Policy of free GP care for children under 6 years: The impact on daytime and out-of-hours general practice.

Ireland does not yet have a comprehensive system of universal access to primary care. In 2015, access to general practitioner (GP) care at no charge was introduced for the 70% of children aged under six who previously paid out-of-pocket fees. This study uses data from 16 practices and a regional out-of-hours (OOH) GP service to assess the impact of this policy on attendance. A difference-in-difference (DiD) analysis was applied to visit records of paediatric patients over a period of five years, two years of which were pre-policy, with treatment and control differentiated by age. Attendance at daytime GP by children aged under-six increased by 20%-21% in the three years following the introduction of the policy, largely explained by an increase in the number of patients attending (17.4%-18.6%). Of children aged under-six attending pre-policy, 14.9%-15.8% had >6 visits annually, increasing to 18.5%-20.3% post-policy. OOH GP attendance also increased by 20.5%-29.4% over the same period. Findings are consistent with international literature on the provision of financially accessible healthcare. Prior unmet need, the provision of additional assessments to children aged under six, parental response to a service at no charge, and rerouting of access to the ED through GP, are all possible contributors to this increased demand. A more integrated policy of boosting supply as well as demand is desirable, particularly in the context of future expansion plans, to ensure the health benefits anticipated from the introduction of this policy have every opportunity to be realised.

Policy of free GP care for children under 6 years: The impact on emergency department attendance.

Universal health coverage (UHC) aims to improve child health. Ireland, the only country in the European Union without universal access to primary care, introduced general practitioner (GP) care at no charge for children aged under six in 2015. This paper aims to evaluate the impact of this policy on attendance at the emergency department (ED). A difference-in-difference (DiD) analysis was applied to visit records of 367,000 paediatric patients at five hospitals over a period of five years, with treatment and control differentiated by age. DiD was also used to assess if GP referrals and the severity of presentations altered as a consequence of this policy. While existing research estimates that this policy increased attendance by children aged under six at general practice by over 25%, this policy did not lead to a reduction in ED attendance. Hospital level effects on attendance varied from no impact to increased attendance by children aged under six of 28.9%. While increased GP referrals, particularly for injury and medical reasons, indicated more patients presented to their GP prior to ED attendance, walk-ins without referral did not decrease. Attendance increased at both regional hospitals, which also had the highest proportion of GP referred visits. While the marginal probability of a visit being GP referred increased at four of the five hospitals in this study, only in two of these can the entire effect be attributed to the introduction of this policy (effects 1.4 and 1.8 percentage points). Previous unmet need, capacity constraints in general practice, regional variability in the GP to population ratio, restricted hours of access to GPs, coupled with faster access to diagnostics in the ED setting, may explain variability in the effect and why the expected reduction in ED attendances did not occur.

Characterization of 16S rRNA Processing with Pre-30S Subunit Assembly Intermediates from E. coli.

Ribosomal RNA (rRNA) is a major component of ribosomes and is fundamental to the process of translation. In bacteria, 16S rRNA is a component of the small ribosomal subunit and plays a critical role in mRNA decoding. rRNA maturation entails the removal of intervening spacer sequences contained within the pre-rRNA transcript by nucleolytic enzymes. Enzymatic activities involved in maturation of the 5'-end of 16S rRNA have been identified, but those involved in 3'-end maturation of 16S rRNA are more enigmatic. Here, we investigate molecular details of 16S rRNA maturation using purified in vivo-formed small subunit (SSU) assembly intermediates (pre-SSUs) from wild-type Escherichia coli that contain precursor 16S rRNA (17S rRNA). Upon incubation of pre-SSUs with E. coli S100 cell extracts or purified enzymes implicated in 16S rRNA processing, the 17S rRNA is processed into additional intermediates and mature 16S rRNA. These results illustrate that exonucleases RNase R, RNase II, PNPase, and RNase PH can process the 3'-end of pre-SSUs in vitro. However, the endonuclease YbeY did not exhibit nucleolytic activity with pre-SSUs under these conditions. Furthermore, these data demonstrate that multiple pathways facilitate 16S rRNA maturation with pre-SSUs in vitro, with the dominant pathways entailing complete processing of the 5'-end of 17S rRNA prior to 3'-end maturation or partial processing of the 5'-end with concomitant processing of the 3'-end. These results reveal the multifaceted nature of SSU biogenesis and suggest that E. coli may be able to escape inactivation of any one enzyme by using an existing complementary pathway.

In praise of ambidexterity: How a continuum of handedness predicts social adjustment.

This paper estimates the relationship between handedness and social adjustment in children. In addition to binary measures of hand preference, we also use a continuous measure of relative hand skill. Outcomes at ages 7, 11 and 16 are studied. The data used is the British 1958 Birth. Using a partially linear semi-parametric regression estimator, it is shown that non-right-handedness (as hand preference) is associated with poorer social adjustment but this effect weakens as individuals age into their teens. The continuous measure of hand skill has a non-monotonic effect on social adjustment with poorer social adjustment in the tails of the continuum. The results are consistent with a growing body of evidence which shows that it is the consistency or degree of laterality (rather than direction) that is important for many outcomes.

Economics of childbirth.

BACKGROUND: Increasing birth rates have raised questions for policy makers and hospital management about the economic costs of childbirth. OBJECTIVE: The purpose of this article is to identify and review all existing scientific studies in relation to the economic costs of alternative modes of childbirth delivery and to highlight deficiencies in the existing scientific research. METHOD: We searched Cochrane, Centre for Reviews and Dissemination, EconLit, the Excerpta Medica Database, the Health Economic Evaluations Database, MEDLINE and PubMed. RESULTS: Thirty articles are included in this review. The main findings suggest that there is no internationally acceptable childbirth cost and clinical outcome classification system that allows for comparisons across different delivery modes. CONCLUSION: This review demonstrates that a better understanding and classification of the costs and associated clinical outcomes of childbirth is required to allow for valid comparisons between maternity units, and to inform policy makers and hospital management.

Resting-state multi-spectrum functional connectivity networks for identification of MCI patients.

In this paper, a high-dimensional pattern classification framework, based on functional associations between brain regions during resting-state, is proposed to accurately identify MCI individuals from subjects who experience normal aging. The proposed technique employs multi-spectrum networks to characterize the complex yet subtle blood oxygenation level dependent (BOLD) signal changes caused by pathological attacks. The utilization of multi-spectrum networks in identifying MCI individuals is motivated by the inherent frequency-specific properties of BOLD spectrum. It is believed that frequency specific information extracted from different spectra may delineate the complex yet subtle variations of BOLD signals more effectively. In the proposed technique, regional mean time series of each region-of-interest (ROI) is band-pass filtered (0.025 ≤ ƒ ≤ 0.100 Hz) before it is decomposed into five frequency sub-bands. Five connectivity networks are constructed, one from each frequency sub-band. Clustering coefficient of each ROI in relation to the other ROIs are extracted as features for classification. Classification accuracy was evaluated via leave-one-out cross-validation to ensure generalization of performance. The classification accuracy obtained by this approach is 86.5%, which is an increase of at least 18.9% from the conventional full-spectrum methods. A cross-validation estimation of the generalization performance shows an area of 0.863 under the receiver operating characteristic (ROC) curve, indicating good diagnostic power. It was also found that, based on the selected features, portions of the prefrontal cortex, orbitofrontal cortex, temporal lobe, and parietal lobe regions provided the most discriminant information for classification, in line with results reported in previous studies. Analysis on individual frequency sub-bands demonstrated that different sub-bands contribute differently to classification, providing extra evidence regarding frequency-specific distribution of BOLD signals. Our MCI classification framework, which allows accurate early detection of functional brain abnormalities, makes an important positive contribution to the treatment management of potential AD patients.

Breastfeeding predicts handedness.

This study examined whether being breastfed predicts handedness. Two large representative samples from Britain (n=13,421) and Ireland (n=8,426) were used. Multivariate probit models are estimated, reporting the marginal effects of covariates on the probability of a child being right-handed. For both datasets, children who have been breastfed for a minimum period (between 1 month and 6 weeks) are significantly less likely to be left-handed. The results are robust to a variety of controls. Hence breastfeeding is an environmental factor that predicts handedness in a non-linear way, although the mechanism is unknown.

Identification of MCI individuals using structural and functional connectivity networks.

Different imaging modalities provide essential complementary information that can be used to enhance our understanding of brain disorders. This study focuses on integrating multiple imaging modalities to identify individuals at risk for mild cognitive impairment (MCI). MCI, often an early stage of Alzheimer's disease (AD), is difficult to diagnose due to its very mild or insignificant symptoms of cognitive impairment. Recent emergence of brain network analysis has made characterization of neurological disorders at a whole-brain connectivity level possible, thus providing new avenues for brain diseases classification. Employing multiple-kernel Support Vector Machines (SVMs), we attempt to integrate information from diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (rs-fMRI) for improving classification performance. Our results indicate that the multimodality classification approach yields statistically significant improvement in accuracy over using each modality independently. The classification accuracy obtained by the proposed method is 96.3%, which is an increase of at least 7.4% from the single modality-based methods and the direct data fusion method. A cross-validation estimation of the generalization performance gives an area of 0.953 under the receiver operating characteristic (ROC) curve, indicating excellent diagnostic power. The multimodality classification approach hence allows more accurate early detection of brain abnormalities with greater sensitivity.

Identification of individuals with MCI via multimodality connectivity networks.

Alzheimer's disease (AD), is difficult to diagnose due to the subtlety of cognitive impairment. Recent emergence of reliable network characterization techniques based on diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (rs-fMRI) has made the understanding of neurological disorders at a whole-brain connectivity level possible, providing new avenues for brain classification. Taking a multi-kernel SVM, we attempt to integrate these two imaging modalities for improving classification performance. Our results indicate that the multimodality classification approach performs better than the single modality approach, with statistically significant improvement in accuracy. It was also found that the prefrontal cortex, orbitofrontal cortex, temporal pole, anterior and posterior cingulate gyrus, precuneus, amygdala, thalamus, parahippocampal gyrus and insula regions provided the most discriminant features for classification, in line with the results reported in previous studies. The multimodality classification approach allows more accurate early detection of brain abnormalities with larger sensitivity, and is important for treatment management of potential AD patients.

Instrumental variable estimation of the effect of prayer on depression.

This paper uses a cross-country representative sample of Europeans over the age of 50 to analyse whether individuals' religiosity is associated with higher levels of well-being as a large number of studies by mental health researchers and economists have suggested. It is shown that in simple models which take no account of possible simultaneity that religiosity, as measured by the frequency of prayer, is associated with a higher level of depression. To circumvent possible reverse causality, the paper utilises a quasi-experimental/instrumental variable design which allows one to interpret the findings as causal. This leads to the conclusion that prayer has a positive effect i.e. it leads to a lower level of depressive symptoms.

Structural integrity of the uncinate fasciculus and resting state functional connectivity of the ventral prefrontal cortex in late life depression.

BACKGROUND: Neuroimaging studies in late life depression have reported decreased structural integrity of white matter tracts in the prefrontal cortex. Functional studies have identified changes in functional connectivity among several key areas involved in mood regulation. Few studies have combined structural and functional imaging. In this study we sought to examine the relationship between the uncinate fasciculus, a key fronto-temporal tract and resting state functional connectivity between the ventral prefrontal cortex ((PFC) and limbic and striatal areas. METHODS: The sample consisted of 24 older patients remitted from unipolar major depression. Each participant had a magnetic resonance imaging brain scan using standardized protocols to obtain both diffusion tensor imaging and resting state functional connectivity data. Our statistical approach compared structural integrity of the uncinate fasciculus and functional connectivity data. RESULTS: We found positive correlations between left uncinate fasciculus (UF) fractional anisotropy (FA) and resting state functional connectivity (rsFC) between the left ventrolateral PFC and left amygdala and between the left ventrolateral PFC and the left hippocampus. In addition, we found a significant negative correlation between left ventromedial PFC-caudate rsFC and left UF FA. The right UF FA did not correlate with any of the seed region based connectivity. CONCLUSIONS: These results support the notion that resting state functional connectivity reflects structural integrity, since the ventral PFC is structurally connected to temporal regions by the UF. Future studies should include larger samples of patients and healthy comparison subjects in which both resting state and task-based functional connectivity are examined.

Altered cerebellar-cerebral functional connectivity in geriatric depression.

Although volumetric and activation changes in the cerebellum have frequently been reported in studies on major depression, its role in the neural mechanism of depression remains unclear. To understand how the cerebellum may relate to affective and cognitive dysfunction in depression, we investigated the resting-state functional connectivity between cerebellar regions and the cerebral cortex in samples of patients with geriatric depression (n = 11) and healthy controls (n = 18). Seed-based connectivity analyses were conducted using seeds from cerebellum regions previously identified as being involved in the executive, default-mode, affective-limbic, and motor networks. The results revealed that, compared with controls, individuals with depression show reduced functional connectivity between several cerebellum seed regions, specifically those in the executive and affective-limbic networks with the ventromedial prefrontal cortex (vmPFC) and increased functional connectivity between the motor-related cerebellum seed regions with the putamen and motor cortex. We further investigated whether the altered functional connectivity in depressed patients was associated with cognitive function and severity of depression. A positive correlation was found between the Crus II-vmPFC connectivity and performance on the Hopkins Verbal Learning Test-Revised delayed memory recall. Additionally, the vermis-posterior cinglate cortex (PCC) connectivity was positively correlated with depression severity. Our results suggest that cerebellum-vmPFC coupling may be related to cognitive function whereas cerebellum-PCC coupling may be related to emotion processing in geriatric depression.

Handedness and drinking behaviour.

OBJECTIVES: A number of papers have investigated whether there is an association between handedness and alcohol consumption hypothesizing that alcoholism may be a consequence of atypical cerebral lateralization or a response to the stress involved in being a minority in a right-handed world. Research to date has mostly used small clinical samples, some without a comparison group. This paper exams this issue using a large population-based random sample. DESIGN: A large multi-country data set of nationally representative samples of the non-institutional population aged 50 years and older from 12 European countries was used (N= 27,428). methods: Logistic regression was used to model the frequency with which individuals self-report the frequency of alcohol consumption. A series of models with differing numbers of potential confounders are estimated. The predictors of frequent and infrequent drinking are investigated separately. RESULTS: After controlling for a number of confounders it is shown that left-handers do drink more often. However, this is due to them being less likely to drink rarely (less than once a month) or not at all. CONCLUSIONS: The evidence suggests that while there is an association between left-handedness and frequency of alcohol consumption there is no reason to believe that it is associated with excessive alcohol consumption or risky drinking.

Enriched white matter connectivity networks for accurate identification of MCI patients.

Mild cognitive impairment (MCI), often a prodromal phase of Alzheimer's disease (AD), is frequently considered to be a good target for early diagnosis and therapeutic interventions of AD. Recent emergence of reliable network characterization techniques has made it possible to understand neurological disorders at a whole-brain connectivity level. Accordingly, we propose an effective network-based multivariate classification algorithm, using a collection of measures derived from white matter (WM) connectivity networks, to accurately identify MCI patients from normal controls. An enriched description of WM connections, utilizing six physiological parameters, i.e., fiber count, fractional anisotropy (FA), mean diffusivity (MD), and principal diffusivities(λ(1), λ(2), and λ(3)), results in six connectivity networks for each subject to account for the connection topology and the biophysical properties of the connections. Upon parcellating the brain into 90 regions-of-interest (ROIs), these properties can be quantified for each pair of regions with common traversing fibers. For building an MCI classifier, clustering coefficient of each ROI in relation to the remaining ROIs is extracted as feature for classification. These features are then ranked according to their Pearson correlation with respect to the clinical labels, and are further sieved to select the most discriminant subset of features using an SVM-based feature selection algorithm. Finally, support vector machines (SVMs) are trained using the selected subset of features. Classification accuracy was evaluated via leave-one-out cross-validation to ensure generalization of performance. The classification accuracy given by our enriched description of WM connections is 88.9%, which is an increase of at least 14.8% from that using simple WM connectivity description with any single physiological parameter. A cross-validation estimation of the generalization performance shows an area of 0.929 under the receiver operating characteristic (ROC) curve, indicating excellent diagnostic power. It was also found, based on the selected features, that portions of the prefrontal cortex, orbitofrontal cortex, parietal lobe and insula regions provided the most discriminant features for classification, in line with results reported in previous studies. Our MCI classification framework, especially the enriched description of WM connections, allows accurate early detection of brain abnormalities, which is of paramount importance for treatment management of potential AD patients.

Handedness and depression: evidence from a large population survey.

There is a considerable body of research arguing for an association between psychotic disorders and atypical brain lateralisation--where non-right-handedness is usually taken as a marker for the latter. By contrast, there has been less attention given to a possible link between handedness and affective disorders (particularly major depression) and, unlike the case of psychosis, there is no a priori reason for such a link. There are very few studies of the relationship between depression and handedness in normal populations. This paper uses a new large population survey from 12 European countries to measure the association between handedness and depression. It is found that, using three different measures, left-handers are significantly more likely to have depressive symptoms than right-handers. For example left-handers are about 5% more likely to have reported having ever experienced symptoms of depression compared to about 27% of the total sample.

Cognitive ability and continuous measures of relative hand skill: a note.

This note re-examines a finding by Crow et al. [Crow, T. J., Crow, L. R., Done, D. J., & Leask, S. (1998). Relative hand skill predicts academic ability: Global deficits at the point of hemispheric indecision. Neuropsychologia, 36(12), 1275-1281] that equal skill of right and left hands is associated with deficits in cognitive ability. This is consistent with the idea that failure to develop dominance of one hemisphere is associated with various pathologies such as learning difficulties. Using the same data source but utilising additional data, evidence is found of a more complex relationship between cognitive ability and relative hand skill.

"... Take up thy bed, and vote." Measuring the relationship between voting behaviour and indicators of health.

In most countries health policy is an important part of the political agenda. Yet few studies have examined the relationship between the two. This study investigates the association between health and voter turnout in Britain using the National Child Development Study. Self-rated general health, the Malaise Inventory score and indicators of smoking and alcohol consumption, as measured at ages 23, 33 and 42, are regressed on voter turnout in the 1979, 1987 and 1997 general elections. The results indicate that individuals with poor general and mental health and smokers are less likely to vote at election time.

Effects of human and murine antisense oligonucleotide inhibitors of ICAM-1 on reproductive performance, fetal development, and post-natal development in mice.

The potential for reproductive toxicity of an antisense oligonucleotide designed to inhibit ICAM-1 was evaluated as part of the safety assessment for this compound. Since antisense compounds are often specific to the species in which they are intended to work, both the human and murine active ICAM-1 inhibitors were tested (ISIS 2302 and ISIS 3082, respectively). Male and female mice were treated prior to cohabitation, through cohabitation, gestation, delivery, and weaning. Mice were treated with 0, 3, 6, and 12 mg/kg ISIS 2302 or ISIS 3082 by daily i.v. injection. Reproductive indices evaluated included estrus cycling, sperm count and motility, fertility, litter parameters, fetal development, delivery, fetal body weight, lactation, and weaning. Behavioral assessment and reproductive capacity of the F1 generation mice was assessed on selected animals. Concentrations of oligonucleotide in selected maternal target organs, placenta, fetal tissues, and expressed milk were also measured. There were no changes in reproductive performance, litter parameters, fetal development, or postnatal development in mice treated with either ISIS 2302 or ISIS 3082. Maternal liver and kidney contained dose-dependent concentrations of oligonucleotide, but there was relatively little or no oligonucleotide measured in placenta, fetal tissues, or expressed milk. Neither the human nor murine-specific antisense inhibitor of ICAM-1 produced any reproductive toxicity in mice, and exposure of fetus or pups was negligible.