Analysis of the effect of pneumonia on mortality (ORACLE-RF)

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Alexander G. Arutyunov, Anna V. Sokolova, Grigoriy P. Arutyunov, Dmitry O. Dragunov
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e0205
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Abstract: 
Objective — To analyze the effect of pneumonia on mortality among patients with circulatory decompensation. Material and methods — The study was based on the ORACLE-RF registry containing information obtained from 20 cities in Russia. Patients were monitored for one year. The research included men and women with symptoms of chronic heart failure during circulatory decompensation period. The patients' average age was 67±13 years. Final analysis included 2404 patients. Results — Hospital mortality was at 9%. By the 30th day of observation, overall mortality rate stood at 13%. Within the year, the overall mortality rate was 43%. Pneumonia and chronic kidney disease (CKD) had the most pronounced effect on death risk – 49.5% and 47.2%. The study showed that patients who do not have pneumonia and CKD among other associated diseases were 2.5 times more likely to survive after 360 days of observation than patients who have them among other associated diseases. The chances of favorable prognosis in patients without pneumonia are 1.7 times higher than in patients with pneumonia among other diseases. Conclusion — Pneumonia probably triggered the decompensation mechanism and significantly increased mortality in these patients.
Cite as: 
Arutyunov AG, Sokolova AV, Arutyunov GP, Dragunov DO. Analysis of the effect of pneumonia on mortality (ORACLE-RF). Russian Open Medical Journal 2020; 9: e0205.

Introduction

Analysis of major registries from around the world over the past decade [1–8] has convincingly shown that in-hospital mortality, annual mortality, and rehospitalization after discharge remain extremely high in patients with circulatory decompensation. In most countries, hospitalization for chronic heart failure (CHF) dominates in hospitals. Hospitalization itself is an independent factor in the increasing risk of death in heart failure [9]. In 2013, a survey carried out in 136 centers in 12 European countries among 5,118 patients showed that the mortality rate in patients with circulatory decompensation at 1 year was 17.4%, which is 2.4 times higher than the same indicator in patients who did not have episodes of decompensation within the year [10]. Infectious pulmonary diseases remain one of the leading non-cardiac causes of death in patients with heart failure [11].

Objective: To analyze the effect of pneumonia on mortality among patients with circulatory decompensation.

 

Material and Methods

Research design

The study was based on the ORACLE-RF registry containing information from 20 cities in Russia. Patients were monitored for one year.

The registry included men and women over 18 years old:

i)       With symptoms of chronic congestive heart failure of any etiology during the circulation decompensation period requiring hospitalization;

ii)     With clinical signs of volume overload, as evidenced by at least two of the following: 1. Shortness of breath or orthopedic position; 2. Bubbling rale; 3. Peripheral edema; 4. Increased jugular venous pulse; 5. Chest x-ray showing signs of stagnation in pulmonary circulation; 6. Plasma BNP level of >150 pg\ml or NT-proBNP level of ≥450 pg\ml.

iii)    Those who wish to participate in the registry and sign an informed consent.

Exclusion criteria: This study has no exclusion criteria.

 

Patients

The study included 2,498 patients. Final analysis included 2,404 patients. Contact with 94 patients (3.76% of the total number of patients) in the post-hospital period was lost (Appendix 1, Appendix 2).

The clinical profile of the patients is presented in Table 1.

 

Table 1. Clinical profile of patients (n=2,498)

Patient characteristics

Value

Age, years

67±13

Female patients, %

53

BMI, kg/m2

29.5±6.8

BMI>30 kg/m2, %

33

SBP, mmHg

140±27

DBP, mmHg

84±14

Heart rate, bpm

87±21

Respiration rate, breaths per minute

21±5

Body temperature, 0C

36.6±0.33

Bubbling rale, %

76

Ascites, %

16

Leg swelling, %

73

Ejection fraction, %

48±13

Laboratory findings

 

Hemoglobin, g/L

132±22

Leukocytes, 109 /l

7.8±3.15

Glycose, mmol/L

5.3 (4.6, 6.6)

Creatinine, mcmol/L

97.0 (80.0, 120.0)

MDRD GFR, ml/min

78.5 (59.0, 100.0)

Urea, mmol/L

7.0 (5.4, 9.6)

Δ creatinine > 0.3 mg/dL (%)

9

CRP, mg/L (on admission)

6.0 (4.0, 16.0)

Total cholesterol, mmol/L

4.8±1.4

Total bilirubin, mmol/L

14.7 (11.0, 21.0)

International Classification of Diseases (ICD)

 

Atrial fibrillation, %

48

CHF class III – IV NYHA FC, %

80

CHD, %

77

COPD, %

16

CKD, %

23

Rheumatic heart disease, %

1

Diabetes, %

24

History of acute cerebrovascular accident, %

11

Pneumonia on admission, %

17

Pyelonephritis, %

21

Hepatic cirrhosis, %

8

Trophic ulcers, %

6

Cancer, %

5

BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; MDRD GFR, estimated glomerular filtration rate using Modification of Diet in Renal Disease (MDRD) formula; CRP, C-reactive protein; CHF, chronic heart failure; CHD, coronary heart disease; COPD, Chronic obstructive pulmonary disease; CKD, chronic kidney disease.

 

Statistical analysis

Analytics software package Statistica 10 was used to statistically process obtained data. The Shapiro-Wilk test was used to determine that the data set comes from a normal distribution. Methods of nonparametric and parametric statistics were used to present results. Quantitative indicators were presented in the form of mean value with standard deviation – M±SD or median with lower and upper quartiles – Me (LQ, UQ). Multivariate analysis was performed using the Cox proportional hazards model. Survival analysis was evaluated using the Kaplan-Meier method. Logistic regression was used to predict the likelihood of a fatal outcome. The odds ratio (OR) or risk relation (RR) criterion was used to determine the significance of the influence of a particular factor on mortality. Values p<0.05 were recognized as statistically significant.

 

Results

Overall mortality in patients with circulatory decompensation

The data presented suggests that hospital mortality was 9%. The highest mortality rate was observed in the first 30 days after discharge from hospital. The overall mortality rate by the 30th day of observation was 13%. Moreover, women over 60 years of age had considerably higher mortality – more than that in men of the same age category – 19.4% vs 16%, respectively (p>0.05). During the year, the overall mortality rate was 43%. Analysis of the parameters reflecting patients' comorbid status revealed the ones with the most significant effect on mortality (see Table 2). The most pronounced influence on the risk of death came from pneumonia (49.5% mortality), chronic kidney disease (CKD) (47.2% mortality) and cirrhosis (45.7% mortality). This indicates that these conditions are highly significant in the structure of mortality in patients with decompensated chronic heart failure.

 

Table 2. Multivariate Cox analysis: Effect of various predictors on mortality

ICD

Beta

p

RR

95% CI

Pneumonia

0.204

<0.05

1.22

1.04-1.44

CKD

0.180

>0.05

1.19

1.01-1.41

Cirrhosis

0.130

>0.05

1.15

0.92-1.43

High blood pressure

0.012

>0.05

1.01

0.84-1.21

Atrial fibrillation

0.221

<0.05

1.24

1.09-1.42

COPD

-0.120

>0.05

0.87

0.73-1.04

ACA

0.202

>0.05

1.22

0.99-1.50

χ2= 24.3, p<0.001. CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; ACA, acute cerebrovascular accident; RR, risk relation; CI, confidence interval.

 

Odds ratio of a favorable outcome for patients who have been diagnosed with pneumonia among other associated diseases

For statistical analysis, all patients were divided into groups depending on combination of specific diseases. The following groups were identified:

1. Group 1 – pneumonia + associated diseases (with cirrhosis and/or CKD)

2. Group 2 – pneumonia + associated diseases (without cirrhosis and/or CKD)

The chances of survival in the patients divided into groups with different combinations of associated diseases are as follows: OR1=0.78 and OR2=1.33.

Patients who do not have pneumonia and CKD among other associated diseases are 2.5 times more likely to survive after 360 days of observation than patients who have the two conditions among other associated diseases. The chances of favorable prognosis in patients without pneumonia are 1.7 times higher than in patients with pneumonia among other diseases.

 

Discussion

Pronounced comorbidity is the most important feature of the modern clinical portrait of a patient with circulatory decompensation. Apart from the widely discussed hypertension and diabetes, it includes coronary heart disease (CHD), chronic obstructive pulmonary disease (COPD), CKD, anemia, bacterial chronic and acute diseases.

Our study showed a rather high incidence (17% of cases) of pneumonia than in the often-cited registries [1-10]. For instance, the Cardiovascular Health Study, analyzing 5880 patients older than 65 years, who were observed for more than 10 years, showed that pneumonia developed in 10% of patients with cardiovascular disease. It was also shown that a combination of heart failure and pneumonia requiring hospitalization increased the risk of death by 4.9 times [12, 13]. In a study by Kaplan et al. [14], the authors analyzed 67,162 patients hospitalized for decompensated heart failure and patients who made up the comparison group without signs of heart failure. Comparison of groups showed that CHF presence increases the risk of developing pneumonia by 1.82 times. The highest risk was observed among patients receiving loop diuretics. In the NHANES I Epidemiologic Follow up study, observation of 5,474 patients over 55 years of age over the course of 12 years showed that pneumonia developed most often among patients with circulatory failure (16%), cancer, diabetes and muscle deficiency. Thus, pneumonia occurs quite often both in patients with decompensated heart failure and in patients with stable course of heart failure, including in the Russian population. Our study (within the ORACLE-RF registry) showed that the risk of death in patients with pneumonia increased significantly more (RR=1.22 [95% CI 1.04; 1.44]) than in the OPTIMIZE-HF registry, where the presence of pneumonia increased the risk of death by only 10.6% [5], or in the V.F. Corrales-Medina meta-analysis (4,215 patients), where increased risk of death was 23.9% [95% CI 16.9-32.6] [15]. Such a result can only be explained by the greater initial comorbidity and the greater initial severity of Russian patients.

 

Conclusion

So, too many pneumonia cases at the time a patient with decompensated heart failure is hospitalized represents an important feature of the Russian population. Spectrum of bacterial flora in these patients does not always correspond to the classical spectrum of community-acquired pneumonia – a significant proportion in the spectrum of flora is occupied by the flora, which is more typical for hospital-acquired pneumonia. Pneumonia probably triggered the decompensation mechanism and significantly increased mortality in these patients.

 

Ethical approval

The study was approved by the Ethics Committee of Pirogov Russian National Research Medical University via Report No. 122, dated September 2, 2010.

 

Limitations

The study did not monitor research centers. The authenticity of the primary information was confirmed by a medical doctor – a researcher. The study was performed in therapeutic and cardiology departments and did not involve resuscitation departments.

 

Conflict of interest

The authors declare no conflict of interest.

 

Funding

The registry was maintained with support from the Russian Scientific Medical Society of Therapists.

 

Acknowledgement

The research team wishes to express its profound gratitude to Professor S.A. Shalnova and Professor A.D. Deev for their counselling assistance in organizing and conducting the research.

 

Appendix 1. Distribution of patients of different age groups by gender, considering the number of rehospitalizations and localization of foci of pneumonia

 

Localization

Number of rehospitalizations

1

2

3

4

50 to 59 years old

 

Male patients

Right lower lobe

4

0

0

1

Left lower lobe

0

1

0

0

Right lower lobe + Left lower lobe

0

2

0

0

Right lower lobe + Left upper lobe

0

0

1

0

Female patients

Right lower lobe

4

0

0

0

Right lower lobe + Left lower lobe

1

0

0

0

60 to 69 years old

 

Male patients

Right middle lobe

0

0

1

0

Right lower lobe

6

1

0

0

Left lower lobe

0

3

2

0

Right lower lobe + Left lower lobe

4

2

2

0

Female patients

Right middle lobe

0

0

1

0

Right lower lobe

11

4

0

0

Left lower lobe

0

0

0

1

Right middle lobe + Left lower lobe

0

0

0

0

Right lower lobe + Left lower lobe

3

1

2

0

70 years and above

 

Male patients

Right lower lobe

12

3

1

0

Left lower lobe

1

1

0

0

Right lower lobe + Left lower lobe

5

0

0

0

Right middle lobe + Left upper lobe

0

0

1

0

Female patients

Right middle lobe

5

6

1

0

Right lower lobe

24

0

1

0

Left lower lobe

7

0

1

0

Right lower lobe + Left lower lobe

14

9

0

0

Right lower lobe + Left upper lobe

0

0

0

2

 

Appendix 2. Distribution of patients of different age groups by gender, considering frequency of deaths and localization of foci of pneumonia

 

Localization

Distribution of deceased/survivors by period

Surv.

30 days

90 days

180 days

360 days

decd.

surv.

decd.

surv.

decd.

surv.

decd.

surv.

 

50 to 59 years old

 

 

Male patients

Right lower lobe

0

9

2

7

0

7

1

6

9

Left upper lobe

0

1

0

1

0

1

1

0

1

Left lower lobe

0

3

0

3

0

3

0

3

3

Right lower lobe + Left lower lobe

1

3

1

2

0

2

1

1

4

Surv.

1

16

3

13

0

13

3

10

17

Female patients

Right lower lobe

1

4

1

3

0

3

0

3

5

Left lower lobe

0

1

0

1

0

1

0

1

1

Right lower lobe + Left upper lobe

1

0

0

0

0

0

0

0

1

Surv.

2

5

1

4

0

4

0

4

7

60 to 69 years old

Male patients

Right middle lobe

0

1

0

1

0

1

0

1

1

Right lower lobe

1

9

0

9

2

7

1

6

10

Left lower lobe

0

6

0

6

1

5

1

4

6

Right lower lobe + Left lower lobe

0

9

1

8

3

5

1

4

9

Surv.

1

25

1

24

6

18

3

15

26

Female patients

Right lower lobe

8

11

1

10

1

9

2

7

19

Left lower lobe

0

1

0

1

0

1

0

1

1

Right middle lobe + Left lower lobe

1

0

0

0

0

0

0

0

1

Right lower lobe + Left lower lobe

1

8

1

7

2

5

0

5

9

Surv.

10

20

2

18

3

15

2

13

30

70 years and above

Male patients

Right lower lobe

6

22

2

20

6

14

1

13

28

Left lower lobe

1

2

0

2

0

2

0

2

3

Right lower lobe + Left lower lobe

0

16

2

14

4

10

5

5

16

Right lower lobe + Left upper lobe

0

1

0

1

0

1

0

1

1

Surv.

7

41

4

37

10

27

6

21

48

Female

patients

Right middle lobe

5

2

0

2

0

2

0

2

7

Right lower lobe

15

44

5

39

2

37

5

32

59

Left upper lobe

0

1

0

1

0

1

0

1

1

Left lower lobe

4

7

0

7

0

7

1

6

11

Right lower lobe + Left lower lobe

8

31

7

24

2

22

7

15

39

Right lower lobe + Left upper lobe

0

2

0

2

0

2

0

2

2

Surv.

32

87

12

75

4

71

13

58

119

decd., deceased; surv., survivors.

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About the Authors: 

Alexander G. Arutyunov – MD, DSc, Professor, Department of Internal Medicine and General Physiotherapy, Faculty of Pediatrics, Pirogov Russian National Research Medical University, Moscow, Russia. http://orcid.org/0000-0003-1180-3549.
Anna V. Sokolova – MD, PhD, Associate Professor, Department of Internal Medicine and General Physiotherapy, Faculty of Pediatrics, Pirogov Russian National Research Medical University, Moscow, Russia. http://orcid.org/0000-0003-0823-9190.
Grigoriy P. Arutyunov – MD, DSc, Professor, Head of Department of Internal Medicine and General Physiotherapy, Faculty of Pediatrics, Pirogov Russian National Research Medical University, Moscow, Russia. http://orcid.org/0000-0002-6645-2515.
Dmitry O. Dragunov – MD, PhD, Associate Professor, Department of Internal Medicine and General Physiotherapy, Faculty of Pediatrics, Pirogov Russian National Research Medical University, Moscow, Russia. http://orcid.org/0000-0003-1059-8387.

Received 15 April 2019, Revised 27 April 2020, Accepted 08 May 2020

© 2019, Arutyunov A.G., Sokolova A.V., Arutyunov G.P., Dragunov D.O.
© 2019, Russian Open Medical Journal

Correspondence to Dmitry O. Dragun. Address: 25, Pavlovskaya Str., block 13, Moscow, 113093, Russia. Phone: +79104634039. Fax: +7 (495) 954-87-29. E-mail: tamops2211@gmail.com.

DOI: 
10.15275/rusomj.2020.0205

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