- Open Access
Physiological predictors of survival during high-frequency oscillatory ventilation inadults with acute respiratory distress syndrome
Critical Care volume 17, Article number: R40 (2013)
Data that provide clinical criteria for the identification of patients likely torespond to high-frequency oscillatory ventilation (HFOV) are scarce. Our aim wasto describe physiological predictors of survival during HFOV in adults with severeacute respiratory distress syndrome (ARDS) admitted to a respiratory failurecenter in the United Kingdom.
Electronic records of 102 adults treated with HFOV were reviewed retrospectively.We used logistic regression and receiving-operator characteristics curve to testassociations with oxygenation and mortality.
Patients had severe ARDS with a mean (SD) Murray's score of 2.98 (0.7). Partialpressure of oxygen in arterial blood to fraction of inspired oxygen(PaO2/FiO2) ratio and oxygenation index improved only insurvivors. The earliest time point at which the two groups differed was at threehours after commencing HFOV. An improvement of >38% inPaO2/FiO2 occurring at any time within the first 72hours, was the best predictor of survival at 30 days (area under the curve (AUC)of 0.83, sensitivity 93%, specificity 78% and a positive likelihood ratio (LR) of4.3). These patients also had a 3.5 fold greater reduction in partial pressure ofcarbon dioxide in arterial blood (PaCO2). Multivariate analysis showedthat HFOV was more effective in younger patients, when instituted early, and inpatients with milder respiratory acidosis.
HFOV is effective in improving oxygenation in adults with ARDS, particularly wheninstituted early. Changes in PaO2/FiO2 during the firstthree hours of HFOV can identify those patients more likely to survive.
Patients with acute respiratory distress syndrome (ARDS) exhibit a highly inhomogeneous,compliance-dependent distribution of regional ventilation during conventional mechanicalventilation (CMV) . Consequently, CMV can lead to further lung injury through tidalhyperinflation and shear stress injury, even when it is administered according to a'lung protective strategy' that limits tidal volumes and plateau pressure , and employs recruitment maneuvers to maximize the proportion of aeratedalveolar tissue . High-frequency oscillatory ventilation (HFOV) can theoretically offereffective lung protective ventilation by delivering very low tidal volumes (1 to 3 mLKg-1) around a fixed mean airway pressure at frequencies of 5 to 12 Hz(lower frequencies are used in adults). At high respiratory frequencies, the shortinspiratory time results in a distribution of ventilation which, compared to mechanicalventilation at conventional breathing rates, is more homogeneous and less dependent onthe distribution of regional lung compliance [3, 4]. This results in the protection of the recruited lung (with greatercompliance) from excessive cyclic variations in alveolar pressure. In addition, if thecontinuous distending pressure (CDP) is optimized following a stepwise recruitmentmaneuver, the more compliant lung regions are less susceptible to static hyperinflation [3, 5, 6], thereby reducing lung strain and ventilation-induced inflammation [7, 8].
HFOV improves gas exchange and reduces lung injury in animal models of ARDS [9–11] and in human neonatal and pediatric populations [12–15]. In adults the effects of HFOV are largely limited to observational studies [16–24] and two randomized trials [25, 26]. Overall these studies show that HFOV might improve gas exchange andsurvival. However, data that provide clinical criteria for identification of patientslikely to benefit from HFOV are scarce [23, 24]. Large studies outside North America, utilizing different protocols arelacking, although the results of two multicenter clinical trials in the UK and Canada(OSCAR and OSCILLATE trials) are awaited [16, 27, 28].
In this study we aim to describe potential physiological predictors of survival duringHFOV in adults with severe ARDS admitted to an advanced respiratory failure center inthe United Kingdom.
Materials and methods
This was a single center observational study of patients with ARDS admitted to theAdult Intensive Care Service at Guy's and St Thomas' Hospital in London between 1998and 2002. We included patients who were treated with HFOV because of severe gasexchange impairments while on CMV. Medical records and physiological data before,during and after HFOV were retrieved from our ICU electronic patient record(Intellivue Clinical Information Portfolio, Philips Medical Systems UK Limited).Patients' demographic data, hemodynamic variables, oxygenation and ventilatorsettings were recorded while on CMV prior to HFOV, during HFOV, prior todiscontinuation of HFOV and on recommencement of CMV. Oxygenation index (OI =(FiO2CDP 100)/PaO2) and partial pressure of oxygen inarterial blood to fraction of inspired oxygen (PaO2/FiO2) ratiowere calculated at the same intervals. Acute Physiology and Chronic Health Evaluation(APACHE II) and Murray lung injury severity score (which combines degree of lunginfiltration on chest × ray, lung compliance, PaO2/FiO2 and positive end expiratory pressure (PEEP))  at admission and on commencement of HFOV were determined (with a blindedand independent radiologist scoring the chest x-ray appearance). Hemodynamic datawere obtained using cardiac output monitors PiCCOplus (Pulsion, Munich, Germany,Software version 7.0 non USA), or a LiDCO (LiDCO Ltd, London, UK). This study wasconsidered by the National Research Ethics Service as 'service evaluation' andtherefore did not require Research Ethics Committee review .
Ventilator settings and study protocol
All patients were ventilated with pressure-controlled ventilation before startingHFOV, using a lung protective strategy [31, 32]. Patients were considered for HFOV if SaO2 <88%/PaO2 <60 mmHg, FiO2 >0.6 and pH <7.2.
HFOV was delivered using an adult high-frequency oscillatory ventilator (3100B,Viasys (CareFusion), Yorba Linda, CA, USA). All patients were initiated onto HFOVusing the following settings: a FiO2 of 1.0, a frequency of 4 to 6 Hz,inspiratory time of 33%, a bias flow of 30 to 40 Lmin-1, a CDP set 3 to 5cmH2O above the CDP during CMV and a Power to obtain transmittedoscillation ('wiggles') up to the level of mid-thigh. The power dial determines theamount of power that drives the oscillator piston to and fro. The Power control is a10-turn locking dial, electrical potentiometer covering the power range of 0 to 100%.The effect of this control is to change the displacement of the oscillator piston andhence to determine the oscillatory pressure ΔP. The Power setting interacts withthe pulmonary artery wedge (Paw) and the conditions existing within the circuit toproduce the resultant ΔP .
On starting HFOV, patients underwent a standardized slow recruitment maneuver (SRM),which represents the standard of care for patients receiving HFOV in thisInstitution. The SRM is derived from the maneuver included in the original MOAT Studyprotocol . The SRM was performed by a stepwise increase in CDP by increments of 3cmH2O every 10 minutes, starting from the CDP on CMV + 3 to 5cmH2O, up to 50 cmH2O. SRM was interrupted if the meanarterial pressure fell below 55 mmHg or if desaturations (SpO2 <85%) orarrhythmias occurred. Subsequently, CDP was reduced by 2 cmH2O every 5minutes. Arterial blood gases were taken every 10 minutes (every step during theincremental CDP, phase, and every two steps of the decremental CDP, phase). The'optimal' CDP was established as the lowest CDP that achieved the most favorablecombination between the highest PaO2 and/or lowest PaCO2, whilemaintaining the FiO2 constant at 1.0.
The protocol for the adjustment of HFOV was published previously . A reduction of CDP was initiated when the FiO2 was ≤0.5.Once CDP ≤20 to 22 cmH2O was achieved on a FiO2 of 0.4,the patients returned to CMV. CMV was restarted in the pressure-control mode with CDPclose to the CDP on HFOV, plateau pressures <28 cmH2O and PEEP adjustedto a tidal volume of 6 mLKg-1 of predicted body weight.
The primary outcome measures were: improvement in PaO2/FiO2 andOI and identification of physiological variables associated with 30-day survival.
To stratify patients we used an empirical score generated from the available datathat was solely designed to give a pragmatic quantification of disease severity andnot intended to have diagnostic or prognostic value. The score includedPaO2/FiO2, basal PaCO2, respiratory systemcompliance, minute ventilation and mean airway pressure. This score was used as adichotomous variable to separate patients with a more severe index of disease (score>50th percentile) from those with a less severe index of disease (score <50thpercentile).
Distribution of baseline variables was assessed using the Kolmogorov-Smirnov test.Differences in baseline variables between survivors and non-survivors were comparedusing the two-tailed t-test or Mann-Withney U test for continuous data, andχ2 or the Fisher test for qualitative data. Differences inphysiological variables over time between the two outcome groups were evaluated usingrepeated-measure analysis of variance (ANOVA). The Friedman test and Dunn'spost-hoc analysis was performed for non-normally distributed data.Multiple regression analysis and analysis of co-variance (ANCOVA) were used to testthe effect of various physiological variables on oxygenation indices. Continuousoutcome variables were corrected for confounding variables at baseline. Post hoc analyses were performed using Bonferrroni's correction. Variables associatedwith mortality in an analysis of covariance were entered in a multivariate logisticbackward-likelihood ratio regression analysis, to identify predictors of mortality atdifferent end-points. The Hosmer-Lemeshow goodness-of-fit test was used to test thevalidity of the model. Receiver-operating characteristic (ROC) curves were plotted todetermine the best predictor of survival. The value with the best sensitivity,specificity and positive predictive value was selected as the cut-off point topredict survival.
Analyses were performed using SPSS software (version 12; SPSS, Chicago, IL, USA) andMediCalc (Mariakerke, Belgium) for ROC curve analysis. Two-tailed tests forsignificance were used, and a P value less than 0.05 was consideredstatistically significant.
We report the results on 102 consecutive ARDS patients who received HFOV. The median(IQR) duration of ARDS prior to HFOV was 48 hours (24 to 120 hours). The median (IQR)duration of CMV prior to HFOV was 45 hours (9 to 138 hours). Table 1 presents the baseline patient demographics, physiological variables andseverity scores at study entry. Table 2 summarizes patients'outcome and complications from HFOV.
Overall, HFOV was well tolerated with low incidence of new or worsening pneumothoraces,pneumomediastinum or subcutaneous emphysema (2%) and hemodynamic compromise. Twopatients (1.96%) suffered profound hypotension during HFOV.
Effects of HFOV on gas exchange
During the first 72 hours of HFOV, PaO2/FiO2 improvedsignificantly from baseline only in survivors (Figure 1a). Theearliest time-point at which PaO2/FiO2 was statisticallydifferent from baseline in the survivor group was at three hours of HFOV (P <0.05) (Figure 1a). The improvement inPaO2/FiO2 was not determined by the level of CDP (Figure1b) with mean CDP ± SD of 33.9 ± 5.4cmH2O versus 32.0 ± 7.05 cmH2O (P = 0.08),respectively, for survivors and non-survivors. The change inPaO2/FiO2 remained significantly different (P =0.03) between the two outcome groups after adjusting for baseline confounding factorssuch as age, PaO2/FiO2 and CDP. The independence from CDPduring HFOV was further demonstrated by the divergence of OI between the two groupsand the fact that OI improved significantly over the first 72 hours only in survivors(Figure 1c). Analysis of ROC curves identified an improvementof 38% in PaO2/FiO2 and an improvement of >22% in the OIduring the first 72 hours of HFOV as the criteria with the best positive predictivevalues for survival, with respective sensitivities of 93.3% and 87%, specificities of78.3% and 78.0% and positive likelihood ratios of 4.29 and 3.96. Change inPaO2/FiO2 was a better indicator of survival compared withthe change in OI, with an area under the ROC curve of 0.83 (95% CI, 0.71 to 0.92)versus 0.69 (95 % CI 0.55 to 0.8) (P = 0.039, pair-wise comparison of ROCcurves).
Multivariate logistic regression analysis identified the following four independentpredictive factors of mortality at 30 days: 1) days with ARDS prior to HFOV (OR 1.5,95%CI 1.08 to 1.92; P = 0.01); 2) improvement in PaO2/FiO2 in the first 72 hours (OR 0.8, 95 % CI 0.77 to 0.9; P <0.001), 3)age (OR 1.1, 95 % CI 1.02 to 1.14; P = 0.03); and 4) pre-HFOV pH (OR 0.8, 95% CI 0.7 to 0.9; P = 0.004). The change in PaO2/FiO2 and OI after three hours of HFOV was the earliest time point to predictoutcome.
There was an interaction between change in PaO2/FiO2 and theetiology of ARDS, with a greater change in PaO2/FiO2 forpatients with extra-pulmonary ARDS, independent of baselinePaO2/FiO2, which may reflect the different degree of lungrecruitability.
Effects of HFOV on PaCO2
Survivors had a lower baseline PaCO2 with a median (IQR) of 47 mmHg (38.6to 62.2 mmHg) versus 58 mmHg (47.5 to 72.3 mmHg) (P = 0.008) and lowerPaCO2 throughout HFOV treatment (P <0.001) and on return toCMV (Table 3). Overall, PaCO2 decreasedsignificantly throughout the duration of HFOV (P = 0.001, repeated measureANOVA) and, at each time-point, PaCO2 was significantly lower thanbaseline in both groups (P <0.001) (Figure 2a).
There was a trend towards greater reduction in PaCO2 in 'responders' asdefined on the ROC curve by an increase in PaO2/FiO2 ratio of>38 % compared to 'non-responders' (increase in PaO2/FiO2 ratio of <38 %), with a median per cent change (IQR) of -17.4 % (-33.4 to5.48) versus -4.9 % (-19.8 to 11.9) (P = 0.07) (Figure 2b). Furthermore, patients with a worse empirical disease severity scoreshowed a more rapid clearance of PaCO2 during the first 12 hours of HFOV(Figure 2c) despite similar settings of frequency, amplitudeand power (Figure 3). The absolute PaCO2 remainedhigher in the more severe group. This result may suggest that patients with moresevere disease have a greater proportion of recruitable lung and an increase inalveolar ventilation following HFOV. Overall, patients with lower respiratory systemcompliance had a trend towards a greater change in PaCO2 post-SRM (-20.5%versus -2.4 %; P = 0.08), and there was a correlation between change inPaCO2 post-SRM and change in compliance post-HFOV (r2 = 0.6;P = 0.04).
This study aimed to identify potential predictors of survival in patients with severeARDS who received HFOV after failing lung-protective CMV. The key results of our studyare that: 1) an early improvement in PaO2/FiO2 ratio is apredictor of survival at 30 days; 2) patients with more severe disease and lowerrespiratory system compliance pre-HFOV show greater CO2 clearance; and 3) ifthere is no improvement in gas exchange within three hours, patients can be consideredto have failed HFOV and perhaps should be considered for alternative treatment (forexample, extracorporeal support).
Despite theoretical beneficial effects on minimizing lung injury and improving gasexchange, HFOV is not widely utilized because of the lack of evidence supporting a clearsurvival benefit over CMV [25, 26, 34]. Furthermore, available clinical trials do not help the clinician decide whento consider HFOV and, importantly, how long HFOV should be continued to enhance patientsurvival. Our study has a similar scope to the series reported by Adhikari et al. ; however, there are important methodological differences in the HFOVprotocols and the type of recruitment maneuver (that is, a slow stepwise maneuver in ourstudy versus a sustained inflation in Adhikari et al.) used in the two studies.Furthermore, recruitment maneuvers were performed in all patients in our case series,whereas in the study by Adhikari et al only 49.5% of the patients received arecruitment maneuver. The rationale of the stepwise recruitment we used in this studywas similar to the stepwise recruitment used in neonates , in that it allowed for setting of the optimal CDP but it differed in twoaspects. First, we used a fixed FiO2 of 1.0 and response to the recruitmentwas assessed as changes in PaO2. Second, in order to allow time forequilibration of PaO2  and to minimize hemodynamic instability, our protocol required longer timesbetween changes in CDP (ten minutes during the incremental phase and five minutes duringthe decremental phase) compared to the recruitment used in neonates . It is possible that the slower and early recruitment, as performed in thisstudy, can explain the early identification of responders to HFOV.
Although our study is not a randomized comparative study, we believe it identifiesclinically important predictors of clinical outcome within the first few hours ofinitiation of HFOV, possibly in response to the initial SRM. Our study populationincluded, as might be expected for a rescue study, patients with more severe ARDS thanin the MOAT trial where patients received HFOV as a primary ventilation mode  and similar to that of the EMOAT trial  and the recent case series.
In contrast to other published reports [17, 18], in our study gas exchange variables (PaO2/FiO2, andOI) improved significantly only in survivors, and change in PaO2/FiO2 remained significantly different between the two outcome groups after adjustingfor baseline confounding factors. Although the CDP on HFOV was higher than the CDP onCMV, there was no difference in CDP between survivors and non-survivors. Despite similarlevels of CDP, the response to HFOV within the first three hours could identify patientswith a favorable outcome based on PaO2/FiO2 and OI.
An important factor for the response to HFOV may be played by the proportion of patientswith pulmonary versus extra-pulmonary ARDS. Indeed, in this study we show that thelargest change in PaO2/FiO2 post HFOV was seen for extra-pulmonaryARDS whereas little difference in PaO2/FiO2 was seen in pulmonaryARDS. This is consistent with the findings reported by Pachl et al. that showthat oxygenation and recruitment during HFOV are more pronounced in patients withextra-pulmonary ARDS . However, Pachl et al. studied changes in oxygenation undernormocapnic conditions; therefore, no data on the different behavior of PaCO2 in the two types of ARDS are available for comparison with our data. The otherimportant finding of our study is the effect of HFOV on PaCO2. In our study,in contrast to other reports [19, 26], the PaCO2 decreased significantly throughout the duration of HFOVin parallel to an increase in PaO2/FiO2 despite similar settingsof frequency, power and amplitude. We found that in survivors there was both an increasein PaO2/FiO2 and a decrease in PaCO2. In addition,patients who had at least a 38% increase in their PaO2//FiO2 (asidentified by the ROC curve), also showed greater reductions in PaCO2 allowing for a reduction in delta pressure. Patients with a greater diseaseseverity (higher PaCO2, lower compliance and worse gas exchange), showed ahigher rate of clearance in PaCO2 during the first six hours of HFOV. Thesechanges in physiological variables have been described in patients with severe ARDS andhigher potential for lung recruitment .
The increase in intra-thoracic pressure generated during a SRM could have caused areduction in cardiac output and pulmonary blood flow, leading to a decrease in venousadmixture and to an apparent improvement in PaO2/FiO2 in theabsence of true alveolar recruitment [39, 40]. However, this mechanism seems less likely as an explanation for the changesseen in our study, as the cardiac output and oxygen delivery were unchanged followingthe SRM, and therefore the combined improvement in PaO2/FiO2 andPaCO2 leads us to speculate that HFOV facilitated lung recruitment in amanner similar to that described for patients responding to prone positioning .
The 30-day mortality in this study was 56%, comparable to the mortality rate reported inother uncontrolled studies (61.7% [23, 42], 66% , 53% ) but higher than the studies using HFOV as primary intervention (43%  and 37% ) and studies of trauma patients . Multivariate analysis shows that changes in PaO2/FiO2, age, days with ARDS prior to HFOV and baseline pH are independent predictivefactors of mortality. Lung injury is positively associated with duration of mechanicalventilation in both animal and human studies: increased lung injury is associated withreduced likelihood of pulmonary recruitment
In conclusion, this study shows that HFOV is effective in improving oxygenation in someadults with ARDS, particularly when instituted early. This study also shows that changesin PaO2/FiO2 are sensitive criteria to predict survival and thechange in PaCO2 may identify patients with a greater proportion ofrecruitable lung more likely to benefit from HFOV. Patients who do not show improvementin PaO2/FiO2 ratio and oxygenation index within six hours oncommencing HFOV should be considered for extracorporeal support. These data are ofpotential value in aiding decision making.
Further randomized controlled trials powered to detect a difference in survival betweenHFOV strategies are expected. Interpretation of these comparisons will also need to takeinto consideration the number, the duration, and the type of recruitment maneuverscarried out during HFOV and CMV (for example, slow stepwise RMs, as employed in thisstudy versus traditional RMs, with continuous positive airway pressure (CPAP) of 40cmH2O for 40 seconds). The identification of patients likely to benefitfrom HFOV and the identification of physiological variables associated with thepotential for lung recruitment will prove essential to ensure the best use of HFOV inadults with ARDS.
Changes in PaO2/FiO2 early during HFOV are sensitivecriteria to predict survival.
Patients who do not show improvement in the PaO2/FiO2 ratio and OI within three hours should be considered for alternative treatment(for example, extracorporeal support).
The identification of patients likely to benefit from HFOV and theidentification of physiological variables associated with the potential for lungrecruitment will prove essential to ensure the best use of HFOV in adults with ARDS.
analysis of variance
- APACHE II:
Acute Physiology And Chronic Health Evaluation
Acute Respiratory Distress Syndrome
continuous distending pressure
conventional mechanical ventilation
continuous positive airway pressure
fraction of inspired oxygen
high frequency oscillatory ventilation
Molecular Adsorbents Recirculation System
partial pressure of oxygen In arterial blood
partial pressure of carbon dioxide in arterial blood
pulmonary artery wedgepressure
positive end expiratory pressure
peak inspiratory pressure
recombinant human activated protein C (Drotrecogin Alfa Activated)
slow recruitment maneuver.
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The authors wish to thank Prof. Luciano Gattinoni and Dr. Massimo Cressoni for theircritical revision of the manuscript and analysis of the severity score.
The authors declare that they have no competing interests.
LC designed the study, performed the statistical analysis and drafted the manuscript. TSparticipated in data collection. JS participated in the design of the study, datacollection, and data analysis. KL participated in the data collection and analysis. AMparticipated in the design of the study, data analysis and critical revisions of thedraft. RB participated in the design of the study, data analysis and critical revisionsof the draft. All authors read and approved the final manuscript.
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Camporota, L., Sherry, T., Smith, J. et al. Physiological predictors of survival during high-frequency oscillatory ventilation inadults with acute respiratory distress syndrome. Crit Care 17, R40 (2013). https://doi.org/10.1186/cc12550
- Lung Injury
- Acute Respiratory Distress Syndrome
- Oxygenation Index
- Recruitment Maneuver
- Lung Recruitment