Regional vulnerability of hippocampal subfields to aging measured by structural and diffusion MRI

In the past few years, there has been an increasing awareness of the regional vulnerability of the hippocampus to age‐related processes. However, to date, no studies have assessed the effects of age on different structural magnetic resonance parameters in the specific hippocampal subfields. In this study, we measured volume, mean diffusivity (MD) and fractional anisotropy (FA) in the presubiculum, subiculum, fimbria, cornu ammonis (CA) 1,2‐3,4‐DG and the whole hippocampus in fifty cognitively intact elder adults between 50 and 75 years of age (20 men, 30 women). Segmentation of hippocampal subfields was performed using FreeSurfer. Individual MD and FA images were coregistered to T1‐weighted volumes using FLIRT of FSL. Linear regression analyses were performed to assess the effects of age on the anatomical measures of each subfield. In addition, multiple regression analyses were also carried out to assess which of the anatomical measures that showed a correlation with age in the previous analyses, were the best age predictors in the hippocampus. In agreement with previous studies, our results showed a significant association between age and volume (P < 0.001) as well as MD (P < 0.001) in the whole hippocampus. Regarding the specific hippocampal subfields, we found that age had a significant negative effect on volume in CA2‐3 (P < 0.001) and CA4‐DG (P < 0.001). Importantly, we found a positive effect of age on MD in CA2‐3 (P < 0.001) and fimbria (P < 0.001) as well as a negative age effect on FA in the subiculum (P < 0.001). Multiple regression analyses revealed that the best overall predictors of age in the hippocampus were MD in the fimbria and volume of CA2‐3, which explained 73.8% of the age variance. These results indicate that age has an effect both on volume and diffusion tensor imaging measures in different subfields, suggesting they provide complementary information on age‐related processes in the hippocampus. © 2013 Wiley Periodicals, Inc.     

Effect of Dapagliflozin in DAPA-HF According to Background Glucose-Lowering Therapy

OBJECTIVETo determine whether the benefits of dapagliflozin in patients with heart failure and reduced ejection fraction (HFrEF) and type 2 diabetes in the Dapagliflozin And Prevention of Adverse-Outcomes in Heart Failure trial (DAPA-HF) varied by background glucose-lowering therapy (GLT).RESEARCH DESIGN AND METHODSWe examined the effect of study treatment by the use or not of GLT and by GLT classes and combinations. The primary outcome was a composite of worsening heart failure (hospitalization or urgent visit requiring intravenous therapy) or cardiovascular death.RESULTSIn the 2,139 type 2 diabetes patients, the effect of dapagliflozin on the primary outcome was consistent by GLT use or no use (hazard ratio 0.72 [95% CI 0.58–0.88] vs. 0.86 [0.60–1.23]; interaction P = 0.39) and across GLT classes.CONCLUSIONSIn DAPA-HF, dapagliflozin improved outcomes irrespective of use or no use of GLT or by GLT type used in patients with type 2 diabetes and HFrEF.     

MRI in Neuromuscular Diseases: An Emerging Diagnostic Tool and Biomarker for Prognosis and Efficacy

There is an unmet need to identify biomarkers sensitive to change in rare, slowly progressive neuromuscular diseases. Quantitative magnetic resonance imaging (MRI) of muscle may offer this opportunity, as it is noninvasive and can be carried out almost independent of patient cooperation and disease severity. Muscle fat content correlates with muscle function in neuromuscular diseases, and changes in fat content precede changes in function, which suggests that muscle MRI is a strong biomarker candidate to predict prognosis and treatment efficacy. In this paper, we review the evidence suggesting that muscle MRI may be an important biomarker for diagnosis and to monitor change in disease severity. ANN NEUROL 2020;88:669–681     

The brain-enriched microRNA miR-124 in plasma predicts neurological outcome after cardiac arrest

Introduction

Early prognostication after successful cardiopulmonary resuscitation is difficult, and there is a need for novel methods to estimate the extent of brain injury and predict outcome. In this study, we evaluated the impact of the cardiac arrest syndrome on the plasma levels of selected tissue-specific microRNAs (miRNAs) and assessed their ability to prognosticate death and neurological disability.

Methods

We included 65 patients treated with hypothermia after cardiac arrest in the study. Blood samples were obtained at 24 hours and at 48 hours. For miRNA-screening purposes, custom quantitative polymerase chain reaction (qPCR) panels were first used. Thereafter individual miRNAs were assessed at 48 hours with qPCR. miRNAs that successfully predicted prognosis at 48 hours were further analysed at 24 hours. Outcomes were measured according to the Cerebral Performance Category (CPC) score at 6 months after cardiac arrest and stratified into good (CPC score 1 or 2) or poor (CPC scores 3 to 5).

Results

At 48 hours, miR-146a, miR-122, miR-208b, miR-21, miR-9 and miR-128 did not differ between the good and poor neurological outcome groups. In contrast, miR-124 was significantly elevated in patients with poor outcomes compared with those with favourable outcomes (P < 0.0001) at 24 hours and 48 hours after cardiac arrest. Analysis of receiver operating characteristic curves at 24 and 48 hours after cardiac arrest showed areas under the curve of 0.87 (95% confidence interval (CI) = 0.79 to 0.96) and 0.89 (95% CI = 0.80 to 0.97), respectively.

Conclusions

The brain-enriched miRNA miR-124 is a promising novel biomarker for prediction of neurological prognosis following cardiac arrest.     

Fatigue after myocardial infarction: Relationships with indices of emotional distress,and sociodemographic and clinical variables

Alsén P, Brink E, Brändström Y, Karlson BW, Persson L‐O. International Journal of Nursing Practice 2010; 16 : 326–334
Fatigue after myocardial infarction: Relationships with indices of emotional distress, and sociodemographic and clinical variables Fatigue and depressive symptoms are relatively common among patients recovering from myocardial infarction (MI). The symptoms of depression and fatigue overlap. The present study aimed at identifying patient fatigue and at examining the incidence of fatigue, particularly without coexisting depression, after MI. The sample comprised 204 consecutive patients who had completed the questionnaires Hospital Anxiety and Depression Scale and the Multidimensional Fatigue Inventory–20 after MI (1 week and 4 months). The results showed that fatigue had decreased after 4 months compared with the time of MI onset. Compared with the general population, patients reported significantly higher levels of fatigue. Furthermore, fatigue was associated with depression, but 33% of the sample reported fatigue without coexisting depression after 4 months. In order to prevent or treat patients' symptoms of fatigue after MI, the concepts of fatigue and depression should be assessed separately so as to exclude overlapping effects.