<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/NCT02216695</url>
  </required_header>
  <id_info>
    <org_study_id>1.2</org_study_id>
    <nct_id>NCT02216695</nct_id>
  </id_info>
  <brief_title>Epidemiology of Acute Kidney Injury in England - 1998 to 2013</brief_title>
  <official_title>Epidemiology of Acute Kidney Injury in England - 1998 to 2013</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University Hospitals of Derby and Burton NHS Foundation Trust</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>University Hospitals of Derby and Burton NHS Foundation Trust</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
  </oversight_info>
  <brief_summary>
    <textblock>
      The true population incidence of acute kidney injury (AKI), previously called acute renal&#xD;
      failure, in England is not known. A better understanding of the epidemiology of AKI at a&#xD;
      national level is essential to inform initiatives to prevent AKI as well as reduce the&#xD;
      associated morbidity and mortality. The purpose of this study is to combine the national&#xD;
      database of all hospital discharges with national census data to investigate trends in the&#xD;
      incidence of both, AKI not requiring dialysis and AKI requiring dialysis, as well as its&#xD;
      associated mortality and its determinants in England between 1998 and 2013&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Subject Selection and Withdrawal We will identify all cases of AKI by using validated&#xD;
      International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM)&#xD;
      codes in any of he diagnoses codes, in keeping with the objective of the study. Patients with&#xD;
      any of the following codes will be included: N17.0 for acute renal failure with tubular&#xD;
      necrosis, N17.1 for acute renal failure with acute cortical necrosis, N17.2 for acute renal&#xD;
      failure with medullary necrosis, N17.8 for other acute renal failure and N17.9 for acute&#xD;
      renal failure, unspecified. Acute renal failure has been replaced by new terminology, acute&#xD;
      kidney injury, but due to lack of ICD-10-CM codes for AKI, we will use the ICD-10-CM codes&#xD;
      for acute renal failure and henceforth, will be referred to as AKI in this protocol.&#xD;
&#xD;
      Subject Recruitment and Screening We will extract 1998 to 2013 data from the Hospital Episode&#xD;
      Statistics (HES), a data warehouse containing details of all admissions, outpatient&#xD;
      appointments and A&amp;E attendances at National Health Service (NHS) hospitals in England. HES&#xD;
      collects a detailed record for each 'episode' of admitted patient care delivered in England,&#xD;
      either by NHS hospitals, primary care trusts, mental health trusts or delivered in the&#xD;
      independent sector but commissioned by the NHS. These data are collected during a patient's&#xD;
      time in hospital and stored as a large collection of separate records, one for each period of&#xD;
      care, in a secure data warehouse. We will extract secondary diagnosis codes for up to 14&#xD;
      diagnoses available till 2006-07 and up to 20 additional diagnoses from 2007 till 2013. In&#xD;
      addition to demographic data, we will also extract up to 15 procedure codes. To identify AKI&#xD;
      patients requiring dialysis, we will include procedure code of X40.3 for hemodialysis or&#xD;
      X40.4 for hemofiltration in any of the 15 procedures. To exclude patients with chronic kidney&#xD;
      disease starting dialysis, we will exclude patients who had chronic kidney disease (CKD)&#xD;
      stage 5 (N18.5) and end stage renal disease (N18.6) and procedure codes for arteriovenous&#xD;
      fistula (L74.2) or arteriovenous shunt (L74.3) during the inpatient admission (figure 1).&#xD;
      This algorithm has been shown to be sensitive and specific, with a high positive and negative&#xD;
      predictive value (all &gt;90%. Patients who were admitted, but were not discharged during the&#xD;
      study period will not be included in the study.&#xD;
&#xD;
      We will obtain data on patient demographics, hospital characteristics, in-hospital mortality,&#xD;
      disposition, length of stay (LOS), and up to 20 diagnosis and 15 procedure codes that are&#xD;
      based on the ICD-10-CM and Office of Population Censuses and Surveys Classification of&#xD;
      Surgical Operations and Procedures, 4th revision (OPCS-4) from the HES database. To obtain&#xD;
      population incidence of AKI requiring dialysis, we will obtain mid-year populations of&#xD;
      England in each year from 1998 to 2013 from the Office of National Statistics (ONS). We will&#xD;
      also obtain length of stay and mortality for all patients who did not have acute kidney&#xD;
      injury coded as N17 in any of the diagnoses codes, in England over the same time period.&#xD;
&#xD;
      Patients will not be contacted. This study will not obtain informed consent from the&#xD;
      patients' as we will be working with anonymous patient data. No screening requirements&#xD;
      (laboratory or diagnostic testing) are necessary to meet the inclusion or exclusion criteria.&#xD;
      Unique Subject Identification numbers are already allocated to the patients and the HES&#xD;
      database does not include any patient's name or hospital number.&#xD;
&#xD;
      Sample Size Determination The data from HES will be extracted for the period between April&#xD;
      1998 and March 2013. HES data is collected during a patients' time at hospital and is&#xD;
      submitted to allow hospitals to be paid for the care they deliver. As this is a retrospective&#xD;
      population cohort study using a national database, all cases of AKI as defined by the&#xD;
      inclusion criteria, from the HES database will be used.&#xD;
&#xD;
      Statistical Methods All analyses will be performed using validated statistical software. Data&#xD;
      during the 15-year period will be divided into three 5-yr periods (April 1988 to March 2003,&#xD;
      April 2003 to March 2008 and April 2008 to March 2013) and also presented by individual year.&#xD;
      Age will be categorized into the groups &lt;65, 65-74, 75-84 and&gt;85. Charlson scores greater&#xD;
      than 5 will be grouped into one category. Method of admission will be defined as one of&#xD;
      elective admission; emergency admission; maternity admission; other admission or unknown.&#xD;
      Ethnicity will be grouped as White, Mixed, Asian, Black, other ethnic groups and ethnicity&#xD;
      not stated/unknown.&#xD;
&#xD;
      Continuous variables will be expressed as mean with 95% confidence interval (CI). Categorical&#xD;
      variables will be expressed as proportions and compared with the chi square test. Incidence&#xD;
      rates per 1000 person-years and 95% confidence intervals will be calculated using Poisson&#xD;
      regression analysis and compared using a chi-squared test for proportions. Age-adjusted&#xD;
      incidence rates for AKI will be calculated based on the UK standard population using the&#xD;
      direct standardization method. Further analysis will be done to identify regional variation&#xD;
      in epidemiology of both AKI not requiring dialysis and AKI requiring dialysis in England.&#xD;
&#xD;
      The Poisson regression model will be used to analyse the effect of gender, age group, period&#xD;
      of admission, method of admission, Charlson co-morbidity index and ethnicity on incidence of&#xD;
      AKI. Cox Proportional Hazard Models will be applied to test the association between mortality&#xD;
      and these variables. Multivariable logistic regression will be considered to assess the&#xD;
      association between AKI and all these variables simultaneously. We will use the middle period&#xD;
      of 2003-2008 as reference, which will enable us to evaluate improvement in mortality as&#xD;
      compared to 1998-2003 and also to evaluate whether the improvement has been sustained in the&#xD;
      later period of 2008-2013. The effect of AKI on mortality and length of stay will be tested&#xD;
      using the Cox Proportional Hazard Models and the Linear Regression respectively. Long-term&#xD;
      survival of patients will be plotted using Kaplan Meir curves after obtaining the date and&#xD;
      cause of death for all patients obtained from Office of National Statistics.&#xD;
&#xD;
      We will randomly select a number of patients who had a recorded diagnosis of AKI in HES&#xD;
      database since 1998. Controls will also be selected and matched to each patient by age, sex,&#xD;
      date of diagnosis and region. The association between AKI and each exposure will be analyzed&#xD;
      using conditional logistic regression.&#xD;
&#xD;
      Data Handling and Record Keeping The data obtained from HES will be anonymised and will not&#xD;
      have any patient identifiable characteristics. The study protocol, documentation, data and&#xD;
      all other information generated will be held in strict confidence. No information concerning&#xD;
      the study or the data will be released to any unauthorized third party, without prior written&#xD;
      approval of the sponsoring institution. Authorized representatives of the sponsoring&#xD;
      institution may inspect all documents and records, required to be maintained, by the&#xD;
      Investigator, including but not limited to, medical records (office, clinic or hospital) for&#xD;
      the subjects in this study. The clinical study site will permit access to such records.&#xD;
      Information about study subjects will be kept confidential and managed according to the&#xD;
      requirements of the Data Protection Act, NHS Caldicott Guardian, The Research Governance&#xD;
      Framework for Health and Social Care, Ethics Committee Approval and Trust IM&amp;T Policy. The&#xD;
      Chief/Principal Investigator will be the &quot;Custodian&quot; of the data&#xD;
&#xD;
      Source Documents The source document will be the HES database. HES data is held as financial&#xD;
      year data-sets, although the source data is collected monthly from NHS - and originates from&#xD;
      commissioning messages sent by healthcare providers to healthcare commissioners via the&#xD;
      secondary User Services (SUS). At pre-arranged date during the year, SUS takes an extract&#xD;
      from their database and sends it to HES. HES then validates and clean the extract, before&#xD;
      deriving new items and making the information available in the data warehouse. Data quality&#xD;
      reports and checks are completed at various stages in the cleaning and processing cycle.&#xD;
&#xD;
      Records Retention The data will be kept for 15 years after the completion of the study, in&#xD;
      accordance with the requirements of the Therapeutic Goods Administration and Health Privacy&#xD;
      Principals.&#xD;
&#xD;
      All research data and study related documents will be stored, following the end of the study.&#xD;
      The data will be secured in password-protected computer with access to the chief&#xD;
      investigator. The data will be deleted from the hard drive of the computer at the end of the&#xD;
      archival period.&#xD;
&#xD;
      Study Monitoring, Auditing, and Inspecting The investigator will permit study-related&#xD;
      monitoring, audits and inspections by the Ethics Committee, the Sponsor and the Research&#xD;
      Governance Manager. This study will be monitored by the Research Governance Manager according&#xD;
      to the Research &amp; Development Office procedure for monitoring all non-commercial research&#xD;
      carried out at the Derby Hospitals NHS Foundation Trust and the Southern Derbyshire Primary&#xD;
      Care Trusts. In line with the responsibilities set out in the Research Governance Framework,&#xD;
      the Investigator will ensure that the research governance manager or other regulatory&#xD;
      monitoring authority is given access to all study-related documents and study related&#xD;
      facilities.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date>October 2014</start_date>
  <completion_date type="Actual">December 2014</completion_date>
  <primary_completion_date type="Actual">December 2014</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Cohort</observational_model>
    <time_perspective>Retrospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Secular Trends in the Mortality After Acute Kidney Injury From 1998 to 2013</measure>
    <time_frame>Participants will be followed for the duration of hospital stay (average of 15 days)</time_frame>
    <description>A retrospective cohort study of patients with acute kidney injury in England over a period of fifteen years, describing the trends in the mortality of acute kidney injury.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Incidence of AKI-D From 1998-9 to 2012-13</measure>
    <time_frame>15-years</time_frame>
    <description>The population incidence of acute kidney injury requiring dialysis (AKI-D) was calculated using mid-year population of England in each year from 1998 to 2013 and expressed as people per million population. This was calculated by dividing number of cases by mid year population of England and multiplying by million.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Mortality From Acute Kidney Injury in Each Age Group From 1998 to 2013</measure>
    <time_frame>Participants will be followed for the duration of hospital stay (average 13 days)</time_frame>
    <description>The secondary objective is evaluate factors affecting mortality due to acute kidney injury in the fifteen year period between 1998 and 2013.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Mortality From Acute Kidney Injury in Each Five-year Period From 1998 to 2013</measure>
    <time_frame>Participants will be followed for the duration of hospital stay (average 13 days)</time_frame>
    <description>The secondary objective is evaluate factors affecting mortality due to acute kidney injury in the fifteen year period between 1998 and 2013.</description>
  </secondary_outcome>
  <enrollment type="Actual">64882</enrollment>
  <condition>Acute Kidney Injury</condition>
  <eligibility>
    <study_pop>
      <textblock>
        This is a historical cohort study using already collected data from the Hospital Episode&#xD;
        Statistics (HES), a data warehouse containing details of all admissions, outpatient&#xD;
        appointments and A&amp;E attendances at NHS hospitals in England.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          1. Patients with any of the following ICD 10 codes, in any of the diagnoses, in the HES&#xD;
             database, will be included: N17.0 for acute renal failure with tubular necrosis, N17.1&#xD;
             for acute renal failure with acute cortical necrosis, N17.2 for acute renal failure&#xD;
             with medullary necrosis, N17.8 for other acute renal failure and N17.9 for acute renal&#xD;
             failure, unspecified.&#xD;
&#xD;
          2. All patients of any age and gender, with AKI as identified as above between the period&#xD;
             of 1st April 1998 and 31st March 2013.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          1. Patients with any of the following codes in any of the diagnoses codes will be&#xD;
             excluded: N18.5 for chronic kidney disease stage 5, N18.6 for end stage renal disease.&#xD;
&#xD;
          2. Patients with following codes in the any of the procedure codes will be excluded:&#xD;
             L74.2 for arterio-venous fistula, L74.3 for arterio-venous graft.&#xD;
&#xD;
          3. Patients', who were admitted in the study period, but were not discharged, will be&#xD;
             excluded.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>1 Day</minimum_age>
    <maximum_age>120 Years</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Nitin V Kolhe, MD, DM</last_name>
    <role>Principal Investigator</role>
    <affiliation>Derby Hospital NHS Trust</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Derby Hospital NHS Foundation Trust</name>
      <address>
        <city>Derby</city>
        <state>Derbyshire</state>
        <zip>DE22 3NE</zip>
        <country>United Kingdom</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United Kingdom</country>
  </location_countries>
  <verification_date>December 2016</verification_date>
  <study_first_submitted>August 8, 2014</study_first_submitted>
  <study_first_submitted_qc>August 13, 2014</study_first_submitted_qc>
  <study_first_posted type="Estimate">August 15, 2014</study_first_posted>
  <results_first_submitted>August 8, 2016</results_first_submitted>
  <results_first_submitted_qc>December 8, 2016</results_first_submitted_qc>
  <results_first_posted type="Estimate">December 9, 2016</results_first_posted>
  <last_update_submitted>December 8, 2016</last_update_submitted>
  <last_update_submitted_qc>December 8, 2016</last_update_submitted_qc>
  <last_update_posted type="Estimate">December 9, 2016</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>University Hospitals of Derby and Burton NHS Foundation Trust</investigator_affiliation>
    <investigator_full_name>Dr. Nitin Kolhe</investigator_full_name>
    <investigator_title>Consultant Nephrologist</investigator_title>
  </responsible_party>
  <keyword>acute kidney injury</keyword>
  <keyword>epidemiology</keyword>
  <keyword>mortality</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Acute Kidney Injury</mesh_term>
    <mesh_term>Wounds and Injuries</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
    <ipd_description>The data is freely available from www.hscic.gov.uk</ipd_description>
  </patient_data>

  <clinical_results>

    <participant_flow>
      <recruitment_details>The recruitment was from Hospital episode statistic dataset</recruitment_details>
      <group_list>
        <group group_id="P1">
          <title>Acute Kidney Injury</title>
          <description>All patients who had acute kidney injury requiring dialysis between 1998 and 2013 were identified from hospital episode statistic</description>
        </group>
      </group_list>
      <period_list>
        <period>
          <title>Overall Study</title>
          <milestone_list>
            <milestone>
              <title>STARTED</title>
              <participants_list>
                <participants group_id="P1" count="64882"/>
              </participants_list>
            </milestone>
            <milestone>
              <title>COMPLETED</title>
              <participants_list>
                <participants group_id="P1" count="64882">This is a database study and hence, 64882 patients were finally included</participants>
              </participants_list>
            </milestone>
            <milestone>
              <title>NOT COMPLETED</title>
              <participants_list>
                <participants group_id="P1" count="0"/>
              </participants_list>
            </milestone>
          </milestone_list>
        </period>
      </period_list>
    </participant_flow>

    <baseline>
      <group_list>
        <group group_id="B1">
          <title>Acute Kidney Injury</title>
          <description>we analysed acute kidney injury requiring dialysis in England</description>
        </group>
      </group_list>
      <analyzed_list>
        <analyzed>
          <units>Participants</units>
          <scope>Overall</scope>
          <count_list>
            <count group_id="B1" value="64882"/>
          </count_list>
        </analyzed>
      </analyzed_list>
      <measure_list>
        <measure>
          <title>Age</title>
          <units>years</units>
          <param>Mean</param>
          <dispersion>Inter-Quartile Range</dispersion>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="59.7" lower_limit="58.4" upper_limit="61"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Gender</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <category_list>
                <category>
                  <title>Female</title>
                  <measurement_list>
                    <measurement group_id="B1" value="24859"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Male</title>
                  <measurement_list>
                    <measurement group_id="B1" value="40023"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Region of Enrollment</title>
          <units>participants</units>
          <param>Number</param>
          <class_list>
            <class>
              <title>United Kingdom</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="64882"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>AKI identified by ICD10 codes of N17</title>
          <units>participants</units>
          <param>Number</param>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="64882"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </measure_list>
    </baseline>

    <outcome_list>
      <outcome>
        <type>Primary</type>
        <title>Secular Trends in the Mortality After Acute Kidney Injury From 1998 to 2013</title>
        <description>A retrospective cohort study of patients with acute kidney injury in England over a period of fifteen years, describing the trends in the mortality of acute kidney injury.</description>
        <time_frame>Participants will be followed for the duration of hospital stay (average of 15 days)</time_frame>
        <group_list>
          <group group_id="O1">
            <title>1998-03</title>
            <description>All patients who had acute kidney injury and required dialysis between 1998 and 2013 were identified from hospital episode statistic.Data during the 15-year period were divided into three 5-year periods (April 1988 to March 2003, April 2003 to March 2008 and April 2008 to March 2013)</description>
          </group>
          <group group_id="O2">
            <title>2003-08</title>
            <description>Data during the 15-year period were divided into three 5-year periods (April 1988 to March 2003, April 2003 to March 2008 and April 2008 to March 2013)</description>
          </group>
          <group group_id="O3">
            <title>2008-13</title>
            <description>Data during the 15-year period were divided into three 5-year periods (April 1988 to March 2003, April 2003 to March 2008 and April 2008 to March 2013)</description>
          </group>
        </group_list>
        <measure>
          <title>Secular Trends in the Mortality After Acute Kidney Injury From 1998 to 2013</title>
          <description>A retrospective cohort study of patients with acute kidney injury in England over a period of fifteen years, describing the trends in the mortality of acute kidney injury.</description>
          <units>participants</units>
          <param>Number</param>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="4268"/>
                <count group_id="O2" value="12434"/>
                <count group_id="O3" value="48180"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="1296"/>
                    <measurement group_id="O2" value="3763"/>
                    <measurement group_id="O3" value="19793"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Primary</type>
        <title>Incidence of AKI-D From 1998-9 to 2012-13</title>
        <description>The population incidence of acute kidney injury requiring dialysis (AKI-D) was calculated using mid-year population of England in each year from 1998 to 2013 and expressed as people per million population. This was calculated by dividing number of cases by mid year population of England and multiplying by million.</description>
        <time_frame>15-years</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Acute Kidney Injury</title>
            <description>All patients who had acute kidney injury requiring dialysis between 1998 and 2013 were identified from hospital episode statistic</description>
          </group>
        </group_list>
        <measure>
          <title>Incidence of AKI-D From 1998-9 to 2012-13</title>
          <description>The population incidence of acute kidney injury requiring dialysis (AKI-D) was calculated using mid-year population of England in each year from 1998 to 2013 and expressed as people per million population. This was calculated by dividing number of cases by mid year population of England and multiplying by million.</description>
          <units>cases per million population</units>
          <param>Number</param>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="64882"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <title>1998-99</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="774"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>1999-00</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="807"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>2000-01</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="793"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>2001-02</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="914"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>2002-03</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="980"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>2003-04</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="1172"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>2004-05</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="1398"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>2005-06</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="1551"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>2006-07</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="2465"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>2007-08</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="5848"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>2008-09</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="6973"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>2009-10</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="8443"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>2010-11</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="10153"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>2011-12</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="11447"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>2012-13</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="11164"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>Mortality From Acute Kidney Injury in Each Age Group From 1998 to 2013</title>
        <description>The secondary objective is evaluate factors affecting mortality due to acute kidney injury in the fifteen year period between 1998 and 2013.</description>
        <time_frame>Participants will be followed for the duration of hospital stay (average 13 days)</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Acute Kidney Injury Requiring Dialysis</title>
            <description>Age was categorized into the groups 65, 65-74, 75-84, and &gt; 85. The associations between discharge status was tested with multivariable regression model which included gender, age group, discharge period, admission method, CCS, ethnicity, and AKI in diagnoses code.</description>
          </group>
        </group_list>
        <measure>
          <title>Mortality From Acute Kidney Injury in Each Age Group From 1998 to 2013</title>
          <description>The secondary objective is evaluate factors affecting mortality due to acute kidney injury in the fifteen year period between 1998 and 2013.</description>
          <units>participants</units>
          <param>Number</param>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="64882"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <title>Less than 65 years</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="8271"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>65 to 74 years</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="7030"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>75 to 84 years</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="7959"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>More than or equal to 85 years</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="1592"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <analysis_list>
          <analysis>
            <group_id_list>
              <group_id>O1</group_id>
            </group_id_list>
            <non_inferiority_type>Superiority or Other</non_inferiority_type>
            <param_type>Odds Ratio (OR)</param_type>
            <param_value>1.35</param_value>
            <ci_percent>95</ci_percent>
            <ci_n_sides>2-Sided</ci_n_sides>
            <ci_lower_limit>1.30</ci_lower_limit>
            <ci_upper_limit>1.40</ci_upper_limit>
            <estimate_desc>This is OR for 65 to 74 years age group with &lt; 65 years as the reference group</estimate_desc>
          </analysis>
          <analysis>
            <group_id_list>
              <group_id>O1</group_id>
            </group_id_list>
            <non_inferiority_type>Superiority or Other</non_inferiority_type>
            <param_type>Odds Ratio (OR)</param_type>
            <param_value>1.72</param_value>
            <ci_percent>95</ci_percent>
            <ci_n_sides>2-Sided</ci_n_sides>
            <ci_lower_limit>1.66</ci_lower_limit>
            <ci_upper_limit>1.79</ci_upper_limit>
            <estimate_desc>This is OR for age group 75 to 84 years age group with &lt; 65 years as reference</estimate_desc>
          </analysis>
          <analysis>
            <group_id_list>
              <group_id>O1</group_id>
            </group_id_list>
            <non_inferiority_type>Superiority or Other</non_inferiority_type>
            <param_type>Odds Ratio (OR)</param_type>
            <param_value>2.03</param_value>
            <ci_percent>95</ci_percent>
            <ci_n_sides>2-Sided</ci_n_sides>
            <ci_lower_limit>1.89</ci_lower_limit>
            <ci_upper_limit>2.19</ci_upper_limit>
            <estimate_desc>This is OR for age group equal to greater than 85 years age group with &lt; 65 years as reference</estimate_desc>
          </analysis>
        </analysis_list>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>Mortality From Acute Kidney Injury in Each Five-year Period From 1998 to 2013</title>
        <description>The secondary objective is evaluate factors affecting mortality due to acute kidney injury in the fifteen year period between 1998 and 2013.</description>
        <time_frame>Participants will be followed for the duration of hospital stay (average 13 days)</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Acute Kidney Injury Requiring Dialysis</title>
            <description>The associations between discharge status was tested with multivariable regression model which included age group and discharge period,</description>
          </group>
        </group_list>
        <measure>
          <title>Mortality From Acute Kidney Injury in Each Five-year Period From 1998 to 2013</title>
          <description>The secondary objective is evaluate factors affecting mortality due to acute kidney injury in the fifteen year period between 1998 and 2013.</description>
          <units>participants</units>
          <param>Number</param>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="64882"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <title>1998-2003</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="1296"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>2003-2008</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="3763"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>2008-2013</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="19793"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <analysis_list>
          <analysis>
            <group_id_list>
              <group_id>O1</group_id>
            </group_id_list>
            <non_inferiority_type>Superiority or Other</non_inferiority_type>
            <param_type>Odds Ratio (OR)</param_type>
            <param_value>1.20</param_value>
            <ci_percent>95</ci_percent>
            <ci_n_sides>2-Sided</ci_n_sides>
            <ci_lower_limit>1.10</ci_lower_limit>
            <ci_upper_limit>1.30</ci_upper_limit>
            <estimate_desc>This is the OR for 1998-2003 discharge period with 2003-08 as the reference group</estimate_desc>
          </analysis>
          <analysis>
            <group_id_list>
              <group_id>O1</group_id>
            </group_id_list>
            <non_inferiority_type>Superiority or Other</non_inferiority_type>
            <param_type>Odds Ratio (OR)</param_type>
            <param_value>1.13</param_value>
            <ci_percent>95</ci_percent>
            <ci_n_sides>2-Sided</ci_n_sides>
            <ci_lower_limit>1.07</ci_lower_limit>
            <ci_upper_limit>1.18</ci_upper_limit>
            <estimate_desc>This is the OR for 2008-13 discharge period with 2003-08 as the reference group</estimate_desc>
          </analysis>
        </analysis_list>
      </outcome>
    </outcome_list>

    <reported_events>
      <desc>No adverse event was collected for this retrospective observational study</desc>
      <group_list>
        <group group_id="E1">
          <title>Dialysis Requiring AKI</title>
          <description>AKI patients who required renal replacement therapy</description>
        </group>
      </group_list>
      <serious_events>
        <category_list>
          <category>
            <title>Total</title>
            <event_list>
              <event>
                <sub_title>Total, serious adverse events</sub_title>
                <counts group_id="E1" subjects_affected="0" subjects_at_risk="0"/>
              </event>
            </event_list>
          </category>
        </category_list>
      </serious_events>
      <other_events>
        <frequency_threshold>0</frequency_threshold>
        <category_list>
          <category>
            <title>Total</title>
            <event_list>
              <event>
                <sub_title>Total, other adverse events</sub_title>
                <counts group_id="E1" subjects_affected="0" subjects_at_risk="0"/>
              </event>
            </event_list>
          </category>
        </category_list>
      </other_events>
    </reported_events>

    <certain_agreements>
      <pi_employee>All Principal Investigators ARE employed by the organization sponsoring the study.</pi_employee>
      <restrictive_agreement>There is NOT an agreement between Principal Investigators and the Sponsor (or its agents) that restricts the PI's rights to discuss or publish trial results after the trial is completed. </restrictive_agreement>
    </certain_agreements>
    <point_of_contact>
      <name_or_title>Nitin V Kolhe</name_or_title>
      <organization>Derby Teaching Hospital NHS Trust</organization>
      <phone>01332788266</phone>
      <email>nitin.kolhe@nhs.net</email>
    </point_of_contact>
  </clinical_results>
</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/NCT02216695
org study id: 1.2
nct id: NCT02216695
lead sponsor: 
has dmc: No
The true population incidence of acute kidney injury (AKI), previously called acute renal
      failure, in England is not known. A better understanding of the epidemiology of AKI at a
      national level is essential to inform initiatives to prevent AKI as well as reduce the
      associated morbidity and mortality. The purpose of this study is to combine the national
      database of all hospital discharges with national census data to investigate trends in the
      incidence of both, AKI not requiring dialysis and AKI requiring dialysis, as well as its
      associated mortality and its determinants in England between 1998 and 2013
Subject Selection and Withdrawal We will identify all cases of AKI by using validated
      International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM)
      codes in any of he diagnoses codes, in keeping with the objective of the study. Patients with
      any of the following codes will be included: N17.0 for acute renal failure with tubular
      necrosis, N17.1 for acute renal failure with acute cortical necrosis, N17.2 for acute renal
      failure with medullary necrosis, N17.8 for other acute renal failure and N17.9 for acute
      renal failure, unspecified. Acute renal failure has been replaced by new terminology, acute
      kidney injury, but due to lack of ICD-10-CM codes for AKI, we will use the ICD-10-CM codes
      for acute renal failure and henceforth, will be referred to as AKI in this protocol.

      Subject Recruitment and Screening We will extract 1998 to 2013 data from the Hospital Episode
      Statistics (HES), a data warehouse containing details of all admissions, outpatient
      appointments and A&E attendances at National Health Service (NHS) hospitals in England. HES
      collects a detailed record for each 'episode' of admitted patient care delivered in England,
      either by NHS hospitals, primary care trusts, mental health trusts or delivered in the
      independent sector but commissioned by the NHS. These data are collected during a patient's
      time in hospital and stored as a large collection of separate records, one for each period of
      care, in a secure data warehouse. We will extract secondary diagnosis codes for up to 14
      diagnoses available till 2006-07 and up to 20 additional diagnoses from 2007 till 2013. In
      addition to demographic data, we will also extract up to 15 procedure codes. To identify AKI
      patients requiring dialysis, we will include procedure code of X40.3 for hemodialysis or
      X40.4 for hemofiltration in any of the 15 procedures. To exclude patients with chronic kidney
      disease starting dialysis, we will exclude patients who had chronic kidney disease (CKD)
      stage 5 (N18.5) and end stage renal disease (N18.6) and procedure codes for arteriovenous
      fistula (L74.2) or arteriovenous shunt (L74.3) during the inpatient admission (figure 1).
      This algorithm has been shown to be sensitive and specific, with a high positive and negative
      predictive value (all >90%. Patients who were admitted, but were not discharged during the
      study period will not be included in the study.

      We will obtain data on patient demographics, hospital characteristics, in-hospital mortality,
      disposition, length of stay (LOS), and up to 20 diagnosis and 15 procedure codes that are
      based on the ICD-10-CM and Office of Population Censuses and Surveys Classification of
      Surgical Operations and Procedures, 4th revision (OPCS-4) from the HES database. To obtain
      population incidence of AKI requiring dialysis, we will obtain mid-year populations of
      England in each year from 1998 to 2013 from the Office of National Statistics (ONS). We will
      also obtain length of stay and mortality for all patients who did not have acute kidney
      injury coded as N17 in any of the diagnoses codes, in England over the same time period.

      Patients will not be contacted. This study will not obtain informed consent from the
      patients' as we will be working with anonymous patient data. No screening requirements
      (laboratory or diagnostic testing) are necessary to meet the inclusion or exclusion criteria.
      Unique Subject Identification numbers are already allocated to the patients and the HES
      database does not include any patient's name or hospital number.

      Sample Size Determination The data from HES will be extracted for the period between April
      1998 and March 2013. HES data is collected during a patients' time at hospital and is
      submitted to allow hospitals to be paid for the care they deliver. As this is a retrospective
      population cohort study using a national database, all cases of AKI as defined by the
      inclusion criteria, from the HES database will be used.

      Statistical Methods All analyses will be performed using validated statistical software. Data
      during the 15-year period will be divided into three 5-yr periods (April 1988 to March 2003,
      April 2003 to March 2008 and April 2008 to March 2013) and also presented by individual year.
      Age will be categorized into the groups <65, 65-74, 75-84 and>85. Charlson scores greater
      than 5 will be grouped into one category. Method of admission will be defined as one of
      elective admission; emergency admission; maternity admission; other admission or unknown.
      Ethnicity will be grouped as White, Mixed, Asian, Black, other ethnic groups and ethnicity
      not stated/unknown.

      Continuous variables will be expressed as mean with 95% confidence interval (CI). Categorical
      variables will be expressed as proportions and compared with the chi square test. Incidence
      rates per 1000 person-years and 95% confidence intervals will be calculated using Poisson
      regression analysis and compared using a chi-squared test for proportions. Age-adjusted
      incidence rates for AKI will be calculated based on the UK standard population using the
      direct standardization method. Further analysis will be done to identify regional variation
      in epidemiology of both AKI not requiring dialysis and AKI requiring dialysis in England.

      The Poisson regression model will be used to analyse the effect of gender, age group, period
      of admission, method of admission, Charlson co-morbidity index and ethnicity on incidence of
      AKI. Cox Proportional Hazard Models will be applied to test the association between mortality
      and these variables. Multivariable logistic regression will be considered to assess the
      association between AKI and all these variables simultaneously. We will use the middle period
      of 2003-2008 as reference, which will enable us to evaluate improvement in mortality as
      compared to 1998-2003 and also to evaluate whether the improvement has been sustained in the
      later period of 2008-2013. The effect of AKI on mortality and length of stay will be tested
      using the Cox Proportional Hazard Models and the Linear Regression respectively. Long-term
      survival of patients will be plotted using Kaplan Meir curves after obtaining the date and
      cause of death for all patients obtained from Office of National Statistics.

      We will randomly select a number of patients who had a recorded diagnosis of AKI in HES
      database since 1998. Controls will also be selected and matched to each patient by age, sex,
      date of diagnosis and region. The association between AKI and each exposure will be analyzed
      using conditional logistic regression.

      Data Handling and Record Keeping The data obtained from HES will be anonymised and will not
      have any patient identifiable characteristics. The study protocol, documentation, data and
      all other information generated will be held in strict confidence. No information concerning
      the study or the data will be released to any unauthorized third party, without prior written
      approval of the sponsoring institution. Authorized representatives of the sponsoring
      institution may inspect all documents and records, required to be maintained, by the
      Investigator, including but not limited to, medical records (office, clinic or hospital) for
      the subjects in this study. The clinical study site will permit access to such records.
      Information about study subjects will be kept confidential and managed according to the
      requirements of the Data Protection Act, NHS Caldicott Guardian, The Research Governance
      Framework for Health and Social Care, Ethics Committee Approval and Trust IM&T Policy. The
      Chief/Principal Investigator will be the "Custodian" of the data

      Source Documents The source document will be the HES database. HES data is held as financial
      year data-sets, although the source data is collected monthly from NHS - and originates from
      commissioning messages sent by healthcare providers to healthcare commissioners via the
      secondary User Services (SUS). At pre-arranged date during the year, SUS takes an extract
      from their database and sends it to HES. HES then validates and clean the extract, before
      deriving new items and making the information available in the data warehouse. Data quality
      reports and checks are completed at various stages in the cleaning and processing cycle.

      Records Retention The data will be kept for 15 years after the completion of the study, in
      accordance with the requirements of the Therapeutic Goods Administration and Health Privacy
      Principals.

      All research data and study related documents will be stored, following the end of the study.
      The data will be secured in password-protected computer with access to the chief
      investigator. The data will be deleted from the hard drive of the computer at the end of the
      archival period.

      Study Monitoring, Auditing, and Inspecting The investigator will permit study-related
      monitoring, audits and inspections by the Ethics Committee, the Sponsor and the Research
      Governance Manager. This study will be monitored by the Research Governance Manager according
      to the Research & Development Office procedure for monitoring all non-commercial research
      carried out at the Derby Hospitals NHS Foundation Trust and the Southern Derbyshire Primary
      Care Trusts. In line with the responsibilities set out in the Research Governance Framework,
      the Investigator will ensure that the research governance manager or other regulatory
      monitoring authority is given access to all study-related documents and study related
      facilities.
observational model: Cohort
time perspective: Retrospective
measure: Secular Trends in the Mortality After Acute Kidney Injury From 1998 to 2013
time frame: Participants will be followed for the duration of hospital stay (average of 15 days)
description: A retrospective cohort study of patients with acute kidney injury in England over a period of fifteen years, describing the trends in the mortality of acute kidney injury.
measure: Incidence of AKI-D From 1998-9 to 2012-13
time frame: 15-years
description: The population incidence of acute kidney injury requiring dialysis (AKI-D) was calculated using mid-year population of England in each year from 1998 to 2013 and expressed as people per million population. This was calculated by dividing number of cases by mid year population of England and multiplying by million.
measure: Mortality From Acute Kidney Injury in Each Age Group From 1998 to 2013
time frame: Participants will be followed for the duration of hospital stay (average 13 days)
description: The secondary objective is evaluate factors affecting mortality due to acute kidney injury in the fifteen year period between 1998 and 2013.
measure: Mortality From Acute Kidney Injury in Each Five-year Period From 1998 to 2013
time frame: Participants will be followed for the duration of hospital stay (average 13 days)
description: The secondary objective is evaluate factors affecting mortality due to acute kidney injury in the fifteen year period between 1998 and 2013.
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 1 Day
maximum age: 120 Years
healthy volunteers: No
last name: Nitin V Kolhe, MD, DM
role: Principal Investigator
affiliation: Derby Hospital NHS Trust
facility: 
country: United Kingdom
responsible party type: Principal Investigator
investigator affiliation: University Hospitals of Derby and Burton NHS Foundation Trust
investigator full name: Dr. Nitin Kolhe
investigator title: Consultant Nephrologist
mesh term: Acute Kidney Injury
mesh term: Wounds and Injuries
sharing ipd: No
ipd description: The data is freely available from www.hscic.gov.uk
participant flow: 
baseline: 
outcome list: 
reported events: 
certain agreements: 
point of contact: 