Abstract
Atypical agents such as Mycoplasma, Legionella, Chlamydia species, and Coxiella burnetii (Q-fever agent) are responsible for some adult community-acquired pneumonia (CAP). Insufficient studies on this topic can be blamed for the failure to include atypical pathogens in empirical management. We followed adult CAP cases for two years, and samples (respiratory and serum) were tested by culture, ELISA (IgM, IgG, and IgA), and PCR. A risk factor analysis was performed. Overall in 21.3% adult CAP patients, atypical agents found were Mycoplasma pneumoniae (51.5%), Legionella pneumophila (28.8%), and Chlamydophila pneumoniae (19.7%). However, amongst patients <60 years of age and in the summer season, the proportion of atypical agents increased significantly. There is thus a need to re-examine empirical antibiotic regimes.
Keywords
Introduction
Atypical pathogens are not given priority in laboratory identification.1,2 Thus factors linked to higher risk of atypical aetiology need to be recognized for appropriate management protocols. Such factors include co-morbidity, for example, chronic obstructive pulmonary disease (COPD), and smoking.3–6
Methods
Subjects for our study were drawn continuously in our tertiary care hospital between October 2014 and September 2016. The Institutional Ethics Committee approval was obtained (letter no MC/138/2011/pt-III/221).Inclusion criteria were adults (≥18 years) with new or progressive pneumonia on a chest radiograph with clinical symptoms of cough, sputum production, or fever > 37.8°C or with minor criteria such as pleuritic chest pain, dyspnoea. 2 Exclusion criteria included subjects with seven or more days of clinical symptoms, previous admission within the previous three weeks, or an emerging alternative diagnosis (e.g. pulmonary or septic emboli, tuberculosis, or severe immunosuppression. 2
Blood for serology, and spot urine sample were collected. Serum samples underwent ELISA for IgA, IgM and IgG of Mycoplasma pneumonia, Legionella pneumophila and Chlamydia pneumonia and C. burnetii (QF) phase II IgM was done. 2
Data generated were analyzed by SPSS version 27 for Windows (SPSS Inc., Chicago, IL, USA). Mean, and Standard deviation was used to express in continuous variables while frequencies and percent denoted a categorical variables. The relationship between categorical variables was examined. Chi-square and Fisher's exact tests, taking P < 0.05 as significant level in all tests
Univariable logistic regression analysis was performed for parameters such as age below 60 years, smoking habit, male gender, presence of COPD, and summer season. Factors found significant in univariable analysis and factors expected to be associated with atypical agents were selected for multivariable analysis.
Results
A total of 663 subjects were included in the initial screening, but 75 subjects were lost to follow up or non-traceable results (51), refusal to be part of the study (9), and inadequate sample (15). A detected atypical agent profile is shown in the Supplementary Table. Distribution of risk factors (atypical infection) are shown in Table 1.
Associated factors under study for the acquisition of pathogens.
Logistic regression for association of various known risk factors of atypical pathogens (multivariable) is shown in Table 2.
Multivariable logistic regression analysis of atypical versus other pathogens (cases with unknown etiology excluded).
OR: Odd Ratio; CI: Confidence Interval; Age < 60: Age less than 60 years.
Some 588 adult community-acquired pneumonia (CAP) patients were tested and Mycoplasma pneumoniae (34/66), Legionella pneumophila (19/66), and Chlamydia pneumonia (13/66) were the major atypical agents. Out of risk factors (as in Table 1), summer season, age <60 years, and smoking were found significantly linked to CAP due to atypical agents (Table 2).
Discussion
Similar to our findings, an Iranian study found M pneumonia, L pneumophila, and C pneumoniae to be predominant agents of CAP, which corroborated well with a Delhi based study.7,8
In our study, atypical agents were found to cause CAP more in summer (36.7%) than in winter (14.9%) in a significant manner (Table 2). Those below 60 years age group suffered more (approaching 47%) (Table 2) and both these findings were similar with the result of a Dutch study done earlier. 3 One Japanese study too concluded the same. 5
One article concluded that an age <45 years to be significantly linked to atypical bacterial CAP, 9 but another could find no specific risk factor for atypical agents in their cohort of severe hospitalized CAP patients. 6 Nonetheless, a multi-centric Indian study found COPD to be significantly associated with CAP by atypical agents. 8
Earlier, studies had concluded that there could be higher incidences of atypical agents in mild adult CAP cases in ambulatory than in hospital settings. 4 It suggested that age, summer season and the smoking habit are essential considerations for coverage of atypical agents by empirical therapy of adult CAP cases. This is noteworthy from the point of view of family medical practice.
Empirical therapy coverage of atypicals in most non-severe CAP management guidelines is suboptimal.1,2 BTS guidelines rely heavily on beta-lactams with an exception only in penicillin-sensitive cases. 10 ICS/NCCP (Indian) guidelines recommend macrolides and betalactams (combined or individually). 11 According to IDSA/ATS, macrolides are to be used in outdoor cases first, with other drugs such as Fluoroquinolone/Doxycycline to be reserved for cases with co-morbidity or in the presence of previous antibiotic use.1,2
One important aspect therefore to consider is the emergence of macrolide resistant Mycoplasma pneumoniae. 12 Hence, with a high proportion of atypical agents likely in CAP subjects, coverage with doxycycline and fluoroquinolones should be included
Non-utilization of molecular techniques was a drawback of this study, though we attempted to offset this by using standard serological techniques with multiple kits (IgG, IgM & IgA) targeting the same organism.
Broader research on clinical outcome differences where identified risk factors exist will be useful.
Supplemental Material
sj-docx-1-tdo-10.1177_00494755221080587 - Supplemental material for Seasonal predominance of atypical agents in adult community-acquired pneumonia in India's northeastern region: Is it the time to look again at empirical therapy guidelines?
Supplemental material, sj-docx-1-tdo-10.1177_00494755221080587 for Seasonal predominance of atypical agents in adult community-acquired pneumonia in India's northeastern region: Is it the time to look again at empirical therapy guidelines? by Deepjyoti Kalita, Sangeeta Deka and Kripesh Ranjan Sharma, Ridip Kumar Sarma, Naba Kumar Hazarika in Tropical Doctor
Supplemental Material
sj-docx-2-tdo-10.1177_00494755221080587 - Supplemental material for Seasonal predominance of atypical agents in adult community-acquired pneumonia in India's northeastern region: Is it the time to look again at empirical therapy guidelines?
Supplemental material, sj-docx-2-tdo-10.1177_00494755221080587 for Seasonal predominance of atypical agents in adult community-acquired pneumonia in India's northeastern region: Is it the time to look again at empirical therapy guidelines? by Deepjyoti Kalita, Sangeeta Deka and Kripesh Ranjan Sharma, Ridip Kumar Sarma, Naba Kumar Hazarika in Tropical Doctor
Footnotes
Acknowledgements
We are thankful to NERBPMC section of DBT (Dept. of Biotechnology, Govt. of India for kindly providing the research grant, under DBT Twining scheme. Also acknowledge the kind permission of authorities of Gauhati Medical College, Guwahati, and AIIMS Rishikesh to carry out the study.
Author contributions
DK: concepts, design, definition of intellectual content, data analysis, manuscript editing and manuscript review. SD: design, literature search, data analysis, statistical analysis, manuscript preparation. KRS: concepts, design, clinical studies, data analysis, manuscript editing and manuscript review. RKS: experimental studies, data acquisition, manuscript preparation, NKH: definition of intellectual content, experimental studies, data acquisition, statistical analysis, manuscript editing and manuscript review.
Data availability
All data used to support the findings of this study are included within the article. Any further data can be made available upon a request to the corresponding author at
Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Department of Biotechnology, Ministry of Science and Technology, Govt. of India via NERBPMC run project called “Twining Project for North East Region”- sanction letter no (grant number BT/245/NE/DBT/2011-27.11.12).
Supplemental material
Supplemental material for this article is available online.
References
Supplementary Material
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