Separation of trait and state in stuttering

Stuttering is a disorder in which the smooth flow of speech is interrupted. People who stutter show structural and functional abnormalities in the speech and motor system. It is unclear whether functional differences reflect general traits of the disorder or are specifically related to the dysfluent speech state. We used a hierarchical approach to separate state and trait effects within stuttering. We collected sparse‐sampled functional MRI during two overt speech tasks (sentence reading and picture description) in 17 people who stutter and 16 fluent controls. Separate analyses identified indicators of: (1) general traits of people who stutter; (2) frequency of dysfluent speech states in subgroups of people who stutter; and (3) the differences between fluent and dysfluent states in people who stutter. We found that reduced activation of left auditory cortex, inferior frontal cortex bilaterally, and medial cerebellum were general traits that distinguished fluent speech in people who stutter from that of controls. The stuttering subgroup with higher frequency of dysfluent states during scanning (n = 9) had reduced activation in the right subcortical grey matter, left temporo‐occipital cortex, the cingulate cortex, and medial parieto‐occipital cortex relative to the subgroup who were more fluent (n = 8). Finally, during dysfluent states relative to fluent ones, there was greater activation of inferior frontal and premotor cortex extending into the frontal operculum, bilaterally. The above differences were seen across both tasks. Subcortical state effects differed according to the task. Overall, our data emphasise the independence of trait and state effects in stuttering

Modelling the distribution of white matter hyperintensities due to ageing on MRI images using Bayesian inference

White matter hyperintensities (WMH), also known as white matter lesions, are localised white matter areas that appear hyperintense on MRI scans. WMH commonly occur in the ageing population, and are often associated with several factors such as cognitive disorders, cardiovascular risk factors, cerebrovascular and neurodegenerative diseases. Despite the fact that some links between lesion location and parametric factors such as age have already been established, the relationship between voxel-wise spatial distribution of lesions and these factors is not yet well understood. Hence, it would be of clinical importance to model the distribution of lesions at the population-level and quantitatively analyse the effect of various factors on the lesion distribution model. In this work we compare various methods, including our proposed method, to generate voxel-wise distributions of WMH within a population with respect to various factors. Our proposed Bayesian spline method models the spatio-temporal distribution of WMH with respect to a parametric factor of interest, in this case age, within a population. Our probabilistic model takes as input the lesion segmentation binary maps of subjects belonging to various age groups and provides a population-level parametric lesion probability map as output. We used a spline representation to ensure a degree of smoothness in space and the dimension associated with the parameter, and formulated our model using a Bayesian framework. We tested our algorithm output on simulated data and compared our results with those obtained using various existing methods with different levels of algorithmic and computational complexity. We then compared the better performing methods on a real dataset, consisting of 1000 subjects of the UK Biobank, divided in two groups based on hypertension diagnosis. Finally, we applied our method on a clinical dataset of patients with vascular disease. On simulated dataset, the results from our algorithm showed a mean square error (MSE) value of , which was lower than the MSE value reported in the literature, with the advantage of being robust and computationally efficient. In the UK Biobank data, we found that the lesion probabilities are higher for the hypertension group compared to the non-hypertension group and further verified this finding using a statistical t-test. Finally, when applying our method on patients with vascular disease, we observed that the overall probability of lesions is significantly higher in later age groups, which is in line with the current literature

The impact of transfer learning on 3D deep learning convolutional neural network segmentation of the hippocampus in mild cognitive impairment and Alzheimer disease subjects

Research on segmentation of the hippocampus in magnetic resonance images through deep learning convolutional neural networks (CNNs) shows promising results, suggesting that these methods can identify small structural abnormalities of the hippocampus, which are among the earliest and most frequent brain changes associated with Alzheimer disease (AD). However, CNNs typically achieve the highest accuracy on datasets acquired from the same domain as the training dataset. Transfer learning allows domain adaptation through further training on a limited dataset. In this study, we applied transfer learning on a network called spatial warping network segmentation (SWANS), developed and trained in a previous study. We used MR images of patients with clinical diagnoses of mild cognitive impairment (MCI) and AD, segmented by two different raters. By using transfer learning techniques, we developed four new models, using different training methods. Testing was performed using 26% of the original dataset, which was excluded from training as a hold-out test set. In addition, 10% of the overall training dataset was used as a hold-out validation set. Results showed that all the new models achieved better hippocampal segmentation quality than the baseline SWANS model (ps <.001), with high similarity to the manual segmentations (mean dice [best model] = 0.878 ± 0.003). The best model was chosen based on visual assessment and volume percentage error (VPE). The increased precision in estimating hippocampal volumes allows the detection of small hippocampal abnormalities already present in the MCI phase (SD = [3.9 ± 0.6]%), which may be crucial for early diagnosis

The use of the SF-36 questionnaire in adult survivors of childhood cancer: evaluation of data quality, score reliability, and scaling assumptions

BACKGROUND: The SF-36 has been used in a number of previous studies that have investigated the health status of childhood cancer survivors, but it never has been evaluated regarding data quality, scaling assumptions, and reliability in this population. As health status among childhood cancer survivors is being increasingly investigated, it is important that the measurement instruments are reliable, validated and appropriate for use in this population. The aim of this paper was to determine whether the SF-36 questionnaire is a valid and reliable instrument in assessing self-perceived health status of adult survivors of childhood cancer. METHODS: We examined the SF-36 to see how it performed with respect to (1) data completeness, (2) distribution of the scale scores, (3) item-internal consistency, (4) item-discriminant validity, (5) internal consistency, and (6) scaling assumptions. For this investigation we used SF-36 data from a population-based study of 10,189 adult survivors of childhood cancer. RESULTS: Overall, missing values ranged per item from 0.5 to 2.9 percent. Ceiling effects were found to be highest in the role limitation-physical (76.7%) and role limitation-emotional (76.5%) scales. All correlations between items and their hypothesised scales exceeded the suggested standard of 0.40 for satisfactory item-consistency. Across all scales, the Cronbach's alpha coefficient of reliability was found to be higher than the suggested value of 0.70. Consistent across all cancer groups, the physical health related scale scores correlated strongly with the Physical Component Summary (PCS) scale scores and weakly with the Mental Component Summary (MCS) scale scores. Also, the mental health and role limitation-emotional scales correlated strongly with the MCS scale score and weakly with the PCS scale score. Moderate to strong correlations with both summary scores were found for the general health perception, energy/vitality, and social functioning scales. CONCLUSION: The findings presented in this paper provide support for the validity and reliability of the SF-36 when used in long-term survivors of childhood cancer. These findings should encourage other researchers and health care practitioners to use the SF-36 when assessing health status in this population, although it should be recognised that ceiling effects can occur

The development of a new measure of quality of life in the management of gastro-oesophageal reflux disease: the Reflux Questionnaire.

INTRODUCTION This paper reports on the development of a new measure of health-related quality of life for use among patients with gastro-oesophageal reflux disease (GORD), funded as part of the REFLUX trial. This is a large UK multi centre trial that aims to compare the clinical and cost effectiveness of minimal access surgery with best medical treatment for patients with GORD within the NHS. Method Potential items were identified via a series of interviews and focus groups carried out with patients who were receiving/had received medical or surgical treatment for GORD. The final measure consisted of 31 items covering 7 categories (Heartburn; Acid reflux; Wind; Eating and swallowing; Bowel movements; Sleep; Work, physical and social activities). The measure produced two outputs: a quality of life score (RQLS) and five Reflux symptom scores. Reliability (internal consistency), criterion validity with the SF-36 and, sensitivity to change in terms of relationship with reported change in prescribed medication were assessed amongst a sample of 794 patients recruited into the trial. RESULTS The measure was shown to be internally consistent, to show criterion validity with the SF-36 and sensitive to changes in patients use of prescribed medication at baseline and 3 month follow-up. DISCUSSION The Reflux questionnaire is a new self-administered questionnaire for use amongst patients with GORD. Initial findings suggest that the new measure is valid, reliable, acceptable to respondents and simple to administer in both a clinical and research context

Maximising response to postal questionnaires – A systematic review of randomised trials in health research

Background Postal self-completion questionnaires offer one of the least expensive modes of collecting patient based outcomes in health care research. The purpose of this review is to assess the efficacy of methods of increasing response to postal questionnaires in health care studies on patient populations. Methods The following databases were searched: Medline, Embase, CENTRAL, CDSR, PsycINFO, NRR and ZETOC. Reference lists of relevant reviews and relevant journals were hand searched. Inclusion criteria were randomised trials of strategies to improve questionnaire response in health care research on patient populations. Response rate was defined as the percentage of questionnaires returned after all follow-up efforts. Study quality was assessed by two independent reviewers. The Mantel-Haenszel method was used to calculate the pooled odds ratios. Results Thirteen studies reporting fifteen trials were included. Implementation of reminder letters and telephone contact had the most significant effect on response rates (odds ratio 3.7, 95% confidence interval 2.30 to 5.97 p = <0.00001). Shorter questionnaires also improved response rates to a lesser degree (odds ratio 1.4, 95% confidence interval 1.19 to 1.54). No evidence was found that incentives, re-ordering of questions or including an information brochure with the questionnaire confer any additional advantage. Conclusion Implementing repeat mailing strategies and/or telephone reminders may improve response to postal questionnaires in health care research. Making the questionnaire shorter may also improve response rates. There is a lack of evidence to suggest that incentives are useful. In the context of health care research all strategies to improve response to postal questionnaires require further evaluation

White matter hyperintensities classified according to intensity and spatial location reveal specific associations with cognitive performance.

White matter hyperintensities (WMHs) on T2-weighted images are radiological signs of cerebral small vessel disease. As their total volume is variably associated with cognition, a new approach that integrates multiple radiological criteria is warranted. Location may matter, as periventricular WMHs have been shown to be associated with cognitive impairments. WMHs that appear as hypointense in T1-weighted images (T1w) may also indicate the most severe component of WMHs. We developed an automatic method that sub-classifies WMHs into four categories (periventricular/deep and T1w-hypointense/nonT1w-hypointense) using MRI data from 684 community-dwelling older adults from the Whitehall II study. To test if location and intensity information can impact cognition, we derived two general linear models using either overall or subdivided volumes. Results showed that periventricular T1w-hypointense WMHs were significantly associated with poorer performance in the trail making A (p = 0.011), digit symbol (p = 0.028) and digit coding (p = 0.009) tests. We found no association between total WMH volume and cognition. These findings suggest that sub-classifying WMHs according to both location and intensity in T1w reveals specific associations with cognitive performance

Is volunteering a public health intervention? A systematic review and meta-analysis of the health and survival of volunteers

Background Volunteering has been advocated by the United Nations, and American and European governments as a way to engage people in their local communities and improve social capital, with the potential for public health benefits such as improving wellbeing and decreasing health inequalities. Furthermore, the US Corporation for National and Community Service Strategic Plan for 2011–2015 focused on increasing the impact of national service on community needs, supporting volunteers’ wellbeing, and prioritising recruitment and engagement of underrepresented populations. The aims of this review were to examine the effect of formal volunteering on volunteers’ physical and mental health and survival, and to explore the influence of volunteering type and intensity on health outcomes. Methods Experimental and cohort studies comparing the physical and mental health outcomes and mortality of a volunteering group to a non-volunteering group were identified from twelve electronic databases (Cochrane Library, Medline, Embase, PsychINFO, CINAHL, ERIC, HMIC, SSCI, ASSIA, Social Care Online, Social Policy and Practice) and citation tracking in January 2013. No language, country or date restrictions were applied. Data synthesis was based on vote counting and random effects meta-analysis of mortality risk ratios. Results Forty papers were selected: five randomised controlled trials (RCTs, seven papers); four non-RCTs; and 17 cohort studies (29 papers). Cohort studies showed volunteering had favourable effects on depression, life satisfaction, wellbeing but not on physical health. These findings were not confirmed by experimental studies. Meta-analysis of five cohort studies found volunteers to be at lower risk of mortality (risk ratio: 0.78; 95% CI: 0.66, 0.90). There was insufficient evidence to demonstrate a consistent influence of volunteering type or intensity on outcomes. Conclusion Observational evidence suggested that volunteering may benefit mental health and survival although the causal mechanisms remain unclear. Consequently, there was limited robustly designed research to guide the development of volunteering as a public health promotion intervention. Future studies should explicitly map intervention design to clear health outcomes as well as use pragmatic RCT methodology to test effects

Blood levels of adiponectin and IL-1Ra distinguish type 3c from type 2 diabetes: Implications for earlier pancreatic cancer detection in new-onset diabetes

BACKGROUND: Screening for pancreatic ductal adenocarcinoma (PDAC) in populations at high risk is recommended. Individuals with new-onset type 2 diabetes mellitus (NOD) are the largest high-risk group for PDAC. To facilitate screening, we sought biomarkers capable of stratifying NOD subjects into those with type 2 diabetes mellitus (T2DM) and those with the less prevalent PDAC-related diabetes (PDAC-DM), a form of type 3c DM commonly misdiagnosed as T2DM. METHODS: Using mass spectrometry- and immunoassay-based methodologies in a multi-stage analysis of independent sample sets (n=443 samples), blood levels of 264 proteins were considered using Ingenuity Pathway Analysis, literature review and targeted training and validation. FINDINGS: Of 30 candidate biomarkers evaluated in up to four independent patient sets, 12 showed statistically significant differences in levels between PDAC-DM and T2DM. The combination of adiponectin and interleukin-1 receptor antagonist (IL-1Ra) showed strong diagnostic potential, (AUC of 0.91; 95% CI: 0.84-0.99) for the distinction of T3cDM from T2DM. INTERPRETATION: Adiponectin and IL-1Ra warrant further consideration for use in screening for PDAC in individuals newly-diagnosed with T2DM. FUNDING: North West Cancer Research, UK, Cancer Research UK, Pancreatic Cancer Action, UK

Quality of life and burden of morbidity in primary care users with multimorbidity

Purpose: The aim of this study was to assess the quality of life, number of diseases and burden of morbidity of multimorbid primary care users and whether a simple disease count or a multimorbidity burden score is more predictive of quality of life. Patients and methods: Primary care patients with at least 1 of 11 specified chronic conditions were invited to participate in a postal survey. Participants completed the Disease Burden Impact Scale (DBIS) questionnaire, the five dimension-five level Euro-Qol (EQ-5D-5L) and standard demographics questions. The DBIS asks participants to self-report chronic conditions and to rate the impact of each condition. Descriptive statistics and analysis of variance were used to determine quality of life, count of diseases and burden of morbidity. Multiple linear regression analyses determined whether disease count or the DBIS, adjusted for demographics, was more predictive of the EQ-5D-5L scores. Results: Thirty-one percent (n=917) responded, from which 69 were excluded as they reported no or only one condition, leaving 848 (92%) in the analysis. Slightly more women (50.9%) participated; the mean age was 67.0 (SD 13.9) and the mean number of conditions was 6.5 (SD 3.49). The mean scores were: DBIS 15.5 (SD 12.00; score range 0–140, with higher scores indicating higher multimorbidity burden), EQ-5D-5L score 0.69 (SD 0.28; score range −0.28 [a state worse than death] to 1 [best possible health state]) and EQ-5D Visual Analog Scale (EQ-VAS) 65.44 (SD 23.66; score range 0–100 with higher scores meaning better health). The model using the DBIS score was more predictive of the EQ-5D-5L score and EQ-VAS than the model using the disease count (R2adj=0.53 using DBIS and R2adj=0.42 using disease count for EQ-5D-5L score, and R2adj=0.44 using DBIS versus R2adj=0.34 using disease count for EQ-VAS). All models were statistically significant (p<0.001). Conclusion: The DBIS is a useful measure for assessing multimorbidity from the perspective of primary care users in particular, as it is more predictive of health outcomes than a simple count of conditions