94 resultados para c-index


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In many fields, the spatial clustering of sampled data points has many consequences. Therefore, several indices have been proposed to assess the level of clustering affecting datasets (e.g. the Morisita index, Ripley's Kfunction and Rényi's generalized entropy). The classical Morisita index measures how many times it is more likely to select two measurement points from the same quadrats (the data set is covered by a regular grid of changing size) than it would be in the case of a random distribution generated from a Poisson process. The multipoint version (k-Morisita) takes into account k points with k >= 2. The present research deals with a new development of the k-Morisita index for (1) monitoring network characterization and for (2) detection of patterns in monitored phenomena. From a theoretical perspective, a connection between the k-Morisita index and multifractality has also been found and highlighted on a mathematical multifractal set.

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AIM: The clinical relevance of sentinel lymph node (SLN) analysis was evaluated prospectively and compared with other known risk factors of relapse in early stage melanoma. METHODS: Surgery was guided by lymphoscintigraphy, blue dye and gamma probe detection. SLN were analysed by haematoxylin eosin (HE) histochemistry and multimarker immunohistochemistry (IHC). Disease free survival (DFS) was evaluated with Kaplan-Meier plots according to different parameters and Cox analyses of variance. RESULTS: From 210 patients a total of 381 SLN were excised. Lymphoscintigraphy identified all excised SLN with only 2 false positive lymphatic lakes. Fifty patients (24%) had tumour positive SLN. With a mean follow-up of 31.3 months, 29 tumour recurrences were observed, 19 (38%) in 50 SLN positive and 10 (6%) in 160 SLN negative patients. Strong predictive factors for early relapse (p < 0.0005) were SLN positivity and a high Breslow index. CONCLUSION: SLN tumour positivity is an independent factor of high risk for early relapse with a higher power of discrimination than the Breslow index.

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Background: Mucosal healing in ulcerative colitis (UC) is reported to be associated with favourable clinical outcomes such as reduced hospitalization and surgery rates. Activity monitoring by endoscopy has its shortcomings due to invasiveness, costs, and potential patient discomfort. Data on the correlation of noninvasive biomarkers with endoscopic severity in UC are scarce. Aim: to evaluate the correlation between endoscopic activity according to the modified Baron Index and fecal calprotectin, C-reactive protein (CRP), blood leukocytes, and the Lichtiger Index (clinical score). Methods: UC patients with leftsided and extensive colitis undergoing complete colonoscopy were prospectively enrolled and scored clinically and endoscopically. Fecal and blood samples were analyzed in UC patients (in a blinded fashion) and controls. The modified Baron score describes the following 5 endoscopic conditions: 0 = normal, 1 = granular mucosa, edema, 2 = friable mucosa but no spontaneous bleeding, 3 = microulcerations with spontaneous bleeding, 4 = gross ulceration, denuded mucosa. Results: We enrolled 228 UC patients (mean age 41 ± 13 years, 39 female) and 52 healthy controls. Disease was located in 40% in the left colon, 21% had an extensive and 39% a pancolitis. Endoscopic disease activity correlated best with fecal calprotectin (Spearman's rank correlation coefficient r = 0.821), followed by the Lichtiger Index (r = 0.682), CRP (r = 0.556), and blood leukocytes (r = 0.401). Fecal calprotectin was the only marker that could discriminate between different grades of endoscopic activity (grade 0, 25 ± 11 μg/g; grade 1, 44 ± 34 μg/g; grade 2, 111 ± 74 μg/g; grade 3, 330 ± 332 μg/g; grade 4, 659 ± 319 μg/g; P = 0.002 for discriminating grade 0 vs. 1, and P < 0.001 for discriminating grade 1 vs. 2, grade 2 vs. 3, and grade 3 vs. 4). Fecal calprotectin had the highest overall accuracy (91%) to detect endoscopically active disease (modified Baron Index ≥ 2), followed by the Lichtiger Index score of ≥ 4 (77%), CRP > 5 mg/L (69%) and blood leukocytosis (58%). Conclusions: Fecal calprotectin better correlated with endoscopic disease activity than clinical activity, CRP, and blood leukocytes. The strong correlation with endoscopic disease activity suggests that FC represents a useful biomarker for noninvasive monitoring of disease activity in UC patients.

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Digital holographic microscopy (DHM) allows optical-path-difference (OPD) measurements with nanometric accuracy. OPD induced by transparent cells depends on both the refractive index (RI) of cells and their morphology. This Letter presents a dual-wavelength DHM that allows us to separately measure both the RI and the cellular thickness by exploiting an enhanced dispersion of the perfusion medium achieved by the utilization of an extracellular dye. The two wavelengths are chosen in the vicinity of the absorption peak of the dye, where the absorption is accompanied by a significant variation of the RI as a function of the wavelength.

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IMPORTANCE There is a high prevalence of obesity in psychiatric patients, possibly leading to metabolic complications and reducing life expectancy. The CREB-regulated transcription coactivator 1 (CRTC1) gene is involved in energy balance and obesity in animal models, but its role in human obesity is unknown. OBJECTIVE To determine whether polymorphisms within the CRTC1 gene are associated with adiposity markers in psychiatric patients and the general population. DESIGN, SETTING, AND PARTICIPANTS Retrospective and prospective data analysis and population-based samples at Lausanne and Geneva university hospitals in Switzerland and a private clinic in Lausanne, Switzerland. The effect of 3 CRTC1 polymorphisms on body mass index (BMI) and/or fat mass was investigated in a discovery cohort of psychiatric outpatients taking weight gain-inducing psychotropic drugs (sample 1, n = 152). The CRTC1 variant that was significantly associated with BMI and survived Bonferroni corrections for multiple comparison was then replicated in 2 independent psychiatric samples (sample 2, n = 174 and sample 3, n = 118) and 2 white population-based samples (sample 4, n = 5338 and sample 5, n = 123 865). INTERVENTION Noninterventional studies. MAIN OUTCOME AND MEASURE Difference in BMI and/or fat mass between CRTC1 genotype groups. RESULTS Among the CRTC1 variants tested in the first psychiatric sample, only rs3746266A>G was associated with BMI (Padjusted = .003). In the 3 psychiatric samples, carriers of the rs3746266 G allele had a lower BMI than noncarriers (AA genotype) (sample 1, P = .001; sample 2, P = .05; and sample 3, P = .0003). In the combined analysis, excluding patients taking other weight gain-inducing drugs, G allele carriers (n = 98) had a 1.81-kg/m2 lower BMI than noncarriers (n = 226; P < .0001). The strongest association was observed in women younger than 45 years, with a 3.87-kg/m2 lower BMI in G allele carriers (n = 25) compared with noncarriers (n = 48; P < .0001), explaining 9% of BMI variance. In the population-based samples, the T allele of rs6510997C>T (a proxy of the rs3746266 G allele; r2 = 0.7) was associated with lower BMI (sample 5, n = 123 865; P = .01) and fat mass (sample 4, n = 5338; P = .03). The strongest association with fat mass was observed in premenopausal women (n = 1192; P = .02). CONCLUSIONS AND RELEVANCE These findings suggest that CRTC1 contributes to the genetics of human obesity in psychiatric patients and the general population. Identification of high-risk subjects could contribute to a better individualization of the pharmacological treatment in psychiatry.

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OBJECTIVE: The aim of the study was to validate a French adaptation of the 5th version of the Addiction Severity Index (ASI) instrument in a Swiss sample of illicit drug users. PARTICIPANTS AND SETTING: The participants in the study were 54 French-speaking dependent patients, most of them with opiates as the drug of first choice. Procedure: Analyses of internal consistency (convergent and discriminant validity) and reliability, including measures of test-retest and inter-observer correlations, were conducted. RESULTS: Besides good applicability of the test, the results on composite scores (CSs) indicate comparable results to those obtained in a sample of American opiate-dependent patients. Across the seven dimensions of the ASI, Cronbach's alpha ranged from 0.42 to 0.76, test-retest correlations coefficients ranged from 0.48 to 0.98, while for CSs, inter-observer correlations ranged from 0.76 to 0.99. CONCLUSIONS: Despite several limitations, the French version of the ASI presents acceptable criteria of applicability, validity and reliability in a sample of drug-dependent patients.

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BACKGROUND: We sought to improve upon previously published statistical modeling strategies for binary classification of dyslipidemia for general population screening purposes based on the waist-to-hip circumference ratio and body mass index anthropometric measurements. METHODS: Study subjects were participants in WHO-MONICA population-based surveys conducted in two Swiss regions. Outcome variables were based on the total serum cholesterol to high density lipoprotein cholesterol ratio. The other potential predictor variables were gender, age, current cigarette smoking, and hypertension. The models investigated were: (i) linear regression; (ii) logistic classification; (iii) regression trees; (iv) classification trees (iii and iv are collectively known as "CART"). Binary classification performance of the region-specific models was externally validated by classifying the subjects from the other region. RESULTS: Waist-to-hip circumference ratio and body mass index remained modest predictors of dyslipidemia. Correct classification rates for all models were 60-80%, with marked gender differences. Gender-specific models provided only small gains in classification. The external validations provided assurance about the stability of the models. CONCLUSIONS: There were no striking differences between either the algebraic (i, ii) vs. non-algebraic (iii, iv), or the regression (i, iii) vs. classification (ii, iv) modeling approaches. Anticipated advantages of the CART vs. simple additive linear and logistic models were less than expected in this particular application with a relatively small set of predictor variables. CART models may be more useful when considering main effects and interactions between larger sets of predictor variables.

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IMPORTANCE: Depression and obesity are 2 prevalent disorders that have been repeatedly shown to be associated. However, the mechanisms and temporal sequence underlying this association are poorly understood. OBJECTIVE: To determine whether the subtypes of major depressive disorder (MDD; melancholic, atypical, combined, or unspecified) are predictive of adiposity in terms of the incidence of obesity and changes in body mass index (calculated as weight in kilograms divided by height in meters squared), waist circumference, and fat mass. DESIGN, SETTING, AND PARTICIPANTS: This prospective population-based cohort study, CoLaus (Cohorte Lausannoise)/PsyCoLaus (Psychiatric arm of the CoLaus Study), with 5.5 years of follow-up included 3054 randomly selected residents (mean age, 49.7 years; 53.1% were women) of the city of Lausanne, Switzerland (according to the civil register), aged 35 to 66 years in 2003, who accepted the physical and psychiatric baseline and physical follow-up evaluations. EXPOSURES: Depression subtypes according to the DSM-IV. Diagnostic criteria at baseline and follow-up, as well as sociodemographic characteristics, lifestyle (alcohol and tobacco use and physical activity), and medication, were elicited using the semistructured Diagnostic Interview for Genetic Studies. MAIN OUTCOMES AND MEASURES: Changes in body mass index, waist circumference, and fat mass during the follow-up period, in percentage of the baseline value, and the incidence of obesity during the follow-up period among nonobese participants at baseline. Weight, height, waist circumference, and body fat (bioimpedance) were measured at baseline and follow-up by trained field interviewers. RESULTS: Only participants with the atypical subtype of MDD at baseline revealed a higher increase in adiposity during follow-up than participants without MDD. The associations between this MDD subtype and body mass index (β = 3.19; 95% CI, 1.50-4.88), incidence of obesity (odds ratio, 3.75; 95% CI, 1.24-11.35), waist circumference in both sexes (β = 2.44; 95% CI, 0.21-4.66), and fat mass in men (β = 16.36; 95% CI, 4.81-27.92) remained significant after adjustments for a wide range of possible cofounding. CONCLUSIONS AND RELEVANCE: The atypical subtype of MDD is a strong predictor of obesity. This emphasizes the need to identify individuals with this subtype of MDD in both clinical and research settings. Therapeutic measures to diminish the consequences of increased appetite during depressive episodes with atypical features are advocated.

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In order to assess the validity of the weight per square of length ratio as an index of adiposity during the neonatal period, 37 premature infants (gestational age, mean +/- SD, = 31.5 +/- 1.1 weeks, birthweight, mean +/- SD, = 1.448 +/- 147 g) were studied for weight, length and skinfold thickness at 5 sites (biceps, triceps, subscapular, suprailiac and quadriceps) during their stay in the Neonatal Unit of the University Hospital in Lausanne. The results show a significant correlation between the adiposity index and the sum of 5 skinfold thickness sites in premature infants. The adiposity index gives a fair estimate of the body fat mass during the postnatal growth in premature infants.

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Objective: Microalbuminuria (MAU) is a marker of early kidney injury and cardiovascular risk. We assessed the association of MAU with plasma adiponectin, leptin and hsCRP, as inflammatory markers, accounting for hypertension, diabetes and obesity. Design and methods: Population based, cross-sectional study in Caucasian subjects aged 35 to 75 years in Lausanne, Switzerland. MAU, measured on spot morning urine, was used either as a continuous (MAU) or dichotomized variable (MA defined as MAU >2.5 and >3.5 mg/mmol creatinine in men and women, respectively). Results: The 2955 women (age 53.3 ± 10.7, mean ± SD years) had mean body mass index (BMI) 24.9 ± 4.5 kg/m. The 2479 men (age 53.1 ± 10.8 years) had mean BMI 27.0 ± 3.9 kg/m². Median hsCRP was 1.3 and 1.3 mg/L, median adiponectin 6.2 and 10.6 mg/mL in men and women, respectively. MA prevalence was 4.9% in women and 9.8% in men. In multivariate regression analysis adjusting for potential confounders (age, sex, hypertension, diabetes, eGFR, BMI, percent fat mass, insulin and smoking), log-transformed MAU was positively associated with hsCRP (P <0.001) and adiponectin (P = 0.002), but not with leptin. The association of adiponectin with MAU was stronger in subjects with low hsCRP, and vice versa (P interaction <0.001). Conclusion: Adiponectin and hsCRP are significant positive determinants of MAU, independently of diabetes, hypertension and fat mass. A negative interaction between hsCRP and adiponectin was found for their effect on MAU. Whether hyperadiponectinemia represents an adequate protective response to vascular stress or has negative causal impact on the development of MAU should be assessed in further studies.

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Several recent studies suggest that obesity may be a risk factor for fracture. The aim of this study was to investigate the association between body mass index (BMI) and future fracture risk at different skeletal sites. In prospective cohorts from more than 25 countries, baseline data on BMI were available in 398,610 women with an average age of 63 (range, 20-105) years and follow up of 2.2 million person-years during which 30,280 osteoporotic fractures (6457 hip fractures) occurred. Femoral neck BMD was measured in 108,267 of these women. Obesity (BMI ≥ 30 kg/m(2) ) was present in 22%. A majority of osteoporotic fractures (81%) and hip fractures (87%) arose in non-obese women. Compared to a BMI of 25 kg/m(2) , the hazard ratio (HR) for osteoporotic fracture at a BMI of 35 kg/m(2) was 0.87 (95% confidence interval [CI], 0.85-0.90). When adjusted for bone mineral density (BMD), however, the same comparison showed that the HR for osteoporotic fracture was increased (HR, 1.16; 95% CI, 1.09-1.23). Low BMI is a risk factor for hip and all osteoporotic fracture, but is a protective factor for lower leg fracture, whereas high BMI is a risk factor for upper arm (humerus and elbow) fracture. When adjusted for BMD, low BMI remained a risk factor for hip fracture but was protective for osteoporotic fracture, tibia and fibula fracture, distal forearm fracture, and upper arm fracture. When adjusted for BMD, high BMI remained a risk factor for upper arm fracture but was also a risk factor for all osteoporotic fractures. The association between BMI and fracture risk is complex, differs across skeletal sites, and is modified by the interaction between BMI and BMD. At a population level, high BMI remains a protective factor for most sites of fragility fracture. The contribution of increasing population rates of obesity to apparent decreases in fracture rates should be explored. © 2014 American Society for Bone and Mineral Research.

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OBJECTIVE: To determine reference values for fat-free mass index (FFMI) and fat mass index (FMI) in a large Caucasian group of apparently healthy subjects, as a function of age and gender and to develop percentile distribution for these two parameters. DESIGN: Cross-sectional study in which bioelectrical impedance analysis (50 kHz) was measured (using tetrapolar electrodes and cross-validated formulae by dual-energy X-ray absorptiometry in order to calculate FFMI (fat-free mass/height squared) and FMI (fat mass/height squared). SUBJECTS: A total of 5635 apparently healthy adults from a mixed non-randomly selected Caucasian population in Switzerland (2986 men and 2649 women), varying in age from 24 to 98 y. RESULTS: The median FFMI (18-34 y) were 18.9 kg/m(2) in young males and 15.4 kg/m(2) in young females. No difference with age in males and a modest increase in females were observed. The median FMI was 4.0 kg/m(2) in males and 5.5 kg/m(2) in females. From young to elderly age categories, FMI progressively rose by an average of 55% in males and 62% in females, compared to an increase in body mass index (BMI) of 9 and 19% respectively. CONCLUSIONS: Reference intervals for FFMI and FMI could be of practical value for the clinical evaluation of a deficit in fat-free mass with or without excess fat mass (sarcopenic obesity) for a given age category, complementing the classical concept of body mass index (BMI) in a more qualitative manner. In contrast to BMI, similar reference ranges seems to be utilizable for FFMI with advancing age, in particular in men.

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BACKGROUND: The factors that contribute to increasing obesity rates in human immunodeficiency virus (HIV)-positive persons and to body mass index (BMI) increase that typically occurs after starting antiretroviral therapy (ART) are incompletely characterized. METHODS: We describe BMI trends in the entire Swiss HIV Cohort Study (SHCS) population and investigate the effects of demographics, HIV-related factors, and ART on BMI change in participants with data available before and 4 years after first starting ART. RESULTS: In the SHCS, overweight/obesity prevalence increased from 13% in 1990 (n = 1641) to 38% in 2012 (n = 8150). In the participants starting ART (n = 1601), mean BMI increase was 0.92 kg/m(2) per year (95% confidence interval, .83-1.0) during year 0-1 and 0.31 kg/m(2) per year (0.29-0.34) during years 1-4. In multivariable analyses, annualized BMI change during year 0-1 was associated with older age (0.15 [0.06-0.24] kg/m(2)) and CD4 nadir <199 cells/µL compared to nadir >350 (P < .001). Annualized BMI change during years 1-4 was associated with CD4 nadir <100 cells/µL compared to nadir >350 (P = .001) and black compared to white ethnicity (0.28 [0.16-0.37] kg/m(2)). Individual ART combinations differed little in their contribution to BMI change. CONCLUSIONS: Increasing obesity rates in the SHCS over time occurred at the same time as aging of the SHCS population, demographic changes, earlier ART start, and increasingly widespread ART coverage. Body mass index increase after ART start was typically biphasic, the BMI increase in year 0-1 being as large as the increase in years 1-4 combined. The effect of ART regimen on BMI change was limited.

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BACKGROUND: Insulin-like growth factor-I (IGF-I) and C-reactive protein (CRP) may be positively associated with the risk of epithelial ovarian cancer (EOC) but no previous studies have investigated their associations with non-epithelial ovarian cancers (NEOC). METHODS: A case-control study was nested within the Finnish Maternity Cohort. Case subjects were 58 women diagnosed with sex cord-stromal tumors (SCST) and 30 with germ cell tumors (GCT) after recruitment. Control subjects (144 for SCST and 74 for GCT) were matched for age, parity, and date of blood donation of the index case. RESULTS: Doubling of IGF-I concentration was not related to maternal risk of either SCST (OR 0.97, 95% CI 0.58-1.62) or GCT (OR 1.13, 95% CI 0.51-2.51). Similarly, doubling of CRP concentrations was not related to maternal risk of either SCST (OR 1.10, 95% CI 0.85-1.43) or GCT (OR 0.93, 95% CI 0.68-1.28). CONCLUSIONS: Pre-diagnostic IGF-I and CRP concentrations during the first trimester of pregnancy were not associated with increased risk of NEOC in the mother. Risk factors for NEOC may differ from those of EOC.

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OBJECTIVE: Low and high body mass index (BMI) values have been shown to increase health risks and mortality and result in variations in fat-free mass (FFM) and body fat mass (BF). Currently, there are no published ranges for a fat-free mass index (FFMI; kg/m(2)), a body fat mass index (BFMI; kg/m(2)), and percentage of body fat (%BF). The purpose of this population study was to determine predicted FFMI and BFMI values in subjects with low, normal, overweight, and obese BMI. METHODS: FFM and BF were determined in 2986 healthy white men and 2649 white women, age 15 to 98 y, by a previously validated 50-kHz bioelectrical impedance analysis equation. FFMI, BFMI, and %BF were calculated. RESULTS: FFMI values were 16.7 to 19.8 kg/m(2) for men and 14.6 to 16.8 kg/m(2) for women within the normal BMI ranges. BFMI values were 1.8 to 5.2 kg/m(2) for men and 3.9 to 8.2 kg/m(2) for women within the normal BMI ranges. BFMI values were 8.3 and 11.8 kg/m(2) in men and women, respectively, for obese BMI (>30 kg/m(2)). Normal ranges for %BF were 13.4 to 21.7 and 24.6 to 33.2 for men and women, respectively. CONCLUSION: BMI alone cannot provide information about the respective contribution of FFM or fat mass to body weight. This study presents FFMI and BFMI values that correspond to low, normal, overweight, and obese BMIs. FFMI and BFMI provide information about body compartments, regardless of height.