Materiały źródłowe

• #1 Survival of people with valvular heart disease in a large, English community-based cohort study | Heart

  https://heart.bmj.com/content/107/16/1336

  Valvular heart disease (VHD) is present in half the population aged 65 years but is usually mild and of uncertain importance. […] In adjusted analyses, neither mild VHD (prevalence 44.9%) nor clinically significant VHD (moderate or severe stenosis or regurgitation; 5.2%) was associated with increased all-cause mortality (HR 1.20, 95%CI 0.96 to 1.51 and HR 1.47, 95%CI 0.94 to 2.31, respectively). […] Advanced aortic sclerosis or MAC is associated with a worse outcome, particularly for patients with significant VHD, but also in the absence of other VHD. […] Older patients with mild VHD can be reassured about their prognosis. […] The absence of an association between significant VHD and mortality may reflect its relatively low prevalence in our cohort. […] Mortality was highest for people with both clinically significant VHD and advanced aortic sclerosis or MAC (HR 4.38, 95%CI 1.99 to 9.67).

• #2 Survival of people with valvular heart disease in a large, English community-based cohort study | Heart

  https://heart.bmj.com/content/107/16/1336

  Advanced aortic sclerosis (HR 2.05, 95%CI 1.28 to 3.30) and MAC (HR 2.51, 95%CI 1.41 to 4.49) remained associated with all-cause mortality, independent of other VHD phenotypes. […] Mild VHD was common but not associated with an increased risk of all-cause mortality, thereby providing important reassurance to many patients.

• #3 Machine Learning Prediction for Prognosis of Patients With Aortic Stenosis

  https://pmc.ncbi.nlm.nih.gov/articles/PMC11450950/

  Aortic valve stenosis of any degree is associated with poor outcomes. […] The authors aimed to develop a risk prediction model for aortic stenosis (AS) prognosis using machine learning techniques. […] The composite outcome included aortic valve replacement or mortality. […] In patients with AS, a machine learning algorithm predicts outcomes with good accuracy, and prognostic characteristics were identified. […] The model can potentially guide risk factor modification and clinical decisions to improve patient prognosis. […] The median follow-up of the primary cohort was 48 (21-87) months. During this period, 1,116 patients underwent AVR, and 5,069 patients died. […] Among others, moderate (hazard ratio: 1.57; 95% CI: 1.38-1.52; P 0.001) and severe (hazard ratio: 2.50; 95% CI: 2.32-2.70; P 0.001) AS were 2 of the most relevant predictors of outcome.

• #4 Machine Learning Prediction for Prognosis of Patients With Aortic Stenosis

  https://pmc.ncbi.nlm.nih.gov/articles/PMC11450950/

  The RSF model showed an area under the curve (AUC) of 0.83 (95% CI: 0.80-0.86) and 0.83 (95% CI: 0.81-0.84) to predict the composite outcome at 1 and 5 years, respectively. […] The developed algorithm exhibited good diagnostic accuracy. When tested on external cohorts, the diagnostic accuracy remained good, albeit slightly lower compared to the primary cohort. […] Using advanced ML methods, we have developed an algorithm that accurately predicts patient outcomes across all grades of AS while identifying crucial prognosis-related variables.

• #5 Predicting mortality after transcatheter aortic valve replacement using preprocedural CT | Scientific Reports

  https://www.nature.com/articles/s41598-024-63022-x

  Transcatheter aortic valve replacement (TAVR) is a widely used intervention for patients with severe aortic stenosis. Identifying high-risk patients is crucial due to potential postprocedural complications. […] Our model demonstrates an AUROC of 0.725 for predicting all-cause mortality during postprocedure follow-up on a cohort of 1449 TAVR patients. […] Thus, these findings underscore the potential of the proposed model in automatically analyzing CT volumes and integrating them with patient characteristics for predicting mortality after TAVR. […] In this study, we define the outcome as all-cause mortality during the postprocedural follow-up period. […] Across all patients, the two output classes are fairly balanced: 44% of patients passed away during follow-up (class 1) and 56% survived (class 0).

• #6 Predicting mortality after transcatheter aortic valve replacement using preprocedural CT | Scientific Reports

  https://www.nature.com/articles/s41598-024-63022-x

  Our model delivers a prediction within 5 to 20 seconds on a consumer CPU depending on the number of missing variables allowing patient assessment with minimal manual labor. […] The results in Table 2 confirm that our automatic feature extraction can replace manually extracted image measurements without forfeiting prediction accuracy, which is an important and surprising point. […] Our model only resorts to manual image measurements J when the unprocessed image I is missing (for 49% of patients in our data set). […] The manually extracted features are complex measurements that integrate clinical experience and medical knowledge. However, extracting such features for every patient can create a bottleneck during preprocedural patient assessment. […] The proposed probabilistic model is built on the assumption of predictor independence. […] Before using the presented model to guide treatment decisions, its performance should thus be evaluated on a separate, independent patient registry.

• #7 Predicting in-hospital mortality after transcatheter aortic valve replacement using administrative data and machine learning | Scientific Reports

  https://www.nature.com/articles/s41598-023-37358-9

  Transcatheter aortic valve replacement (TAVR) is the gold standard treatment for patients with symptomatic aortic stenosis. […] This study examined whether statistical/machine learning models trained with solely preoperative information encoded in the administrative National Inpatient Sample database could accurately predict in-hospital outcomes (death/survival) post-TAVR. […] The overarching goal of this study was to examine whether the preoperative information encoded in the administrative NIS database could accurately predict in-hospital death/survival after transcatheter aortic valve replacement (TAVR), which is the gold standard treatment for patients with severe symptomatic aortic stenosis. […] This study demonstrated the feasibility of using solely the preoperative information available in administrative data to accurately predict in-hospital mortality post-TAVR. […] Our study illustrates that administrative data can be used to predict and/or risk adjust complex medical procedures, such as TAVR, without the need for frequent retraining.

• #8 Clinical Prediction Models for Valvular Heart Disease

  https://pmc.ncbi.nlm.nih.gov/articles/PMC6818049/

  While many clinical prediction models (CPMs) exist to guide valvular heart disease treatment decisions, the relative performance of these CPMs is largely unknown. […] Only 35 (71%) CPMs have been externally validated. […] Nearly two-thirds of validations (n=129) demonstrate at least a 10% relative decline in discrimination. […] For surgical valve interventions, there are existing predictive models that perform reasonably well on related populations. […] For transcatheter aortic valve replacement (CPMs additional external validations are needed to broadly understand the trustworthiness of predictions. […] Risk prediction is central to decision making for patients with advanced valvular heart disease; however, the performance of clinical predictive models in external validations is often substantially worse than expected based on derivation data set performance.

• #9 Clinical Prediction Models for Valvular Heart Disease

  https://pmc.ncbi.nlm.nih.gov/articles/PMC6818049/

  Isolated external validations appear insufficient to broadly understand the performance of valvular heart disease clinical predictive models. […] The trustworthiness of transcatheter aortic valve replacement predictions is largely unknown as these models have not been widely tested in external validations. […] For the CPMs that have been externally validated, models often perform substantially worse than expected based on performance in derivation data sets. […] The fidelity of TAVR CPM predictions is largely unknown, as these models have not been widely tested in external validations. […] The decrease in discrimination that is observed in this study may be attributable to model overfitting, differences in case mix (ie, narrower populations in the validation data set), and phenotypic heterogeneity.

• #10 Clinical Prediction Models for Valvular Heart Disease

  https://pmc.ncbi.nlm.nih.gov/articles/PMC6818049/

  This strongly suggests that adequate performance demonstrated in a single external validation may be insufficient to assess the quality (and utility) of VHD CPMs and that a more tailored approach is needed to understand the trustworthiness of CPM predictions in specific settings. […] There are no CPMs for patients treated with TAVR that demonstrate good performance across multiple related validation databases.

• #11 A review of outcome following valve surgery for rheumatic heart disease in Australia | BMC Cardiovascular Disorders | Full Text

  https://bmccardiovascdisord.biomedcentral.com/articles/10.1186/s12872-015-0094-1

  Outcome of 1384 RHD and 15843 non-RHD valve procedures was analysed. […] Mortality following RHD surgery at 30 days was 3.1 % (95 % CI 2.2 4.3), 5 years 15.3 % (11.7 19.5) and 10 years 25.0 % (10.7 44.9). […] Mortality following non-RHD surgery at 30 days was 4.3 % (95 % CI 3.9 – 4.6), 5 years 17.6 % (16.4 – 18.9) and 10 years 39.4 % (33.0 – 46.1). […] Factors independently associated with poorer longer term survival following RHD surgery included older age (OR1.03/additional year, 95 % CI 1.01 1.05), concomitant diabetes (OR 1.7, 95 % CI 1.1 2.5) and chronic kidney disease (1.9, 1.2 2.9), longer invasive ventilation time (OR 1.7 if greater than median value, 1.1 2.9) and prolonged stay in hospital (1.02/additional day, 1.01 1.03). […] Survival in Indigenous Australians was comparable to that seen in non-Indigenous Australians.

• #12 A review of outcome following valve surgery for rheumatic heart disease in Australia | BMC Cardiovascular Disorders | Full Text

  https://bmccardiovascdisord.biomedcentral.com/articles/10.1186/s12872-015-0094-1

  In a large prospective cohort study we have demonstrated survival following RHD valve surgery in Australia is comparable to earlier studies. […] Patients with diabetes and chronic kidney disease, were at particular risk of poorer long-term survival. […] Unlike earlier studies we did not find pre-existing atrial fibrillation, being an Indigenous Australian or the nature of the underlying valve lesion were independent predictors of survival. […] Thirty day mortality following RHD valve surgery in Indigenous Australians was comparable to that seen in non-Indigenous Australians (2.9 % compared with 3.1 %, p=0.895). […] Longer term mortality following RHD surgery was also comparable in Indigenous and non-Indigenous patients (10.3 % compared with 11.5 %, p=0.657). […] Three factors were independently associated with longer term mortality in Indigenous Australians using Cox proportional modelling: LVEF 30 % (HR 31.3, 95 % CI 7.0 142.9), a longer period of ventilation (1.04/additional hour, 95 % CI 1.01 1.07), and a shorter initial stay in hospital (0.5/additional day, 95 % CI 0.3 0.8). […] Of note was, once these factors were controlled for, the superior longer term survival associated with RHD was no longer present. […] This study highlights that survival following valve surgery in the short (30 days) and longer term is equivalent in RHD and non-RHD patients.

• #13 Characterization and outcome analysis of cardiac valve surgery for infective endocarditis | REC: CardioClinics

  https://www.reccardioclinics.org/en-characterization-outcome-analysis-cardiac-valve-articulo-S2605153222000383

  Evaluating the effect of cardiac valve surgery in the context of infective endocarditis (IE), an uncommon and still deadly disease, can be particularly advantageous in whole-nation population-based studies. […] The in-hospital all-cause postoperative mortality rate was 15.6%. Factors associated with in-hospital mortality were female sex, liver, kidney and coronary disease, valve prosthesis, Staphylococcus spp, acute renal failure and sepsis. […] This analysis identified factors associated with worse outcome in surgically managed patients with IE in Portugal. Appropriate early identification of surgical stratification markers that may influence the overall prognosis in IE is crucial in the real world clinical setting. […] Factors associated with in-hospital heart valve surgery in IE were: age (patients younger than 60 years old were most likely to undergo surgery), previous heart valve disease, congenital heart disease, infectious agent Streptococcus spp, the presence of complications such as heart failure, systemic embolism, or acute renal failure. […] Female patients, patients with previous coronary, renal, or liver chronic disease, cardiac valve prosthesis, infection with Staphylococcus spp, acute renal failure, and the presence of sepsis had higher odds of in-hospital mortality.

• #14 Heart Valve Disease: Symptoms & Treatment

  https://my.clevelandclinic.org/health/diseases/17639-what-you-need-to-know-heart-valve-disease

  If you have heart valve disease, you’ll have it for your whole life. But your experience of heart valve disease depends on the valve affected and the severity of the problem. […] Some people may have valve disease and never experience any symptoms. Others may have many symptoms and need a valve repair or replacement. Even if your healthcare provider repairs or replaces your valve, you’ll still need to take medicine and possibly have another replacement in 10 or 15 years. […] It’s important to follow up regularly with a healthcare provider to monitor the progression of your valve disease over time.

• #15 Understanding Your Heart Valve Treatment Options | American Heart Association

  https://www.heart.org/en/health-topics/heart-valve-problems-and-disease/understanding-your-heart-valve-treatment-options

  Recovery statistics are very good for people who receive proper treatment. […] Heart valve disease is usually progressive. The outlook for those who receive no treatment can be poor. But many who do receive treatment go on to live very full and healthy lives, especially when their cardiovascular risks are otherwise low. […] Evidence is also clear that, with proper treatment, most people enjoy an improvement in health and quality of life. […] But once you begin to experience symptoms such as angina (chest pain), syncope (fainting or sudden loss of consciousness) and dyspnea (breathing difficulty or discomfort), life expectancy and quality of life can decline.

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