Prevalence of influenza and other acute respiratory illnesses in patients with acute myocardial infarction in Bangladesh: A cross‐sectional study

Abstract

Background and Aims
Several studies imply that influenza and other respiratory illnesses could lead to acute myocardial infarction (AMI), but data from low‐income countries are scarce. We investigated the prevalence of recent respiratory illnesses and confirmed influenza in AMI patients, while also exploring their relationship with infarction severity as defined by ST‐elevation MI (STEMI) or high troponin levels.

Methods
This cross‐sectional study, held at a Dhaka tertiary hospital from May 2017 to October 2018, involved AMI inpatients. The study examined self‐reported clinical respiratory illnesses (CRI) in the week before AMI onset and confirmed influenza using baseline real‐time reverse transcription polymerase chain reaction (qRT‐PCR).

Results
Of 744 patients, 11.3% reported a recent CRI, most prominently during the 2017 influenza season (35.7%). qRT‐PCR testing found evidence of influenza in 1.5% of 546 patients, with all positives among STEMI cases. Frequencies of CRI were higher in patients with STEMI and in those with high troponin levels, although these relationships were not statistically significant after adjusting for other variables. The risk of STEMI was significantly greater during influenza seasons in the unadjusted analysis (relative risk: 1.09, 95% confidence interval [CI]: 1.02–1.18), however, this relationship was not significant in the adjusted analysis (adjusted relative risk: 1.03, 95% CI: 0.91–1.16).

Conclusion
In Bangladesh, many AMI patients had a recent respiratory illness history, with some showing evidence of influenza. However, these illnesses showed no significant relationship to AMI severity. Further research is needed to understand these relationships better and to investigate the potential benefits of infection control measures and influenza vaccinations in reducing AMI incidence.

Full text

Received: 17 November 2023
|
Revised: 29 May 2024
|
Accepted: 11 June 2024
DOI: 10.1002/hsr2.2234
ORIGINAL RESEARCH
Prevalence of influenza and other acute respiratory illnesses
in patients with acute myocardial infarction in Bangladesh: A
cross‐sectional study
Mohammad Abdul Aleem
1,2
|Abrar Ahmad Chughtai
1
|Bayzid Rahman
3
|
Zubair Akhtar
2,3
|Fahmida Chowdhury
2
|Firdausi Qadri
4
|C. Raina Macintyre
3
1
School of Population Health, Faculty of
Medicine & Health, The University of New
South Wales, Sydney, New South Wales,
Australia
2
Infectious Diseases Division, Program for
Emerging Infections, International Centre for
Diarrhoeal Disease Research, Bangladesh
(icddr,b), Dhaka, Bangladesh
3
Biosecurity Program, Faculty of Medicine &
Health, The Kirby Institute, The University of
New South Wales, Sydney, New South Wales,
Australia
4
Infectious Diseases Division, Respiratory and
Enteric Infections, International Centre for
Diarrhoeal Disease and Research, Bangladesh
(icddr,b), Dhaka, Bangladesh
Correspondence
Mohammad Abdul Aleem, Infectious Diseases
Division, Program for Emerging Infections,
International Centre for Diarrhoeal Disease
Research, Bangladesh (icddr,b), 68 Shaheed
Tajuddin Ahmed Sarani, Mohakhali, Dhaka
1212, Bangladesh.
Email: drmdaleem@icddrb.org and
m.aleem@student.unsw.edu.au
Funding information
Swedish International Development
Cooperation Agency (Sida),
Grant/Award Number: GR‐01455
Abstract
Background and Aims: Several studies imply that influenza and other respiratory
illnesses could lead to acute myocardial infarction (AMI), but data from low‐income
countries are scarce. We investigated the prevalence of recent respiratory illnesses
and confirmed influenza in AMI patients, while also exploring their relationship with
infarction severity as defined by ST‐elevation MI (STEMI) or high troponin levels.
Methods: This cross‐sectional study, held at a Dhaka tertiary hospital from May
2017 to October 2018, involved AMI inpatients. The study examined self‐reported
clinical respiratory illnesses (CRI) in the week before AMI onset and confirmed
influenza using baseline real‐time reverse transcription polymerase chain reaction
(qRT‐PCR).
Results: Of 744 patients, 11.3% reported a recent CRI, most prominently during the
2017 influenza season (35.7%). qRT‐PCR testing found evidence of influenza in 1.5%
of 546 patients, with all positives among STEMI cases. Frequencies of CRI were
higher in patients with STEMI and in those with high troponin levels, although these
relationships were not statistically significant after adjusting for other variables. The
risk of STEMI was significantly greater during influenza seasons in the unadjusted
analysis (relative risk: 1.09, 95% confidence interval [CI]: 1.02–1.18), however, this
relationship was not significant in the adjusted analysis (adjusted relative risk: 1.03,
95% CI: 0.91–1.16).
Conclusion: In Bangladesh, many AMI patients had a recent respiratory illness
history, with some showing evidence of influenza. However, these illnesses showed
no significant relationship to AMI severity. Further research is needed to understand
these relationships better and to investigate the potential benefits of infection
control measures and influenza vaccinations in reducing AMI incidence.
KEYWORDS
acute myocardial infarction, acute respiratory illness, influenza, non‐ST‐elevation myocardial
infarction, ST‐elevation myocardial infarction
Health Sci. Rep. 2024;7:e2234. wileyonlinelibrary.com/journal/hsr2
|
1of13
https://doi.org/10.1002/hsr2.2234
This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any
medium, provided the original work is properly cited and is not used for commercial purposes.
© 2024 The Author(s). Health Science Reports published by Wiley Periodicals LLC.

1|INTRODUCTION
Influenza‐associated acute respiratory illness (ARI) accounts for millions of
severe cases and more than half a million deaths worldwide every year.
1,2
Adults with comorbid illness and those aged more than 65 years are at
higher risk of severe influenza outcomes
1
such as intensive care unit
admissions.
3
The2009pandemicH1N1influenzaisthoughttohave
contributed to more than 80,000 additional cardiovascular deaths globally
indicating an unrecognized burden of severe influenza.
4
Furthermore,
adverse cardiovascular incidents such as acute myocardial infarction
(AMI) and stroke contribute to almost one‐third of all deaths worldwide,
and the majority of the global burden of AMI is currently observed in low‐
and middle‐income countries, such as Bangladesh, where it is on a yearly
rise.
5–7
An AMI may be precipitated from a vulnerable atherosclerotic
plaque rupture after short‐term exposure of certain triggering factors
such as acute respiratory infection.
8
An increase in the incidence of
acute cardiovascular events such as AMI and stroke during winter
months has been attributed to ARI, along with other determinants
over the past years.
9
Temporal variations in acute cardiovascular
events were reported as early as 1937
10
and several time‐series
analyzes showed correlations of seasonal peaks of influenza‐
associated mortality with cardiovascular deaths.
11–15
Meta‐analysis
of multiple case‐control studies revealed that AMI cases were
associated with greater incidence rates of recent acute respiratory
illness, influenza‐like illness, and laboratory‐confirmed influenza
compared to control groups (pooled odds ratio: 2.01; 95% confidence
interval [CI]: 1.47–2.76),
16
which suggests that recent ARI and
influenza may significantly contribute to the occurrence of AMI
events. Furthermore, self‐controlled case‐series investigations have
reported a heightened risk of AMI in the immediate aftermath of
acute respiratory illness and laboratory‐confirmed influenza.
17–20
Influenza and ARI have also been known to exacerbate myocardial
injury, as indicated by troponin levels.
21
Although influenza‐
associated AMI may go unnoticed, it can be prevented through
influenza‐specific preventive measures, such as influenza vaccination,
which has been proven effective in various large‐scale randomized
controlled trials (RCTs)
22
as well as several smaller RCTs.
23–25
Like other low‐to middle‐income countries, an inadequately
investigated double burden of communicable illnesses such as ARIs
and non‐communicable diseases such as adverse acute cardiovascu-
lar events like AMI prevails in Bangladesh.
26
National surveillance
data confirms annual seasonal influenza prevalent among hospitalized
patients throughout Bangladesh with unimodal peak during rainy
season and may be associated with deaths among older adults and
elderly.
27,28
Despite the existing burden of incidences of AMI, as well
as the concomitant evidence of circulating influenza among the
population there is lack of data and awareness on the prevalence of
influenza as well as recent ARI exclusively among AMI patients in
Bangladesh, which incited the current investigation. Therefore, the
primary research question was about the prevalence of recent ARI
and laboratory evidence of influenza among patients with AMI in
Bangladesh. This information is crucial for understanding the extent
of the impact of these illnesses on the cardiovascular health of the
population and for developing targeted interventions. To address the
gap, the current exploratory study aimed to estimate the prevalence
of recent respiratory illness and laboratory‐confirmed influenza
among patients hospitalized with AMI. A secondary aim was to
explore the relationship of recent respiratory illness with severity of
infarction. As an initiative, we opted for a cross‐sectional design
without a control group for its time efficiency, simplicity and ability to
include a larger population.
2|METHODS
2.1 |Study design and study population
Across‐sectional study was conducted on patients aged ≥18 years
hospitalized with AMI to the cardiology unit of National Institute of
Cardiovascular Diseases in Dhaka, Bangladesh (NICVD). The patients
were enrolled during the study period between 1st May 2017 and 31st
October 2018 which included the 2017 annual influenza season (rainy
season; between 1st May and 31st October) and the 2018 annual
influenza seasons (rainy season; between 1st May and 31st October) and
non‐influenza season (winter; November 1, 2017 to April 30, 2018). The
description of annual influenza seasons for Bangladesh based on national
surveillance data is discussed in detail by Zaman et al.
27
Bangladesh is the
eighth‐most populous country in the world, with a population exceeding
165 million, and also among the most densely populated countries in the
world.
29
TheNICVDisthelargestgovernment‐operated tertiary‐level
acute care teaching hospital in Bangladesh specialized exclusively in
management of cardiovascular patients traveling from all regions of the
country. Project staff followed a standardized protocol to identify and
recruit cases with AMI, diagnosed on electrocardiogram (ECG) findings
(ST‐segment elevation or depression, pathological Q waves) and ischemic
symptoms (chest or arm pain, nausea or vomiting, sweating, shortness of
breath), with either a change in blood level of cardiac biomarkers of
myocardial necrosis (typical rise and gradual fall inTroponin or more rapid
rise and fall in Creatine Kinase MB) or coronary artery intervention.
30
To
minimize the potential misclassification bias, after reviewing the criteria
for case definition of AMI from hospital records, staff consulted with
attending cardiologist to further ensure the diagnosis of AMI. Cases with
previous history of cardiovascular event were eligible. Cases with self‐
reported history of chronic liver impairment, chronic renal impairment,
malignancy, and autoimmune disorders or those not providing consent
were excluded from the study. These conditions and their treatments
could independently affect inflammatory markers and cardiovascular risk,
complicating the interpretation of the relationship between influenza
and AMI.
2.2 |Sample size
We projected that 15%
27
of patients with AMI would have a history
of recent respiratory illness, and therefore we required a minimum
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sample size of 396 patients to estimate this proportion with an
absolute precision of 5% points and a 95% level of confidence at 80%
power. The 5% absolute precision for sample size calculation was
chosen to balance accuracy in prevalence estimates with resource
limitations, allowing significant differences to be detected within the
10%–20% expected prevalence range while maintaining practical
feasibility. To calculate the sample size, we utilized the power and
sample size function in STATA 13 for Windows. The formula used
was “sampsi 0.15 0.10, power(0.80) onesample.”This approach
enabled us to determine the minimum sample size required to
achieve our desired level of precision and confidence in the
estimation of the proportion of recent respiratory illness among
AMI patients. However, we enrolled 744 participants instead of the
initially planned 396 to enhance robustness and reliability. This
increase accounted for potential dropouts and ensured sufficient
statistical power for detailed subgroup and stratified analyzes by
influenza and non‐influenza seasons among AMI patients.
2.3 |Data collection
On a daily basis staff reviewed medical records and interviewed
recruited AMI patients using a structured interviewer‐administered
questionnaire to record sociodemographic data, self‐reported history
of recent respiratory symptoms including fever, cough, sore throat,
runny nose, and difficulty breathing within the past week of AMI
onset, information on lifestyle and co‐morbid illness and conducted
clinical examination as well as anthropometric measurements of the
participants. The blood cardiac troponin results were obtained from
hospital records measured at baseline in nanograms per milliliter
(ng/mL).
2.4 |Specimen collection and laboratory analysis
Trained staff collected nasopharyngeal and oropharyngeal swabs at
recruitment within 72 h of the date and time of AMI onset. Specimen
collection within the aforementioned timeframe was conducted to
maximize the sensitivity of the study to detect influenza RNA in the
swabs before the cessation of viral shedding. The specimens
were transported daily in Viral Transport Medium (VTM) at 2–8°C
to the virology laboratory of International Centre for Diarrheal
Disease Research, Bangladesh (icddr,b), in Dhaka. The specimens
were aliquoted in a BSL‐2 (bio‐safety level‐2) safety cabinet and were
stored in freezers at or below −70°C until analysis. Viral RNA was
extracted from the swab specimen and real‐time reverse transcrip-
tion polymerase chain reaction (qRT‐PCR) was performed using
primers and probes specific for influenza A and B viruses provided by
the Influenza Division at CDC. Hemagglutinin subtyping of types A
and B viruses was performed to detect subtypes, A/H3, A/
H1N1pdm09, B/Victoria, and B/Yamagata. The laboratory used
validated protocols
31
and followed standard quality control
procedures.
2.5 |Exposure and outcome measures
The primary exposure was clinical respiratory illness (CRI) defined as
self‐reported history of ≥2 respiratory symptoms (fever, cough, sore
throat, runny nose, and difficulty breathing) within the prior 7 days of
the date of onset of AMI.
32,33
The secondary exposure was baseline
qRT‐PCR confirmed influenza A or B. In the current study, the main
predictor variables of interest were CRI and laboratory evidence of
Influenza, and the outcome variables were AMI and AMI sub‐types.
2.6 |Data analysis
Categorical data were expressed as frequencies and percentages, while
continuous data was expressed as mean ± standard deviation (SD).
2.6.1 |Prevalence of CRI among all AMI cases and
sub‐groups of AMI cases
Descriptive analysis was performed to determine the prevalence
(frequencies and percentages) of CRI and qRT‐PCR‐confirmed influenza
among all AMI cases as well as among various sub‐groups of AMI cases.
TheprevalenceofCRIandinfluenza among the enrolled patients was
estimated by study seasons: during 2017 annual influenza season
(1st May to 31st October, 2017), 2017/2018 non‐influenza season
(November 1, 2017 to April 30, 2018) and 2018 annual influenza season
(1st May to 31st October, 2018). The sub‐groups of AMI cases included
the binary variables created for non‐ST‐Elevation Myocardial Infarction
(NSTEMI) or, ST‐Elevation Myocardial Infarction (STEMI), for blood
troponin level (high or low) and for new onset or recurrent onset AMI.
TheSTEMIandNSTEMIwereclassifiedbythepresenceorabsenceof
ST‐elevation findings in ECG. High‐troponin was defined as the upper 4th
quartile of the blood cardiac troponin level ≥24.3 ng/mL. STEMI and high‐
troponin were measures of more severe myocardial damage among AMI
cases. The Pearson χ
2
test
34
was conducted to compare the proportions
of CRI and influenza across AMI subgroups and also between influenza
and non‐influenza seasons. For the differences between groups, a
p≤0.05 was considered as statistically significant.
2.6.2 |Relationship of recent clinical respiratory
illness with STEMI and high‐troponin level in blood
among AMI patients
Multivariable log‐binomial regression
35
analyzes were performed to
investigate the relationships of CRI with the occurrence of STEMI and
high blood troponin among AMI patients, controlling for potential
confounders. All variables deemed clinically relevant as well as having
potential confounding effect and also based on p‐valuewereenteredin
thebasemodelandsequentiallyremovedusingabackwardstepwise
approach whereby variables with p‐values ≤0.25 remained in the final
model. Additionally, the variables altering the exposure‐outcome
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association, in the multivariable model, by 10% were considered
confounders. We investigated the aforementioned relationships for,
(1) entire study period and (2) independently for either the influenza or
non‐influenza seasons. The magnitudes of relationships were expressed
as relative risk (RR) and adjusted relative risk (aRR) with 95% CI in
unadjustedandadjustedanalyzes,respectively.
2.6.3 |Risk of occurrence of STEMI during influenza
season compared to non‐influenza season
We compared proportion of STEMI over NSTEMI among all AMI
cases between influenza and non‐influenza seasons. The purpose
was to examine if exposure to influenza season as opposed non‐
influenza season had any significant impact on the frequency of
events of STEMI compared to that of NSTEMI. Univariate and
multivariable Log binomial regression analyzes were performed to
measure the unadjusted and adjusted RRs of occurrence of STEMI
during influenza versus non‐influenza season. The steps for building
the multivariable regression model followed the previously men-
tioned process.
All of the statistical tests conducted in the current work was
two‐tailed. The SAS statistical software version 9.4 (SAS institute,
USA) was used to run all the analyzes.
2.7 |Ethical approval
The authors assert that all procedures contributing to this work
comply with the ethical standards of the relevant national and
institutional committees on human experimentation and with the
Helsinki Declaration of 1975, as revised in 2008. Enrollment of the
participants started after approval of the study by the icddr,b
Institutional Review Board (PR‐17039) and UNSW Human Research
Ethics Committee (HC 17861). Informed written consent to partici-
pate in the study was obtained.
3|RESULTS
A total of 744 AMI patients were enrolled during the study period
(Table 1). The mean age of participants was 51.7 years. The majority
were male (91%) and more than three‐fourth of the participants
reported tobacco use. Sixty‐three percent had family history of CVD.
TABLE 1 Demography, lifestyle, and clinical characteristics of
enrolled patients with acute myocardial infarction.
Characteristics N= 744; n(%)
Mean (SD) age in years 51.7 (10.4)
Male 677 (91)
Marital status
Never married 20 (2.7)
Married 695 (93.4)
Divorced/widow/other 29 (3.9%)
Location
Rural 351 (47.2)
Urban 393 (52.8)
Education
≤primary level 538 (72.3)
Primary to HSC 143 (19.2)
Completed graduation 63 (8.5)
Lifestyle
Ever used tobacco 551 (74.1)
Doing moderate to heavy physical activity
every week
383 (51.5)
Family history of cardiovascular diseases 469 (63)
Self‐reported chronic illnesses or past illnesses
At least one chronic illness 442 (59.4)
Hypertension 285 (38.3)
Diabetes 187 (25.1)
High blood cholesterol 63 (8.5)
Stroke 23 (3.1)
Coronary heart disease 68 (9.1)
Heart failure 16 (2.2)
Structural heart disease 2 (0.3)
History of percutaneous coronary
intervention (PCI)
9 (1.2)
History of coronary artery bypass graft (CABG) 2 (0.3)
Onset of AMI
New 678 (91.1)
Recurrent 66 (8.9)
Type of AMI
NSTEMI 143 (19.2)
STEMI 601 (80.8)
Subtype of STEMI
Anterior STEMI 189 (25.4)
Anteroseptal STEMI 106 (14.2)
Inferior STEMI 308 (41.4)
Lateral STEMI 11 (1.5)
TABLE 1 (Continued)
Characteristics N= 744; n(%)
Other subtypes of STEMI 71 (9.5)
Mean (SD) BMI 25.4 (13.8)
Abbreviations: AMI, acute myocardial infarction; NSTEMI, non‐ST‐
segment elevation myocardial infarction; SD, standard deviation; STEMI,
ST‐segment elevation myocardial infarction.
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The most commonly reported chronic illness was hypertension
(38.3%) followed by diabetes (25.1%). Among the cases, 91.1% were
of new‐onset AMI and 80.8% were STEMI. The majority of the
STEMI cases were inferior STEMI (41.4%).
3.1 |Proportion of CRI among patients with AMI
Out of the 744 AMI patients enrolled during the entire study
duration, 84 (11.3%) had reported having CRI during the week
before AMI onset (Table 2). The majority of participants reporting
CRI (77/84; 91.7%) had developed CRI within 3 days of AMI
onset. The most common respiratory symptoms reported during
the week preceding AMI were fever (17.9%), cough (16.5%), and
runny nose (10.6%). The prevalence of CRI among AMI cases and
subgroups varied between influenza and non‐influenza seasons,
with the highest prevalence observed during the 2017 influenza
season (35.7%). During the 2018 influenza season, CRI was more
common in recurrent than new onset AMI cases (11.9% vs. 7.3%;
p= 0.36). Furthermore, during the 2017 influenza season, the
prevalence of CRI was higher among STEMI cases than NSTEMI
cases (36.8% vs. 33.3%; p= 0.79), and prevalence of CRI was
higherinSTEMIthaninNSTEMIcasesduringthenon‐influenza
season (14.2% vs. 7.3%; p= 0.24) and during the 2018 influenza
season (7.9% vs. 6.5%; p= 0.74). The high‐troponin AMI cases
had higher rates of CRI compared to low‐troponin cases during
2017 (37.5% vs. 35.0%; p= 0.90) and during 2018 influenza
season (11% vs. 8.7%; p= 0.62). Last, the percentage of CRI
within 3 days of onset of AMI was higher in recurrent than new
onset AMI cases (p=0.15), in high‐troponin than low‐troponin
AMI cases (p= 0.62) during 2018 influenza season and higher in
STEMI than NSTEMI cases during both non‐influenza (p=0.31)
and 2018 influenza season (p=0.50).
3.2 |Proportions of laboratory‐confirmed
influenza
Out of 744 participants enrolled in the study, 546 (73.4%) were
tested for influenza by qRT‐PCR, and among them only 8 (1.5%)
were positive (Table 2). Of the positive cases, one was confirmed
during the 2017 influenza season and seven during the
2018 influenza season. The identified influenza subtypes were
one influenza B/Yamagata during October 2017, four A/H3
TABLE 2 Prevalence of self‐reported clinical respiratory illness and laboratory‐confirmed influenza among the patients with acute
myocardial infarction by study seasons.
Patients
Proportion, n/N(%)
2017 Influenza
season
Non‐influenza
season
2018 Influenza
season All seasons
Clinical respiratory illness
All AMI 20/56 (35.7) 27/210 (12.9) 37/478 (7.7) 84/744 (11.3)
New onset AMI 18/44 (40.9) 27/198 (13.6) 32/436 (7.3) 77/678 (11.4)
Recurrent onset AMI 2/12 (16.7) 0/12 (0) 5/42 (11.9) 7/66 (10.6)
NSTEMI 6/18 (33.3) 3/41 (7.3) 3/46 (6.5) 12/105 (11.4)
STEMI 14/38 (36.8) 24/169 (14.2) 34/432 (7.9) 72/639 (11.3)
Low‐troponin AMI 7/20 (35.0) 9/78 (11.5) 11/127 (8.7) 27/225 (12.0)
High‐troponin AMI 3/8 (37.5) 1/32 (3.1) 4/35 (11.0) 8/75 (10.7)
Laboratory‐confirmed influenza
All AMI 1/56 (1.8) 0/12 (0) 7/478 (1.5) 8/546 (1.5)
New onset AMI 1/44 (2.3) 0/11 (0) 5/436 (1.1) 6/491 (1.2)
Recurrent AMI 0/12 (0) 0/1 (0) 2/42 (4.8) 2/55 (3.6)
NSTEMI 0/18 (0) 0/4 (0) 0/46 (0) 0/68 (0)
STEMI 1/38 (2.6) 0/8 (0) 7/432 (1.6) 8/478 (1.7)
Low‐troponin AMI 1/20 (5) 0/3 (0) 2/127 (1.6) 3/150 (2)
High troponin AMI 0/8 (0) 0/2 (0) 1/35 (2.9) 1/45 (2.2)
Note: 2017 annual influenza season: rainy season; during 1st May to 31st October, 2017. Non‐influenza season: winter; November 1, 2017 to April 30,
2018. 2018 annual influenza seasons: rainy season; during 1st May to 31st October, 2018.
Abbreviations: AMI, acute myocardial infarction; NSTEMI, non‐ST‐segment elevation myocardial infarction; STEMI, ST‐segment elevation myocardial
infarction.
ALEEM ET AL.
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during July, one A/H3 during August, and two A/H1N1pdm09
during July 2018 influenza season. Influenza virus was detected
exclusively among STEMI cases. Influenza was more prevalent
among recurrent AMI cases than new AMI cases during the
overall study period (3.6% vs. 1.2%; 0 = 0.16) and the 2018
influenza season (4.8% vs. 1.1%; p= 0.06). Influenza positivity
was higher among AMI cases with high troponin levels than those
with low troponin levels during the 2018 influenza season (2.9%
vs. 1.6%; p=0.62).
3.3 |Proportion of CRI compared between
2017/2018 non‐influenza season and all influenza
seasons
We compared the proportions of AMI cases and also sub‐groups
of AMI cases reporting recent CRI during the combined duration
of annual influenza seasons to that during the 2017/2018 non‐
influenza season. Among AMI patients with high blood level of
troponin, proportion of CRI was higher during influenza seasons
(16.3%) compared to non‐influenza season (3.1%) with p= 0.07.
Similarly, NSTEMI patients had a higher proportion of CRI during
influenza season (14.1%) compared to non‐influenza season
(7.3%) with a pvalue of p=0.3.
3.4 |Log binomial regression
3.4.1 |Relationship of CRI with STEMI by study
seasons
Overall, the proportions of STEMI were similar between AMI cases
with or without CRI during either non‐influenza and influenza
seasons. However, STEMI proportion was slightly higher among
patients with CRI than patients without CRI during 2017‐influenza
season and during non‐influenza season (Table 3). Nevertheless, the
aRRs for relationship of CRI with STEMI were around 1 during
different study seasons which was statistically not significant.
3.4.2 |Relationship of CRI with high blood level of
troponin among AMI patients by study seasons
Overall, the results demonstrate that there was no significant relationship
between recent CRI (Table 4) and high blood levels of troponin among
patients with AMI, during different study seasons. However, there was a
positive trend in the relationship between CRI and high‐troponin AMI,
especially during the 2018 influenza season where the RR is 1.26 and the
aRR is 1.79. However, these estimates were not statistically significant.
Similarly, during all influenza seasons, there was a slight positive trend in
TABLE 3 Relationship of clinical respiratory illness with ST‐elevation myocardial infarction by study seasons.
Clinical respiratory
illness status Total NSTEMI n(%) STEMI n(%) RR
a
(95% CI) aRR
b
(95% CI)
All seasons
No 660 93 (14.1) 567 (85.9) Ref. Ref.
Yes 84 12 (14.3) 72 (85.7) 0.99 (0.91–1.09) 1.03 (0.87–1.22)
2017 influenza season
No 36 12 (33.3) 24 (66.7) Ref. Ref.
Yes 20 6 (30.0) 14 (70.0) 1.05 (0.73–1.52) 1.03 (0.60–1.75)
During 2017/2018 non‐influenza season
No 183 38 (20.8) 145 (79.2) Ref. Ref.
Yes 27 3 (11.1) 24 (88.9) 1.12 (0.96–1.31) 1.05 (0.82–1.34)
During 2018 influenza season
No 441 43 (9.8) 398 (90.2) Ref. Ref.
Yes 37 3 (8.1) 34 (91.9) 1.02 (0.92–1.13) 1.01 (0.87–1.19)
During all influenza seasons
c
No 477 55 (11.5) 422 (88.5) Ref. Ref.
Yes 57 9 (15.8) 48 (84.2) 0.95 (0.85–1.06) 0.92 (0.29–2.87)
Abbreviations: aRR, adjusted relative risk; BMI, body mass index; CI, confidence interval; CVD, cardiovascular disease; NSTEMI, non‐ST‐segment elevation
myocardial infarction; RR, relative risk; STEMI, ST‐segment elevation myocardial infarction.
a
RR: unadjusted relative risk.
b
aRR: adjusted relative risk; adjusted for age, sex, tobacco use, hypertension, diabetes, high blood cholesterol, heart failure, exercise level, previous history
of CHD, family history of CVD and BMI.
c
Includes both annual influenza seasons of 2017 and 2018.
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the RR of 1.28 and the aRR of 1.12, but again, the results were not
statistically significant.
3.4.3 |Risk of STEMI during influenza season
compared to non‐influenza season
Table 5shows the regression analysis for the risk of experiencing a STEMI
over NTEMI during the influenza season compared to the non‐influenza
season. In the univariate analysis, onset of STEMI was significantly more
likely during influenza compared to non‐influenzaseason,withariskof
RR: 1.09, 95% CI: 1.02–1.18, but this relationship was not found
significant after adjusting for confounders in the multivariate analysis
(aRR: 1.03, 95% CI: 0.91–1.16).
4|DISCUSSION
To the best of our knowledge, this is the first study in Bangladesh to
investigate the prevalence of recent CRI and laboratory‐confirmed
influenza among patients with AMI. The results of this study indicate
that a significant proportion of the participants had a history of CRI
TABLE 4 Relationship of clinical respiratory illness with high level of troponin in blood among patients with myocardial infarction by study
seasons.
Respiratory
illness Total
Low troponin
n(%)
High troponin
n(%) RR
a
(95% CI) aRR
b
(95% CI)
During all seasons
No 265 198 (74.7) 67 (25.3) Ref. Ref.
Yes 35 27 (77.1) 8 (22.9) 0.90 (0.47–1.72) 0.89 (0.42–1.87)
During 2017 influenza season
No 18 13 (72.2) 5 (27.8) Ref. Ref.
Yes 10 7 (70.0) 3 (30.0) 1.08 (0.70–1.67) 1.03 (0.46–2.31)
During 2017/2018 non‐influenza season
No 100 69 (69) 31 (31) Ref. Ref.
Yes 10 9 (90) 1 (10) 0.32 (0.05–2.12) 0.36 (0.08–1.61)
During 2018 influenza season
No 147 116 (78.9) 31 (21.1) Ref. Ref.
Yes 15 11 (73.3) 4 (26.7) 1.26 (0.52–3.1) 1.79 (0.58–5.48)
During all influenza seasons
c
No 165 129 (78.2) 36 (21.8) Ref. Ref.
Yes 25 18 (72.0) 7 (28.0) 1.28 (0.79–2.09) 1.12 (0.53–2.35)
Abbreviations: aRR, adjusted relative risk; BMI, body mass index; CI, confidence interval; CVD, cardiovascular disease; RR, relative risk.
a
RR: unadjusted relative risk.
b
aRR: adjusted relative risk; adjusted for age, sex, tobacco use, hypertension, diabetes, high blood cholesterol, heart failure, exercise level, previous history
of CHD, family history of CVD and BMI.
c
Includes both annual influenza seasons of 2017 and 2018.
TABLE 5 Relationship of influenza seasons with ST‐elevation myocardial infarction.
Seasons Total NSTEMI n(%) STEMI n/N(%) RR
b
(95% CI) aRR
c
(95% CI)*
Non‐influenza season 210 41 (19.5) 169 (80.5) Ref. Ref.
Influenza seasons
a
534 64 (12.0) 470 (88.0) 1.09 (1.02–1.18) 1.03 (0.91–1.16)
Abbreviations: aRR, adjusted relative risk; CI, confidence interval; NSTEMI, non‐ST‐segment elevation myocardial infarction; RR, relative risk; STEMI,
ST‐segment elevation myocardial infarction.
a
Includes both annual influenza seasons of 2017 and 2018.
b
RR: unadjusted relative risk.
c
aRR: adjusted relative risk; adjusted for age, sex, tobacco use, exercise level, hypertension, diabetes, high blood cholesterol, heart failure, previous history
of CHD and BMI.
*p= 0.67.
ALEEM ET AL.
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within a week of AMI onset and that qRT‐PCR‐confirmed influenza
was present, suggesting that recent acute respiratory illness and
influenza may potentially contribute to triggering AMI. Notably, the
self‐reported CRI among AMI patients was prevalent during both
influenza and non‐influenza seasons, indicating that the circulation of
non‐influenza respiratory viral pathogens could also potentially play a
role in triggering the onset of AMI.
36–38
These findings highlight the
need for further investigation into the potential association between
recent respiratory illnesses and AMI, including the identification of
specific viral pathogens and mechanisms underlying this association.
About one‐third of the enrolled AMI patients during the 2017
influenza season reported a history of CRI which was much more
frequent than that reported during 2018 influenza season. This could
be validated in the context of report by the national hospital‐based
influenza surveillance program in Bangladesh indicating a relatively
more severe influenza epidemic and upward surge in severe acute
respiratory illness (SARI) admissions occurred in the country during
2017 compared to the 2018 influenza season
39
suggesting that there
could be a potential link between the intensity of the influenza
season and the number of AMI cases associated with influenza. The
current study did not find a statistically significant relationship
between recent CRI and the severity of myocardial damage, as
defined by STEMI or high blood troponin. However, in general, the
proportion of STEMI cases over NSTEMI was higher during the
influenza season compared to the non‐influenza season, and this
difference was statistically significant in the unadjusted but not in
adjusted regression analysis. It is possible that unrecognized recent
influenza infection may play a role in triggering STEMI, however,
further research is needed to establish a definitive relationship.
Although our findings imply a potential link between recent acute
respiratory illnesses and influenza with the occurrence of AMI, it is
crucial to acknowledge that our study's cross‐sectional design does
not allow us to establish a definitive association between the
exposures and the outcome and hence recommend further valida-
tion. Further studies, including case‐control studies or prospective
cohort studies, are needed to confirm an association and elucidate
the mechanisms underlying this association. However, these results
do highlight the importance of considering the potential impact of
respiratory illness, including seasonal influenza, on cardiovascular
health among population in Bangladesh. Importance of further
research and analysis of the potential benefits of robust infection
control measures and influenza vaccination programs for AMI
prevention cannot be overstated.
Previous studies have reported a wide range of frequencies of
recent respiratory illness among AMI cases, ranging from 2.8% to
60.3%.
16
The overall frequency of recent CRI in this study (11.3%) is
comparable to previous reports,
16
from London (14.3%) and Finland
(12.2%), and the frequency of CRI during the 2017 influenza season
in this study (36%) is comparable to reports,
16
from Sydney, Australia
(31.1%), Massachusetts (28%), London (24.3%), Finland (28%) and
lastly from Karachi, Pakistan
37
(36.2%). However, it is possible that
the differences in reported frequency of acute respiratory illness
among AMI cases across studies may be attributed to various factors,
such as demographic variations among participants and discrepancies
in the criteria used to define recent acute respiratory illness. Most of
the previous studies were conducted in high‐income countries where
the average age of recruited AMI patients was over 60 years old,
which was significantly older than the average age of participants in
our study (52 years). While Warren et al.
40
defined recent acute
respiratory illness for AMI cases as having both respiratory and
systemic symptoms with an onset of illness within the past month,
our criteria for CRI did not include systemic symptoms. This
difference in criteria may be an important limiting factor in
appropriately classifying cases with recent acute respiratory illness,
as including systemic symptoms in the criteria for recent acute
respiratory illness may be crucial in accurately identifying cases that
have truly had a recent acute respiratory infection. Our study's
definition for CRI
32,33
only included respiratory symptoms that
developed within a week of AMI to minimize recall bias. We believe
that major cardiovascular events following an acute respiratory
infection are more clinically plausible during this timeframe than a
longer period of time after the infection. Despite the lack of systemic
symptoms in our case definition, we still believe that our definition
for recent respiratory illness in the current study is clinically sensitive
enough to increase the likelihood of capturing cases with recent
respiratory infection preceding onset of AMI. However, we acknowl-
edge that our definition may have lower specificity, potentially
leading to the inclusion of false positive cases for CRI. Another
potential contributing factor to the differing frequencies across
previous studies is that some were restricted to only influenza
seasons while others were conducted during both influenza
30,40
and
non‐influenza seasons.
41
Due to cross‐sectional study design, we were unable to show a
direct association between recent CRI and AMI. However, several
previous case‐control studies showed an association of recent
respiratory illness with AMI. A case‐control study based on large
general practice database in Europe showed risk of AMI incidence
twofold within 7 days after respiratory infection.
41,42
Another
longitudinal population‐based cohort study performed in the United
States indicated risk of acute cardiovascular events including AMI,
stroke and death highest during the first month of hospitalization for
pneumonia.
41,42
In general AMI cases could be as much as twice
more likely than controls to report history of recent respiratory illness
occurring within 7 days of AMI onset and the strength of this
association is lesser for respiratory illness occurring >7 days of onset
of AMI and fell over time.
30,40,41
There is high double burden of both
acute respiratory infections as well as acute cardiovascular events
26
in Bangladesh and despite evidence in other countries there is no
data for Bangladesh about prevalence of recent respiratory illness
preceding onset of AMI.
We reported a low frequency of influenza positivity in AMI cases.
In the previous studies, the frequency of influenza detection by real‐
time PCR, paired serum influenza antibodies and single baseline
influenza antibody titer among AMI patients ranged from 14% to
86.3%.
16
The detection rates may considerably vary due to study‐
specific laboratory methods applied, pattern as well as intensity of
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ALEEM ET AL.

influenza strains during study period, and study conducted during
both or either influenza and/or non‐influenza seasons. The most
confirmatory standard test method to diagnose influenza is the
RT‐PCR test of respiratory swabs as recommended by the World
Health Organization (WHO). Most of the previous studies identified
low numbers of influenza by PCR alone.
30,40,43
Nevertheless,
investigators considered using baseline serology
43
and analysis of
paired serums
30
for immunoglobulin G or baseline serology for
immunoglobulin A
40
to report additional influenza with or without
PCR. The WHO recommends swabbing patients within 10 days of
onset of respiratory symptoms to increase the likelihood of detecting
influenza RNA by PCR before diminution of viral shedding.
44
There is
still limited clarity on the exact timeline of onset of AMI after
influenza infection, hence PCR test will likely have lower sensitivity if
viral shedding diminishes before swabbing AMI patients. However, to
maximize sensitivity to detect viral shedding, all participants in our
study were swabbed within 72 h of the onset of AMI. Serological
analysis of convalescent serum in addition to PCR could have
enhanced the sensitivity to detect more influenza‐positive AMI
patients which is limitation of the current study. Moreover, due to
administrative delays, we enrolled and tested only a minimal number
of AMI cases during the peak influenza months May‐September in
2017 influenza season when sequentially A(H1N1)pdm09, A/H3, and
influenza B were the predominant strains circulating nationally.
39
During the current study, all cases of qRT‐PCR‐confirmed
influenza among AMI patients were identified only within the
influenza seasons. The influenza subtypes that were identified fully
corresponded to the month‐specific circulating influenza strains
identified through the national influenza surveillance scheme in the
country
39
signifying typical influenza strains were also circulating
among AMI patients in Bangladesh during the 2017 and 2018
influenza seasons. Interestingly, our study found a higher frequency
of real‐time PCR‐confirmed influenza in AMI patients compared to
similar studies conducted in high‐income countries, where only 0/70
and 1/275 AMI cases tested positive for influenza nucleic acid.
30,40
It
is possible that the population in Bangladesh has a higher
susceptibility to influenza‐associated AMI due to factors such as
low vaccination rates, or high prevalence of cardiovascular co‐
morbidities. Nevertheless, our study design was cross‐sectional and
did not have a control group, therefore not specifically designed to
investigate the association between laboratory‐confirmed influenza
and AMI. However, very few previous case‐control studies were able
to reveal a direct association between laboratory‐confirmed influenza
and AMI,
43
perhaps due to the fact that influenza may be less
common in the particular age group where AMI usually occurs.
Conversely, more case‐control studies have reported significant
effectiveness of influenza vaccine against AMI
16,30
which could be an
indirect evidence of influenza's association with AMI.
When we explored the relationship between recent CRI and the
severity of myocardial damage, particularly during influenza seasons,
our findings indicated that recent CRI frequencies were generally
higher among STEMI patients compared to NSTEMI patients.
Similarly, the analysis showed a positive trend in the relation
between CRI and high troponin levels‐up to 80% higher during the
2018 influenza season. However, none of these findings had
statistical significance. Therefore, caution should be exercised in
interpreting these trends, as they do not necessarily indicate a
definitive association. Furthermore, while all of the identified
influenza strains were exclusive to STEMI cases, it is important to
interpret these findings with caution in patient evaluations, as this
observation may not represent a genuine relationship. Both STEMI
and high troponin level are related to severe myocardial damage. We
believe that the analyzes conducted during influenza seasons were
underpowered because the sample sizes were too small within the
AMI subgroups categorized by myocardial damage severity. This
small sample size likely prevented us from detecting statistically
significant results, even if a genuine relationship between CRI and
infarction severity existed. Nevertheless, there is previous evidence
that influenza infection may increase the risk while the influenza
vaccine is effective against large‐size infarcts, high troponin or
CK‐MB levels in patients with AMI.
45
Potential connection between
seasonal fluctuations in the occurrence of severe acute respiratory
infections, such as influenza, and AMI events with significant
myocardial damage in high‐risk, unvaccinated individuals could
benefit from more detailed investigation. This investigation should
involve robust analytical studies carried out over multiple seasons to
enhance the clarity and reliability of the findings. It seems plausible
that the magnitude and direction of such relationships might be
influenced by the intensity and pattern of circulating seasonal
influenza strains embedded within climatic factors
37,46
and perhaps
additionally and importantly, on clinically unrecognized respiratory
viral infections.
11,13,36
For example, five out of seven influenza‐
positive cases in the current study did not report recent CRI which
may imply that the link between influenza and AMI may be more
complex than our current understanding. This may also suggest that
there may be other mechanisms by which influenza increases the risk
of AMI, even in the absence of an acute respiratory illness. For
example, influenza may cause changes in the immune system, blood
clotting, or cardiac function increasing the risk of AMI. Alternatively,
it may be that the individuals in the study who tested positive for
influenza but did not report recent acute respiratory illness had
underlying conditions predisposing them to AMI, and the influenza
infection simply acted as a trigger.
47
Accordingly, further analysis in
the current study showed a higher prevalence of STEMI over
NSTEMI among participants during influenza season than during non‐
influenza season. The univariate analysis showed there was a
significant 9% increase in the risk of STEMI during influenza than
during non‐influenza season suggesting that acute respiratory
illnesses could potentially intensify STEMI events during periods of
influenza.
The underlying pathophysiology of STEMI is complete blockage
of the coronary artery by atherothrombosis causing transmural
cardiac myonecrosis. This is primarily driven by an acute end stage of
a chronic inflammatory atherosclerotic lesion characterized by abrupt
rupturing of the de‐stabilized atherosclerotic plaque due to short‐
term exposure of certain triggering factors that may differ from the
ALEEM ET AL.
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number of known cardiovascular risk factors.
48
Such triggers of
plaque rupture can include respiratory viral infections including
influenza along with smoking, excessive alcohol, hypertension, heavy
physical exertion or any kind of stressful events.
49,50
One study
showed respiratory viral infections can precipitate both STEMI and
NSTEMI and were positively associated with risk of mortality among
NSTEMI, but not among STEMI.
51
Nevertheless, patients after STEMI
have a higher in‐hospital mortality rate and worse short‐term
outcomes while NSTEMI patients have poorer long‐term prognosis.
52
Blood troponin levels are well correlated to the extent of infarction in
both STEMI and NSTEMI but more impressive in STEMI.
53,54
In the
current study, age at onset of STEMI was significantly lower than
NSTEMI, suggesting that these different subtypes of AMI may have
different risk factors and underlying mechanisms. Further research is
needed to explore the relationship between influenza and different
subtypes of AMI, as well as any factors influencing the association
between influenza and STEMI. Preventing early onset STEMI is
crucial in Bangladesh, where the age of onset for AMI is much earlier
than in high‐income countries. A simple yet effective measure to
combat this issue could be the administration of the influenza
vaccine. This could not only help curb the early onset of STEMI but
also significantly lower in‐hospital mortality among young individuals
in Bangladesh.
Theimmunesystemplaysacriticalroleinboththe
pathophysiology of AMI and the physiological mechanisms
behind the protection offered by the influenza vaccine against
AMI. This interplay between the immune system and AMI
highlights the vital importance of understanding the intricacies
of this relationship to effectively prevent and treat AMI.
Dominant pro‐inflammatory over the anti‐inflammatory compo-
nent of the immune system may favor sudden atherosclerosis
progression leading to acute cardiovascular events like AMI.
55
Influenza virus can induce significant acute changes in pro‐
inflammatory cytokine levels in blood and pro‐inflammatory as
well as prothrombotic effects in atherosclerotic plaques which
can trigger AMI onset through plaque destabilization.
56
However,
there are interindividual differences in the intensity of a rapid
pro‐inflammatory response which may explain the difference in
the level of risk of AMI among individuals in response to an acute
stimulus such as influenza.
57
Investigations continue globally to
understand the relationship between influenza and AMI, with the
goal of using influenza vaccination to prevent AMI in high‐risk
individuals. Several observational studies,
16,30,58
small scale
59,60
and large scale
22
randomized clinical trials reported protective
efficacy of influenza vaccine against adverse cardiovascular
events including hospitalization or death due to AMI. Animal
study showed influenza vaccine stabilized atherosclerotic plaque
through promoting anti‐inflammatory atheroprotective immune
response
61
implying possibly a greater protection against under-
lying pathophysiology of onset of STEMI than NSTEMI. Influenza
vaccine has been shown to blunt pro‐inflammatory and enhance
anti‐inflammatory mediators after coronary artery bypass
surgery.
62
5|STRENGTHS AND LIMITATIONS
The study's large sample size improves the generalizability of findings
on CRI/influenza prevalence among AMI patients. Conducted in a
specialized tertiary‐level cardiac hospital, it strengthens the applica-
bility of our findings to similar settings. By spanning both influenza
and non‐influenza seasons, the study compares the impact of
respiratory illnesses on AMI patients across different seasons. A
standardized protocol and verification by attending cardiologists
minimized misclassification bias. The clear case definition for recent
acute respiratory illness and qRT‐PCR testing for influenza enhanced
exposure sensitivity. Multivariate regression analysis controlled for
confounders, further reducing bias in assessing the relationship
between recent respiratory illness and AMI severity. However, it's
crucial to acknowledge certain limitations in the present study. First
of all, the cross‐sectional design of our study did not allow us to
investigate the association of CRI and influenza with onset of AMI.
For this inaugural Bangladeshi study, we favored a cross‐sectional
design, lacking a control group, over a case‐control approach due to
time sensitivity, the need for rapid data collection, its efficiency, cost‐
effectiveness, and capability to study a larger population. Therefore,
in our recommendation for future research, we recognize that a case‐
control design would be the appropriate method to enable statistical
investigation of the association of CRI and influenza with AMI.
Second, any clinical definition for acute respiratory illness has
inherent limitations including subjectivity, limited specificity, and
variability of respiratory symptoms depending on the patient's age
and individual experiences, compounded by the lack of standardiza-
tion. This could lead to potential bias in our prevalence estimates.
Our case definition of CRI excluded systemic symptoms like body
ache, likely compromising sensitivity and underestimating the
prevalence of AMI patients with recent CRI. Consequently, indivi-
duals with systemic symptoms might have been missed, leading to a
reported prevalence lower than the actual prevalence. A more
standardized and objective measures of respiratory illness may
improve the reliability and generatability of the findings. Third, we
were unable to further confirm every AMI diagnosis through
angiogram findings of coronary artery blockage and echocardiogram
findings of regional wall motion abnormalities. Fourth, due to delay in
initiation of the field implementation we had not enrolled participants
during peak influenza months June–July of 2017 which might
significantly affect our overall estimates for frequencies of CRI and
influenza. Our study only investigated two annual influenza seasons,
which may not fully reflect the broader trends of influenza
prevalence among AMI patients. As influenza activity varies
significantly year to year, a longer study period would yield a more
comprehensive understanding of these patterns and their impact on
AMI. Fifth, we utilized only qRT‐PCR to identify influenza among
participants which had limited sensitivity due to diminution of viral
shedding. We believe addition of influenza serology would have
significantly enhanced the sensitivity of the current study to identify
additional influenza‐positive participants. Lastly as our study was
conducted in a single center in Bangladesh, our results are limited due
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ALEEM ET AL.

lack of generalizability and hence may not represent the broader
population of the country.
6|CONCLUSION
The present study results indicate that recent influenza and other
acute respiratory illnesses may commonly occur before onset of AMI
among Bangladeshi patients. Additionally, the study has generated
some data regarding the relationship between recent respiratory
illness and influenza with severity of myocardial infarction across
different study seasons in Bangladesh which, however, were
statistically not significant. Nevertheless, our results emphasize the
importance of increased awareness among patients with heart
conditions as well as among healthcare providers in Bangladesh
about the possible risk of seasonal outbreaks of influenza and other
acute respiratory illnesses. This may lead to improved timeliness of
early interventions and hence better patient outcomes. Our results
indicate the need for further studies, using prospective cohort or
case‐control design, and in particular conducted over multiple
seasons and multiple centers across the country to investigate the
association between recent respiratory illness and influenza with
onset of AMI in Bangladeshi context. Given the known high
prevalence of both acute cardiovascular events like AMI as well as
seasonal influenza
27
in Bangladesh, and potential efficacy of
influenza vaccination against incidence of AMI, as revealed through
recently completed large scale clinical trial
22
and other observational
studies, benefits of influenza vaccination program as well as infection
prevention and control practices in Bangladesh deserve further
exploration. Our study may provide valuable insights about the latent
risk of acute respiratory illness and influenza for cardiovascular
patients in Bangladesh, but our results should be cautiously
considered in the context of their limitations and potential biases.
There is currently no acute respiratory illness surveillance
exclusively among patients hospitalized with adverse cardiovascular
events in Bangladesh highlighting a gap in the healthcare system in
Bangladesh. Without dedicated surveillance, there is limited under-
standing of respiratory illness's impact among patients with cardio-
vascular diseases. The current study findings emphasized the
relevance of dedicated respiratory illness surveillance among
hospitalized individuals with adverse cardiovascular events. A
dedicated surveillance would improve our understanding of the
impact of respiratory illnesses among these groups of patients,
provide data for health planning, and mitigate missed opportunities
for early detection and intervention.
AUTHOR CONTRIBUTIONS
Mohammad Abdul Aleem: Conceptualization; data curation; formal
analysis; funding acquisition; investigation; methodology; project
administration; validation; writing—original draft; writing—review &
editing. Abrar Ahmad Chughtai: Formal analysis; supervision;
writing—original draft; writing—review & editing. Bayzid Rahman:
Formal analysis; methodology; supervision; writing—review & editing.
Zubair Akhtar: Investigation; project administration; writing—review
& editing. Fahmida Chowdhury: Investigation; project administration;
resources; writing—review & editing. Firdausi Qadri: Conceptualiza-
tion; investigation; methodology; project administration; resources;
supervision; writing—review & editing. C Raina Macintyre: Concep-
tualization; investigation; methodology; project administration;
supervision; writing—review & editing. All authors have read and
approved the final version of the manuscript.
ACKNOWLEDGMENTS
The authors are grateful to the study data collection team and study
participants for their valuable data. We also acknowledge the support of
NICVD authority in conducting this study. This work was supported by
The Swedish International Development Cooperation Agency (Sida), grant
number: GR‐01455. This supporting source was not involved in the study
design, collection, analysis, and interpretation of data, writing of the
report, and the decision to submit the report for publication.
CONFLICT OF INTEREST STATEMENT
The authors declare no conflicts of interest.
DATA AVAILABILITY STATEMENT
No additional data are available. Mohammad Abdul Aleem, the lead
and corresponding author, had full access to all of the data in this
study and takes complete responsibility for the integrity of the data
and the accuracy of the data analysis. Data generated during the
study are subject to a data access policy of icddr,b and are available
from icddrb's research administration on reasonable request through
the corresponding author.
TRANSPARENCY STATEMENT
The lead author Mohammad Abdul Aleem affirms that this manu-
script is an honest, accurate, and transparent account of the study
being reported; that no important aspects of the study have been
omitted; and that any discrepancies from the study as planned (and, if
relevant, registered) have been explained.
ORCID
Mohammad Abdul Aleem http://orcid.org/0000-0003-1634-8725
Zubair Akhtar http://orcid.org/0000-0001-5054-9243
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How to cite this article: Aleem MA, Chughtai AA, Rahman B,
et al. Prevalence of influenza and other acute respiratory
illnesses in patients with acute myocardial infarction in
Bangladesh: a cross‐sectional study. Health Sci Rep.
2024;7:e2234. doi:10.1002/hsr2.2234
ALEEM ET AL.
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