Atrial fibrillation (AF) occurs in 16–30% of patients after cardiac and thoracic surgery [
This SRMA was conducted with a predesigned protocol (Supplementary File
We included studies which reported on perioperative AF in adult patients (>18 years), along with a control group, after noncardiothoracic surgery. Perioperative AF is defined as that identified in the intraoperative/postoperative period, as a single occurrence on electrocardiogram (ECG) or a series of recordings on a 24-h ECG, with an onset within 30 days of the surgery. We did not have a fixed ECG definition for the AF, which could be symptomatic or asymptomatic and paroxysmal or persistent. We excluded case series, case reports, and any study without explicit and exclusive reporting of perioperative AF. We also excluded studies that were conducted in the cardiac and thoracic surgery setting and those studies reporting on patients with documented AF that occurred before the surgical procedures as our aim was to identify new-onset perioperative AF associated with noncardiothoracic surgeries. Abstracts and conference publications were excluded as they were not deemed to have undergone an adequate peer review process, and studies that were not published in English language were also excluded due to resource limitations.
Based on predefined search criteria, an expert librarian systematically searched the following electronic databases: PubMed, Medline, Embase, Web of Science, and Cochrane databases, using the following terms and combinations of keywords, per the National Center for Biotechnology Information Medical Subject Headings (NCBI MeSH): “after surgery” or “following surgery” or “post-surgery” or “post-transplant” or “perioperative” or “periprocedural” or “intraoperative” or “intraprocedural” or “postoperative” or “postprocedural” or “perioperative period” or “arrhythmia” or “bradycardia” or “tachycardia” or “atrial flutter” or “atrial fibrillation” or “afib” or “dysrhythmia” or “tachyarrhythmia” or “bradyarrhythmia.” The search was run on February 2019 and updated February 2020. The search strategy is attached as a supplementary file (
A data collection form was designed and the following data were extracted: study characteristics, including name of the author, publication year, study type, and participant number; preoperative data including age, sex, preoperative medications, cardiovascular, respiratory and general medical comorbidities, like diabetes mellitus, and hypertension; intraoperative data including type of surgery, duration, blood loss, and intraoperative cardiopulmonary complications; and postoperative data including postoperative complications like cardiopulmonary events, postoperative sepsis, stroke, and mortality. The definition and timing of the perioperative AF were recorded. The abovementioned were collected using a standardized data collection proforma. The authors YS and AF confirmed the accuracy and completeness of all the data.
The primary outcome was the demographic and clinical risk factors for new-onset perioperative AF with noncardiothoracic surgery. Secondary outcomes were the incidence and perioperative complications associated with the perioperative AF.
Data on demographics, comorbidities, and perioperative complications were analysed by extracting and pooling odds ratios and mean differences using an inverse variance statistical method that incorporates a measure of the extent of heterogeneity into study weights, following DerSimonian and Laird’s method. Continuous data were reported as mean difference (MD). Dichotomous data were reported as odds ratio (OR) and 95% confidence interval (CI). A two-sided
Each analysis was assessed for statistical heterogeneity using the
An influence analysis was performed by excluding each study in the analysis for the significant risk factors and outcomes, and the pooled estimates were recalculated. If the quality or eligibility of any of the studies was in doubt, the analysis was performed by both including and excluding these studies to check the sensitivity of the pooled estimates. Study quality assessment was conducted (as categorical variable) by meta-regression and sensitivity analysis of various subgroups based on the study type (retrospective versus prospective), quality of study (good versus poor-moderate), clearly defined outcomes (yes versus no), and sample size >1000 (yes versus no), and type of surgery (Transplant versus nontransplant procedure). The analysis was conducted using the Review Manager software (RevMan, V.5.3) and Comprehensive Meta-Analysis (CMA) software.
Our initial search identified 2,973 studies, and after removing duplicates, 2,603 were screened, by titles and abstracts, to yield 51 studies for full-text eligibility review. Forty studies were excluded as they did not meet the eligibility criteria. Finally, 11 studies met the inclusion criteria and were included in this SRMA (Figure
PRISMA flow diagram showing the articles screened for eligibility as per the inclusion criteria to be included in the systematic review and meta-analyses.
Regarding age, eleven studies involving 121,517 patients reported on age: 2,944 patients in the AF group and 118,573 patients in the control group [
Forest plot evaluating age as a risk factor for perioperative atrial fibrillation in patients undergoing noncardiothoracic surgery. The mean difference of each included study is plotted. A pooled estimate of overall mean difference (diamonds) and 95% confidence intervals (width of diamonds) summarizes the effect size using the random effects model. CI = confidence interval; IV = inverse variance; MD = mean difference;
Regarding gender, eleven of the included studies consisting of 121,517 patients reported on gender (perioperative AF versus control: 2944 versus 118,573) [
Forest plot evaluating male gender as a risk factor for perioperative atrial fibrillation in patients undergoing noncardiothoracic surgery. The odds ratio of each included study is plotted. A pooled estimate of overall odds ratio (diamonds) and 95% confidence intervals (width of diamonds) summarizes the effect size using the random effects model. CI = confidence interval; M–H = Mantel–Haenszel; OR = odds ratio;
Regarding body mass index (BMI), there was no significant difference in BMI between the perioperative AF and control group. The mean BMI was 26.67 ± 5.52 for the perioperative AF group compared to 24.97 ± 3.98 among the control group (MD: 0.18; 95% CI: −1.14 to 1.50;
Ten studies consisting of 121,268 patients reported on hypertension [
Forest plot evaluating hypertension as a risk factor for perioperative atrial fibrillation in patients undergoing noncardiothoracic surgery. The odds ratio of each included study is plotted. A pooled estimate of overall odds ratio (diamonds) and 95% confidence intervals (width of diamonds) summarizes the effect size using the random effects model. CI = confidence interval; M–H = Mantel–Haenszel; OR = odds ratio;
Nine of the included studies reported on diabetes [
Forest plot evaluating diabetes mellitus as a risk factor for perioperative atrial fibrillation in patients undergoing noncardiothoracic surgery. The odds ratio of each included study is plotted. A pooled estimate of overall odds ratio (diamonds) and 95% confidence intervals (width of diamonds) summarizes the effect size using the random effects model. CI = confidence interval; M–H = Mantel–Haenszel; OR = odds ratio;
Nine of the included studies with 113,512 reported on the incidence of preoperative cardiac disease (perioperative AF versus control: 2901 versus 110,611) [
Forest plot evaluating cardiac disease as a risk factor for perioperative atrial fibrillation in patients undergoing noncardiothoracic surgery. The odds ratio of each included study is plotted. A pooled estimate of overall odds ratio (diamonds) and 95% confidence intervals (width of diamonds) summarizes the effect size using the random effects model. CI = confidence interval; M–H = Mantel–Haenszel; OR = odds ratio;
Six of the included studies reported on the incidence of preoperative respiratory disease (perioperative AF versus control: 2741 versus 107,821) [
Two studies involving 2446 patients reported the data on the MELD score [
Supplementary Table
Cardiac complications: six of the included studies reported on the incidence of postoperative cardiac complications (perioperative AF versus control: 2771 versus 107,885) [
Forest plot comparing cardiac complications between atrial fibrillation group and control groups in patients undergoing noncardiothoracic surgery. The odds ratio of each included study is plotted. A pooled estimate of overall odds ratio (diamonds) and 95% confidence intervals (width of diamonds) summarizes the effect size using the random effects model. CI = confidence interval; M–H = Mantel–Haenszel; OR = odds ratio;
Stroke: two studies involving 2686 patients in the AF group and 106586 patients in the control group reported the data on the stroke [
Mortality: six studies involving 108 patients in the AF group and 9905 patients in the control group reported the data on the mortality [
Forest plot comparing mortality between atrial fibrillation group and control groups in patients undergoing noncardiothoracic surgery. The odds ratio of each included study is plotted. A pooled estimate of overall odds ratio (diamonds) and 95% confidence intervals (width of diamonds) summarizes the effect size using the random effects model. CI = confidence interval; M–H = Mantel–Haenszel; OR = odds ratio;
Study quality assessment: study quality assessment was conducted (as categorical variable) by meta-regression and sensitivity analysis of various subgroups based on the study type (retrospective versus prospective), quality of study (good versus poor-moderate), whether or not outcomes were clearly defined (yes versus no), sample size >1000 (yes versus no), and surgery type (transplant versus nontransplant procedures) did not show any significant differences in the results (Table
Study quality assessment: meta-regression and sensitivity analysis of various subgroups (as categorical variable).
Risk factor or outcome | Study characteristics (number of studies) | Summary estimate | 95% CI | Meta-regression | ||
---|---|---|---|---|---|---|
Age | Coefficient (SE) | |||||
Study type | Retrospective (9) [ | 3.75 | 0.75–6.76 | 90 | 0.6155 | 0.8651 |
Prospective (2) [ | 5.03 | 2.97–7.09 | 0 | (3.6220) | ||
Quality of study | Poor-moderate (1) [ | 14.34 | −11.37–40.05 | — | −0.3148 | 0.9486 |
Good (10) [ | 3.97 | 1.57–6.38 | 89 | (4.8794) | ||
Outcome defined | Yes (7) [ | 4.58 | 2.08–7.08 | 88 | 0.3634 | 0.9250 |
No (4) [ | 3.12 | −4.31–10.55 | 83 | (3.8607) | ||
Sample size >1000 | Yes (4) [ | 3.11 | −0.41–6.62 | 94 | 1.9924 | 0.4748 |
No (7) [ | 4.93 | 1.51–8.34 | 67 | (2.7880) | ||
Surgery type | Transplant (3) [ | 3.04 | −4.03–10.11 | 90 | −1.6709 | 0.6740 |
Nontransplant (8) [ | 4.42 | 1.68–7.17 | 86 | (3.9716) | ||
Gender | ||||||
Study type | Retrospective (9) [ | 1.07 | 0.42–1.72 | 87 | −0.1621 | 0.8230 |
Prospective (2) [ | 1.15 | 0.66–1.64 | 0 | (0.7248) | ||
Quality of study | Poor-moderate (1) [ | 0.68 | −0.26–1.62 | — | −0.5386 | 0.5592 |
Good (10) [ | 1.14 | 0.55–1.72 | 86 | (0.9223) | ||
Outcome defined | Yes (7) [ | 1.43 | 1.33–1.52 | 0 | 0.4614 | 0.5366 |
No (4) [ | 0.56 | −0.01–1.12 | 34 | (0.7465) | ||
Sample size >1000 | Yes (4) [ | 1.07 | 0.29–1.86 | 95 | −0.3247 | 0.4981 |
No (7) [ | 1.02 | 0.46–1.57 | 0 | (0.4793) | ||
Surgery type | Transplant (3) [ | 0.80 | −0.04–1.63 | 83 | −0.3795 | 0.5944 |
Nontransplant (8) [ | 1.43 | 1.33–1.53 | 0 | (0.7126) | ||
Hypertension | ||||||
Study type | Retrospective (8) [ | 1.15 | 1.07–1.22 | 0 | −0.1036 | 0.8490 |
Prospective (2) [ | 1.24 | 0.75–1.74 | 0 | (0.5441) | ||
Quality of study | Poor-moderate (0) | — | — | — | — | — |
Good (10) [ | 1.15 | 1.08–1.23 | 0 | |||
Outcome defined | Yes (7) [ | 1.15 | 1.08–1.23 | 0 | −0.8519 | 0.1879 |
No (3) [ | 2.81 | −0.77–6.39 | 0 | (0.6469) | ||
Sample size >1000 | Yes (4) [ | 1.15 | 1.08–1.23 | 0 | −0.2608 | 0.3738 |
No (6) [ | 1.32 | 0.50–2.13 | 0 | (0.2933) | ||
Surgery type | Transplant (3) [ | 1.24 | 0.74–1.75 | 0 | −0.0418 | 0.9409 |
Nontransplant (7) [ | 1.15 | 1.07–1.23 | 0 | (0.5639) | ||
Cardiac disease | ||||||
Study type | Retrospective (7) [ | 2.79 | 0.17–5.41 | 92 | 1.3910 | 0.0545 |
Prospective (2) [ | 1.32 | 0.16–2.49 | 55 | (0.7236) | ||
Quality of study | Poor-moderate (0) | — | — | — | — | — |
Good (9) [ | 2.30 | 0.28–4.31 | 93 | |||
Outcome defined | Yes (6) [ | 2.15 | −0.16–4.46 | 95 | 0.0043 | 0.9956 |
No (3) [ | 3.28 | −1.90–8.46 | 27 | (0.7790) | ||
Sample size >1000 | Yes (3) [ | 3.86 | 0.90–6.82 | 92 | 0.7579 | 0.1808 |
No (6) [ | 0.94 | 0.29–1.58 | 0 | (0.5663) | ||
Surgery type | Transplant (3) [ | 2.94 | −0.63–6.52 | 13 | 0.9274 | 0.2304 |
Nontransplant (6) [ | 2.01 | −0.42–4.44 | 96 | (0.7732) | ||
Diabetes mellitus | ||||||
Study type | Retrospective (8) [ | 0.97 | 0.89–1.05 | 0 | 0.7277 | 0.4019 |
Prospective (1) [ | 0.61 | −0.70–1.92 | — | (0.8681) | ||
Quality of study | Poor-moderate (0) | — | — | — | — | — |
Good (9) [ | 0.97 | 0.89–1.05 | 0 | |||
Outcome defined | Yes (6)[ | 0.97 | 0.89–1.05 | 0 | −0.2032 | 0.7579 |
No (3)[ | 1.51 | 0.14–2.88 | 0 | (0.6595) | ||
Sample size >1000 | Yes (3)[ | 0.97 | 0.89–1.05 | 0 | −0.2644 | 0.5052 |
No (6) [ | 0.94 | 0.17–1.71 | 0 | (0.3968) | ||
Surgery type | Transplant (2) [ | 1.48 | −0.51–3.48 | 0 | 0.3992 | 0.5901 |
Nontransplant (7) [ | 0.97 | 0.89–1.05 | 0 | (0.7410) | ||
Cardiac complications | ||||||
Study type | Retrospective (5) [ | 5.71 | −0.18–11.61 | 83 | 0.3609 | 0.6949 |
Prospective (1) [ | 4.34 | −1.11–9.79 | — | (0.9292) | ||
Quality of study | Poor-moderate (0) | — | — | — | — | — |
Good (6) [ | 5.44 | 0.49–10.39 | 82 | |||
Outcome defined | Yes (5) [ | 5.41 | 0.36–10.46 | 85 | −0.7377 | 0.6474 |
No (1) [ | 11.58 | −83.6–106.76 | 0 | (1.6127) | ||
Sample size >1000 | Yes (1) [ | 10.51 | 9.63–11.39 | — | 0.9718 | 0.0023 |
No (5) [ | 3.18 | 0.54–5.82 | 0 | (0.3193) | ||
Surgery type | Transplant (1) [ | 11.58 | −83.60–106.76 | — | 0.7377 | 0.6474 |
Nontransplant (5) [ | 5.41 | 0.36–10.46 | 85 | (1.6127) | ||
Mortality | ||||||
Study type | Retrospective (6) [ | 3.58 | 0.14–7.02 | 0 | — | — |
Prospective (0) | — | — | — | |||
Quality of study | Poor-moderate (1) [ | 2.47 | −22.62–27.56 | — | −0.7977 | 0.6530 |
Good (5) [ | 3.60 | 0.13–7.08 | 0 | (1.7743) | ||
Outcome defined | Yes (4) [ | 3.20 | −1.16–7.57 | 0 | 0.4607 | 0.6670 |
No (2) [ | 4.21 | −1.39–9.81 | 0 | (1.0705) | ||
Sample size >1000 | Yes (2) [ | 6.51 | −3.79–16.81 | 22 | 1.2296 | 0.0934 |
No (4) [ | 2.69 | −1.67–7.06 | 0 | (0.7329) | ||
Surgery type | Transplant (1) [ | 4.30 | −1.44–10.04 | — | −0.2072 | 0.8651 |
Nontransplant (5) [ | 3.18 | −1.12–7.48 | 0 | (1.2196) |
Study quality scores were obtained from the Ottawa–Newcastle quality assessment [
There is a change in the old perception that postoperative arrhythmias like AF were a benign condition [
Evidence on the incidence of postoperative arrhythmias shows that 16% to 46% of patients after cardiac surgery, 3% to 30% of patients after thoracic surgery, and up to 8% of noncardiothoracic surgical patients developed new-onset atrial arrhythmias [
Recognizing the risk factors of perioperative AF helps to individualize patient care, as well as to guide future studies of interventions to lower the incidence of perioperative AF and the associated complications. Age is an important predictor of perioperative AF. Our study found that the perioperative AF group patients were older compared to the control group. This is consistent with the findings from other studies [
We identified hypertension and diabetes as predictors of perioperative arrhythmias. Hypertension is well established to be a risk factor for perioperative AF in both experimental animal and human studies [
In our review, increased BMI was not identified as a risk factor for perioperative AF. However, BMI was identified as an important risk factor of new-onset atrial fibrillation (NOAF) after cardiac surgery [
In our analysis, preexisting cardiac disease increases the odds of perioperative AF. In a study by Christians et al. [
Fulminant hepatic failure and a higher MELD score were identified as independent predictors of intraoperative AF [
Perioperative AF after noncardiothoracic surgery has been associated with poor postoperative cardiovascular outcomes. Our meta-analysis found that perioperative AF was associated with increased odds of postoperative cardiac complications, like myocardial infarction (MI) and congestive cardiac failure. Four studies have identified perioperative AF as an independent predictor for postoperative cardiac complications in a multivariate analysis [
Our study found increased odds of mortality in the AF group versus the control group. Several other studies [
The lack of consistent definition, precision in identifying AF, and consistent monitoring protocols are major risks for bias in many of the included studies. The application of cardiac monitoring intraoperatively was reported in only 2 studies [
This SRMA identified advanced age, male gender, preexisting hypertension, diabetes mellitus, and cardiac disease as important risk factors associated with perioperative AF. We also found that the AF group had increased odds for postoperative cardiac complications, stroke, and higher mortality compared to the control group, emphasizing the need for risk stratification and close monitoring of this surgical population.
Atrial Fibrillation
Body mass index
Confidence Interval
Comprehensive Meta-Analysis
Electrocardiogram
Mean Difference
Model for End-stage Liver Disease
New-Onset Atrial Fibrillation
Odds Ratios
Preferred Items for Systematic Reviews and Meta-Analyses
Quality in Prognostic Studies
Systematic Review and Meta-analysis
The data are available upon request to the corresponding author.
Yamini Subramani and Omar El Tohamy share the first authorship.
The authors declare no conflicts of interest.
All authors have read and approved the manuscript. YS designed the study, reviewed the literature, performed data collection and analysis, and prepared the manuscript. OT helped in reviewing the literature, data collection, and analysis. DJ helped in reviewing the literature, data collection, and analysis. MN helped with statistical analysis and preparing and editing the manuscript. HY helped with analysis and preparing and editing the manuscript. AF helped in designing the study, data collection, analysis, preparing, and editing the manuscript.
The authors thank Rachel Sandieson, Librarian, and Brie McConnell MLIS (Media and Information Manager, London Health Science Centre, Western University) for their assistance with the literature search.
S1: predesigned study protocol. S2: study search strategy. S3: definitions of outcome atrial fibrillation. S4: table on systematic review. S5: Newcastle–Ottawa scale scoring system (quantitative study assessment). S6: bias assessment results of each study with the quality in prognostic studies (QUIPS) tool. S7: distribution of the type of surgical procedures for the atrial fibrillation group and control groups.