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  • br It is reasonable to postulate that cancer


    It is reasonable to postulate that cancer patients, particularly those free of advanced disease, should share similar resuscitation rates compared to cancer-free patients. Yet, whether cancer patients share similar improvements in post-IHCA outcomes and post-arrest cardio-resuscitory procedural utilization is unknown.
    Data source
    To investigate the aforementioned relationships and temporal trends, we retrospectively reviewed contemporary population data collected via the National Inpatient Sample (NIS) dataset from 2003 to 2014. We specifically selected this interval given the widespread adoption of ICD-9 codes around this time, as well as the publication of sentinel reports from the American Heart Association in 2002–03 describing the state of IHCA within the U.S.11,12 The NIS is a publicly available database of ~7 million admissions per year, representative of all ~35 million inpatient admissions to acute-care, D-Luciferin hospitals in the US and is compiled as part of the Healthcare Cost and Utilization Project (HCUP) by the Agency for Healthcare Research and Quality. Prior to 2012, the NIS included 100% of discharges from a stratified sample of 20% of eligible hospitals, but in 2012, this database was redesigned to include a stratified sample of 20% of admissions from 100% of eligible hospitals. Medical information contained in the NIS includes the primary diagnosis for hospital admission (labeled “DX1”), secondary diagnoses (labeled “DX2,” “DX3,” etc.), procedures performed during the admission, and routine demographic informa-tion, all recorded using ICD-9 codes.
    Study population
    All patients age 18 years old who sustained IHCA during an index admission were analyzed. Cardiac arrests were identified using ICD-9 codes 427.41 or 427.5 (ventricular fibrillation and cardiac arrest, respectively). Since DX1 represents the diagnosis code for the primary reason for hospitalization, only those cases that had 
    ICD-9 codes of 427.41 or 427.5 ascribed as a secondary diagnosis were included in the analysis. Conversely, if either code appeared as a primary diagnosis, these were considered to be hospitalizations for an out-of-hospital cardiac arrest and were therefore excluded from the analysis.13–15
    Discharge diagnoses and procedures were recoded using the Clinical Classification of Diseases Software (“DXCCS” ) into broad categories, available as separate variables within NIS. We identified cancer hospitalizations using ICD-9 and DXCCS codes (DXCCS 1–
    30) or the presence of an indicator of cancer in the comorbid condition files. DXCCS codes indicating cancer are 11–45. The comorbidity file included in the NIS lists 29 comorbidities (also known as Elixhauser’s Comorbidity measures) based on ICD-9 CM diagnoses and the diagnosis-related group in effect on the discharge date. These comorbidities are not directly related to the principal diagnosis or the
    main reason for admission and are likely to have originated before the hospital stay.16 In 2015, the Healthcare Cost and Utilization Project (HCUP) State Inpatient Database was used to create two indices
    based on 29 co-morbidity measures designed to predict in-hospital mortality and 30-day readmission.17 Those indices were calculated for our cohort as well.
    For flagella analysis, all hospitalizations that lacked an ICD-9 or DXCCS code indicating a diagnosis of cancer were considered non-cancer hospitalizations. Admissions with metastatic cancer were excluded due to the metabolic derangements and systemic inflamma-
    tion associated with advanced malignancy, and the fact that such diagnoses tend to portend limited survival.18,19