DÄ internationalArchive22-23/2017Incidence, Treatment and Mortality in Patients with Abdominal Aortic Aneurysms: An Analysis of Hospital Discharge Data from 2005–2014

Original article

Incidence, Treatment and Mortality in Patients with Abdominal Aortic Aneurysms: An Analysis of Hospital Discharge Data from 2005–2014

An analysis of hospital discharge data from 2005–2014

Dtsch Arztebl Int 2017; 114(22-23): 391-8; DOI: 10.3238/arztebl.2017.0391

Kühnl, A; Erk, A; Trenner, M; Salvermoser, M; Schmid, V; Eckstein, H

Background: Aim of this study was to analyze hospital incidence, type of treatment, and hospital mortality rates of patients with abdominal aortic aneurysm (AAA) in Germany from 2005 to 2014.

Methods: Microdata of the diagnosis-related group (DRG) statistics compiled by the German Federal Statistical Office for the years 2005–2014 were analyzed. Patients who were hospitalized for a ruptured AAA (rAAA, ICD-10 code I71.3, treated either surgically or conservatively) or received surgical treatment for an unruptured AAA (nrAAA, ICD-10-Code I71.4, treated either with open surgery or an endovascular procedure) were included in the analysis. The “European Standard Population 2013” was used for direct standardization of the hospital incidences. In-hospital mortality was calculated with standardization for age and risk.

Results: The standardized overall hospital incidence of AAA was 27.9 and 3.3 cases per 100 000 people for men and women, respectively; over the period of the study, the incidence of rAAA fell by 30% in both sexes and that of nrAAA rose by 16% in men and 42% in women. The percentage of patients receiving endovascular treatment rose from 29% to 75% in patients with nrAAA and from 8% to 36% in patients with rAAA. The age- and risk-standardized in-hospital mortality of nrAAA was 3.3% in men and 5.3% in women. The in-hospital mortality of surgically treated rAAA was 39% in men and 48% in women.

Conclusion: The hospital incidence of AAA rose from 2005 to 2014, while that of rAAA fell. Endovascular treatment became more common for nrAAA as well as rAAA, and in-hospital mortality fell for both.

Abdominal aortic aneurysms (AAA) are defined as an enlargement of the infrarenal or suprarenal aorta to a diameter of at least 3 cm, which corresponds to 1.5 times the original vessel diameter (13). About 3% (1–7%) of the population aged over 50 are affected by an AAA (1, 2). Risk factors include familial predisposition, smoking, and arterial hypertension, among others; in contrast, women and patients with diabetes mellitus are less frequently affected (3, 4). AAA often remain asymptomatic until rupture but then have an in-hospital mortality of about 40%. However, the total mortality of a ruptured AAA (rAAA) is presumably significantly higher due to pre-hospitalization deaths (approximately 60–80%) (1, 3, 5). The therapeutic indication for an non-ruptured AAA (nrAAA) is usually set at a diameter of 5.0–5.5 cm (for men) and 4.5–5.0 cm (for women) (3, 6). Treatment consists of open surgical repair, in which the affected vessel segment is replaced with a prosthesis (OAR, open aortic repair), or endovascular repair, by implanting a stent graft (EVAR, endovascular aortic repair) (3). An analysis of register data (>35 000 patients) of the German Vascular Society (DGG; Deutsche Gesellschaft für Gefäßchirurgie und Gefäßmedizin) showed a mortality rate after elective AAA therapy of approximately 3.6% for OAR and 1.3% for EVAR (7).

Although nationwide analyses in Germany on the epidemiology and treatment of AAA have already been published, they were based on nationally aggregated diagnosis-related group (DRG) data from the German Federal Statistical Office (Statistisches Bundesamt, StBA) (8, 9). A disadvantage of these aggregated data is that they can be evaluated either only after a hospital principal diagnosis or after treatment procedure (according to the German Classification of Operations and Procedures [Operationen- und Prozedurenschlüssel, OPS]). More detailed evaluations of the management and therapy of AAA in Germany were carried out using the quality assurance register of the DGG (7, 10, 11). However, this register is not legally compulsory, contains only a fraction of the AAA cases treated in Germany (<20% of the rAAA, <50% of the nrAAA), and allows neither a sex-specific nor a regional analysis (7, 10, 11).

The aim of this study was therefore to describe the hospital incidence, treatment form, and in-hospital mortality of patients with AAA from 2005 to 2014 from the patient perspective, using the DRG statistics of the StBA. In contrast to previous studies, this study describes the provision of vascular services at a national level over a long term, defines cases by linking diagnosis and procedure codes, and includes all cases treated in Germany. In addition, outcome measures were adjusted for sex and age.

Methods

Using controlled remote data processing (CRDP), the DRG statistics of the StBA were evaluated from 2005 to 2014 (e1). The basic methods of CRDP have already been described in detail (e2e5). A detailed description of the methodology can be found in the eBox.

eMethods
eMethods
eBox
eMethods

This study is a secondary data analysis based on case-related hospital discharge data (according to the Hospital Finance Act (Krankenhausentgeltgesetz [KHEntgG]). Microdata were stored on servers of the StBA according to the applicable data protection regulations. The total population consists of all patients who were treated in a hospital that is in compliance with § 1, KHEntgG. The geographical coverage extended over all of Germany.

The study was approved by the ethics committee of the Technical University of Munich and was carried out according to current guidelines (e6, e7).

Based on the case-specific DRG, a link was made with the G-DRG case-fee catalog of the German Institute for the Hospital Remuneration System (Institut für das Entgeltsystem im Krankenhaus, InEK). The sex- and age-specific population size, the type of settlement structure, the DRG case-mix, and the average length of stay were linked. Compliance with data protection regulations was ensured by employees of the Research Data Center.

Inclusion and exclusion criteria were based, in general, on the study by Landenhed (e8). In our study, all DRG cases were included for which either nrAAA (I71.4) or rAAA (I71.3) was coded as the principal or secondary diagnosis (PD, SD) during the reporting years 2005–2014. All DRG cases that had been transferred to another hospital without surgical treatment (OAR or EVAR) were excluded. The surgical treatment OPS codes 5–384.5* and 5–384.7* were used for OAR, and 5–38a.1 *, for EVAR. Details are given in eFigure 1 and eTable 1.

Patient flow diagram
Patient flow diagram
eFigure 1
Patient flow diagram
Codes used based on OPS or ICD-10, according to the available version from DIMDI (www.dimdi.de)
Codes used based on OPS or ICD-10, according to the available version from DIMDI (www.dimdi.de)
eTable 1
Codes used based on OPS or ICD-10, according to the available version from DIMDI (www.dimdi.de)
Characteristics of excluded patients with I71.4 as a principal or secondary diagnosis but without an operative treatment (without OAR or EVAR during the stay)
Characteristics of excluded patients with I71.4 as a principal or secondary diagnosis but without an operative treatment (without OAR or EVAR during the stay)
eTable 2
Characteristics of excluded patients with I71.4 as a principal or secondary diagnosis but without an operative treatment (without OAR or EVAR during the stay)

Each analysis refers to one hospital case / episode (unit of analysis). The patient flow diagram is depicted in eFigure 1. We assumed that the majority of patients with nrAAA (as PD) were treated only once with OAR or EVAR, and that the majority of the patients had only a single event of a ruptured infrarenal aortic aneurysm. Thus, double counting is considered unlikely. Patients with a PD of nrAAA who were not operatively treated during the same stay (Tables 2 and 3) were excluded from the main analyses. This led to the following subgroups (eFigure 1):

  • nrAAA (OP): operatively treated nrAAA
  • rAAA (OP): operatively treated rAAA
  • rAAA (conservative): non-operatively treated rAAA, not transferred..

The group of all patients with ruptured AAA was identified as “rAAA (all)”, and the group of all patients with either rAAA or nrAAA, as “AAA (all)”. The hospital incidence, the length of stay, the proportion of endovascularly treated patients, and the mortality in the groups of AAA (all), rAAA (all), nrAAA (OP), rAAA (OP), and rAAA (cons) were analyzed. Incidences were calculated as directly age-standardized values. The „European Standard Population 2013“ was used for direct age standardization (e9). The methods of direct and indirect age standardization have been described previously (e10). Mortality rates are reported as absolute as well as age– and risk-standardized values. The Elixhauser Comorbidity Index was used for risk standardization (e11e13).

Statistical analysis

For metric variables, the median and the 25% and 75% quantiles were calculated. Data processing and analyses (as CRDP, using the NewVar Makro software, version 1.2, provided by the Federal Statistical Office) was carried out with the SAS statistical software, version 9.2 for Microsoft Windows (SAS Institute Inc., Cary, NC). Graphical processing of data was performed using Microsoft Excel and R (version 3.2.1; The R Foundation, www.r-project.org).

Results

Between 2005 and 2014, 118 162 patients were included in this study; 86% were men (Table 1). In total, 81% of patients presented with nrAAA and 19%, with rAAA. The crude hospital incidence for all AAA (nrAAA and all rAAA) was on average 13.2 per 100 000 inhabitants. The standardized hospital incidence for all AAA patients was 27.9 per 100 000 men, and 3.3 per 100 000 women. These values ​​rose for nrAAA from 2005 to 2014 (from 20.3 to 23.6 for men, and from 2.0 to 2.8 for women, per 100 000 inhabitants) and fell for rAAA over the same period (from 6.3 to 4.4 for men, and from 1.1 to 0.8 for women, per 100 000 inhabitants). The group-specific courses of the age-standardized hospital incidence are depicted in Figure 1 and eFigure 2. The median age from 2005 to 2014 was 73 years, and was higher for women than for men.

Age-standardized hospital incidence from 2005–2014
Age-standardized hospital incidence from 2005–2014
Figure 1
Age-standardized hospital incidence from 2005–2014
Characteristics of the patient cohort*1
Characteristics of the patient cohort*1
Table 1
Characteristics of the patient cohort*1
Age-standardized hospital incidence for all included AAA (left) and all included rAAA (right) from 2005–2014
Age-standardized hospital incidence for all included AAA (left) and all included rAAA (right) from 2005–2014
eFigure 2
Age-standardized hospital incidence for all included AAA (left) and all included rAAA (right) from 2005–2014

The most common documented comorbidities of AAA were arterial hypertension (69%), coronary heart disease (33%), other cardiac diseases (32%), peripheral arterial occlusive disease (32%), and renal insufficiency (20%) (Table 1). The coincidence of cerebrovascular disease was 7%, and of malignant diseases, 3%. The mean Elixhauser score was 5, and the case-mix index, 4.94. Changes over time of the case-mix index and the Elixhauser score are shown in eFigure 3.

Time period 2005–2014 for the median case-mix index (top) and the median Elixhauser Comorbidity Index (bottom) for treated nrAAA (left) and rAAA (right)
Time period 2005–2014 for the median case-mix index (top) and the median Elixhauser Comorbidity Index (bottom) for treated nrAAA (left) and rAAA (right)
eFigure 3
Time period 2005–2014 for the median case-mix index (top) and the median Elixhauser Comorbidity Index (bottom) for treated nrAAA (left) and rAAA (right)

Patients underwent endovascular aneurysm repair (EVAR) in 48% of the overall cases, in 56% of the nrAAA cases, and in 20% of the rAAA cases (Table 2). The median length of stay was 11 days for nrAAA and 14 days for operatively treated rAAA. An increase in EVAR treatments, and a decrease in length of stay, are shown in eFigures 4 and 5. The in-hospital case volume of all AAA patients who underwent surgery or endovascular treatment was 37 per year (32 for nrAAA and 4 for rAAA).

Management and outcome*1
Management and outcome*1
Table 2
Management and outcome*1
Median length of stay for patients treated for nrAAA (left) or rAAA (right) during 2005–2014
Median length of stay for patients treated for nrAAA (left) or rAAA (right) during 2005–2014
eFigure 5
Median length of stay for patients treated for nrAAA (left) or rAAA (right) during 2005–2014

The most common complications for all nrAAA and rAAA combined were acute limb ischemia (4.4%), acute myocardial infarction (2.0%), and acute mesenteric ischaemia (2.0%) (eTable 3). Mortality was 3.4% for nrAAA (with 5.3% for OAR, and 1.7% for EVAR), 40% for rAAA treated with surgery, and 71% for non-operatively treated rAAA (Table 2). The crude mortality of all AAA was reduced for men, from 27.4% in 2005 to 17.4% in 2014 (with a 37% relative risk reduction [RRR]) (eFigure 6). A similar trend was observed for women (of 14.4% to 9.7%, 33% RRR). After age and risk adjustment (eBox), this trend was still present but less pronounced (men, 9% RRR; women, 18% RRR) (Figure 2 and eFigure 7).

Mortality (age- and risk-adjusted) for the period from 2005 to 2014
Mortality (age- and risk-adjusted) for the period from 2005 to 2014
Figure 2
Mortality (age- and risk-adjusted) for the period from 2005 to 2014
Raw values for in-hospital mortality
Raw values for in-hospital mortality
eFigure 6
Raw values for in-hospital mortality
Mortality (age- and risk-adjusted) for all included AAA (left) as well as for all included rAAA (right) from 2005–2014
Mortality (age- and risk-adjusted) for all included AAA (left) as well as for all included rAAA (right) from 2005–2014
eFigure 7
Mortality (age- and risk-adjusted) for all included AAA (left) as well as for all included rAAA (right) from 2005–2014
Complications and secondary outcomes
Complications and secondary outcomes
eTable 3
Complications and secondary outcomes

Discussion

The present study shows that, during the reporting years (2005–2014) and over all subgroups, the hospital incidence for AAA was significantly higher for men than for women. Further, the hospital incidence for nrAAA increased while that of rAAA decreased. While mortality was higher for women than for men, the overall mortality for all subgroups and for both sexes decreased.

Hospital incidence

The hospital incidence for AAA, standardized to the European Standard Population 2013, was 27.9 per 100 000 men, and 3.3 per 100 000 women. Taking into account bias due to methodological differences, these data are congruent with results from southern Sweden (of 32.6 per 100 000 men, and 5.6 per 100 000 women), among others (12). However, hospital incidence values found in analysis were at the lower end of internationally reported incidences (of 11–117 per 100 000 men, and 2.2–34 per 100 000 women) (13). It should be noted, however, that the underlying data collection procedures, the reporting periods, the health systems (and thus the remuneration system), the case definitions, and the procedures for age standardization, including the standard populations used, were different (6, 1318). With respect to case definitions used in this study, it was assumed that rupture of an AAA is always an indication for treatment. For nrAAA, indication for treatment was determined a posteriori (19). Thus, DRG cases would have been excluded if the patients presented with nrAAA that required treatment but were not, or could not be, treated. In the rAAA group, however, DRG cases would be included if they were coded as ruptured but for which there was no indication for treatment or therapeutic possibilities. We also cannot rule out that DRG cases are included in this group that do not actually correspond to a ruptured aortic aneurysm (but to a penetrating atherosclerotic ulcer, for instance), which required different treatments or which were encoded with an unspecified or incorrect OPS code. Indeed, such a situation could explain the relatively low mortality that we observed, of 71%, in non-treated rAAA. However, such misclassifications can not be clinically double-checked on the basis of the available data.

We observed a slightly lower hospital incidence than that reported in the literature. This may be due to the fact that our study excluded aortic aneurysms without location information (I71.8/9), untreated nrAAA, thoracoabdominal aneurysms, and aneurysms due to aortic dissection (I71.0) (14, 17, 1921). In general, aortic dissection was excluded (exemplary illustration: n = 5596 cases in 2014 with dissection of the aorta as principal diagnosis; ICD-10 code I71.0), since the pathogenesis and the therapy options are significantly different. Further, although both thoracoabdominal aneurysms (n = 1667 cases in 2014, according to ICD-10 codes I71.5/6) and suprarenal aneurysms (n = 218 procedures in 2014, according to OPS code 5 384.7) have similar pathogenesis as infrarenal aneurysms, both were excluded, as they differ significantly in their treatment options, morbidity, and mortality from infrarenal aneurysms. In our opinion, this more restrictive case definition describes the patient collective more specifically, without leading to a relevant reduction in the case number.

The overall higher hospital incidence for men as compared to women (of 10:1 for nrAAA, and 6:1 for rAAA) is consistent with the results of other studies, which estimate the sex ratio to be around 2.6–6:1, although direct comparisons are difficult to make due to methodological heterogeneity (13, 2225).

Our study found that the hospital incidence increased slightly for nrAAA, and decreased for rAAA, for both sexes; this is similar to observations from the USA (26), Sweden (27, 28) and England, Wales and Scotland (14). The course of nrAAA may reflect either a real increase in incidence or modified DRG coding policy. In our opinion, however, it is more likely that a better awareness of disease among patients and physicians, screening programs, and improved therapeutic options have led to more patients undergoing elective treatment.

Proportion of endovascular treatments

Overall, the proportion of endovascularly treated patients increased, and more for nrAAA than for rAAA. While approximately the same percentage of men and women underwent EVAR for rAAA, women were usually less frequently treated endovascularly for nrAAA. The absolute values as well as the development over time are comparable with other countries (16, 2931). In our opinion, the differences between the sexes for nrAAA are most likely due to distinct vascular anatomy, smaller access vessels, shorter landing zones for EVAR, and greater calcification of the vessel wall (3234).

Hospital mortality

Standardized in-hospital mortality decreased slightly, similar to other countries (26, 31), but was lower for men than for women in all subgroups and over all years. The hospital mortality for nrAAA, of an average of 3.3% for men and 5.3% for women, is comparable with other countries (including the United States, Great Britain, Switzerland, Sweden, and Australia; men, 2.1–3.6%, women 2.9–6.5% [31, 35]). Sex-specific differences are probably due to anatomical characteristics, lifestyle factors, sex hormones, immunological processes, or genetic causes (13). It is also assumed that cardiovascular diseases are more often underdiagnosed in women (36). For rAAA, the overall sex-specific difference of in-hospital mortality is lower than for nrAAA; the absolute values for men (39%) and women (48%) are also comparable with those from other countries (men, 28–44%, and women, 22–53% [31, 35]). Variability between study results is most likely due to different standardization procedures for age and risk, distinct reporting periods, and varying proportions of endovascularily treated patients, making a comparison difficult. Interestingly, as shown in eFigure 3, women presenting with nrAAA generally have a higher Elixhauser risk score but the same case-mix index, whereas the opposite is observed for women presenting with rAAA (i.e., lower case-mix index with the same risk score). Despite possible coding effects, the higher risk score for women with nrAAA could indicate a higher comorbidity, which—in combination with the generally higher age and lower percentage of EVAR in women (eFigure 4)—explains the increased hospital mortality. This is a likely reason for prolonged in-hospital stays of female patients presenting with nrAAA. Additionally, women often live longer than their husbands, which could lead to a longer length of hospital stay in the absence of support from the spouse and if home care is lacking (37, 38). As the diameters of aneurysms are not recorded in the DRG data, we can only speculate as to whether women, who have constitutionally smaller vessels, only reach an aneurysm size of 5.0–5.5 cm at an advanced age, and thereby with the indication of treatment being „too late“. In addition, women already have a higher risk of rupture at smaller AAA diameters (39).

Proportion of endovascularly-treated patients presenting with nrAAA (left) or rAAA (right) during 2005–2014
Proportion of endovascularly-treated patients presenting with nrAAA (left) or rAAA (right) during 2005–2014
eFigure 4
Proportion of endovascularly-treated patients presenting with nrAAA (left) or rAAA (right) during 2005–2014

Limitations

There are several limitations to this analysis, which are briefly summarized here (and given in more detail in the eBox):

  • Data are not clinical, but administrative, so that miscoding or changes in coding procedures could lead to biased case selection, case grouping, diagnoses, and procedures.
  • While overreporting is rather unlikely due to regular monitoring by the Health Insurance Medical Service (Medizinischer Dienst der Kran­ken­ver­siche­rungen; MDK), an underreporting of secondary diagnoses or procedures that are not relevant to DRGs may be assumed.
  • Risk-adjustment of mortality included only age, sex, and Elixhauser score. While the latter is a validated instrument (40), some aneurysm-specific risk factors, such as diameter of aneurysm and technical level of expertise, are not available in the database.
  • The observation period ended with the patient’s discharge from the hospital. Deaths and complications that occurred after hospital discharge were not recorded.
  • Secondary („soft“) outcomes, such as quality of life or other „patient-reported outcomes,“ were not recorded and therefore could not be analyzed.

Acknowledgment
We would like to thank Melanie Scheller from the Research Data Center of the German Federal Statistical Office and the Federal States in Wiesbaden for her unfailingly pleasant and very competent support in planning and implementing controlled remote data processing. We also thank Jutta Spindler, Sabine Nemitz, and their co-workers from the German Federal Statistical Office for supporting the project. Finally, we thank the reviewers for their valuable comments and suggestions for improvement.

Conflict of interest statement

The authors declare that no conflict of interest exists.

Manuscript received on 16 December 2016, revised version accepted on 16 March 2017.

Translated from the original German by Veronica Raker, PhD.

Corresponding author
Prof. Dr. med. Hans-Henning Eckstein
Klinik und Poliklinik für Vaskuläre und Endovaskuläre Chirurgie
Klinikum rechts der Isar der Technischen Universität München
Ismaninger Str. 22,
81675 Munich, Germany
gefaesschirurgie@lrz.tum.de

Supplementary material
For eReferences please refer to:
www.aerzteblatt-international.de/ref2217

eBox, eFigures, eTables:
www.aerzteblatt-international.de/17m0391

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e1.
Forschungsdatenzentren (FDZ) der Statistischen Ämter des Bundes und der Länder: Fallpauschalenbezogene Krankenhausstatistik (DRG-Statistik), 2005–2014, eigene Berechnungen.
e2.
Nimptsch U, Krautz C, Weber GF, Mansky T, Grutzmann R: Nationwide in-hospital mortality following pancreatic surgery in Germany is higher than anticipated. Ann Surg 2016; 264: 1082–90 CrossRef MEDLINE
e3.
Nimptsch U, Mansk T: Deaths following cholecystectomy and herniotomy: an analysis of nationwide German hospital discharge data from 2009 to 2013. Dtsch Arztebl Int 2015; 112: 535–43 VOLLTEXT
e4.
Nimptsch U, Mansky T: Trends in acute inpatient stroke care in Germany—an observational study using administrative hospital data from 2005–2010. Dtsch Arztebl Int 2012; 109: 885–92 VOLLTEXT
e5.
Wengler A, Nimptsch U, Mansky T: Hip and knee replacement in Germany and the USA: analysis of individual inpatient data from German and US hospitals for the years 2005 to 2011. Dtsch Arztebl Int 2014; 111: 407–16 VOLLTEXT
e6.
Swart E, Gothe H, Geyer S, et al.: Good practice of secondary data analysis (GPS): guidelines and recommendations. Gesundheitswesen 2015; 77: 120–6.
e7.
Swart E, Bitzer EM, Gothe H, et al.: [A consensus German reporting standard for secondary data analyses, version 2 (STROSA-Standardisierte Berichtsroutine fur Sekundardatenanalysen)]. Gesundheitswesen 2016; 78: e145–60.
e8.
Landenhed M, Engstrom G, Gottsater A, et al.: Risk profiles for aortic dissection and ruptured or surgically treated aneurysms: a prospective cohort study. J Am Heart Assoc 2015; 4: e001513.
e9.
Gesundheitsberichterstattung des Bundes: Standardbevölkerungen. www.gbe-bund.de (last accessed on 31 March 2016).
e10.
Kuhn J, Heißenhuber A, Wildner M: Epidemiologie und Gesundheitsberichterstattung: Begriffe, Methoden, Beispiele. Bayerisches Landesamt für Gesundheit und Lebensmittelsicherheit. Erlangen 2014.
e11.
Sharabiani MT, Aylin P, Bottle A: Systematic review of comorbidity indices for administrative data. Med Care 2012; 50: 1109–18 CrossRef MEDLINE
e12.
Van Walraven C, Austin PC, Jennings A, Quan H, Forster AJ: A modification of the Elixhauser comorbidity measures into a point system for hospital death using administrative data. Med Care 2009; 47: 626–33 CrossRef MEDLINE
e13.
Elixhauser A, Steiner C, Harris DR, Coffey RM: Comorbidity measures for use with administrative data. Med Care 1998; 36: 8–27 CrossRef
e14.
Lenth RV: Technical report no. 378. Post hoc power: tables and commentary. Iowa City: The University of Iowa, Department of Statistics and Actuarial Science 2007.
e15.
Quan H, Sundararajan V, Halfon P, et al.: Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 2005; 43: 1130–9 CrossRef MEDLINE
e16.
Quan H, Li B, Couris CM, et al.: Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. Am J Epidemiol 2011; 173: 676–82 CrossRef MEDLINE
Department of Vascular and Endovascular Surgery/Vascular Center, Klinikum rechts der Isar, Technical University of Munich: PD Dr. med. Kühnl, MPH, Alexander Erk, Matthias Trenner, MD,
Michael Salvermoser, M.Sc., Prof. Dr. med. Eckstein
Department of Statistics, Ludwig-Maximilians-University Munich: Prof. Dr. rer. nat. Schmid
Age-standardized hospital incidence from 2005–2014
Age-standardized hospital incidence from 2005–2014
Figure 1
Age-standardized hospital incidence from 2005–2014
Mortality (age- and risk-adjusted) for the period from 2005 to 2014
Mortality (age- and risk-adjusted) for the period from 2005 to 2014
Figure 2
Mortality (age- and risk-adjusted) for the period from 2005 to 2014
Key messages
Characteristics of the patient cohort*1
Characteristics of the patient cohort*1
Table 1
Characteristics of the patient cohort*1
Management and outcome*1
Management and outcome*1
Table 2
Management and outcome*1
The clinical perspective
eMethods
eMethods
eBox
eMethods
Patient flow diagram
Patient flow diagram
eFigure 1
Patient flow diagram
Age-standardized hospital incidence for all included AAA (left) and all included rAAA (right) from 2005–2014
Age-standardized hospital incidence for all included AAA (left) and all included rAAA (right) from 2005–2014
eFigure 2
Age-standardized hospital incidence for all included AAA (left) and all included rAAA (right) from 2005–2014
Time period 2005–2014 for the median case-mix index (top) and the median Elixhauser Comorbidity Index (bottom) for treated nrAAA (left) and rAAA (right)
Time period 2005–2014 for the median case-mix index (top) and the median Elixhauser Comorbidity Index (bottom) for treated nrAAA (left) and rAAA (right)
eFigure 3
Time period 2005–2014 for the median case-mix index (top) and the median Elixhauser Comorbidity Index (bottom) for treated nrAAA (left) and rAAA (right)
Proportion of endovascularly-treated patients presenting with nrAAA (left) or rAAA (right) during 2005–2014
Proportion of endovascularly-treated patients presenting with nrAAA (left) or rAAA (right) during 2005–2014
eFigure 4
Proportion of endovascularly-treated patients presenting with nrAAA (left) or rAAA (right) during 2005–2014
Median length of stay for patients treated for nrAAA (left) or rAAA (right) during 2005–2014
Median length of stay for patients treated for nrAAA (left) or rAAA (right) during 2005–2014
eFigure 5
Median length of stay for patients treated for nrAAA (left) or rAAA (right) during 2005–2014
Raw values for in-hospital mortality
Raw values for in-hospital mortality
eFigure 6
Raw values for in-hospital mortality
Mortality (age- and risk-adjusted) for all included AAA (left) as well as for all included rAAA (right) from 2005–2014
Mortality (age- and risk-adjusted) for all included AAA (left) as well as for all included rAAA (right) from 2005–2014
eFigure 7
Mortality (age- and risk-adjusted) for all included AAA (left) as well as for all included rAAA (right) from 2005–2014
Codes used based on OPS or ICD-10, according to the available version from DIMDI (www.dimdi.de)
Codes used based on OPS or ICD-10, according to the available version from DIMDI (www.dimdi.de)
eTable 1
Codes used based on OPS or ICD-10, according to the available version from DIMDI (www.dimdi.de)
Characteristics of excluded patients with I71.4 as a principal or secondary diagnosis but without an operative treatment (without OAR or EVAR during the stay)
Characteristics of excluded patients with I71.4 as a principal or secondary diagnosis but without an operative treatment (without OAR or EVAR during the stay)
eTable 2
Characteristics of excluded patients with I71.4 as a principal or secondary diagnosis but without an operative treatment (without OAR or EVAR during the stay)
Complications and secondary outcomes
Complications and secondary outcomes
eTable 3
Complications and secondary outcomes
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e1.Forschungsdatenzentren (FDZ) der Statistischen Ämter des Bundes und der Länder: Fallpauschalenbezogene Krankenhausstatistik (DRG-Statistik), 2005–2014, eigene Berechnungen.
e2.Nimptsch U, Krautz C, Weber GF, Mansky T, Grutzmann R: Nationwide in-hospital mortality following pancreatic surgery in Germany is higher than anticipated. Ann Surg 2016; 264: 1082–90 CrossRef MEDLINE
e3.Nimptsch U, Mansk T: Deaths following cholecystectomy and herniotomy: an analysis of nationwide German hospital discharge data from 2009 to 2013. Dtsch Arztebl Int 2015; 112: 535–43 VOLLTEXT
e4.Nimptsch U, Mansky T: Trends in acute inpatient stroke care in Germany—an observational study using administrative hospital data from 2005–2010. Dtsch Arztebl Int 2012; 109: 885–92 VOLLTEXT
e5.Wengler A, Nimptsch U, Mansky T: Hip and knee replacement in Germany and the USA: analysis of individual inpatient data from German and US hospitals for the years 2005 to 2011. Dtsch Arztebl Int 2014; 111: 407–16 VOLLTEXT
e6.Swart E, Gothe H, Geyer S, et al.: Good practice of secondary data analysis (GPS): guidelines and recommendations. Gesundheitswesen 2015; 77: 120–6.
e7.Swart E, Bitzer EM, Gothe H, et al.: [A consensus German reporting standard for secondary data analyses, version 2 (STROSA-Standardisierte Berichtsroutine fur Sekundardatenanalysen)]. Gesundheitswesen 2016; 78: e145–60.
e8.Landenhed M, Engstrom G, Gottsater A, et al.: Risk profiles for aortic dissection and ruptured or surgically treated aneurysms: a prospective cohort study. J Am Heart Assoc 2015; 4: e001513.
e9.Gesundheitsberichterstattung des Bundes: Standardbevölkerungen. www.gbe-bund.de (last accessed on 31 March 2016).
e10.Kuhn J, Heißenhuber A, Wildner M: Epidemiologie und Gesundheitsberichterstattung: Begriffe, Methoden, Beispiele. Bayerisches Landesamt für Gesundheit und Lebensmittelsicherheit. Erlangen 2014.
e11. Sharabiani MT, Aylin P, Bottle A: Systematic review of comorbidity indices for administrative data. Med Care 2012; 50: 1109–18 CrossRef MEDLINE
e12.Van Walraven C, Austin PC, Jennings A, Quan H, Forster AJ: A modification of the Elixhauser comorbidity measures into a point system for hospital death using administrative data. Med Care 2009; 47: 626–33 CrossRef MEDLINE
e13. Elixhauser A, Steiner C, Harris DR, Coffey RM: Comorbidity measures for use with administrative data. Med Care 1998; 36: 8–27 CrossRef
e14. Lenth RV: Technical report no. 378. Post hoc power: tables and commentary. Iowa City: The University of Iowa, Department of Statistics and Actuarial Science 2007.
e15. Quan H, Sundararajan V, Halfon P, et al.: Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 2005; 43: 1130–9 CrossRef MEDLINE
e16. Quan H, Li B, Couris CM, et al.: Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. Am J Epidemiol 2011; 173: 676–82 CrossRef MEDLINE