924 resultados para Bias-adjusted AR estimators


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We recently reported that nuclear grading in prostate cancer is subject to a strong confirmation bias induced by the tumor architecture. We now wondered whether a similar bias governs nuclear grading in breast carcinoma. An unannounced test was performed at a pathology conference. Pathologists were asked to grade nuclei in a PowerPoint presentation. Circular high power fields of 27 invasive ductal carcinomas were shown, superimposed over low power background images of either tubule-rich or tubule-poor carcinomas. We found (a) that diagnostic reproducibility of nuclear grades was poor to moderate (weighed kappa values between 0.07 and 0.54, 27 cases, 44 graders), but (b) that nuclear grades were not affected by the tumor architecture. We speculate that the categorized grading in breast cancer, separating tubule formation, nuclear pleomorphism, and mitotic figure counts in a combined three tier score, prevents the bias that architecture exerts on nuclear grades in less well-controlled situations.

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Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression

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INTRODUCTION. Neurally Adjusted Ventilatory Assist (NAVA) is an assisted ventilatorymode in which the ventilator is driven by the electrical activity of the diaphragm (Eadi).NAVAimproves patient-ventilator synchrony [1] but little is known about how to set the NAVA gaini.e., how to choose the ratio between Eadi and delivered pressure. The aim of the present studywas to assess the relationship between Eadi and tidal volume (Vt) at various NAVA gainsettings and to evaluate whether modifying the gain influenced this relationship in non-invasivelyventilated (NIV) patients.METHODS. Prospective interventional study comparing 3 values of NAVA gain during NIV(20 min each). NAVA100 was set by the clinician according to the manufacturer's recommendations.In NAVA50 and NAVA150 the gain was set as -50% and +50% of NAVA100gain respectively. Vt and maximal Eadi value (Eadi max) were recorded. The ratio Vt/Eadi wasthen assessed for each breath. 5-95% range (range 90) of Vt/Eadi was calculated for eachpatient at each NAVA gain setting. Vt/Eadi ratio has the advantage to give an objectiveassessment Vt/Eadi max relationship independently from the nature of this relationship. Asmaller Range90 indicates a better matching of Vt to Eadi max.RESULTS. 12 patients were included, 5 had obstructive pulmonary disease and 2 mixedobstructive and restrictive disease. For NAVA100, the median [IQR] Range 90 was 32[19-87]. For NAVA150 Range 90 was 37 [20-95] and for NAVA50 Range 90 was 33 [16-92].That means that globally NAVA100 allowed a better match between Eadi max and Vt thanNAVA50 and 150. However, by patient, NAVA100 had the lowest Range 90 value for only 4patients (33%), NAVA150 for 2 (17%) and NAVA50 for 6 (50%) patients, indicating thatNAVA100 was not the best NAVA gain for minimizing Range 90 in every patients.Comparing the lowest Range 90 value to the next lowest for each patient, showed that 3 patientshad differences of less than 10% (one each for NAVA50, NAVA100 and NAVA150). Theremainder had differences from 17 to 24%, indicating that most patients (9/12 or 75%) had aclear better match between Eadi and Vt for one specific NAVA gain.CONCLUSIONS. Different NAVA gains yielded markedly different ability to match Vt toEadi max. This approach could be a new way to determine optimalNAVAgain for each patientbut require further investigations.REFERENCE. Piquilloud L, et al. Intensive Care Med 2011;37:263-71.

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Background: Mortality from invasive meningococcal disease (IMD) has remained stable over the last thirty years and it is unclear whether pre-hospital antibiotherapy actually produces a decrease in this mortality. Our aim was to examine whether pre-hospital oral antibiotherapy reduces mortality from IMD, adjusting for indication bias. Methods: A retrospective analysis was made of clinical reports of all patients (n = 848) diagnosed with IMD from 1995 to 2000 in Andalusia and the Canary Islands, Spain, and of the relationship between the use of pre-hospital oral antibiotherapy and mortality. Indication bias was controlled for by the propensity score technique, and a multivariate analysis was performed to determine the probability of each patient receiving antibiotics, according to the symptoms identified before admission. Data on in-hospital death, use of antibiotics and demographic variables were collected. A logistic regression analysis was then carried out, using death as the dependent variable, and prehospital antibiotic use, age, time from onset of symptoms to parenteral antibiotics and the propensity score as independent variables. Results: Data were recorded on 848 patients, 49 (5.72%) of whom died. Of the total number of patients, 226 had received oral antibiotics before admission, mainly betalactams during the previous 48 hours. After adjusting the association between the use of antibiotics and death for age, time between onset of symptoms and in-hospital antibiotic treatment, pre-hospital oral antibiotherapy remained a significant protective factor (Odds Ratio for death 0.37, 95% confidence interval 0.15–0.93). Conclusion: Pre-hospital oral antibiotherapy appears to reduce IMD mortality.

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El objetivo principal de este proyecto es el de obtener unos conocimientos detallados del sistema operativo Android y el de ejemplificarlos mediante un aplicativo que haga uso de las características más peculiares de los dispositivos móviles en los que se ejecuta.

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PURPOSE OF REVIEW: Adherence to preventive measures and prescribed medications is the cornerstone of the successful management of hypertension. The role of adherence is particularly important when treatments are not providing the expected clinical results, for example, in patients with resistant hypertension. The goal of this article is to review the recent observations regarding drug adherence in resistant hypertension. RECENT FINDINGS: Today, the role of drug adherence as a potential cause of resistant hypertension is largely underestimated. Most studies suggest that a low adherence to the prescribed medications can affect up to 50% of patients with resistant hypertension.A good adherence to therapy is generally associated with an improved prognosis. Nonetheless, adherence should probably not be a target for treatment per se because data on adherence should always be interpreted in the view of clinical results. In our opinion, the availability of reliable data on drug adherence would be a major help for physicians to manage patients apparently resistant to therapy. SUMMARY: The actual development of new drugs for hypertension is slow. Thus, focusing on drug adherence to the drugs available is an important way to improve blood pressure control in the population. More emphasis should be put on measuring drug adherence in patients with resistant hypertension to avoid costly investigations and treatments.

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In the histomorphological grading of prostate carcinoma, pathologists have regularly assigned comparable scores for the architectural Gleason and the now-obsolete nuclear World Health Organization (WHO) grading systems. Although both systems demonstrate good correspondence between grade and survival, they are based on fundamentally different biological criteria. We tested the hypothesis that this apparent concurrence between the two grading systems originates from an interpretation bias in the minds of diagnostic pathologists, rather than reflecting a biological reality. Three pathologists graded 178 prostatectomy specimens, assigning Gleason and WHO scores on glass slides and on digital images of nuclei isolated out of their architectural context. The results were analysed with respect to interdependencies among the grading systems, to tumour recurrence (PSA relapse > 0.1 ng/ml at 48 months) and robust nuclear morphometry, as assessed by computer-assisted image analysis. WHO and Gleason grades were strongly correlated (r = 0.82) and demonstrated identical prognostic power. However, WHO grades correlated poorly with nuclear morphology (r = 0.19). Grading of nuclei isolated out of their architectural context significantly improved accuracy for nuclear morphology (r = 0.55), but the prognostic power was virtually lost. In conclusion, the architectural organization of a tumour, which the pathologist cannot avoid noticing during initial slide viewing at low magnification, unwittingly influences the subsequent nuclear grade assignment. In our study, the prognostic power of the WHO grading system was dependent on visual assessment of tumour growth pattern. We demonstrate for the first time the influence a cognitive bias can have in the generation of an error in diagnostic pathology and highlight a considerable problem in histopathological tumour grading.

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Background: Although combination antiretroviral therapy (cART) dramatically reduces rates of AIDS and death, a minority of patients experience clinical disease progression during treatment. <p>Objective: To investigate whether detection of CXCR4(X4)-specific strains or quantification of X4-specific HIV-1 load predict clinical outcome. Methods: From the Swiss HIV Cohort Study, 96 participants who initiated cART yet subsequently progressed to AIDS or death were compared with 84 contemporaneous, treated nonprogressors. A sensitive heteroduplex tracking assay was developed to quantify plasma X4 and CCR5 variants and resolve HIV-1 load into coreceptor-specific components. Measurements were analyzed as cofactors of progression in multivariable Cox models adjusted for concurrent CD4 cell count and total viral load, applying inverse probability weights to adjust for sampling bias. Results: Patients with X4 variants at baseline displayed reduced CD4 cell responses compared with those without X4 strains (40 versus 82 cells/mu l; P= 0.012). The adjusted multivariable hazard ratio (HR) for clinical progression was 4.8 [95% confidence interval (Cl) 2.3-10.0] for those demonstrating X4 strains at baseline. The X4-specific HIV-1 load was a similarly independent predictor, with HR values of 3.7(95%Cl, 1.2-11.3) and 5.9 (95% Cl, 2.2-15.0) for baseline loads of 2.2-4.3 and > 4.3 log(10)copies/ml, respectively, compared with < 2.2 log(10)copies/ml. Conclusions: HIV-1 coreceptor usage and X4-specific viral loads strongly predicted disease progression during cART, independent of and in addition to CD4 cell count or total viral load. Detection and quantification of X4 strains promise to be clinically useful biomarkers to guide patient management and study HIV-1 pathogenesis.

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SummaryDiscrete data arise in various research fields, typically when the observations are count data.I propose a robust and efficient parametric procedure for estimation of discrete distributions. The estimation is done in two phases. First, a very robust, but possibly inefficient, estimate of the model parameters is computed and used to indentify outliers. Then the outliers are either removed from the sample or given low weights, and a weighted maximum likelihood estimate (WML) is computed.The weights are determined via an adaptive process such that if the data follow the model, then asymptotically no observation is downweighted.I prove that the final estimator inherits the breakdown point of the initial one, and that its influence function at the model is the same as the influence function of the maximum likelihood estimator, which strongly suggests that it is asymptotically fully efficient.The initial estimator is a minimum disparity estimator (MDE). MDEs can be shown to have full asymptotic efficiency, and some MDEs have very high breakdown points and very low bias under contamination. Several initial estimators are considered, and the performances of the WMLs based on each of them are studied.It results that in a great variety of situations the WML substantially improves the initial estimator, both in terms of finite sample mean square error and in terms of bias under contamination. Besides, the performances of the WML are rather stable under a change of the MDE even if the MDEs have very different behaviors.Two examples of application of the WML to real data are considered. In both of them, the necessity for a robust estimator is clear: the maximum likelihood estimator is badly corrupted by the presence of a few outliers.This procedure is particularly natural in the discrete distribution setting, but could be extended to the continuous case, for which a possible procedure is sketched.RésuméLes données discrètes sont présentes dans différents domaines de recherche, en particulier lorsque les observations sont des comptages.Je propose une méthode paramétrique robuste et efficace pour l'estimation de distributions discrètes. L'estimation est faite en deux phases. Tout d'abord, un estimateur très robuste des paramètres du modèle est calculé, et utilisé pour la détection des données aberrantes (outliers). Cet estimateur n'est pas nécessairement efficace. Ensuite, soit les outliers sont retirés de l'échantillon, soit des faibles poids leur sont attribués, et un estimateur du maximum de vraisemblance pondéré (WML) est calculé.Les poids sont déterminés via un processus adaptif, tel qu'asymptotiquement, si les données suivent le modèle, aucune observation n'est dépondérée.Je prouve que le point de rupture de l'estimateur final est au moins aussi élevé que celui de l'estimateur initial, et que sa fonction d'influence au modèle est la même que celle du maximum de vraisemblance, ce qui suggère que cet estimateur est pleinement efficace asymptotiquement.L'estimateur initial est un estimateur de disparité minimale (MDE). Les MDE sont asymptotiquement pleinement efficaces, et certains d'entre eux ont un point de rupture très élevé et un très faible biais sous contamination. J'étudie les performances du WML basé sur différents MDEs.Le résultat est que dans une grande variété de situations le WML améliore largement les performances de l'estimateur initial, autant en terme du carré moyen de l'erreur que du biais sous contamination. De plus, les performances du WML restent assez stables lorsqu'on change l'estimateur initial, même si les différents MDEs ont des comportements très différents.Je considère deux exemples d'application du WML à des données réelles, où la nécessité d'un estimateur robuste est manifeste : l'estimateur du maximum de vraisemblance est fortement corrompu par la présence de quelques outliers.La méthode proposée est particulièrement naturelle dans le cadre des distributions discrètes, mais pourrait être étendue au cas continu.

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BACKGROUND: Highly recurrent major depressive disorder (MDD) has reportedly increased risk of shifting to bipolar disorder; high recurrence frequency has, therefore, featured as evidence of 'soft bipolarity'. We aimed to investigate the genetic underpinnings of total depressive episode count in recurrent MDD. METHODS: Our primary sample included 1966 MDD cases with negative family history of bipolar disorder from the RADIANT studies. Total episode count was adjusted for gender, age, MDD duration, study and center before being tested for association with genotype in two separate genome-wide analyses (GWAS), in the full set and in a subset of 1364 cases with positive family history of MDD (FH+). We also calculated polygenic scores from the Psychiatric Genomics Consortium MDD and bipolar disorder studies. RESULTS: Episodicity (especially intermediate episode counts) was an independent index of MDD familial aggregation, replicating previous reports. The GWAS produced no genome-wide significant findings. The strongest signals were detected in the full set at MAGI1 (p=5.1×10(-7)), previously associated with bipolar disorder, and in the FH+ subset at STIM1 (p=3.9×10(-6) after imputation), a calcium channel signaling gene. However, these findings failed to replicate in an independent Munich cohort. In the full set polygenic profile analyses, MDD polygenes predicted episodicity better than bipolar polygenes; however, in the FH+ subset, both polygenic scores performed similarly. LIMITATIONS: Episode count was self-reported and, therefore, subject to recall bias. CONCLUSIONS: Our findings lend preliminary support to the hypothesis that highly recurrent MDD with FH+ is part of a 'soft bipolar spectrum' but await replication in larger cohorts.

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INTRODUCTION. NAVA is a new spontaneous-assisted ventilatory mode based on thedetection of diaphragmatic electrical activity (Eadi) and its feedback to adjust ventilatorsettings. NAVA uses the Eadi, an expression of the respiratory center's activity, to initiatepressurization, set the level of pressure support and cycle the ventilator into exhalation.Therefore, NAVA should theoretically allow near-perfect synchronization between the patientand the ventilator. However there are few data documenting these effects in intensive carepatients.OBJECTIVES. To determine whether NAVA can improve patient-ventilator synchronycompared to standard pressure support (PS) in intubated intensive care patients.METHODS. Comparative study of patient-ventilator interaction during PS with cliniciandetermined ventilator settings and NAVA with NAVA gain (proportionality factor betweenEadi and the amount of delivered inspiratory pressure) set as to obtain the same peak airwaypressure as the total pressure obtained in PS. A 20 min continuous recording with eachventilatory mode was performed allowing determination of trigger delay (Td), patient neuralinspiratory time (Tin), duration of pressurization by the ventilator (Tiv), excess durationof pressurization (Ti excess = Tiv - Tin/Tin 9 100) and number of asynchrony events byminute: non-triggering breaths, auto-triggering, double triggering, premature and delayedcycling.Results are given in mean ± SD. p is considered significant if\0.05.RESULTS. Preliminary results (mean ± SD): five patients (age 75 ± 12 years, 1 M/4F,BMI 25.7 ± 4.1 kg m-2), two pts with COPD, 1 with restrictive disease, initial settings: PS14.6 ± 1.7 cm H2O, PEEP 6.4 ± 1.5 cm H2O, NAVA gain 2.8 ± 1.3PS NAVA % reduction NAVAversus PSTd (ms) 210.4 ± 63.0 51.8 ± 12.1* 74.5 ± 5.0Ti excess (%) 12.9 ± 19.6 2.2 ± 0.6 70.8 ± 37.8n asynchrony/minute 7.6 ± 6.4 4.1 ± 3.7* 47.5 ± 17.0Respiratory rate (min-1) 16.8 ± 2.6 20.4 ± 4.7 NA* p\0.05CONCLUSION. Compared to standard PS, NAVA improves patient ventilator interaction byreducing Td and the overall incidence of asynchrony events. There is also a strong trend inreducing delayed cycling. This ongoing trial should provide evidence that NAVA can indeedimprove patient-ventilator synchrony in intubated patients undergoing PS.REFERENCE(S). 1. Sinderby C, Navalesi P et al (1995) Neural control of mechanicalventilation in respiratory failure. Nat Med 5(12):1433-1436.2. Colombo D, Cammarota G et al (2008) Physiologic response to varying levels of pressuresupport and neurally adjusted ventilator assist in patients with acute respiratory failure.Intensive Care Med 34(11):2010-2018.