World Rural Health Conference
Home Print this page Email this page Small font size Default font size Increase font size
Users Online: 2619
Home About us Editorial board Search Ahead of print Current issue Archives Submit article Instructions Subscribe Contacts Login 


 
 Table of Contents 
ORIGINAL ARTICLE
Year : 2016  |  Volume : 5  |  Issue : 2  |  Page : 411-415  

Predictors of outcome in patients admitted with acute exacerbation of chronic obstructive pulmonary disease in a rural Tertiary Care Center


1 Department of Medicine, Malankara Orthodox Syrian Church Medical College and Hospital, Ernakulam District, Kolenchery, Kerala, India
2 Department of Community Medicine, Malankara Orthodox Syrian Church Medical College and Hospital, Ernakulam District, Kolenchery, Kerala, India
3 Department of Pulmonary Medicine, Malankara Orthodox Syrian Church Medical College and Hospital, Ernakulam District, Kolenchery, Kerala, India

Date of Web Publication18-Oct-2016

Correspondence Address:
Abraham M Ittyachen
Department of Medicine, Malankara Orthodox Syrian Church Medical College and Hospital, Ernakulam District, Kolenchery - 682 311, Kerala
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2249-4863.192365

Rights and Permissions
  Abstract 


Background: Chronic obstructive pulmonary disease (COPD) is associated with a high degree of mortality and morbidity around the world with the burden of the disease being more in the developing countries. In the Indian context data is limited. This study was carried out to determine the predictors of outcome in patients admitted with acute exacerbation of COPD in a rural Tertiary Care Center in the state of Kerala. Materials and Methods: This was a prospective cohort study. Patients admitted with acute exacerbation of COPD in the Intensive Care Unit between August 2013 and July 2014 was included in the study. Sociodemographic data, clinical variables, and investigations were collected. Mortality with respect to relevant risk factors was compared using Kaplan–Meier method and Cox proportional hazard model. Results: Seventy patients were enrolled in the study of whom 58 (82.9%) were above the age of 60 years. Majority of the patients (87.1%) were males. Tobacco smoking was the main risk factor in them. All the females had a history of exposure to biomass fuel in the form of firewood; none of them were smokers. Majority of patients (80.0%) had a history of one or more co-existing illnesses. Anemia was found to be an independent risk factor for mortality (adjusted hazard ratio: 3.167, 95% confidence interval: 1.516–6.616). Risk factors for poor outcome in COPD patients reported from other centers in India were not found to be relevant in this study. Conclusions: Anemia could be an independent risk factor for mortality in COPD patients. India already has a high prevalence of iron deficiency anemia especially in the rural area and in the geriatric population. Henceforth, family practitioners and primary care physicians may remain vigilant regarding the development of anemia in their COPD patients and institute remedial measures without delay. Futhermore, the wide variation reported in the predictors of outcome of COPD along with the finding of this study calls for an urgent need for more studies.

Keywords: Acute exacerbation, chronic obstructive pulmonary disease, predictors of outcome, rural area


How to cite this article:
Ittyachen AM, Krishnamoorthy S, Bhatt AN, Abdulla S, Roy JO, Sugathan M, Ambadan K, Kuriakose J. Predictors of outcome in patients admitted with acute exacerbation of chronic obstructive pulmonary disease in a rural Tertiary Care Center. J Family Med Prim Care 2016;5:411-5

How to cite this URL:
Ittyachen AM, Krishnamoorthy S, Bhatt AN, Abdulla S, Roy JO, Sugathan M, Ambadan K, Kuriakose J. Predictors of outcome in patients admitted with acute exacerbation of chronic obstructive pulmonary disease in a rural Tertiary Care Center. J Family Med Prim Care [serial online] 2016 [cited 2019 May 21];5:411-5. Available from: http://www.jfmpc.com/text.asp?2016/5/2/411/192365




  Introduction Top


Chronic obstructive pulmonary disease (COPD) is a major cause of death and disability around the world.[1] The age-adjusted death rate of this disease is highest in low-income areas of the world including South Asia and sub-Saharan Africa.[2] Even in high-income countries, there is a definite trend in socioeconomic related outcome with those in the lower socioeconomic status faring worse.[3] The high economic burden this disease imposes on the individual, and the health care delivery system of a nation needs to be emphasized.[4]

In the Indian context, there is limited data regarding prevalence of COPD. The estimated prevalence is between 6.5% and 7.7%; but this is by no means accurate.[5] The nationwide prevalence of chronic bronchitis alone has been estimated to be 3.49%[6] but this data do not include emphysema which is the other major determinant of COPD. The predictors of poor outcome in Indian patients admitted with acute exacerbation have variously been estimated to be hypotension,[7] need for invasive ventilation, presence of co-morbid illness, and hypercapnia.[8] Owing to the heterogenecity of present studies [5] and large populations in the country being out of the scope of available studies, even this data is far from complete. In the setting of Kerala where this study was done, also, there is a significant dearth of information regarding COPD in indexed literature.


  Materials and Methods Top


This prospective cohort study was done to determine the predictors of outcome in patients admitted with acute exacerbation of COPD in a Tertiary Care Center in the state of Kerala, India. The hospital where this study was done is situated in a rural setting not far from the Western Ghats. The climate in the region is humid and the vegetation green throughout without any significant air pollution.

A total of 70 patients admitted with acute exacerbation of COPD in the Intensive Care Unit (ICU) between August 2013 and July 2014 were included in the study. There were no set criteria to define ICU admission and was left best to the clinical judgment of the admitting physician who first saw the patient in the emergency. The only other inclusion criteria was a known clinician made diagnosis of COPD with supporting spirometry or a high probability of the disease (on the basis of clinical history, history of chronic exposure to respiratory irritants, smoking history, physical examination, and chest radiograph).

Type II respiratory failure was defined as hypercarbia (PaCO2 < 45 mm Hg) (N: 35–45 mm of Hg) with a co-existing hypoxia (PaO2 < 80 mm Hg) (N: 80–100 mm of Hg).

A peer reviewed, pilot tested, structured questionnaire was used to collect data which included sociodemographic variables, clinical variables, and investigations. Data entry was done using Epidata software, version 3.1 (developed by “The Epidata Association”, Odense, Denmark) and analysis was done using R software, version 3.1.1 (developed by “The R Foundation for Statistical Computing”, Vienna, Austria). Event in the study was defined as death occurred while in hospital. All the discharges from hospital were right censored. Continuous variables were categorized by relevant clinical cut-off values. Overall mortality and mortality within each group of patients were expressed as number of deaths per 100 person days. Survival curve was plotted using Kaplan–Meier method and median survival period with its 95% confidence interval (CI) was calculated. The log-rank test was done for statistical association of relevant risk factors with mortality. The effect size of risk factors on mortality was calculated as hazard ratios (HRs). Univariate and multivariate analysis to derive HR was done using Cox proportional hazard model. P < 0.05 was considered statistically significant association.

The study was approved by the Institutional Ethics Committee of the hospital and has been registered with the “Clinical Trials Registry of India”: CTRI/2013/12/004210.


  Results Top


The total number of patients enrolled in the study was 70 of whom 58 (82.9%) were designated as elderly (above 60 years of age). Sixty-one (87.1%) were males. History of tobacco smoking was given by all the male participants. There was a general mix of both cigarette and bidi and hence an attempt was not made to differentiate between them. All the females (n = 9, 12.9%) had a history of exposure to biomass fuel in the form of firewood. None of them were smokers. Majority of patients (80.0%) had history of one or more co-existing illnesses; 19 (27.1%) had diabetes mellitus, 20 patients (28.6%) had hypertension, 29 (41.4%) had ischemic heart disease, four patients (5.7%) had past history of tuberculosis, and 32 (45.7%) had history of other significant co-morbidities (cerebrovascular accident, renal failure, leukemia, chronic liver disease, hypothyroidism, seizure disorder, and benign prostatic hypertrophy).

Three participants were admitted for exacerbation of breathlessness for the first time. All the other participants had previous history of hospital admissions. Nine patients (12.9%) were already on home oxygen therapy.

On initial admission analysis of the primary parameters reflecting gas exchange/oxygen supply (arterial blood gas analysis and hemoglobin) 49 patients (70.0%) were in type II respiratory failure and 35 (50.0%) had anemia (males <13 g % and females <12 g %).[9],[10] The mean PaO2 was 70 mm of Hg with standard deviation (SD) of 17.54 and mean PaCO2 was 67.93 with SD of 27.92.

The major X-ray finding was hyperinflated lung fields (emphysema) (n = 51, 72.9%). Signs of pneumonia were seen in 29 patients (41.4%); 4 (5.7%) had pneumothorax, 3 (4.3%) had bronchiectasis, 3 (4.3%) had some degree of lung fibrosis, 2 (2.8%) had a cavitatory lesion, 1 (1.4%) had a lobar collapse, and 1 (1.4%) had effusion on the chest X-ray.

Regarding causes of exacerbation, infection was suspected to be culprit in majority of the patients (n = 51, 72.9%). This was corroborated by clinical findings (fever/increase in purulence of sputum) and investigations (increased white cell count/positive sputum culture/chest X-ray).

The mean duration of hospital stay was 6.55 days (SD of 4.29) and mean duration of ICU stay was 3.67 days (SD of 3.38). The cohort constituted 459 person-days of observation, and the mortality rate was 8 per 100 person-days; 37 (52.9%) died in hospital. Median follow-up period for the entire cohort as well as for the censored was 6 days. A Kaplan–Meier survival curve was plotted [Figure 1]; the median survival time was found to be 11 days (95% CI: 8–15).
Figure 1: Kaplan–Meier survival curve with 95% confidence interval for the cohort of chronic obstructive pulmonary disease patients

Click here to view


Forty-seven patients (67.14%) needed noninvasive ventilation, 32 (45.71%) needed invasive ventilation and 21 (30.0%) needed both noninvasive and invasive ventilation; 12 patients (17.14%) did not require any source of assisted ventilation.

Mortality in relation to the different characteristics of the cohort was tabulated [Table 1]. Among the different characteristics, only hemoglobin status had a significant association with mortality by Kaplan–Meier survival analysis (P = 0.001). Furthermore, HR of mortality for anemia with reference to normal hemoglobin status was 2.829 (95% CI: 1.404–5.702) by Cox proportional hazard method. Other lab parameters (liver function, renal function, electrolytes, etc.) did not have any significant association with mortality. In regression model involving clinical and laboratory parameters at the time of admission, again anemia emerged as an independent risk factor for mortality [Table 2]. A dose-response relationship of hemoglobin with mortality could not be studied because the numbers of patients with moderate and severe grades of anemia were small. Historical and demographic variables were not associated with mortality [Table 3]. Association of gender with mortality could not be studied due to very small numbers (n = 9) in female category.
Table 1: Mortality in the cohort in the different risk groups

Click here to view
Table 2: Cox proportional hazard model predicting risk factors of mortality by clinical and laboratory parameters at the time of admission

Click here to view
Table 3: Cox proportional hazard model predicting risk factors of mortality from patient history

Click here to view



  Discussion Top


In this study, males formed the predominant gender with tobacco smoking being the main etiology in them. Studies from other centers in India also paint a similar picture regarding gender and etiology.[11],[12],[13] A definite delineation could not be made between cigarette and bidi in this study. Females though limited in number were united by a single cause, exposure to biomass fuel in the form of firewood; this mirrored studies across India and in other developing economies.[14],[15],[16],[17],[18]

Anemia was significantly associated with mortality (HR of 2.829). On the basis of human physiology polycythemia is what is expected of the long-standing hypoxia of COPD. Hypoxia increases erythropoietin (EPO) production in the proximal convoluted cell of the kidney which in turn enhances red blood cell (RBC) production. EPO also decreases apoptosis of the RBCs and increases their survival.[19] Though physiologically coherent, in actual practice anemia is more common than polycythemia.[20] The mechanisms of anemia in COPD are multifactorial.[21] Postulated mechanisms include anemia of chronic disease (ACD), iron deficiency, vitamin deficiency, associated co-morbidities, hypogonadism, and treatment related.[22] Of these ACD is probably the predominant mechanism. ACD is an immune-mediated phenomenon where inflammation plays an important role in the pathogenesis.[23] Studies have demonstrated high levels of inflammatory parameters in anemic COPD patients.[24] The mechanisms incriminated in causing ACD are iron homeostasis dysregulation, blunted endogenous EPO production, impaired bone marrow erythropoietic response, and shortened RBC survival.[23]

Anemia being a risk factor for a poor outcome in COPD has far-reaching implications in a country like India. India already has a high prevalence of iron deficiency anemia, especially in the rural setting.[9],[25] Moreover, this is further aggravated in the geriatric population.[26] Henceforth, health planners may have to consider COPD patients also as a risk group for anemia and target them for correction.

The postulated predictors of negative outcome in COPD patients reported from other centers in India are hypotension,[7] need for invasive ventilation, presence of co-morbid illness and the presence of hypercapnia.[8] The sample size in this study was inadequate to find an association of these risk factors and a negative outcome.

In a developing country like India frequent episodes of acute exacerbation of COPD puts a great strain on the meager health resources of the nation. The wide variation reported in the predictors of outcome [7],[8] of COPD along with the finding of this study stand testimony to the fact that there is an urgent need for more studies. The vastness of the nation, rural-urban divide, cultural differences, poverty, and contrasting climate are all challenging aspects of doing a study that is representative of the population at large.

A small sample size has been a major limitation of this study. Never the less considering the dearth of data regarding COPD from Kerala and from India in general, it is hoped that the information generated will help to compute an adequately powered study in future. Meanwhile, family practitioners and primary care physicians may remain vigilant regarding the development of anemia in their COPD patients and institute remedial measures without delay.


  Conclusions Top


Anemia could be an independent risk factor for mortality in COPD patients. India already has a high prevalence of iron deficiency anemia especially in the rural area, and this is compounded in the geriatric population. Henceforth, health planners may have to consider COPD patients also as a risk group for anemia and target them for correction. Meanwhile family practitioners and primary care physicians may remain vigilant regarding the development of anemia in their COPD patients and institute remedial measures without delay. In addition, the wide variation reported in the predictors of outcome of COPD along with the finding of this study calls for an urgent need for more studies.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

 
  References Top

1.
Burney PG, Patel J, Newson R, Minelli C, Naghavi M. Global and regional trends in COPD mortality, 1990-2010. Eur Respir J 2015;45:1239-47.  Back to cited text no. 1
[PUBMED]    
2.
Burney P, Jarvis D, Perez-Padilla R. The global burden of chronic respiratory disease in adults. Int J Tuberc Lung Dis 2015;19:10-20.  Back to cited text no. 2
[PUBMED]    
3.
Gershon AS, Hwee J, Victor JC, Wilton AS, To T. Trends in socioeconomic status-related differences in mortality among people with chronic obstructive pulmonary disease. Ann Am Thorac Soc 2014;11:1195-202.  Back to cited text no. 3
[PUBMED]    
4.
Srivastava K, Thakur D, Sharma S, Punekar YS. Systematic review of humanistic and economic burden of symptomatic chronic obstructive pulmonary disease. Pharmacoeconomics 2015;33:467-88.  Back to cited text no. 4
[PUBMED]    
5.
McKay AJ, Mahesh PA, Fordham JZ, Majeed A. Prevalence of COPD in India: A systematic review. Prim Care Respir J 2012;21:313-21.  Back to cited text no. 5
[PUBMED]    
6.
Jindal SK, Aggarwal AN, Gupta D, Agarwal R, Kumar R, Kaur T, et al. Indian study on epidemiology of asthma, respiratory symptoms and chronic bronchitis in adults (INSEARCH). Int J Tuberc Lung Dis 2012;16:1270-7.  Back to cited text no. 6
    
7.
Chandra D, Guntupalli KK, Guleria R. Hypotension is a predictor of mortality in acute exacerbations of chronic obstructive pulmonary disease. Indian J Chest Dis Allied Sci 2007;49:13-8.  Back to cited text no. 7
[PUBMED]    
8.
Mohan A, Premanand R, Reddy LN, Rao MH, Sharma SK, Kamity R, et al. Clinical presentation and predictors of outcome in patients with severe acute exacerbation of chronic obstructive pulmonary disease requiring admission to intensive care unit. BMC Pulm Med 2006;6:27.  Back to cited text no. 8
[PUBMED]    
9.
Alvarez-Uria G, Naik PK, Midde M, Yalla PS, Pakam R. Prevalence and severity of anaemia stratified by age and gender in rural India. Anemia 2014;2014:176182.  Back to cited text no. 9
[PUBMED]    
10.
Nutritional anaemias. Report of a WHO scientific group. World Health Organ Tech Rep Ser 1968;405:5-37.  Back to cited text no. 10
[PUBMED]    
11.
Parasuramalu BG, Huliraj N, Prashanth Kumar SP, Gangaboraiah, Ramesh Masthi NR, Srinivasa Babu CR. Prevalence of chronic obstructive pulmonary disease and its association with tobacco smoking and environmental tobacco smoke exposure among rural population. Indian J Public Health 2014;58:45-9.  Back to cited text no. 11
[PUBMED]  Medknow Journal  
12.
Jain NK, Thakkar MS, Jain N, Rohan KA, Sharma M. Chronic obstructive pulmonary disease: Does gender really matter? Lung India 2011;28:258-62.  Back to cited text no. 12
  Medknow Journal  
13.
Ray D, Abel R, Selvaraj KG. A 5-yr prospective epidemiological study of chronic obstructive pulmonary disease in rural South India. Indian J Med Res 1995;101:238-44.  Back to cited text no. 13
    
14.
Mukherjee S, Roychoudhury S, Siddique S, Banerjee M, Bhattacharya P, Lahiri T, et al. Respiratory symptoms, lung function decrement and chronic obstructive pulmonary disease in pre-menopausal Indian women exposed to biomass smoke. Inhal Toxicol 2014;26:866-72.  Back to cited text no. 14
[PUBMED]    
15.
Gordon SB, Bruce NG, Grigg J, Hibberd PL, Kurmi OP, Lam KB, et al. Respiratory risks from household air pollution in low and middle income countries. Lancet Respir Med 2014;2:823-60.  Back to cited text no. 15
    
16.
Mahesh PA, Jayaraj BS, Prabhakar AK, Chaya SK, Vijaysimha R. Identification of a threshold for biomass exposure index for chronic bronchitis in rural women of Mysore district, Karnataka, India. Indian J Med Res 2013;137:87-94.  Back to cited text no. 16
[PUBMED]  Medknow Journal  
17.
Prasad R, Singh A, Garg R, Giridhar GB. Biomass fuel exposure and respiratory diseases in India. Biosci Trends 2012;6:219-28.  Back to cited text no. 17
[PUBMED]    
18.
Johnson P, Balakrishnan K, Ramaswamy P, Ghosh S, Sadhasivam M, Abirami O, et al. Prevalence of chronic obstructive pulmonary disease in rural women of Tamilnadu: Implications for refining disease burden assessments attributable to household biomass combustion. Glob Health Action 2011;4:7226.  Back to cited text no. 18
[PUBMED]    
19.
Carroz KP. Anemia in COPD: Should it be taken into consideration? Arch Bronconeumol 2007;43:392-8.  Back to cited text no. 19
[PUBMED]    
20.
Chambellan A, Chailleux E, Similowski T; ANTADIR Observatory Group. Prognostic value of the hematocrit in patients with severe COPD receiving long-term oxygen therapy. Chest 2005;128:1201-8.  Back to cited text no. 20
[PUBMED]    
21.
Sarkar M, Rajta PN, Khatana J. Anemia in chronic obstructive pulmonary disease: Prevalence, pathogenesis, and potential impact. Lung India 2015;32:142-51.  Back to cited text no. 21
[PUBMED]  Medknow Journal  
22.
John M, Lange A, Hoernig S, Witt C, Anker SD. Prevalence of anemia in chronic obstructive pulmonary disease: Comparison to other chronic diseases. Int J Cardiol 2006;111:365-70.  Back to cited text no. 22
[PUBMED]    
23.
Weiss G, Goodnough LT. Anemia of chronic disease. N Engl J Med 2005;352:1011-23.  Back to cited text no. 23
[PUBMED]    
24.
John M, Hoernig S, Doehner W, Okonko DD, Witt C, Anker SD. Anemia and inflammation in COPD. Chest 2005;127:825-9.  Back to cited text no. 24
[PUBMED]    
25.
Malhotra P, Kumari S, Kumar R, Varma S. Prevalence of anemia in adult rural population of North India. J Assoc Physicians India 2004;52:18-20.  Back to cited text no. 25
[PUBMED]    
26.
Shrivastava SR, Hippargi SB, Ambali AP, Yelikar BR. Patterns of anemia in geriatric age group. J Krishna Inst Med Sci Univ 2013;2:77-81.  Back to cited text no. 26
    


    Figures

  [Figure 1]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]



 

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
  Conclusions
   References
   Article Figures
   Article Tables

 Article Access Statistics
    Viewed845    
    Printed9    
    Emailed0    
    PDF Downloaded143    
    Comments [Add]    

Recommend this journal