Introduction 1 2 3 4 5 6 7 8 7 4 The observed regression of the cumulative relative risks to the level of unity was due to publication bias. Use of the Sensormedics ventilator resulted in better results in HFV treated patients. A prolonged ventilation on CMV before initiating HFV treatment could reduce the benefits of HFV. In subgroups of more premature neonates with lower birth weight with a higher susceptibility for CLD, HFV could result in better pulmonary outcome. 9 10 Methods 4 11 4 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 2 3 12 13 14 15 16 17 18 19 20 21 22 23 24 2 3 12 13 16 17 19 20 22 23 24 2 12 13 17 22 23 14 15 18 21 1 22 17 21 12 14 16 2 3 18 19 20 21 22 23 24 3 2 Table 1 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 Year Time CMV Age Birth weight HLVS LPVS Surf CLD LnRR 1 p 1 p 1 p p Fig. 1 x y Blue diamonds: HLVS LPVS pink diamonds: dotted line: dashed colored lines: CMV  2 3 4 2 3 2 3 4 2 2 Fig. 2 y x Blue diamonds: pink diamonds: Thin blue line: thick pink line: CMV  Fig. 3 Same as Fig. 2  Fig. 4 Same as Fig. 2  Table 2 Univariable linear regression analysis    95% confidence interval  95% confidence interval  Crude B Sig. Lower Upper RRR Lower Upper    boundary boundary  boundary boundary  All studies CLD  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 Death or CLD  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  Studies with surfactant, HLVS, and LPVS CLD  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 Death or CLD  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 SensorM TimeCMV Age Weight HLVS LPVS Surf RRR covariate=1 covariate=0 SensorM HLVS LPVS CMV CMV years year=2005 year=1992,
  time on CMV time=9 h time=0.3 h age age=31 weeks year=26 weeks weight weight=1.5 kg year=0.7 kg incidence
 of CLD in CMV=0.75 incidence=0.08 5 Fig. 5 y x Thin pink line:  2 2 4 2 3 2 3 3 2 Table 3 Multivariable linear regression analysis  Adjusted 95% confidence interval  95% confidence interval  B Sig. Lower boundary Upper boundary RRR Lower boundary Upper boundary  Model A CLD  (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 Death or CLD  (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  Model B CLD  (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 Death or CLD  (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 CLD SensorM TimeCMV HLVS LPVS RRR covariate=1 covariate=0 age age=31 weeks year=26 weeks 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 12 4 5 7 25 25 26 p 9 10 2 3 25 4 5 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. Electronic supplementary material Electronic Supplementary Material (DOC 514K)