Study of Adrenal Crises in Adults With Adrenal Insufficiency
Study of Adrenal Crises in Adults With Adrenal Insufficiency
The State of NSW, Australia has a population of approximately 5 million adults aged 20 years and over (5,389,908 people in 2011). The age structure of the population is shown in Table 1. Clinical information on all admissions to public and private hospitals in NSW is reviewed and extracted from the health care record of each patient by staff trained in clinical coding. The documented diseases, injuries, complications, co-morbidities, and procedures noted in this record are then coded according to the International Classification of Diseases (ICD) 10. Each hospital conducts audits on the coded data, rectifies any errors and submits the data to the NSW Ministry of Health to form part of the Admitted Patient Data Collection (APDC). In addition to the auditing procedures conducted at the hospital level, the NSW Ministry of Health also subjects these data to regular quality assurance assessments.
For this study, we selected all admissions to NSW hospitals between July 1, 2000 and June 30, 2011 in which the principal diagnosis (main reason for the admission) or any secondary (co-morbid) diagnosis was coded as E27.2 (Addisonian Crisis). Each de-identified unit record included information on the year (according to the Australian financial year (July 1 to June 30)), hospital type (private or public), age, sex, mode of admission, mode of separation (departure from hospital, including in-hospital mortality), the length of hospital stay (LOS), principal diagnosis, all secondary diagnoses and any surgical procedures performed in an operating theatre during each patient's admission.
An infection was classified as a principal or any secondary diagnosis in which the diagnosis was a disease or condition caused by an organism such as a urinary tract infection (UTI), pneumonia (excluding pneumonitis due to aspiration) or lower respiratory tract infection (LRTI), sepsis, or where an infectious agent was coded. A virus was identified as present when a specific viral agent was identified or where a diagnostic code had a viral agent included, such as "viral gastroenteritis". A bacterial infection was identified when a bacterium as a cause of disease was coded in a diagnosis field or where a bacterial infection was identified but not named (B96.88- Other & unspecified bacterial agent cause of disease). Where a UTI (N39) was coded but there was no bacterial agent identified (23 cases) these cases were assumed to be bacterial in origin and were classified accordingly.
Gastroenteritis was identified by any code specifying gastroenteritis, whether viral, bacterial or non-infective. Colitis was also included in the gastroenteritis group but "nausea and vomiting" (R11) was not. "Pneumonia/LRTI" was classified as any pneumonia, LRTI, acute bronchitis and chronic obstructive pulmonary disease (COPD) with mention of infection but excluded COPD, asthma exacerbation or bronchiectasis, where an infection was not mentioned.
For the purposes of analysis, age was reclassified into ten-year groups and the LOS was classified into 4 categories (0–1, 2–3, 4–6 and 7 or more days). Chi sq tests were used to assess the differences in frequencies of categorical variables between groups. Age-specific incidence rates were determined by dividing the number of AC admissions in each age category by the corresponding NSW population in that age category for each year and this was then converted into a rate per million population per year. A mean rate for each age group for the study period was computed, together with 95% confidence intervals. Poisson regression was used to assess the significance of the observed change in rates of AC related admissions with age, while controlling for any secular trends by including year in the model. A value of p < 0.05 was considered significant.
The data were analysed using Excel (Microsoft. (2007) Microsoft Excel [computer software]. Redmond, Washington: Microsoft) and SPSS (IBM Corp. Released 2013. IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corp.). The study was approved by the Human Resource Ethics Committee by the University of Notre Dame, Australia.
Methods
The State of NSW, Australia has a population of approximately 5 million adults aged 20 years and over (5,389,908 people in 2011). The age structure of the population is shown in Table 1. Clinical information on all admissions to public and private hospitals in NSW is reviewed and extracted from the health care record of each patient by staff trained in clinical coding. The documented diseases, injuries, complications, co-morbidities, and procedures noted in this record are then coded according to the International Classification of Diseases (ICD) 10. Each hospital conducts audits on the coded data, rectifies any errors and submits the data to the NSW Ministry of Health to form part of the Admitted Patient Data Collection (APDC). In addition to the auditing procedures conducted at the hospital level, the NSW Ministry of Health also subjects these data to regular quality assurance assessments.
For this study, we selected all admissions to NSW hospitals between July 1, 2000 and June 30, 2011 in which the principal diagnosis (main reason for the admission) or any secondary (co-morbid) diagnosis was coded as E27.2 (Addisonian Crisis). Each de-identified unit record included information on the year (according to the Australian financial year (July 1 to June 30)), hospital type (private or public), age, sex, mode of admission, mode of separation (departure from hospital, including in-hospital mortality), the length of hospital stay (LOS), principal diagnosis, all secondary diagnoses and any surgical procedures performed in an operating theatre during each patient's admission.
An infection was classified as a principal or any secondary diagnosis in which the diagnosis was a disease or condition caused by an organism such as a urinary tract infection (UTI), pneumonia (excluding pneumonitis due to aspiration) or lower respiratory tract infection (LRTI), sepsis, or where an infectious agent was coded. A virus was identified as present when a specific viral agent was identified or where a diagnostic code had a viral agent included, such as "viral gastroenteritis". A bacterial infection was identified when a bacterium as a cause of disease was coded in a diagnosis field or where a bacterial infection was identified but not named (B96.88- Other & unspecified bacterial agent cause of disease). Where a UTI (N39) was coded but there was no bacterial agent identified (23 cases) these cases were assumed to be bacterial in origin and were classified accordingly.
Gastroenteritis was identified by any code specifying gastroenteritis, whether viral, bacterial or non-infective. Colitis was also included in the gastroenteritis group but "nausea and vomiting" (R11) was not. "Pneumonia/LRTI" was classified as any pneumonia, LRTI, acute bronchitis and chronic obstructive pulmonary disease (COPD) with mention of infection but excluded COPD, asthma exacerbation or bronchiectasis, where an infection was not mentioned.
For the purposes of analysis, age was reclassified into ten-year groups and the LOS was classified into 4 categories (0–1, 2–3, 4–6 and 7 or more days). Chi sq tests were used to assess the differences in frequencies of categorical variables between groups. Age-specific incidence rates were determined by dividing the number of AC admissions in each age category by the corresponding NSW population in that age category for each year and this was then converted into a rate per million population per year. A mean rate for each age group for the study period was computed, together with 95% confidence intervals. Poisson regression was used to assess the significance of the observed change in rates of AC related admissions with age, while controlling for any secular trends by including year in the model. A value of p < 0.05 was considered significant.
The data were analysed using Excel (Microsoft. (2007) Microsoft Excel [computer software]. Redmond, Washington: Microsoft) and SPSS (IBM Corp. Released 2013. IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corp.). The study was approved by the Human Resource Ethics Committee by the University of Notre Dame, Australia.
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