• Users Online: 184
  • Home
  • Print this page
  • Email this page
Home About us Editorial board Ahead of print Current issue Search Archives Submit article Instructions Subscribe Contacts Login 


 
 Table of Contents  
ORIGINAL ARTICLE
Year : 2019  |  Volume : 21  |  Issue : 1  |  Page : 63-68

Determinants of influenza patients requiring additional support in adult urban population


1 Department of Internal Medicine, INHS Asvini, Mumbai, Maharashtra, India
2 Commanding Officer, INHS Asvini, Mumbai, Maharashtra, India
3 Department of Pathology, INHS Asvini, Mumbai, Maharashtra, India
4 INS Gharial, Eastern Fleet, Visakhapatnam, Andhra Pradesh, India

Date of Submission29-Oct-2018
Date of Acceptance23-Feb-2019
Date of Web Publication19-Jun-2019

Correspondence Address:
Surg R Adm Naveen Chawla
Commanding Officer INHS Asvini, Mumbai, Maharashtra
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jmms.jmms_63_18

Rights and Permissions
  Abstract 


Background: Influenza is a global disease with frequent outbreaks which vary in extent and severity. Although Influenza Like Illness (ILI) has a low fatality, it can cause a spurt in hospitalizations and sick absenteeism. Understanding the risk factors and using the knowledge to limit complication is the need of the hour to ensure adequate resource allocation and patient outcome. Aim and Objective: The study analysed the proportion of influenza cases requiring additional supportive care and the factors associated with it in the study population. Material and Methods: A retrospective observational study was conducted on 139 patients who were admitted with ILI at a tertiary care centre in Mumbai. Patients records were evaluated in detail for clinical history, socio-demographic details, relevant co-morbidities, physical examination findings and imaging & laboratory investigations. IBM SPSS version 22 was used for statistical analysis. Results: The proportion of Influenza patients requiring additional support (IPRAS) was 18.71%(95% CI 13.1% to 26%) in the study population. The most common additional support was extra oxygen therapy in 53.85% of IPRAS patients. Conclusion: The risk factors with significant association with IPRAS were higher age of the individual, H1N1 influenza, female gender, and presence of 3 or more co-morbidities, presence of fever, cough or breathlessness at presentation, higher respiratory rate and lower SpO2 at the time of presentation.

Keywords: H1N1 influenza, influenza-like illness, severe acute respiratory infections


How to cite this article:
Tyagi R, Chawla N, Manu V, Anand KB, Budhwar V, Sharma A. Determinants of influenza patients requiring additional support in adult urban population. J Mar Med Soc 2019;21:63-8

How to cite this URL:
Tyagi R, Chawla N, Manu V, Anand KB, Budhwar V, Sharma A. Determinants of influenza patients requiring additional support in adult urban population. J Mar Med Soc [serial online] 2019 [cited 2019 Jul 23];21:63-8. Available from: http://www.marinemedicalsociety.in/text.asp?2019/21/1/63/260668




  Introduction Top


Influenza is an international disease with outbreaks, documented virtually every year with a variated severity and extent. Due to its antigenic shift and drift, all outbreaks are potential pandemics with one documented in almost every decade. The interpandemic outbreaks contribute further, in loss to the community in terms of life, manpower, and resources. The reported mortality rate due to influenza-like illness (ILI) is variable and ranges from “0.3 to 1.3, 0.6 to 8.3, and 4 to 119 respiratory deaths per 100,000 population for children, adults, and older adults (≥65 years), respectively.”[1] Although ILI has a low fatality rate, its high attack rate, short incubation period, large susceptible population, no cross-immunity, and largely subclinical presentation lead to a spurt in hospitalization and sick absenteeism.

Following emergence and spread of novel infl uenza A (H1N1) virus in April 2009 into a phase 6 pandemic till its end in 2010, sporadic outbreaks have been occurring in various parts globally, including India.[2],[3] As per the official data from 2011 to March 2018, a total of 95,826 influenza A H1N1 cases and 7036 deaths were reported from all the states across India.[4]

Majority of influenza cases are mild and self-limiting; a significant proportion do develop serious complications and can even be fatal.[5] Effective risk stratification of patients with high probability of developing complications is of vital importance to ensure efficient resource utilization without impacting the treatment outcomes. Studies have reported numerous demographic and clinical factors associated with higher risk of developing serious complications.[5],[6],[7] Attempts have been made by various researchers to develop scoring systems to predict the propensity to develop complication in influenza patients; however, no conclusive result exists that links various clinical and laboratory criteria as a predictor of complications.[8],[9] Studies reflecting the risk factors are nonspecific and reflect mostly population at risk including infants, young children, elderly, pregnant, and those with chronic illness.[10] Hence, the present study has been undertaken to analyze the clinical profile of influenza cases presenting to a tertiary care teaching hospital in western India. Understanding the risk factors and using the knowledge to limit complication is the need of the hour to ensure adequate resource allocation and patient outcome. The study thus analyzed the proportion of influenza cases requiring additional supportive care and the factors associated with it in a study population.


  Materials and Methods Top


The retrospective observational study was conducted by the department of medicine at a tertiary care teaching hospital in Mumbai between August 2017 and December 2017. All patients fitting the case definition were included in the study. A total of 139 patients were analyzed. Sample size was calculated considering the proportion of outcome as 18.71%, the precision of 6.48%, with 95% confidence level. Patient identity was not disclosed during the study and ethical clearance was taken from institutional committee.

Data for all participants were retrieved and evaluated from case sheets and Unique Hospital Identification Data software which included detailed clinical history sociodemographic details, relevant comorbidities followed by a thorough physical examination, and appropriate imaging and laboratory investigations at the time of admission as per hospital protocol. Throat swab for polymerase chain reaction-reverse transcription (PCR-RT) to confirm H1N1 was sent at initial evaluation for all suspected patients. The patients were followed up till the time of discharge.

Admission criteria

The admission criteria were as per the guidelines issued by the Ministry of Health and Family Welfare, Government of India. All cases classified as Category B and C were hospitalized. However, Category A patients were advised quarantine and follow-up on outpatient basis.[11]

Case definition

A suspected case was defined as one having temperature ≥38.5°C with at least one of the following symptoms: sore throat, cough, rhinorrhea, or nasal congestion. A confirmed case was defined by a positive result of real-time RT-PCR assay.

Influenza Patients Requiring Additional Support

“Influenza Patients Requiring Additional Support (IPRAS)” was defined as occurrence of intrahospital mortality or requirement of any of the following additional supportive interventions such as oxygen, noninvasive ventilation, mechanical ventilation, inotropic support, or fluid resuscitation. Baseline, laboratory, and clinical parameters were considered as primary explanatory variable.

Statistical analysis

Descriptive analysis was carried out by mean and standard deviation for normally distributed quantitative variables, frequency and median and interquartile range (IQR) for non normally distributed quantitative variables and proportion for categorical variables. The mean and standard deviation of normally distributed quantitative variables were compared between people with and without association (IPRAS) by unpaired t-test. Nonnormally distributed quantitative variables were compared by their median and IQR using Mann–Whitney U-test. Categorical variables were compared using cross tabulation. Chi-square test/Fisher's exact test was used to test statistical significance with P < 0.05 considered statistically significant. IBM SPSS version 22 (IBM Corp., New York, USA) was used for statistical analysis.


  Results Top


A total of 139 participants with suspected influenza were analyzed.

The mean age of the study population was 33.24 ± 13.62 years. About 71.22% cases tested positive for H1N1. The mean duration of symptoms at presentation was 2.47 ± 1.52 days. Fever was the most common presenting symptom in 95.68% followed by cough in 71.22% and sore throat in 64.03% of participants. Twenty percentage cases had adventitious sounds on auscultation. Nearly, 16.55% participants had three or more comorbidities [Table 1]. Distribution of comorbidities is given in [Figure 1]. Capsule oseltamivir (75/150 mg) was given as per protocol to all Category B and C patients for a period of 5 days. Oral/ parentral antibiotics were used based on clinical, radiological and laboratory assessment. Category A individuals with positive H1N1 were also initiated on oral antibiotics.[12] The study cohort had not been immunized for influenza. Median time of patients presenting to medical center was 3 days. The median time from the onset of treatment to resolution of fever was 4 days. Mean hospital stay for H1N1-positive patients was 4.5 ± 0.5 days. Case fatality rate was 2.87%.
Table 1: Descriptive analysis of baseline and clinical parameters in study population (n=139)

Click here to view
Figure 1: Distribution of comorbidities

Click here to view


The average blood counts were within the physiological range in study population. The average liver enzyme levels and renal function parameters were also within normal limits [Table 2].
Table 2: Descriptive analysis for laboratory parameters in study population (n=139)

Click here to view


The proportion of IPRAS was 18.71% (95% confidence interval [CI]: 13.1%–26%) in the study population. The most common additional support was extra oxygen therapy in 53.85% of IPRAS patients, followed by noninvasive ventilation in 26.92% and mechanical ventilation in 19.23% of the participants. Fluid resuscitation and inotropic support were required in 19.23% of patients. The proportion of intrahospital mortality was 15.38% [Table 3].
Table 3: Descriptive analysis of Influenza Patients Requiring Additional Support in study population (n=139)

Click here to view


The factors which had shown statistically significant association with IPRAS were higher age of the individual, H1N1 influenza, female gender, presence of three or more comorbidities, presence of fever, cough or breathlessness at presentation, higher respiratory rate, and lower spo2 at the time of presentation [Table 4].
Table 4: Comparison of baseline parameters between two study groups (n=139)

Click here to view


The only laboratory parameter which has shown statistically significant association with the occurrence of IPRAS was lower plate count (196.50 [150–232] thousands in people with IPRAS vs. 223 [180.50–267.50] thousands in people without additional support), which was statistically significant (P = 0.03) [Table 5].
Table 5: Comparison of laboratory parameters between two study groups (n=139)

Click here to view



  Discussion Top


Summary of key findings

In this study, influenza A (H1N1) contributed to three-fourths of influenza cases. The proportion of IPRAS was 18.71% (95% CI - 13.1% to 26%), and 15.38% died during hospital stay. The risk factors with significant association with IPRAS were higher age of the individual, H1N1 influenza, female gender, presence of three or more comorbidities, presence of fever, cough, or breathlessness at presentation, higher respiratory rate, and lower spo2 at the time of presentation. Solitary laboratory parameter with significant association to IPRAS was low plate count.

Strengths and limitations of the study

The key strength of the study is that it has attempted to analyze the wide range of demographic and clinical factors associated with adverse outcome among Indian patients with ILI, which was not done by previous studies. The key limitations were retrospective nature of the study, and hence, the analysis was limited to only the factors, which were available in the medical records. Another key limitation was the limited sample size of the study because of which the role of potential confounding could not be adjusted for the data analysis. The role of chance occurrence of many differences can also be attributable to smaller sample size.

Interpretation and implications in the context of the totality of evidence

There is quite variability in the terminology used and the operational definitions of intrahospital adverse outcomes. A study has defined severe in-hospital complications as occurrence mortality, mechanical ventilation, septic shock, acute respiratory distress syndrome, and requirement for resuscitation maneuvers and reported 9.9% developing symptomatic intracerebral hemorrhage and 1.3% developing in-hospital mortality.[10] Another study has vaguely defined severe disease as the occurrence of any untoward complication and reported it in 15% of the patients. One study considered mechanical ventilation, inotropic use, and PaO2/FiO2 ratio ≤250 as severe disease and reported it in 32.43% of the participants.[12] Due to the lack of standardized definition on severe intrahospital complications, it is difficult to compare the proportion of the severe disease across the studies and draw conclusions about its exact incidence.

Attempts have been made in the past by many authors to identify high-risk clinical and laboratory parameters to predict the adverse outcomes among ILI either with the help of existing mortality predictions scores such as sequential organ failure assessment score, CURB 65 (Confusion, Blood Urea Nitrogen, Respiratory Rate, Systolic BP, Age>65) criterion For PICS read PSI (Pneumonia Severity Index) or with the help of new structured scoring systems and tested them for their predictive validity specific to influenza.[9],[13] The current study even though could not propose a structured predictive scoring system has identified age of the individual, H1N1 influenza, female gender, presence of three or more comorbidities, presence of fever, cough or breathlessness at presentation, higher respiratory rate, and lower SpO2 at the time of presentation as risk factors for poor outcomes. A study conducted on influenza cases has reported that altered mental status, hypoxia (PaO2/FiO2≤250), bilateral lung infiltration, and old age (≥65 years) were independent risk factors for severe cases (all P < 0.001).[13] Another study has reported higher age of the individual, longer duration of illness before ICU admission, higher acute physiology and chronic health evaluation II score, septic shock, and elevated serum creatinine to be strong predictors of mortality.[14] Higher age, levels of lactate dehydrogenase, and white cell count on admission were reported to be strong predictors of mortality in another study, and the authors have proposed a prediction model based on these variables.[15] Serum CRP level at admission was reported to the only predictor of adverse outcomes by another prospective study.[16] Another study reported younger age of the individual, comorbid chronic illness, morbid obesity, and associated bacterial infection as independent risk factors for severe disease. Another study conducted on influenza A (H1N1) patients has reported older age, immunodeficiency, or longer duration of time between onset of disease and admission as independent predictors of adverse outcomes and disease progression.[17] As can be seen from the discussion, there is a quite amount of heterogeneity across the studies, and the results often are conflicting. This can be attributed to differences in the definitions used, quality of health-care services, and key differences among characteristics of study population.

Controversies raised by the study

No controversies have been raised by the study.

Future directions for research

There is a strong need to develop a standardized definition for intrahospital adverse events in influenza patients and also to develop composite scoring system to predict them, based on the published literature. This score needs to be validated across different settings to generate quality evidence to recommend further use in clinical practice.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Li L, Wong JY, Wu P, Bond HS, Lau EH, Sullivan SG, et al. Heterogeneity in estimates of the impact of influenza on population mortality: A systematic review. Am J Epidemiol 2018;187:378-88.  Back to cited text no. 1
    
2.
Chan M. World Now at the Start of 2009 Influenza Pandemic. Geneva: World Health Organization; 2009. Available from: http://www.who.int/mediacentre/news/statements/2009/h1n1_pandemic_phase6_20090611/en/. [Last assessed on 2019 Mar 18].  Back to cited text no. 2
    
3.
MInistry of Health and Family Welfare, editor. Seasonal Influenza (H1N1) – State/UT- Wise, Year- Wise Number of Cases and Death from 2011 to 2018 (Till 18th March, 2018). New Delhi: MInistry of Health and Family Welfare; 2018.  Back to cited text no. 3
    
4.
Sohn CH, Ryoo SM, Yoon JY, Seo DW, Lim KS, Kim SH, et al. Comparison of clinical features and outcomes of hospitalized adult patients with novel influenza A (H1N1) pneumonia and other pneumonia. Acad Emerg Med 2013;20:46-53.  Back to cited text no. 4
    
5.
Viasus D, Paño-Pardo JR, Pachón J, Campins A, López-Medrano F, Villoslada A, et al. Factors associated with severe disease in hospitalized adults with pandemic (H1N1) 2009 in spain. Clin Microbiol Infect 2011;17:738-46.  Back to cited text no. 5
    
6.
Van Kerkhove MD, Vandemaele KA, Shinde V, Jaramillo-Gutierrez G, Koukounari A, Donnelly CA, et al. Risk factors for severe outcomes following 2009 influenza A (H1N1) infection: A global pooled analysis. PLoS Med 2011;8:e1001053.  Back to cited text no. 6
    
7.
Damak H, Chtara K, Bahloul M, Kallel H, Chaari A, Ksibi H, et al. Clinical features, complications and mortality in critically ill patients with 2009 influenza A (H1N1) in sfax, Tunisia. Influenza Other Respir Viruses 2011;5:230-40.  Back to cited text no. 7
    
8.
Capelastegui A, Quintana JM, Bilbao A, España PP, Garin O, Alonso J, et al. Score to identify the severity of adult patients with influenza A (H1N1) 2009 virus infection at hospital admission. Eur J Clin Microbiol Infect Dis 2012;31:2693-701.  Back to cited text no. 8
    
9.
Oh WS, Lee SJ, Lee CS, Hur JA, Hur AC, Park YS, et al. A prediction rule to identify severe cases among adult patients hospitalized with pandemic influenza A (H1N1) 2009. J Korean Med Sci 2011;26:499-506.  Back to cited text no. 9
    
10.
Abdelaty NM. Risk factors and prognostic criteria in 230 patients with influenza A (H1N1) infection. Egypt J Chest Dis Tuberc 2013;62:1-8.  Back to cited text no. 10
    
11.
Ministry of Health and Family welfare, Government of India. Guidelines on Categorization of Seasonal Influenza Cases During Screening for Home Isolation, Testing, Treatment and Hospitalization. Available from: https://www.mohfw.gov.in/basicpage/technical-guidelines. [Last revised on 2016 Oct 18].  Back to cited text no. 11
    
12.
Centres for Disease Control and Prevention. Updated Interim Recommendations for the Use of Antiviral Medications in the Treatment and Prevention of Influenza for the 2009-2010 Season. Atlanta: Centres for Disease Control and Prevention; 2009. Available from: https://www.cdc.gov/h1n1flu/recommendations.htm. [Last assessed on 2019 Mar 18].  Back to cited text no. 12
    
13.
Cho WH, Kim YS, Jeon DS, Kim JE, Kim KI, Seol HY, et al. Outcome of pandemic H1N1 pneumonia: Clinical and radiological findings for severity assessment. Korean J Intern Med 2011;26:160-7.  Back to cited text no. 13
    
14.
Bar-Lavie Y, Hussein K, Mayo A, King D, Kra-Oz Z, Paul M, et al. The morbidity and mortality of influenza patients treated at rambam medical center intensive care unit in the years 2009-2014. Harefuah 2017;156:559-63.  Back to cited text no. 14
    
15.
Hernández-Cárdenas CM, Serna-Secundino H, García-Olazarán JG, Aguilar-Pérez CL, Rocha-Machado J, Campos-Calderón LF, et al. Acute respiratory distress syndrome secondary to influenza A (H1N1) pdm09: Clinical characteristics and mortality predictors. Rev Invest Clin 2016;68:235-44.  Back to cited text no. 15
    
16.
Zimmerman O, Rogowski O, Aviram G, Mizrahi M, Zeltser D, Justo D, et al. C-reactive protein serum levels as an early predictor of outcome in patients with pandemic H1N1 influenza A virus infection. BMC Infect Dis 2010;10:288.  Back to cited text no. 16
    
17.
Lynfield R, Davey R, Dwyer DE, Losso MH, Wentworth D, Cozzi-Lepri A, et al. Outcomes of influenza A (H1N1) pdm09 virus infection: Results from two international cohort studies. PLoS One 2014;9:e101785.  Back to cited text no. 17
    


    Figures

  [Figure 1]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
Abstract
Introduction
Materials and Me...
Results
Discussion
References
Article Figures
Article Tables

 Article Access Statistics
    Viewed29    
    Printed0    
    Emailed0    
    PDF Downloaded14    
    Comments [Add]    

Recommend this journal


[TAG2]
[TAG3]
[TAG4]