155 research outputs found

    Ectopic Calcification: What Do We Know and What Is the Way Forward?

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    Ectopic calcification, or ectopic mineralization, is a pathologic condition in which calcifications develop in soft tissues [...]

    A prediction model for one- and three-year mortality in dementia: results from a nationwide hospital-based cohort of 50,993 patients in the Netherlands

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    OBJECTIVE: to develop a model to predict one- and three-year mortality in patients with dementia attending a hospital, through hospital admission or day/memory clinic. DESIGN: we constructed a cohort of dementia patients through data linkage of three Dutch national registers: the hospital discharge register (HDR), the population register and the national cause of death register. SUBJECTS: patients with dementia in the HDR aged between 60 and 100 years registered between 1 January 2000 and 31 December 2010. METHODS: logistic regression analysis techniques were used to predict one- and three-year mortality after a first hospitalisation with dementia. The performance was assessed using the c-statistic and the Hosmer-Lemeshow test. Internal validation was performed using bootstrap resampling. RESULTS: 50,993 patients were included in the cohort. Two models were constructed, which included age, sex, setting of care (hospitalised versus day clinic) and the presence of comorbidity using the Charlson comorbidity index. One model predicted one-year mortality and the other three-year mortality. Model discrimination according to the c-statistic for the models was 0.71 (95% CI 0.71-0.72) and 0.72 (95% CI 0.72-0.73), respectively. CONCLUSION: both models display acceptable ability to predict mortality. An important advantage is that they are easy to apply in daily practise and thus are helpful for individual decision-making regarding diagnostic/therapeutic interventions and advance care planning

    Drug-related readmissions in older hospitalized adults: External validation and updating of OPERAM DRA prediction tool.

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    BACKGROUND Drug-related readmissions (DRAs) are defined as rehospitalizations with an adverse drug event as their main or significant contributory cause. DRAs represent a major adverse health burden for older patients. A prediction model which identified older hospitalized patients at high risk of a DRA <1 year was previously developed using the OPERAM trial cohort, a European cluster randomized controlled trial including older hospitalized patients with multimorbidity and polypharmacy. This study has performed external validation and updated the prediction model consequently. METHODS The MedBridge trial cohort (a multicenter cluster randomized crossover trial performed in Sweden) was used as a validation cohort. It consisted of 2516 hospitalized patients aged ≄65 years. Model performance was assessed by: (1) discriminative power, assessed by the C-statistic with a 95% confidence interval (CI); (2) calibration, assessed by visual examination of the calibration plot and use of the Hosmer-Lemeshow goodness-of-fit test; and (3) overall accuracy, assessed by the scaled Brier score. Several updating methods were carried out to improve model performance. RESULTS In total, 2516 older patients were included in the validation cohort, of whom 582 (23.1%) experienced a DRA <1 year. In the validation cohort, the original model showed a good overall accuracy (scaled Brier score 0.03), but discrimination was moderate (C-statistic 0.62 [95% CI 0.59-0.64]), and calibration showed underestimation of risks. In the final updated model, the predictor "cirrhosis with portal hypertension" was removed and "polypharmacy" was added. This improved the model's discriminative capability to a C-statistic of 0.64 (95% CI 0.59-0.70) and enhanced calibration plots. Overall accuracy remained good. CONCLUSIONS The updated OPERAM DRA prediction model may be a useful tool in clinical practice to estimate the risk of DRAs in older hospitalized patients subsequent to discharge. Our efforts lay the groundwork for the future development of models with even better performance

    Rule induction performance in amnestic mild cognitive impairment and Alzheimer’s dementia: examining the role of simple and biconditional rule learning processes

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    Introduction: Rule induction tests such as the Wisconsin Card Sorting Test require executive control processes, but also the learning and memorization of simple stimulus–response rules. In this study, we examined the contribution of diminished learning and memorization of simple rules to complex rule induction test performance in patients with amnestic mild cognitive impairment (aMCI) or Alzheimer’s dementia (AD). Method: Twenty-six aMCI patients, 39 AD patients, and 32 control participants were included. A task was used in which the memory load and the complexity of the rules were independently manipulated. This task consisted of three conditions: a simple two-rule learning condition (Condition 1), a simple four-rule learning condition (inducing an increase in memory load, Condition 2), and a complex biconditional four-rule learning condition—inducing an increase in complexity and, hence, executive control load (Condition 3). Results: Performance of AD patients declined disproportionately when the number of simple rules that had to be memorized increased (from Condition 1 to 2). An additional increment in complexity (from Condition 2 to 3) did not, however, disproportionately affect performance of the patients. Performance of the aMCI patients did not differ from that of the control participants. In the patient group, correlation analysis showed that memory performance correlated with Condition 1 performance, whereas executive task performance correlated with Condition 2 performance. Conclusions: These results indicate that the reduced learning and memorization of underlying task rules explains a significant part of the diminished complex rule induction performance commonly reported in AD, although results from the correlation analysis suggest involvement of executive control functions as well. Taken together, these findings suggest that care is needed when interpreting rule induction task performance in terms of executive function deficits in these patients

    The impact of frailty on adverse outcomes after transcatheter aortic valve replacement in older adults: A retrospective cohort study

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    BACKGROUND: Transcatheter aortic valve replacement (TAVR) is an effective alternative to surgical aortic valve replacement for patients who are at increased surgical risk. Consequently, frailty is common in patients undergoing TAVR. OBJECTIVES: This study aims to investigate the impact of frailty on outcomes following TAVR. METHODS: A retrospective cohort study was conducted, including all TAVR candidates who visited the geriatric outpatient clinic for preoperative screening. Frailty status was assessed according to the Groningen Frailty Indicator. The primary outcome of the study was defined as the occurrence of postoperative complications, and this was evaluated according to the Clavien-Dindo classification. An additional analysis was performed to assess the impact of frailty on 1-year all-cause mortality and complications within 30 days of TAVR according to the Valve Academic Research Consortium (VARC-2) criteria. The VARC-2 criteria provide harmonized endpoint definitions for TAVR studies. RESULTS: In total, 431 patients with a mean age of 80.8 ± 6.2 years were included, of whom 56% were female. Frailty was present in 36% of the participants. Frailty was associated with a higher risk of the composite outcome of complications [adjusted odds ratio (OR): 1.55 (95% confidence interval, CI: 1.03-2.34)], 30-day mortality [adjusted OR: 4.84 (95% CI: 1.62-14.49)], 3-month mortality [adjusted OR: 2.52 (95% CI: 1.00-6.28)] and 1-year mortality [adjusted OR: 2.96 (95% CI: 1.46-6.00)]. CONCLUSIONS: Frailty is common in TAVR patients and is associated with an increased overall risk of postoperative complications, particularly mortality. Increased optimization of screening and treatment of frailty in the guidelines for valvular heart diseases is recommended

    Serum biomarkers for arterial calcification in humans: A systematic review

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    Aim: To clarify the role of mediators of ectopic mineralization as biomarkers for arterial calcifications. Methods: MEDLINE and Embase were searched for relevant literature, until January 4th 2022. The investigated biomarkers were: calcium, phosphate, parathyroid hormone, vitamin D, pyrophosphate, osteoprotegerin, receptor activator of nuclear factor-kappa B ligand (RANKL), fibroblast growth factor-23 (FGF-23), Klotho, osteopontin, osteocalcin, Matrix Gla protein (MGP) and its inactive forms and vitamin K. Studies solely performed in patients with kidney insufficiency or diabetes mellitus were excluded. Results: After screening of 8985 articles, a total of 129 articles were included in this systematic review. For all biomarkers included in this review, the results were variable and more than half of the studies for each specific biomarker had a non-significant result. Also, the overall quality of the included studies was low, partly as a result of the mostly cross-sectional study designs. The largest body of evidence is available for phosphate, osteopontin and FGF-23, as a little over half of the studies showed a significant, positive association. Firm statements for these biomarkers cannot be drawn, as the number of studies was limited and hampered by residual confounding or had non-significant results. The associations of the other mediators of ectopic mineralization with arterial calcifications were not clear. Conclusion: Associations between biomarkers of ectopic mineralization and arterial calcification are variable in the published literature. Future longitudinal studies differentiating medial and intimal calcification could add to the knowledge of biomarkers and mechanisms of arterial calcifications

    Association between perioperative statin treatment and short-term clinical outcomes following transcatheter aortic valve implantation: a retrospective cohort study

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    BACKGROUND: Studies have found statin treatment to be associated with improved 1-year survival after transcatheter aortic valve implantation (TAVI), suggesting pleiotropic effects of statins on preventing perioperative complications. Statin treatment is not associated with postoperative cardiovascular complications or mortality; however, other postoperative complications have not been investigated. AIM: To explore whether preoperative statin treatment is associated with a lower short-term risk of mortality, readmission and major postoperative complications in older patients undergoing TAVI. METHODS: A retrospective cohort study including patients aged 65 years and older who had undergone a comprehensive geriatric assessment prior to TAVI between January 2014 and January 2021. The primary outcomes were 90-day mortality, 90-day readmissions and major postoperative complications according to the Clavien-Dindo classification. Multivariable logistic regression was performed with adjustment for potential confounders, namely age, gender, comorbidity, body mass index, smoking, diminished renal function, alcohol use and falls . RESULTS: This study included 584 patients, of whom 324 (55.5%) were treated with a statin. In the statin treated group, 15 (4.6%) patients died within 90 days of TAVI compared with 10 (3.8%) patients in the non statin group (adjusted OR 1.17; 95% CI 0.51 to 2.70). The number of 90-day readmissions was 39 (12.0%) and 34 (13.1%) (adjusted OR 0.91; 95% CI 0.54 to 1.52), respectively. In the statin treated group, 115 (35.5%) patients experienced a major complication compared with 98 (37.7%) in the non-statin group (adjusted OR 0.95; 95% CI 0.67 to 1.37). CONCLUSION: Preoperative statin treatment is not associated with improved short-term outcomes after TAVI. A randomised controlled trial with different statin doses may be warranted to investigate whether initiating statin treatment before TAVI improves both postoperative outcomes and long-term survival

    Association between perioperative statin treatment and short-term clinical outcomes following transcatheter aortic valve implantation: a retrospective cohort study

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    BACKGROUND: Studies have found statin treatment to be associated with improved 1-year survival after transcatheter aortic valve implantation (TAVI), suggesting pleiotropic effects of statins on preventing perioperative complications. Statin treatment is not associated with postoperative cardiovascular complications or mortality; however, other postoperative complications have not been investigated. AIM: To explore whether preoperative statin treatment is associated with a lower short-term risk of mortality, readmission and major postoperative complications in older patients undergoing TAVI. METHODS: A retrospective cohort study including patients aged 65 years and older who had undergone a comprehensive geriatric assessment prior to TAVI between January 2014 and January 2021. The primary outcomes were 90-day mortality, 90-day readmissions and major postoperative complications according to the Clavien-Dindo classification. Multivariable logistic regression was performed with adjustment for potential confounders, namely age, gender, comorbidity, body mass index, smoking, diminished renal function, alcohol use and falls . RESULTS: This study included 584 patients, of whom 324 (55.5%) were treated with a statin. In the statin treated group, 15 (4.6%) patients died within 90 days of TAVI compared with 10 (3.8%) patients in the non statin group (adjusted OR 1.17; 95% CI 0.51 to 2.70). The number of 90-day readmissions was 39 (12.0%) and 34 (13.1%) (adjusted OR 0.91; 95% CI 0.54 to 1.52), respectively. In the statin treated group, 115 (35.5%) patients experienced a major complication compared with 98 (37.7%) in the non-statin group (adjusted OR 0.95; 95% CI 0.67 to 1.37). CONCLUSION: Preoperative statin treatment is not associated with improved short-term outcomes after TAVI. A randomised controlled trial with different statin doses may be warranted to investigate whether initiating statin treatment before TAVI improves both postoperative outcomes and long-term survival

    Inorganic phosphate exporter heterozygosity in mice leads to brain vascular calcification, microangiopathy, and microgliosis

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    Calcification of the cerebral microvessels in the basal ganglia in the absence of systemic calcium and phosphate imbalance is a hallmark of primary familial brain calcification (PFBC), a rare neurodegenerative disorder. Mutation in genes encoding for sodium-dependent phosphate transporter 2 (SLC20A2), xenotropic and polytropic retrovirus receptor 1 (XPR1), platelet-derived growth factor B (PDGFB), platelet-derived growth factor receptor beta (PDGFRB), myogenesis regulating glycosidase (MYORG), and junctional adhesion molecule 2 (JAM2) are known to cause PFBC. Loss-of-function mutations in XPR1, the only known inorganic phosphate exporter in metazoans, causing dominantly inherited PFBC was first reported in 2015 but until now no studies in the brain have addressed whether loss of one functional allele leads to pathological alterations in mice, a commonly used organism to model human diseases. Here we show that mice heterozygous for Xpr1 (Xpr1WT/lacZ^{WT/lacZ} ) present with reduced inorganic phosphate levels in the cerebrospinal fluid and age- and sex-dependent growth of vascular calcifications in the thalamus. Vascular calcifications are surrounded by vascular basement membrane and are located at arterioles in the smooth muscle layer. Similar to previously characterized PFBC mouse models, vascular calcifications in Xpr1WT/lacZ^{WT/lacZ} mice contain bone matrix proteins and are surrounded by reactive astrocytes and microglia. However, microglial activation is not confined to calcified vessels but shows a widespread presence. In addition to vascular calcifications, we observed vessel tortuosity and transmission electron microscopy analysis revealed microangiopathy-endothelial swelling, phenotypic alterations in vascular smooth muscle cells, and thickening of the basement membrane

    Drug-related readmissions in older hospitalized adults: External validation and updating of OPERAM DRA prediction tool

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    Background: Drug-related readmissions (DRAs) are defined as rehospitalizations with an adverse drug event as their main or significant contributory cause. DRAs represent a major adverse health burden for older patients. A prediction model which identified older hospitalized patients at high risk of a DRA <1 year was previously developed using the OPERAM trial cohort, a European cluster randomized controlled trial including older hospitalized patients with multimorbidity and polypharmacy. This study has performed external validation and updated the prediction model consequently. Methods: The MedBridge trial cohort (a multicenter cluster randomized crossover trial performed in Sweden) was used as a validation cohort. It consisted of 2516 hospitalized patients aged ≄65 years. Model performance was assessed by: (1) discriminative power, assessed by the C-statistic with a 95% confidence interval (CI); (2) calibration, assessed by visual examination of the calibration plot and use of the Hosmer–Lemeshow goodness-of-fit test; and (3) overall accuracy, assessed by the scaled Brier score. Several updating methods were carried out to improve model performance. Results: In total, 2516 older patients were included in the validation cohort, of whom 582 (23.1%) experienced a DRA <1 year. In the validation cohort, the original model showed a good overall accuracy (scaled Brier score 0.03), but discrimination was moderate (C-statistic 0.62 [95% CI 0.59–0.64]), and calibration showed underestimation of risks. In the final updated model, the predictor “cirrhosis with portal hypertension” was removed and “polypharmacy” was added. This improved the model's discriminative capability to a C-statistic of 0.64 (95% CI 0.59–0.70) and enhanced calibration plots. Overall accuracy remained good. Conclusions: The updated OPERAM DRA prediction model may be a useful tool in clinical practice to estimate the risk of DRAs in older hospitalized patients subsequent to discharge. Our efforts lay the groundwork for the future development of models with even better performance
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