Literature DB >> 32585019

Association of Azithromycin Use With Cardiovascular Mortality.

Jonathan G Zaroff1, T Craig Cheetham2, Niki Palmetto3, Lucy Almers1, Charles Quesenberry1, Jennifer Schneider1, Nicolle Gatto3, Douglas A Corley1.   

Abstract

Importance: Azithromycin is one of the most commonly prescribed antibiotics in the US. It has been associated with an increased risk of cardiovascular death in some observational studies. Objective: To estimate the relative and absolute risks of cardiovascular and sudden cardiac death after an outpatient azithromycin prescription compared with amoxicillin, an antibiotic not known to increase cardiovascular events. Design, Setting, and Participants: This retrospective cohort study included 2 large, diverse, community-based integrated care delivery systems with comprehensive capture of encounters and prescriptions from January 1, 1998, to December 31, 2014. The cohort included patients aged 30 to 74 years who had at least 12 months of health-plan enrollment prior to antibiotic exposure. The exclusion criteria were absence of prescription benefits, prescription for more than 1 type of study antibiotic within 10 days, hospitalization or nursing home residence, and serious medical conditions. Risk of cardiovascular death associated with azithromycin vs amoxicillin exposure was calculated after controlling for confounding factors using a propensity score. Data were analyzed from December 1, 2016, to March 30, 2020. Exposures: Outpatient prescription of azithromycin or amoxicillin. Main Outcomes and Measures: The primary outcomes were cardiovascular death and sudden cardiac death. An a priori subgroup analysis quantified the effects of azithromycin exposure among patients with increased baseline cardiovascular risk. The secondary outcomes were noncardiovascular death and all-cause mortality.
Results: The study included 7 824 681 antibiotic exposures, including 1 736 976 azithromycin exposures (22.2%) and 6 087 705 amoxicillin exposures (77.8%), among 2 929 008 unique individuals (mean [SD] age, 50.7 [12.3] years; 1 810 127 [61.8%] women). Azithromycin was associated with a significantly increased hazard of cardiovascular death (hazard ratio [HR], 1.82; 95% CI, 1.23-2.67) but not sudden cardiac death (HR, 1.59; 95% CI, 0.90-2.81) within 5 days of exposure. No increases in risk were found 6 to 10 days after exposure. Similar results were observed in patients within the top decile of cardiovascular risk (HR, 1.71; 95% CI, 1.06-2.76). Azithromycin was also associated with an increased risk of noncardiovascular death (HR, 2.17; 95% CI, 1.44-3.26) and all-cause mortality (HR, 2.00; 95% CI, 1.51-2.63) within 5 days of exposure. Conclusions and Relevance: These findings suggest that outpatient azithromycin use was associated with an increased risk of cardiovascular death and noncardiovascular death. Causality cannot be established, particularly for noncardiovascular death, owing to the likelihood of residual confounding.

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Year:  2020        PMID: 32585019      PMCID: PMC7301226          DOI: 10.1001/jamanetworkopen.2020.8199

Source DB:  PubMed          Journal:  JAMA Netw Open        ISSN: 2574-3805


Introduction

Azithromycin, a macrolide, is one of the most commonly prescribed antibiotics in the US, with an estimated 44.9 million prescriptions dispensed to outpatients in 2016.[1] A safety concern was raised following a study by Ray et al in 2012[2] that reported an association of azithromycin use with sudden cardiac death. Prompted by concern over QT prolongation and reports of cardiac deaths, the US Food and Drug Administration made changes to the product labeling between 2011 and 2013 advising against using azithromycin in patients with known risk factors for ventricular arrhythmia.[3] Epidemiological studies[4,5,6,7,8,9] subsequent to Ray et al[2] have produced conflicting results regarding an association between azithromycin and cardiac events. Of 6 epidemiological studies subsequently published, 3 reported an increased risk of cardiovascular deaths, serious cardiac arrhythmias, or myocardial infarction,[5,8,9] and 3 reported no such associations.[4,6,7] The conflicting results reported may, in part, be due to differences in the study populations, outcome measures, methods of confounding control, exposure risk periods, and statistical methods. In particular, studies have been limited in their ability to control for key confounders, such as indication for use. In 2014, the Food and Drug Administration and the Pharmacovigilance Risk Assessment Committee requested the manufacturer of azithromycin conduct additional epidemiological investigations to evaluate the association of azithromycin use with cardiovascular mortality. The primary objectives of this study were to estimate the relative and absolute risks of cardiovascular death and sudden cardiac death within 5 days and within 6 to 10 days of a dispensed azithromycin prescription among individuals aged 30 to 74 years.

Methods

This study was approved by the institutional review board at Kaiser Permanente, which waived the requirement for individual written informed consent because data were deidentified and there was no patient contact. This study is reported following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.

Study Design and Population

This retrospective cohort study was designed to examine the risk of cardiovascular death and sudden cardiac death associated with azithromycin use compared with amoxicillin use in a general member population of Kaiser Permanente California. To account for potential confounding by indication (ie, need for an antibiotic), we used amoxicillin use as a relevant comparison group. Kaiser Permanente California consists of 2 regions, Northern California and Southern California, with a combined membership of more than 8.2 million individuals. The demographic profile of the Kaiser Permanente California membership is racially, ethnically, and socioeconomically diverse and closely resembles the underlying populations of Northern and Southern California.[10,11] Kaiser Permanente is an integrated health care delivery system, and members receive almost all their care through Kaiser Permanente facilities, which include hospitals, outpatient medical offices, laboratory centers, and pharmacies. Data generated from patient encounters within the health care system are available for research purposes; information on care received at outside facilities are captured through a claims system.

Cohort Definition

Cohort inclusion criteria were an outpatient prescription for azithromycin or amoxicillin, including amoxicillin-clavulanate, between January 1, 1998, and December 31, 2013, for Southern California and December 31, 2014, for Northern California; age 30 to 74 years on the index date (ie, prescription dispense date); and health plan enrollment with prescription benefit coverage for at least 12 months prior to the index date (allowing up to 60-day gaps in membership). Exclusion criteria were lack of prescription benefit coverage on the index date, receipt of more than 1 type of study antibiotic (azithromycin or amoxicillin) on the index date or within 10 days prior to the index date, hospitalization during the 30 days prior to the index date, or residence for more than 30 days in a nursing home in the 365 days prior to the index date. To reduce potential confounding, patients with serious underlying medical conditions prior to the index date were also excluded. Examples of these conditions include a diagnosis of cancer within 3 years prior to index or HIV at any time prior to index (eTable 1 in the Supplement).[2]

Exposure Definitions

The exposures of interest were outpatient dispensed prescriptions for oral azithromycin or amoxicillin (with or without clavulanate). Topical and injectable preparations for these products were excluded from the analysis. Amoxicillin was chosen as the comparator antibiotic because its infectious disease indications are similar to those of azithromycin, and amoxicillin is not associated with cardiovascular death. Patients with more than 1 course of antibiotics during the study period could be entered into the cohort again if they met the inclusion and exclusion criteria; therefore, the level of analysis was set at the individual prescription.

Outcome Definitions

The primary outcomes were cardiovascular death and sudden cardiac death. Since a hypothesized mechanism of harm is potential increased risk of cardiac arrhythmia during therapy and the typical duration of use for azithromycin and amoxicillin is between 7 to 10 days, the analysis was restricted to exposure windows of 0 to 5 and 6 to 10 days after the index (prescription) date. Follow-up was censored if the patient was admitted to the hospital during the 10-day exposure window, as inpatient medications, procedures, and diagnoses may not be comprehensively captured from the inpatient setting. A cardiovascular death was defined as death with an underlying cardiovascular cause (eg, myocardial infarction, heart failure, arrhythmia, stroke); sudden cardiac deaths were analyzed as a subgroup of cardiovascular death. Secondary outcomes were all-cause death and noncardiovascular death. Deaths were identified using International Classification of Diseases, Ninth Revision (ICD-9)[12] and Tenth Revision (ICD-10)[13] codes from state death certificates (using underlying cause of death) except for sudden cardiac death, which used a validated algorithm based on state death certificates, radiology codes, thrombolytic drug use, and anesthesia codes (eTable 4 in the Supplement).[14] To assess the validity of death outcome coding, cardiovascular deaths with available charts were abstracted, reviewed, and adjudicated by a panel of cardiologists. Adjudicated cardiovascular deaths were further categorized as sudden cardiac death or death due to other cardiac causes. A random sample of noncardiovascular deaths was also adjudicated to quantify the rate of false negative cardiovascular deaths (ie, miscoding of true cardiovascular deaths as noncardiovascular deaths).

Confounding and Effect Modification

Covariates included demographic information, health plan benefit data, and clinical characteristics, including indication of use, based on coded diagnoses and dispensed pharmacy prescriptions. A complete listing of variables is presented in the eAppendix in the Supplement. Given the large number of potential confounders and relatively low outcome frequencies, propensity scores were used for confounder control. Propensity scores were developed using a logistic regression model without reference to or linkage between exposures and study outcomes of interest. Variables for inclusion in the propensity score model were determined a priori and included covariates hypothesized to be associated with exposures and study outcomes and not considered mediators of the potential outcomes of interest. Variable definitions and methods, including diagnostics, are included in eTables 10-12 in the Supplement. Two methods were used to identify the indication of use for each antibiotic exposure. Beginning in 2008, medications prescribed within the electronic medical record were directly linked to a single diagnosis code, allowing for direct capture of indication of use. For prescriptions written prior to 2008, recent medical visit diagnostic codes were temporally linked to the antibiotic prescriptions, allowing for an indirect ascertainment of indication of use (similar to the method used by Ray et al[2]) (eTable 2 in the Supplement). Prophylactic antibiotic prescriptions were considered as 2 separate categories. The term immediate prophylaxis describes a prescription that was to be started immediately to prevent an infection from developing (eg, the routine use of antibiotics before or after an elective surgical procedure). Delayed prophylaxis describes a prescription that is to be started at an unknown future date (eg, azithromycin for traveler’s diarrhea or amoxicillin for dental prophylaxis) (eAppendix in the Supplement).

Statistical Analysis

Descriptive comparisons were made between the azithromycin and amoxicillin cohorts for all of the baseline covariates collected during 12 months prior to the index date using t tests and χ2 tests. Cox regression models were used for point and interval estimations of study outcome hazard ratios (HRs) associated with azithromycin vs amoxicillin in each time interval of interest adjusted for potential confounders. The propensity score was included in all regression models as a categorical covariate, expressed in deciles. In addition, age and sex were a priori included as model covariates, given their strong associations with study outcomes. A robust sandwich variance estimator for the Cox regression model was used to account for the effects of multiple exposures per patient. Unadjusted cumulative incidences for days 0 to 5 and 6 to 10 were calculated by means of the product limit estimator. Using the same approach as Ray et al,[2] covariate-adjusted estimates of the difference in risk between azithromycin and amoxicillin for time intervals of interest were calculated as (HR – 1) × I, in which HR is the adjusted HR for azithromycin vs amoxicillin and I is the unadjusted cumulative incidence among patients prescribed amoxicillin. Primary analyses used the exposures, outcomes, and methods for confounder adjustment as previously described. Secondary analyses examined the risk of cardiovascular death among individuals with high baseline cardiovascular risk, defined as a history of baseline cardiovascular disease or patients in the top decile of a cardiovascular risk score. Individuals with baseline cardiovascular disease were defined using inpatient or outpatient encounters with a diagnostic code for cardiovascular diseases (eTable 5 in the Supplement). High baseline cardiovascular risk was defined by generating a cardiovascular risk score, using an approach similar to that of Ray and colleagues (eTable 5 and eTable 6 in the Supplement).[2,14,15] The cardiovascular risk score variables included cardiovascular diseases, cardiovascular medications, and smoking (eTables 7-9 in the Supplement). A sensitivity analysis was conducted that included only prescriptions associated with an infection indication of use, excluding prescriptions with prophylactic (eg, prophylaxis against endocarditis during dental procedures) or missing indications. Additional sensitivity analyses were conducted that added individual variables not adequately balanced between groups within the propensity score to the cardiovascular and noncardiovascular death models (eAppendix in the Supplement). Subgroup analyses were also performed that excluded prescription records with specific pulmonary disease variables, which were imbalanced according to antibiotic exposure. All analyses were conducted using SAS statistical software version 9.4 (SAS Institute). P values were 2-sided, and statistical significance was set at .05. Data were analyzed from December 1, 2016, to March 30, 2020.

Results

This cohort study included 7 824 681 antibiotic exposures, including 1 736 976 azithromycin exposures (22.2%) and 6 087 705 amoxicillin exposures, among 2 929 008 unique individuals (mean [SD] age, 50.7 [12.3] years; 1 810 127 [61.8%] women). Among individual patients, 1 341 489 patients (45.8%) received only 1 study prescription, 622 346 patients (21.3%) received 2 prescriptions, and 964 713 patients (32.9%) received 3 or more prescriptions. The demographic and baseline clinical characteristics of the study population are presented in Table 1. Azithromycin exposures were dispensed more frequently during the latter part of the study period, with a mean (SD) of 2008.3 (4.4) calendar years, vs 2005.5 (4.8) calendar years for amoxicillin prescriptions. Patients receiving azithromycin prescriptions, compared with those receiving amoxicillin, had higher rates of pneumonia (242 875 patients [14.0%] vs 213 275 patients [3.5%]; P < .001), chronic obstructive pulmonary disease (356 871 patients [20.6%] vs 478 768 patients [7.9%]; P < .001), asthma (392 895 patients [22.6%] vs 635 138 patients [10.4%]; P < .001), and β-agonist use (706 244 patients [40.7%] vs 1 211 125 patients [19.9%]; P < .001) in the year prior to prescription. In addition, patients exposed to azithromycin, compared with patients exposed to amoxicillin, were more likely to receive cardioprotective medications, including angiotensin-converting enzyme inhibitors (304 134 patients [17.5%] vs 894 732 patients [14.7%]; P < .001), angiotensin receptor blockers (100 208 patients [5.8%] vs 205 390 patients [3.4%]; P < .001), statins (432 033 patients [24.9%] vs 1 194 075 patients [19.6%]; P < .001), and β-blockers (265 818 patients [15.3%] vs 839 572 patients [13.8%]; P < .001) and were more likely to have had a noncardiovascular-related emergency department encounter within 30 days prior to study antibiotic exposure (92 976 patients [5.4%] vs 125 647 patients [2.1%]; P < .001). Azithromycin was dispensed more frequently for an indication of pulmonary infections, whereas amoxicillin was dispensed more frequently for ear, nose, and throat infections. Indication of use data were missing for 2 155 048 amoxicillin prescriptions (35.4%) and 248 388 azithromycin prescriptions (14.3%) (eTable 3 in the Supplement). A total of 197 379 azithromycin prescriptions (11.4%) and 571 728 amoxicillin prescriptions (9.4%) were dispensed to individuals with a history of cardiovascular disease; 139 290 azithromycin prescriptions (8.0%) and 574 234 amoxicillin prescriptions (9.4%) were dispensed to patients in the top decile of the cardiovascular risk score.
Table 1.

Demographic and Clinical Characteristics of the Study Population

CharacteristicNo. (%)P valuea
Azithromycin (n = 1 736 976)Amoxicillin (n = 6 087 705)
Age, mean (SD), y51.7 (12.0)50.4 (11.7)<.001
Prescriptions, No. (% of total)
KP Northern California1 093 980 (63.0)2 856 689 (46.9)<.001
KP Southern California642 996 (37.0)3 231 016 (53.1)<.001
Women1 104 417 (63.6)3 733 583 (61.3)<.001
Calendar year of prescriptions, mean (SD)2008.3 (4.4)2005.5 (4.8)<.001
Race/ethnicity
Hispanic339 685 (19.6)1 393 493 (22.9)<.001
Black147 448 (8.5)602 716 (9.9)
Hawaiian or Pacific Islander15 688 (0.9)47 693 (0.8)
Asian222 723 (12.8)603 639 (9.9)
Native American7865 (0.5)22 691 (0.4)
White915 575 (52.7)2 978 294 (48.9)
Missing or other87 992 (5.1)439 179 (7.2)
Dose
Azithromycin
250 mg (2 tabs typically taken on the 1st day)1 686 423 (97.1)NANA
500 mg43 181 (2.5)NA
Other7372 (0.4)NA
Amoxicillin
Trihydrate 500 mgNA4 912 019 (80.7)NA
Amoxicillin-clavulanate 875-125 mgNA750 312 (12.3)
Trihydrate, 250 mgNA231 917 (3.8)
Clavulanate, 500-125 mgNA182 254 (3.0)
OtherNA11 203 (0.2)
Supply, d
Mean (SD)5.0 (5.8)9.9 (5.8)<.001
<357 639 (3.3)NANA
3711 700 (41.0)NA
4-5712 138 (41.0)NA
<7NA534 020 (8.8)
7NA1 061 860 (17.4)
6-10217 816 (12.5)NA
8-10NA3 851 110 (63.3)
>1037 683 (2.2)NA
11-14NA345 265 (5.7)
>14NA295 450 (4.9)
Current or 1-y past use of medications
ACE inhibitor304 134 (17.5)894 732 (14.7)<.001
Angiotensin receptor blocker100 208 (5.8)205 390 (3.4)<.001
Anticoagulant50 679 (2.9)200 079 (3.3)<.001
Antiarrhythmic14 414 (0.8)60 286 (1.0)<.001
β-agonist706 244 (40.7)1 211 125 (19.9)<.001
β-blocker265 818 (15.3)839, 572 (13.8)<.001
Calcium-channel blocker157 840 (9.1)443 543 (7.3)<.001
Digoxin11 171 (0.6)59 383 (1.0)<.001
Insulin61 473 (3.5)161 260 (2.7)<.001
Loop diuretic58 889 (3.4)141 423 (2.3)<.001
Other diuretic303 124 (17.5)874 343 (14.4)<.001
Nitrate60 212 (3.5)184 332 (3.0)<.001
Oral hypoglycemic176 914 (10.2)514 486 (8.5)<.001
Platelet inhibitor21 064 (1.2)56 372 (0.9)<.001
Statin432 033 (24.9)1 194 075 (19.6)<.001
Systemic glucocorticoid421 811 (24.3)869 807 (14.3)<.001
Cardiovascular comorbidity
Arrhythmia53 459 (3.1)170 411 (2.8)<.001
Cardiac valve disease16 790 (1.0)86 979 (1.4)<.001
Myocardial infarction30 149 (1.7)83 613 (1.4)<.001
Cardiac revascularization6768 (0.4)25 879 (0.4)<.001
Other coronary heart disease61 410 (3.5)179 895 (3.0)<.001
Heart failure27 686 (1.6)76 906 (1.3)<.001
Peripheral vascular disease68 682 (4.0)160 425 (2.6)<.001
Stroke4186 (0.2)10 562 (0.2)<.001
TIA8812 (0.5)25 773 (0.4)<.001
Noncardiovascular comorbidity
Asthma392 895 (22.6)635 138 (10.4)<.001
Chronic obstructive pulmonary disease356 871 (20.6)478 768 (7.9)<.001
Prior pneumonia242 875 (14.0)213 275 (3.5)<.001
Diabetes233 531 (13.4)691 758 (11.4)<.001
Complications of diabetes100 425 (5.8)255 582 (4.2)<.001
Smoking736 700 (42.4)2 163 908 (35.6)<.001
Renal disease63 643 (3.7)134 488 (2.2)<.001
Incontinence of urine or feces58 791 (3.4)145 508 (2.4)<.001
Use of wheelchair or walker1613 (0.1)4272 (0.1)<.001
Health care utilization<.001
ED visit for cardiovascular disease
Within 31-365 d17 204 (1.0)54 422 (0.9)<.001
Within 30 d2408 (0.1)4866 (0.1)<.001
ED visit for noncardiovascular disease
Within 31-365 d263 682 (15.2)730 229 (12.0)<.001
Within 30 d92 976 (5.4)125 647 (2.1)<.001
Cardiovascular disease hospitalization
Within 91-365 d7801 (0.5)30 776 (0.5)<.001
Within 30-90 d1703 (0.1)6715 (0.1)<.001
Noncardiovascular disease hospitalization within 365 d51 497 (3.0)202 146 (3.3)<.001
Use of a study antibiotic within the past 30 d72 486 (4.2)281 661 (4.6)<.001
Use of any other antibiotic within the past 30 d118 005 (6.8)259 457 (4.3)<.001
Cardiovascular risk score
Mean (SD)8.78 (5.97)9.45 (5.64)<.001
Median (IQR)9 (3-14)9 (5-14)

Abbreviations: ACE, angeiotensin-conveting enzyme; ED, emergency department; IQR, interquartile range; KP, Kaiser Permanente; NA, not applicable; TIA, transient ischemic attack.

Comparisons made using t tests and χ2 tests.

Abbreviations: ACE, angeiotensin-conveting enzyme; ED, emergency department; IQR, interquartile range; KP, Kaiser Permanente; NA, not applicable; TIA, transient ischemic attack. Comparisons made using t tests and χ2 tests. A total of 485 deaths occurred within 10 days of a study antibiotic index date. Of these deaths, 256 (52.8%) were cardiovascular deaths. Among cardiovascular deaths, 112 (44%) were classified as sudden cardiac deaths. For those with available records, most (82 deaths [89.0%]) were confirmed as cardiovascular deaths after medical review. There were 229 noncardiovascular deaths during the 10-day follow-up period; the most commonly coded causes of death were lung disease (42 deaths [18.3%]), infection (34 deaths [14.8%]), cancer (37 deaths [16.2%]), and diabetes (28 deaths [12.2%]).

Primary and Secondary Analyses

Compared with amoxicillin, patients receiving azithromycin were at significantly higher risk of cardiovascular death (HR, 1.82; 95% CI, 1.23-2.67) but not sudden cardiac death (HR, 1.59; 95% CI, 0.90-2.81) within 5 days of the index date (Table 2). The results were not significant within 6 to 10 days after the index date. The adjusted risk difference for cardiovascular death for azithromycin within 5 days of the index date was 12.79 (95% CI, 3.66-26.21) per 1 000 000 prescriptions. There was an increased risk of cardiovascular death within 5 days for those in the top decile of the cardiovascular risk score (HR, 1.71; 95% CI, 1.06-2.76) (Table 3). Azithromycin was also associated with an increased hazard of all-cause death within 5 days (HR, 2.17; 95% CI, 1.44-3.26) and noncardiovascular death within 5 days (HR, 2.00; 95% CI, 1.51-2.63) but not 6-10 days after exposure (Table 4).
Table 2.

Cardiovascular Death and Sudden Cardiac Death After Azithromycin and Amoxicillin Exposure

MortalityAzithromycin (n = 1 736 976)Amoxicillin (n = 6 087 705)Adjusted
Deaths, No.Cumulative incidenceaDeaths, No.Cumulative incidenceaRisk difference (95% CI)a,bHazard ratio (95% CI)b
Cardiovascular, d
0-56235.919515.6812.79 (3.66 to 26.21)1.82 (1.23 to 2.67)
6-103118.346811.413.15 (−2.31 to 11.91)1.28 (0.80 to 2.04)
Sudden cardiac, d
0-5 2112.17396.443.83 (−0.63 to 11.70)1.59 (0.90 to 2.81)
6-10169.47366.044.04 (−3.82 to 19.04)1.32 (0.69 to 2.52)

Per 1 000 000 prescriptions.

Adjusted for propensity score decile, age, and sex.

Table 3.

Cardiovascular Death in High Cardiovascular Risk Subgroups After Azithromycin and Amoxicillin Exposure

SubgroupAzithromycinAmoxicillinAdjustedb
No.Cumulative IncidenceaNo.Cumulative incidenceaRisk difference (95% CI)Hazard ratio (95% CI)
PrescriptionsDeathsPrescriptionsDeaths
Prior CV disease197 37947NA571 72881NANANA
0-5 dNA30153.13NA5088.0151.47 (−8.73 to 157.40)1.58 (0.90 to 2.79)
6-10 dNA1789.57NA3155.8225.69 (−14.10 to 103.43)1.46 (0.75 to 2.85)
Top decile CVRS139 29057NA574 234120NANANA
0-5 dNA37268.33NA69120.9185.48 (6.80 to 212.66)1.71 (1.06 to 2.76)
6-10 dNA20149.83NA5191.2024.00 (−25.79 to 111.68)1.26 (0.72 to 2.22)

Abbreviations: CV, cardiovascular; CVRS, cardiovascular risk score; NA, not applicable.

Per 1 000 000 prescriptions.

Adjusted for propensity score decile, age, and sex.

Table 4.

Noncardiovascular Death and All-Cause Death After Azithromycin and Amoxicillin Exposure

MortalityAzithromycin (n = 1 736 976)Amoxicillin (n = 6 087 705)Adjusted
Deaths, No.Cumulative incidenceaDeaths, No.Cumulative incidenceaRisk difference (95% CI)a,bHazard ratio (95% CI)b
Noncardiovascular, d
0-5 d8348.066811.2213.13 (4.99-25.37)2.17 (1.44-3.26)
6-10 d3520.71437.223.29 (-0.89-10.21)1.46 (0.88-2.41)
All-cause, d
0-5 d14583.9716326.9026.77 (13.74-43.97)2.00 (1.51-2.63)
6-10 d6639.0511118.636.37 (-0.89-16.59)1.34 (0.95-1.89)

Per 1 000 000 prescriptions.

Adjusted for propensity score decile, age, and sex.

Per 1 000 000 prescriptions. Adjusted for propensity score decile, age, and sex. Abbreviations: CV, cardiovascular; CVRS, cardiovascular risk score; NA, not applicable. Per 1 000 000 prescriptions. Adjusted for propensity score decile, age, and sex. Per 1 000 000 prescriptions. Adjusted for propensity score decile, age, and sex.

Sensitivity Analyses

Among prescriptions with a coded infection indication of use, the results were similar to those observed in the primary analysis within 5 days of exposure (HR for cardiovascular death, 1.62; 95% CI, 1.06-2.49; adjusted risk difference, 10.21; 95% CI, 0.92-24.49). The addition of individual variables not adequately balanced between groups within the propensity score to the model did not substantially change the HR point estimates for cardiovascular or noncardiovascular death (eAppendix in the Supplement). The exclusion of records with specific pulmonary disease variables (eg, asthma, chronic obstructive pulmonary disease, history of pneumonia, β-agonist use, glucocorticoid use, smoking) also did not substantially change the point estimates for cardiovascular death. While there were some statistically significant interactions between these variables and noncardiovascular death, the direction of the associations did not change.

Discussion

In this cohort study of more than 7.8 million antibiotic exposures, there was a statistically significantly increased relative risk and absolute risk of cardiovascular death associated with azithromycin exposure compared with amoxicillin within 5 days of index date but not within 6 to 10 days after index date. This study also found an increased risk of noncardiovascular and all-cause death within 5 days of exposure among individuals prescribed azithromycin. While the risk of cardiovascular death is consistent with proposed mechanisms, an increased risk of noncardiovascular mortality is not. Reports of an association of erythromycin, one of the first macrolide antibiotics, with QT interval prolongation and cardiac arrhythmias first appeared more than 20 years ago.[16,17,18,19] Subsequently, cardiac arrhythmias have been reported for clarithromycin and azithromycin, and macrolide antibiotics, as a class, are now known to cause QT prolongation in some at-risk populations.[20] In most of the case reports of macrolide antibiotic use and cardiac arrhythmias, patients had other factors that put them at an increased risk for cardiac arrhythmias, including underlying cardiac disease (ie, bradycardia, congestive heart failure, baseline QT prolongation, cardiomyopathy, atrial fibrillation, and myocardial ischemia), metabolic anomalies that increase the risk of arrhythmia (ie, hypokalemia, hypocalcemia, hypomagnesemia, and hypoxia), or concomitant use of other medications known to prolong the QT interval.[21] Our observed association of azithromycin with cardiovascular death is similar to that reported by Ray et al[2] in a Tennessee Medicaid population but differs from the findings reported by Svanstrom et al[4] in a Danish general population sample. When examining the findings across these studies, it is important to note key differences between populations. The incidence of cardiovascular death at Kaiser Permanente was 35.9 deaths per 1 000 000 azithromycin exposures, which was lower than the incidence found by Ray et al (85.2 deaths per 1 000 000 azithromycin exposures)[2] yet higher than the incidence found by Svanstrom et al (15.4 deaths per 1 000 000 azithromycin exposures).[4] These differences may largely be explained by baseline differences in population characteristics, although there also may have been differences in detection and classification of cardiovascular deaths.

Limitations and Strengths

Several limitations need to be considered when evaluating the results of this observational study. Although several strategies were used to decrease the potential for confounding by indication of use, severity of infection, and underlying comorbidities, there is the potential for residual confounding. First, although indication of use was included in the propensity score, full control of this confounder was not possible because 31% of the records had a missing indication of use; however, a sensitivity analysis restricted to patients with an infection indication produced similar results to the primary analysis. Second, varying disease severity within the specific indication for antibiotic use may be associated with both choice of antibiotic and risk of cardiovascular death. To mitigate the potential for confounding by unmeasured infection severity, this study only included outpatient prescriptions; patients with severe infections are generally hospitalized. Third, comorbid conditions may be important if patients with other comorbid diseases are more likely to receive azithromycin, even for the same antibiotic indication, and to have an increased risk of cardiovascular or noncardiovascular death.[22] Consistent with this, azithromycin was associated with an increased risk for noncardiovascular mortality from causes unlikely to be related to recent antibiotic exposures, such as lung disease and cancer. However, additional sensitivity analyses that added individual variables not adequately balanced between groups within the propensity score to the model did not change the HR point estimates for cardiovascular or noncardiovascular death. Serious underlying illnesses and all clinical characteristics captured in the propensity score were assessed in the 12 months prior to the index date. Underlying health status within the prior year is likely correlated with but may not fully reflect the health of the person at the time of the infection. Fourth, temporal changes may influence disease risk and prescribing patterns. During the time period for this study (1998-2014), there was a significant decline in the rate of cardiovascular events within the study population[23] and increased use of azithromycin. The influence of this was addressed by including prescription year within the propensity score. Fifth, misclassification of study outcomes (ie, cardiovascular vs noncardiovascular death) is possible given the potential for errors in the ICD codes used to define the outcomes. However, adjudication of the cardiovascular deaths showed a high confirmation rate for coded cardiovascular deaths. This study also has many strengths, including its large sample of patients prescribed antibiotics; detailed pharmacy data that included date, dose, duration, and indication of use (beginning in 2008); high-quality electronic data; availability of written records for manual validation; a diverse community-based population that is comparable to the region’s underlying census distribution by multiple demographic factors; and the extensive efforts that were made to address confounding. The adjudication process was also able to provide a degree of reassurance about the validity of the coded outcomes.

Conclusions

This cohort study found an approximately 2-fold increased risk of cardiovascular death and noncardiovascular death after outpatient azithromycin use compared with use of amoxicillin within a 5-day window after dispensing. Although these analyses cannot establish causality, prescribers should be aware of this potential association.
  20 in total

Review 1.  Concomitant risk factors in reports of torsades de pointes associated with macrolide use: review of the United States Food and Drug Administration Adverse Event Reporting System.

Authors:  Douglas Shaffer; Sarah Singer; Joyce Korvick; Peter Honig
Journal:  Clin Infect Dis       Date:  2002-06-19       Impact factor: 9.079

2.  Azithromycin and the risk of cardiovascular death.

Authors:  Wayne A Ray; Katherine T Murray; Kathi Hall; Patrick G Arbogast; C Michael Stein
Journal:  N Engl J Med       Date:  2012-05-17       Impact factor: 91.245

3.  Long Q-T syndrome associated with oral erythromycin used in preoperative bowel preparation.

Authors:  A W Vogt; R A Zollo
Journal:  Anesth Analg       Date:  1997-11       Impact factor: 5.108

4.  Azithromycin and levofloxacin use and increased risk of cardiac arrhythmia and death.

Authors:  Gowtham A Rao; Joshua R Mann; Azza Shoaibi; Charles Lee Bennett; Georges Nahhas; S Scott Sutton; Sony Jacob; Scott M Strayer
Journal:  Ann Fam Med       Date:  2014 Mar-Apr       Impact factor: 5.166

5.  ADHD drugs and serious cardiovascular events in children and young adults.

Authors:  William O Cooper; Laurel A Habel; Colin M Sox; K Arnold Chan; Patrick G Arbogast; T Craig Cheetham; Katherine T Murray; Virginia P Quinn; C Michael Stein; S Todd Callahan; Bruce H Fireman; Frank A Fish; Howard S Kirshner; Anne O'Duffy; Frederick A Connell; Wayne A Ray
Journal:  N Engl J Med       Date:  2011-11-01       Impact factor: 91.245

Review 6.  QT-interval prolongation by non-cardiac drugs: lessons to be learned from recent experience.

Authors:  F De Ponti; E Poluzzi; N Montanaro
Journal:  Eur J Clin Pharmacol       Date:  2000-04       Impact factor: 2.953

7.  Oral erythromycin and the risk of sudden death from cardiac causes.

Authors:  Wayne A Ray; Katherine T Murray; Sarah Meredith; Sukumar Suguna Narasimhulu; Kathi Hall; C Michael Stein
Journal:  N Engl J Med       Date:  2004-09-09       Impact factor: 91.245

8.  Cardiac actions of erythromycin: influence of female sex.

Authors:  M D Drici; B C Knollmann; W X Wang; R L Woosley
Journal:  JAMA       Date:  1998-11-25       Impact factor: 56.272

Review 9.  Macrolide antibiotics and the risk of cardiac arrhythmias.

Authors:  Richard K Albert; Joseph L Schuller
Journal:  Am J Respir Crit Care Med       Date:  2014-05-15       Impact factor: 21.405

10.  Sociodemographic characteristics of members of a large, integrated health care system: comparison with US Census Bureau data.

Authors:  Corinna Koebnick; Annette M Langer-Gould; Michael K Gould; Chun R Chao; Rajan L Iyer; Ning Smith; Wansu Chen; Steven J Jacobsen
Journal:  Perm J       Date:  2012
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  7 in total

1.  Antibiotics for secondary prevention of coronary heart disease.

Authors:  Naqash J Sethi; Sanam Safi; Steven Kwasi Korang; Asbjørn Hróbjartsson; Maria Skoog; Christian Gluud; Janus C Jakobsen
Journal:  Cochrane Database Syst Rev       Date:  2021-02-23

2.  Using Medicare Data to Assess the Proarrhythmic Risk of Non-Cardiac Treatment Drugs that Prolong the QT Interval in Older Adults: An Observational Cohort Study.

Authors:  Kin Wah Fung; Fitsum Baye; Joan Kapusnik-Uner; Clement J McDonald
Journal:  Drugs Real World Outcomes       Date:  2021-02-10

3.  Error in Results Section.

Authors: 
Journal:  JAMA Netw Open       Date:  2020-12-01

4.  Sub-growth-inhibitory concentrations of omadacycline inhibit Staphylococcus aureus haemolytic activity in vitro.

Authors:  Alisa W Serio; S Ken Tanaka; Kelly Wright; Lynne Garrity-Ryan
Journal:  JAC Antimicrob Resist       Date:  2021-12-22

5.  Comparative safety of inhaled corticosteroids and macrolides in Medicare enrolees with bronchiectasis.

Authors:  Emily Henkle; Charles L Daley; Jeffrey R Curtis; Benjamin Chan; Timothy R Aksamit; Kevin L Winthrop
Journal:  ERJ Open Res       Date:  2022-03-07

6.  Optimizing Nanopore Sequencing for Rapid Detection of Microbial Species and Antimicrobial Resistance in Patients at Risk of Surgical Site Infections.

Authors:  Emma Whittle; Jennifer A Yonkus; Patricio Jeraldo; Roberto Alva-Ruiz; Heidi Nelson; Michael L Kendrick; Thomas E Grys; Robin Patel; Mark J Truty; Nicholas Chia
Journal:  mSphere       Date:  2022-02-16       Impact factor: 4.389

7.  Effects of azithromycin on ventricular repolarization in children with COVID-19.

Authors:  Suleyman Sunkak; Mustafa Argun; Binnaz Celik; Onur Tasci; Agah Bahadir Ozturk; Dogan Bahadir Inan; Murat Dogan
Journal:  Rev Port Cardiol       Date:  2022-02-21       Impact factor: 1.651

  7 in total

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