Presentation of risk factors for fata outcome in influenza-confirmed cases admitted to ICU in EU/EEA countries; Options IX conference, Chicago

1. Intensive care surveillance of
influenza, 11 EU countries, 2009–2016
Cornelia Adlhoch
European Centre for Disease Prevention and Control
Options IX for the control of influenza, 24–28 August 2016

2. Thank you for the tireless commitment in collecting and
providing high-quality European influenza surveillance data
Finland: Outi Lyytikäinen, Niina Ikonen, Satu Murtopuro, Anu Haveri; France: Blanchon Thierry, Clement
Turbelin, Emmanuel Belchior, Isabelle Bonmarin, Sylvie Behillil, Bruno Lina, Martine Valette, Sylvie van der
Werf, Vincent Enouf; Ireland: Lisa Domegan, Allison Waters, Joan O’Donnell, Margaret Duffy, Suzie
Coughlan, Derval Igoe; Malta: Christopher Barbara, Jackie Maistre Melillo, Tanya Melillo, Graziella Zahra;
Netherlands: Mariette Hooiveld, Anne Teirlinck, Adam Meijer, Frederika Dijkstra, Gé Donker, Guus
Rimmelzwaan, Marit de Lange; Portugal: Ana Paula Rodrigues , Helena Rebelo De Andrade, Raquel
Moreira Guiomar; Romania: Emilia Lupulescu, Florin Popovici; Slovak Republic: Edita Staronová; Spain:
Amparo Larrauri, Francisco Pozo, Inmaculada Casas, Leonardo Raul Ortiz De Lejarazu, Tomas Pumarola,
Tomas Vega.
All practitioners and hospitals providing samples and epidemiological data.
I have no potential conflict of interest to report

3. Rational for severe disease surveillance
• to monitor and assess the impact of influenza
• to identify high risk groups and risk factors

4. Objective of the study
To describe confirmed influenza cases admitted to intensive
care units (ICU) in order to identify risk factors for fatal
outcome in EU/EEA countries

5. Methods
Data collection
 Laboratory-confirmed influenza cases admitted to ICU
- age and gender
- influenza type and A subtype
- underlying conditions, complications and vaccination status
- outcome
 11 EU/EEA countries
 2009/10 – 2015/16 (weeks 40–20)
Data analysis
 Descriptive analysis
 Uni- and multivariable logistic regression

6. Reporting countries and number of cases
Variable number of countries reporting each season, 11 in total

7. Age 58; 0-97 54; 0-100
(median, range) (median, range)
Descriptive analysis
Fatal
N=621
Recovered
N=1 658
18% 19%
57% 55%

8. Descriptive analysis
Fatal
N=621
Recovered
N=1 658

9. Cases by (sub)type, age-group and outcome
A(H1N1)pdm09 affects mostly 40–64 year-olds, A(H3N2) 65+ year-olds

10. Descriptive analysis – chronic conditions
Lung disease 15% 15%
Heart disease 14% 8%
Diabetes 11% 11%
HIV 11% 5%
Obesity 10% 13%
Cancer 5% 2%
Kidney disease 5% 3%
Liver disease 4% 3%
Morbid obesity 4% 5%
Asthma 2% 3%
Pregnancy 2% 4%
Fatal
N=621
Recovered
N=1 658

11. Descriptive analysis - complications
ARDS 56% 53%
Pneumonia 34% 36%
Sepsis 9% 3%
Fatal
N=621
Recovered
N=1 658

12. Risk factors for fatal outcome
pooled data 2009/10–2015/16, EU/EEA
Factors Univariable analysis Multivariable analysis
Odds ratio (95%CI) Adjusted odds ratio* (95%CI)
0–9 years Ref.
10–19 years 1.2 (0.5-2.7) 1.0 (0.4-2.4)
20–29 years 1.8 (1.0-3.4) 1.6 (0.8-3.2)
30–39 years 2.4 (1.4-4.2) 1.9 (1.1-3.4)
40–49 years 2.0 (1.2-3.4) 1.4 (0.8-2.5)
50–59 years 3.3 (2.0-5.5) 2.6 (1.5-4.4)
60–69 years 3.2 (1.9-5.4) 2.5 (1.5-4.3)
70–79 years 3.7 (2.2-6.3) 3.1 (1.8-5.5)
80+ years 3.7 (2.0-6.8) 3.6 (1.9-7.0)
Increasing age is a risk factor for fatal outcome
*adjusted for gender, season and country
Bold: p<0.05

13. Risk factors for fatal outcome
pooled data 2009/10–2015/16, EU/EEA
Univariable analysis Multivariable analysis
Virus (sub)type Odds ratio (95%CI) Adjusted odds ratio* (95%CI)
B Ref. Ref.
A(H1N1)pdm09 1.8 (1.3-2.4) 2.1 (1.5-3.1)
A(H3N2) 1.4 (1.0-2.1) 1.5 (1.0-2.3)
Vaccination
status
Vaccinated 1.1 (0.8-1.4) 1.0 (0.8-1.4)
Complications
Sepsis 5.8 (3.7-9.1) 5.5 (3.4-8.9)
ARDS 1.2 (0.9-1.6)
Pneumonia 0.8 (0.6-1.1)
Infection with influenza A(H1N1)pdm09 is a risk factor for fatal outcome
*adjusted for gender, season and country
Bold: p<0.05

14. Risk factors for fatal outcome
pooled data 2009/10–2015/16, EU/EEA
Underlying
conditions
Univariable analysis Multivariable analysis
Odds ratio (95%CI) Adjusted odds ratio* (95%CI)
Cancer 2.8 (1.7-4.7) 2.7 (1.5-4.9)
HIV 2.5 (1.7-3.5) 2.7 (1.8-4.0)
Kidney disease 1.9 (1.2-3.1) 1.8 (1.1-3.1)
Liver disease 1.6 (0.9-2.6) 2.2 (1.2-3.9)
Heart disease 1.5 (1.1-2.1) 1.3 (0.9-1.9)
Pregnancy 0.6 (0.3-1.0) 0.9 (0.5-1.7)
Asthma 0.6 (0.3-1.2)
Diabetes 1.0 (0.8-1.4)
Lung disease 0.9 (0.7-1.2)
Obesity 0.8 (0.6-1.1)
Morbid obesity 1.1 (0.7-1.7)
Cancer, kidney and liver disease, and HIV are risk factors for fatal outcome
*adjusted for gender, season and country
Bold: p<0.05

15. Limitations
• Small subset of reporting countries might introduce bias
• Inconsistent reporting over time
• Lack of denominator data

16. Conclusions
• Identified risk factors for fatal outcome:
• Increasing age
• Infection with influenza A virus
• Cancer
• HIV
• Kidney disease
• Liver disease
• Vaccination not protective in these severely ill patients
• Need for more countries in EU/EEA to perform severe
influenza surveillance

17. ECDC team:
Pasi Penttinen
Eeva Broberg
Julien Beauté
René Snacken
Joana Gomes Dias
Adrian Prodan
Gaetan Guyodo
...and the influenza programme at WHO Regional Office for Europe
Thank you for your attention!