997 resultados para Logistic Regression
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Fundamento: La prevalencia de discapacidad en la población general presenta una gran variabilidad geográfica, de manera que identificar aquellos factores que pudieran explicarla será importante para la planificación de políticas sociales. En este trabajo se analiza la variabilidad de la discapacidad por comunidades autónomas desde una doble vertiente, los factores individuales y del entorno. Métodos: Los datos proceden principalmente de la Encuesta de Discapacidad, Deficiencias y Estado de Salud de 1999 y del Inebase, ambas del Instituto Nacional de Estadística (INE). Se calculó la prevalencia de discapacidad simple y ajustada por edad de las CCAA. Se analizan los factores individuales asociados a la discapacidad mediante una regresión logística y los factores individuales y de la comunidad autónoma conjuntamente con una regresión logística de dos niveles. Resultados: La prevalencia de discapacidad muestra una diferencia máxima de 5,75 puntos entre las comunidades autónomas. En la regresión logística la comunidad de residencia fue estadísticamente significativa (OR: 3,35 en la de mayor prevalencia respecto a la de menor) junto con otras variables individuales: edad (OR de 40-64= 1,78 OR de 65-79= 1,87 y OR de >79= 3,34), sexo (OR mujer= 0,66), situación laboral (OR sin trabajo=2,25 OR amas casa/estudiante=1,39 y OR otros=2,03), estado de salud (OR regular= 1,69 OR malo/muy malo= 2,05) y enfermedades crónicas (OR 1-3=1,56 OR4-6=1,82 OR>6=2,59). En la regresión de dos niveles las variables individuales explican poca varianza (s=0,261) y ninguna de las variables relativas a las CCAA mejora el modelo. Conclusiones: Las características individuales no explican suficientemente la variabilidad de la discapacidad entre CCAA y no se han identificado variables del entorno que sean significativas.
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Background: Development of three classification trees (CT) based on the CART (Classification and Regression Trees), CHAID (Chi-Square Automatic Interaction Detection) and C4.5 methodologies for the calculation of probability of hospital mortality; the comparison of the results with the APACHE II, SAPS II and MPM II-24 scores, and with a model based on multiple logistic regression (LR). Methods: Retrospective study of 2864 patients. Random partition (70:30) into a Development Set (DS) n = 1808 and Validation Set (VS) n = 808. Their properties of discrimination are compared with the ROC curve (AUC CI 95%), Percent of correct classification (PCC CI 95%); and the calibration with the Calibration Curve and the Standardized Mortality Ratio (SMR CI 95%). Results: CTs are produced with a different selection of variables and decision rules: CART (5 variables and 8 decision rules), CHAID (7 variables and 15 rules) and C4.5 (6 variables and 10 rules). The common variables were: inotropic therapy, Glasgow, age, (A-a)O2 gradient and antecedent of chronic illness. In VS: all the models achieved acceptable discrimination with AUC above 0.7. CT: CART (0.75(0.71-0.81)), CHAID (0.76(0.72-0.79)) and C4.5 (0.76(0.73-0.80)). PCC: CART (72(69- 75)), CHAID (72(69-75)) and C4.5 (76(73-79)). Calibration (SMR) better in the CT: CART (1.04(0.95-1.31)), CHAID (1.06(0.97-1.15) and C4.5 (1.08(0.98-1.16)). Conclusion: With different methodologies of CTs, trees are generated with different selection of variables and decision rules. The CTs are easy to interpret, and they stratify the risk of hospital mortality. The CTs should be taken into account for the classification of the prognosis of critically ill patients.
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BACKGROUND: Increasing incidence of head and neck cancer (HNC) in young adults has been reported. We aimed to compare the role of major risk factors and family history of cancer in HNC in young adults and older patients. METHODS: We pooled data from 25 case-control studies and conducted separate analyses for adults ≤45 years old ('young adults', 2010 cases and 4042 controls) and >45 years old ('older adults', 17 700 cases and 22 704 controls). Using logistic regression with studies treated as random effects, we estimated adjusted odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: The young group of cases had a higher proportion of oral tongue cancer (16.0% in women; 11.0% in men) and unspecified oral cavity / oropharynx cancer (16.2%; 11.1%) and a lower proportion of larynx cancer (12.1%; 16.6%) than older adult cases. The proportions of never smokers or never drinkers among female cases were higher than among male cases in both age groups. Positive associations with HNC and duration or pack-years of smoking and drinking were similar across age groups. However, the attributable fractions (AFs) for smoking and drinking were lower in young when compared with older adults (AFs for smoking in young women, older women, young men and older men, respectively, = 19.9% (95% CI = 9.8%, 27.9%), 48.9% (46.6%, 50.8%), 46.2% (38.5%, 52.5%), 64.3% (62.2%, 66.4%); AFs for drinking = 5.3% (-11.2%, 18.0%), 20.0% (14.5%, 25.0%), 21.5% (5.0%, 34.9%) and 50.4% (46.1%, 54.3%). A family history of early-onset cancer was associated with HNC risk in the young [OR = 2.27 (95% CI = 1.26, 4.10)], but not in the older adults [OR = 1.10 (0.91, 1.31)]. The attributable fraction for family history of early-onset cancer was 23.2% (8.60% to 31.4%) in young compared with 2.20% (-2.41%, 5.80%) in older adults. CONCLUSIONS: Differences in HNC aetiology according to age group may exist. The lower AF of cigarette smoking and alcohol drinking in young adults may be due to the reduced length of exposure due to the lower age. Other characteristics, such as those that are inherited, may play a more important role in HNC in young adults compared with older adults.
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BACKGROUND: Obesity is strongly associated with major depressive disorder (MDD) and various other diseases. Genome-wide association studies have identified multiple risk loci robustly associated with body mass index (BMI). In this study, we aimed to investigate whether a genetic risk score (GRS) combining multiple BMI risk loci might have utility in prediction of obesity in patients with MDD. METHODS: Linear and logistic regression models were conducted to predict BMI and obesity, respectively, in three independent large case-control studies of major depression (Radiant, GSK-Munich, PsyCoLaus). The analyses were first performed in the whole sample and then separately in depressed cases and controls. An unweighted GRS was calculated by summation of the number of risk alleles. A weighted GRS was calculated as the sum of risk alleles at each locus multiplied by their effect sizes. Receiver operating characteristic (ROC) analysis was used to compare the discriminatory ability of predictors of obesity. RESULTS: In the discovery phase, a total of 2,521 participants (1,895 depressed patients and 626 controls) were included from the Radiant study. Both unweighted and weighted GRS were highly associated with BMI (P <0.001) but explained only a modest amount of variance. Adding 'traditional' risk factors to GRS significantly improved the predictive ability with the area under the curve (AUC) in the ROC analysis, increasing from 0.58 to 0.66 (95% CI, 0.62-0.68; χ(2) = 27.68; P <0.0001). Although there was no formal evidence of interaction between depression status and GRS, there was further improvement in AUC in the ROC analysis when depression status was added to the model (AUC = 0.71; 95% CI, 0.68-0.73; χ(2) = 28.64; P <0.0001). We further found that the GRS accounted for more variance of BMI in depressed patients than in healthy controls. Again, GRS discriminated obesity better in depressed patients compared to healthy controls. We later replicated these analyses in two independent samples (GSK-Munich and PsyCoLaus) and found similar results. CONCLUSIONS: A GRS proved to be a highly significant predictor of obesity in people with MDD but accounted for only modest amount of variance. Nevertheless, as more risk loci are identified, combining a GRS approach with information on non-genetic risk factors could become a useful strategy in identifying MDD patients at higher risk of developing obesity.
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Background: Gender-related differences are seen in multiple aspects of both health and illness. Ischemic heart disease (IHD) is a pathology in which diagnostic, treatment and prognostic differences are seen between sexes, especially in the acute phase and in the hospital setting. The objective of the present study is to analyze whether there are differences between men and women when examining associated cardiovascular risk factors and secondary pharmacological prevention in the primary care setting. Methods: Retrospective descriptive observational study from January to December of 2006, including 1907 patients diagnosed with ischemic heart disease in the city of Lleida, Spain. The clinical data were obtained from computerized medical records and pharmaceutical records of medications dispensed in pharmacies with official prescriptions. Data was analyzed using bivariate descriptive statistical analysis as well as logistic regression. Results: There were no gender-related differences in screening percentages for arterial hypertension, diabetes, obesity, dyslipemia, and smoking. A greater percentage of women were hypertensive, obese and diabetic compared to men. However, men showed a tendency to achieve control targets more easily than women, with no statistically significant differences. In both sexes cardiovascular risk factors control was inadequate, between 10 and 50%. For secondary pharmaceutical prevention, the percentages of prescriptions were greater in men for anticoagulants, beta-blockers, lipid-lowering agents and angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers, with age group variations up to 10%. When adjusting by age and specific diagnoses, differences were maintained for anticoagulants and lipid-lowering agents. Conclusion: Screening of cardiovascular risk factors was similar in men and women with IHD. Although a greater percentage of women were hypertensive, diabetic or obese, their management of risk factors tended to be worse than men. Overall, a poor control of cardiovascular risk factors was noted. Taken as a whole, more men were prescribed secondary prevention drugs, with differences varying by age group and IHD diagnosis.
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BACKGROUND: Chronic HCV infection is a leading cause of liver-related morbidity globally. The innate and adaptive immune responses are thought to be important in determining viral outcomes. Polymorphisms associated with the IFNL3 (IL28B) gene are strongly associated with spontaneous clearance and treatment outcomes. OBJECTIVE: This study investigates the importance of HLA genes in the context of genetic variation associated with the innate immune genes IFNL3 and KIR2DS3. DESIGN: We assess the collective influence of HLA and innate immune genes on viral outcomes in an Irish cohort of women (n=319) who had been infected from a single source as well as a more heterogeneous cohort (Swiss Cohort, n=461). In the Irish cohort, a number of HLA alleles are associated with different outcomes, and the impact of IFNL3-linked polymorphisms is profound. RESULTS: Logistic regression was performed on data from the Irish cohort, and indicates that the HLA-A*03 (OR 0.36 (0.15 to 0.89), p=0.027) -B*27 (OR 0.12 (0.03 to 0.45), p=<0.001), -DRB1*01:01 (OR 0.2 (0.07 to 0.61), p=0.005), -DRB1*04:01 (OR 0.31 (0.12 to 0.85, p=0.02) and the CC IFNL3 rs12979860 genotypes (OR 0.1 (0.04 to 0.23), p<0.001) are significantly associated with viral clearance. Furthermore, DQB1*02:01 (OR 4.2 (2.04 to 8.66), p=0.008), KIR2DS3 (OR 4.36 (1.62 to 11.74), p=0.004) and the rs12979860 IFNL3 'T' allele are associated with chronic infection. This study finds no interactive effect between IFNL3 and these Class I and II alleles in relation to viral clearance. There is a clear additive effect, however. Data from the Swiss cohort also confirms independent and additive effects of HLA Class I, II and IFNL3 genes in their prediction of viral outcome. CONCLUSIONS: This data supports a critical role for the adaptive immune response in the control of HCV in concert with the innate immune response.
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BACKGROUND: The aim of the current study was to assess whether widely used nutritional parameters are correlated with the nutritional risk score (NRS-2002) to identify postoperative morbidity and to evaluate the role of nutritionists in nutritional assessment. METHODS: A randomized trial on preoperative nutritional interventions (NCT00512213) provided the study cohort of 152 patients at nutritional risk (NRS-2002 ≥3) with a comprehensive phenotyping including diverse nutritional parameters (n=17), elaborated by nutritional specialists, and potential demographic and surgical (n=5) confounders. Risk factors for overall, severe (Dindo-Clavien 3-5) and infectious complications were identified by univariate analysis; parameters with P<0.20 were then entered in a multiple logistic regression model. RESULTS: Final analysis included 140 patients with complete datasets. Of these, 61 patients (43.6%) were overweight, and 72 patients (51.4%) experienced at least one complication of any degree of severity. Univariate analysis identified a correlation between few (≤3) active co-morbidities (OR=4.94; 95% CI: 1.47-16.56, p=0.01) and overall complications. Patients screened as being malnourished by nutritional specialists presented less overall complications compared to the not malnourished (OR=0.47; 95% CI: 0.22-0.97, p=0.043). Severe postoperative complications occurred more often in patients with low lean body mass (OR=1.06; 95% CI: 1-1.12, p=0.028). Few (≤3) active co-morbidities (OR=8.8; 95% CI: 1.12-68.99, p=0.008) were related with postoperative infections. Patients screened as being malnourished by nutritional specialists presented less infectious complications (OR=0.28; 95% CI: 0.1-0.78), p=0.014) as compared to the not malnourished. Multivariate analysis identified few co-morbidities (OR=6.33; 95% CI: 1.75-22.84, p=0.005), low weight loss (OR=1.08; 95% CI: 1.02-1.14, p=0.006) and low hemoglobin concentration (OR=2.84; 95% CI: 1.22-6.59, p=0.021) as independent risk factors for overall postoperative complications. Compliance with nutritional supplements (OR=0.37; 95% CI: 0.14-0.97, p=0.041) and supplementation of malnourished patients as assessed by nutritional specialists (OR=0.24; 95% CI: 0.08-0.69, p=0.009) were independently associated with decreased infectious complications. CONCLUSIONS: Nutritional support based upon NRS-2002 screening might result in overnutrition, with potentially deleterious clinical consequences. We emphasize the importance of detailed assessment of the nutritional status by a dedicated specialist before deciding on early nutritional intervention for patients with an initial NRS-2002 score of ≥3.
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Colorectal cancer (CRC) is the second leading cause of cancer-related death in developed countries. Early detection of CRC leads to decreased CRC mortality. A blood-based CRC screening test is highly desirable due to limited invasiveness and high acceptance rate among patients compared to currently used fecal occult blood testing and colonoscopy. Here we describe the discovery and validation of a 29-gene panel in peripheral blood mononuclear cells (PBMC) for the detection of CRC and adenomatous polyps (AP). Blood samples were prospectively collected from a multicenter, case-control clinical study. First, we profiled 93 samples with 667 candidate and 3 reference genes by high throughput real-time PCR (OpenArray system). After analysis, 160 genes were retained and tested again on 51 additional samples. Low expressed and unstable genes were discarded resulting in a final dataset of 144 samples profiled with 140 genes. To define which genes, alone or in combinations had the highest potential to discriminate AP and/or CRC from controls, data were analyzed by a combination of univariate and multivariate methods. A list of 29 potentially discriminant genes was compiled and evaluated for its predictive accuracy by penalized logistic regression and bootstrap. This method discriminated AP >1cm and CRC from controls with a sensitivity of 59% and 75%, respectively, with 91% specificity. The behavior of the 29-gene panel was validated with a LightCycler 480 real-time PCR platform, commonly adopted by clinical laboratories. In this work we identified a 29-gene panel expressed in PBMC that can be used for developing a novel minimally-invasive test for accurate detection of AP and CRC using a standard real-time PCR platform.
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AIM: This study examined whether problematic Internet use was associated with substance use among young adolescents and assessed whether this association accounted for the use of tobacco, alcohol, cannabis and other drugs. METHODS: Using the Internet Addiction Test, we divided a representative sample of 3067 adolescents in Switzerland (mean age 14 years) into regular and problematic Internet users. We performed a bivariate analysis and two logistic regression models, to analyse substances separately and simultaneously, and developed a log-linear model to define the associations between significant variables. RESULTS: Problematic Internet users were more likely to be female, to use substances, to come from nonintact families, to report poor emotional well-being and to be below average students. The first model showed significant associations between problematic users and each substance, with adjusted odds ratios of 2.05 for tobacco, 1.72 for alcohol, 1.94 for cannabis and 2.73 for other drugs. Only smoking remained significant in the second model, with an adjusted odds ratio of 1.71. CONCLUSION: Problematic Internet use is associated with other risky behaviours and may be an important early predictor of adolescent substance use. Therefore, it should be included in the psychosocial screening of adolescents.
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Unintended pregnancies reflect an unmet need for family planning, and are part of health disparities. Using the only database to inquire about pregnancy intention among women in Switzerland, this study examined the relationship between immigrant documentation and unintended pregnancy (UP). Among pregnant women presenting to a Swiss hospital, we compared pregnancy intention between documented and undocumented women. We used logistic regression to examine whether undocumented status was associated with UP after adjusting for other significant predictors. Undocumented women had more unintended pregnancies (75.2 vs. 20.6 %, p = 0.00). Undocumented status was associated with UP after adjustment (OR 6.23, 95 % CI 1.83-21.2), as was a history of psychological problems (OR 4.09, 95 % CI 1.32-12.7). Contraception non-use was notably associated with lower odds of UP (OR 0.01, 95 % CI 0.004-0.04). Undocumented status was significantly associated with UP, even after adjusting for well-recognized risk factors. This highlights the tremendous risk of undocumented status on UP among women in Switzerland.
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BACKGROUND AND PURPOSE: To compare safety and efficacy of bridging approach with intravenous (IV) thrombolysis in patients with acute anterior strokes and proximal occlusions. PATIENTS AND METHODS: Consecutive patients with ischemic anterior strokes admitted within a 4 h 30 min window in two different centers were included. The first center performed IV therapy (alteplase 0.6 mg/kg) during 30 min and, in absence of clinical improvement, mechanical thrombectomy with flow restoration using a Solitaire stent (StS); the second carried out IV thrombolysis (alteplase 0.9 mg/kg) alone. Only T, M1 or M2 occlusions present on CT angiography were considered. Endpoints were clinical outcome and mortality at 3 months. RESULTS: There were 63 patients in the bridging and 163 in the IV group. No significant differences regarding baseline characteristics were observed. At 3 months, 46% (n = 29) of the patients treated in the combined and 23% (n = 38) of those treated in the IV group had a modified Rankin scale (mRS) of 0-1 (P < 0.001). A statistical significant difference was observed for all sites of occlusion. In a logistic regression model, National Institute of Health Stroke Scale (NIHSS) and bridging therapy were independent predictors of good outcome (respectively, P = 0.001 and P = 0.0018). Symptomatic hemorrhage was documented in 6.3% vs 3.7% in the bridging and in the IV group, respectively (P = 0.32). There was no difference in mortality. CONCLUSIONS: Our results suggest that patients treated with a bridging approach were more likely to have minimal or no deficit at all at 3 months as compared to the IV treated group.
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BACKGROUND: Visceral obesity (VO) increases technical difficulty in laparoscopic surgery. The body mass index (BMI) does not always correlate to intra-abdominal fat distribution. Our hypothesis was that simple anthropometric measures that reflect VO, could predict technical difficulty in laparoscopic colorectal surgery, as reflected by the operative time, more accurately than the BMI. METHODS: Charts of all consecutive patients who underwent laparoscopic left colon resection in our institution between 2007 and 2010 were reviewed retrospectively. On a preoperative CT scan, anthropometric measures were taken on an axial plane at the L4-L5 level. Demographic, operative and anthropometric CT measures were correlated with the operative time. Logistic regression analysis was performed to assess the value of anthropometric CT measures or BMI to predict the duration of the colectomy. RESULTS: 121 patients with elective left colon resection for benign (56%) or malignant disease (44%) were included. There were 74 sigmoid resections (61%), 21 left hemicolectomies (17%) and 26 low anterior resections (22%). A longer sagittal abdominal diameter (≥24.8 cm) was significantly associated with longer corrected operative time (248 vs. 228 min, p = 0.043). In multivariate analysis, greater sagittal abdominal diameter, sagittal internal diameter and abdominal perimeter were significantly associated with longer operative time. No significant association was found for the BMI neither in univariate nor in multivariate analysis. CONCLUSIONS: This study suggests that simple linear measures taken on a CT scan, such as sagittal abdominal diameter, sagittal internal diameter and abdominal perimeter, may predict longer operative time in laparoscopic left colonic resections more accurately than BMI.
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BACKGROUND AND PURPOSE: Statins display anti-inflammatory and anti-epileptogenic properties in animal models, and may reduce the epilepsy risk in elderly humans; however, a possible modulating role on outcome in patients with status epilepticus (SE) has not been assessed. METHODS: This cohort study was based on a prospective registry including all consecutive adults with incident SE treated in our center between April 2006 and September 2012. SE outcome was categorized at hospital discharge into 'return to baseline', 'new disability' and 'mortality'. The role of potential predictors, including statins treatment on admission, was evaluated using a multinomial logistic regression model. RESULTS: Amongst 427 patients identified, information on statins was available in 413 (97%). Mean age was 60.9 (±17.8) years; 201 (49%) were women; 211 (51%) had a potentially fatal SE etiology; and 191 (46%) experienced generalized-convulsive or non-convulsive SE in coma. Statins (simvastatin, atorvastatin or pravastatin) were prescribed prior to admission in 76 (18%) subjects, mostly elderly. Whilst 208 (50.4%) patients returned to baseline, 58 (14%) died. After adjustment for established SE outcome predictors (age, etiology, SE severity score), statins correlated significantly with lower mortality (relative risk ratio 0.38, P = 0.046). CONCLUSION: This study suggests for the first time that exposure to statins before an SE episode is related to its outcome, involving a possible anti-epileptogenic role. Other studies are needed to confirm this intriguing finding.
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In this study, the evaluation of the accuracy and performance of a light detection and ranging (LIDAR) sensor for vegetation using distance and reflection measurements aiming to detect and discriminate maize plants and weeds from soil surface was done. The study continues a previous work carried out in a maize field in Spain with a LIDAR sensor using exclusively one index, the height profile. The current system uses a combination of the two mentioned indexes. The experiment was carried out in a maize field at growth stage 12–14, at 16 different locations selected to represent the widest possible density of three weeds: Echinochloa crus-galli (L.) P.Beauv., Lamium purpureum L., Galium aparine L.and Veronica persica Poir.. A terrestrial LIDAR sensor was mounted on a tripod pointing to the inter-row area, with its horizontal axis and the field of view pointing vertically downwards to the ground, scanning a vertical plane with the potential presence of vegetation. Immediately after the LIDAR data acquisition (distances and reflection measurements), actual heights of plants were estimated using an appropriate methodology. For that purpose, digital images were taken of each sampled area. Data showed a high correlation between LIDAR measured height and actual plant heights (R2 = 0.75). Binary logistic regression between weed presence/absence and the sensor readings (LIDAR height and reflection values) was used to validate the accuracy of the sensor. This permitted the discrimination of vegetation from the ground with an accuracy of up to 95%. In addition, a Canonical Discrimination Analysis (CDA) was able to discriminate mostly between soil and vegetation and, to a far lesser extent, between crop and weeds. The studied methodology arises as a good system for weed detection, which in combination with other principles, such as vision-based technologies, could improve the efficiency and accuracy of herbicide spraying.
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BACKGROUND: Analyses of brain responses to external stimuli are typically based on the means computed across conditions. However in many cognitive and clinical applications, taking into account their variability across trials has turned out to be statistically more sensitive than comparing their means. NEW METHOD: In this study we present a novel implementation of a single-trial topographic analysis (STTA) for discriminating auditory evoked potentials at predefined time-windows. This analysis has been previously introduced for extracting spatio-temporal features at the level of the whole neural response. Adapting the STTA on specific time windows is an essential step for comparing its performance to other time-window based algorithms. RESULTS: We analyzed responses to standard vs. deviant sounds and showed that the new implementation of the STTA gives above-chance decoding results in all subjects (in comparison to 7 out of 11 with the original method). In comatose patients, the improvement of the decoding performance was even more pronounced than in healthy controls and doubled the number of significant results. COMPARISON WITH EXISTING METHOD(S): We compared the results obtained with the new STTA to those based on a logistic regression in healthy controls and patients. We showed that the first of these two comparisons provided a better performance of the logistic regression; however only the new STTA provided significant results in comatose patients at group level. CONCLUSIONS: Our results provide quantitative evidence that a systematic investigation of the accuracy of established methods in normal and clinical population is an essential step for optimizing decoding performance.