27 resultados para Rainfall indices
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BACKGROUND AND OBJECTIVE: Patient-specific quality of life indices show great potential, but certain conceptual and methodological concerns have yet to be fully addressed. The present study reviewed nine patient-specific instruments used in musculoskeletal disorders: the Canadian Occupational Performance Measure (COPM), Juvenile Arthritis Quality of life Questionnaire (JAQQ), McMaster-Toronto Arthritis questionnaire (MACTAR), Measure Yourself Medical Outcome Profile (MYMOP), Patient-Specific Index (PASI) for total hip arthroplasty, Problem Elicitation Technique (PET), Patient Generated Index (PGI) of quality of life, Patient-Specific Functional Scale (PSFS), and Schedule for the Evaluation of Individual Quality of Life (SEIQoL). STUDY DESIGN AND SETTING: Each tool was evaluated for purpose, content validity, face validity, feasibility, psychometric properties, and responsiveness. RESULTS: This critical appraisal revealed important differences in terms of the concept underlying these indices, the domains covered, the item-generation techniques and the scoring (response scale, methods) in each scale. The nine indices would generate different responses and likely scores for the same patient, despite the fact that they all include patient-generated items. CONCLUSION: Although the value of these indices in treatment planning and monitoring at an individual level is strong, more studies are needed to improve our understanding of how to interpret the numeric scores of patient-specific indices at both an individual and a group level.
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Background a nd A ims: There is a n ongoing d ebate which i sthe most appropriate w ay t o measure inflammatory boweldisease (IBD) activity (be it b y clinical i ndices, e ndoscopy, orbiomarkers). Accumulating evidence associates m ucosalhealing with a reduction in I BD-related s urgery andhospitalizations. We a imed to i nvestigate which outcomeparameters are used in daily practice for IBD monitoring.Methods: A q uestionnaire was sent in J uly 2010 t o all boardcertified gastroenterologists in S witzerland to evaluate t heassessment strategy of IBD activity, t he items on whichtherapeutic decisions w ere based upon, and the kind ofbiomarkers used for monitoring IBD activity.Results: Response rate was 57% (153/270). Mean physician'sage was 5 0±9years, mean duration o f gastroenterologicpractice 1 4±8years, 52% of them were working in p rivatepractice a nd 48% in h ospitals. S eventy-eight percent usedclinical activity i ndices as g old standard for IBD activityassessment, followed by 15% choosing endoscopic activity, and7% favouring biomarkers. Gastroenterologists based theirtherapeutic decisions in 70% on clinical activity indices, 24% onendoscopic activity, a nd 6% o n biomarkers. Most frequentlyused biomarkers were C-reactive protein (94%), complete bloodcount (78%) and fecal calprotectin (74%).Conclusions: I n daily p ractice, most IBD patients a remonitored based u pon t heir clinical a ctivity. B iomarkers a reperceived as l ess important compared to clinical andendoscopic activity. S imilar to activity a ssessment, alsotherapeutic decisions a re mostly made on the basis of clinicalactivity indices. The upcoming scientific evidence on the impactof mucosal h ealing does n ot yet seem to influence the dailypractice of gastroenterologists.
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Biomarkers of blood lipid modification and oxidative stress have been associated with increased cardiovascular morbidity. We sought to determine whether these biomarkers were related to functional indices of stenosis severity among patients with stable coronary artery disease. We studied 197 consecutive patients with stable coronary artery disease due to single vessel disease. Fractional flow reserve (FFR) ≤ 0.80 was assessed as index of a functionally significant lesion. Serum levels of secretory phospholipase A2 (sPLA2) activity, secretory phospholipase A2 type IIA (sPLA2-IIA), myeloperoxydase (MPO), lipoprotein-associated phospholipase A2 (Lp-PLA2), and oxidized low-density lipoprotein (OxLDL) were assessed using commercially available assays. Patients with FFR > 0.8 had higher sPLA2 activity, sPLA2 IIA, and OxLDL levels than patients with FFR ≤ 0.8 (21.25 [16.03-27.28] vs 25.85 [20.58-34.63] U/mL, p < 0.001, 2.0 [1.5-3.4] vs 2.6 [2.0-3.4] ng/mL, p < 0.01; and 53.0 [36.0-71.0] vs 64.5 [50-89.25], p < 0.001 respectively). Patients with FFR > 0.80 had similar Lp-PLA2 and MPO levels versus those with FFR ≤ 0.8. sPLA2 activity, sPLA2 IIA significantly increased area under the curve over baseline characteristics to predict FFR ≤ 0.8 (0.67 to 0.77 (95 % confidence interval [CI]: 0.69-0.85) p < 0.01 and 0.67 to 0.77 (95 % CI: 0.69-0.84) p < 0.01, respectively). Serum sPLA2 activity as well as sPLA2-IIA level is related to functional characteristics of coronary stenoses in patients with stable coronary artery disease.
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INTRODUCTION: Preoperative scores are widely used predictors of complications after major surgery. These scores, however, are not widely used in transurethral procedures. The aim of this study was to assess the value of the Charlson Comorbidity Index (CCI), the age-adjusted CCI, the American Society of Anesthesiologist score (ASA) and the Nutritional Risk Score (NRS) in predicting early morbidity after transurethral urological procedures. METHODS: Consecutive patients undergoing transurethral resection of the bladder or the prostate were prospectively enrolled. The scores were calculated preoperatively; 30-day complications were prospectively recorded according to the Dindo-Clavien classification. Univariate logistic regression was performed to investigate the value of each score and of other factors (i.e., age, sex, body mass index, anemia, smoking habit, type of operation and anaesthesia) as predictors of complications. A multivariate model was then calculated using these predictors. RESULTS: Overall, 197 patients were included. The mean age was 72 (standard deviation ± 10). In total, 26.9% patients had at least 1 complication. Using univariate analysis, we found that each score significantly predicted complications. In multivariate analysis, only the ASA (odds ration [OR] 2.11; 95% confidence interval [CI] 1.01-4.43) and the NRS (OR 2.42; 95% CI 1.56-3.74) remained independent predictors. The best model incorporated ASA, NRS and gender, and predicted morbidity with an area under the curve of 76%. Our study's main limitations are population heterogeneity and limited sample size. CONCLUSION: The ASA and the NRS are important and independent determinants of early morbidity after transurethral procedures. The use of these indices may assist clinicians in the decision-making process to balance the possible benefits of transurethral procedures with the potential risks.
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Reaching a consensus in terms of interchangeability and utility (i.e., disease detection/monitoring) of a medical device is the eventual aim of repeatability and agreement studies. The aim of the tolerance and relative utility indices described in this report is to provide a methodology to compare change in clinical measurement noise between different populations (repeatability) or measurement methods (agreement), so as to highlight problematic areas. No longitudinal data are required to calculate these indices. Both indices establish a metric of least to most effected across all parameters to facilitate comparison. If validated, these indices may prove useful tools when combining reports and forming the consensus required in the validation process for software updates and new medical devices.
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BACKGROUND: Globally, Africans and African Americans experience a disproportionate burden of type 2 diabetes, compared to other race and ethnic groups. The aim of the study was to examine the association of plasma glucose with indices of glucose metabolism in young adults of African origin from 5 different countries. METHODS: We identified participants from the Modeling the Epidemiologic Transition Study, an international study of weight change and cardiovascular disease (CVD) risk in five populations of African origin: USA (US), Jamaica, Ghana, South Africa, and Seychelles. For the current study, we included 667 participants (34.8 ± 6.3 years), with measures of plasma glucose, insulin, leptin, and adiponectin, as well as moderate and vigorous physical activity (MVPA, minutes/day [min/day]), daily sedentary time (min/day), anthropometrics, and body composition. RESULTS: Among the 282 men, body mass index (BMI) ranged from 22.1 to 29.6 kg/m(2) in men and from 25.8 to 34.8 kg/m(2) in 385 women. MVPA ranged from 26.2 to 47.1 min/day in men, and from 14.3 to 27.3 min/day in women and correlated with adiposity (BMI, waist size, and % body fat) only among US males after controlling for age. Plasma glucose ranged from 4.6 ± 0.8 mmol/L in the South African men to 5.8 mmol/L US men, while the overall prevalence for diabetes was very low, except in the US men and women (6.7 and 12 %, respectively). Using multivariate linear regression, glucose was associated with BMI, age, sex, smoking hypertension, daily sedentary time but not daily MVPA. CONCLUSION: Obesity, metabolic risk, and other potential determinants vary significantly between populations at differing stages of the epidemiologic transition, requiring tailored public health policies to address local population characteristics.
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Snow cover is an important control in mountain environments and a shift of the snow-free period triggered by climate warming can strongly impact ecosystem dynamics. Changing snow patterns can have severe effects on alpine plant distribution and diversity. It thus becomes urgent to provide spatially explicit assessments of snow cover changes that can be incorporated into correlative or empirical species distribution models (SDMs). Here, we provide for the first time a with a lower overestimation comparison of two physically based snow distribution models (PREVAH and SnowModel) to produce snow cover maps (SCMs) at a fine spatial resolution in a mountain landscape in Austria. SCMs have been evaluated with SPOT-HRVIR images and predictions of snow water equivalent from the two models with ground measurements. Finally, SCMs of the two models have been compared under a climate warming scenario for the end of the century. The predictive performances of PREVAH and SnowModel were similar when validated with the SPOT images. However, the tendency to overestimate snow cover was slightly lower with SnowModel during the accumulation period, whereas it was lower with PREVAH during the melting period. The rate of true positives during the melting period was two times higher on average with SnowModel with a lower overestimation of snow water equivalent. Our results allow for recommending the use of SnowModel in SDMs because it better captures persisting snow patches at the end of the snow season, which is important when modelling the response of species to long-lasting snow cover and evaluating whether they might survive under climate change.