Trends in radiation dose for low grade gliomas across the United States

Journal of Neuro-Oncology - Adjuvant radiation is often used in patients with low grade gliomas with high-risk characteristics with a recommended dose of 45–54 Gy. We used the...     

Defining minimum volume thresholds to increase quality of care: a new patient-oriented approach using mixed integer programming

A positive relationship between treatment volume and outcome quality has been demonstrated in the literature and is thus evident for a variety of procedures. Consequently, policy makers have tried to translate this so-called volume–outcome relationship into minimum volume regulation (MVR) to increase the quality of care—yet with limited success. Until today, the effect of strict MVR application remains unclear as outcome quality gains cannot be estimated adequately and restrictions to application such as patient travel time and utilization of remaining hospital capacity are not considered sufficiently. Accordingly, when defining MVR, its effectiveness cannot be assessed. Thus, we developed a mixed integer programming model to define minimum volume thresholds balancing utility in terms of outcome quality gain and feasibility in terms of restricted patient travel time and utilization of hospital capacity. We applied our model to the German hospital sector and to four surgical procedures. Results showed that effective MVR needs a minimum volume threshold of 125 treatments for cholecystectomy, of 45 and 25 treatments for colon and rectum resection, respectively, of 32 treatments for radical prostatectomy and of 60 treatments for total knee arthroplasty. Depending on procedure type and incidence as well as the procedure’s complication rate, outcome quality gain ranged between 287 (radical prostatectomy) and 977 (colon resection) avoidable complications (11.7% and 11.9% of all complications). Ultimately, policy makers can use our model to leverage MVR’s intended benefit: concentrating treatment delivery to improve the quality of care.

     

Standardisierte Kontrastmittelsonographie (CEUS) in der klinischen Akut- und Notfallmedizin sowie Intensivmedizin (CEUS-Akut)

Die Anaesthesiologie -     

Selective Laser Melting of Al-Based Matrix Composites with Al2O3 Reinforcement: Features and Advantages

Aluminum matrix composites (AMC) are of great interest and importance as high-performance materials with enhanced mechanical properties. Al₂O₃ is a commonly used reinforcement in AMCs fabricated by means of various technological methods, including casting and sintering. Selective laser melting (SLM) is a suitable modern method of the fabrication of net-shape fully dense parts from AMC with alumina. The main results, achievements, and difficulties of SLM applied to AMCs with alumina are discussed in this review and compared with conventional methods. It was shown that the initial powder preparation, namely the particle size distribution, sphericity, and thorough mixing, affected the final microstructure and properties of SLMed materials drastically. The distribution of reinforcing particles tends to consolidate the near-melting pool-edges process because of pushing by the liquid–solid interface during the solidification process that is a common problem of various fabrication methods. The achievement of an homogeneous distribution was shown to be possible through both the thorough mixing of the initial powders and the precise optimization of SLM parameters. The strength of the AMCs fabricated by the SLM method was relatively low compared with materials produced by conventional methods, while for superior relative densities of more than 99%, hardness and tribological properties were obtained, making SLM a promising method for the Al-based matrix composites with Al₂O₃.     

Mechanisms of vascular dysfunction in the interleukin-10–deficient murine model of preeclampsia indicate nitric oxide dysregulation

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Risk as a pattern over time: Delineation of time-dependent risk factors in biological,psychological, and social variables in cancer patients

Background

Survival in cancer patients is associated with a multitude of biological, social, and psychological factors. Although it is well established that all these factors add to overall mortality, it is not well understood how the predictive power of these parameters changes in a comprehensive model and over time.

Methods

Patients who attended the authors’ outpatient clinic were invited to participate. The authors followed 5180 mixed cancer patients (51.1% female; mean age, 59.1 years [SD = 13.8]) for up to 16 years and analyzed biological (age, sex, cancer site, anemia), psychological (anxiety, depression), and social variables (marital status, education, employment status) potentially predicting overall survival in a Cox proportional hazards model.

Results

The median survival time for the entire sample was 4.3 years (95% confidence interval, 4.0–4.7). The overall survival probabilities for 1 and 10 years were 76.8% and 38.0%, respectively. Following an empirical approach, the authors split the time interval into five periods: acute, subacute, short-term, medium-term, and long-term. A complex pattern of variables predicted overall survival differently in the five periods. Biological parameters were important throughout most of the time, social parameters were either time-independent predictors or tended to be more important in the longer term. Of the psychological parameters, only depression was a significant predictor and lost its predictive power in the long-term.

Conclusions

The findings of this study allow the development of comprehensive patient-specific models of risk and resilience factors addressing biopsychosocial needs of cancer patients, paving the way for a personalized treatment plan that goes beyond biomedical cancer care.     

Chirurgische Therapie von Tumoren im Bereich des Ober- und Unterkiefers

best practice onkologie - Die heterogene Gruppe der Kopf-Hals-Tumoren zählt zu den häufigsten malignen Erkrankungen weltweit, wobei ein großer Teil von den Schleimhäuten der...