Characteristics Associated with Quality of Life in Long-Term Care Residents with Dementia: A Cross-Sectional Study

Geriatrics in primary car

Symptoms and treatment when death is expected in dementia patients in long-term care facilities

Geriatrics in primary car

The Psychological Impact of Prenatal Diagnosis and Disclosure of Susceptibility Loci: First Impressions of Parents’ Experiences

Genomic microarray may detect susceptibility loci (SL) for neurodevelopmental disorders such as autism and epilepsy, with a yet unquantifiable risk for the fetus. The prenatal disclosure of susceptibility loci is a topic of much debate. Many health care professionals fear that reporting susceptibility loci may put a psychological burden on pregnant couples. It is our policy to disclose prenatal susceptibility loci as we recognize them as actionable for prospective parents. The aim of this report was to evaluate the psychological impact of disclosing a prenatal diagnosis of susceptibility loci. The psychological impact of disclosing susceptibility loci was evaluated in the first patients who received such results. Eight out of 15 women who had a susceptibility locus disclosed and four of their partners consented to share their experiences through a telephonic evaluation (n = 12). Follow-up time ranged from 3 to 15 months after their prenatal test result. The reporting of susceptibility loci was initially ‘shocking’ for five parents while the other seven felt ‘worried’. Ten out of 12 participants indicated they would like to be informed about the susceptibility locus again, two were unsure. Most had no enduring worries. Participants unanimously indicated that pregnant couples should have an individualized pre-test choice about susceptibility loci (non)disclosure. We observed no negative psychological impact with the prenatal diagnosis and disclosure of SL on participants. A key factor in mitigating parental anxiety with SL disclosure appears to be post-test genetic counseling. Our report confirms that pregnant women and their partners prefer an individualized choice regarding the scope of prenatal testing

Choosing between Higher and Lower Resolution Microarrays

Developments in prenatal testing allow the detection of more findings. SNP arrays in prenatal diagnosis (PND) can be analyzed at 0.5 Mb resolution detecting more clinically relevant anomalies, or at 5 Mb resolution. We investigated whether women had sufficient knowledge to make informed choices regarding the scope of their prenatal test that were consistent with their attitude. Pregnant women could choose between testing at 5 or at 0.5 Mb array. Consenting women (N = 69) received pre-test genetic counseling by phone and filled out the Measure of Informed Choice questionnaire designed for this study. Choices based on sufficient knowledge and consistent with attitude were considered informed. Sixty-two percent of the women made an adequately informed choice, based on sufficient knowledge and attitude-consistent with their choice of microarray resolution. Women who made an informed choice, opted for 0.5 Mb array resolution more often. There were no differences between women making adequately informed or less informed choices regarding level of experienced anxiety or doubts. Over time on T0 and T1, anxiety and doubts significantly decreased. While previous studies demonstrated that knowledge is an important component in informed decision-making, this study underlines that a consistent attitude might be equally important for decision-making. We advocate more focus on attitude-consistency and deliberation as compared to only a strong focus on knowledge

Trends in quality of care and dying perceived by family caregivers of nursing home residents with dementia 2005-2019

Background: Dementia palliative care is increasingly subject of research and practice improvement initiatives. Aim: To assess any changes over time in the evaluation of quality of care and quality of dying with dementia by family caregivers. Design: Combined analysis of eight studies with bereaved family caregivers' evaluations 2005-2019. Setting/participants: Family caregivers of nursing home residents with dementia in the Netherlands (n = 1189) completed the End-of-Life in Dementia Satisfaction With Care (EOLD-SWC; quality of care) and Comfort Assessment in Dying (EOLD-CAD, four subscales; quality of dying) instruments. Changes in scores over time were analysed using mixed models with random effects for season and facility and adjustment for demographics, prospective design and urbanised region. Results: The mean total EOLD-SWC score was 33.40 (SD 5.08) and increased by 0.148 points per year (95% CI, 0.052-0.244; adjusted 0.170 points 95% CI, 0.055-0.258). The mean total EOLD-CAD score was 30.80 (SD 5.76) and, unadjusted, there was a trend of decreasing quality of dying over time of -0.175 points (95% CI, -0.291 to -0.058) per year increment. With adjustment, the trend was not significant (-0.070 EOLD-CAD total score points, 95% CI, -0.205 to 0.065) and only the EOLD-CAD subscale 'Well being' decreased. Conclusion: We identified divergent trends over 14 years of increased quality of care, while quality of dying did not increase and well-being in dying decreased. Further research is needed on what well-being in dying means to family. Quality improvement requires continued efforts to treat symptoms in dying with dementia.Development and application of statistical models for medical scientific researc

Clinically relevant potential drug-drug interactions in intensive care patients: a large retrospective observational multicenter study

Purpose: Potential drug-drug interactions (pDDIs) may harm patients admitted to the Intensive Care Unit (ICU). Due to the patient's critical condition and continuous monitoring on the ICU, not all pDDIs are clinically relevant. Clinical decision support systems (CDSSs) warning for irrelevant pDDIs could result in alert fatigue and overlooking important signals. Therefore, our aim was to describe the frequency of clinically relevant pDDIs (crpDDIs) to enable tailoring of CDSSs to the ICU setting. Materials & methods: In this multicenter retrospective observational study, we used medication administration data to identify pDDIs in ICU admissions from 13 ICUs. Clinical relevance was based on a Delphi study in which intensivists and hospital pharmacists assessed the clinical relevance of pDDIs for the ICU setting. Results: The mean number of pDDIs per 1000 medication administrations was 70.1, dropping to 31.0 when con -sidering only crpDDIs. Of 103,871 ICU patients, 38% was exposed to a crpDDI. The most frequently occurring crpDDIs involve QT-prolonging agents, digoxin, or NSAIDs. Conclusions: Considering clinical relevance of pDDIs in the ICU setting is important, as only half of the detected pDDIs were crpDDIs. Therefore, tailoring CDSSs to the ICU may reduce alert fatigue and improve medication safety in ICU patients. ? 2020 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).Perioperative Medicine: Efficacy, Safety and Outcome (Anesthesiology/Intensive Care

Clinically relevant potential drug-drug interactions in intensive care patients: A large retrospective observational multicenter study

Purpose: Potential drug-drug interactions (pDDIs) may harm patients admitted to the Intensive Care Unit (ICU). Due to the patient's critical condition and continuous monitoring on the ICU, not all pDDIs are clinically relevant. Clinical decision support systems (CDSSs) warning for irrelevant pDDIs could result in alert fatigue and overlooking important signals. Therefore, our aim was to describe the frequency of clinically relevant pDDIs (crpDDIs) to enable tailoring of CDSSs to the ICU setting. Materials & methods: In this multicenter retrospective observational study, we used medication administration data to identify pDDIs in ICU admissions from 13 ICUs. Clinical relevance was based on a Delphi study in which intensivists and hospital pharmacists assessed the clinical relevance of pDDIs for the ICU setting. Results: The mean number of pDDIs per 1000 medication administrations was 70.1, dropping to 31.0 when considering only crpDDIs. Of 103,871 ICU patients, 38% was exposed to a crpDDI. The most frequently occurring crpDDIs involve QT-prolonging agents, digoxin, or NSAIDs. Conclusions: Considering clinical relevance of pDDIs in the ICU setting is important, as only half of the detected pDDIs were crpDDIs. Therefore, tailoring CDSSs to the ICU may reduce alert fatigue and improve medication safety in ICU patients

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations

Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure

Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies