No abstract

Self-management support interventions that take informational support in patients' networks into account may be most effective, especially in deprived populations.

Euchromatin histone methyltransferase 1 (EHMT1) is a highly conserved protein that catalyzes mono- and dimethylation of histone H3 lysine 9, thereby epigenetically regulating transcription. Kleefstra syndrome (KS), is caused by haploinsufficiency of the EHMT1 gene, and is an example of an emerging group of intellectual disability (ID) disorders caused by genes encoding epigenetic regulators of neuronal gene activity. Little is known about the mechanisms underlying this disorder, prompting us to study the Euchromatin histone methyltransferase 1 heterozygous knockout (Ehmt1(+/-)) mice as a model for KS. In agreement with the cognitive disturbances observed in patients with KS, we detected deficits in fear extinction learning and both novel and spatial object recognition in Ehmt1(+/-) mice. These learning and memory deficits were associated with a significant reduction in dendritic arborization and the number of mature spines in hippocampal CA1 pyramidal neurons of Ehmt1(+/-) mice. In-depth analysis of the electrophysiological properties of CA3-CA1 synapses revealed no differences in basal synaptic transmission or theta-burst induced long-term potentiation (LTP). However, paired-pulse facilitation (PPF) was significantly increased in Ehmt1(+/-) neurons, pointing to a potential deficiency in presynaptic neurotransmitter release. Accordingly, a reduction in the frequency of miniature excitatory post-synaptic currents (mEPSCs) was observed in Ehmt1(+/-) neurons. These data demonstrate that Ehmt1 haploinsufficiency in mice leads to learning deficits and synaptic dysfunction, providing a possible mechanism for the ID phenotype in patients with KS.

BackgroundSelf-management support is an important component of the clinical management of many chronic conditions. The validated Self-Management Screening questionnaire (SeMaS) assesses individual characteristics that influence a patient’s ability to self-manage.AimTo assess the effect of providing personalised self-management support in clinical practice on patients’ activation and health-related behaviours.Design and settingA cluster randomised controlled trial was conducted in 15 primary care group practices in the south of the Netherlands.MethodAfter attending a dedicated self-management support training session, practice nurses in the intervention arm discussed the results of SeMaS with the patient at baseline, and tailored the self-management support. Participants completed a 13-item Patient Activation Measure (PAM-13) and validated lifestyle questionnaires at baseline and after 6 months. Data, including individual care plans, referrals to self-management interventions, self-monitoring, and healthcare use, were extracted from patients’ medical records. Multilevel multiple regression was used to assess the effect on outcomes.ResultsThe PAM-13 score did not differ significantly between the control (n= 348) and intervention (n= 296) arms at 6 months. In the intervention arm, 29.4% of the patients performed self-monitoring, versus 15.2% in the control arm (effect sizer= 0.9,P= 0.01). In the per protocol analysis (controln= 348; interventionn= 136), the effect of the intervention was significant on the number of individual care plans (effect sizer= 1.3,P= 0.04) and on self-monitoring (effect sizer= 1.0,P= 0.01).ConclusionThis study showed that discussing SeMaS and offering tailored support did not affect patient activation or lifestyle, but did stimulate patients to self-monitor and use individual care plans.

Aims To evaluate the (cost‐)effectiveness of Beyond Good Intentions ( BGI ), a 12‐week group‐based, nurse‐led self‐management programme, in terms of cardiovascular risk factors, self‐management and quality of life, after 2.5 years of follow‐up in pre‐selected individuals with known Type 2 diabetes of up to 5 years’ duration. Methods A parallel randomized controlled trial comparing BGI with usual care, based on a self‐management screening questionnaire, was conducted in 43 general practices after pre‐selection of participants. After 2.5 years of follow‐up, the between‐group changes in the abovementioned variables were assessed using analysis of covariance. Results A total of 108 participants ( BGI group, n = 56; control group, n = 52) were included. Changes over time in BMI (–0.4 vs –0.5 kg/m 2 ) were similar in the two groups. Median HbA 1c [ BGI group 47 mmol/mol (6.5%); control group: 49 mmol/mol (6.6%)] and mean systolic blood pressure ( BGI group: 132±13 mmHg; control group: 133±14 mmHg) were well controlled at baseline and no intervention effect was found. LDL cholesterol levels decreased from 2.4 to 2.2 mmol/l in the control group and remained stable at 2.6 mmol/l in the intervention group ( P =0.032). No intervention effect was found for self‐management or quality of life. Conclusion In contrast to the first BGI study, we did not observe significant effects of the BGI intervention, despite pre‐selection of individuals. In diabetes populations with target levels for HbA 1c , systolic blood pressure and LDL cholesterol, no further beneficial effects can be expected from self‐management programmes with regard to biomedical factors and quality of life.