<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT01718561</url>
  </required_header>
  <id_info>
    <org_study_id>DIFFICAIR</org_study_id>
    <nct_id>NCT01718561</nct_id>
  </id_info>
  <brief_title>The Difficult Airway Management Trial: &quot;The DIFFICAIR-Trial&quot;</brief_title>
  <acronym>DIFFICAIR</acronym>
  <official_title>Incidence of Unanticipated Difficult Airway Using an Objective Airway Score Versus a Standard Clinical Airway Assessment, The DIFFICAIR Trial - A Cluster-randomized Clinical Trial on 28 Anaesthesia Departments With 70,000 Patients Registered in the Danish Anaesthesia Database</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Hillerod Hospital, Denmark</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Copenhagen Trial Unit, Center for Clinical Intervention Research</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>TrygFonden, Denmark</agency>
      <agency_class>Industry</agency_class>
    </collaborator>
  </sponsors>
  <source>Hillerod Hospital, Denmark</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
  </oversight_info>
  <brief_summary>
    <textblock>
      In general anesthetic the patient is deprived of his awareness and ability to breathe. It is&#xD;
      therefore one of the most important tasks in anesthesia to ensure the patient's airway and&#xD;
      breathing. It has been shown both in Denmark and internationally that failed management of&#xD;
      the patient's airway is the main anesthesia-related cause of death and brain damage.&#xD;
      Therefore, it is very important and highly prioritized among anesthesia personal, to be able&#xD;
      to identify patients with a difficult airway. The aim of &quot;The DIFFICAIR Trial&quot; is to reduce&#xD;
      the incidence of UNEXPECTED difficult airway management by optimizing assessment of the&#xD;
      patient's airway before anesthesia. There is an international consensus on the importance of&#xD;
      proper identification of patients with a difficult airway prior to anesthesia. Enabling&#xD;
      optimal preparation and thus reducing mortality and complications. The DIFFICAIR Trial is a&#xD;
      nationwide multicentre trial with approx. 70,000 patients. 28 of the country's anesthesia&#xD;
      departments is randomized either to airway assessment based on the physicians' clinical&#xD;
      judgment (current practice) or to use an objective risk score for airway evaluations&#xD;
      including anatomical conditions known to be associated with difficult airway management. Data&#xD;
      from The Danish Anesthesia Database is used to compare the success rates of the two methods.&#xD;
      We hope that by using a systematic airway assessment we may reduce the number of unexpected&#xD;
      difficult airway managements and thereby reducing the associated complications and death.&#xD;
      Based on data we will contribute to a national recommendation for airway assessment before&#xD;
      anesthesia.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      The full trial protocol is published in Trials (2013) Volume: 14, Issue: 1, Pages: 347 ISSN:&#xD;
      1745-6215 DOI: 10.1186/1745-6215-14-347 PubMed: 24152537&#xD;
      http://www.trialsjournal.com/content/14/1/347/abstract&#xD;
&#xD;
      Detailed statistical analysis plan for the difficult airway management (DIFFICAIR) trial:&#xD;
&#xD;
      Introduction The difficult airway management trial (DIFFICAIR) is a stratified, parallel&#xD;
      group, cluster (cluster = department) randomized and multicentre trial involving 28&#xD;
      departments of anaesthesia in Denmark. The DIFFICAIR trial compares the effect of two&#xD;
      regimens of preoperative airway assessment on the frequency of unanticipated difficult airway&#xD;
      management.&#xD;
&#xD;
      Prediction of difficult airway management remains a pivotal challenge in anaesthesia.&#xD;
      Difficult tracheal intubation and difficult mask ventilation may cause serious patient&#xD;
      complications [1-6]. By allocating experienced personnel and relevant equipment, better&#xD;
      prediction of difficult airway management may reduce complications and thereby associated&#xD;
      morbidity and mortality. There is no single predictor that is sufficiently valid in&#xD;
      predicting difficult tracheal intubation[7-12]. However, several studies show that by&#xD;
      combining multiple predictors of difficult tracheal intubation, the positive and the negative&#xD;
      predictive value of the assessment increases[12]. In Denmark as well as internationally,&#xD;
      there is no clear recommendation on how to perform airway assessment. Consequently, airway&#xD;
      assessment in Denmark is based exclusively on the individual anaesthesiologist's preoperative&#xD;
      clinical assessment. It is poorly documented how accurately this preoperative clinical&#xD;
      assessment predicts actual airway management conditions.&#xD;
&#xD;
      The &quot;Simplified Airway Risk Index&quot; (SARI)[13] is based on a multivariate model for airway&#xD;
      assessment described by El-Ganzouri and colleagues enabling an estimation of the likelihood&#xD;
      of a difficult direct laryngoscopy. The SARI contains seven individual predictors for a&#xD;
      difficult direct laryngoscopy, each given a weighted score of 0-1 or 0-2. A summarized value&#xD;
      of the SARI score &gt; 3 indicate that a future direct laryngoscopy will be difficult. It is&#xD;
      unknown, whether the SARI score predicts difficult intubation better or worse than a clinical&#xD;
      assessment. The rationale for this trial was to prospectively compare the effect of the SARI&#xD;
      with an unspecified clinical airway assessment on the frequency of unanticipated difficult&#xD;
      airway management.&#xD;
&#xD;
      The target population was adult patients undergoing anaesthesia. Twenty-eight departments of&#xD;
      anaesthesia were randomized to one of two groups. Intervention departments used the SARI&#xD;
      score for preoperative airway assessment. The intervention group additionally did an&#xD;
      assessment of risk factors for difficult mask ventilation as described by Kheterpal and&#xD;
      colleagues[14-16]. Departments in the control group continued normal practice of preoperative&#xD;
      airway assessment. All data were registered in the DAD. A more detailed trial protocol&#xD;
      describing background, design and rationale has been published in TRIALS[17].&#xD;
&#xD;
      In order to prevent outcome reporting bias and results based on data driven analysis it has&#xD;
      been increasingly encouraged to prospectively publish a trial protocol [18, 19]. The same&#xD;
      argument applies for a prospective publication of a statistical analysis plan. Concordantly,&#xD;
      the International Conference on Harmonisation (ICH) of Good Clinical Practice (GCP)&#xD;
      recommends that clinical trials are analysed according to a pre-specified plan[19].&#xD;
&#xD;
      This analysis plan has been written while the data collection from the DIFFICAIR trial was&#xD;
      still on-going and trial data not accessible. The data analysis of the main publication will&#xD;
      follow this plan. The statistical analysis was approved by the DIFFICAIR steering committee&#xD;
      on 29 December 2013. The last day of data collection was 31 December 2013. The involved&#xD;
      departments were given one additional month to ensure registration of all patients in the&#xD;
      Danish Anaesthesia Database. On 31 January 2014 the database was locked and data extracted.&#xD;
      The statistical analysis plan was published on www.clinicaltrials.gov before the last data&#xD;
      entry and before data was extracted and data management commenced.&#xD;
&#xD;
      The DIFFICAIR trial protocol has been written according to the SPIRIT guidelines and has been&#xD;
      public on www.difficair.com since the beginning of the trial and is registered at&#xD;
      www.clinicaltrials.gov (NCT01718561). The Danish Anaesthesia Database and the Danish Society&#xD;
      of Anaesthesiology and Intensive care Medicine (DASAIM) endorsed the trial.&#xD;
&#xD;
      The trial is carried out in accordance with the Helsinki declaration. The Scientific Ethics&#xD;
      Committee of Copenhagen County has declared that it is regarded as a quality assurance&#xD;
      project and thus should not be reported to the committee system (Journal No.: H-3-2012-FSP2).&#xD;
      The trial is approved by The Danish Data Protection Agency (J.No.: 2007-58- 0015/HIH-2011-10,&#xD;
      I-Suite nr: 02079)&#xD;
&#xD;
      Objective The primary aim of the DIFFICAIR trial is to compare the effect of using a&#xD;
      systematic airway assessment with a standard clinical airway assessment on the frequency of&#xD;
      unanticipated difficult airway management. Both are registered in the database. The primary&#xD;
      null hypothesis is • There is no difference in the proportion of unanticipated difficult&#xD;
      intubations when the preoperative airway assessment is based on the SARI score compared with&#xD;
      a preoperative airway assessment based on the individual anaesthesiologist's assessment.&#xD;
&#xD;
      The alternative hypothesis is&#xD;
&#xD;
      • The use of a systematic SARI airway assessment, registration of the SARI and risk factors&#xD;
      for difficult mask ventilation, and continuous education in airway assessment will decrease&#xD;
      the relative risk of a difficult intubation with 30%, corresponding to a NNT of 180 patients.&#xD;
&#xD;
      Methods Randomisation and sample size Our sample size calculation was based on an adjustment&#xD;
      for the stratification and the cluster randomized design [20, 21]. Since there are no&#xD;
      previous records of the trial's primary outcome measure, &quot;unanticipated difficult intubation&quot;&#xD;
      a baseline study was conducted based on data from the Danish Anaesthesia Database (DAD). In&#xD;
      order to reject or detect a 30 % relative risk reduction in the proportions of unanticipated&#xD;
      difficult intubation between the intervention group and the control group approximately 30&#xD;
      departments were required in a 15 months period. Calculations were based on a maximum risk of&#xD;
      type 1 error of 5% and risk of type 2 error of maximum 20 % (80 % power).&#xD;
&#xD;
      A total of 28 departments were included and randomized 1:1 using a computer generated list.&#xD;
      The sample size calculation was based on an average cluster size of 1,611 patients. We&#xD;
      estimated the average cluster size in the DIFFICAIR trial to approximately 2,500 patients,&#xD;
      giving a total of 70,000 included patients during the trial period. The enhanced sample size&#xD;
      allows for a potentially slight loss of clusters according to the power calculation, from 30&#xD;
      to potentially 26. Our sample size estimation might be of a conservative nature, calling for&#xD;
      more clusters than necessary[22].&#xD;
&#xD;
      Populations The DIFFICAIR trial focuses on two essential elements of airway management i.e.&#xD;
      tracheal intubation by direct laryngoscopy and mask ventilation. This statistical analysis&#xD;
      plan will address analysis of the data regarding tracheal intubation. Data analysis regarding&#xD;
      prediction of difficult mask ventilation will be handled in an analogous way, but will not be&#xD;
      further elaborated in the present paper.&#xD;
&#xD;
      The part of the DIFFICAIR trial regarding prediction of difficult intubation comprises two&#xD;
      populations; 1) patients that were primarily attempted intubated by direct laryngoscopy; 2)&#xD;
      patients that were primarily attempted intubated by direct laryngoscopy (population 1) plus&#xD;
      patients anticipated to be difficult to intubate and therefore scheduled for and intubated&#xD;
      with an advanced method (e.g. video laryngoscopic or fibre optic intubation).&#xD;
&#xD;
      The results of population 1 and 2 will be presented in one publication. Due to the extent of&#xD;
      data, further publications presenting data from the DIFFICAIR trial will follow, but further&#xD;
      elaboration on data analysis exceeds the content frame of this paper.&#xD;
&#xD;
      Adjusting and stratification variables Each cluster (department) was randomized to a control&#xD;
      or intervention group, making this the intervention group indicator. The trial site may&#xD;
      account for further intervention heterogeneity and will be used for adjustment in the&#xD;
      analysis of the intervention effect. Further, a stratification variable that grouped the&#xD;
      departments according to whether the proportion of unanticipated difficult intubation at&#xD;
      baseline was ≥ or &lt; 2% will be used for adjustment according to recent evidence of increased&#xD;
      power in the analysis of stratified trials[21].&#xD;
&#xD;
      Assumed confounding covariates We define age; gender; ASA classification; emergency/elective&#xD;
      procedure; Body Mass Index (BMI); and use of neuromuscular blocking agents as covariates that&#xD;
      are possible confounders, necessitating adjusted analyses of the primary outcome and&#xD;
      pre-defined subgroup analyses.&#xD;
&#xD;
      Primary outcomes&#xD;
&#xD;
      The primary outcome measures are:&#xD;
&#xD;
        1. Fraction of unanticipated difficult intubations = all intubations with unanticipated&#xD;
           difficulties [False negative] / all patients primarily (attempted) intubated by direct&#xD;
           laryngoscopy&#xD;
&#xD;
        2. Fraction of unanticipated easy intubations = all intubations with anticipated&#xD;
           difficulties that were easy [False Positive] / all patients primarily (attempted)&#xD;
           intubated by direct laryngoscopy&#xD;
&#xD;
      2. The two primary outcomes are linked and simultaneous low fractions are desirable for the&#xD;
      optimal prediction of a difficult intubation.&#xD;
&#xD;
      Secondary outcomes&#xD;
&#xD;
        1. 48 hour mortality&#xD;
&#xD;
        2. 30 day mortality&#xD;
&#xD;
        3. Fraction = anticipated difficult intubations planned for, and intubated by an advanced&#xD;
           method / all patients (attempted) intubated.&#xD;
&#xD;
        4. Fraction = unanticipated difficult intubations [False Negative] / all difficult&#xD;
           intubations ([False negative] + [True Positive])&#xD;
&#xD;
        5. Sensitivity&#xD;
&#xD;
        6. Specificity&#xD;
&#xD;
        7. Positive predictive value&#xD;
&#xD;
        8. Negative predictive value&#xD;
&#xD;
        9. Positive Likelihood Ratio = (Sensitivity / (1-Specificity))&#xD;
&#xD;
       10. Negative Likelihood Ratio = ((1-Sensitivity) / Specificity)&#xD;
&#xD;
       11. The Receiver Operating Characteristic (ROC) curve. A graphical representation of&#xD;
           sensitivity as a function of (1-Specificity).&#xD;
&#xD;
      Outcomes 5-11 are measured for prediction of difficult intubation for both intervention&#xD;
      groups.&#xD;
&#xD;
      Datapoints Baseline covariates&#xD;
&#xD;
      Individual level:&#xD;
&#xD;
        1. Sex&#xD;
&#xD;
        2. Age&#xD;
&#xD;
        3. Height&#xD;
&#xD;
        4. Weight&#xD;
&#xD;
        5. BMI&#xD;
&#xD;
        6. American Society of Anesthesiologists (ASA) Classification&#xD;
&#xD;
        7. Use of neuromuscular blocking agents&#xD;
&#xD;
        8. Hospital unit&#xD;
&#xD;
        9. Region&#xD;
&#xD;
       10. Anticipated difficult tracheal intubation&#xD;
&#xD;
       11. Anticipated difficult mask ventilation&#xD;
&#xD;
       12. Scheduled airway&#xD;
&#xD;
       13. Priority; Acute/Elective&#xD;
&#xD;
       14. Surgical procedure codes&#xD;
&#xD;
       15. Intubation score&#xD;
&#xD;
       16. Mask ventilation score&#xD;
&#xD;
      Intervention covariates&#xD;
&#xD;
        1. Mouth opening&#xD;
&#xD;
        2. Thyro-mental distance&#xD;
&#xD;
        3. Modified Mallampati classification&#xD;
&#xD;
        4. Jaw protrusion&#xD;
&#xD;
        5. Neck mobility&#xD;
&#xD;
        6. Previous difficult airway management&#xD;
&#xD;
        7. Number of completed risk factors&#xD;
&#xD;
        8. The calculated SARI score&#xD;
&#xD;
        9. Dichotomised SARI score (&lt; or ≥ 4)&#xD;
&#xD;
       10. Snoring&#xD;
&#xD;
       11. Sleep apnoea&#xD;
&#xD;
       12. Presence of beard&#xD;
&#xD;
       13. Changes in the neck due to radiation&#xD;
&#xD;
      Cluster level summaries&#xD;
&#xD;
        1. Mean cluster size&#xD;
&#xD;
        2. Mean number of intubated patients&#xD;
&#xD;
        3. Fraction of private hospitals&#xD;
&#xD;
        4. Mean fraction of unanticipated difficult intubation&#xD;
&#xD;
        5. Age&#xD;
&#xD;
        6. BMI&#xD;
&#xD;
        7. ASA classification&#xD;
&#xD;
      Definition of difficult intubation In the DAD an intubation score is programmed based on&#xD;
      numbers of intubation attempts and use of equipment.&#xD;
&#xD;
        1. A maximum of two intubation attempts - Only by direct laryngoscopy&#xD;
&#xD;
        2. A maximum of two intubation attempts in which other intubation equipment or assistive&#xD;
           devices for direct laryngoscopy is used (e.g. videolaryngoscope)&#xD;
&#xD;
        3. Three intubation attempts or more - Regardless of intubation method&#xD;
&#xD;
        4. Intubation failed despite attempts&#xD;
&#xD;
      Tracheal intubation by direct laryngoscopy is pre-defined in the DAD as unproblematic by a&#xD;
      score = 1 and difficult by a score ≥ 2. In our primary analyses and sample size calculation&#xD;
      we will use the same definition as DAD.&#xD;
&#xD;
      General analysis principles&#xD;
&#xD;
        1. Unless otherwise stated, all main analyses will compare the two intervention groups&#xD;
           using intention-to-treat (ITT) [23].&#xD;
&#xD;
        2. In order to ensure a correct type 1 error rate, all main analyses will account for the&#xD;
           clustered design of the trial and the stratification variable [24-26]. Analyses will be&#xD;
           based on individual patient level data but clustering of patients and the stratification&#xD;
           variable will be accounted for in a mixed effects model.&#xD;
&#xD;
        3. In all analyses a maximum level of 5 % (two sided) type 1 error will be regarded as&#xD;
           statistically significant unless otherwise stated&#xD;
&#xD;
        4. Main analyses will be according to ITT adjusted for cluster and stratification&#xD;
           variables. Sensitivity analyses will be performed adjusted and unadjusted for the prior&#xD;
           listed potential confounding covariates. We will discuss if results differ from the main&#xD;
           analyses. The conclusion of the trial will be based on the primary analyses.&#xD;
&#xD;
        5. Test of interaction will be applied for subgroup analyses.&#xD;
&#xD;
        6. Risks are reported as relative risks. When relative risks are calculated from odds&#xD;
           ratios with 95% confidence interval (CI) it will be done according to Zhang et Yu[27].&#xD;
&#xD;
        7. For missing data exceeding a rate of 5 %, and with a statistical significant Little's&#xD;
           test, indicating that the missing data is not a completely random sample of the total&#xD;
           data, point estimates with 95 % CI will be calculated using a worst/best case scenario&#xD;
           imputation on the missing values. If the imputation of a worst/best case scenario&#xD;
           implies different conclusions, multiple imputations will be performed on the missing&#xD;
           values assuming missingness at random[28]. Unadjusted and complete case analyses will&#xD;
           also be presented.&#xD;
&#xD;
        8. In order to avoid rejecting a true null hypothesis we will address the problem of&#xD;
           multiplicity by Bonferroni adjustments on the secondary outcome measures. If unadjusted&#xD;
           analyses are insignificant (P&gt;0,05), Bonferroni adjustments will not be applied. In case&#xD;
           the adjustment changes an unadjusted significant P-value to a non-significant P-value,&#xD;
           this will be discussed.&#xD;
&#xD;
        9. To ensure complete objectivity, the statistician will be blinded for the intervention&#xD;
           group in the primary outcome analysis. After data collection, a third party data manager&#xD;
           will generate a complete data set with blinded coding of the intervention groups and&#xD;
           other variables possibly revealing the intervention. The statistician performs the&#xD;
           primary outcome analysis on this data set. If the primary outcome differs between groups&#xD;
           we will construct different conclusions reflecting the results, considering that&#xD;
           significant differences of the intervention could be both of benefit or harm. After&#xD;
           writing the conclusions, we will uncover the code of the blinding, and subsequently the&#xD;
           correct conclusion will be employed[29].&#xD;
&#xD;
      Statistical analyses Trial profile The flow of study participants will be displayed in a&#xD;
      Consolidated Standards of Reporting Trials (CONSORT) diagram at a cluster level and at&#xD;
      individual level. The number of clusters fulfilling the inclusion criterion and the number of&#xD;
      clusters included in primary and secondary analyses will be presented. The number of patients&#xD;
      who fulfilled study inclusion criteria as well as the number included in the primary and&#xD;
      secondary analyses will be reported. Reasons for exclusions of clusters and patients in the&#xD;
      primary and secondary analyses will be reported.&#xD;
&#xD;
      Primary outcome Frequencies and percentages per group will be reported with 95 % CI. The&#xD;
      primary outcome is presented as odds ratios and relative risk ratios.&#xD;
&#xD;
      The first analysis of the primary outcome will be adjusted for the stratification- and the&#xD;
      cluster-variable performed according to the ITT principle including patients that met the&#xD;
      inclusion- and not the exclusion-criteria. A logistic regression including a mixed effect&#xD;
      model will be used. Intervention group and stratification variable are regarded as fixed&#xD;
      effects and trial site is regarded as random effects in the model.&#xD;
&#xD;
      The second analysis of the primary outcome will be adjusted for the stratification- and&#xD;
      cluster-variables as well as baseline covariates assumed as confounders incorporated in a&#xD;
      mixed effect model.&#xD;
&#xD;
      The third analysis of the primary outcome will compare the patients in the control group that&#xD;
      met the inclusion- and not the exclusion-criteria with patients in the intervention group who&#xD;
      received the protocoled intervention. That is, a per protocol analysis of control group vs.&#xD;
      the subgroup in the intervention group that had a sufficiently registered SARI. Interaction&#xD;
      test will be performed in the intervention group between patients receiving&#xD;
      sufficient/insufficient SARI registration.&#xD;
&#xD;
      In an alternative sensitivity analysis of the first analysis of the primary outcome we will&#xD;
      employ a different cut-off value for difficult intubation using ≥ 3 instead of ≥ 2 as the&#xD;
      definition of difficult intubation.&#xD;
&#xD;
      Secondary outcomes Frequencies, proportions, percentages, odds and risk ratios are presented&#xD;
      with 95 % CI for each group. A chi- squared test is used to assess the effect of the&#xD;
      intervention on binary outcomes. For categorical outcomes and the adjusted analyses logistic&#xD;
      regression analysis will be performed.&#xD;
&#xD;
      Baseline comparisons of patient characteristics Baseline characteristics are presented for&#xD;
      each intervention group. Frequencies, proportions and percentages will be used to summarize&#xD;
      discrete variables. In case of missing values, percentages are presented with the actual&#xD;
      denominator and otherwise calculated according to the number of participating patients.&#xD;
      Continuous variables are summarized using standard measures of central tendency and&#xD;
      dispersion using either mean ± SD for data with normal distribution or median and&#xD;
      interquartile range for non-normally distributed data.&#xD;
&#xD;
      Baseline comparisons of cluster characteristics Cluster characteristics are presented for&#xD;
      each group, control and intervention. Unless otherwise stated, data will be presented as&#xD;
      means with SD for data with normal distribution or median and interquartile range for&#xD;
      non-normally distributed data.&#xD;
&#xD;
      Outline of figures and tables The first figure will be a CONSORT flow chart on individual&#xD;
      patient level and cluster level. The second figure will illustrate the SARI score and&#xD;
      tutorial instruments. The third figure will demonstrate the registration in the DAD,&#xD;
      including the intubation score. The fourth figure will present baseline data from each&#xD;
      intervention group on individual and cluster level and the fifth figure will be outlining the&#xD;
      main outcome results for each intervention group.&#xD;
&#xD;
      Discussion In order to avoid outcome reporting bias and data driven results this paper&#xD;
      presents the detailed statistical analysis plan for the main publication of the DIFFICAIR&#xD;
      trial. The DIFFICAIR trial raises two important questions i.e. is it possible via the&#xD;
      intervention to reduce the frequency of difficult intubation and/or difficult mask&#xD;
      ventilation? This plan only addresses the statistical analysis of the population of intubated&#xD;
      patients. This is because our sample size calculations were based on the same population; the&#xD;
      SARI was developed as a prediction tool for difficult intubation; and due to the extent of&#xD;
      data.&#xD;
&#xD;
      By adjusting our primary outcome analysis for different design variables, such as clustering&#xD;
      and stratification we strive to eliminate inflated type 1 error rates as a consequence of the&#xD;
      trial design. A mixed effect model is applied based on an evaluation of each variable as&#xD;
      having random or fixed effects[30, 31].&#xD;
&#xD;
      When multiple comparisons are performed between two groups, you may risk accepting an&#xD;
      intervention effect erroneously (Type 1 error). There are several approaches that deal with&#xD;
      multiple testing. We chose to employ a Bonferroni adjustment on the secondary outcome&#xD;
      measures in order to evaluate, identify and discuss dubious significant outcomes that may be&#xD;
      due to statistical multiplicity.&#xD;
&#xD;
      The value of a diagnostic test is usually presented as sensitivity and specificity. We have&#xD;
      chosen (1 - total accuracy) i.e. the proportion of unanticipated difficult intubations (False&#xD;
      Negative, FN) and the proportion of unanticipated easy intubations (False Positive, FP). Both&#xD;
      scenarios are of clinical relevance since the FN are at risk of hypoxia, increased morbidity&#xD;
      and even death, while the FP are at risk of being imposed unnecessary discomfort by e.g.&#xD;
      awake intubation. At the same time, both the FN and FP can take up unnecessary resources.&#xD;
      Sensitivity and specificity are more difficult to interpret intuitively. Consequently, we&#xD;
      chose to present more transparent primary outcomes. Using proportions of unanticipated&#xD;
      difficult intubation allowed us to perform a baseline cohort study, on which we based our&#xD;
      sample size and power calculations.&#xD;
&#xD;
      By publishing this paper where we pre-specify our methods and analyses, it is our hope that&#xD;
      the results from the DIFFICAIR trial will be as transparent and robust as possible.&#xD;
&#xD;
      Conclusion This paper presents the principles of analyses used in the DIFFICAIR trial for the&#xD;
      first publication of the main outcomes for the population of intubated patients. Our approach&#xD;
      aims to minimize the risk of data-driven results and outcome reporting bias.&#xD;
&#xD;
      References&#xD;
&#xD;
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&#xD;
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&#xD;
        9. Lundstrøm LH, Møller AM, Rosenstock C, Astrup G, Wetterslev J: High body mass index is a&#xD;
           weak predictor for difficult and failed tracheal intubation: a cohort study of 91,332&#xD;
           consecutive patients scheduled for direct laryngoscopy registered in the Danish&#xD;
           Anesthesia Database. Anesthesiology 2009, 107:266-274.&#xD;
&#xD;
       10. Lundstrøm LH, Møller AM, Rosenstock C, Astrup G, Gätke MR, Wetterslev J: Avoidance of&#xD;
           neuromuscular blocking agents may increase the risk of difficult tracheal intubation: a&#xD;
           cohort study of 103,812 consecutive adult patients recorded in the Danish Anaesthesia&#xD;
           Database. Br J Anaesth 2009, 103:283-90.&#xD;
&#xD;
       11. Lundstrøm LH, Møller AM, Rosenstock C, Astrup G, Gätke MR, Wetterslev J: A documented&#xD;
           previous difficult tracheal intubation as a prognostic test for a subsequent difficult&#xD;
           tracheal intubation in adults. Anaesthesia 2009, 64:1081-8.&#xD;
&#xD;
       12. Shiga T, Wajima Z, Inoue T, Sakamoto S, Sakamoto A: Predicting difficult intubation in&#xD;
           apparently normal patients. Anesthesiology 2005, 103:429-437.&#xD;
&#xD;
       13. El-Ganzouri AR, McCarthy RJ, Tuman KJ, Tanck EN, Ivankovich AD: Preoperative airway&#xD;
           assessment: predictive value of a multivariate risk index. Anesth Analg 1996,&#xD;
           82:1197-1204.&#xD;
&#xD;
       14. Kheterpal S, Han R, Tremper KK, Shanks AM, Tait AR, O'Reilly M, Ludwig TA, Martin L:&#xD;
           Incidence and predictors of difficult and impossible mask ventilation. Anesthesiology&#xD;
           2006, 105:885-891.&#xD;
&#xD;
       15. Kheterpal S, Martin L, Shanks AM, Tremper KK: Prediction and outcomes of impossible mask&#xD;
           ventilation: a review of 50,000 anesthetics. Anesthesiology 2009, 110:891-897.&#xD;
&#xD;
       16. Kheterpal S, Healy D, Aziz M: Incidence, Predictors, and Outcome of Difficult Mask&#xD;
           Ventilation Combined with Difficult Laryngoscopy: A Report from the Multicenter&#xD;
           Perioperative Outcomes Group. Anesthesiology 2013:1-10.&#xD;
&#xD;
       17. Nørskov AK, Rosenstock CV, Wetterslev J, Lundstrøm LH: Incidence of unanticipated&#xD;
           difficult airway using an objective airway score versus a standard clinical airway&#xD;
           assessment: the DIFFICAIR trial -- trial protocol for a cluster randomized clinical&#xD;
           trial. Trials 2013, 14:347.&#xD;
&#xD;
       18. Chan A-W, Tetzlaff JM, Altman DG, Laupacis A, Gøtzsche PC, Hro A, Mann H, Dickersin K,&#xD;
           Berlin JA, Dore CJ, Parulekar WR, Summerskill WSM, Groves T, Schulz KF, Sox HC, Rockhold&#xD;
           FW, Rennie D, Moher D, Krleža-Jerić K, Hróbjartsson A, Doré CJ: Research and Reporting&#xD;
           Methods SPIRIT 2013 Statement : Defining Standard Protocol Items for Clinical Trials.&#xD;
           Ann Intern Med 2013, 158:200-7.&#xD;
&#xD;
       19. Dwan K, Gamble C, Williamson PR, Altman DG: Reporting of clinical trials: a review of&#xD;
           research funders' guidelines. Trials 2008, 9:66.&#xD;
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       20. Hayes RJ, Bennett S: Simple sample size calculation for cluster-randomized trials. Int J&#xD;
           Epidemiol 1999, 28:319-26.&#xD;
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       21. Kahan B, Morris T: Reporting and analysis of trials using stratified randomisation in&#xD;
           leading medical journals: review and reanalysis. BMJ 2012, 345:e5840.&#xD;
&#xD;
       22. Crespi CM, Wong WK, Wu S: A new dependence parameter approach to improve the design of&#xD;
           cluster randomized trials with binary outcomes. Clin Trials 2011, 8:687-98.&#xD;
&#xD;
       23. Fergusson D, Aaron SD, Guyatt G, Hébert P: Post-randomisation exclusions: the intention&#xD;
           to treat principle and excluding patients from analysis. BMJ 2002, 325:652-4.&#xD;
&#xD;
       24. Klar N, Donner A: Current and future challenges in the design and analysis of cluster&#xD;
           randomization trials. Stat Med 2001, 20:3729-3740.&#xD;
&#xD;
       25. Hayes RJ, Moulton LH: Cluster Randomised Trials (Chapman &amp; Hall/CRC Interdisciplinary&#xD;
           Statistics). Chapman and Hall/CRC; 2009:338.&#xD;
&#xD;
       26. Kahan BC, Morris TP: Assessing potential sources of clustering in individually&#xD;
           randomised trials. BMC Med Res Methodol 2013, 13:58.&#xD;
&#xD;
       27. Zhang J, Yu KF: What's the relative risk? A method of correcting the odds ratio in&#xD;
           cohort studies of common outcomes. JAMA 1998, 280:1690-1.&#xD;
&#xD;
       28. Schafer JL: Multiple imputation: a primer. Stat Methods Med Res 1999, 8:3-15.&#xD;
&#xD;
       29. Gøtzsche PC: Blinding during data analysis and writing of manuscripts. Control Clin&#xD;
           Trials 1996, 17:285-90.&#xD;
&#xD;
       30. Kahan BC, Morris TP: Adjusting for multiple prognostic factors in the analysis of&#xD;
           randomised trials. BMC Med Res Methodol 2013, 13:99.&#xD;
&#xD;
       31. Kahan BC, Morris TP: Analysis of multicentre trials with continuous outcomes: when and&#xD;
           how should we account for centre effects? Stat Med 2013, 32:1136-49.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date>October 2012</start_date>
  <completion_date type="Actual">January 2014</completion_date>
  <primary_completion_date type="Actual">December 2013</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>Randomized</allocation>
    <intervention_model>Parallel Assignment</intervention_model>
    <primary_purpose>Prevention</primary_purpose>
    <masking>Single (Outcomes Assessor)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Fraction of unanticipated difficult intubations = intubations with unanticipated difficulties [False negative] / all patients primarily (attempted) intubated by direct laryngoscopy</measure>
    <time_frame>From October 2012 to December 2013</time_frame>
    <description>This outcome measure will also be assessed for mask ventilation instead of intubation</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Fraction of unanticipated easy intubations = intubations with anticipated difficulties that were easy [False Positive] / all patients primarily (attempted) intubated by direct laryngoscopy</measure>
    <time_frame>From October 2012 to December 2013</time_frame>
    <description>This outcome measure will also be assessed for mask ventilation instead of intubation</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>48 hour mortality</measure>
    <time_frame>From October 2012 to October 2013</time_frame>
    <description>This outcome measure will be assessed for all three cohorts</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>30-day mortality</measure>
    <time_frame>From October 2012 to October 2013</time_frame>
    <description>This outcome measure will be assessed for all three cohorts</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>unexpected difficult intubation [False Negative] / actual difficult intubation ([False-negative] + [True Positive]).</measure>
    <time_frame>From October 2012 to October 2013</time_frame>
    <description>This outcome measure will also be assessed for mask ventilation instead of intubation (cohort 3)</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Sensitivity: [True Positive] / ([Sand Positive] + [False Negative]).</measure>
    <time_frame>From October 2012 to October 2013</time_frame>
    <description>This outcome measure will be assessed for all three cohorts</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Specificity: [True Negative] / ([True Negative] + [False Positive])</measure>
    <time_frame>From October 2012 to October 2013</time_frame>
    <description>This outcome measure will be assessed for all three cohorts</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Positive Predictive Value: [True Positive] / ([Sand Positive] + [False Positive])</measure>
    <time_frame>From October 2012 to October 2013</time_frame>
    <description>This outcome measure will be assessed for all three cohorts</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Negative predictive value: [True Negative] / ([True Negative] + [False Negative])</measure>
    <time_frame>From October 2012 to October 2013</time_frame>
    <description>This outcome measure will be assessed for all three cohorts</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Positive Likelihood Ratio = (Sensitivity / (1-specificity))</measure>
    <time_frame>From October 2012 to October 2013</time_frame>
    <description>This outcome measure will be assessed for all three cohorts</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>ROC curve</measure>
    <time_frame>From October 2012 to October 2013</time_frame>
    <description>&quot;The receiver operating characteristic&quot; curve. Graphical representation of the sensitivity as a function of (1-specificity). Suitable for comparison of predictive models.&#xD;
This outcome measure will be assessed for all three cohorts</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>• Fraction = intubations anticipated to be difficult, thus planned for, and intubated by, an advanced method / all patients (attempted) intubated.</measure>
    <time_frame>October 2012 - December 2013</time_frame>
  </secondary_outcome>
  <number_of_arms>2</number_of_arms>
  <enrollment type="Actual">76058</enrollment>
  <condition>Airway Management</condition>
  <condition>Intubation, Intratracheal</condition>
  <arm_group>
    <arm_group_label>Control</arm_group_label>
    <arm_group_type>No Intervention</arm_group_type>
    <description>Usual clinical airway evaluation and usual registration in Danish Anaesthesia Database (without SARI registration)</description>
  </arm_group>
  <arm_group>
    <arm_group_label>SARI</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Registration of Modified SARI score and predictors for difficult mask ventilation in Danish Anaesthesia Database</description>
  </arm_group>
  <intervention>
    <intervention_type>Procedure</intervention_type>
    <intervention_name>SARI</intervention_name>
    <description>The use of Modified Simplified Airway Risk Index (SARI) as preoperative airway assessment and assessment of risk factor for difficult mask ventilation. Registration in Danish Anesthesia Database</description>
    <arm_group_label>SARI</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
        Cohort 1:&#xD;
&#xD;
        Patients with a preoperative airway plan of either&#xD;
&#xD;
          -  Non / unknown&#xD;
&#xD;
          -  Spontaneous respiration&#xD;
&#xD;
          -  Mask Ventilation&#xD;
&#xD;
          -  Laryngeal Mask etc.. (any kind)&#xD;
&#xD;
          -  Intubation by direct laryngoscopy&#xD;
&#xD;
        and primarily (attempted) intubated by direct laryngoscopy&#xD;
&#xD;
        Cohort 2:&#xD;
&#xD;
        All patients in cohort 1, and patients with an airway plan of either&#xD;
&#xD;
          -  Intubation with video laryngoscope&#xD;
&#xD;
          -  Intubation with flexible fiber optic scope&#xD;
&#xD;
          -  Intubation by another method (Fastrach, Trachlight, etc.).&#xD;
&#xD;
        which was expected difficult to intubate by direct laryngoscopy&#xD;
&#xD;
        Cohort 3:&#xD;
&#xD;
        All patients who are mask ventilated.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Children under 15 years&#xD;
&#xD;
          -  Patients who can not co-operate for the examination (unconscious, demented, severely&#xD;
             traumatized, etc..)&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>15 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Anders K Nørskov, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Hillerod Hospital, Denmark</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Department of anesthesia, Hillerød Hospital</name>
      <address>
        <city>Hillerød</city>
        <state>Region Hovedstaden</state>
        <zip>3400</zip>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Abdominalcentret Rigshospitalet</name>
      <address>
        <city>Copenhagen</city>
        <zip>2100</zip>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Bispebjerg hospital</name>
      <address>
        <city>Copenhagen</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Hovedorto centret Rigshospitalet</name>
      <address>
        <city>Copenhagen</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Juliane Marie centret Rigshospitalet</name>
      <address>
        <city>Copenhagen</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Neurocentret Rigshospitalet</name>
      <address>
        <city>Copenhagen</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>thoraxcentret Rigshospitalet</name>
      <address>
        <city>Copenhagen</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Aleris-Hamlet</name>
      <address>
        <city>Esbjerg</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Frederiksberg hospital</name>
      <address>
        <city>Frederiksberg</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Glostrup Hospital</name>
      <address>
        <city>Glostrup</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Haderslev Hospital</name>
      <address>
        <city>Haderslev</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Bekkevold klinikken</name>
      <address>
        <city>Hellerup</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Herlev Hospital</name>
      <address>
        <city>Herlev</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Aleris-Hamlet</name>
      <address>
        <city>Herning</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Kolding sygehus</name>
      <address>
        <city>Kolding</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Kollund privathospital</name>
      <address>
        <city>Kollund</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Københavnsprivathospital</name>
      <address>
        <city>Lyngby</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Nykøbing falster sygehus</name>
      <address>
        <city>Nykøbing Falster</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Næstved Hospital</name>
      <address>
        <city>Næstved</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Roskilde Sygehus</name>
      <address>
        <city>Roskilde</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Bornholm sygehus</name>
      <address>
        <city>Rønne</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Aleris-Hamlet</name>
      <address>
        <city>Søborg</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Sønder sygehus</name>
      <address>
        <city>Sønderborg</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Thisted sygehus</name>
      <address>
        <city>Thisted</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Vejle Sygehus</name>
      <address>
        <city>Vejle</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Åbenrå sygehus</name>
      <address>
        <city>Åbenrå</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Aleris-Hamlet</name>
      <address>
        <city>Ålborg</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Aleris-Hamlet</name>
      <address>
        <city>Århus</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>Denmark</country>
  </location_countries>
  <verification_date>February 2014</verification_date>
  <study_first_submitted>October 29, 2012</study_first_submitted>
  <study_first_submitted_qc>October 30, 2012</study_first_submitted_qc>
  <study_first_posted type="Estimate">October 31, 2012</study_first_posted>
  <last_update_submitted>February 7, 2014</last_update_submitted>
  <last_update_submitted_qc>February 7, 2014</last_update_submitted_qc>
  <last_update_posted type="Estimate">February 10, 2014</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Hillerod Hospital, Denmark</investigator_affiliation>
    <investigator_full_name>Anders Nørskov</investigator_full_name>
    <investigator_title>MD, clinical assistant</investigator_title>
  </responsible_party>
  <keyword>Airway assessment</keyword>
  <keyword>Intubation</keyword>
  <keyword>Mask ventilation</keyword>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT01718561
org study id: DIFFICAIR
nct id: NCT01718561
lead sponsor: 
collaborator: 
collaborator: 
has dmc: No
In general anesthetic the patient is deprived of his awareness and ability to breathe. It is
      therefore one of the most important tasks in anesthesia to ensure the patient's airway and
      breathing. It has been shown both in Denmark and internationally that failed management of
      the patient's airway is the main anesthesia-related cause of death and brain damage.
      Therefore, it is very important and highly prioritized among anesthesia personal, to be able
      to identify patients with a difficult airway. The aim of "The DIFFICAIR Trial" is to reduce
      the incidence of UNEXPECTED difficult airway management by optimizing assessment of the
      patient's airway before anesthesia. There is an international consensus on the importance of
      proper identification of patients with a difficult airway prior to anesthesia. Enabling
      optimal preparation and thus reducing mortality and complications. The DIFFICAIR Trial is a
      nationwide multicentre trial with approx. 70,000 patients. 28 of the country's anesthesia
      departments is randomized either to airway assessment based on the physicians' clinical
      judgment (current practice) or to use an objective risk score for airway evaluations
      including anatomical conditions known to be associated with difficult airway management. Data
      from The Danish Anesthesia Database is used to compare the success rates of the two methods.
      We hope that by using a systematic airway assessment we may reduce the number of unexpected
      difficult airway managements and thereby reducing the associated complications and death.
      Based on data we will contribute to a national recommendation for airway assessment before
      anesthesia.
The full trial protocol is published in Trials (2013) Volume: 14, Issue: 1, Pages: 347 ISSN:
      1745-6215 DOI: 10.1186/1745-6215-14-347 PubMed: 24152537
      http://www.trialsjournal.com/content/14/1/347/abstract

      Detailed statistical analysis plan for the difficult airway management (DIFFICAIR) trial:

      Introduction The difficult airway management trial (DIFFICAIR) is a stratified, parallel
      group, cluster (cluster = department) randomized and multicentre trial involving 28
      departments of anaesthesia in Denmark. The DIFFICAIR trial compares the effect of two
      regimens of preoperative airway assessment on the frequency of unanticipated difficult airway
      management.

      Prediction of difficult airway management remains a pivotal challenge in anaesthesia.
      Difficult tracheal intubation and difficult mask ventilation may cause serious patient
      complications [1-6]. By allocating experienced personnel and relevant equipment, better
      prediction of difficult airway management may reduce complications and thereby associated
      morbidity and mortality. There is no single predictor that is sufficiently valid in
      predicting difficult tracheal intubation[7-12]. However, several studies show that by
      combining multiple predictors of difficult tracheal intubation, the positive and the negative
      predictive value of the assessment increases[12]. In Denmark as well as internationally,
      there is no clear recommendation on how to perform airway assessment. Consequently, airway
      assessment in Denmark is based exclusively on the individual anaesthesiologist's preoperative
      clinical assessment. It is poorly documented how accurately this preoperative clinical
      assessment predicts actual airway management conditions.

      The "Simplified Airway Risk Index" (SARI)[13] is based on a multivariate model for airway
      assessment described by El-Ganzouri and colleagues enabling an estimation of the likelihood
      of a difficult direct laryngoscopy. The SARI contains seven individual predictors for a
      difficult direct laryngoscopy, each given a weighted score of 0-1 or 0-2. A summarized value
      of the SARI score > 3 indicate that a future direct laryngoscopy will be difficult. It is
      unknown, whether the SARI score predicts difficult intubation better or worse than a clinical
      assessment. The rationale for this trial was to prospectively compare the effect of the SARI
      with an unspecified clinical airway assessment on the frequency of unanticipated difficult
      airway management.

      The target population was adult patients undergoing anaesthesia. Twenty-eight departments of
      anaesthesia were randomized to one of two groups. Intervention departments used the SARI
      score for preoperative airway assessment. The intervention group additionally did an
      assessment of risk factors for difficult mask ventilation as described by Kheterpal and
      colleagues[14-16]. Departments in the control group continued normal practice of preoperative
      airway assessment. All data were registered in the DAD. A more detailed trial protocol
      describing background, design and rationale has been published in TRIALS[17].

      In order to prevent outcome reporting bias and results based on data driven analysis it has
      been increasingly encouraged to prospectively publish a trial protocol [18, 19]. The same
      argument applies for a prospective publication of a statistical analysis plan. Concordantly,
      the International Conference on Harmonisation (ICH) of Good Clinical Practice (GCP)
      recommends that clinical trials are analysed according to a pre-specified plan[19].

      This analysis plan has been written while the data collection from the DIFFICAIR trial was
      still on-going and trial data not accessible. The data analysis of the main publication will
      follow this plan. The statistical analysis was approved by the DIFFICAIR steering committee
      on 29 December 2013. The last day of data collection was 31 December 2013. The involved
      departments were given one additional month to ensure registration of all patients in the
      Danish Anaesthesia Database. On 31 January 2014 the database was locked and data extracted.
      The statistical analysis plan was published on www.clinicaltrials.gov before the last data
      entry and before data was extracted and data management commenced.

      The DIFFICAIR trial protocol has been written according to the SPIRIT guidelines and has been
      public on www.difficair.com since the beginning of the trial and is registered at
      www.clinicaltrials.gov (NCT01718561). The Danish Anaesthesia Database and the Danish Society
      of Anaesthesiology and Intensive care Medicine (DASAIM) endorsed the trial.

      The trial is carried out in accordance with the Helsinki declaration. The Scientific Ethics
      Committee of Copenhagen County has declared that it is regarded as a quality assurance
      project and thus should not be reported to the committee system (Journal No.: H-3-2012-FSP2).
      The trial is approved by The Danish Data Protection Agency (J.No.: 2007-58- 0015/HIH-2011-10,
      I-Suite nr: 02079)

      Objective The primary aim of the DIFFICAIR trial is to compare the effect of using a
      systematic airway assessment with a standard clinical airway assessment on the frequency of
      unanticipated difficult airway management. Both are registered in the database. The primary
      null hypothesis is • There is no difference in the proportion of unanticipated difficult
      intubations when the preoperative airway assessment is based on the SARI score compared with
      a preoperative airway assessment based on the individual anaesthesiologist's assessment.

      The alternative hypothesis is

      • The use of a systematic SARI airway assessment, registration of the SARI and risk factors
      for difficult mask ventilation, and continuous education in airway assessment will decrease
      the relative risk of a difficult intubation with 30%, corresponding to a NNT of 180 patients.

      Methods Randomisation and sample size Our sample size calculation was based on an adjustment
      for the stratification and the cluster randomized design [20, 21]. Since there are no
      previous records of the trial's primary outcome measure, "unanticipated difficult intubation"
      a baseline study was conducted based on data from the Danish Anaesthesia Database (DAD). In
      order to reject or detect a 30 % relative risk reduction in the proportions of unanticipated
      difficult intubation between the intervention group and the control group approximately 30
      departments were required in a 15 months period. Calculations were based on a maximum risk of
      type 1 error of 5% and risk of type 2 error of maximum 20 % (80 % power).

      A total of 28 departments were included and randomized 1:1 using a computer generated list.
      The sample size calculation was based on an average cluster size of 1,611 patients. We
      estimated the average cluster size in the DIFFICAIR trial to approximately 2,500 patients,
      giving a total of 70,000 included patients during the trial period. The enhanced sample size
      allows for a potentially slight loss of clusters according to the power calculation, from 30
      to potentially 26. Our sample size estimation might be of a conservative nature, calling for
      more clusters than necessary[22].

      Populations The DIFFICAIR trial focuses on two essential elements of airway management i.e.
      tracheal intubation by direct laryngoscopy and mask ventilation. This statistical analysis
      plan will address analysis of the data regarding tracheal intubation. Data analysis regarding
      prediction of difficult mask ventilation will be handled in an analogous way, but will not be
      further elaborated in the present paper.

      The part of the DIFFICAIR trial regarding prediction of difficult intubation comprises two
      populations; 1) patients that were primarily attempted intubated by direct laryngoscopy; 2)
      patients that were primarily attempted intubated by direct laryngoscopy (population 1) plus
      patients anticipated to be difficult to intubate and therefore scheduled for and intubated
      with an advanced method (e.g. video laryngoscopic or fibre optic intubation).

      The results of population 1 and 2 will be presented in one publication. Due to the extent of
      data, further publications presenting data from the DIFFICAIR trial will follow, but further
      elaboration on data analysis exceeds the content frame of this paper.

      Adjusting and stratification variables Each cluster (department) was randomized to a control
      or intervention group, making this the intervention group indicator. The trial site may
      account for further intervention heterogeneity and will be used for adjustment in the
      analysis of the intervention effect. Further, a stratification variable that grouped the
      departments according to whether the proportion of unanticipated difficult intubation at
      baseline was ≥ or < 2% will be used for adjustment according to recent evidence of increased
      power in the analysis of stratified trials[21].

      Assumed confounding covariates We define age; gender; ASA classification; emergency/elective
      procedure; Body Mass Index (BMI); and use of neuromuscular blocking agents as covariates that
      are possible confounders, necessitating adjusted analyses of the primary outcome and
      pre-defined subgroup analyses.

      Primary outcomes

      The primary outcome measures are:

        1. Fraction of unanticipated difficult intubations = all intubations with unanticipated
           difficulties [False negative] / all patients primarily (attempted) intubated by direct
           laryngoscopy

        2. Fraction of unanticipated easy intubations = all intubations with anticipated
           difficulties that were easy [False Positive] / all patients primarily (attempted)
           intubated by direct laryngoscopy

      2. The two primary outcomes are linked and simultaneous low fractions are desirable for the
      optimal prediction of a difficult intubation.

      Secondary outcomes

        1. 48 hour mortality

        2. 30 day mortality

        3. Fraction = anticipated difficult intubations planned for, and intubated by an advanced
           method / all patients (attempted) intubated.

        4. Fraction = unanticipated difficult intubations [False Negative] / all difficult
           intubations ([False negative] + [True Positive])

        5. Sensitivity

        6. Specificity

        7. Positive predictive value

        8. Negative predictive value

        9. Positive Likelihood Ratio = (Sensitivity / (1-Specificity))

       10. Negative Likelihood Ratio = ((1-Sensitivity) / Specificity)

       11. The Receiver Operating Characteristic (ROC) curve. A graphical representation of
           sensitivity as a function of (1-Specificity).

      Outcomes 5-11 are measured for prediction of difficult intubation for both intervention
      groups.

      Datapoints Baseline covariates

      Individual level:

        1. Sex

        2. Age

        3. Height

        4. Weight

        5. BMI

        6. American Society of Anesthesiologists (ASA) Classification

        7. Use of neuromuscular blocking agents

        8. Hospital unit

        9. Region

       10. Anticipated difficult tracheal intubation

       11. Anticipated difficult mask ventilation

       12. Scheduled airway

       13. Priority; Acute/Elective

       14. Surgical procedure codes

       15. Intubation score

       16. Mask ventilation score

      Intervention covariates

        1. Mouth opening

        2. Thyro-mental distance

        3. Modified Mallampati classification

        4. Jaw protrusion

        5. Neck mobility

        6. Previous difficult airway management

        7. Number of completed risk factors

        8. The calculated SARI score

        9. Dichotomised SARI score (< or ≥ 4)

       10. Snoring

       11. Sleep apnoea

       12. Presence of beard

       13. Changes in the neck due to radiation

      Cluster level summaries

        1. Mean cluster size

        2. Mean number of intubated patients

        3. Fraction of private hospitals

        4. Mean fraction of unanticipated difficult intubation

        5. Age

        6. BMI

        7. ASA classification

      Definition of difficult intubation In the DAD an intubation score is programmed based on
      numbers of intubation attempts and use of equipment.

        1. A maximum of two intubation attempts - Only by direct laryngoscopy

        2. A maximum of two intubation attempts in which other intubation equipment or assistive
           devices for direct laryngoscopy is used (e.g. videolaryngoscope)

        3. Three intubation attempts or more - Regardless of intubation method

        4. Intubation failed despite attempts

      Tracheal intubation by direct laryngoscopy is pre-defined in the DAD as unproblematic by a
      score = 1 and difficult by a score ≥ 2. In our primary analyses and sample size calculation
      we will use the same definition as DAD.

      General analysis principles

        1. Unless otherwise stated, all main analyses will compare the two intervention groups
           using intention-to-treat (ITT) [23].

        2. In order to ensure a correct type 1 error rate, all main analyses will account for the
           clustered design of the trial and the stratification variable [24-26]. Analyses will be
           based on individual patient level data but clustering of patients and the stratification
           variable will be accounted for in a mixed effects model.

        3. In all analyses a maximum level of 5 % (two sided) type 1 error will be regarded as
           statistically significant unless otherwise stated

        4. Main analyses will be according to ITT adjusted for cluster and stratification
           variables. Sensitivity analyses will be performed adjusted and unadjusted for the prior
           listed potential confounding covariates. We will discuss if results differ from the main
           analyses. The conclusion of the trial will be based on the primary analyses.

        5. Test of interaction will be applied for subgroup analyses.

        6. Risks are reported as relative risks. When relative risks are calculated from odds
           ratios with 95% confidence interval (CI) it will be done according to Zhang et Yu[27].

        7. For missing data exceeding a rate of 5 %, and with a statistical significant Little's
           test, indicating that the missing data is not a completely random sample of the total
           data, point estimates with 95 % CI will be calculated using a worst/best case scenario
           imputation on the missing values. If the imputation of a worst/best case scenario
           implies different conclusions, multiple imputations will be performed on the missing
           values assuming missingness at random[28]. Unadjusted and complete case analyses will
           also be presented.

        8. In order to avoid rejecting a true null hypothesis we will address the problem of
           multiplicity by Bonferroni adjustments on the secondary outcome measures. If unadjusted
           analyses are insignificant (P>0,05), Bonferroni adjustments will not be applied. In case
           the adjustment changes an unadjusted significant P-value to a non-significant P-value,
           this will be discussed.

        9. To ensure complete objectivity, the statistician will be blinded for the intervention
           group in the primary outcome analysis. After data collection, a third party data manager
           will generate a complete data set with blinded coding of the intervention groups and
           other variables possibly revealing the intervention. The statistician performs the
           primary outcome analysis on this data set. If the primary outcome differs between groups
           we will construct different conclusions reflecting the results, considering that
           significant differences of the intervention could be both of benefit or harm. After
           writing the conclusions, we will uncover the code of the blinding, and subsequently the
           correct conclusion will be employed[29].

      Statistical analyses Trial profile The flow of study participants will be displayed in a
      Consolidated Standards of Reporting Trials (CONSORT) diagram at a cluster level and at
      individual level. The number of clusters fulfilling the inclusion criterion and the number of
      clusters included in primary and secondary analyses will be presented. The number of patients
      who fulfilled study inclusion criteria as well as the number included in the primary and
      secondary analyses will be reported. Reasons for exclusions of clusters and patients in the
      primary and secondary analyses will be reported.

      Primary outcome Frequencies and percentages per group will be reported with 95 % CI. The
      primary outcome is presented as odds ratios and relative risk ratios.

      The first analysis of the primary outcome will be adjusted for the stratification- and the
      cluster-variable performed according to the ITT principle including patients that met the
      inclusion- and not the exclusion-criteria. A logistic regression including a mixed effect
      model will be used. Intervention group and stratification variable are regarded as fixed
      effects and trial site is regarded as random effects in the model.

      The second analysis of the primary outcome will be adjusted for the stratification- and
      cluster-variables as well as baseline covariates assumed as confounders incorporated in a
      mixed effect model.

      The third analysis of the primary outcome will compare the patients in the control group that
      met the inclusion- and not the exclusion-criteria with patients in the intervention group who
      received the protocoled intervention. That is, a per protocol analysis of control group vs.
      the subgroup in the intervention group that had a sufficiently registered SARI. Interaction
      test will be performed in the intervention group between patients receiving
      sufficient/insufficient SARI registration.

      In an alternative sensitivity analysis of the first analysis of the primary outcome we will
      employ a different cut-off value for difficult intubation using ≥ 3 instead of ≥ 2 as the
      definition of difficult intubation.

      Secondary outcomes Frequencies, proportions, percentages, odds and risk ratios are presented
      with 95 % CI for each group. A chi- squared test is used to assess the effect of the
      intervention on binary outcomes. For categorical outcomes and the adjusted analyses logistic
      regression analysis will be performed.

      Baseline comparisons of patient characteristics Baseline characteristics are presented for
      each intervention group. Frequencies, proportions and percentages will be used to summarize
      discrete variables. In case of missing values, percentages are presented with the actual
      denominator and otherwise calculated according to the number of participating patients.
      Continuous variables are summarized using standard measures of central tendency and
      dispersion using either mean ± SD for data with normal distribution or median and
      interquartile range for non-normally distributed data.

      Baseline comparisons of cluster characteristics Cluster characteristics are presented for
      each group, control and intervention. Unless otherwise stated, data will be presented as
      means with SD for data with normal distribution or median and interquartile range for
      non-normally distributed data.

      Outline of figures and tables The first figure will be a CONSORT flow chart on individual
      patient level and cluster level. The second figure will illustrate the SARI score and
      tutorial instruments. The third figure will demonstrate the registration in the DAD,
      including the intubation score. The fourth figure will present baseline data from each
      intervention group on individual and cluster level and the fifth figure will be outlining the
      main outcome results for each intervention group.

      Discussion In order to avoid outcome reporting bias and data driven results this paper
      presents the detailed statistical analysis plan for the main publication of the DIFFICAIR
      trial. The DIFFICAIR trial raises two important questions i.e. is it possible via the
      intervention to reduce the frequency of difficult intubation and/or difficult mask
      ventilation? This plan only addresses the statistical analysis of the population of intubated
      patients. This is because our sample size calculations were based on the same population; the
      SARI was developed as a prediction tool for difficult intubation; and due to the extent of
      data.

      By adjusting our primary outcome analysis for different design variables, such as clustering
      and stratification we strive to eliminate inflated type 1 error rates as a consequence of the
      trial design. A mixed effect model is applied based on an evaluation of each variable as
      having random or fixed effects[30, 31].

      When multiple comparisons are performed between two groups, you may risk accepting an
      intervention effect erroneously (Type 1 error). There are several approaches that deal with
      multiple testing. We chose to employ a Bonferroni adjustment on the secondary outcome
      measures in order to evaluate, identify and discuss dubious significant outcomes that may be
      due to statistical multiplicity.

      The value of a diagnostic test is usually presented as sensitivity and specificity. We have
      chosen (1 - total accuracy) i.e. the proportion of unanticipated difficult intubations (False
      Negative, FN) and the proportion of unanticipated easy intubations (False Positive, FP). Both
      scenarios are of clinical relevance since the FN are at risk of hypoxia, increased morbidity
      and even death, while the FP are at risk of being imposed unnecessary discomfort by e.g.
      awake intubation. At the same time, both the FN and FP can take up unnecessary resources.
      Sensitivity and specificity are more difficult to interpret intuitively. Consequently, we
      chose to present more transparent primary outcomes. Using proportions of unanticipated
      difficult intubation allowed us to perform a baseline cohort study, on which we based our
      sample size and power calculations.

      By publishing this paper where we pre-specify our methods and analyses, it is our hope that
      the results from the DIFFICAIR trial will be as transparent and robust as possible.

      Conclusion This paper presents the principles of analyses used in the DIFFICAIR trial for the
      first publication of the main outcomes for the population of intubated patients. Our approach
      aims to minimize the risk of data-driven results and outcome reporting bias.

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allocation: Randomized
intervention model: Parallel Assignment
primary purpose: Prevention
masking: Single (Outcomes Assessor)
measure: Fraction of unanticipated difficult intubations = intubations with unanticipated difficulties [False negative] / all patients primarily (attempted) intubated by direct laryngoscopy
time frame: From October 2012 to December 2013
description: This outcome measure will also be assessed for mask ventilation instead of intubation
measure: Fraction of unanticipated easy intubations = intubations with anticipated difficulties that were easy [False Positive] / all patients primarily (attempted) intubated by direct laryngoscopy
time frame: From October 2012 to December 2013
description: This outcome measure will also be assessed for mask ventilation instead of intubation
measure: 48 hour mortality
time frame: From October 2012 to October 2013
description: This outcome measure will be assessed for all three cohorts
measure: 30-day mortality
time frame: From October 2012 to October 2013
description: This outcome measure will be assessed for all three cohorts
measure: unexpected difficult intubation [False Negative] / actual difficult intubation ([False-negative] + [True Positive]).
time frame: From October 2012 to October 2013
description: This outcome measure will also be assessed for mask ventilation instead of intubation (cohort 3)
measure: Sensitivity: [True Positive] / ([Sand Positive] + [False Negative]).
time frame: From October 2012 to October 2013
description: This outcome measure will be assessed for all three cohorts
measure: Specificity: [True Negative] / ([True Negative] + [False Positive])
time frame: From October 2012 to October 2013
description: This outcome measure will be assessed for all three cohorts
measure: Positive Predictive Value: [True Positive] / ([Sand Positive] + [False Positive])
time frame: From October 2012 to October 2013
description: This outcome measure will be assessed for all three cohorts
measure: Negative predictive value: [True Negative] / ([True Negative] + [False Negative])
time frame: From October 2012 to October 2013
description: This outcome measure will be assessed for all three cohorts
measure: Positive Likelihood Ratio = (Sensitivity / (1-specificity))
time frame: From October 2012 to October 2013
description: This outcome measure will be assessed for all three cohorts
measure: ROC curve
time frame: From October 2012 to October 2013
description: "The receiver operating characteristic" curve. Graphical representation of the sensitivity as a function of (1-specificity). Suitable for comparison of predictive models.
This outcome measure will be assessed for all three cohorts
measure: • Fraction = intubations anticipated to be difficult, thus planned for, and intubated by, an advanced method / all patients (attempted) intubated.
time frame: October 2012 - December 2013
arm group label: Control
arm group type: No Intervention
description: Usual clinical airway evaluation and usual registration in Danish Anaesthesia Database (without SARI registration)
arm group label: SARI
arm group type: Experimental
description: Registration of Modified SARI score and predictors for difficult mask ventilation in Danish Anaesthesia Database
intervention type: Procedure
intervention name: SARI
description: The use of Modified Simplified Airway Risk Index (SARI) as preoperative airway assessment and assessment of risk factor for difficult mask ventilation. Registration in Danish Anesthesia Database
arm group label: SARI
criteria: 
gender: All
minimum age: 15 Years
maximum age: N/A
healthy volunteers: Accepts Healthy Volunteers
last name: Anders K Nørskov, MD
role: Principal Investigator
affiliation: Hillerod Hospital, Denmark
facility: 
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country: Denmark
responsible party type: Principal Investigator
investigator affiliation: Hillerod Hospital, Denmark
investigator full name: Anders Nørskov
investigator title: MD, clinical assistant