Although inequitable care due to racism and bias is well documented in health care, the impact on health care-associated infections is less understood.
To determine whether disparities in first ...central catheter-associated bloodstream infection (CLABSI) rates existed for pediatric patients of minoritized racial, ethnic, and language groups and to evaluate the outcomes associated with quality improvement initiatives for addressing these disparities.
This cohort study retrospectively examined outcomes of 8269 hospitalized patients with central catheters from October 1, 2012, to September 30, 2019, at a freestanding quaternary care children's hospital. Subsequent quality improvement interventions and follow-up were studied, excluding catheter days occurring after the outcome and episodes with catheters of indeterminate age through September 2022.
Patient self-reported (or parent/guardian-reported) race, ethnicity, and language for care as collected for hospital demographic purposes.
Central catheter-associated bloodstream infection events identified by infection prevention surveillance according to National Healthcare Safety Network criteria were reported as events per 1000 central catheter days. Cox proportional hazards regression was used to analyze patient and central catheter characteristics, and interrupted time series was used to analyze quality improvement outcomes.
Unadjusted infection rates were higher for Black patients (2.8 per 1000 central catheter days) and patients who spoke a language other than English (LOE; 2.1 per 1000 central catheter days) compared with the overall population (1.5 per 1000 central catheter days). Proportional hazard regression included 225 674 catheter days with 316 infections and represented 8269 patients. A total of 282 patients (3.4%) experienced a CLABSI (mean IQR age, 1.34 0.07-8.83 years; female, 122 43.3%; male, 160 56.7%; English-speaking, 236 83.7%; LOE, 46 16.3%; American Indian or Alaska Native, 3 1.1%; Asian, 14 5.0%; Black, 26 9.2%; Hispanic, 61 21.6%; Native Hawaiian or Other Pacific Islander, 4 1.4%; White, 139 49.3%; ≥2 races, 14 5.0%; unknown race and ethnicity or refused to answer, 15 5.3%). In the adjusted model, a higher hazard ratio (HR) was observed for Black patients (adjusted HR, 1.8; 95% CI, 1.2-2.6; P = .002) and patients who spoke an LOE (adjusted HR, 1.6; 95% CI, 1.1-2.3; P = .01). Following quality improvement interventions, infection rates in both subgroups showed statistically significant level changes (Black patients: -1.77; 95% CI, -3.39 to -0.15; patients speaking an LOE: -1.25; 95% CI, -2.23 to -0.27).
The study's findings show disparities in CLABSI rates for Black patients and patients who speak an LOE that persisted after adjusting for known risk factors, suggesting that systemic racism and bias may play a role in inequitable hospital care for hospital-acquired infections. Stratifying outcomes to assess for disparities prior to quality improvement efforts may inform targeted interventions to improve equity.
Due to their flexibility Gaussian processes are a well-known Bayesian framework for nonparametric function estimation. Integrating inequality constraints, such as monotonicity, convexity, and ...boundedness, into Gaussian process models significantly improves prediction accuracy and yields more realistic credible intervals in various real-world data applications. The Gaussian process approximation, originally proposed in 22 is considered. It satisfies interpolation conditions and handles a wide range of inequality constraints everywhere. Our contribution in this paper is threefold. First, we extend this approach to handle noisy observations and multiple, more general convex and non-convex constraints. Second, we propose new basis functions in order to extend the smoothness of sample paths to differentiability of class C^p , for any p ≥ 1. Third, we examine its behavior in specific scenarios such as monotonicity with flat regions and boundedness near lower and/or upper bounds. In that case, we show that, unlike the Maximum a posteriori (MAP) estimate, the mean a posteriori (mAP) estimate fails to capture flat regions. To address this issue, we propose incorporating multiple constraints, such as monotonicity with bounded slope constraints. According to the theoretical convergence and based on a variety of numerical experiments, the MAP estimate behaves well and outperforms the mAP estimate in terms of prediction accuracy. The performance of the proposed approach is confirmed through real-world data studies.
Statistical Analysis of Management Data provides a comprehensive approach to multivariate statistical analyses that are important for researchers in all fields of management, including finance, ...production, accounting, marketing, strategy, technology, and human resources. This book is especially designed to provide doctoral students with a theoretical knowledge of the concepts underlying the most important multivariate techniques and an overview of actual applications. It offers a clear, succinct exposition of each technique with emphasis on when each technique is appropriate and how to use it. This second edition, fully revised, updated, and expanded, reflects the most current evolution in the methods for data analysis in management and the social sciences. In particular, it places a greater emphasis on measurement models, and includes new chapters and sections on: confirmatory factor analysis canonical correlation analysis cluster analysis analysis of covariance structure multi-group confirmatory factor analysis and analysis of covariance structures. Featuring numerous examples, the book may serve as an advanced text or as a resource for applied researchers in industry who want to understand the foundations of the methods and to learn how they can be applied using widely available statistical software. TOC:1: Introduction.- 2: Multivariate Normal Distribution.- 3: Measurement Theory: Reliability and Factor Analysis.- 4: Multiple Regression with a Single Dependent Variable.- 5: System of Equations.- 6: Categorial Dependent Variables.- 7: Rank Ordered Data.- 8: Error in Variables - Analysis of Covariance Structure.- 9: Analyses of Similarity and Preference Data.- Appendices: A: Rules in Matrix Algebra.- B: Statistical Tables.- C: Description of Data Sets.
Introduction: Hairy-cell leukemia (HCL) is a chronic B-cell lymphoproliferative disorder with a favorable outcome thanks to treatment with purine analogues (PNA) like cladribine and pentostatin. ...Here, we updated the French national retrospective cohort of HCL after 10 years of follow-up, in order to evaluate the risk of second cancers in these patients.
Methods: Data were collected up to June 2018 through a questionnaire sent to the members of the Société Française d'Hématologie, and centralized in the cohort database. We described the second malignancies observed during the follow-up, distinguishing second ‘solid’ cancers from second hematological malignancies. Then, using a Fine and Gray model, we performed a multivariate analysis in order to identify second cancer risk factors. Finally, to evaluate the excess of cancers in our cohort in comparison with the French general population, we calculated the standardized incidence ratio (SIR).
Results: 279 patients (pts) from 19 centers were included in our retrospective cohort. The median age was 59 years old (range 29-88). 21% had an infectious disease at diagnosis, 23% had a familial history of cancer and 11% a personal history of cancer before HCL diagnosis. The median number of lines of treatments was 1 (0-7). PNA (cladribine or pentostatin) were the first therapeutic choice in frontline (75% of pts) and at relapse (69%). With a median follow-up of 127 months (2-413), the median overall survival for the overall study population was 328 months (95% CI 299-357) and the median relapse-free survival (RFS) was 136 months (95% CI 109-163). Pts treated with cladribine or pentostatin in first line had a statistically significant better RFS than pts treated with ‘other’ treatments (log rank test, p < 0.001). The 10-year cumulative incidence of relapse was 39% (95% CI 33-46). Pts who received treatments other than PNA in first line had a higher risk of relapse (Gray's test, p < 0.001). For pts receiving PNA in first and second lines, there was no difference in outcomes between those who switched PNA and those who did not. In this cohort, we observed 68 second malignancies during the follow-up: 49 solid cancers (most prevalent: prostate and non-melanoma skin cancers) and 19 hematological malignancies (most prevalent: monoclonal gammopathy of undetermined significance (MGUS) and myelodysplastic syndromes (MDS)). The median onset of second cancer, second solid cancer and second hematological malignancy from HCL diagnosis was 81 months, 99 months and 78 months, respectively. The median age at diagnosis of cancer, solid cancer and hematological malignancy was 70, 69 and 77 years old, respectively. Considering death as a competing risk, the 10-year cumulative incidence of cancer, solid cancer and hematological malignancy was 15% (95% CI 11-19), 11% (95% CI 7.2-15), and 5.0% (95% CI 2.8-8.2), respectively. In multivariate analyses, IFN treatment was associated with a decreased risk for all cancers (Fine and Gray regression model, subdistribution Hazard Ratio (sdHR) 0.53 (95% CI 0.29-0.97); p = 0.038), a familial history of cancer was a risk factor for solid cancers (sdHR 2.12 (95% CI 1.15-3.91); p = 0.017), a personal history of cancer was a risk factor for hematological malignancies (sdHR 3.47 (95% CI 1.14-10.55); p = 0.028). Even after excluding non-melanoma skin cancers and MGUS, there was an excess of cancers (SIR = 2.22), solid cancers (SIR = 1.81) and hematological malignancies (SIR = 6.67).
Conclusions: In this updated real-world retrospective cohort with a long follow-up and most pts treated with PNA, we highlighted the importance and the excess of second cancers in HCL patients, in particular hematological malignancies.
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Paillassa:Janssen: Other: Bibliography board with young hematologists. Thieblemont:Roche: Honoraria, Research Funding; Gilead: Honoraria; Novartis: Honoraria; Kyte: Honoraria; Janssen: Honoraria; Celgene: Honoraria; Cellectis: Membership on an entity's Board of Directors or advisory committees. Hermine:AB Science: Membership on an entity's Board of Directors or advisory committees. Feugier:janssen: Honoraria, Research Funding, Speakers Bureau; gilead: Honoraria, Research Funding, Speakers Bureau; roche: Honoraria, Research Funding, Speakers Bureau; abbvie: Honoraria, Research Funding, Speakers Bureau. Troussard:Innate Pharma: Consultancy, Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees; Roche: Other: Research Support; Sysmex: Other: Research Support.
The health system of Mexico Gómez Dantés, Octavio; Sesma, Sergio; Becerril, Victor M ...
Salud pública de México,
2011, Letnik:
53 Suppl 2
Journal Article
Recenzirano
This paper describes the Mexican health system. In part one, the health conditions of the Mexican population are discussed, with emphasis in those emerging diseases that are now the main causes of ...death, both in men and women: diabetes, ischaemic heart disease, cerebrovascular diseases and cancer. Part two is devoted to the description of the basic structure of the system: its main institutions, the population coverage, the health benefits of those affiliated to the different heath institutions, its financial sources, the levels of financial protection in health, the availability of physical, material and human resources for health, and the stewardship functions displayed by the Ministry of Health and other actors. This part also discusses the role of citizens in the monitorization and evaluation of the health system, as well as the levels of satisfaction with the rendered health services. In part three the most recent innovations and its impact on the performance of the health system are discussed. Salient among them are the System of Social Protection in Health and the Popular Health Insurance. The paper concludes with a brief analysis of the short- and middle-term challenges faced by the Mexican health system.
This paper proposes a smooth copula-based Generalized Extreme Value (GEV) model to map and predict extreme rainfall in central eastern Canada. Furthermore, we provide a comparison with different ...classical interpolation-based approaches. The considered data represents a station network particularly spatially sparse. Furthermore, one observes several missing values and non-concomitant record periods at different stations. We compare the classical GEV parameter interpolation approaches with our smooth GEV modeling approach, in which the parameters are modeled as smooth functions in space through the use of spatial covariates and by using copula-clustering techniques recently introduced in the literature.
To improve the performance of individual DNA sequencing results, researchers often use replicates from the same individual and various statistical clustering models to reconstruct a high-performance ...callset. Here, three technical replicates of genome NA12878 were considered and five model types were compared (consensus, latent class, Gaussian mixture, Kamila–adapted k-means, and random forest) regarding four performance indicators: sensitivity, precision, accuracy, and F1-score. In comparison with no use of a combination model, i) the consensus model improved precision by 0.1%; ii) the latent class model brought 1% precision improvement (97%–98%) without compromising sensitivity (= 98.9%); iii) the Gaussian mixture model and random forest provided callsets with higher precisions (both >99%) but lower sensitivities; iv) Kamila increased precision (>99%) and kept a high sensitivity (98.8%); it showed the best overall performance. According to precision and F1-score indicators, the compared non-supervised clustering models that combine multiple callsets are able to improve sequencing performance vs. previously used supervised models. Among the models compared, the Gaussian mixture model and Kamila offered non-negligible precision and F1-score improvements. These models may be thus recommended for callset reconstruction (from either biological or technical replicates) for diagnostic or precision medicine purposes.
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