European Journal of Cardiovascular Medicine

CABG surgery patients commonly develop AF which manifests as the most frequent arrhythmia following these procedures in research-based studies that document occurrences from 20 to 50 percent.¹ The occurrence of POAF contributes negatively to patient clinical results by making patients vulnerable to stroke danger and hemodynamic instability while leading to extended hospitalizations and increased healthcare costs.² Medical practitioners need to comprehend determining risk factors because it helps them select patients who are at high risk and execute prevention approaches. The combined structural, electrophysiological and inflammatory changes make up the complex pathogenesis of postoperative atrial fibrillation (POAF). Atrial remodeling occurs through myocardial ischemia together with oxidative stress and systemic inflammation to create a condition which leads patients toward AF development. The arrhythmic substrate becomes worse in patients following CABG because of surgical trauma and pericardial inflammation together with changes in autonomic tone.³

Atrial fibrillation which develops after CABG surgery depends on various combinations of preoperative, intraoperative and postoperative factors. The combination of old age exceeding 65 years and hypertension, diabetes mellitus and COPD demonstrates high risk for patients before surgery. ⁴The development of POAF receives greater risk from patients who show structural heart abnormalities combining left atrial enlargement with left ventricular dysfunction.⁵ Prior experiences with atrial fibrillation double the chances that surgery patients will experience a return of this condition.⁶ The development of POAF after cardiac surgery is influenced by long cardiopulmonary bypass operations and prolonged usage of aortic clamp time and additional intraoperative treatment with inotropic drugs. The risk of developing arrhythmias in patients relates to the choice between arterial or venous grafts used in the surgical procedure. The extent of myocardial ischemia together with reperfusion injury throughout surgery serves as a major trigger for postoperative arrhythmias.⁶

Research shows that patients with elevated C-reactive protein levels after surgery experience greater chances of developing postoperative atrial fibrillation (POAF). The development of atrial myocardium electrical instability occurs due to electrolyte disturbances that typically include hypokalemia together with hypomagnesemia. The combination of fluid overload and atrial dilatation subjects the heart to mechanical pressure that enhances the development of irregular heartbeats.⁷ POAF risk elevation stems from postoperative drug use and high-dose beta-adrenergic agonist treatment as well as vasoactive drug utilization and infection development. ⁵ The occurrence of POAF presents serious prognostic risks because it leads to a greater probability of developing stroke and transient ischemic attacks along with thromboembolic events. POAF increases hospital stay duration in the intensive care unit as well as patient readmissions and increases mortality statistics. The prevention of POAF becomes more successful when healthcare organizations implement strategies to locate patients at risk and use medications like beta-blockers along with amiodarone and statins to minimize POAF development. ⁷ The onset of atrial fibrillation during coronary artery bypass grafting leads to significant clinical problems arising from several contributing factors before, during, and after the surgical procedure. Observational studies should evaluate these risk factors to enable healthcare professionals to determine who requires additional prevention strategies focusing on improved patient outcomes and lower POAF occurrence in cardiac surgery patients .⁶ This study aims to assess the incidence of AF in post-CABG patients at JIPMER and identify the clinical factors associated with its development. By analyzing preoperative, intraoperative, and postoperative variables, this research seeks to enhance clinical decision-making and develop targeted preventive strategies. Understanding the role of factors such as hypoxia, potassium imbalances, and diabetes in the onset of POAF will help refine post-operative monitoring protocols and improve patient outcomes in CABG surgery.

METHODOLOGY

Study Design: This is an observational prospective study that took place at JIPMER to determine atrial fibrillation (AF) rates in post-CABG surgical patients as well as potential clinical connections between phenomena.

Participants: The study enrolled all patients aged 18 years and above who received elective CABG surgery while maintaining normal sinus rhythm prior to the procedure. The research investigators enrolled 144 patients who qualified as per the inclusion and exclusion standards.

Inclusion Criteria:

• Patients aged >18 years.
• Patients undergoing elective CABG.
• Patients in normal sinus rhythm preoperatively.

Exclusion Criteria:

• Patients undergoing emergency CABG procedures.
• Patients requiring preoperative intra-aortic balloon pump (IABP) insertion.
• Patients with chronic kidney disease (CKD) or chronic obstructive pulmonary disease (COPD).
• The study excluded patients who needed preoperative insertion of intra-aortic balloon pump (IABP).

Data Collection: Data were collected from patient case records, intraoperative data, anesthesia charts, perfusion data, and post-operative parameters recorded in daily doctor’s notes and ICU investigation reports.  Medical staff used electrocardiography monitoring to track new AF occurrences during intensive care period of patients while providing ongoing surveillance until the rhythm returned to normal. The healthcare professional performed a 12-lead ECG examination before the patient left the facility.

Measured Outcomes

1. Primary Outcome: Incidence of atrial fibrillation in post-operative CABG patients.
2. Secondary Outcomes: Clinical factors associated with post-operative AF, including demographic details, preoperative comorbidities (diabetes, hypertension, smoking status, left main coronary artery disease, left ventricular function, valvular lesions, beta-blocker use), intraoperative factors (cardiopulmonary bypass time, aortic cross-clamp time), and post-operative factors (hypoxia, hypokalemia, prolonged ventilation, hemodynamic instability, post-op LV function).

Data Analysis: Continuous variables were represented as the mean accompanied by the standard deviation. The incidence of AF was compared with continuous variables using one-way analysis of variance (ANOVA). A chi-square test was conducted to compare the incidence of AF with categorical factors. All statistical analyses were performed at a 5% significance level (p < 0.05 deemed statistically significant).

Table 1. Age Distribution of Patients

Table 1 shows that the study participants mostly fall within the 51–60-year-old category since they make up 43.1% of the total population. The study population consists mostly of adults between 61 and 70 years old at 25.0% and second to the 41–50-year group at 22.9%. The 30–40-year and 71 years and above age ranges contained 6.9% and 2.1% of the research participants respectively. The research participants had an average age of 55.16 ± 8.64 years since they mainly belonged to an older middle-aged demographic.

Table 2. Age as a Risk Factor for Atrial Fibrillation

In study using Table 2 evaluates age as a significant risk factor leading to development of atrial fibrillation (AF). Older participants beyond fifty years of age demonstrated higher prevalence of AF at 34.7% while participants under fifty years old had a prevalence rate of 16.3%. Statistics show age acts as a major risk factor for AF because the chi-square test proved age affects AF occurrence significantly (p = 0.026). The data strengthens medical knowledge about AF risk progression that occurs with increasing age thus requiring more thorough monitoring for early diagnosis and treatment of older people.

Table 3. Diabetes Mellitus and Atrial Fibrillation

Table 3 evaluates the association between diabetes mellitus and atrial fibrillation (AF). Among patients with diabetes (n=84), 31.0% developed AF, while 69.0% did not. In contrast, among non-diabetic patients (n=60), the incidence of AF was slightly lower at 26.7%, with 73.3% remaining free of AF. Although there appears to be a higher prevalence of AF among diabetic patients, the difference is not markedly significant. These findings suggest that while diabetes may contribute to AF risk, additional factors likely play a role in its development.

Table 4. Hypoxia and Atrial Fibrillation

Table 4 demonstrates that hypoxic conditions after surgery create a strong relationship between post-operative hypoxic events and development of AF. Postoperative hypoxia came with an AF occurrence rate of 43.2% among 74 affected patients yet non-hypoxic patients (n=70) experienced AF in 14.3% of cases. The statistical analysis through chi-square produced a very low p-value that reached less than 0.001 along with an odds ratio of 4.571 which displays hypoxic patients have more than four times greater risk of developing AF than non-hypoxic patients. The research results demonstrate hypoxic conditions stand as a significant factor for AF occurrence thus identifying proper oxygen maintenance as a vital element in post-operative care.

Table 5. PO2/FiO2 Ratio and Atrial Fibrillation

Table 5 demonstrate PO₂/FiO₂ ratio affects atrial fibrillation (AF) development by displaying data. Patients who maintained a ratio between oxygen partial pressure and fraction of inspired oxygen at ≤250 showed previously unobserved Atrial fibrillation incidence reaching 36.5% while the patients with ratios >250 displayed an incidence of 14.6%. The chi-square analysis produced a statistically important p-value (0.006) that confirms that poor oxygenation levels create elevated risks for the development of AF. Infection rates of new atrial fibrillation increase when patients exhibit poor lung oxygenation suggesting that such conditions play a central part in AF pathogenesis thus demanding better assessment and management of postoperative oxygenation levels.

Table 6. Potassium Levels and Atrial Fibrillation

Atrial fibrillation incidence during lab tests was found to have its highest correlations between potassium levels spanning from 2.5-3 mEq/L according to Table 6. Patients with potassium levels between 2.5-3 mEq/L experienced the highest rates of atrial fibrillation development and reached an incidence rate of 65.7% in this group. The patient population with potassium ranges from 1.5-2 mEq/L or 4-4.5 mEq/L showed no AF occurrences. Patients with potassium measured at 3-3.5 mEq/L recorded a 12.5% AF rate and those with potassium values at 3.5-4 mEq/L had a 33.3% AF incidence. The data indicates that abnormal potassium concentrations especially hypokalemia centrally cause AF while electrolyte control represents a critical practice in post-surgical medical care.

Table 7. Potassium as a Predictor of Atrial Fibrillation

Table 7 highlights the role of potassium levels as a predictor of atrial fibrillation (AF). Patients with potassium levels ≤3 mEq/L had a significantly higher incidence of AF (55.1%) compared to those with levels >3 mEq/L, where only 15.8% developed AF. The chi-square test yielded a statistically significant association (p < 0.001), with an odds ratio of 6.545 (95% CI: 2.976–14.394), indicating that hypokalemia greatly increases the risk of AF. These results underscore the critical importance of maintaining adequate potassium levels in post-operative patients to minimize AF occurrence.

The findings of this study highlight several important factors influencing the occurrence of atrial fibrillation (AF) in post-operative patients. Age, hypoxia, oxygenation levels, and potassium levels were all significantly associated with an increased risk of AF, underscoring the need for vigilant monitoring and management of these parameters. Research found that patients in the study exhibited a mean age of 55.16 ± 8.64 years and most participants belonged to middle-aged or older groups. The research found age to be a fundamental threat factor because patients who exceeded the age of 50 presented a 34.7% AF prevalence rate while participants under 50 years maintained a 16.3% AF incidence level. The strong statistical relationship (p = 0.026) confirms existing knowledge about how age advancement boosts AF risk therefore promoting targeted screening along with preventive measures for older patients. The research conducted by Musa et al.,⁸ demonstrated that AF prevalence increases as people grow older because it reaches its maximum levels in people whose age exceeds eighty years. The independent risk factor status of age leads to AF development and the study demonstrated that the risk escalates with increasing age (Mohammadi et al.,) ⁹ just like this investigation of AF as an age-related condition

The prevalence rates between diabetic and non-diabetic patients with AF usage was 31.0% and 26.7% but lacked statistical significance. In this patient population diabetes seems to increase risks of AF but does not establish itself as an individual predictor for AF development. Comorbidities together with metabolic disturbances seem to affect how diabetes influences the development of AF. The research concluded that diabetes conditions create a 40% greater risk of developing AF regardless of other risk variables according toAccording to the research hyperglycemia alongside insulin resistance causes atrial remodeling and fibrosis which Creates conditions that favor AF development in patients. Antia et al.,¹⁰ showed diabetic patients experience increased AF prevalence apparently because diabetes-induced inflammation and oxidative stress damage heart tissue.

Post-operative hypoxia presented a strong connection to the development of AF among patients. The patient population with hypoxia showed a dramatic rise in AF occurrence at 43.2% as compared to 14.3% among non-hypoxic subjects where the p-value reached an exceptional threshold below 0.001 while the odds ratio reached 4.571 with 95% confidence interval of 2.029–10.299. The research data confirms that oxygenation levels play a vital role in AF development because hypoxia might serve as an arrhythmic event trigger. Those patients with a PO₂/FiO₂ ratio of ≤250 demonstrated significantly higher AF incidence (36.5%) as compared to patients with a ratio >250 who had an incidence of 14.6% (p = 0.006). Research by Al Turki et al., ¹¹ proved that intermittent hypoxia during sleep apnea causes AF development because it activates the autonomic nervous system and creates oxidative stress. The research conducted by Pooria et al.,¹² demonstrated that atrial remodeling together with inflammation serve as crucial connections between hypoxic conditions and AF while focusing on post-operative patients. The research conducted by Musa et al., ⁸ demonstrated that patients with poor oxygenation levels measured by PO₂/FiO₂ ratio faced elevated AF risks during intensive care. The researchers found that conditions causing decreased oxygen levels which resulted in stretching of the atria and inflammation together advanced the development of AF.

The results showed that inadequate potassium regulation strongly contributes to the risk of developing AF. Patients displaying potassium levels between 2.5-3 mEq/L had the greatest AF incidence reaching 65.7% whereas the other groups with 1.5-2 mEq/L or 4-4.5 mEq/L potassium showed no AF cases. Hospital patients with potassium levels lower than 3 mEq/L developed AF at a rate of 55.1% whereas patients with higher potassium levels-maintained levels at 15.8% or below. Hypokalemia proves to be a powerful AF predictor based on a very significant p value of <0.001 alongside an odds ratio of 6.545 (95% CI: 2.976–14.394). Post-operative patients need regulated potassium levels to prevent arrhythmogenic complications because these results demonstrate this requirement. Similarly, Wu et al., ⁵ demonstrated that AF incidence increases with hypokalemic and hyperkalemic conditions though hypokalemia generates a higher risk because it disrupts myocardial functions related to excitability and conduction. The study by Khan et al., ¹³ discovered that potassium abnormalities modify atrial action potential duration and refractoriness which promotes the onset of AF. The study results demonstrate that AF develops from multiple risk factors in patients after surgery. This data confirms that age continues as a known risk factor yet confirms the risk reduction potential of addressing hypoxia and hypokalemia and maintaining proper PO₂/FiO₂ ratios in preventing AF development. Investigations should analyze how early repair of these medical conditions results in improved clinical health and reduced adverse AF effects in surgical patients.

This study highlights the significant burden of post-operative AF in CABG patients, emphasizing the role of age, hypoxia, oxygenation status, and potassium levels as critical risk factors. The findings suggest that closer perioperative monitoring and targeted management of these factors may help reduce AF incidence and improve patient outcomes. Future research should explore preventive strategies and individualized approaches to minimize the occurrence of post-operative AF in high-risk patients.

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