Prevalence of New-Onset Atrial Fibrillation and Associated Outcomes in Patients with Sepsis: A Systematic Review and Meta-Analysis

A nationwide study on new onset atrial fibrillation risk factors and its association with hospital mortality in sepsis patients

Atrial fibrillation (AF) is the most common arrhythmia and its incidence increases with sepsis. However, data on new-onset AF during sepsis hospitalization remain limited in China. We aimed to evaluate the incidence, risk factors, and associated mortality of new-onset AF in sepsis patients in China. We conducted a retrospective study using the National Data Center for Medical Service system, from 1923 tertiary and 2363 secondary hospitals from 31 provinces in China from 2017 to 2019.In total we included 1,425,055 sepsis patients ≥ 18 years without prior AF. The incidence of new-onset AF was 1.49%. Older age, male sex, hypertension, heart failure, coronary disease, valvular disease, and mechanical ventilation were independent risk factor. New-onset AF was associated with a slight increased risk of mortality (adjusted RR 1.03, 95% CI 1.01-1.06). Population attributable fraction suggested AF accounted for 0.2% of sepsis deaths. In this large nationwide cohort, new-onset AF occurred in 1.49% of sepsis admissions and was associated with a small mortality increase. Further research should examine whether optimized AF management can improve sepsis outcomes in China.

Long-term Risk of Stroke After New-Onset Atrial Fibrillation in Sepsis Survivors: A 2-Year Follow-Up Study

BACKGROUND

Cardiovascular complications such as new-onset atrial fibrillation (NOAF) are common in sepsis and are known to increase the risk of in-hospital mortality and stroke. However, only a handful of studies have evaluated the long-term risk of stroke after NOAF in sepsis survivors. As part of our efforts to address this issue, we conducted the first-ever follow-up study in a developing country evaluating the long-term risk of stroke for sepsis survivors following NOAF. Methods: This retrospective study evaluated all adult patients admitted at the Aga Khan University Hospital between July 2019 and December 2019 with the diagnosis of sepsis. Data was collected from medical records of the included patients. Outcome measures included in-hospital mortality and ischemic stroke within 2 years. Results: Seven hundred thirty patients were included in the study; 415 (57%) were males and 315 (43%) females; mean age was 59.4 ± 18 years. 59 (8%) patients developed NOAF. The risk of stroke within 2 years in sepsis survivors was 3.5%. Six out of 30 (20%) patients in the atrial fibrillation (AF) group developed stroke, whereas 11 out of 448 (2%) patients in the non-AF group developed stroke. NOAF was associated with an increased risk of ischemic stroke within 2 years (OR = 6.6; 95% CI, 2.3-12.8; P = <.001). Conclusion: We conclude that AF occurred frequently in sepsis patients and was also associated with a 6-fold increase in the risk of ischemic stroke within 2 years. Reliable interventions for identifying high-risk patients for ischemic stroke are still poorly characterized, and this study may serve as a basis for more extensive multicenter studies to identify patients at high risk for ischemic stroke in the aftermath of septic AF and develop precise interventions for preventing it.

Fibrinaloid Microclots and Atrial Fibrillation

Atrial fibrillation (AF) is a comorbidity of a variety of other chronic, inflammatory diseases for which fibrinaloid microclots are a known accompaniment (and in some cases, a cause, with a mechanistic basis). Clots are, of course, a well-known consequence of atrial fibrillation. We here ask the question whether the fibrinaloid microclots seen in plasma or serum may in fact also be a cause of (or contributor to) the development of AF. We consider known 'risk factors' for AF, and in particular, exogenous stimuli such as infection and air pollution by particulates, both of which are known to cause AF. The external accompaniments of both bacterial (lipopolysaccharide and lipoteichoic acids) and viral (SARS-CoV-2 spike protein) infections are known to stimulate fibrinaloid microclots when added in vitro, and fibrinaloid microclots, as with other amyloid proteins, can be cytotoxic, both by inducing hypoxia/reperfusion and by other means. Strokes and thromboembolisms are also common consequences of AF. Consequently, taking a systems approach, we review the considerable evidence in detail, which leads us to suggest that it is likely that microclots may well have an aetiological role in the development of AF. This has significant mechanistic and therapeutic implications.

Study protocol: A systematic review and meta-analysis regarding the influence of coagulopathy and immune activation on new onset atrial fibrillation in patients with sepsis

BACKGROUND

New onset atrial fibrillation (NOAF) is the most common arrhythmia affecting critically ill patients with sepsis. NOAF is associated with increased intensive care unit mortality, increased hospital mortality, development of heart failure and increased risk of permanent atrial fibrillation and thromboembolic events such as stroke. The pathophysiology of NOAF has been outlined, however, a knowledge gap exists regarding the association between abnormalities in coagulation and immune biomarkers, and the risk of developing NOAF in patients with sepsis.

METHODS AND ANALYSIS

This protocol describes a systematic review and meta-analysis following the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols guideline (PRISMA-P) and the Meta-Analyses and Systematic Reviews of Observational Studies guideline (MOOSE). We will conduct the literature search in Medline, Scopus and Cochrane Library. We will include studies that report data in adult patients (>18 years) with sepsis that develop NOAF. We will extract data from studies that report at least one coagulation or immune biomarker. Risk of bias will be assessed by using the Newcastle Ottawa Scale (NOS) and Risk of Bias 2 tool (RoB2) for non-randomized and randomized trials respectively. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach will be utilized in assessing the quality of evidence.

DISCUSSION

This systematic review and meta-analysis will explore the scientific literature regarding the association between coagulation and immune activation in critically ill patients with sepsis, who develop NOAF. The findings will add to the existing knowledge base of NOAF in sepsis, highlight areas of uncertainty and identify future areas of interest to guide and improve management strategies for NOAF.

TRIAL REGISTRATION

Registration details. CRD42022385225 (PROSPERO).

Recognition of Strokes in the ICU: A Narrative Review

Despite the remarkable progress in acute treatment for stroke, in-hospital stroke is still devastating. The mortality and neurological sequelae are worse in patients with in-hospital stroke than in those with community-onset stroke. The leading cause of this tragic situation is the delay in emergent treatment. To achieve better outcomes, early stroke recognition and immediate treatment are crucial. In general, in-hospital stroke is initially witnessed by non-neurologists, but it is sometimes challenging for non-neurologists to diagnose a patient's state as a stroke and respond quickly. Therefore, understanding the risk and characteristics of in-hospital stroke would be helpful for early recognition. First, we need to know "the epicenter of in-hospital stroke". Critically ill patients and patients who undergo surgery or procedures are admitted to the intensive care unit, and they are potentially at high risk for stroke. Moreover, since they are often sedated and intubated, evaluating their neurological status concisely is difficult. The limited evidence demonstrated that the intensive care unit is the most common place for in-hospital strokes. This paper presents a review of the literature and clarifies the causes and risks of stroke in the intensive care unit.

DEVELOPMENT OF A MACHINE LEARNING MODEL FOR PREDICTING 28-DAY MORTALITY OF SEPTIC PATIENTS WITH ATRIAL FIBRILLATION

ABSTRACT

Introduction: Septic patients with atrial fibrillation (AF) are common in the intensive care unit accompanied by high mortality. The early prediction of prognosis of these patients is critical for clinical intervention. This study aimed to develop a model by using machine learning (ML) algorithms to predict the risk of 28-day mortality in septic patients with AF. Methods: In this retrospective cohort study, we extracted septic patients with AF from the Medical Information Mart for Intensive Care III (MIMIC-III) and IV database. Afterward, only MIMIC-IV cohort was randomly divided into training or internal validation set. External validation set was mainly extracted from MIMIC-III database. Propensity score matching was used to reduce the imbalance between the external validation and internal validation data sets. The predictive factors for 28-day mortality were determined by using multivariate logistic regression. Then, we constructed models by using ML algorithms. Multiple metrics were used for evaluation of performance of the models, including the area under the receiver operating characteristic curve, sensitivity, specificity, recall, and accuracy. Results: A total of 5,317 septic patients with AF were enrolled, with 3,845 in the training set, 960 in the internal testing set, and 512 in the external testing set, respectively. Then, we established four prediction models by using ML algorithms. AdaBoost showed moderate performance and had a higher accuracy than the other three models. Compared with other severity scores, the AdaBoost obtained more net benefit. Conclusion: We established the first ML model for predicting the 28-day mortality of septic patients with AF. Compared with conventional scoring systems, the AdaBoost model performed moderately. The model established will have the potential to improve the level of clinical practice.

Prevalence of new-onset atrial fibrillation in hospitalized patients with community-acquired pneumonia: a systematic review and meta-analysis

Community-acquired pneumonia (CAP) is a common lower respiratory tract infection, often complicated by cardiovascular events, including cardiac arrhythmias. New-onset atrial fibrillation (newAF) has been associated with increased mortality in CAP patients, especially in those critically ill; however, limited data on the prevalence of newAF in patients with CAP are available. We aim to estimate the pooled prevalence of newAF and its impact on adverse outcomes in patients with CAP, through a systematic review and meta-analysis. MEDLINE and EMBASE were systematically searched from inception to 27 January 2022. All studies reporting the prevalence of newAF in CAP patients were included and all-cause mortality was extracted when available. The pooled prevalence of newAF, 95% Confidence Intervals (CI), and 95% Prediction Intervals (PI) were computed. The inconsistency index (I²) was calculated to measure heterogeneity. Subgroup analyses were also performed. A protocol for this study was registered on PROSPERO (CRD42022307422). Among 7,655 records retrieved, 10 studies were included, with a total of 280,589 CAP patients. Pooled prevalence of newAF in CAP patients was 7.6% (95% CI 6.4-9.0%, 95% PI 4.3-13.1%, I² = 95%). Subgroup analyses showed no significant differences according to geographical location or study design. Patients with newAF had a higher risk of mortality among the studies included in the systematic review. NewAF is a common complication, occurring in 7.6% of CAP patients, with prediction intervals suggesting an even higher burden. CAP patients who develop newAF during hospitalization may be at higher risk of mortality in both short- and long-term follow-up.

Atrial Fibrillation and Sepsis in Elderly Patients and Their Associaton with In-Hospital Mortality

BACKGROUND

Atrial fibrillation (AF) affects about 2% to 4% of the world population, and in patients hospitalized in intensive care units, this incidence can reach up to 23% in those with septic shock. The impact of AF in patients with sepsis is reflected in worse clinical outcomes, and the identification of the triggering factors can be a target for future prevention and treatment strategies.

OBJECTIVES

To verify the relationship between the development of AF and mortality in patients over 80 years of age included in the sepsis protocol and to identify the risk factors that contribute to the development of AF in this population.

METHODS

Retrospective observational study, with a review of electronic medical records and inclusion of 895 patients aged 80 years or older, included in the sepsis protocol of a high-complexity private hospital in São Paulo, SP, from January 2018 to December 2020. All tests were performed with a significance level of 5%.

RESULTS

The incidence of AF in the sample was 13%. After multivariate analysis, using multiple logistic regression, it was possible to demonstrate an association of mortality, in the studied population, with the SOFA score (odds ratio [OR] 1.21 [1.09 - 1.35]), higher values of C-reactive protein (OR 1.04 [1.01 - 1.06]), need for vasoactive drugs (OR 2.4 [1.38 - 4.18]), use of mechanical ventilation (OR 3.49 [1.82 - 6.71]), and mainly AF (OR 3.7 [2.16 - 6.31]).

CONCLUSION

In very elderly patients (80 years of age and older) with sepsis, the development of AF was shown to be an independent risk factor for in-hospital mortality.

Development and validation of a predictive model for new-onset atrial fibrillation in sepsis based on clinical risk factors

Objective

New-onset atrial fibrillation (NOAF) is a common complication and one of the primary causes of increased mortality in critically ill adults. Since early assessment of the risk of developing NOAF is difficult, it is critical to establish predictive tools to identify the risk of NOAF.

Methods

We retrospectively enrolled 1,568 septic patients treated at Wuhan Union Hospital (Wuhan, China) as a training cohort. For external validation of the model, 924 patients with sepsis were recruited as a validation cohort at the First Affiliated Hospital of Xinjiang Medical University (Urumqi, China). Least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression analyses were used to screen predictors. The area under the ROC curve (AUC), calibration curve, and decision curve were used to assess the value of the predictive model in NOAF.

Results

A total of 2,492 patients with sepsis (1,592 (63.88%) male; mean [SD] age, 59.47 [16.42] years) were enrolled in this study. Age (OR: 1.022, 1.009–1.035), international normalized ratio (OR: 1.837, 1.270–2.656), fibrinogen (OR: 1.535, 1.232–1.914), C-reaction protein (OR: 1.011, 1.008–1.014), sequential organ failure assessment score (OR: 1.306, 1.247–1.368), congestive heart failure (OR: 1.714, 1.126–2.608), and dopamine use (OR: 1.876, 1.227–2.874) were used as risk variables to develop the nomogram model. The AUCs of the nomogram model were 0.861 (95% CI, 0.830–0.892) and 0.845 (95% CI, 0.804–0.886) in the internal and external validation, respectively. The clinical prediction model showed excellent calibration and higher net clinical benefit. Moreover, the predictive performance of the model correlated with the severity of sepsis, with higher predictive performance for patients in septic shock than for other patients.

Conclusion

The nomogram model can be used as a reliable and simple predictive tool for the early identification of NOAF in patients with sepsis, which will provide practical information for individualized treatment decisions.

New Paradigms in Antithrombotic Strategies: A Leap into the Future of Cardiovascular Medicine

During the last decades, significant improvements have changed the landscape of antithrombotic treatment strategies and, more generally, the treatment of thrombotic and cardiovascular diseases [...].