Objectives: The aim of this study was to assess the predictive value of PMA measurement for mortality. Background: Current surgical risk stratification have limited predictive value in the transcatheter aortic valve implantation (TAVI) population. In TAVI workup, a CT scan is routinely performed but body composition is not analyzed. Psoas muscle area (PMA) reflects a patient's global muscle mass and accordingly PMA might serve as a quantifiable frailty measure. Methods: Multi-slice computed tomography scans (between 2010 and 2016) of 583 consecutive TAVI patients were reviewed. Patients were divided into equal sex-specific tertiles (low, mid, and high) according to an indexed PMA. Hazard ratios (HR) and their confidence intervals (CI) were determined for cardiac and all-cause mortality after TAVI. Results: Low iPMA was associated with cardiac and all-cause mortality in females. One-year adjusted cardiac mortality HR in females for mid-iPMA and high-iPMA were 0.14 [95%CI, 0.05–0.45] and 0.40 [95%CI, 0.15–0.97], respectively. Similar effects were observed for 30-day and 2-years cardiac and all-cause mortality. In females, adding iPMA to surgical risk scores improved the predictive value for 1-year mortality. C-statistics changed from 0.63 [CI = 0.54–0.73] to 0.67 [CI: 0.58–0.75] for EuroSCORE II and from 0.67 [CI: 0.59–0.77] to 0.72 [CI: 0.63–0.80] for STS-PROM. Conclusions: Particularly in females, low iPMA is independently associated with an higher all-cause and cardiac mortality. Prospective studies should confirm whether PMA or other body composition parameters should be extracted automatically from CT-scans to include in clinical decision making and outcome prediction for TAVI.
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BACKGROUND: The COVID-19 pandemic has led to a national lockdown in the Netherlands, which also affected transcatheter aortic valve implantation (TAVI) patients. The objective of the study was to describe physical activity, dietary intake and quality of life (QoL) in patients on the waiting list for TAVI pre-lockdown and during lockdown.METHODS: Consecutive patients awaiting TAVI at the Amsterdam University Medical Centers, the Netherlands were included. Measurements were self-reported effect of lockdown, physical activity, dietary intake and QoL.RESULTS: In total, 58 patients (median age 80, interquartile range (IQR) 76-84, 45% female) were observed pre-lockdown and 16 patients (median age 78, IQR 76-82, 25% female) during lockdown. Ten of the 16 patients during lockdown reported a decline in physical activity. However, we observed a median number of 5861 steps a day (IQR 4579-7074) pre-lockdown and 8404 steps a day (IQR 7653-10,829) during lockdown. Median daily protein intake was 69 g (IQR 59-82) pre-lockdown and 90 g (IQR 68-107) during lockdown. Self-rated health on a visual analogue scale was 63 points (IQR 51-74) pre-lockdown and 73 points (IQR 65-86) during lockdown.CONCLUSIONS: More than half of the patients during lockdown reported less physical activity, while we observed a higher number of steps a day, a similar dietary intake and a higher QoL. Therefore, patients on the TAVI waiting list appeared to be able to cope with the lockdown measures.
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BACKGROUND & AIMS: Diagnosed prevalence of malnutrition and dietary intake are currently unknown in patients with severe aortic stenosis planned to undergo Transcatheter Aortic Valve Implantation (TAVI). This study describes the preprocedural nutritional status, protein intake and diet quality.METHODS: Consecutive preprocedural TAVI patients were asked to participate in this explorative study. Nutritional status was diagnosed with the global leadership initiative on malnutrition (GLIM) criteria. Preprocedural protein intake and diet quality were assessed with a three-day dietary record. To increase the record's validity, a researcher visited the participants at their homes to confirm the record. Protein intake was reported as an average intake of three days and diet quality was assessed using the Dutch dietary guidelines (score range 0-14, 1 point for adherence to each guideline).RESULTS: Of the included patients (n = 50, median age 80 ± 5, 56% male) 32% (n = 16) were diagnosed with malnutrition. Patients diagnosed with malnutrition had a lower protein intake (1.02 ± 0.28 g/kg/day vs 0.87 ± 0.21 g/kg/day, p = 0.04). The difference in protein intake mainly took place during lunch (20 ± 13 g/kg vs 13 ± 7 g/kg, p = 0.03). Patients adhered to 6.4 ± 2.2 out of 14 dietary guidelines. Adherence to the guideline of whole grains and ratio of whole grains was lower in the group of patients with malnutrition than in patients with normal nutritional status (both 62% vs 19%, p = 0.01). In a multivariate analysis diabetes mellitus was found as an independent predictor of malnutrition.CONCLUSION: Prevalence of malnutrition among TAVI patients is very high up to 32%. Patients with malnutrition had lower protein and whole grain intake than patients with normal nutritional status. Furthermore, we found diabetes mellitus as independent predictor of malnutrition. Nutrition interventions in this older patient group are highly warranted.
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It is suggested that older patients waiting for an elective surgical procedure have a poor nutritional status and low physical activity level. It is unknown if this hypothesis is true and if these conditions improve after a medical procedure. We aimed to determine the trajectory of both conditions before and after transcatheter aortic valve implantation (TAVI). Included patients (n = 112, age 81 ± 5 years, 58% male) received three home visits (preprocedural, one and six months postprocedural). Nutritional status was determined with the mini nutritional assessment-short form (MNA-SF) and physical activity using an ankle-worn monitor (Stepwatch). The median MNA-SF score was 13 (11-14), and 27% of the patients were at risk of malnutrition before the procedure. Physical activity was 6273 ± 3007 steps/day, and 69% of the patients did not meet the physical activity guidelines (>7100 steps/day). We observed that nutritional status and physical activity did not significantly change after the procedure (β 0.02 [95% CI -0.03, 0.07] points/months on the MNA-SF and β 16 [95% CI -47, 79] steps/month, respectively). To conclude, many preprocedural TAVI patients should improve their nutritional status or activity level. Both conditions do not improve naturally after a cardiac procedure.
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PurposeThe majority of older patients, scheduled for a cardiac procedure, do not adhere to international dietary intake and physical activity guidelines. The purpose of this study was to explore barriers and facilitators regarding dietary intake and physical activity behaviour change in older patients undergoing transcatheter aortic valve implantation (TAVI).MethodsWe conducted a qualitative study using semi-structured interviews with patients undergoing TAVI. Interviews were analysed by two independent researchers using thematic analysis, the capability, opportunity and motivation behaviour model was used as a framework.ResultsThe study included 13 patients (82 ± 6 years old, 6 females) until data saturation was reached. Six themes were identified, which were all applicable to both dietary intake and physical activity. Three following themes were identified as barriers: (1) low physical capability, (2) healthy dietary intake and physical activity are not a priority at an older age and (3) ingrained habits and preferences. Three following themes were identified as facilitators: (1) knowledge that dietary intake and physical activity are important for maintaining health, (2) norms set by family, friends and caregivers and (3) support from the social environment.ConclusionOur study found that older patients had mixed feelings about changing their behaviour. The majority initially stated that dietary intake and physical activity were not a priority at older age. However, with knowledge that behaviour could improve health, patients also stated willingness to change, leading to a state of ambivalence. Healthcare professionals may consider motivational interviewing techniques to address this ambivalence.
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BACKGROUND: A significant number of older patients planned for transcatheter aortic valve implantation (TAVI) experience a decline in physical functioning and death, despite a successful procedure.OBJECTIVE: To systematically review the literature on the association of preprocedural muscle strength and physical performance with functional decline or long-term mortality after TAVI.METHODS: We followed the PRISMA guidelines and pre-registered this review at PROSPERO (CRD42020208032). A systematic search was conducted in MEDLINE and EMBASE from inception to 10 December 2021. Studies reporting on the association of preprocedural muscle strength or physical performance with functional decline or long-term (>6 months) mortality after the TAVI procedure were included. For outcomes reported by three or more studies, a meta-analysis was performed.RESULTS: In total, two studies reporting on functional decline and 29 studies reporting on mortality were included. The association with functional decline was inconclusive. For mortality, meta-analysis showed that low handgrip strength (hazard ratio (HR) 1.80 [95% confidence interval (CI): 1.22-2.63]), lower distance on the 6-minute walk test (HR 1.15 [95% CI: 1.09-1.21] per 50 m decrease), low performance on the timed up and go test (>20 s) (HR 2.77 [95% CI: 1.79-4.30]) and slow gait speed (<0.83 m/s) (HR 2.24 [95% CI: 1.32-3.81]) were associated with higher long-term mortality.CONCLUSIONS: Low muscle strength and physical performance are associated with higher mortality after TAVI, while the association with functional decline stays inconclusive. Future research should focus on interventions to increase muscle strength and physical performance in older cardiac patients.
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Background & aims: Accurate diagnosis of sarcopenia requires evaluation of muscle quality, which refers to the amount of fat infiltration in muscle tissue. In this study, we aim to investigate whether we can independently predict mortality risk in transcatheter aortic valve implantation (TAVI) patients, using automatic deep learning algorithms to assess muscle quality on procedural computed tomography (CT) scans. Methods: This study included 1199 patients with severe aortic stenosis who underwent transcatheter aortic valve implantation (TAVI) between January 2010 and January 2020. A procedural CT scan was performed as part of the preprocedural-TAVI evaluation, and the scans were analyzed using deep-learning-based software to automatically determine skeletal muscle density (SMD) and intermuscular adipose tissue (IMAT). The association of SMD and IMAT with all-cause mortality was analyzed using a Cox regression model, adjusted for other known mortality predictors, including muscle mass. Results: The mean age of the participants was 80 ± 7 years, 53% were female. The median observation time was 1084 days, and the overall mortality rate was 39%. We found that the lowest tertile of muscle quality, as determined by SMD, was associated with an increased risk of mortality (HR 1.40 [95%CI: 1.15–1.70], p < 0.01). Similarly, low muscle quality as defined by high IMAT in the lowest tertile was also associated with increased mortality risk (HR 1.24 [95%CI: 1.01–1.52], p = 0.04). Conclusions: Our findings suggest that deep learning-assessed low muscle quality, as indicated by fat infiltration in muscle tissue, is a practical, useful and independent predictor of mortality after TAVI.
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Aim To provide insight into the basic characteristics of decision making in the treatment of symptomatic severe aortic stenosis (SSAS) in Dutch heart centres with specific emphasis on the evaluation of frailty, cognition, nutritional status and physical functioning/functionality in (instrumental) activities of daily living [(I)ADL]. Methods A questionnaire was used that is based on the European and American guidelines for SSAS treatment. The survey was administered to physicians and non-physicians in Dutch heart centres involved in the decision-making pathway for SSAS treatment. Results All 16 Dutch heart centres participated. Before a patient case is discussed by the heart team, heart centres rarely request data from the referring hospital regarding patients’ functionality (n = 5), frailty scores (n = 0) and geriatric consultation (n = 1) as a standard procedure. Most heart centres ‘often to always’ do their own screening for frailty (n = 10), cognition/mood (n = 9), nutritional status (n = 10) and physical functioning/functionality in (I)ADL (n = 10). During heart team meetings data are ‘sometimes to regularly’ available regarding frailty (n = 5), cognition/mood (n = 11), nutritional status (n = 8) and physical functioning/functionality in (I)ADL (n = 10). After assessment in the outpatient clinic patient cases are re-discussed ‘sometimes to regularly’ in heart team meetings (n = 10). Conclusions Dutch heart centres make an effort to evaluate frailty, cognition, nutritional status and physical functioning/functionality in (I)ADL for decision making regarding SSAS treatment. However, these patient data are not routinely requested from the referring hospital and are not always available for heart team meetings. Incorporation of these important data in a structured manner early in the decision-making process may provide additional useful information for decision making in the heart team meeting.
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Background: Manual muscle mass assessment based on Computed Tomography (CT) scans is recognized as a good marker for malnutrition, sarcopenia, and adverse outcomes. However, manual muscle mass analysis is cumbersome and time consuming. An accurate fully automated method is needed. In this study, we evaluate if manual psoas annotation can be substituted by a fully automatic deep learning-based method.Methods: This study included a cohort of 583 patients with severe aortic valve stenosis planned to undergo Transcatheter Aortic Valve Replacement (TAVR). Psoas muscle area was annotated manually on the CT scan at the height of lumbar vertebra 3 (L3). The deep learning-based method mimics this approach by first determining the L3 level and subsequently segmenting the psoas at that level. The fully automatic approach was evaluated as well as segmentation and slice selection, using average bias 95% limits of agreement, Intraclass Correlation Coefficient (ICC) and within-subject Coefficient of Variation (CV). To evaluate performance of the slice selection visual inspection was performed. To evaluate segmentation Dice index was computed between the manual and automatic segmentations (0 = no overlap, 1 = perfect overlap).Results: Included patients had a mean age of 81 ± 6 and 45% was female. The fully automatic method showed a bias and limits of agreement of -0.69 [-6.60 to 5.23] cm2, an ICC of 0.78 [95% CI: 0.74-0.82] and a within-subject CV of 11.2% [95% CI: 10.2-12.2]. For slice selection, 84% of the selections were on the same vertebra between methods, bias and limits of agreement was 3.4 [-24.5 to 31.4] mm. The Dice index for segmentation was 0.93 ± 0.04, bias and limits of agreement was -0.55 [1.71-2.80] cm2.Conclusion: Fully automatic assessment of psoas muscle area demonstrates accurate performance at the L3 level in CT images. It is a reliable tool that offers great opportunities for analysis in large scale studies and in clinical applications.
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Objectives: To determine the psychometric properties of a questionnaire to assess fear of movement (kinesiophobia): the Tampa Scale for Kinesiophobia (TSK-NL Heart), and to investigate the prevalence of kinesiophobia in patients attending cardiac rehabilitation.Methods: A total of 152 patients were evaluated with the TSK-NL Heart during intake and 7 days later. Internal consistency, test-retest reliability and construct validity were assessed. For construct validity, the Cardiac Anxiety Questionnaire (CAQ) and the Hospital Anxiety and Depression Scale (HADS) were used. The factor structure of the TSK-NL Heart was determined by a principal component analysis (PCA).Results: After removal of 4 items due to low internal consistency, the TSK-NL Heart showed substantial reliability (intraclass correlation coefficient; ICC: 0.80). A strong positive correlation was found between the TSK-NL Heart and the CAQ (rs: 0.61). Strong positive correlations were found between the TSK-NL Heart and de HADS (Anxiety) (rs: 0.60) and between the TSK-NL Heart and the CAQ (rs: 0.61). The PCA revealed a 3-factor structure as most suitable (fear of injury, avoidance of physical activity, perception of risk). High levels of kinesiophobia were found in 45.4% of patients.Conclusion: The 13-item TSK-NL Heart has good psychometric properties, and we recommend using this version to assess kinesiophobia, which is present in a substantial proportion of patients referred for cardiac rehabilitation.Keywords: Tampa Scale for Kinesiophobia; cardiac rehabilitation; exercise; fear of movement; physical activity; cardiovascular disease
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