Materiały źródłowe

• #1 Arrhythmia: Symptoms & Treatment

  https://my.clevelandclinic.org/health/diseases/16749-arrhythmia

  An arrhythmia is a heart rhythm that isnt normal. The prognosis varies greatly depending on the type. […] Some types of arrhythmia are harmless and dont require treatment. Others can put you at risk for cardiac arrest. […] Depending on the type of cardiac arrhythmia you have, you may have mild or severe symptoms or none at all. You may not need treatment, but some people need medicine or a procedure. With heart arrhythmia treatment, many people can live full lives. Some people with more serious arrhythmias have a cardiac arrest and may or may not survive. […] Harmless arrhythmias go away and come back in response to what triggers them. However, people with other types of arrhythmias especially those that put you at risk for cardiac arrest need treatment for the rest of their lives.

• #2 Atrial Fibrillation: Prognosis, Life Expectancy

  https://www.webmd.com/heart-disease/atrial-fibrillation/atrial-fibrillation-prognosis-life-expectancy

  When your doctor diagnoses you with atrial fibrillation (AFib), you might wonder what to expect. Your prognosis is a prediction of how your disease could affect you in the future and how long you might live. […] Untreated AFib can raise your risk for problems like a heart attack, stroke, and heart failure, which could shorten your life expectancy. But treatments and lifestyle changes can help prevent these problems and manage your risks. […] Many things affect your AFib prognosis, including your age, health, and what medicines you take. […] If you have a health condition like diabetes, obesity, or high blood pressure, your outcome may be worse than someone who doesn’t have other health issues. […] Medications to control your heart rate and blood thinners to prevent blood clots can help you avoid AFib complications. These treatments could improve your prognosis.

• #3 Predicting factors, incidence and prognosis of cardiac arrhythmia in medical, non-acute coronary syndrome, critically ill patients – PubMed

  https://pubmed.ncbi.nlm.nih.gov/23590048/

  Cardiac arrhythmia is an important complication of critically ill patients, especially in perioperative period and early after myocardial infarction. […] To identify the predictive factors, incidence, and prognosis of tachyarrhythmia and bradyarrhythmia in non-coronary critically ill medical patients. […] The incidence of arrhythmia was 39.7%. […] The presence of arrhythmia, especially ventricular fibrillation, symptomatic sinus bradycardia and junctional bradycardia in medical ICU is associated with higher hospital mortality (bradyarrhythmia 88.7%, tachyarrhythmia 66.70%) than the absent group (18.1%, p 0.001). […] Arrhythmia is a serious complication of medical critically ill patients and associated with high mortality rate.

• #4 Arrhythmic sudden death survival prediction using deep learning analysis of scarring in the heart

  https://pmc.ncbi.nlm.nih.gov/articles/PMC9022904/

  Sudden cardiac death from arrhythmia is a major cause of mortality worldwide. […] The DL-predicted survival curves offer accurate predictions at times up to 10 years and allow for estimation of uncertainty in predictions. […] This technology has the potential to transform clinical decision-making by offering accurate and generalizable predictions of patient-specific survival probabilities of arrhythmic death over time. […] A robust, generalizable SCDA risk stratifier with the ability to predict individualized, patient-specific risk trajectories and confidence estimates could significantly enhance clinical decision-making. […] SSCAR uses the data to directly estimate uncertainty in its predictions. […] Therefore, SSCAR has the potential to significantly shape clinical decision-making regarding arrhythmia risk, offering not a simple at risk/not at risk prediction, but instead, an estimate of the time to SCDA together with a sense of how certain the model is about each predicted TSCDA.

• #5 Arrhythmic sudden death survival prediction using deep learning analysis of scarring in the heart | Nature Cardiovascular Research

  https://www.nature.com/articles/s44161-022-00041-9

  Sudden cardiac death from arrhythmia is a major cause of mortality worldwide. […] The DL-predicted survival curves offer accurate predictions at times up to 10 years and allow for estimation of uncertainty in predictions. […] This technology has the potential to transform clinical decision-making by offering accurate and generalizable predictions of patient-specific survival probabilities of arrhythmic death over time. […] A robust, generalizable SCDA risk stratifier with the ability to predict individualized, patient-specific risk trajectories and confidence estimates could considerably enhance clinical decision-making. […] Our approach, which we term Survival Study of Cardiac Arrhythmia Risk (SSCAR), embeds, within a survival model, neural networks to estimate individual patient times to SCDA.

• #6 Arrhythmic sudden death survival prediction using deep learning analysis of scarring in the heart

  https://pmc.ncbi.nlm.nih.gov/articles/PMC9022904/

  SSCAR was developed and internally validated using data from 156 patients with ischemic cardiomyopathy (ICM) enrolled in the Left Ventricle Structural Predictors of SCD (LVSPSCD) prospective observational study. […] SSCAR has excellent concordance on the internal set (.82.89) for all times up to 10 years. […] The model maintains its risk discrimination abilities at all times, as further evidenced by the high areas under the receiver operator characteristic (ROC) curves evaluated at years 29. […] SSCAR predicts cause-specific survival curves for each patient through two individualized parameters: the location and scale, characterizing the probability distribution of TSCDA. […] The predicted location parameter estimates the most probable TSCDA and the predicted scale parameter provides a measure of confidence for the location.

• #7 Arrhythmic sudden death survival prediction using deep learning analysis of scarring in the heart | Nature Cardiovascular Research

  https://www.nature.com/articles/s44161-022-00041-9

  The predicted patient-specific survival curves offer accurate SCDA probabilities at all times up to 10 years. […] SSCAR has excellent concordance on the internal set (.82.89) for all times up to 10 years. […] SSCAR performance carries over well to the external cohort, resulting in a c-index of 0.710.77 and \(\overline{\,{{\mbox{Bs}}}\,}\) of 0.030.14. […] The predicted location parameter estimates the most probable TSCDA, and the predicted scale parameter provides a measure of confidence for the location. […] SSCARs predicted patient-specific survival curves offer accurate SCDA probabilities at all times up to 10 years. […] SSCAR represents innovation in CMR imaging feature extraction and learning of non-linear relationships among standard clinical covariates.

• #8 Arrhythmic sudden death survival prediction using deep learning analysis of scarring in the heart | Nature Cardiovascular Research

  https://www.nature.com/articles/s44161-022-00041-9

  The technology aims to transform clinical decision-making regarding arrhythmia risk and patient prognosis by encouraging practitioners to eschew the view of predicted risk as a single number outputted by a black-box algorithm but, rather, to be guided by the estimated time-to-outcome in the context of patient-specific time prediction uncertainty.

• #9 Arrhythmic sudden death survival prediction using deep learning analysis of scarring in the heart

  https://pmc.ncbi.nlm.nih.gov/articles/PMC9022904/

  SSCAR achieves performance that is beyond the state-of-the-art in both relative terms SCDA risk ordering among patients as well as absolute accurately calibrated probabilities of SCDA. […] SSCAR represents innovation in CMR imaging feature extraction and learning of nonlinear relationships between standard clinical covariates. […] The technology aims to transform clinical decision-making regarding arrhythmia risk and patient prognosis by encouraging practitioners to eschew the view of predicted risk as a single number outputted by a black-box algorithm, but rather be guided by the estimated time-to-outcome in the context of patient-specific time prediction uncertainty.

• #10 Internationally validated score to predict the outcome of non-paroxysmal atrial fibrillation ablation: the ‘FLAME score’ | Open Heart

  https://openheart.bmj.com/content/8/2/e001653

  The clinical effectiveness of ablating non-paroxysmal atrial fibrillation (non-PAF) relies on proper patient selection. We developed and validated a scoring system to predict non-PAF ablation outcomes. […] The FLAME score was applied to data (882 non-PAF ablations) at a Californian centre, and predicted the outcome of both single (p0.0001) and multiple (p0.0001) procedures. […] FLAME score is easily calculated, derived in London, and predicted single and multiple procedural outcomes for non-PAF ablations in California. In patients with a high score, even multiple procedures are usually ineffective. […] The Female, Long-lasting, Atrial diameter, Mitral, Extreme score is the first outcome prediction tool focusing only on the non-PAF population undergoing catheter ablation. […] The score can stratify patients both for first and multiprocedural outcomes after catheter ablation.

• #11 Internationally validated score to predict the outcome of non-paroxysmal atrial fibrillation ablation: the ‘FLAME score’ | Open Heart

  https://openheart.bmj.com/content/8/2/e001653

  The clinically challenging and thereby pertinent cohort of non-PAF patients would benefit from a validated outcome prediction score used before embarking on a journey of ablative therapy. […] Patients with high scores had reduced success rates following their first procedure, and their final procedure, with fewer maintaining sinus rhythm despite undergoing more repeat procedures than patients with lower scores. […] The FLAME score is the first cohort-specific (non-PAF) outcome prediction score for patients undergoing radiofrequency ablation. […] The variables we found independently associated with the outcome are intuitively understandable and consistent with existing literature. […] Our results showed that with FLAME scores 04, patients could obtain good long-term results with a mean of 1.5 procedures.

• #12

  https://link.springer.com/article/10.1007/s11517-022-02713-x

  Methods for characterization of atrial fibrillation (AF) episode patterns have been introduced without establishing clinical significance. […] This study investigates, for the first time, whether post-ablation recurrence of AF can be predicted by evaluating episode patterns. […] The risk of AF recurrence after catheter ablation using the Hawkes parameters log(mu) and beta1, AF burden, and AF density was evaluated. […] The combination of log(mu) and beta1 is related to a hazard ratio of 1.95 (1.033.70; p0.05). […] The Hawkes parameters showed increased risk of AF recurrence within 1 year after the procedure for patients with high AF dominance and high episode aggregation and may be used for pre-ablation risk assessment. […] The risk of AF recurrence for the Hawkes parameters was found to have an HR of 1.95 (95% CI, 1.033.70; p0.05). […] The proposed parameter combination is related to increased risk of AF recurrence within 1 year of the procedure for patients with more dominant AF and more episode aggregation.

• #13 Higher heart rate variability as a predictor of atrial fibrillation in patients with hypertension | Scientific Reports

  https://www.nature.com/articles/s41598-022-07783-3

  The main finding of this study was that higher HRV in patients with hypertension could predict the development of AF independent of demographics or known cardiovascular risk factors. […] Our findings suggest that higher HRV representing abnormal autonomic fluctuation is associated with a higher risk of AF development. […] Higher HRV parameters including high-frequency (P0.001), the square root of the mean squared differences of successive NN intervals (P0.001), and the percentage of NN intervals that are more than 50 ms different from the previous interval (P0.001) were associated with the occurrence of AF in univariate analysis. […] In Cox regression analysis, higher HRV (representing excessive autonomic fluctuation) was an independent risk factor for AF. […] Higher HF, rMSSD, and pNN50 in patients with hypertension as surrogate markers for excessive autonomic fluctuation could predict the occurrence of AF.

• #14 Association between programmed electrical stimulation inducibility and arrhythmic risk in hypertrophic cardiomyopathy: a systematic review and meta-analysis | Heart

  https://heart.bmj.com/content/early/2025/04/16/heartjnl-2024-325043

  PES inducibility is associated with a 10 times higher risk of MAE in patients with HCM. […] This systematic review and meta-analysis demonstrate that PES inducibility is strongly associated with a more than 10-times increased risk of major arrhythmic events in patients with HCM. […] These findings suggest that PES could have a role in refining risk stratification strategies for HCM, particularly for intermediate-risk patients. […] Our analysis provides evidence of an association between PES inducibility in patients with HCM and the occurrence of arrhythmic events in primary prevention, with an estimated 10 times higher risk.

• #15 Postoperative atrial fibrillation (POAF) after cardiac surgery: clinical practice review – Suero – Journal of Thoracic Disease

  https://jtd.amegroups.org/article/view/83529/html

  Postoperative atrial fibrillation (POAF) after cardiac surgery is associated with elevated morbidity and mortality. […] Although current prediction models have limited efficacy, several perioperative interventions can reduce patients risk of POAF. […] Decision-making regarding anticoagulation should recognize that the stroke risk associated with POAF appears to be lower than that for general nonvalvular AF. […] The long-term stroke risk was examined by Wang et al. in a systematic review and meta-analysis of 55 studies and 540,209 patients who underwent cardiac surgery. […] In addition, paroxysmal AF progresses to permanent AF in an estimated 25% of patients over 5-10 years; patients who develop POAF have a 5-fold greater risk of long-term AF than no-POAF patients. […] The findings of the CTSNet trial are further confirmed by a systematic review by Ahmed et al. of eight RCTs and 990 patients that compared rate versus rhythm control. […] The recommendations found in various national and international societal guidelines echo the discrepancies in practice for POAF management, emphasizing the importance of an individualized approach for each patient.

• #16 Predicting in-hospital mortality in patients with heart failure combined with atrial fibrillation using stacking ensemble model: an analysis of the medical information mart for intensive care IV (MIMIC-IV) | BMC Medical Informatics and Decision Making | F

  https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-024-02829-0

  Heart failure (HF) and atrial fibrillation (AF) usually coexist and are associated with a poorer prognosis. This study aimed to develop a model to predict in-hospital mortality in patients with HF combined with AF. […] Therefore, early identification of the risk of mortality in patients with HF combined with AF is important for disease management and burden reduction. […] The stacking ensemble model showed a good predictive effect in predicting in-hospital mortality in patients with HF combined with AF and may provide clinicians with a reference tool for early identification of mortality risk. […] Patients with HF combined with AF tend to have a poorer prognosis. This study constructed a model to predict in-hospital mortality in patients with HF combined with AF using four single models and the stacking ensemble model, respectively.

• #17 Predicting in-hospital mortality in patients with heart failure combined with atrial fibrillation using stacking ensemble model: an analysis of the medical information mart for intensive care IV (MIMIC-IV) | BMC Medical Informatics and Decision Making | F

  https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-024-02829-0

  The AUC of the stacking ensemble model was superior to that of the four single models, with AUCs of 0.837 and 0.768 for the training set and testing set, respectively. […] The stacking ensemble model may provide a reference for a true mortality risk assessment tool in clinical practice among patients with HF combined with AF.

• #18 Development of a multidimensional prediction model for long-term prognostic risk in patients with acute coronary syndromes after percutaneous coronary intervention: A retrospective observational cohort study | PLOS One

  https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0318445

  The aim of this study is to examine the critical variables that impact the long-term prognosis of patients with acute coronary syndrome (ACS) after percutaneous coronary intervention (PCI) and to create a multidimensional predictive risk assessment model that can serve as a theoretical basis for accurate cardiac rehabilitation. […] We found white blood cell count (WBC) (OR: 4.110) and the effective average number of daily steps (ANS) (OR: 2.689) as independent prognostic risk factors for acute myocardial infarction (AMI). The independent risk factors for unstable angina prognosis were white blood cell count (OR: 6.257), VO2 at anaerobic threshold (OR: 4.294), and effective autonomic nervous system function (OR: 4.097). […] This study developed a multimodal predictive model that integrates the inflammatory response after onset, physical performance and exercise tolerance before discharge, and daily activity after discharge to predict the long-term prognosis of patients with ACS. The multidimensional model is more effective than the single-factor model for assessing risk in ACS patients.

• #19 Development of a multidimensional prediction model for long-term prognostic risk in patients with acute coronary syndromes after percutaneous coronary intervention: A retrospective observational cohort study | PLOS One

  https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0318445

  This study found that the inflammatory response after onset, physical performance and exercise tolerance before discharge, and daily activity after discharge were the independent risk factors for predicting the long-term prognosis of patients with ACS. The multidimensional prognostic model to risk-stratify for the patients with ACS, was better than the single factor model. This study also provides a theoretical basis that the prognosis of potentially high-risk patients can be improved by precise and rational exercise prescription.

• #20 Distinguishing Potentially Lethal from Benign Arrhythmias | SpringerLink

  https://link.springer.com/chapter/10.1007/978-3-642-73666-7_6

  Benign cardiac arrhythmias are those which cause neither symptoms nor haemodynamic upset and which have no prognostic significance. […] Prognostically important arrhythmias are more complex. The basic arrhythmia is often a transient disturbance of which the patient is unaware and it is the underlying cardiovascular pathology which is the major determinant of prognosis. The majority of prognostically important arrhythmias are merely markers of risk and do not in themselves jeopardize life.

• #21 Predicting Atrial Fibrillation Treatment Outcome with Siamese Multi-modal Fusion and Cardiac Digital Twins | OpenReview

  https://openreview.net/forum?id=hV2WtoJKGp

  Atrial fibrillation, the most common heart rhythm disorder, presents challenges in treatment due to difficulty pinpointing the patient-specific regions of abnormal electrical activity. […] By accurately predicting freedom from atrial fibrillation, our pipeline paves the way for personalized atrial fibrillation therapy with a fast and precise selection of optimal treatments.

• #22 Atrial Fibrillation: Prognosis, Life Expectancy

  https://www.webmd.com/heart-disease/atrial-fibrillation/atrial-fibrillation-prognosis-life-expectancy

  AFib does raise the risk of dying early. Heart failure and stroke are two of the main causes of death in people with AFib. But with improved treatments, overall deaths from AFib have dropped. […] There arent life expectancy statistics for people with AFib. For a personalized prognosis, ask your doctor what you can expect and what treatments and lifestyle changes can help.

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