Deformation processing of titanium and its alloys

Deformation processing of titanium alloy

Treatment patterns and blood counts in patients with polycythemia vera treated with hydroxyurea in the United States: An analysis from the REVEAL study

BACKGROUND: Polycythemia vera (PV) is associated with increased blood cell counts, risk of thrombosis, and symptoms including fatigue and pruritus. National guidelines support the use of hydroxyurea (HU) in high-risk patients or those with some other clinical indication for cytoreduction. PATIENTS AND METHODS: REVEAL is a prospective, observational study designed to collect data pertaining to demographics, disease burden, clinical management, patient-reported outcomes, and health care resource utilization of patients with PV in the United States. In this analysis, HU treatment patterns and outcomes were assessed from 6 months prior to enrollment to the time of discontinuation, death, or data cutoff. RESULTS: Of the 1381 patients who received HU for ≥ 3 months, the median HU exposure was 23.6 months (range, 3.1-38.5 months). The most common maximum daily HU doses were 1000 mg (30.6%) and 500 mg (30.1%); only 6.4% received ≥ 2 g/d HU. Approximately one-third (32.3%) of patients had dose adjustments, 23.8% had dose interruptions, and 257 (18.6%) discontinued HU. The most common reasons for HU discontinuations and interruptions were adverse events/intolerance (37.1% and 54.5%, respectively) and lack of efficacy (35.5% and 22.1%, respectively). Of those who received HU for ≥ 3 months, 57.1% had hematocrit values \u3e 45% on ≥ 1 occasion, 33.1% continued to receive phlebotomies, and 27.4% had uncontrolled myeloproliferation. CONCLUSION: The results of this analysis emphasize the need for active management of patients with PV with appropriate HU dose titration to maintain blood count control while monitoring for signs and symptoms of HU intolerance

Return to work after COVID-19 infection – A Danish nationwide registry study

OBJECTIVES: This study aimed to explore return to work after COVID-19 and how disease severity affects this. STUDY DESIGN: This is a Nationwide Danish registry–based cohort study using a retrospective follow-up design. METHODS: Patients with a first-time positive SARS-CoV-2 polymerase chain reaction test between 1 January 2020 and 30 May 2020, including 18–64 years old, 30-day survivors, and available to the workforce at the time of the first positive test were included. Admission types (i.e. no admission, admission to non–intensive care unit [ICU] department and admission to ICU) and return to work was investigated using Cox regression standardised to the age, sex, comorbidity and education-level distribution of all included subjects with estimates at 3 months from positive test displayed. RESULTS: Among the 7466 patients included in the study, 81.9% (6119/7466) and 98.4% (7344/7466) returned to work within 4 weeks and 6 months, respectively, with 1.5% (109/7466) not returning. Of the patients admitted, 72.1% (627/870) and 92.6% (805/870) returned 1 month and 6 months after admission to the hospital, with 6.6% (58/870) not returning within 6 months. Of patients admitted to the ICU, 36% (9/25) did not return within 6 months. Patients with an admission had a lower chance of return to work 3 months from positive test (relative risk [RR] 0.95, 95% confidence interval [CI] 0.94–0.96), with the lowest chance in patients admitted to an ICU department (RR 0.54, 95% CI 0.35–0.72). Female sex, older age, and comorbidity were associated with a lower chance of returning to work. CONCLUSION: Hospitalised patients with COVID-19 infection have a lower chance of returning to work with potential implications for postinfection follow-up and rehabilitation

Seasonality of ventricular fibrillation at first myocardial infarction and association with viral exposure

AIMS:To investigate seasonality and association of increased enterovirus and influenza activity in the community with ventricular fibrillation (VF) risk during first ST-elevation myocardial infarction (STEMI). METHODS:This study comprised all consecutive patients with first STEMI (n = 4,659; aged 18-80 years) admitted to the invasive catheterization laboratory between 2010-2016, at Copenhagen University Hospital, Rigshospitalet, covering eastern Denmark (2.6 million inhabitants, 45% of the Danish population). Hospital admission, prescription, and vital status data were assessed using Danish nationwide registries. We utilized monthly/weekly surveillance data for enterovirus and influenza from the Danish National Microbiology Database (2010-2016) that receives copies of laboratory tests from all Danish departments of clinical microbiology. RESULTS:Of the 4,659 consecutively enrolled STEMI patients, 581 (12%) had VF before primary percutaneous coronary intervention. In a subset (n = 807), we found that VF patients experienced more generalized fatigue and flu-like symptoms within 7 days before STEMI compared with the patients without VF (OR 3.39, 95% CI 1.76-6.54). During the study period, 2,704 individuals were diagnosed with enterovirus and 19,742 with influenza. No significant association between enterovirus and VF (OR 1.00, 95% CI 0.99-1.02), influenza and VF (OR 1.00, 95% CI 1.00-1.00), or week number and VF (p-value 0.94 for enterovirus and 0.89 for influenza) was found. CONCLUSION:We found no clear seasonality of VF during first STEMI. Even though VF patients had experienced more generalized fatigue and flu-like symptoms within 7 days before STEMI compared with patients without VF, no relationship was found between enterovirus or influenza exposure and occurrence of VF

Prognostic Value of Three Different Methods of MGMT Promoter Methylation Analysis in a Prospective Trial on Newly Diagnosed Glioblastoma

Hypermethylation in the promoter region of the MGMT gene encoding the DNA repair protein O6-methylguanine-DNA methyltransferase is among the most important prognostic factors for patients with glioblastoma and predicts response to treatment with alkylating agents like temozolomide. Hence, the MGMT status is widely determined in most clinical trials and frequently requested in routine diagnostics of glioblastoma. Since various different techniques are available for MGMT promoter methylation analysis, a generally accepted consensus as to the most suitable diagnostic method remains an unmet need. Here, we assessed methylation-specific polymerase chain reaction (MSP) as a qualitative and semi-quantitative method, pyrosequencing (PSQ) as a quantitative method, and methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) as a semi-quantitative method in a series of 35 formalin-fixed, paraffin-embedded glioblastoma tissues derived from patients treated in a prospective clinical phase II trial that tested up-front chemoradiotherapy with dose-intensified temozolomide (UKT-05). Our goal was to determine which of these three diagnostic methods provides the most accurate prediction of progression-free survival (PFS). The MGMT promoter methylation status was assessable by each method in almost all cases (n = 33/35 for MSP; n = 35/35 for PSQ; n = 34/35 for MS-MLPA). We were able to calculate significant cut-points for the continuous methylation signals at each CpG site analysed by PSQ (range, 11.5 to 44.9%) and at one CpG site assessed by MS-MLPA (3.6%) indicating that a dichotomisation of continuous methylation data as a prerequisite for comparative survival analyses is feasible. Our results show that, unlike MS-MLPA, MSP and PSQ provide a significant improvement of predicting PFS compared with established clinical prognostic factors alone (likelihood ratio tests: p<0.001). Conclusively, taking into consideration prognostic value, cost effectiveness and ease of use, we recommend pyrosequencing for analyses of MGMT promoter methylation in high-throughput settings and MSP for clinical routine diagnostics with low sample numbers

Regularized Regression Incorporating Network Information: Simultaneous Estimation of Covariate Coefficients and Connection Signs

We develop an algorithm that incorporates network information into regression settings. It simultaneously estimates the covariate coefficients and the signs of the network connections (i.e. whether the connections are of an activating or of a repressing type). For the coefficient estimation steps an additional penalty is set on top of the lasso penalty, similarly to Li and Li (2008). We develop a fast implementation for the new method based on coordinate descent. Furthermore, we show how the new methods can be applied to time-to-event data. The new method yields good results in simulation studies concerning sensitivity and specificity of non-zero covariate coefficients, estimation of network connection signs, and prediction performance. We also apply the new method to two microarray time-to-event data sets from patients with ovarian cancer and diffuse large B-cell lymphoma. The new method performs very well in both cases. The main application of this new method is of biomedical nature, but it may also be useful in other fields where network data is available