary outcome between HFV and CMV in randomized trials conducted in premature neonates with IRDS over the years. The most likely hypothesis for this trend was the application of a LPVS in the most recent studies. Use of surfactant could also have a significant contribution, but only one study did not use surfactant [12]. In previous meta-analyses, subgroup analyses or cumulative methods were used to explore heterogeneity [4, 5, 7]. Subgroup analysis is equivalent to meta-regression with a categorical trial-level covariate. Considering subgroup analysis formally as a meta-regression has advantages, since it focuses on differences between subgroups as is appropriate, rather than the effects in each subgroup separately. Furthermore, it is appropriate to use meta-regression to explore sources of heterogeneity, even if an initial overall test for heterogeneity is non-significant. This test often has low power and therefore a non-significant result does not reliably identify lack of heterogeneity [25].

In this meta-regression analysis we evaluated in a quantitative way a number of hypotheses that were raised to account for different results between randomized trials. A relatively large proportion of well-conducted trials were available for the analyses. For most explanatory variables there were important differences among trials. The effects of the two most important covariates, HLVS and LPVS, were consistent in the different models and were even increased in effect size by adjusting for other covariates. None of the competing hypotheses were more likely to influence results as shown by calculating the RRRs. Common pitfalls in meta-regression analysis can occur, such as multiple or post-hoc analyses, and lead to data dredging and a high probability of false-positive conclusions [25]. We, therefore, restricted our analyses to a limited number of pre-specified explanatory covariates.

Publication bias was considered unlikely as an explanation of the apparent diminishing relative effect of HFV. Publication bias is selection bias. If trials are selectively published either because of their size or because of significant results, this would result in an association between trial size and/or precision and the trial outcome. Strictly speaking, funnel plots probe whether studies with little precision (small studies) give different results from studies with greater precision (larger studies). Asymmetry in the funnel plot may therefore result not from a systematic under-reporting of negative trials but from an essential difference between smaller and larger studies that arises from inherent between-study heterogeneity [26]; thus, if larger studies were also associated with changes in ventilation strategies and these strategies resulted in changes in reported RRs, the assumed publication bias would be, in fact, a real association between ventilation strategy and study outcome; therefore, we conditioned the association between precision and effect size, presumably caused by publication bias, on ventilation strategies. This resulted in a lower *p*-value for publication bias and more symmetrical distribution of studies in subgroups in the funnel plots; therefore, what appeared to be publication bias could also be explained by differences in ventilation strategies related to both study size and observed relative risks. However, it should be pointed out that the strength of this evidence is difficult to assess because fewer studies in the subgroups automatically resulted in less power to detect publication bias.

Other alternative hypotheses that have been formulated to explain differences among studies were also less compatible with the evidence [9]. The type of ventilator, Sensormedics vs other types of high-frequency ventilators, displayed RRR close to one. In the crude analyses, prior time on CMV before study initiation showed contradictory effects to what was hypothesized [10]. The adjusted analyses showed conflicting results depending on the outcome. Gestational age and birth weight could also influence the magnitude of the effect of HFV compared with CMV. In the adjusted analysis gestational age did not change the RR for CLD but showed an increase of the RR for less premature neonates. Finally, an increased risk of CLD was not accompanied by a greater relative benefit of HFV as compared with CMV.

The observed effects of continuous variables, such as time on CMV or gestational age, could be exaggerated by small studies with outlying results. For the covariate, time on CMV, the two largest studies showed results that were compatible with the hypothesis that this had no important impact on the results of these trials [2, 3]. The same fact applied to the effect of baseline incidence of CLD or death or CLD. Gestational age and weight were comparable between the two largest trials, which made it more difficult to ascertain the relevance of the hypothesis that in smaller and more premature infants HFV performed better than CMV treatment. The observed direction of the effect of gestational age and birth weight, however, was opposite to what the hypothesis predicted. If gestational age was to be interpreted as a higher risk of acquiring CLD, one would expect that an increase in the incidence of CLD was associated with a relatively lower incidence of CLD in HFV treated patients; however, linear regression analysis showed perfectly equal increase in both treatment groups. Still, the possibility remains that the relationship with patient averages, such as gestational age and birth weight, across trials was not the same as the relationship for patients within trials, and therefore an effect of these patient characteristics cannot be excluded but only considered in relation to other covariates [25].

Similar findings of the effects of ventilation strategies have been reported by us and other authors as well [4, 5]; however, meta-analyses are subject to bias when differences among trials are used to explain differences in reported RRs. In this meta-regression analysis we were able to estimate adjusted association measures, thereby diminishing the effects of possible confounders/effect-modifiers. By calculating less biased estimates of the effects of ventilation strategies and the effect of using a Sensormedics ventilator instead of other ventilators on the outcome in the different HFV trials we were able to reinforce the hypothesis that ventilation strategies are more important than type of ventilator to prevent CLD.

The results of this meta-analysis stresses the importance of using appropriate ventilation strategies to prevent ventilator-induced lung damage in a highly vulnerable group of patients; therefore, in clinical practice the question of how to use the ventilator is more important than the question of which ventilator should be used. The major theoretical advantage of HFV to CMV is delivery of smaller tidal volumes to an optimally recruited lung. As this meta-regression analysis did not confirm that subgroups of more premature neonates, avoidance of CMV prior to initiating HFV, or neonates with higher risk of CLD were more likely to benefit form elective HFV in IRDS, future research should be directed at identifying patients in whom HFV does have a benefit over CMV. To improve the robustness of these conclusions and to avoid the limitations of meta-analysis of trials, an individual-patient-data-based meta-regression analysis should be conducted.

## Conclusion

In conclusion, confining randomized trails to smaller or more premature children with IRDS did not seem to result in better pulmonary outcomes of HFV compared with CMV. A generally held opinion that a prolonged ventilation time on CMV prior to initiating HFV diminished the benefits of HFV was not in agreement with the current evidence. The most important effects resulting in differences among trials were probably caused by ventilation strategies applied in HFV- and CMV-treated patients.

## Supplementary material

## References

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