Prognostic ability of practitioners of traditional arabic medicine: comparison with Western methods through a relative patient progress scale.

The ancient Greek medical theory based on balance or imbalance of humors disappeared in the western world, but does survive elsewhere. Is this survival related to a certain degree of health care efficiency? We explored this hypothesis through a study of classical Greco-Arab medicine in Mauritania. Modern general practitioners evaluated the safety and effectiveness of classical Arabic medicine in a Mauritanian traditional clinic, with a prognosis/follow-up method allowing the following comparisons: (i) actual patient progress (clinical outcome) compared with what the traditional 'tabib' had anticipated (= prognostic ability) and (ii) patient progress compared with what could be hoped for if the patient were treated by a modern physician in the same neighborhood. The practice appeared fairly safe and, on average, clinical outcome was similar to what could be expected with modern medicine. In some cases, patient progress was better than expected. The ability to correctly predict an individual's clinical outcome did not seem to be better along modern or Greco-Arab theories. Weekly joint meetings (modern and traditional practitioners) were spontaneously organized with a modern health centre in the neighborhood. Practitioners of a different medical system can predict patient progress. For the patient, avoiding false expectations with health care and ensuring appropriate referral may be the most important. Prognosis and outcome studies such as the one presented here may help to develop institutions where patients find support in making their choices, not only among several treatment options, but also among several medical systems.

Knowledge of Glasgow coma scale by air-rescue physicians.

OBJECTIVE: To assess the theoretical and practical knowledge of the Glasgow Coma Scale (GCS) by trained Air-rescue physicians in Switzerland. METHODS: Prospective anonymous observational study with a specially designed questionnaire. General knowledge of the GCS and its use in a clinical case were assessed. RESULTS: From 130 questionnaires send out, 103 were returned (response rate of 79.2%) and analyzed. Theoretical knowledge of the GCS was consistent for registrars, fellows, consultants and private practitioners active in physician-staffed helicopters. The clinical case was wrongly scored by 38 participants (36.9%). Wrong evaluation of the motor component occurred in 28 questionnaires (27.2%), and 19 errors were made for the verbal score (18.5%). Errors were made most frequently by registrars (47.5%, p = 0.09), followed by fellows (31.6%, p = 0.67) and private practitioners (18.4%, p = 1.00). Consultants made significantly less errors than the rest of the participating physicians (0%, p < 0.05). No statistically significant differences were shown between anesthetists, general practitioners, internal medicine trainees or others. CONCLUSION: Although the theoretical knowledge of the GCS by out-of-hospital physicians is correct, significant errors were made in scoring a clinical case. Less experienced physicians had a higher rate of errors. Further emphasis on teaching the GCS is mandatory.

Ascertaining late-life depressive symptoms in Europe: an evaluation of the survey version of the EURO-D scale in 10 nations. The SHARE project.

The reported prevalence of late-life depressive symptoms varies widely between studies, a finding that might be attributed to cultural as well as methodological factors. The EURO-D scale was developed to allow valid comparison of prevalence and risk associations between European countries. This study used Confirmatory Factor Analysis (CFA) and Rasch models to assess whether the goal of measurement invariance had been achieved; using EURO-D scale data collected in 10 European countries as part of the Survey of Health, Ageing and Retirement in Europe (SHARE) (n = 22,777). The results suggested a two-factor solution (Affective Suffering and Motivation) after Principal Component Analysis (PCA) in 9 of the 10 countries. With CFA, in all countries, the two-factor solution had better overall goodness-of-fit than the one-factor solution. However, only the Affective Suffering subscale was equivalent across countries, while the Motivation subscale was not. The Rasch model indicated that the EURO-D was a hierarchical scale. While the calibration pattern was similar across countries, between countries agreement in item calibrations was stronger for the items loading on the affective suffering than the motivation factor. In conclusion, there is evidence to support the EURO-D as either a uni-dimensional or bi-dimensional scale measure of depressive symptoms in late-life across European countries. The Affective Suffering sub-component had more robust cross-cultural validity than the Motivation sub-component.

Subjective Memory Deficits in People with and without Dementia: Findings from the 10/66 Dementia Research Group Pilot Studies in Low- and Middle-Income Countries

OBJECTIVES To compare subjective memory deficit (SMD) in older adults with and without dementia or depression across multiple centers in low- and middle-income countries (LAMICs). DESIGN Secondary analysis of data from 23 case control studies. SETTING Twenty-three centers in India, Southeast Asia (including China), Latin America and the Caribbean, Nigeria, and Russia. PARTICIPANTS Two thousand six hundred ninety-two community-dwelling people aged 60 and older in one of three groups: people with dementia, people with depression, and controls free of dementia and depression. MEASUREMENTS SMD was derived from the Geriatric Mental State examination. RESULTS Median SMD frequency was lowest in participants without dementia (26.2%) and higher in those with depression (50.0%) and dementia (66.7%). Frequency of SMD varied between centers. Depression and dementia were consistently associated with SMD. Older age and hypochondriasis were associated with SMD only in subjects without dementia. In those with dementia, SMD was associated with better cognitive function, whereas the reverse was the case in controls. CONCLUSION Associations with SMD may differ between subjects with and without dementia living in LAMICs.

Pioglitazone improves fat distribution, the adipokine profile and hepatic insulin sensitivity in non-diabetic end-stage renal disease subjects on maintenance dialysis: a randomized cross-over pilot study.

BACKGROUND: Fat redistribution, increased inflammation and insulin resistance are prevalent in non-diabetic subjects treated with maintenance dialysis. The aim of this study was to test whether pioglitazone, a powerful insulin sensitizer, alters body fat distribution and adipokine secretion in these subjects and whether it is associated with improved insulin sensitivity. TRIAL DESIGN: This was a double blind cross-over study with 16 weeks of pioglitazone 45 mg vs placebo involving 12 subjects. METHODS: At the end of each phase, body composition (anthropometric measurements, dual energy X-ray absorptometry (DEXA), abdominal CT), hepatic and muscle insulin sensitivity (2-step hyperinsulinemic euglycemic clamp with 2H2-glucose) were measured and fasting blood adipokines and cardiometabolic risk markers were monitored. RESULTS: Four months treatment with pioglitazone had no effect on total body weight or total fat but decreased the visceral/sub-cutaneous adipose tissue ratio by 16% and decreased the leptin/adiponectin (L/A) ratio from 3.63×10-3 to 0.76×10-3. This was associated with a 20% increase in hepatic insulin sensitivity without changes in muscle insulin sensitivity, a 12% increase in HDL cholesterol and a 50% decrease in CRP. CONCLUSIONS/LIMITATIONS: Pioglitazone significantly changes the visceral-subcutaneous fat distribution and plasma L/A ratio in non diabetic subjects on maintenance dialysis. This was associated with improved hepatic insulin sensitivity and a reduction of cardio-metabolic risk markers. Whether these effects may improve the outcome of non diabetic end-stage renal disease subjects on maintenance dialysis still needs further evaluation. TRIAL REGISTRATION: ClinicalTrial.gov NCT01253928.

Orthogonal higher order structure and confirmatory factor analysis of the French Wechsler Adult Intelligence Scale (WAIS-III).

According to the most widely accepted Cattell-Horn-Carroll (CHC) model of intelligence measurement, each subtest score of the Wechsler Intelligence Scale for Adults (3rd ed.; WAIS-III) should reflect both 1st- and 2nd-order factors (i.e., 4 or 5 broad abilities and 1 general factor). To disentangle the contribution of each factor, we applied a Schmid-Leiman orthogonalization transformation (SLT) to the standardization data published in the French technical manual for the WAIS-III. Results showed that the general factor accounted for 63% of the common variance and that the specific contributions of the 1st-order factors were weak (4.7%-15.9%). We also addressed this issue by using confirmatory factor analysis. Results indicated that the bifactor model (with 1st-order group and general factors) better fit the data than did the traditional higher order structure. Models based on the CHC framework were also tested. Results indicated that a higher order CHC model showed a better fit than did the classical 4-factor model; however, the WAIS bifactor structure was the most adequate. We recommend that users do not discount the Full Scale IQ when interpreting the index scores of the WAIS-III because the general factor accounts for the bulk of the common variance in the French WAIS-III. The 4 index scores cannot be considered to reflect only broad ability because they include a strong contribution of the general factor.

Assessing depression outcome in patients with moderate dementia: sensitivity of the HoNOS65+ scale.

To date, there is no widely accepted clinical scale to monitor the evolution of depressive symptoms in demented patients. We assessed the sensitivity to treatment of a validated French version of the Health of the Nation Outcome Scale (HoNOS) 65+ compared to five routinely used scales. Thirty elderly inpatients with ICD-10 diagnosis of dementia and depression were evaluated at admission and discharge using paired t-test. Using the Brief Psychiatric Rating Scale (BPRS) "depressive mood" item as gold standard, a receiver operating characteristic curve (ROC) analysis assessed the validity of HoNOS65+F "depressive symptoms" item score changes. Unlike Geriatric Depression Scale, Mini Mental State Examination and Activities of Daily Living scores, BPRS scores decreased and Global Assessment Functioning Scale score increased significantly from admission to discharge. Amongst HoNOS65+F items, "behavioural disturbance", "depressive symptoms", "activities of daily life" and "drug management" items showed highly significant changes between the first and last day of hospitalization. The ROC analysis revealed that changes in the HoNOS65+F "depressive symptoms" item correctly classified 93% of the cases with good sensitivity (0.95) and specificity (0.88) values. These data suggest that the HoNOS65+F "depressive symptoms" item may provide a valid assessment of the evolution of depressive symptoms in demented patients.

Pilot HIA of European Employment Strategy in Ireland

This pilot Health Impact Assessment (HIA) exercise was conducted as part of the ‘Policy Health Impact Assessment for the European Union’, commissioned by the European Commission ’s Directorate Generale Health and Consumer Protection (DG Sanco). The project is coordinated by Liverpool University and the research partners are from Ireland, Germany and the Netherlands. The aim of the European project is to develop a HIA methodology for assessing the health impacts of EU policies and activities. The purpose of the pilot HIA in Ireland was to test the methodology produced in the first phase of the project in 2002. The policy chosen for assessment was the European Employment Strategy. The Irish pilot used a range of methods suggested in the draft methodology but concentrated particularly on the participatory aspects of HIA. A key stakeholder group with knowledge of employment (including decision makers in labour market policy) was established to provide expert advice and support. Other methods used included policy analysis, information gathering from key informants, community profiling (including demographic and labour force data), data analysis, literature review, the production of a report and the development of recommendations.

Knowledge of Glasgow coma scale by air-rescue physicians

Rapport de synthèse Introduction : Le Glasgow coma score (GCS) est un outil reconnu permettant l'évaluation des patients après avoir subi un traumatisme crânien. Il est réputé pour sa simplicité et sa reproductibilité permettant ainsi aux soignants une évaluation appropriée et continue du status neurologique des patients. Le GCS est composé de trois catégories évaluant la réponse oculaire, verbale et motrice. En Suisse, les soins préhospitaliers aux patients victimes d'un trauma crânien sévère sont effectués par des médecins, essdntiellement à bord des hélicoptères médicalisés. Avant une anesthésie générale nécessaire à ces patients, une évaluation du GCS est essentielle indiquant au personnel hospitalier la gravité des lésions cérébrales. Afin d'évaluer la connaissance du GCS par les médecins à bord des hélicoptères médicalisés en Suisse, nous avons élaboré un questionnaire, contenant dans une première partie des questions sur les connaissances générales du GCS suivi d'un cas clinique. Objectif : Evaluation des connaissances pratiques et théoriques du GCS par les médecins travaillant à bord des hélicoptères médicalisés en Suisse. Méthode : Etude observationnelle prospective et anonymisée à l'aide d'un questionnaire. Evaluation des connaissances générales du GCS et de son utilisation clinique lors de la présentation d'un cas. Résultats : 16 des 18 bases d'hélicoptères médicalisés suisses ont participé à notre étude. 130 questionnaires ont été envoyés et le taux de réponse a été de 79.2%. Les connaissances théoriques du GCS étaient comparables pour tous les médecins indépendamment de leur niveau de formation. Des erreurs dans l'appréciation du cas clinique étaient présentes chez 36.9% des participants. 27.2% ont commis des erreurs dans le score moteur et 18.5% dans le score verbal. Les erreurs ont été répertoriées le plus fréquemment chez les médecins assistants (47.5%, p=0.09), suivi par les chefs de clinique (31.6%, p=0.67) et les médecins installés en cabinet (18.4%, p=1.00). Les médecins cadres ont fait significativement moins d'erreurs que les autres participants (0%, p<0.05). Aucune différence significative n'à été observée entre les différentes spécialités (anesthésie, médecine interne, médecine général et «autres »). Conclusion Même si les connaissances théoriques du GCS sont adéquates parmi les médecins travaillant à bord des hélicoptères médicalisés, des erreurs dans son application clinique sont présentes dans plus d'un tiers des cas. Les médecins avec le moins d'expériences professionnelle font le plus d'erreurs. Au vu de l'importance de l'évaluation correcte du score de Glasgow initial, une amélioration des connaissances est indispensable.

Estudi per la selecció de CAG pel procés de potabilització de l'ETAP Ter

El present document representa l’estudi per la selecció de CAG pel procés de potabilització de l’ETAP Ter a partir d’un disseny experimental de planta pilot de menor escala. Es determina l'adequació de carbó en base a les característiques físiques (superfície BET, índex de iode...) i la capacitat d’eliminació de COT i UV respecte la mostra a tractar.

A modular approach for integrative analysis of large-scale gene-expression and drug-response data

High-throughput technologies are now used to generate more than one type of data from the same biological samples. To properly integrate such data, we propose using co-modules, which describe coherent patterns across paired data sets, and conceive several modular methods for their identification. We first test these methods using in silico data, demonstrating that the integrative scheme of our Ping-Pong Algorithm uncovers drug-gene associations more accurately when considering noisy or complex data. Second, we provide an extensive comparative study using the gene-expression and drug-response data from the NCI-60 cell lines. Using information from the DrugBank and the Connectivity Map databases we show that the Ping-Pong Algorithm predicts drug-gene associations significantly better than other methods. Co-modules provide insights into possible mechanisms of action for a wide range of drugs and suggest new targets for therapy

Causeway HSS Trust - Public Health Practice Development Pilot Report (PDF 257 KB)

Final Causeway HSS Trust Report on its Public Health Practice Development Pilot, part of the Department's redesign of community nursing project

Craigavon & Banbridge Community HSS Trust - Primary Care Mental Health Services Triage Pilot Scheme (PDF 266 KB)

Craigavon & Banbridge Community HSS Trust's final report on Primary Care Mental Health Services Triage Pilot Scheme. Part of the Department's redesign of community nursing project.

Quantitative integration of geophysical and hydraulic data : from the local towards the regional scale range

Des progrès significatifs ont été réalisés dans le domaine de l'intégration quantitative des données géophysique et hydrologique l'échelle locale. Cependant, l'extension à de plus grandes échelles des approches correspondantes constitue encore un défi majeur. Il est néanmoins extrêmement important de relever ce défi pour développer des modèles fiables de flux des eaux souterraines et de transport de contaminant. Pour résoudre ce problème, j'ai développé une technique d'intégration des données hydrogéophysiques basée sur une procédure bayésienne de simulation séquentielle en deux étapes. Cette procédure vise des problèmes à plus grande échelle. L'objectif est de simuler la distribution d'un paramètre hydraulique cible à partir, d'une part, de mesures d'un paramètre géophysique pertinent qui couvrent l'espace de manière exhaustive, mais avec une faible résolution (spatiale) et, d'autre part, de mesures locales de très haute résolution des mêmes paramètres géophysique et hydraulique. Pour cela, mon algorithme lie dans un premier temps les données géophysiques de faible et de haute résolution à travers une procédure de réduction déchelle. Les données géophysiques régionales réduites sont ensuite reliées au champ du paramètre hydraulique à haute résolution. J'illustre d'abord l'application de cette nouvelle approche dintégration des données à une base de données synthétiques réaliste. Celle-ci est constituée de mesures de conductivité hydraulique et électrique de haute résolution réalisées dans les mêmes forages ainsi que destimations des conductivités électriques obtenues à partir de mesures de tomographic de résistivité électrique (ERT) sur l'ensemble de l'espace. Ces dernières mesures ont une faible résolution spatiale. La viabilité globale de cette méthode est testée en effectuant les simulations de flux et de transport au travers du modèle original du champ de conductivité hydraulique ainsi que du modèle simulé. Les simulations sont alors comparées. Les résultats obtenus indiquent que la procédure dintégration des données proposée permet d'obtenir des estimations de la conductivité en adéquation avec la structure à grande échelle ainsi que des predictions fiables des caractéristiques de transports sur des distances de moyenne à grande échelle. Les résultats correspondant au scénario de terrain indiquent que l'approche d'intégration des données nouvellement mise au point est capable d'appréhender correctement les hétérogénéitées à petite échelle aussi bien que les tendances à gande échelle du champ hydraulique prévalent. Les résultats montrent également une flexibilté remarquable et une robustesse de cette nouvelle approche dintégration des données. De ce fait, elle est susceptible d'être appliquée à un large éventail de données géophysiques et hydrologiques, à toutes les gammes déchelles. Dans la deuxième partie de ma thèse, j'évalue en détail la viabilité du réechantillonnage geostatique séquentiel comme mécanisme de proposition pour les méthodes Markov Chain Monte Carlo (MCMC) appliquées à des probmes inverses géophysiques et hydrologiques de grande dimension . L'objectif est de permettre une quantification plus précise et plus réaliste des incertitudes associées aux modèles obtenus. En considérant une série dexemples de tomographic radar puits à puits, j'étudie deux classes de stratégies de rééchantillonnage spatial en considérant leur habilité à générer efficacement et précisément des réalisations de la distribution postérieure bayésienne. Les résultats obtenus montrent que, malgré sa popularité, le réechantillonnage séquentiel est plutôt inefficace à générer des échantillons postérieurs indépendants pour des études de cas synthétiques réalistes, notamment pour le cas assez communs et importants où il existe de fortes corrélations spatiales entre le modèle et les paramètres. Pour résoudre ce problème, j'ai développé un nouvelle approche de perturbation basée sur une déformation progressive. Cette approche est flexible en ce qui concerne le nombre de paramètres du modèle et lintensité de la perturbation. Par rapport au rééchantillonage séquentiel, cette nouvelle approche s'avère être très efficace pour diminuer le nombre requis d'itérations pour générer des échantillons indépendants à partir de la distribution postérieure bayésienne. - Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending corresponding approaches beyond the local scale still represents a major challenge, yet is critically important for the development of reliable groundwater flow and contaminant transport models. To address this issue, I have developed a hydrogeophysical data integration technique based on a two-step Bayesian sequential simulation procedure that is specifically targeted towards larger-scale problems. The objective is to simulate the distribution of a target hydraulic parameter based on spatially exhaustive, but poorly resolved, measurements of a pertinent geophysical parameter and locally highly resolved, but spatially sparse, measurements of the considered geophysical and hydraulic parameters. To this end, my algorithm links the low- and high-resolution geophysical data via a downscaling procedure before relating the downscaled regional-scale geophysical data to the high-resolution hydraulic parameter field. I first illustrate the application of this novel data integration approach to a realistic synthetic database consisting of collocated high-resolution borehole measurements of the hydraulic and electrical conductivities and spatially exhaustive, low-resolution electrical conductivity estimates obtained from electrical resistivity tomography (ERT). The overall viability of this method is tested and verified by performing and comparing flow and transport simulations through the original and simulated hydraulic conductivity fields. The corresponding results indicate that the proposed data integration procedure does indeed allow for obtaining faithful estimates of the larger-scale hydraulic conductivity structure and reliable predictions of the transport characteristics over medium- to regional-scale distances. The approach is then applied to a corresponding field scenario consisting of collocated high- resolution measurements of the electrical conductivity, as measured using a cone penetrometer testing (CPT) system, and the hydraulic conductivity, as estimated from electromagnetic flowmeter and slug test measurements, in combination with spatially exhaustive low-resolution electrical conductivity estimates obtained from surface-based electrical resistivity tomography (ERT). The corresponding results indicate that the newly developed data integration approach is indeed capable of adequately capturing both the small-scale heterogeneity as well as the larger-scale trend of the prevailing hydraulic conductivity field. The results also indicate that this novel data integration approach is remarkably flexible and robust and hence can be expected to be applicable to a wide range of geophysical and hydrological data at all scale ranges. In the second part of my thesis, I evaluate in detail the viability of sequential geostatistical resampling as a proposal mechanism for Markov Chain Monte Carlo (MCMC) methods applied to high-dimensional geophysical and hydrological inverse problems in order to allow for a more accurate and realistic quantification of the uncertainty associated with the thus inferred models. Focusing on a series of pertinent crosshole georadar tomographic examples, I investigated two classes of geostatistical resampling strategies with regard to their ability to efficiently and accurately generate independent realizations from the Bayesian posterior distribution. The corresponding results indicate that, despite its popularity, sequential resampling is rather inefficient at drawing independent posterior samples for realistic synthetic case studies, notably for the practically common and important scenario of pronounced spatial correlation between model parameters. To address this issue, I have developed a new gradual-deformation-based perturbation approach, which is flexible with regard to the number of model parameters as well as the perturbation strength. Compared to sequential resampling, this newly proposed approach was proven to be highly effective in decreasing the number of iterations required for drawing independent samples from the Bayesian posterior distribution.