Study Setting, Population, and Support

The health insurance program of Ontario provides universal access to physician services, hospital care, and laboratory testing for virtually all residents. We included in our study all Ontario residents who were registered for provincial publicly funded health insurance; who underwent testing for one or more respiratory viruses between May 1, 2009, and May 31, 2014; who were 35 years of age or older at the time of testing; and who were hospitalized for an acute myocardial infarction between May 1, 2008, and May 31, 2015. We obtained ethics approval from the institutional review board at Sunnybrook Health Sciences Centre in Toronto.

This study was supported by an operating grant from the Canadian Institutes of Health Research, by Public Health Ontario, and by the Institute for Clinical Evaluative Sciences. The authors vouch for the completeness and accuracy of the data and all analyses.

Data Sources and Definitions

We obtained respiratory virus testing results from the Flu and Other Respiratory Viruses Research (FOREVER) Cohort (see the Supplementary Appendix, available with the full text of this article at NEJM.org). In brief, the cohort features individual-level linkage of respiratory virus testing results from 11 Public Health Ontario laboratories and 8 academic hospital–based laboratories with an extensive array of administrative databases held at the Institute for Clinical Evaluative Sciences. The respiratory specimens that were tested were submitted from physician offices, emergency departments, hospitals, long-term care facilities, and public health departments as part of routine clinical care, outbreak investigations, or research. They were tested for influenza A (with subtype information available for 56% of the positive specimens) and influenza B, and 88% of the specimens were also tested for one or more of the following respiratory viruses: respiratory syncytial virus (RSV), adenovirus, coronavirus, enterovirus (including rhinovirus), parainfluenza virus, and human metapneumovirus. Testing methods included reverse-transcriptase polymerase chain reaction (PCR; monoplex or multiplex assays), viral culture, direct fluorescent antibody staining, and enzyme immunoassays. Limited information regarding clinical symptoms was available for approximately 40% of the cases included in this study (see the Supplementary Appendix). To avoid capturing multiple exposures for the same illness episode, we excluded positive specimens that were obtained within 14 days after a previous positive specimen from the same patient.

Hospitalizations for acute myocardial infarction were ascertained from the Discharge Abstract Database of the Canadian Institute for Health Information, which contains detailed administrative, diagnostic, and clinical information for all admissions to acute care hospitals.22 We included admissions with acute myocardial infarction as the primary diagnosis, defined on the basis of diagnosis code I21 in the International Classification of Diseases, 10th Revision (ICD-10). In a validation study, conducted in Ontario, that used a registry of patients who had been admitted to cardiac care units with acute coronary syndromes as the reference standard, the sensitivity of acute myocardial infarction diagnostic codes was 89%, the specificity was 93%, and the positive predictive value was 89%.22 We restricted the analysis to the first event in an episode of care by excluding transfers between hospitals and admissions within 30 days after a previous hospital discharge for acute myocardial infarction for the same patient. The laboratory and hospitalization data were linked at the individual level with the use of unique encoded identifiers (linkage proportion, 97%) and were analyzed at the Institute for Clinical Evaluative Sciences.

Statistical Analysis

Figure 1. Figure 1. Schematic of the Study Design. Patient A represents a person who is infected with influenza and is hospitalized for acute myocardial infarction at any time during the 7-day risk interval (light-shaded areas) after exposure. Patient B represents a person infected with influenza who has an acute myocardial infarction during the control interval (dark-shaded areas). The study assessed the relative incidence of acute myocardial infarction during the risk interval as compared with the control interval. Note that the figure is not to scale.

The statistical analysis was based on the self-controlled case-series design, as shown in Figure 1. The date the respiratory specimen was obtained served as the index date for defining the exposure (laboratory-confirmed influenza infection) because the date of symptom onset was generally not available and the date of infection could not be determined. We defined the observation period as the interval from 1 year before to 1 year after the index date, and we included in our analyses patients who had at least one admission for acute myocardial infarction during this period. The observation time was truncated in this manner to minimize time-varying confounding, since the self-controlled case-series design does not control for time-varying confounding.

In the primary analysis, we defined the “risk interval” as the first 7 days after the index date and the “control interval” as all other times during the observation period (i.e., 52 weeks before the index date and 51 weeks after the end of the risk interval) (Figure 1). There is often a lag between influenza infection, symptom onset, and subsequent laboratory testing for influenza.23 Therefore, we excluded cases of acute myocardial infarction if the positive influenza specimen was obtained during the admission for acute myocardial infarction because we could not determine the temporal relationship between the influenza exposure and the cardiac outcome.

We estimated the incidence ratio for hospitalizations for acute myocardial infarction during the risk interval as compared with the control interval with the use of a fixed-effects conditional Poisson regression model. The model accounted for multiple influenza exposures and hospitalization episodes for acute myocardial infarction per patient during the observation period.24 In addition to the primary analysis that defined the risk interval as days 1 through 7 after the index date, we also considered narrower risk intervals (days 1 through 3 and days 4 through 7) and alternative risk intervals (days 8 through 14 and days 15 through 28).

To test the robustness of our findings, we conducted a number of sensitivity analyses. These included analyses that controlled for calendar month; that limited the control interval to the postexposure observation time, to the preexposure observation time, or to the 2 months before and after influenza diagnosis; that included patients for whom the specimen was obtained during the admission for acute myocardial infarction; and that applied induction intervals of varying lengths. An induction interval is a portion of the observation time immediately preceding the index date that is excluded from the control interval.25 To examine the specificity of our findings, we repeated the analyses with data on exposures other than influenza. These included a positive test result for RSV, a positive test result for respiratory viruses other than influenza or RSV, and an illness for which no respiratory virus was identified. The last group included cases of infection with nonviral agents, viral infections that had already cleared in the patient, infection with viruses that were not tested for, and false negative samples. We also examined the association between influenza infection and hospitalizations for diabetes and associated complications (ICD-10 codes E10, E11, E13, and E14), an outcome for which no significant association was anticipated.

We performed analyses in subgroups defined according to age (≤65 years vs. >65 years), sex, influenza type (A [all subtypes] vs. B), influenza A subtype (H1N1 vs. H3N2), influenza vaccination status, history of hospitalization for acute myocardial infarction before the study period (yes vs. no), and laboratory testing method (PCR vs. only non-PCR methods). We evaluated the presence of interactions in these subgroups.

All statistical tests were two-tailed, and P values of less than 0.05 were considered to indicate statistical significance. Analyses were performed with SAS software, version 9.4 (SAS Institute).