André Maia Bárbara Moura David João Inês Machado José Silva Liliana Costa Márcio Mesquita...

André MaiaBárbara MouraDavid JoãoInês MachadoJosé SilvaLiliana Costa

Márcio MesquitaMaria Inês RochaIsabel RodriguesPedro NóvoaRui SilvaSara Ramos T20

1. Research Question2. Introduction 3. Main Aims4. Participants and Methods

4.1- Study Participants4.2- Study Design4.3- Variables Description4.4- Confidentiality

5. Results5.1- Summary of the Statistical Analysis 5.2 -Mortality Rates5.3 -Risk Factors Survival Curves5.4 -Complications Crosstable and Chi-Square Test5.5 -Kaplan Meier Survival Curve

6. Discussion7. Conclusion8. References

Index

rAAA: what are the mortality risk factors and the short and

long term mortality rate?

1. Research Question

2. Introduction

The rupture of the aneurism of the infra-renal abdominal aorta:

– very important cause of unheralded deaths in people older than 55 years.

– asymptomatic – with high mortality rates

3.Main Aims• Determining the mortality rates of rAAA patients

admitted in the Angiology and Vascular Surgery Department of HSJ;

• Elaborating a Survival Curve using the Kaplan-Meier method;

• Studying the development of rAAA patients’ condition after surgery;

• Establishing the most common complications caused by surgery;

• Identifying the mortality risk factors associated with ruptured AAA.

4. Participants and Methods

• Target Population– Hospital de São João’s patients.

• Unit of analysis– Each of the patients selected

4.1 Participants and Methods – Study Participants

• Inclusion criteria– Patients admitted to Angiology and Vascular Surgery Department

of HSJ with rAAA in the past 10 years;• Exclusion criteria

– Patients who perished upon hospital arrival, but before entering the operating room;

– Patients whose records lack key information, and whose inclusion would compromise the integrity of the results;

– Patients that lack a minimum number of variables and therefore cannot be used in the analysis;

• Unit of analysis– Each of the patients selected



Data collection: 110 patients

Data collection: 110 patients Data RevisionData Revision Final Count:

109Final Count:

109

AnalysisAnalysis

1 patient excluded

That patient was excluded

because he/she was lacking key

information (Date of Death and

Risk Factors) for the analysis.

4.2 Participants and Methods – Study Design• Classification of the study:

– Retrospective cohort;

• Methods• The first phase consisted in collecting data from the paper

clinical files• Given that several data were missing, a second phase,

regarding research through SAM (“Sistema de Apoio ao Médico”) was required

• Research through SAM still left missing information, so a third phase was employed, which consisted in contacting the surviving patients whose phone number was available

4.3 Participants and Methods – Variables Description

Each patient will be assigned an identification number;The following variables will be collected from the databases: • Identification number• ND• Name• Gender• Date of birth• Phone number• Risk factors:

– Hypertension– COPD– Smoker– Family History– Diabetes– Other risk factors

• Surgery date• ICU exit date• Hospital discharge date• Internment days• Complications:

− Respiratory complications− Cardiac complications− Renal complications

• Aneurism diameter

• Date of death• Death (Dead, Alive)• Timing of death (Operatory,

Hospitalar, After Discharge)• Reintervention date• Age at the Date of the Surgery• Contact Status (Answered, Did

Not Answer, Incorrect Phone Number, Answered but Didn’t Cooperate)

• Age group• Kaplan-Meier Time

4.4 Participants and Methods – Confidentiality

• The voluntary reporting of sensitive outcome data could be compromised unless absolute anonymity was assured;

• The aforementioned identification numbers function as a way to preserve confidentiality;

• Consequently, data is stored in such a way that patients can not be identified, in two different databases:

– The first with NDs, names and contacts;– The second with the other variables.

5. Results

5.1 Summary of the statistical analysis

The data was treated using the SPSS software in order to:1. Determine the mortality rates associated with rAAA in HSJ2. Determine the most common mortality risk factors and

their influence on the mortality rates of rAAA3. Establish the main complications due to the intervention4. Elaborate a Survival Curve using the Kaplan-Meier

estimator method.

5.2 Mortality Rates

Distribution by Gender of Deceased patients

Frequency Valid Percent Cumulative Percent

Male 64 89,9 89,9

Female 7 10,1 100

Total 71 100

Distribution of patients according to age

5.2 Mortality Rates

n = 109

5.2 Mortality Rates

n = 71

5.3 Risk Factors Survival Curves - Hypertension

Time (days) % of surviving patients

1 83

6 65

13 58

31 52

188 39

422 36

Diagnosed

n=57


9 80

70 40

818 0

Diagnosed

5.3 Risk Factors Survival Curves - COPD

n=5


1 92

6 76

12 70

26 58

94 51

432 47

Diagnosed

5.3 Risk Factors Survival Curves - Smoking

n=37


6 75

31 50

Diagnosed

5.3 Risk Factors Survival Curves – Family history

n=4


1 88

6 71

13 58

24 51

99 32

Diagnosed

5.3 Risk Factors Survival Curves - Diabetes

n=17

5.4 Complications Crosstable and Chi-Square Test

• A Chi-Square was employed in order to find out the level of statistical significance

regarding the relationship between the risk factor smoking and mortality.

• The test returned a value of p=0,195.

• Thus, the null hypothesis was accepted (there is no relation between the two

variables).





variables).

n= 51 n= 58





• Thus, the null hypothesis was rejected (there is a relation between the two

variables).




• Thus, the null hypothesis was rejected (there is a relation between the two

variables).

n= 43 n= 66






variables).





variables).

n= 46 n= 63

5.5 Kaplan Meier Survival Curve


1 72

7 58

15 51

31 45

188 33

422 31

n= 109

6. Discussion

6. Discussion of the results

• During the study several inconsistencies were found when collecting data:– The data was incorrectly inserted, or missing, leading to wrong assumptions

such as “Non Diagnosed” patients;– Some risk factors are more accessible than others.

• Considering the way that data was collected, hypertensive patients weren’t as easily identified as smokers;

• As for the risk factor “Smoking”, one possible explanation for this situation could be that it was probably easier for contacted people and the aforementioned relatives to remember about the existence of this factor in comparison to the remaining factors.

– Statistical analysis was therefore affected by these misconceptions. • Example: smoking patients showed a slower death rate than those who

were not diagnosed as smokers. Still, we can not assume this dismisses smoking habits as a risk factor for the rupture of the rAAA.

6. Discussion of the results

• A number of factors may have contributed to the bias observed in the results:

– The decreasing quality of data as it approaches the first years of the study, in both the paper and the electronic archives;

– The low size of the sample (n=109);

– The dubious quality of information provided by the relatives of the contacted people (that is, the people who spoke in their place when they were unavailable);

– The low rate of useable phone numbers

7. Conclusion– Firstly, we can conclude that the mortality rates associated with the rupture of AAA are as high

as referenced in the literature, reaching a value of 65,1% of deaths in patients admitted in the Angiology and Vascular Surgery Department of HSJ with rAAA;

– We have also established that the patients’ deaths occurred mostly during their hospital stay, although there was also a high percentage of deaths occurring during the surgery. Those who were released from the hospital survived for a considerable period of time;

– From the complications gathered from the patients’ clinical files, we assembled three general categories (pulmonary, cardiac and renal complications). None was found to be prevalent, although all of them could be tightly related with the high mortality registered;

– Due to a lack of significance in the results of our statistical analysis, we were unable to conclusively correlate the considered risk factors with actual patient mortality;

– Even though we managed to achieve one of our main goals, namely elaborating a Survival Curve, the rest of our objectives were not fully accomplished given the lack of available information.

8. References

• Kubin K, Sodeck GH, Teufelsbauer H, Nowatschka B, Kretschmer G, Lammer J, Schoder M. Endovascular therapy of ruptured abdominal aortic aneurysm: mid- and long-term results http://www.ncbi.nlm.nih.gov/pubmed/18180989?ordinalpos=15&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_DefaultReportPanel.Pubmed_RVDocSum

• Qureshi NA, Rehman A, Slater N, Moss E, Shiralkar S, Patel RT, Grimley RP, Jayatunga AP. Abdominal aortic aneurysm surgery in a district general hospital: a 15-years experience http://www.ncbi.nlm.nih.gov/pubmed/17512166?ordinalpos=19&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_DefaultReportPanel.Pubmed_RVDocSum

André Maia Bárbara Moura David João Inês Machado José Silva Liliana Costa Márcio Mesquita...

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