51 resultados para Library statistics.
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INTRODUCTION Statins have pleiotropic effects that could influence the prevention and outcome of some infectious diseases. There is no information about their specific effect on Staphylococcus aureus bacteremia (SAB). METHODS A prospective cohort study including all SAB diagnosed in patients aged ≥18 years admitted to a 950-bed tertiary hospital from March 2008 to January 2011 was performed. The main outcome variable was 14-day mortality, and the secondary outcome variables were 30-day mortality, persistent bacteremia (PB) and presence of severe sepsis or septic shock at diagnosis of SAB. The effect of statin therapy at the onset of SAB was studied by multivariate logistic regression and Cox regression analysis, including a propensity score for statin therapy. RESULTS We included 160 episodes. Thirty-three patients (21.3%) were receiving statins at the onset of SAB. 14-day mortality was 21.3%. After adjustment for age, Charlson index, Pitt score, adequate management, and high risk source, statin therapy had a protective effect on 14-day mortality (adjusted OR = 0.08; 95% CI: 0.01-0.66; p = 0.02), and PB (OR = 0.89; 95% CI: 0.27-1.00; p = 0.05) although the effect was not significant on 30-day mortality (OR = 0.35; 95% CI: 0.10-1.23; p = 0.10) or presentation with severe sepsis or septic shock (adjusted OR = 0.89; CI 95%: 0.27-2.94; p = 0.8). An effect on 30-day mortality could neither be demonstrated on Cox analysis (adjusted HR = 0.5; 95% CI: 0.19-1.29; p = 0.15). CONCLUSIONS Statin treatment in patients with SAB was associated with lower early mortality and PB. Randomized studies are necessary to identify the role of statins in the treatment of patients with SAB.
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OBJECTIVE To assess the effectiveness of glatiramer acetate (GA) compared to other multiple sclerosis (MS) therapies in routine clinical practice. MATERIALS AND METHODS Observational cohort study carried out in MS patients treated with GA (GA cohort) or other MS therapies -switched from GA- (non-GA cohort). Study data were obtained through review of our MS patient database. The primary endpoint was the Expanded Disability Status Scale (EDSS) scores reached at the end of treatment/last check-up. RESULTS A total of 180 patients were included: GA cohort n = 120, non-GA cohort n = 60. Patients in the GA cohort showed better EDSS scores at the end of treatment/last check-up (mean ± SD, 2.8 ± 1.8 vs. 3.9 ± 2.2; P = 0.001) and were 1.65 times more likely to show better EDSS scores compared to the non-GA cohort (odds ratio, 0.606; 95%CI, 0.436-0.843; P = 0.003). Patients in the GA cohort showed longer mean time to reach EDSS scores of 6 (209.1 [95%CI, 187.6-230.6] vs. 164.3 [95% CI, 137.0-191.6] months; P = 0.004) and slower disability progression (hazard ratio, 0.415 [95%CI, 0.286-0.603]; P < 0.001). The annualized relapse rate was lower in the GA cohort (mean ± SD, 0.5 ± 0.5 vs. 0.8 ± 0.5; P = 0.001) and patients' quality of life was improved in this study cohort compared to the non-GA cohort (mean ± SD, 0.7 ± 0.1 vs. 0.6 ± 0.2; P = 0.01). CONCLUSIONS GA may slow down the progression of EDSS scores to a greater extent than other MS therapies, as well as achieving a greater reduction in relapses and a greater improvement in patients' quality of life. Switching from GA to other MS therapies has not proved to entail a better response to treatment.
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The restoration of body composition (BC) parameters is considered to be one of the most important goals in the treatment of patients with anorexia nervosa (AN). However, little is known about differences between AN diagnostic subtypes [restricting (AN-R) and binge/purging (AN-BP)] and weekly changes in BC during refeeding treatment. Therefore, the main objectives of our study were twofold: 1) to assess the changes in BC throughout nutritional treatment in an AN sample and 2) to analyze predictors of BC changes during treatment, as well as predictors of treatment outcome. The whole sample comprised 261 participants [118 adult females with AN (70 AN-R vs. 48 AN-BP), and 143 healthy controls]. BC was measured weekly during 15 weeks of day-hospital treatment using bioelectrical impedance analysis (BIA). Assessment measures also included the Eating Disorders Inventory-2, as well as a number of other clinical indices. Overall, the results showed that AN-R and AN-BP patients statistically differed in all BC measures at admission. However, no significant time×group interaction was found for almost all BC parameters. Significant time×group interactions were only found for basal metabolic rate (p = .041) and body mass index (BMI) (p = .035). Multiple regression models showed that the best predictors of pre-post changes in BC parameters (namely fat-free mass, muscular mass, total body water and BMI) were the baseline values of BC parameters. Stepwise predictive logistic regressions showed that only BMI and age were significantly associated with outcome, but not with the percentage of body fat. In conclusion, these data suggest that although AN patients tended to restore all BC parameters during nutritional treatment, only AN-BP patients obtained the same fat mass values as healthy controls. Put succinctly, the best predictors of changes in BC were baseline BC values, which did not, however, seem to influence treatment outcome.
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BACKGROUND Mental and body weight disorders are among the major global health challenges, and their comorbidity may play an important role in treatment and prevention of both pathologies. A growing number of studies have examined the relationship between psychiatric status and body weight, but our knowledge is still limited. OBJECTIVE The present study aims to investigate the cross-sectional relationships of psychiatric status and body mass index (BMI) in Málaga, a Mediterranean city in the South of Spain. MATERIALS AND METHODS A total of 563 participants were recruited from those who came to his primary care physician, using a systematic random sampling, non-proportional stratified by BMI categories. Structured clinical interviews were used to assess current Axes-I and II mental disorders according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR). BMI was calculated as weight (Kg) divided by square of height in meters (m2). Logistic regression was used to investigate the association between BMI and the presence of any mental disorder. BMI was introduced in the models using restricted cubic splines. RESULTS We found that high BMI values were directly associated with mood and adjustment disorders, and low BMI values were directly associated with avoidant and dependent personality disorders (PDs). We observed an inverse relationship between low BMI values and cluster A PDs. There were not significant relationships between anxiety or substance-related disorders and BMI. CONCLUSION Psychiatric status and BMI are related in a Mediterranean Spanish population. A multidisciplinary approach to both pathologies becomes increasingly more necessary.
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BACKGROUND Obesity is positively associated with colorectal cancer. Recently, body size subtypes categorised by the prevalence of hyperinsulinaemia have been defined, and metabolically healthy overweight/obese individuals (without hyperinsulinaemia) have been suggested to be at lower risk of cardiovascular disease than their metabolically unhealthy (hyperinsulinaemic) overweight/obese counterparts. Whether similarly variable relationships exist for metabolically defined body size phenotypes and colorectal cancer risk is unknown. METHODS AND FINDINGS The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed. CONCLUSIONS These results support the idea that individuals with the metabolically healthy/overweight phenotype (with normal insulin levels) are at lower colorectal cancer risk than those with hyperinsulinaemia. The combination of anthropometric measures with metabolic parameters, such as C-peptide, may be useful for defining strata of the population at greater risk of colorectal cancer.
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BACKGROUND Nucleic acid amplification tests are increasingly used for the rapid diagnosis of tuberculosis. We undertook a comparative study of the efficiency and diagnostic yield of a real-time PCR senX3-regX3 based assay versus the classical IS6110 target and the new commercial methods. METHODS This single-blind prospective comparative study included 145 consecutive samples: 76 from patients with culture-confirmed tuberculosis (86.8% pulmonary and 13.2% extrapulmonary tuberculosis: 48.7% smear-positive and 51.3% smear-negative) and 69 control samples (24 from patients diagnosed with non-tuberculous mycobacteria infections and 45 from patients with suspected tuberculosis which was eventually ruled out). All samples were tested by two CE-marked assays (Xpert®MTB/RIF and AnyplexTM plus MTB/NTM) and two in-house assays targeting senX3-regX3 and the IS6110 gene. RESULTS The detection limit ranged from 1.00E+01 fg for Anyplex, senX3-regX3 and IS6110 to 1.00E+04 fg for Xpert. All three Xpert, senX3-regX3 and IS6110 assays detected all 37 smear-positive cases. Conversely, Anyplex was positive in 34 (91.9%) smear-positive cases. In patients with smear-negative tuberculosis, differences were observed between the assays; Xpert detected 22 (56.41%) of the 39 smear-negative samples, Anyplex 24 (61.53%), senX3-regX3 28 (71.79%) and IS6110 35 (89.74%). Xpert and senX3-regX3 were negative in all control samples; however, the false positive rate was 8.7% and 13% for Anyplex and IS6110, respectively. The overall sensitivity was 77.6%, 85.7%, 77.3% and 94.7% and the specificity was 100%, 100%, 90.8% and 87.0% for the Xpert, senX3-regX3, Anyplex and IS6110 assays, respectively. CONCLUSION Real-time PCR assays targeting IS6110 lack the desired specificity. The Xpert MTB/RIF and in-house senX3-regX3 assays are both sensitive and specific for the detection of MTBC in both pulmonary and extrapulmonary samples. Therefore, the real time PCR senX3-regX3 based assay could be a useful and complementary tool in the diagnosis of tuberculosis.