medigraphic.com
SPANISH

Revista del Hospital Juárez de México

  • Contents
  • View Archive
  • Information
    • General Information        
    • Directory
  • Publish
    • Instructions for authors        
  • medigraphic.com
    • Home
    • Journals index            
    • Register / Login
  • Mi perfil

2018, Number 3

<< Back Next >>

Rev Hosp Jua Mex 2018; 85 (3)

Clinical predictors of Influenza, have they changed?

Alonso-Bello CD, Delgado-Cortés HM, Conde-Mercado JM, Pérez-Cruz E, Martínez-Velázquez M, Romero-Vásquez H, Castro-Pérez J, Campos-González JRM
Full text How to cite this article

Language: Spanish
References: 19
Page: 143-148
PDF size: 191.62 Kb.


Key words:

H1N1, influenza, prognosis, predictor risk factors.

ABSTRACT

Introduction: Influenza is an acute respiratory disease that represents a diagnostic challenge, caused by influenza A, B, and C viruses, which occurs in local outbreaks or seasonal epidemics. The epidemiological surveillance guidelines for influenza in Mexico specifies that the management of operative definitions within the epidemiological surveillance, helps to make a standardized measurement of the characteristics that must be met by the individuals admitted to this system. Objective: To identify the clinical predictors of influenza in patients over 18 years of age in a second level hospital in Mexico during a period of three years. Material and methods: We studied 526 cases belonging to a retrospective cohort. The patients complied with one of the operative definitions ILI (disease type influenza) or SARI (severe acute respiratory infection), signs and symptoms were recorded, all positive cases were confirmed by sending pharyngeal exudate, RT-PCR analysis (real-time polymerase chain reaction) and virus typing if result was positive. Results: The predictors were obtained using a multivariate analysis and a binary logistic regression. The mean age of the patients was 42.85 ± 16.59 years, of which 54.9% (n = 289) were women and 45.1% (n = 237) were men. In the univariate analysis the signs and symptoms that showed the best prediction are myalgias OR of 1.84 (1.14-2.97) p = 0.011, arthralgias OR 1.89 (1.19-3.01) p = 0.006, malaise OR 1.74 (1.04-2.91) p = 0.031, cyanosis OR 1.82 (1.17-2.83) p = 0.007. The signs and symptoms with statistical significance in the multivariate analysis were dyspnea OR 0.60 (0.41-0.88) p = 0.009, arthralgias OR 1.80 (1.12-2.90) p = 0.015 and cyanosis OR 1.90 (1.19-3-01) p = 0.006. Conclusions: The clinical predictors of influenza infection have changed in severity and variety in recent years, the frequency and power of prediction of sings and symptoms that are mentioned in the operative definitions differ with the results of our study.


REFERENCES

  1. Paules C, Subbarao K. Influenza. Lancet 2017; 390(10095): 697-708.

  2. Wu X, Wu X, Sun Q, Zhang C, Yang S, Li L, et al. Progress of small molecular inhibitors in the development of anti-influenza virus agents. Theranostics 2017; 7(4): 826-45.

  3. Das K, Aramini JL, Ma LC, Krug RM, Arnold E. Structures of influenza A proteins and insights into antiviral drug targets. Nat Struct Mol Biol 2010; 17(5): 530-8.

  4. Guía de Práctica Clínica. Prevención, diagnóstico y tratamiento de la influenza estacional. SSA. México 2015.

  5. Manual para la Vigilancia epidemiológica de influenza. Secretaría de Salud; México 2014.

  6. Norma Oficial Mexicana NOM-017-SSA2-2012, Para la vigilancia epidemiológica.

  7. Aviso Epidemiológico de Influenza/CONAVE/01/2016/Influenza/10/Febrero/2016.

  8. Monto A, Gravestein S, Elliot M, Colopy M, Scheweinle J. Clinical signs and symptoms predicting influenza infection. Arch Intern Med 2000; 160(21): 3243-7.

  9. Simon E, Long B, Koyfman A. Clinical mimics: an emergency medicine-focused review of influenza mimics. J Emerg Med 2017; 53(1): 49-65.

  10. Boivin G, Hardy I, Tellier G, Maziade J. Predicting influenza infections during epidemics with use of a clinical case definition. Clin Infec Dis 2000; 31(5): 1166-9.

  11. Call SA, Vollenweider MA, Hornung CA, Simel DL, McKinney WP. Does this patient have influenza? JAMA 2005; 293(8): 987-97.

  12. Peltola V, Reunanen T, Ziegler T, Silvennoinen H, Heikkinen T. Accuracy of clinical diagnosis of influenza in outpatient children. Clin Infect Dis 2005; 41(8): 1198-200.

  13. Yang JH, Huang PY, Shie SS, Yang S, Tsao KC, Wu TL, et al. Predictive symptoms and sings of laboratory-confirmed influenza: a prospective surveillance study of two metropolitan areas in Taiwan. Medicine (Baltimore) 2015; 94(44): e1952.

  14. Yang S, Zhou Y, Cui Y, Ding C, Wu J, Deng M, et al. The need for strengthening the influenza virus detection ability of hospital clinical laboratories: an investigation of the 2009 pandemic. Sci Rep 2017; 7(1): 43433.

  15. Kmietowicz Z. WHO downgrades oseltamivir on drug list after reviewing evidence. BMJ 2017; 357(1): j2841.

  16. Ebell MH. WHO downgrades status of oseltamivir. BMJ 2017; 358(1): j3266.

  17. Kawai N, Ikematsu H, Kawashima T, Maeda T, Ukai H, Hirotsu N, et al. Increased symptom severity but unchanged neuraminidase inhibitor effectiveness for A(H1N1)pdm09 in the 2010-2011 season: comparison with the previous season and with seasonal A(H3N2) and B. Influenza Other Respir Viruses 2013; 7(3): 448-55.

  18. Kmietowicz Z. Tamiflu reduces complications of flu, new review finds. BMJ 2015; 350: h537

  19. Dobson J, Whitley RJ, Pocock S, Monto AS. Oseltamivir treatment for influenza in adults: a meta-analysis of randomised controlled trials. Lancet 2015; 385(9979): 1729-37.




2020     |     www.medigraphic.com

Mi perfil

C?MO CITAR (Vancouver)

Rev Hosp Jua Mex. 2018;85