Etude des Solanderiidae de la Baie de Hansa (Papouasie Nouvelle-Guinée) avec une révision du genre <i>Solanderia</i> (Cnidaria, Hydrozoa)

The morphology of the skeleton of the various species of the genus Solandria was studied by scanning electron microscopy. This allowed the listing of synonymies, and the number of valid species was reduced from 13 to 6. Keys and a comparison table have been established for species identification

Frailty in older age in the Whitehall II study: Measurement, validation, and predictive algorithms

BACKGROUND: With population ageing, prevention of frailty is increasingly important. However, significant gaps in the evidence base exist. Accordingly, the purpose of this thesis was to: (1) identify the current measures of frailty undertaking an overview; (2) validate the ‘phenotype of frailty’ using data from the Whitehall II study; and (3) examine the relation of cardiovascular disease (CVD) and diabetes risk factors with future frailty risk. METHODS AND RESULTS: For objective 1, a literature review identified 27 original articles describing 27 different frailty measurements. Of them, the most tested and frequently used measure was the ‘phenotype of frailty’ which comprises five components: weight loss, exhaustion, physical activity, walking speed, and grip strength. For objectives 2 and 3, I used data from the Whitehall II study, an occupationally-based cohort of 10,308 British men and women aged 35-55 years followed-up since 1985. Of the participants aged 55 to 79 years in 2007-2009 (n=5,169), 2.8% were frail and 38.6% pre-frail. Using survival analyses, in sex- and age-adjusted model, compared with the non-frail group, the frail group was 2.40 (95% confidence interval (CI): 1.83, 3.14) times more likely to be hospitalised for any cause during the mean follow-up of 15.2 months, while for the pre-frail group the risk was 1.20 (95%CI: 1.06, 1.35) greater. Logistic regression models were used to examine the performance of risk algorithms for CVD and diabetes assessed in 1997-1999 in predicting frailty in 2007-2009. CVD and diabetes risk scores were significantly associated with frailty: odds ratios per 1-standard deviation increment (disadvantage) in CVD scores ranged from 1.17 (95%CI: 1.10, 1.25) to 1.20 (95%CI: 1.13, 1.28) and in diabetes scores ranged from 1.05 (95%CI: 0.98, 1.14) to 1.27 (95%CI: 1.17, 1.37) depending on the risk score used. CONCLUSIONS: Both frailty and pre-frailty are associated with increased risk of hospitalisation. Better prevention of cardiovascular and diabetes risk factors in midlife is likely to reduce frailty at older ages

Diabetes Risk Factors, Diabetes Risk Algorithms, and the Prediction of Future Frailty: The Whitehall II Prospective Cohort Study

Objective: To examine whether established diabetes risk factors and diabetes risk algorithms are associated with future frailty. / Design: Prospective cohort study. Risk algorithms at baseline (1997–1999) were the Framingham Offspring, Cambridge, and Finnish diabetes risk scores. / Setting: Civil service departments in London, United Kingdom. / Participants: There were 2707 participants (72% men) aged 45 to 69 years at baseline assessment and free of diabetes. / Measurements: Risk factors (age, sex, family history of diabetes, body mass index, waist circumference, systolic and diastolic blood pressure, antihypertensive and corticosteroid treatments, history of high blood glucose, smoking status, physical activity, consumption of fruits and vegetables, fasting glucose, HDL-cholesterol, and triglycerides) were used to construct the risk algorithms. Frailty, assessed during a resurvey in 2007–2009, was denoted by the presence of 3 or more of the following indicators: self-reported exhaustion, low physical activity, slow walking speed, low grip strength, and weight loss; “prefrailty” was defined as having 2 or fewer of these indicators. / Results: After a mean follow-up of 10.5 years, 2.8% of the sample was classified as frail and 37.5% as prefrail. Increased age, being female, stopping smoking, low physical activity, and not having a daily consumption of fruits and vegetables were each associated with frailty or prefrailty. The Cambridge and Finnish diabetes risk scores were associated with frailty/prefrailty with odds ratios per 1 SD increase (disadvantage) in score of 1.18 (95% confidence interval: 1.09–1.27) and 1.27 (1.17–1.37), respectively. / Conclusion: Selected diabetes risk factors and risk scores are associated with subsequent frailty. Risk scores may have utility for frailty prediction in clinical practice

Cardiovascular disease risk scores in identifying future frailty: the Whitehall II prospective cohort study

Objectives: To examine the capacity of existing cardiovascular disease (CVD) risk algorithms widely used in primary care, to predict frailty. / Design: Prospective cohort study. Risk algorithms at baseline (1997–1999) were the Framingham CVD, coronary heart disease and stroke risk scores, and the Systematic Coronary Risk Evaluation. / Setting: Civil Service departments in London, UK. / Participants: 3895 participants (73% men) aged 45–69 years and free of CVD at baseline. / Main outcome measure: Status of frailty at the end of follow-up (2007–2009), based on the following indicators: self-reported exhaustion, low physical activity, slow walking speed, low grip strength and weight loss. / Results: At the end of the follow-up, 2.8% (n=108) of the sample was classified as frail. All four CVD risk scores were associated with future risk of developing frailty, with ORs per one SD increment in the score ranging from 1.35 (95% CI 1.21 to 1.51) for the Framingham stroke score to 1.42 (1.23 to 1.62) for the Framingham CVD score. These associations remained after excluding incident CVD cases. For comparison, the corresponding ORs for the risk scores and incident cardiovascular events varied between 1.36 (1.15 to 1.61) and 1.64 (1.50 to 1.80) depending on the risk algorithm. / Conclusions: The use of CVD risk scores in clinical practice may also have utility for frailty prediction

How reliable is MRI in diagnosing cartilaginous lesions in patients with first and recurrent lateral patellar dislocations?

<p>Abstract</p> <p>Background</p> <p>Lateral dislocation of the patella (LPD) leads to cartilaginous injuries, which have been reported to be associated with retropatellar complaints and the development of patellofemoral osteoarthritis. Therefore, the purpose of this study was to determine the reliability of MRI for cartilage diagnostics after a first and recurrent LPD.</p> <p>Methods</p> <p>After an average of 4.7 days following an acute LPD, 40 patients (21 with first LPDs and 19 with recurrent LPDs) underwent standardized 1.5 Tesla MRI (sagittal T1-TSE, coronal STIR-TSE, transversal fat-suppressed PD-TSE, sagittal fat-suppressed PD-TSE). MRI grading was compared to arthroscopic assessment of the cartilage.</p> <p>Results</p> <p>Sensitivities and positive predictive values for grade 3 and 4 lesions were markedly higher in the patient group with first LPDs compared to the group with recurrent LPDs. Similarly, intra- and inter-observer agreement yielded higher kappa values in patients with first LPDs compared to those with recurrent LPDs. All grade 4 lesions affecting the subchondral bone (osteochondral defects), such as a fissuring or erosion, were correctly assessed on MRI.</p> <p>Conclusions</p> <p>This study demonstrated a comparatively good diagnostic performance for MRI in the evaluation of first and recurrent LPDs, and we therefore recommend MRI for the cartilage assessment after a LPD.</p

Validating a widely used measure of frailty: are all sub-components necessary? Evidence from the Whitehall II cohort study

There is growing interest in the measurement of frailty in older age. The most widely used measure (Fried) characterizes this syndrome using five components: exhaustion, physical activity, walking speed, grip strength, and weight loss. These components overlap, raising the possibility of using fewer, and therefore making the device more time- and cost-efficient. The analytic sample was 5,169 individuals (1,419 women) from the British Whitehall II cohort study, aged 55 to 79 years in 2007–2009. Hospitalization data were accessed through English national records (mean follow-up 15.2 months). Age- and sex-adjusted Cox models showed that all components were significantly associated with hospitalization, the hazard ratios (HR) ranging from 1.18 (95 % confidence interval = 0.98, 1.41) for grip strength to 1.60 (1.35, 1.90) for usual walking speed. Some attenuation of these effects was apparent following mutual adjustment for frailty components, but the rank order of the strength of association remained unchanged. We observed a dose–response relationship between the number of frailty components and the risk for hospitalization [1 component—HR = 1.10 (0.96, 1.26); 2—HR = 1.52 (1.26, 1.83); 3–5—HR = 2.41 (1.84, 3.16), P trend <0.0001]. A concordance index used to evaluate the predictive power for hospital admissions of individual components and the full scale was modest in magnitude (range 0.57 to 0.58). Our results support the validity of the multi-component frailty measure, but the predictive performance of the measure is poor

Model‐based control of mechanical ventilation: design and clinical validation

Background. We developed a model‐based control system using end‐tidal carbon dioxide fraction (FE′CO2) to adjust a ventilator during clinical anaesthesia. Methods. We studied 16 ASA I-II patients (mean age 38 (range 20-59) yr; weight 67 (54-87) kg) during i.v. anaesthesia for elective surgery. After periods of normal ventilation the patients were either hyper‐ or hypoventilated to assess precision and dynamic behaviour of the control system. These data were compared with a previous group where a fuzzy‐logic controller had been used. Responses to different clinical events (invalid carbon dioxide measurement, limb tourniquet release, tube cuff leak, exhaustion of carbon dioxide absorbent, simulation of pulmonary embolism) were also noted. Results. The model‐based controller correctly maintained the setpoint. No significant difference was found for the static performance between the two controllers. The dynamic response of the model‐based controller was more rapid (P<0.05). The mean rise time after a setpoint increase of 1 vol% was 313 (sd 90) s and 142 (17) s for fuzzy‐logic and model‐based control, respectively, and after a 1 vol% decrease was 355 (127) s and 177 (36) s, respectively. The new model‐based controller had a consistent response to clinical artefacts. Conclusion. A model‐based FE′CO2 controller can be used in a clinical setting. It reacts appropriately to artefacts, and has a better dynamic response to setpoint changes than a previously described fuzzy‐logic controller. Br J Anaesth 2004; 92: 800-

Bone mineral content after renal transplantation

Forearm bone mineral content (BMC), as evaluated by photonabsorption densitometry, was measured in 28 cadaver kidney donor recipients who entered the study 8 weeks postoperatively and were followed up for 18 months. BMC decreased signifiantly (p<0.05) but marginally in placebo-treated patients (n=14) (initial BMC 1.09±0.25 g/cm; final BMC 1.05±0.24). Fourteen patients were prophylactically given 1,25(OH)2vitamin D3 in a dose which avoided hypercalcemia and hypercalciuria (sim0.25 µg/day); under 1,25(OH)2 vitamin D3 prophylaxis a significant decrease of forearm BMC was observed no longer (initial BMC 0.94±0.21 g/cm; final BMC 0.95±0.21), but the difference between placebo and 1,25(OH)2 vitamin D3 narrowly missed statistical significance (p=0.066). It is concluded that the decrease of forearm BMC is negligible in transplant recipients with low steroid regimens. The data suggest a trend for prophylaxis with 1,25(OH)2 vitamin D3 to slightly ameliorate forearm (cortical) BMC loss

Predictors of 25(OH)D half-life and plasma 25(OH)D concentration in The Gambia and the UK

Summary: Predictors of 25(OH)D3 half-life were factors associated with vitamin D metabolism, but were different between people in The Gambia and the UK. Country was the strongest predictor of plasma 25(OH)D concentration, probably as a marker of UVB exposure. 25(OH)D3 half-life may be applied as a tool to investigate vitamin D expenditure.  Introduction: The aim of this study was to investigate predictors of 25(OH)D3 half-life and plasma 25(OH)D concentration.  Methods: Plasma half-life of an oral tracer dose of deuterated-25(OH)D3 was measured in healthy men aged 24–39 years, resident in The Gambia, West Africa (n = 18) and in the UK during the winter (n = 18), countries that differ in calcium intake and vitamin D status. Plasma and urinary markers of vitamin D, calcium, phosphate and bone metabolism, nutrient intakes and anthropometry were measured.  Results: Normally distributed data are presented as mean (SD) and non-normal data as geometric mean (95 % CI). Gambian compared to UK men had higher plasma concentrations of 25(OH)D (69 (13) vs. 29 (11) nmol/L; P < 0.0001); 1,25(OH)2D (181 (165, 197) vs. 120 (109, 132) pmol/L; P < 0.01); and parathyroid hormone (PTH) (50 (42, 60) vs. 33 (27, 39); P < 0.0001). There was no difference in 25(OH)D3 half-life (14.7 (3.5) days vs. 15.6 (2.5) days) between countries (P = 0.2). In multivariate analyses, 25(OH)D, 1,25(OH)2D, vitamin D binding protein and albumin-adjusted calcium (Caalb) explained 79 % of variance in 25(OH)D3 half-life in Gambians, but no significant predictors were found in UK participants. For the countries combined, Caalb, PTH and plasma phosphate explained 39 % of half-life variability. 1,25(OH)2D, weight, PTH and country explained 81 % of variability in 25(OH)D concentration; however, country alone explained 74 %.  Conclusion: Factors known to affect 25(OH)D metabolism predict 25(OH)D3 half-life, but these differed between countries. Country predicted 25(OH)D, probably as a proxy measure for UVB exposure and vitamin D supply. This study supports the use of 25(OH)D half-life to investigate vitamin D metabolism