Feeling the Portuguese pulse: unveiling the hospitalisation-leading cardiac arrhythmias

Feeling the Portuguese pulse:

unveiling the hospitalisation-leading

cardiac arrhythmias

ALBERTO,M ANDRADE,T CARDOSO,S CORREIA,C MAGALHÃES,D MEDEIROS,N NEVES,A SANTOS,J TELES,A VIEIRA,B

Class 22

Introdução à

Medicina II

May 2012

Introduction:

background

[1] Lévy S, et al. Arrhythmia management for the primary clinician [Internet]. UpToDate; 2010 May [cited 2011 Oct 27]. Available from: http://www.uptodate.com/contents/arrhythmia-management-for-the-primary-care-clinician?source=preview&anchor=H4&selectedTitle=1~150#H4 2

Cardiac arrhythmias are a large group of conditions in which there is not a normal sinus rhythm and normal atrioventricular (AV) conduction.[1]

Some of the most common arrhythmias:[1]

• Atrioventricular (AV) block;• Atrial premature beats (APB);• Ventricular premature beats (VPB);• Sinus bradycardia;• Atrial fibrillation (AF).

Background

Justification and Aim

Methods

Results

Discussion

Aknowledgments

References

Influencing factors

[2] Benjamin EJ. et al. Independent risk factors for atrial fibrillation in a population-based cohort. The Framingham Heart Study. JAMA 1994;271:840–4[3] Kannel WB. et al. Prevalence, incidence, prognosis, and predisposing conditions for atrial fibrillation: population-based estimates. Am J Cardiol 1998; 82(8A):2N–9N[4] Charlemagne A. et al. Epidemiology of atrial fibrillation in France: extrapolation of international epidemiological data to France and analysis of French hospitalisation data. Archives of Cardiovascular Diseases. 2011 Feb; 104(2):115-24[5] Bonhorst D. et al. Prevalence of atrial fibrillation in the Portuguese population aged 40 and over: the FAMA study. Revista Portuguesa de Cardiologia. 2010 Mar; 29(3):331-50 3

Atrial fibrillation (AF), which affects approximately 0.4% of the global population,[2] doubles its prevalence every ten years beyond the 50 year benchmark.[3]

In the USA, roughly 70% of individuals with AF are between 65 and 85 years of age.[4]

The prevalence of AF in Portugal is higher than in other countries where similar data is available, when focusing on the population aged 40 and onwards.[5]

Background


Methods

Results

Discussion

Aknowledgments

References

AGE

Influencing factors

[6] Mathew B. et al. Obesity: effects on cardiovascular disease and its diagnosis. J Am Board Fam Med. 2008 Novâ Dec; 21(6): 562–568[7] Alves C. et al. Epidemiological data on obesity in Portugal [Internet]. 10º Congresso Português de Obesidade – Porto [2006 November]. Available from: http://www.eurotrials.com/contents/files/publicacao_ficheiro_68_1.pdf[8] Neves C. et al. Doenças da tiróide, dislipidemia, e Patologia Cardiovascular; Rev. Port Cardiol 2008; 27(10): 1211-1236

4

Fatal arrhythmias are pointedas the most frequent cause ofdeath among obese patients.[6]

Associated to greater levels of cardiovascular morbidity, including angina, myocardial infarction and arrhythmias.[8]

Hyperthyroidism increase of cholesterol synthesis [8]

Fig. 1: Prevalence of obesity in Portugal by NUT II regions, 2006[7]

Background


Methods

Results

Discussion

Aknowledgments

References

OBESITY

HYPERTHYROIDISM

Influencing factors

[9] Ishimitsu T, et al. Hypertension complicated with heart disease. Nihon Rinsho. 2011 November; 69(11):2007-14[10] Macedo M, et al. Prevalência, Conhecimento, Tratamento e Controlo da Hipertensão em Portugal. Estudo PAP. Revista Portuguesa de Cardiologia. 2007; 26(1):21-39[11] Coresh J, et al. Prevalence of chronic kidney disease in the United States. JAMA. 2007; 298: 2038-2047[12] Soliman EZ, et al. Chronic kidney disease and prevalent atrial fibrillation: the Chronic Renal Insufficiency Cohort (CRIC). Am Heart J. 2010; 159:1102-1107

5

Hypertension facilitates development and progression of cardiac diseases such as left ventricular hypertrophy (LVH), coronary artery disease (CAD), arrhythmia and heart failure.[9]

A 2007 Portuguese study (subjects aged 18 to 90 years old) pointed North as the region with the lowest prevalence of hypertension (33,4%), and Alentejo with the highest (49,5%).[10]

CKD affects up to 10% of adults [11] and carries a high risk for cardiovascular disease, including AF.[12]

Background


Methods

Results

Discussion

Aknowledgments

References

HYPERTENSION

CHRONIC KIDNEY DISEASE (CKD)

Influencing factors

[13] Aubin MC, et al. A high-fat diet increases risk of ventricular arrhythmia in female rats: enhanced arrhythmic risk in the absence of obesity or hyperlipidemia. J Appl Physiol. 2010; 108: 933–940[14] Huxley R, et al. Type 2 diabetes, glucose homeostasis and incident atrial fibrillation: the Atherosclerosis Risk in Communities Study. Heart. 2012 January; 98(2): 133–138[15] Watanabe H, et al. Association Between Lipid Profile and Risk of Atrial Fibrillation. Official Journal of the Japanese Circulation Society. 6

DM increases the incidence of cardiac arrhythmias.[13]

Individuals with DM had one third greater risk of incident AF compared with those without diabetes after adjustment with no evidence of interactions with race or gender.[14]

Hyperlipidemia, an important risk factor for cardiovascular disease, may be associated with AF.[15]

Background


Methods

Results

Discussion

Aknowledgments

References

DIABETES MELLITUS (DM)

HYPERLIPIDEMIA


7

Current challenge: swiftly manage growing numbers of patients with cardiac arrhythmias.

Analyse Portuguese arrhythmia-caused hospitalisations from 2000 to 2008, dividing it by NUT II regions and age groups;

Resort to population age, Hypertension, Diabetes Mellitus, Hyperthyroidism, Obesity, Chronic Kidney Disease and Hyperlipidemia to try and explain our findings;

Study the evolution of the arrhythmias and associated factors.

Main goal: to find out whether there is or not an asymmetrical distribution in hospitalisations due to cardiac arrhythmias in Portugal, and to provide a possible explanation for those findings.

Background


Methods

Results

Discussion

Aknowledgments

References

Methods: participants

8

Patients resident in mainland Portugal

Mainland Portuguese public

acute care hospitals with

discharges

Between 2000 and 2008

Principal diagnosis codified in ICD-9-CM as “426 Conduction disorders” or “427

Cardiac dysrhythmias”

Hospitalisations

Patient’s age ranged from 0 to 108 years.

51,8 %

48,2 % Male (58 839)

Female (54 792)

Background


Methods

Results

Discussion

Aknowledgments

References

Number of episodes113 631

Methods: Portugal by NUT II regions

[16] INE – Instituto Nacional de Estatística. Available from: http://www.ine.pt/xportal/xmain?xpid=INE&xpgid=ine_princindic 9

Mainland Portugal is currently divided into five NUT II regions:

Fig. 2: Portugal map by NUT II regions [16]

North

Centre

Alentejo

Algarve

Lisbon

Background


Methods

Results

Discussion

Aknowledgments

References

Methods: study design

[17] Trochim W. Time in research [Internet]. Research Methods Knowledge Base; 2006 November [cited 2011 Dec 2]. Available from: http://www.socialresearchmethods.net/kb/timedim.php 10

This study is both descriptive and relational.[17]

Covers a nine-year period (2000-2008).

Each episode was analysed only once: cross-sectional study.[17]

Readmissions were considered independent (new) episodes.

Should be regarded as an epidemiologic study.

Background


Methods

Results

Discussion

Aknowledgments

References

Methods: data collection

[18] Quan H. et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Medical Care. 2005 Nov; 43(11):1130-9 11

Database was provided by Department of Health Information and Decision Sciences, Faculty of Medicine, University of Porto.

Papers about cardiac arrhythmias: to relate them with age, gender, demographic or geographic data,

hyperthyroidism, obesity, hypertension, chronic kidney disease, diabetes mellitus and hyperlipidemia .

ICD-9-CM arrhythmia diagnosis codes based on Quan H. et al. [18]

• 426 Conduction disorders• 427 Cardiac dysrhythmias

Main data collection method: on-line research on Pubmed.

Background


Methods

Results

Discussion

Aknowledgments

References

Methods: Variables description

12

Principal diagnosis

426 and 427 ICD-9-CM codes

Secondary diagnosis

Chosen based on frequency

Congestive heart failure, Syncope and Collapse, Atrial Fibrillation and Chronic Isquemic Heart Disease• Heart related diseases: Excluded from the analysis

Obesity, Hyperlipidemia, Chronic Kidney disease and Diabetes Mellitus

Hypertension• Appeared twice: Frequencies were merged

Background


Methods

Results

Discussion

Aknowledgments

References

10

Methods: Variables description

13

Demographic variables:

Gender

Patient’s age group

Patient’s residence by NUT II regions

Portuguese population data

Ageing Index

[16] INE – Instituto Nacional de Estatística. Available from: http://www.ine.pt/xportal/xmain?xpid=INE&xpgid=ine_princindic

Obtained from INE[16]

Background


Methods

Results

Discussion

Aknowledgments

References

Methods: Statistical analysis

14

IBM SPSS Statistics v20® and Microsoft Office Excel 2010®

Unpaired, two-tail t-tests and Welch tests 95% CI (confidence intervals) Frequencies Logistic regression

Background


Methods

Results

Discussion

Aknowledgments

References

Results

15

Table 1 – Characteristics of the patients hospitalised due to cardiac arrhythmias, from 2000 to 2008, in mainland Portugal.Note: Readmissions were considered independent episodes.

Gender and age distribution were very similar across all NUT II regions, as expected.

In particular, all five regions registered their greatest number of hospitalisations in patients within the 75-79 years old range.

Background


Methods

Results

Discussion

Aknowledgments

References

Results

16

Table 2 – Number of Hospitalisations (NOH) per a hundred thousand inhabitants, by year and NUT II region. Note: Results were obtained by dividing the NOH of each region for its total population, times a hundred thousand.

Background


Methods

Results

Discussion

Aknowledgments

References

Results

17

Chart 1 – Number of Hospitalisations (NOH) per a hundred thousand inhabitants, by year and NUT II region.Note: Results were obtained by dividing the NOH of each region for its total population, times a hundred thousand.

Background


Methods

Results

Discussion

Aknowledgments

References

Results

18

Table 3 – p-values* for comparisons between the values of the NUT II regions.Note: *Obtained through t-tests.

There was a general trend of increasing hospitalisations per year. Lisbon is the sole exception, showing an inversion to negative evolution between 2005 and 2006.

Regarding NOH per a hundred thousand inhabitants, North stands clearly apart from all other regions.

Background


Methods

Results

Discussion

Aknowledgments

References

Results

19

Table 4 – Ageing Index (AgIdx) by NUT II regions, from 2000 to 2008.Notes: Ageing Index: quotient between the number of people of 65 years-old or more and the number of those of 14 or less years-old. It is expressed in number of elders by 100 youngsters; *Obtained through Welch test.

The Ageing Index rose steadily in North and Centre, while it hovered around the same values in the remaining regions.

North is, concerning general population, by far the youngest region, in contrast with Alentejo.

Background


Methods

Results

Discussion

Aknowledgments

References

Results

20

Chart 2 – Number of Hospitalisations (NOH) per a hundred thousand inhabitants, by age group and NUT II region.

Background


Methods

Results

Discussion

Aknowledgments

References

Notes: Results were obtained by dividing the NOH of each region for its total population by age group, times a hundred thousand. A nine year average was used for values of NOH and population by age group.

Results

21

Hypertension

Diabetes mellitus

Hyperlipidemia

Congestive heart failure

Syncope and colapse

Chronic kidney disease

Atrial fibrillation

Chronic ischemic heart disease

Obesity

0 5 10 15 20 25 30 35Percentage (%)

Chart 3 – Most frequent secondary diagnoses registered on patients at time of admission.

Hypertension was the most registered disease, having being diagnosed to 29,1% of patients.

Hyperthyroidism, despite not appearing in this chart, is a well-known arrhythmia-potentiating factor, so was included for analysis.

Background


Methods

Results

Discussion

Aknowledgments

References

Results

22

Table 5 – Number of hospitalisations with Hypertension, Obesity, Hyperlipidemia, Chronic Kidney Disease (CKD), Hyperthyroidism or Diabetes Mellitus (DM) as secondary diagnoses, per a hundred thousand hospitalisations due to cardiac arrhythmias and per NUT II region.

Background


Methods

Results

Discussion

Aknowledgments

References

Results

23

Background


Methods

Results

Discussion

Aknowledgments

References

Table 6 – Odds ratio for secondary diagnoses and demographic variables on the hospitalisations motivated by cardiac arrhythmias.Notes: All hospitalisations in mainland Portugal from 2000 to 2008 were included in this logistic regression. The dependent variable was the principal diagnosis leading to the hospitalisation: 1 – cardiac arrhythmia; 0 – other.* For secondary diagnoses: number of hospitalisations featuring that disease as secondary diagnosis.† For demographic variables: number of hospitalisations in that region.** Base category for odds ratio determination.

Discussion

24

Age is a risk factor in the emergence of cardiac arrhythmias (AOR = 1,04).

All co-morbidities (secondary diagnoses excluding heart-related diseases ), bar CKD and DM, obtained significant adjusted odds ratio values above 1 for hospitalisations due to arrhythmias.

DM apparently turned out being a protective factor, in contrast with what is described.

Hyperthyroidism deserves a special attention, since it is the most important factor for the appearance of cardiac arrhythmias: individuals with hyperthyroidism are 3,45 times likelier to develop arrhythmias than those without this condition.

Background


Methods

Results

Discussion

Aknowledgments

References

Discussion

25

There is no significant difference between Centre, Alentejo and Algarve regarding NOH per a 100 000 inhabitants, nor when eliminating the factor age.

This proved to be strange, because Centre features a lower NOH with any co-morbidities than Alentejo or Algarve and a lower AOR.

A counterbalance between age influence and co-morbidities could explain chart 1, but age was shown to be irrelevant for comparing these three regions (chart 2).

Background


Methods

Results

Discussion

Aknowledgments

References

Discussion

26

Chart 1 brings all attention to North, which registered the lowest NOH per a 100 000 inhabitants.

Lisbon does not stand apart from Centre, Alentejo and Algarve. However, when the age groups are included, age’s influence is

eliminated and significant differences are found for both North and Lisbon in comparison with the other three regions and between themselves (chart 2), but while North still has the lowest ratios, Lisbon holds the worst scenario.

Since North and Lisbon are the youngest regions, some conclusions can be withdrawn:

regarding North, a young population means more protection (other factors also contribute to a low NOH/100 000 inhabitants);

concerning Lisbon, age influence is offsetting co-morbidities, resulting in an outcome on the level of Centre, Alentejo and Algarve. Without age’s protective effect, hospitalisations in Lisbon rose sharply.

In fact, when accounting all the factors, Lisbon has a AOR of 1,56 in comparison with North.

Background


Methods

Results

Discussion

Aknowledgments

References

Discussion

27

North presents higher values of NOH with Obesity, Hyperlipidemia, CKD and DM per a 100 000 hospitalisations due to arrhythmias than Lisbon.

Obesity and Hyperlipidemia increase the odds of being hospitalised due to arrhythmias (Adjusted Odds Ratio (AOR) = 1,17 and AOR=1,14) and are higher in North, which seems to be a contradiction.

However, Hypertension (AOR = 1,30) and Hyperthyroidism (AOR = 3,45) are both more frequent in Lisbon and are more relevant (higher AOR) than Obesity and Hyperlipidemia.

As such, we suppose that hypertension and hyperthyroidism are at the root of the differences found in chart 2.

Nonetheless, we believe they are not the unique reasons for such glaring disparities.

Background


Methods

Results

Discussion

Aknowledgments

References

Conclusions

28

Background


Methods

Results

Discussion

Aknowledgments

References

Age distribution is a major contibutor in assessing the susceptibility of a population to hospitalisation-leading cardiac arrhythmias.

With this factor eliminated, hypertension’s and hyperthyroidism’s prevalence are the most relevant influencers in the number of hospitalisations.

Conclusions

29

Background


Methods

Results

Discussion

Aknowledgments

References

North population has a lower risk of being hospitalised than Lisbon population.

This may be due to the North’ relative youth and to a greater prevalence of hyperthyroidism and hypertension in Lisbon. Nonetheless, we suspect there are other underlying reasons contributing to these results.Centre, Algarve and Alentejo were similar in terms of number of hospitalisations. However, this was an unpredictable result, revealing the high degree of complexity on the epidemiology of cardiac arrhythmias.

Therefore, further studies on this issue are encouraged.

Limitations

30

Some important information is not routinely collected, for example information related to secondary diagnoses. The high prevalence of cardiac arrhythmias as principal diagnosis might be explained by the increase in repeated hospitalisations, (readmissions were considered as independent events).

This could also introduce some bias on the results.

Background


Methods

Results

Discussion

Aknowledgments

References

Acknowledgments

31

We would like to express thanks to:

• Professor Doutor Alberto Freitas, for his continuous commitment, guidance and advice;

• Professor Doutor Altamiro da Costa Pereira, for his constructive criticisms and sharp suggestions to improve our work;

• Professor Fernando Lopes, for decisive orientation on a critical step of our work.

Special thanks go to supervisor Vasco Santos, whose knowledge and assistance was essential for the successful completion of this study.

Background


Methods

Results

Discussion

Aknowledgments

References

References

32

[1] Lévy S. et al. Arrhythmia management for the primary clinician [Internet]. UpToDate; 2010 May [cited 2011 Oct 27]. Available from: http://www.uptodate.com/contents/arrhythmia-management-for-the-primary-care-clinician?source=preview&anchor=H4&selectedTitle=1~150#H4

[2] Benjamin EJ. et al. Independent risk factors for atrial fibrillation in a population-based cohort. The Framingham Heart Study. JAMA 1994;271:840–4

[3] Kannel WB. et al. Prevalence, incidence, prognosis, and predisposing conditions for atrial fibrillation: population-based estimates. Am J Cardiol 1998; 82(8A):2N–9N

[4] Charlemagne A. et al. Epidemiology of atrial fibrillation in France: extrapolation of international epidemiological data to France and analysis of French hospitalisation data. Archives of Cardiovascular Diseases. 2011 Feb; 104(2):115-24

[5] Bonhorst D. et al. Prevalence of atrial fibrillation in the Portuguese population aged 40 and over: the FAMA study. Revista Portuguesa de Cardiologia. 2010 Mar; 29(3):331-50

[6] Mathew B. et al. Obesity: effects on cardiovascular disease and its diagnosis. J Am Board Fam Med. 2008 Novâ Dec; 21(6): 562–568

[7] Alves C. et al. Epidemiological data on obesity in Portugal [Internet]. 10º Congresso Português de Obesidade – Porto [2006 November]. Available from: http://www.eurotrials.com/contents/files/publicacao_ficheiro_68_1.pdf

Background


Methods

Results

Discussion

Aknowledgments

References

References

33

[8] Neves C. et al. Doenças da tiróide, dislipidemia, e Patologia Cardiovascular; Rev. Port Cardiol 2008; 27(10): 1211-1236

[9] Ishimitsu T, et al. Hypertension complicated with heart disease. Nihon Rinsho. 2011 November; 69(11): 2007-14

[10] Macedo M, et al. Prevalência, Conhecimento, Tratamento e Controlo da Hipertensão em Portugal. Estudo PAP. Revista Portuguesa de Cardiologia. 2007; 26(1): 21-39

[11] Coresh J, et al. Prevalence of chronic kidney disease in the United States. JAMA. 2007; 298: 2038-2047

[12] Soliman EZ, et al. Chronic kidney disease and prevalent atrial fibrillation: the Chronic Renal Insufficiency Cohort (CRIC). Am Heart J. 2010; 159: 1102-1107

[13] Aubin MC, et al. A high-fat diet increases risk of ventricular arrhythmia in female rats: enhanced arrhythmic risk in the absence of obesity or hyperlipidemia. J Appl Physiol. 2010; 108: 933–940

[14] Huxley R, et al. Type 2 diabetes, glucose homeostasis and incident atrial fibrillation: the Atherosclerosis Risk in Communities Study. Heart. 2012 January; 98(2): 133–138

[15] Watanabe H, et al. Association Between Lipid Profile and Risk of Atrial Fibrillation. Official Journal of the Japanese Circulation Society

Background


Methods

Results

Discussion

Aknowledgments

References

References

34

[16] INE – Instituto Nacional de Estatística. Available from: http://www.ine.pt/xportal/xmain?xpid=INE&xpgid=ine_princindic

[17] Trochim W. Time in research [Internet]. Research Methods Knowledge Base; 2006 November [cited 2011 Dec 2]. Available from: http://www.socialresearchmethods.net/kb/timedim.php

[18] Quan H. et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Medical Care. 2005 Nov; 43(11): 1130-9

Background


Methods

Results

Discussion

Aknowledgments

References

Documents

Feeling the Portuguese pulse: unveiling the hospitalisation-leading cardiac arrhythmias